- The impact of reservoir conditions on the residual trapping of carbon
dioxide in Berea sandstone
- Authors: Ben Niu; Ali Al‐Menhali, Samuel C. Krevor
Pages: n/a - n/a
Abstract: The storage of carbon dioxide in deep brine‐filled permeable rocks is an important tool for CO2 emissions mitigation on industrial scales. Residual trapping of CO2 through capillary forces within the pore space of the reservoir is one of the most significant mechanisms for storage security and is also a factor determining the ultimate extent of CO2 migration within the reservoir. In this study we have evaluated the impact of reservoir conditions of pressure, temperature and brine salinity on the residual trapping characteristic curve of a fired Berea sandstone rock. The observations demonstrate that the initial‐residual characteristic trapping curve is invariant across a wide range of pressure, temperature and brine salinities and is also the same for CO2‐brine systems as a N2‐water system. The observations were made using a reservoir condition core‐flooding laboratory that included high precision pumps, temperature control, the ability to recirculate fluids for weeks at a time and an x‐ray CT scanner. Experimental conditions covered pressures of 5‐20MPa, temperatures 25‐50∘C and 0‐5mol/kg NaCl brine salinity. A novel coreflooding approach was developed, making use of the capillary end effect to create a large range in initial CO2 saturation (0.15‐0.6) in a single coreflood. Upon subsequent flooding with CO2‐equilibriated brine, the observation of residual saturation corresponded to the wide range of initial saturations before flooding resulting in a rapid construction of the initial‐residual curve. For each condition we report the initial‐residual curve and the resulting parameterisation of the Land hysteresis models. This article is protected by copyright. All rights reserved.
- Enhanced nonlinearity interval mapping scheme for high performance
simulation‐optimization of watershed‐scale BMP placement
- Authors: Rui Zou; John Riverson, Yong Liu, Ryan Murphy, Youn Sim
Pages: n/a - n/a
Abstract: Integrated continuous simulation‐optimization models can be effective predictors of a process‐based responses for cost‐benefit optimization of best management practices (BMPs) selection and placement. However, practical application of simulation‐optimization model is computationally prohibitive for large‐scale systems. This study proposes an enhanced Nonlinearity Interval Mapping Scheme (NIMS) to solve large‐scale watershed simulation‐optimization problems several orders of magnitude faster than other commonly‐used algorithms. An efficient interval response coefficient (IRC) derivation method was incorporated into the NIMS framework to overcome a computational bottleneck. The proposed algorithm was evaluated using a case study watershed in the Los Angeles County Flood Control District. Using a continuous simulation watershed/stream‐transport model, Loading Simulation Program in C++ (LSPC), three nested in‐stream compliance points (CP)—each with multiple Total Maximum Daily Loads (TMDL) targets—were selected to derive optimal treatment levels for each of the 28 subwatersheds, so that the TMDL targets at all the CP were met with the lowest possible BMP implementation cost. Genetic Algorithm (GA) and NIMS were both applied and compared. The results showed that the NIMS took 11 iterations (about 11 minutes) to complete with the resulting optimal solution having a total cost of $67.2 million, while each of the multiple GA executions took 21 to 38 days to reach near optimal solutions. The best solution obtained among all the GA executions compared had a minimized cost of $67.7 million—marginally higher, but approximately equal to that of the NIMS solution. The results highlight the utility for decision making in large‐scale watershed simulation‐optimization formulations. This article is protected by copyright. All rights reserved.
- The value of multiple dataset calibration versus model complexity for
improving the performance of hydrological models in mountain catchments
- Authors: David Finger; Marc Vis, Matthias Huss, Jan Seibert
Pages: n/a - n/a
Abstract: The assessment of snow, glacier and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multi‐dataset calibration approach to estimate runoff composition using hydrological models with three levels of complexity. For this purpose the code of the conceptual runoff model HBV‐light was enhanced to allow calibration and validation of simulations against glacier mass balances, satellite‐derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments in Switzerland, ranging from 39km2 to 103km2. The results indicate that all three observational datasets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results we recommend using all three observational datasets in order to constrain model parameters and compute snow, glacier and rain contributions. Finally, based on the comparison of model performance of different complexities we postulate that the availability and use of different datasets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of runoff composition. This article is protected by copyright. All rights reserved.
- Developing effective messages about potable recycled water: The importance
of message structure and content
- Authors: J. Price; K.S. Fielding, J. Gardner, Z. Leviston, M. Green
Pages: n/a - n/a
Abstract: Community opposition is a barrier to potable recycled water schemes. Effective communication strategies about such schemes are needed. Drawing on social psychological literature, two experimental studies are presented which explore messages that improve public perceptions of potable recycled water. The Elaboration Likelihood Model of information processing and attitude change is tested and supported. Study 1 (N = 415) premeasured support for recycled water, and trust in government information at Time 1. Messages varied in complexity and sidedness were presented at Time 2 (three weeks later), and support and trust were remeasured. Support increased after receiving information, provided that participants received complex rather than simple information. Trust in government was also higher after receiving information. There was tentative evidence of this in response to two‐sided messages rather than one‐sided messages. Initial attitudes to recycled water moderated responses to information. Those initially neutral or ambivalent responded differently to simple and one‐sided messages, compared to participants with positive or negative attitudes. Study 2 (N = 957) tested the effectiveness of information about the low relative risks, and/or benefits of potable recycled water, compared to control groups. Messages about the low risks resulted in higher support when the issue of recycled water was relevant. Messages about benefits resulted in higher perceived issue relevance, but did not translate into greater support. The results highlight the importance of understanding people's motivation to process information, and need to tailor communication to match attitudes and stage of recycled water schemes’ development. This article is protected by copyright. All rights reserved.
- Comment on “Hydraulic fracturing in faulted sedimentary basins:
Numerical simulation of potential long‐term contamination of shallow
- Authors: Samuel A. Flewelling; Manu Sharma
Pages: n/a - n/a
- Reply to comment by Flewelling and Sharma on “Hydraulic fracturing
in faulted sedimentary basins: Numerical simulation of potential
contamination of shallow aquifers over long time scales”
- Authors: René Lefebvre; Tom Gleeson, Jeffrey M. McKenzie, Claire Gassiat
Pages: n/a - n/a
- Multiscale solute transport upscaling for a three‐dimensional
hierarchical porous medium
- Authors: Mingkan Zhang; Ye Zhang
Pages: n/a - n/a
Abstract: A laboratory‐generated hierarchical, fully heterogeneous aquifer model (FHM) provides a reference for developing and testing an upscaling approach that integrates large‐scale connectivity mapping with flow and transport modeling. Based on the FHM, three hydrostratigraphic models (HSMs) that capture lithological (static) connectivity at different resolutions are created, each corresponding to a sedimentary hierarchy. Under increasing system lnK variances (0.1, 1.0, 4.5), flow upscaling is first conducted to calculate equivalent hydraulic conductivity for individual connectivity (or unit) of the HSMs. Given the computed flow fields, an instantaneous, conservative tracer test is simulated by all models. For the HSMs, two upscaling formulations are tested based on the advection‐dispersion equation (ADE), implementing space‐ versus time‐dependent macrodispersivity. Comparing flow and transport predictions of the HSMs against those of the reference model, HSMs capturing connectivity at increasing resolutions are more accurate, although upscaling errors increase with system variance. Results suggest: (1) by explicitly modeling connectivity, an enhanced degree of freedom in representing dispersion can improve the ADE‐based upscaled models by capturing non‐Fickian transport of the FHM; (2) when connectivity is sufficiently resolved, the type of data conditioning used to model transport becomes less critical. Data conditioning, however, is influenced by the prediction goal; (3) when aquifer is weakly‐to‐moderately heterogeneous, the upscaled models adequately capture the transport simulation of the FHM, despite the existence of hierarchical heterogeneity at smaller scales. When aquifer is strongly heterogeneous, the upscaled models become less accurate because lithological connectivity cannot adequately capture preferential flows; (4) three‐dimensional transport connectivities of the hierarchical aquifer differ quantitatively from those analyzed for two‐dimensional systems. This article is protected by copyright. All rights reserved.
- Impact of interfacial tension on residual CO2 clusters in porous sandstone
- Authors: Fei Jiang; Takeshi Tsuji
Pages: n/a - n/a
Abstract: We develop a numerical simulation that uses the lattice Boltzmann method to directly calculate the characteristics of residual nonwetting‐phase clusters to quantify capillary trapping mechanisms in real sandstone. For this purpose, a digital‐rock‐pore model reconstructed from micro‐CT‐scanned images of Berea sandstone is filtered and segmented into a binary file. The residual‐cluster distribution is generated following simulation of the drainage and imbibition processes. The characteristics of the residual cluster in terms of size distribution, major length, interfacial area, and sphericity are investigated under conditions of different interfacial tension (IFT). Our results indicate that high interfacial tension increases the residual saturation and leads to a large size distribution of residual clusters. However, low interfacial tension results in a larger interfacial area, which is beneficial for dissolution and reaction processes during geological carbon storage. Analysis of the force balance acting on the residual clusters demonstrates that trapping stability is higher in high interfacial tension case, and the interfacial tension should be a controlling factor for the trapping stability in addition to the pore geometry and connectivity. The proposed numerical method can handle the complex displacement of multicomponent systems in porous media. By using this method, we can obtain residual‐cluster distributions under different conditions for optimizing the storage capacity of carbon‐storage projects. This article is protected by copyright. All rights reserved.
- Transient response of Salix cuttings to changing water level regimes
- Authors: L. Gorla; C. Signarbieux, P. Turberg, A. Buttler, P. Perona
Pages: n/a - n/a
Abstract: Sustainable water management requires an understanding of the effects of flow regulation on riparian eco‐morphological processes. We investigated the transient response of Salix viminalis by examining the effect of water level regimes on its above and below‐ground biomass. Four sets of Salix cuttings, three juveniles (in the first growing season) and one mature (one year old), were planted and initially grown under the same water‐level regime for one month. We imposed three different water level regime treatments representing natural variability, a seasonal trend with no peaks, and minimal flow (characteristic of hydropower) consisting of a constant water level and natural flood peaks. We measured sap flux, stem water potential, photosynthesis, growth parameters, and final root architecture. The mature cuttings were not affected by water table dynamics, but the juveniles displayed causal relationships between the changing water regime, plant growth, and root distribution during a two‐month transient period. For example, a 50% drop in mean sap flux corresponded with a −1.5 Mpa decrease in leaf water potential during the first day after the water regime was changed. In agreement with published field observations, the cuttings concentrated their roots close to the mean water table of the corresponding treatment, allowing survival under altered conditions and resilience to successive stress events. Juvenile development was strongly impacted by the minimum flow regime, leading to more than 60% reduction of both above‐ and below‐ground biomass, with respect to the other treatments. Hence, we suggest avoiding minimum flow regimes where Salix restoration is prioritized. This article is protected by copyright. All rights reserved.
- Towards Understanding Non‐stationarity in Climate and Hydrology
through Tree‐ring proxy records
- Authors: Saman Razavi; Amin Elshorbagy, Howard Wheater, David Sauchyn
Pages: n/a - n/a
Abstract: Natural proxy records of hydroclimatic behaviour, such as tree‐ring chronologies, are a rich source of information of past climate‐driven non‐stationarities in hydrologic variables. In this study, we investigate tree‐ring chronologies that demonstrate significant correlations with streamflows, with the objective of identifying the spatiotemporal patterns and extents of non‐stationarities in climate and hydrology, which are essentially representations of past “climate changes”. First‐ and second‐order non‐stationarities are of particular interest in this study. As a prerequisite, we develop a methodology to assess the consistency and credibility of a regional network of tree‐ring chronologies as proxies for hydrologic regime. This methodology involves a cluster analysis of available tree‐ring data to understand and evaluate their dependence structure, and a regional temporal‐consistency plot to assess the consistency of different chronologies over time. The major headwater tributaries of the Saskatchewan River basin (SaskRB), the main source of surface water in the Canadian Prairie Provinces, are used as the case study. Results indicate that stationarity might never have existed in the hydrology of the region, as the statistical properties of annual paleo‐hydrologic proxy records across the basin, i.e., the mean and autocorrelation structure, have consistently undergone significant changes (non‐stationarities) at different points in the history of the region. The spatial pattern of the changes in the mean statistic has been variable with time, indicating a time‐varying cross‐correlation structure across the tributaries of the SaskRB. Conversely, the changes in the autocorrelation structure across the basin have been in harmony over time. The results demonstrate that the 89‐year period of observational record in this region is a poor representation of the long‐term properties of the hydrologic regime, and shorter periods, e.g., 30 year periods, are by no means representative. This paper highlights the need to broaden the understanding of hydrologic characteristics in any basin beyond the limited observational records, as an improved understanding is essential for more reliable assessment and management of available water resources. This article is protected by copyright. All rights reserved.
- Toward the camera rain gauge
- Authors: P. Allamano; A. Croci, F. Laio
Pages: n/a - n/a
Abstract: We propose a novel technique based on the quantitative detection of rain intensity from images, i.e. from pictures taken in rainy conditions. The method is fully analytical and based on the fundamentals of camera optics. A rigorous statistical framing of the technique allows one to obtain the rain rate estimates in terms of expected values and associated uncertainty. We show that the method can be profitably applied to real rain events and we obtain promising results with errors of the order of ±25% . A precise quantification of the method's accuracy will require a more systematic and long‐term comparison with benchmark measures. The significant step forward with respect to standard rain gauges resides in the possibility to retrieve measures at very high temporal resolution (e.g., 30 measures per minute) at a very low cost. Perspective applications include the possibility to dramatically increase the spatial density of rain observations by exporting the technique to crowdsourced pictures of rain acquired with cameras and smartphones. This article is protected by copyright. All rights reserved.
- Seasonal hydrologic responses to climate change in the Pacific Northwest
- Authors: Julie A. Vano; Bart Nijssen, Dennis P. Lettenmaier
Pages: n/a - n/a
Abstract: Increased temperatures and changes in precipitation will result in fundamental changes in the seasonal distribution of streamflow in the Pacific Northwest and will have serious implications for water resources management. To better understand local impacts of regional climate change, we conducted model experiments to determine hydrologic sensitivities of annual, seasonal, and monthly runoff to imposed annual and seasonal changes in precipitation and temperature. We used the Variable Infiltration Capacity (VIC) land‐surface hydrology model applied at 1/16° latitude‐longitude spatial resolution over the Pacific Northwest (PNW), a scale sufficient to support analyses at the hydrologic unit code eight (HUC‐8) basin level. These experiments resolve the spatial character of the sensitivity of future water supply to precipitation and temperature changes by identifying the seasons and locations where climate change will have the biggest impact on runoff. The PNW exhibited a diversity of responses, where transitional (intermediate elevation) watersheds experience the greatest seasonal shifts in runoff in response to cool season warming. We also developed a methodology that uses these hydrologic sensitivities as basin‐specific transfer functions to estimate future changes in long‐term mean monthly hydrographs directly from climate model output of precipitation and temperature. When principles of linearity and superposition apply, these transfer functions can provide feasible first‐order estimates of the likely nature of future seasonal streamflow change without performing downscaling and detailed model simulations. This article is protected by copyright. All rights reserved.
- Issue Information
- Pages: i - v
- Thermodynamics in the hydrologic response: Travel time formulation and
application to Alpine catchments
- Authors: F. Comola; B. Schaefli, A. Rinaldo, M. Lehning
Pages: n/a - n/a
Abstract: This paper presents a spatially‐explicit model for hydro‐thermal response simulations of Alpine catchments, accounting for advective and non‐advective energy fluxes in stream networks characterized by arbitrary degrees of geomorphological complexity. The relevance of the work stems from the increasing scientific interest concerning the impacts of the warming climate on water resources management and temperature‐controlled ecological processes. The description of the advective energy fluxes is cast in a travel time formulation of water and energy transport, resulting in a closed form solution for water temperature evolution in the soil compartment. The application to Alpine catchments hinges on the boundary conditions provided by the fully‐distributed and physically‐based snow model Alpine3D. The performance of the simulations is illustrated by comparing modeled and measured hydrographs and thermographs at the outlet of the Dischma catchment (45km2) in the Swiss Alps. The Monte Carlo calibration shows that the model is robust and that a simultaneous fitting of streamflow and stream temperature reduces the uncertainty in the hydrological parameters estimation. The calibrated model also provides a good fit to the measurements in the validation period, suggesting that it could be employed for predictive applications, both for hydrological and ecological purposes. The temperature of the subsurface flow, as described by the proposed travel time formulation, proves warmer than the stream temperature during winter and colder during summer. Finally, the spatially‐explicit results of the model during snowmelt show a notable hydro‐thermal spatial variability in the river network, owing to the small spatial correlation of infiltration and meteorological forcings in Alpine regions. This article is protected by copyright. All rights reserved.
- Multiple regression and inverse moments improve the characterization of
the spatial scaling behavior of daily streamflows in the southeast United
- Authors: William H. Farmer; Thomas M. Over, Richard M. Vogel
Pages: n/a - n/a
Abstract: Understanding the spatial structure of daily streamflow is essential for managing freshwater resources, especially in poorly‐gaged regions. Spatial scaling assumptions are common in flood frequency prediction (e.g., index‐flood method) and the prediction of continuous streamflow at ungaged sites (e.g. drainage‐area ratio), with simple scaling by drainage area being the most common assumption. In this study, scaling analyses of daily streamflow from 173 streamgages in the southeastern US resulted in three important findings. First, the use of only positive integer moment orders, as has been done in most previous studies, captures only the probabilistic and spatial scaling behavior of flows above an exceedance probability near the median; negative moment orders (inverse moments) are needed for lower streamflows. Second, assessing scaling by using drainage area alone is shown to result in a high degree of omitted‐variable bias, masking the true spatial scaling behavior. Multiple regression is shown to mitigate this bias, controlling for regional heterogeneity of basin attributes, especially those correlated with drainage area. Previous univariate scaling analyses have neglected the scaling of low‐flow events and may have produced biased estimates of the spatial scaling exponent. Third, the multiple regression results show that mean flows scale with an exponent of one, low flows scale with spatial scaling exponents greater than one, and high flows scale with exponents less than one. The relationship between scaling exponents and exceedance probabilities may be a fundamental signature of regional streamflow. This signature may improve our understanding of the physical processes generating streamflow at different exceedance probabilities. This article is protected by copyright. All rights reserved.
- Prolonged river water pollution due to variable‐density flow and
solute transport in the riverbed
- Authors: Guangqiu Jin; Hongwu Tang, Ling Li, D. A. Barry
Pages: n/a - n/a
Abstract: A laboratory experiment and numerical modeling were used to examine effects of density gradients on hyporheic flow and solute transport under the condition of a solute pulse input to a river with regular bedforms. Relatively low density gradients due to an initial salt pulse concentration of 1.55kg m−3 applied in the experiment were found to modulate significantly the pore‐water flow and solute transport in the riverbed. Such density gradients increased downward flow and solute transport in the riverbed by factors up to 1.6. This resulted in a 12.2% increase in the total salt transfer from the water column to the riverbed over the salt pulse period. As the solute pulse passed, the effect of the density gradients reversed, slowing down the release of the solute back to the river water by a factor of 3.7. Numerical modeling indicated that these density effects intensified as salt concentrations in the water column increased. Simulations further showed that the density gradients might even lead to unstable flow and result in solute fingers in the bed of large bedforms. The slow release of solute from the bed back to the river led to a long tail of solute concentration in the river water. These findings have implications for assessment of impact of pollution events on river systems, in particular, long‐term effects on both the river water and riverbed due to the hyporheic exchange. This article is protected by copyright. All rights reserved.
- From analytical solutions of solute transport equations to
multidimensional time‐domain random walk (TDRW) algorithms
- Authors: Jacques Bodin
Pages: n/a - n/a
Abstract: In this study, new multi‐dimensional time‐domain random walk (TDRW) algorithms are derived from approximate one‐dimensional (1‐D), two‐dimensional (2‐D), and three‐dimensional (3‐D) analytical solutions of the advection‐dispersion equation and from exact 1‐D, 2‐D, and 3‐D analytical solutions of the pure‐diffusion equation. These algorithms enable the calculation of both the time required for a particle to travel a specified distance in a homogeneous medium and the mass recovery at the observation point, which may be incomplete due to 2‐D or 3‐D transverse dispersion or diffusion. The method is extended to heterogeneous media, represented as a piecewise collection of homogeneous media. The particle motion is then decomposed along a series of intermediate checkpoints located on the medium interface boundaries. The accuracy of the multi‐dimensional TDRW method is verified against (i) exact analytical solutions of solute transport in homogeneous media and (ii) finite‐difference simulations in a synthetic 2‐D heterogeneous medium of simple geometry. The results demonstrate that the method is ideally suited to purely diffusive transport and to advection‐dispersion transport problems dominated by advection. Conversely, the method is not recommended for highly dispersive transport problems because the accuracy of the advection‐dispersion TDRW algorithms degrades rapidly for a low Péclet number, consistent with the accuracy limit of the approximate analytical solutions. The proposed approach provides a unified methodology for deriving multi‐dimensional time‐domain particle equations and may be applicable to other mathematical transport models, provided that appropriate analytical solutions are available. This article is protected by copyright. All rights reserved.
- Model averaging methods to merge operational statistical and dynamic
seasonal streamflow forecasts in Australia
- Authors: Andrew Schepen; Q.J. Wang
Pages: n/a - n/a
Abstract: The Australian Bureau of Meteorology produces statistical and dynamic seasonal streamflow forecasts. The statistical and dynamic forecasts are similarly reliable in ensemble spread; however skill varies by catchment and season. Therefore, it may be possible to optimize forecasting skill by weighting and merging statistical and dynamic forecasts. Two model averaging methods are evaluated for merging forecasts for 12 locations. The first method, Bayesian model averaging (BMA), applies averaging to forecast probability densities (and thus cumulative probabilities) for a given forecast variable value. The second method, quantile model averaging (QMA), applies averaging to forecast variable values (quantiles) for a given cumulative probability (quantile fraction).
BMA and QMA are found to perform similarly in terms of overall skill scores and reliability in ensemble spread. Both methods improve forecast skill across catchments and seasons. However, when both the statistical and dynamical forecasting approaches are skillful but produce, on special occasions, very different event forecasts, the BMA merged forecasts for these events can have unusually wide and bi‐modal distributions. In contrast, the distributions of the QMA merged forecasts for these events are narrower, uni‐modal and generally more smoothly shaped, and are potentially more easily communicated to and interpreted by the forecast users. Such special occasions are found to be rare. However, every forecast counts in an operational service, and therefore the occasional contrast in merged forecasts between the two methods may be more significant than the indifference shown by the overall skill and reliability performance. This article is protected by copyright. All rights reserved.
- Canopy edge flow: A momentum balance analysis
- Authors: Sharon Moltchanov; Yardena Bohbot‐Raviv, Tomer Duman, Uri Shavit
Pages: n/a - n/a
Abstract: Canopy flow models are often dedicated to ideal, infinite, homogenous systems. However, real canopy systems have physical boundaries, where the flow enters and leaves patches of vegetation, generating a complex pressure field and velocity variations.
Here we focus our study on the canopy entry region by examining the terms involved in the double (space and time) averaged momentum equations and their relative contribution to the total momentum balance. The estimation of each term is made possible by particle image velocimetry (PIV) measurements in a model canopy constructed of randomly distributed thin glass plates. The instantaneous velocity fields were used to calculate the mean velocities, pressure, drag, Reynolds stresses and dispersive stresses.
It was found that within the entry region, the pressure gradient, the drag forces and dispersive stresses are the three most significant terms that affect the balance in the streamwise momentum equation. In the vertical direction, the dispersive stresses are also significant and their contribution to the total momentum cannot be ignored.
The study shows that dispersive stresses are initially formed around canopy edges; at both the entry region and the canopy top boundary. They start as a sink term, extracting momentum from the flow, and then become a source term that contributes momentum to the flow until they eventually decay at some short penetration distance into the canopy. These results reveal a new understanding on the evolution of momentum within the entry region, necessary in any closure‐modeling of flow in real canopies. This article is protected by copyright. All rights reserved.
- Experimental study on effects of geologic heterogeneity in enhancing
dissolution trapping of supercritical CO2
- Authors: Elif Agartan; Luca Trevisan, Abdullah Cihan, Jens Birkholzer, Quanlin Zhou, Tissa H. Illangasekare
Pages: n/a - n/a
Abstract: Dissolution trapping is one of the primary mechanisms that enhance the storage security of supercritical carbon dioxide (scCO2) in saline geologic formations. ScCO2, when dissolved in formation brine, produces an aqueous solution that is denser than brine, which leads to convective mixing driven by gravitational instabilities. Convective mixing can enhance the dissolution of CO2 and thus contribute to stable trapping of dissolved CO2. However, in the presence of geologic heterogeneities, diffusive mixing may also contribute to dissolution trapping. The effects of heterogeneity on mixing and its contribution to stable trapping are not well understood. The goal of this experimental study is to investigate the effects of geologic heterogeneity on mixing and stable trapping of dissolved CO2. The homogeneous and heterogeneous media experiments were conducted in a two‐dimensional test tank with various packing configurations using surrogates for scCO2 (water) and brine (propylene glycol) under ambient pressure and temperature conditions. The results show that the density‐driven flow in heterogeneous formations may not always cause significant convective mixing especially in layered systems containing low permeability zones. In homogeneous formations, density‐driven fingering enhances the storage in the deeper parts of the formation and also the contact between the host rock and dissolved CO2 for the potential mineralization. On the other hand, for layered systems, dissolved CO2 becomes immobilized in low permeability zones with low diffusion rates, which reduces the risk of leakage through any fault or fracture. Both cases contribute to the permanence of the dissolve plume in the formation. This article is protected by copyright. All rights reserved.
- Effects of tidal fluctuations and spatial heterogeneity on mixing and
spreading in spatially heterogeneous coastal aquifers
- Authors: María Pool; Vincent E. A. Post, Craig T. Simmons
Pages: n/a - n/a
Abstract: We study the combined effect of heterogeneity in the hydraulic conductivity field and tidal oscillations on the three‐dimensional dynamics of seawater intrusion in coastal aquifers. We focus on the quantification of its impact on solute mixing and spreading of the freshwater‐seawater interface. Three‐dimensional Monte Carlo realizations of log‐normally distributed permeability fields were performed, and for each realization, numerical variable density flow and solute transport simulations were conducted. Mixing is characterized by the spatial moments of concentration. The enhanced solute mixing is quantified by an effective dispersion coefficient. The simulations show that heterogeneity produces an inland movement of the toe location along with a significant widening of the transition zone, which is linearly proportional to the product of the arithmetic mean of the correlation lengths in the three spatial dimensions (λa) and the permeability field variance . We find that once tidal oscillations are included, as the degree of heterogeneity increases, the combined effect of heterogeneity and tidal oscillations on mixing and spreading of the interface reduces. This is explained by the fact that an increase in the log‐permeability variance induces an increase in both the effective permeability and the spatial connectivity, which implies a more uniform hydraulic response to tidal forcing and, as a result, the degree of mixing decreases. This study also identifies that the mixing behavior induced by tidal oscillations in heterogeneous coastal aquifers is controlled by the effective tidal mixing number which depends on the amplitude, the period, the storativity and the effective horizontal permeability. This article is protected by copyright. All rights reserved.
- Impact of errors in the downwelling irradiances on simulations of snow
water equivalent, snow surface temperature, and the snow energy balance
- Authors: Karl E. Lapo; Laura M. Hinkelman, Mark S. Raleigh, Jessica D. Lundquist
Pages: n/a - n/a
Abstract: The forcing irradiances irradiances (downwelling shortwave and longwave irradiances) are the primary drivers of snowmelt; however, in complex terrain, few observations, the use of estimated irradiances, and the influence of topography and elevation all lead to uncertainties in these radiative fluxes. The impact of uncertainties in the forcing irradiances on simulations of snow is evaluated in idealized modeling experiments. Two snow models of contrasting complexity, the Utah Energy Balance Model (UEB) and the Snow Thermal Model (SNTHERM), are forced with irradiances with prescribed errors of the structure and magnitude representative of those found in methods for estimating the downwelling irradiances. Relatively modest biases have substantial impacts on simulated snow water equivalent (SWE) and surface temperature (Ts) across a range of climates, whereas random noise at the daily scale has a negligible effect on modeled SWE and Ts. Shortwave biases have a smaller SWE impact, due to the influence of albedo, and Ts impact, due to their diurnal cycle, compared to equivalent longwave biases. Warmer sites exhibit greater sensitivity to errors when evaluated using SWE, while colder sites exhibit more sensitivity as evaluated using Ts.
The two models displayed different sensitivity and responses to biases. The stability feedback in the turbulent fluxes explains differences in Ts between models in the negative longwave bias scenarios. When the models diverge during melt events, differences in the turbulent fluxes and internal energy change of the snow are found to be responsible. From this analysis we suggest model evaluations use Ts in addition to SWE. This article is protected by copyright. All rights reserved.
- A hierarchical Bayesian regional model for nonstationary precipitation
extremes in Northern California conditioned on tropical moisture exports
- Authors: Scott Steinschneider; Upmanu Lall
Pages: n/a - n/a
Abstract: Warm, moist, and longitudinally confined tropical air masses are being linked to some of the most extreme precipitation and flooding events in the mid‐latitudes. The inter‐annual frequency and intensity of such atmospheric rivers (ARs), or tropical moisture exports (TMEs), are connected to the risk of extreme precipitation events in areas where moisture convergence occurs. This study presents a non‐stationary, regional frequency analysis of precipitation extremes in Northern California that is conditioned on the inter‐annual variability of TMEs entering the region. Parameters of a multi‐site peaks‐over‐threshold model are allowed to vary conditional on the integrated moisture delivery from TMEs over the area. Parameters are also related to time‐invariant, local characteristics to facilitate regionalization to ungaged sites. The model is developed and calibrated in a hierarchical Bayesian framework to support partial pooling and enhance regionalization skill. The model is cross‐validated along with two alternative, increasingly parsimonious formulations to assess the additional skill provided by the covariates. Climate diagnostics are also used to better understand the instances where TMEs fail to explain variations in rainfall extremes to provide a path forward for further model improvement. The modeling structure is designed to link seasonal forecasting and long‐term projections of TMEs directly to regional models of extremes used for risk estimation. Results suggest that the inclusion of TME‐based information greatly improves the characterization of extremes, particularly for their frequency of occurrence. Diagnostics indicate that the model could be further improved by considering an index for frontal systems as an additional covariate. This article is protected by copyright. All rights reserved.
- An efficient and guaranteed stable numerical method for continuous
modeling of infiltration and redistribution with a shallow dynamic water
- Authors: Wencong Lai; Fred L. Ogden, Robert C. Steinke, Cary A. Talbot
Pages: n/a - n/a
Abstract: We have developed a one‐dimensional numerical method to simulate infiltration and redistribution in the presence of a shallow dynamic water table. This method builds upon the Green‐Ampt infiltration with Redistribution (GAR) model (Ogden and Saghafian, 1997) and incorporates features from the Talbot‐Ogden (T‐O) infiltration and redistribution method (Talbot and Ogden, 2008) in a discretized moisture content domain. The redistribution scheme is more physically meaningful than the capillary weighted redistribution scheme in the T‐O method. Groundwater dynamics are considered in this new method instead of hydrostatic groundwater front. It is also computationally more efficient than the T‐O method. Motion of water in the vadose zone due to infiltration, redistribution and interactions with capillary groundwater are described by ordinary differential equations. Numerical solutions to these equations are computationally less expensive than solutions of the highly non‐linear Richards' (1931) partial differential equation. We present results from numerical tests on 11 soil types using multiple rain pulses with different boundary conditions, with and without a shallow water table and compare against the numerical solution of Richards' Equation (RE). Results from the new method are in satisfactory agreement with RE solutions in term of ponding time, de‐ponding time, infiltration rate and cumulative infiltrated depth. The new method, which we call “GARTO” can be used as an alternative to the RE for 1‐D coupled surface and groundwater models in general situations with homogeneous soils with dynamic water table. The GARTO method represents a significant advance in simulating groundwater surface water interactions because it very closely matches the RE solution while being computationally efficient, with guaranteed mass conservation, and no stability limitations that can affect RE solvers in the case of a near‐surface water table. This article is protected by copyright. All rights reserved.
- Exploring storage and runoff generation processes for urban flooding
through a physically based watershed model
- Authors: B. K. Smith; J. A. Smith, M. L. Baeck, A. J. Miller
Pages: n/a - n/a
Abstract: A physically based model of the 14 km2 Dead Run watershed in Baltimore County, MD was created to test the impacts of detention basin storage and soil storage on the hydrologic response of a small urban watershed during flood events. The Dead Run model was created using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) algorithms and validated using U.S. Geological Survey stream gaging observations for the Dead Run watershed and 5 sub‐basins over the largest 21 warm season flood events during 2008‐2012. Removal of the model detention basins resulted in a median peak discharge increase of 11% and a detention efficiency of 0.5, which was defined as the percent decrease in peak discharge divided by percent detention controlled area. Detention efficiencies generally decreased with increasing basin size. We tested the efficiency of detention basin networks by focusing on the “drainage network order,” akin to the stream order but including storm drains, streams, and culverts. The detention efficiency increased dramatically between first order detention and second order detention but was similar for second and third order detention scenarios. Removal of the soil compacted layer, a common feature in urban soils, resulted in a 7% decrease in flood peak discharges. This decrease was statistically similar to the flood peak decrease caused by existing detention. Current soil storage within the Dead Run watershed decreased flood peak discharges by a median of 60%. Numerical experiment results suggested that detention basin storage and increased soil storage have the potential to substantially decrease flood peak discharges. This article is protected by copyright. All rights reserved.
- Adaptive, multiobjective optimal sequencing approach for urban water
supply augmentation under deep uncertainty
- Authors: Eva H.Y. Beh; Holger R. Maier, Graeme C. Dandy
Pages: n/a - n/a
Abstract: Optimal long‐term sequencing and scheduling play an important role in many water resources problems. The optimal sequencing of urban water supply augmentation options is one example of this. In this paper, an adaptive, multi‐objective optimal sequencing approach for urban water supply augmentation under deep uncertainty is introduced. As part of the approach, optimal long‐term sequence plans are updated at regular intervals and trade‐offs between the robustness and flexibility of the solutions that have to be fixed at the current time and objectives over entire planning horizon are considered when selecting the most appropriate course of action. The approach is demonstrated for the sequencing of urban water supply augmentation options for the southern Adelaide water supply system for two assumed future realities. The results demonstrate the utility of the proposed approach, as it is able to identify optimal sequences that perform better than those obtained using static approaches. This article is protected by copyright. All rights reserved.
- Relating reactive solute transport to hierarchical and multiscale
sedimentary architecture in a Lagrangian‐based transport model: 1.
Time‐dependent effective retardation factor
- Authors: Mohamad Reza Soltanian; Robert W. Ritzi, Chao Cheng Huang, Zhenxue Dai
Pages: n/a - n/a
Abstract: This series of papers addresses the transport of reactive solutes in groundwater. In part 1, the time‐dependent effective retardation factor, R˜eff(t), of reactive solutes undergoing equilibrium sorption is linked to hierarchical stratal architecture using a Lagrangian‐based transport model. The model is based on hierarchical expressions of the spatial covariance of the log distribution coefficient, Ξ=In(Kd), and the spatial cross‐covariance between Ξ and the log permeability,Y=In(k). The spatial correlation structure in these covariance expressions is the probability of transitioning across strata types of different scales, and they are parameterized by independent and quantifiable physical attributes of sedimentary architecture including univariate statistics for Y, Ξ, and proportions and facies lengths. Nothing is assumed about Y‐Ξ point correlation; it is allowed to differ by facies type. The duration of the time‐dependent change in R˜eff(t) is a function of the effective ranges of the cross‐transition probability structures (i.e. the ranges of indicator correlation structures) for each scale of stratal architecture. The plume velocity and the effective retardation stabilize at a large‐time limit after the plume centroid has traveled a distance that encompasses the effective ranges of these cross‐transition probability structures. The well‐documented perchloroethene (PCE) tracer test at the Borden research site is used to illustrate the model. The model gives a viable explanation for the observed PCE plume deceleration, and thus the observed R˜eff(t) can be explained by the process of linear equilibrium sorption and the heterogeneity in k and Kd. In part 2 (Soltanian et al., under review), reactive plume dispersion, as quantified by the particle displacement variance is linked to stratal architecture using a Lagrangian‐based transport model. This article is protected by copyright. All rights reserved.
- Relating sorptive solute transport to hierarchical and multiscale
sedimentary architecture in a Lagrangian‐based transport model: 2.
Particle displacement variance
- Authors: Mohamad Reza Soltanian; Robert W. Ritzi, Chao Cheng Huang, Zhenxue Dai
Pages: n/a - n/a
Abstract: This series of papers addresses the transport of sorbing solutes in groundwater. In part 2, plume dispersion, as quantified by the particle displacement variance, X11R(t), is linked to hierarchical sedimentary architecture using a Lagrangian‐based transport model. This allows for a fundamental understanding of how dispersion arises from the hierarchical architecture of sedimentary facies, and allows for a quantitative decomposition of dispersion into facies‐related contributions at different scales within the hierarchy. As in part 1, the plume behavior is assumed to be controlled by linear‐equilibrium sorption and the heterogeneity in both the log permeability, Y = ln(k), and the log distribution coefficient, Ξ = ln(Kd). Heterogeneity in Y and Ξ arises from sedimentary processes and is structured by the consequent sedimentary architecture. Our goal is to understand the basic science of the dispersion process at this very fundamental level. The spatial auto‐ and cross covariances for the relevant attributes are linear sums of terms corresponding to the probability of transitioning across stratal facies types defined at different scales. Unlike previous studies that used empirical relationships for the spatial covariances, here the model parameters are developed from independent measurements of physically quantifiable attributes of the stratal architecture (i.e. proportions and lengths of facies types, and univariate statistics for Y and Ξ). Nothing is assumed about Y‐Ξ point correlation; it is allowed to differ by facies type. However, it is assumed that Y and Ξ variance is small but meaningful, and that pore‐scale dispersion is negligible. The time‐dependent spreading rate is a function of the effective ranges of the cross‐transition probability structures (i.e. the ranges of indicator correlation structures) for each relevant scale of stratal hierarchy. As in part 1, the well‐documented perchloroethene (PCE) tracer test at the Borden research site is used to illustrate the model. The model was parameterized with univariate statistics for Y, Ξ of (PCE), and proportions and lengths of lithologic facies types defined at two scales within a two‐level hierarchical classification, as given by Ritzi et al. . The model gives a viable explanation for the observed PCE plume dispersion, and thus X11R(t) can be explained by the process of linear equilibrium sorption and the heterogeneity in k and Kd. The results quantitatively show that the k ‐ Kd cross‐correlation, though small, and varied by facies type, can significantly impact the particle displacement variance. Furthermore, by quantitatively decomposing the dispersion into facies‐related contributions, we gain the fundamental insight that that the time‐dependent rate of spreading is mostly defined by the cross‐transition probability correlation structure imparted by the proportions and sizes of the larger‐scale facies types. This article is protected by copyright. All rights reserved.
- Prediction of Glossosoma biomass spatial distribution in Valley Creek by
field measurements and a three‐dimensional turbulent
open‐channel flow model
- Authors: M. Morris; M. Haji Mohammadi, S. Day, M. Hondzo, F. Sotiropoulos
Pages: n/a - n/a
Abstract: The fluid flow environment associated with high Glossosoma abundance is predicted by large‐eddy simulation of a natural turbulent open‐channel flow. The spatial distribution of Glossosoma was depicted by high resolution physical variables described by fluid flow and streambed topography. Variogram analysis of the streambed topography revealed a characteristic length scale of the streambed of the order 0.2m over which bed roughness height was correlated. Flow simulation output was spatially and temporally averaged over the streambed characteristic length scale and linked to Glossosoma spatial density. A dimensionless scaling relationship between Glossosoma spatial distribution and streamwise velocity averaged in the longitudinal and transverse direction, spatial velocity fluctuation, and spanwise vorticity from the computational fluid dynamics simulation output explained 79% of the variation in observed dimensionless Glossosoma spatial density. The analysis demonstrated that computational fluid mechanics and high resolution bed topography could be instrumental in predicting benthic macroinvertebrate spatial distribution in streams and rivers. This article is protected by copyright. All rights reserved.
- Toward a true spatial model evaluation in distributed hydrological
modeling: Kappa statistics, Fuzzy theory, and EOF analysis benchmarked by
the human perception and evaluated against a modeling case study
- Authors: Julian Koch; Karsten Høgh Jensen, Simon Stisen
Pages: n/a - n/a
Abstract: The hydrological modeling community is aware that the validation of distributed hydrological models has to move beyond aggregated performance measures, like hydrograph assessment by means of Nash‐Suitcliffe efficiency towards a true spatial model validation. Remote sensing facilitates continuous data and can be measured on a similar spatial scale as the predictive scale of the hydrological model thereby it can serve as suitable data for the spatial validation. The human perception is often described as a very reliable and well trained source for pattern comparison, which this study wants to exploit. A web‐based survey that is interpreted based on approximately 200 replies reflects the consensus of the human perception on map comparisons of a reference map and 12 synthetic perturbations. The resulting similarity ranking can be used as a reference to benchmark various spatial performance metrics. This study promotes Fuzzy theory as a suitable approach because it considers uncertainties related to both location and value in the simulated map. Additionally, an EOF‐analysis (Empirical Orthogonal Function) is conducted to decompose the map comparison into its similarities and dissimilarities. A modeling case study serves to further examine the metrics capability to assess the goodness of fit between simulated and observed land surface temperature maps. The EOF‐analysis unambiguously identifies a systematic depth to groundwater table related model deficiency. Kappa statistic extended by Fuzziness is a suitable and commonly applied measure for map comparison. However, its apparent bias sensitivity limits it's capability as a diagnostic tool to detect the distinct deficiency. This article is protected by copyright. All rights reserved.
- Impacts of rainfall spatial variability on hydrogeological response
- Authors: Gonzalo Sapriza‐Azuri; Jorge Jódar, Vicente Navarro, Luit Jan Slooten, Jesús Carrera, Hoshin V. Gupta
Pages: n/a - n/a
Abstract: There is currently no general consensus on how the spatial variability of rainfall impacts and propagates through complex hydrogeological systems. Most studies to date have focused on the effects of rainfall spatial variability (RSV) on river discharge, while paying little attention to other important aspects of system response. Here, we study the impacts of RSV on several responses of a hydrological model of an overexploited system. To this end, we drive a spatially distributed hydrogeological model for the semi‐arid Upper Guadiana basin in central Spain with stochastic daily rainfall fields defined at three different spatial resolutions (fine → 2.5km x 2.5km, medium → 50km x50km, large → lumped). This enables us to investigate how (i) RSV at different spatial resolutions, and (ii) rainfall uncertainty, are propagated through the hydrogeological model of the system. Our results demonstrate that RSV has a significant impact on the modeled response of the system, by specifically affecting groundwater recharge and runoff generation, and thereby propagating through to various other related hydrological responses (river discharge, river‐aquifer exchange, groundwater levels). These results call into question the validity of management decisions made using hydrological models calibrated or forced with spatially lumped rainfall. This article is protected by copyright. All rights reserved.
- Anomalous solute transport in saturated porous media: Relating transport
model parameters to electrical and nuclear magnetic resonance properties
- Authors: Ryan D. Swanson; Andrew Binley, Kristina Keating, Samantha France, Gordon Osterman, Frederick D. Day‐Lewis, Kamini Singha
Pages: n/a - n/a
Abstract: The advection‐dispersion equation (ADE) fails to describe commonly observed non‐Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual‐domain mass transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct‐current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non‐Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column‐scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more‐ and less‐mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material‐ and flow‐ dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT. This article is protected by copyright. All rights reserved.
- Impact of space‐time mesh adaptation on solute transport modeling in
- Authors: Bahman Esfandiar; Giovanni Porta, Simona Perotto, Alberto Guadagnini
Pages: n/a - n/a
Abstract: We implement a space‐time grid adaptation procedure to efficiently improve the accuracy of numerical simulations of solute transport in porous media in the context of model parameter estimation. We focus on the Advection Dispersion Equation (ADE) for the interpretation of non‐reactive transport experiments in laboratory‐scale heterogeneous porous media. When compared to a numerical approximation based on a fixed space‐time discretization, our approach is grounded on a joint automatic selection of the spatial grid and the time step to capture the main (space‐time) system dynamics. Spatial mesh adaptation is driven by an anisotropic recovery‐based error estimator which enables us to properly select the size, shape and orientation of the mesh elements. Adaptation of the time step is performed through an ad‐hoc local reconstruction of the temporal derivative of the solution via a recovery‐based approach. The impact of the proposed adaptation strategy on the ability to provide reliable estimates of the key parameters of an ADE model is assessed on the basis of experimental solute breakthrough data measured following tracer injection in a non‐uniform porous system. Model calibration is performed in a Maximum Likelihood (ML) framework upon relying on the representation of the ADE solution through a generalized Polynomial Chaos Expansion (gPCE). Our results show that the proposed anisotropic space‐time grid adaptation leads to ML parameter estimates and to model results of markedly improved quality when compared to classical inversion approaches based on a uniform space‐time discretization. This article is protected by copyright. All rights reserved.
- Estimating freshwater flows from tidally affected hydrographic data
- Authors: D.E. Pagendam; D.B. Percival
Pages: n/a - n/a
Abstract: De‐tiding end‐of‐catchment flow data is an important step in determining the total volumes of freshwater (and associated pollutant loads) entering the ocean. We examine three approaches for separating freshwater and tidal flows from tidally‐affected data: (i) a simple low‐pass Butterworth filter (BWF); (ii) a robust, harmonic analysis with Kalman smoothing (RoHAKS) which is a novel approach introduced in this paper; and (iii) dynamic harmonic regression (DHR). Using hydrographic data collected in the Logan River, Australia over a period of 452 days, we judge the accuracy of the three methods based on three criteria: consistency of freshwater flows with upstream gauges; consistency of total discharge volumes with the raw data over the event; and minimal upstream flow. A simulation experiment shows that RoHAKS outperforms both BWF and DHR on a number of criteria. In addition RoHAKS enjoys a computational advantage over DHR in speed and use of freely available software. This article is protected by copyright. All rights reserved.
- Dynamic connectivity in a fluvial network for identifying hot spots of
- Authors: Jonathan A. Czuba; Efi Foufoula‐Georgiou
Pages: n/a - n/a
Abstract: Dynamical processes occurring on the hierarchical branching structure of a river network tend to heterogeneously distribute fluxes on the network, often concentrating them into “clusters,” i.e., places of excess flux accumulation. Here, we put forward the hypothesis that places in the network predisposed (due to process dynamics and network topology) to accumulate excess sediment over a considerable river reach and over a considerable period of time reflect locations where a local imbalance in sediment flux may occur thereby highlighting a susceptibility to potential fluvial geomorphic change. We develop a dynamic connectivity framework which uses the river network structure and a simplified Lagrangian transport model to trace fluxes through the network and integrate emergent “clusters” through a cluster persistence index (CPI). The framework was applied to sand transport in the Greater Blue Earth River Network in the Minnesota River Basin. Three hotspots of fluvial geomorphic change were defined as locations where high rates of channel migration were observed and places of high CPI coincided with two of these hotspots of possibly sediment‐driven change. The third hotspot was not identified by high CPI, but instead is believed to be a hotspot of streamflow‐driven change based on additional information and the fact that high bed shear stress coincided with this hotspot. The proposed network‐based dynamic connectivity framework has the potential to place dynamical processes occurring at small scales into a network context to understand how reach‐scale changes cascade into network‐scale effects, useful for informing the large‐scale consequences of local management actions. This article is protected by copyright. All rights reserved.
- Evaluating observational methods to quantify snow duration under diverse
- Authors: Susan E. Dickerson‐Lange; James A. Lutz, Kael A. Martin, Mark S. Raleigh, Rolf Gersonde, Jessica D. Lundquist
Pages: n/a - n/a
Abstract: Forests cover almost 40% of the seasonally snow‐covered regions in North America. However, operational snow networks are located primarily in forest clearings, and optical remote sensing cannot see through tree canopies to detect forest snowpack. Due to the complex influence of the forest on snowpack duration, ground observations in forests are essential. We therefore consider the effectiveness of different strategies to observe snow‐covered area under forests. At our study location in the Pacific Northwest, we simultaneously deployed fiber‐optic cable, stand‐alone ground temperature sensors, and time‐lapse digital cameras in three diverse forest treatments: control second‐growth forest, thinned forest, and forest gaps (one tree height in diameter). We derived fractional snow‐covered area and snow duration metrics from the co‐located instruments to assess optimal spatial resolution and sampling configuration, and snow duration differences between forest treatments. The fiber‐optic cable and the cameras indicated that mean snow duration was 8 days longer in the gap plots than in the control plots (p
- Variational Lagrangian data assimilation in open channel networks
- Authors: Qingfang Wu; Andrew Tinka, Kevin Weekly, Jonathan Beard, Alexandre M. Bayen
Pages: n/a - n/a
Abstract: This article presents a data assimilation method in a tidal system, where data from both Lagrangian drifters and Eulerian flow sensors were fused to estimate water velocity. The system is modeled by first‐order, hyperbolic partial differential equations subject to periodic forcing. The estimation problem can then be formulated as the minimization of the difference between the observed variables and model outputs, and eventually provide the velocity and water stage of the hydrodynamic system. The governing equations are linearized and discretized using an implicit discretization scheme, resulting in linear equality constraints in the optimization program. Thus, the flow estimation can be formed as a optimization problemming problem and efficiently solved.
The effectiveness of the proposed method was substantiated by a large‐scale field experiment in the Sacramento‐San Joaquin River Delta in California. A fleet of 100 sensors developed at the University of California, Berkeley were deployed in Walnut Grove, CA to collect a set of Lagrangian data, a time‐series of positions as the sensors moved through the water. Measurements were also taken from Eulerian sensors in the region, provided by the United States Geological Survey. It is shown that the proposed method can effectively integrate Lagrangian and Eulerian measurement data, resulting in a suited estimation of the flow variables within the hydraulic system. This article is protected by copyright. All rights reserved.
- Probabilistic precipitation rate estimates with ground‐based radar
- Authors: Pierre‐Emmanuel Kirstetter; Jonathan J. Gourley, Yang Hong, Jian Zhang, Saber Moazamigoodarzi, Carrie Langston, Ami Arthur
Pages: n/a - n/a
Abstract: The uncertainty structure of radar quantitative precipitation estimation (QPE) is largely unknown at fine spatiotemporal scales near the radar measurement scale. By using the WSR‐88D radar network and gauge datasets across the conterminous US, an investigation of this subject has been carried out within the framework of the NOAA/NSSL ground radar‐based Multi‐Radar Multi‐Sensor (MRMS) QPE system. A new method is proposed and called PRORATE for Probabilistic QPE using Radar Observations of Rate And Typology Estimates. Probability distributions of precipitation rates are computed instead of deterministic values using a model quantifying the relation between radar reflectivity and the corresponding “true” precipitation. The probabilistic model acknowledges the uncertainty arising from many factors operative at the radar measurement scale and from the correction algorithm. Ensembles of reflectivity‐to‐precipitation rate relationships accounting explicitly for precipitation typology were derived at a 5‐min/1‐km scale. This approach conditions probabilistic quantitative precipitation estimates (PQPE) on the precipitation rate and type. The model components were estimated on the basis of a 1‐year‐long data sample over the CONUS. This PQPE model provides the basis for precipitation probability maps and the generation of radar precipitation ensembles. Maps of the precipitation exceedance probability for specific thresholds (e.g. precipitation return periods) are computed. Precipitation probability maps are accumulated to the hourly time scale and compare favorably to the deterministic QPE. As an essential property of precipitation, the impact of the temporal correlation on the hourly accumulation is examined. This approach to PQPE can readily apply to other systems including space‐based passive and active sensor algorithms. This article is protected by copyright. All rights reserved.
- North American precipitation isotope (δ18O) zones revealed in time
series modeling across Canada and northern United States
- Authors: Delavau C; Chun K.P, Stadnyk T, Birks S.J, Welker J.M.
Pages: n/a - n/a
Abstract: Delineating spatial patterns of precipitation isotopes (“isoscapes”) is becoming increasingly important to understand the processes governing the modern water isotope cycle and their application to migration forensics, climate proxy interpretation, and ecohydrology of terrestrial systems. However, the extent to which these patterns can be empirically predicted across Canada and the northern United States of America (USA) has not been fully articulated, in part due to a lack of time‐series precipitation isotope data for major regions of North America. In this study, we use multiple linear regressions of CNIP, GNIP and USNIP observations alongside climatological variables, teleconnection indices, and geographic indicators to create empirical models that predict the δ18O of monthly precipitation (δ18Oppt) across Canada and the northern USA. Five regionalization approaches are used to separate the study domain into isotope zones to explore the effect of spatial grouping on model performance. Stepwise regression‐derived parameterizations quantified by permutation testing indicate the significance of precipitable water content and latitude as predictor variables. Within the Canadian Arctic and eastern portion of the study domain, models from all regionalizations capture the inter‐ and intra‐annual variability of δ18Oppt. The Pacific coast and northwestern portions of the study domain show less agreement between models and poorer model performance, resulting in higher uncertainty in simulations throughout these regions. Long‐term annual average δ18Oppt isoscapes are generated, highlighting the uncertainty in the regionalization approach as it compounds over time. Additionally, monthly time‐series simulations are presented at various locations, and model structure uncertainty and 90% bootstrapped prediction bounds are detailed for these predictions. This article is protected by copyright. All rights reserved.
- Hydraulic effects on nitrogen removal in a tidal spring‐fed river
- Authors: Robert T. Hensley; Matthew J. Cohen, Larry V. Korhnak
Pages: n/a - n/a
Abstract: Hydraulic properties such as stage and residence time are important controls on riverine N removal. In most rivers, these hydraulic properties vary with stochastic precipitation forcing, but in tidal rivers, hydraulics variation occurs on a predictable cycle. In Manatee Springs, a highly productive, tidally influenced spring‐fed river in Florida, we observed significant reach‐scale N removal that varied in response to tidally‐driven variation in hydraulic properties as well as sunlight‐driven variation in assimilatory uptake. After accounting for channel residence time and stage variation, we partitioned the total removal signal into assimilatory (i.e., plant uptake) and dissimilatory (principally denitrification) pathways. Assimilatory uptake was strongly correlated with primary production and ecosystem C:N was concordant with tissue stoichiometry of the dominant autotrophs. The magnitude of N removal was broadly consistent in magnitude with predictions from models (SPARROW and RivR‐N). However, contrary to model predictions, the highest removal occurred at the lowest values of τ/d (residence time divided by depth), which occurred at low tide. Removal efficiency also exhibited significant counterclockwise hysteresis with incoming versus outgoing tides. This behavior is best explained by the sequential filling and draining of transient storage zones such that water that has spent the longest time in the storage zone, and thus had the most time for N removal, drains back into the channel at the end of an outgoing tide, concurrent with shortest channel residence times. Capturing this inversion of the expected relationship between channel residence time and N removal highlights the need for non‐steady‐state reactive transport models. This article is protected by copyright. All rights reserved.
- Temporal responses of groundwater‐surface water exchange to
successive storm events
- Authors: Marina Dudley‐Southern; Andrew Binley
Pages: n/a - n/a
Abstract: Groundwater‐surface water exchange within the hyporheic zone is widely recognized as a key mechanism controlling the fate of nutrients within catchments. In gaining river systems, groundwater‐surface water interactions are constrained by upwelling groundwater but there is increasing evidence that a rapid rise in river stage during storm events can result in a temporary reversal of vertical hydraulic gradients, leading to surface water infiltration into the subsurface and supply of surface‐borne reactive solutes to this biogeochemically active interface. At a UK study site, using logged hydraulic heads in the surface water, riverbed and riverbanks and logged electrical conductivity at multiple depths in the riverbed we show that storm events can lead to a temporary reversal of vertical hydraulic gradient with mixing evident up to 30cm beneath the riverbed. Cross‐channel variability is evident, with the center of the channel consistently having shorter reversals of hydraulic gradient, compared to the channel margins. The direction of shallow subsurface riverbank flow at the site is also reactive to storm events, temporarily aligning with the surface flow direction and then reverting back to pre‐event conditions. Such a transition of flow paths during events is also likely to lead to expansion of lateral hyporheic exchange. This study provides evidence that storm events can be a key driver of enhanced hyporheic exchange in gaining river systems, which may support nutrient reactions beyond the duration of event‐driven change. Our observations demonstrate the dynamic nature of the hyporheic zone, which should be considered when evaluating its biogeochemical function. This article is protected by copyright. All rights reserved.
- Blending satellite‐based snow depth products with in situ
- Authors: Yuqiong Liu; Christa D. Peters‐Lidard, Sujay V. Kumar, Kristi R. Arsenault, David M. Mocko
Pages: n/a - n/a
Abstract: In snowmelt‐driven river systems, it is critical to enable reliable predictions of the spatio‐temporal variability in seasonal snowpack to support local and regional water management. Previous studies have shown that assimilating satellite‐station blended snow depth datasets can lead to improved snow predictions, which however do not always translate into improved streamflow predictions, especially in complex mountain regions. In this study, we explore how the existing optimal interpolation‐based blending strategy [Liu et al., 2013] can be enhanced to reduce biases in satellite snow depth products for improving streamflow predictions. Two major new considerations are explored, including: 1) incorporating terrain aspect and 2) incorporating areal snow coverage information. The methodology is applied to the bias reduction of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) snow depth estimates, which are then assimilated into the Noah land surface model via the ensemble Kalman Filtering (EnKF) for streamflow predictions in the Upper Colorado River Basin. Our results indicate that using only observations from low‐elevation stations such as the Global Historical Climatology Network (GHCN) in the bias correction can lead to underestimation in streamflow, while using observations from high‐elevation stations (e.g., the Snow Telemetry (SNOTEL) network) along with terrain aspect is critically important for achieving reliable streamflow predictions. Additionally incorporating areal snow coverage information from the Moderate Resolution Imaging Spectroradiometer (MODIS) can slightly improve the streamflow results further. This article is protected by copyright. All rights reserved.
- Ecohydrologic role of solar radiation on landscape evolution
- Authors: Omer Yetemen; Erkan Istanbulluoglu, J. Homero Flores‐Cervantes, Enrique R. Vivoni, Rafael L. Bras
Pages: n/a - n/a
Abstract: Solar radiation has a clear signature on the spatial organization of ecohydrologic fluxes, vegetation patterns and dynamics, and landscape morphology in semiarid ecosystems. Existing landscape evolution models (LEMs) do not explicitly consider spatially‐explicit solar radiation as model forcing. Here, we improve an existing LEM to represent coupled processes of energy, water, and sediment balance for semiarid fluvial catchments. To ground model predictions a study site is selected in central New Mexico where hillslope aspect has a marked influence on vegetation patterns and landscape morphology. Model predictions are corroborated using limited field observations in central NM and other locations with similar conditions. We design a set of comparative LEM simulations to investigate the role of spatially‐explicit solar radiation on landscape ecohydro‐geomorphic development under different uplift scenarios. Aspect‐ and network‐controls were identified as the two main drivers of soil moisture and vegetation organization on the landscape. Landscape‐scale and long‐term implications of these short‐term ecohdrologic patterns emerged in modeled landscapes. As north facing slopes (NFS) get steeper by continuing uplift they support erosion‐resistant denser vegetation cover which leads to further slope steepening until erosion and uplift attains a dynamic equilibrium. Conversely, on north facing slopes (SFS), as slopes grow with uplift, increased solar radiation exposure with slope supports sparser biomass and shallower slopes. At the landscape scale, these differential erosion processes lead to asymmetric development of catchment forms, consistent with regional observations. Understanding of ecohydro‐geomorphic evolution will improve to assess the impacts of past and future climates on landscape response and morphology. This article is protected by copyright. All rights reserved.
- Analysis of subsurface storage and streamflow generation in urban
- Authors: Aditi S. Bhaskar; Claire Welty
Pages: n/a - n/a
Abstract: Subsurface storage as a regulator of streamflow was investigated as an explanation for the large proportion of pre‐event water observed in urban streams during storm events. We used multiple lines of inquiry to explore the relationship between pre‐event water proportion, subsurface storage, and streamflow under storm conditions. First, we used a three‐dimensional model of integrated subsurface and surface flow and solute transport to simulate an idealized hillslope to perform model‐based chemical hydrograph separation of storm flow. Second, we employed simple dynamical systems analysis to derive the relationship between subsurface storage and streamflow for three Baltimore, Maryland watersheds (3.8 to 14km2 in area) along an urban‐to‐rural gradient. Last, we applied chemical hydrograph separation to high‐frequency specific conductance data in nested urban watersheds (∼50% impervious surface cover) in Dead Run, Baltimore County, Maryland. Unlike the importance of antecedent subsurface storage observed in some systems, we found that rainfall depth and not subsurface storage was the primary control on pre‐event water proportion in both field observations and hillslope numerical experiments. Field observations showed that antecedent stream base flow did not affect pre‐event water proportion or streamflow values under storm conditions. Hillslope model results showed that the relationship between streamflow values under storm conditions and subsurface storage was clockwise hysteretic. The simple dynamical systems approach showed that stream base flow in the most urbanized of three watersheds exhibited the largest sensitivity to changes in storage. This work raises questions about the streamflow generation mechanisms by which pre‐event water dominates urban storm hydrographs, and the shifts between mechanisms in rural and urban watersheds. This article is protected by copyright. All rights reserved.
- Functional error modeling for uncertainty quantification in hydrogeology
- Authors: L. Josset; D. Ginsbourger, I. Lunati
Pages: n/a - n/a
Abstract: Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine Functional Data Analysis and Machine Learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose‐oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization. This article is protected by copyright. All rights reserved.
- Evaluating the complementary relationship of evapotranspiration in the
alpine steppe of the Tibetan Plateau
- Authors: Ning Ma; Yinsheng Zhang, Jozsef Szilagyi, Yanhong Guo, Jianqing Zhai, Haifeng Gao
Pages: n/a - n/a
Abstract: The complementary relationship (CR) of evapotranspiration allows the estimation of the actual evapotranspiration rate (ETa) of the land surface using only routine meteorological data, which is of great importance in the Tibetan Plateau (TP) due to its sparse observation network. With the highest in‐situ automatic climate observation system in a typical semi‐arid alpine steppe region of the TP, the wind function of Penman was replaced by one based on the Monin‐Obukhov Similarity theory for calculating the potential evapotranspiration rate (ETp); the Priestley‐Taylor coefficient, α, was estimated using observations in wet days; and the slope of the saturation vapor pressure curve was evaluated at an estimate of the wet surface temperature, provided the latter was smaller than the actual air temperature. A symmetric CR was obtained between the observed daily actual and potential evapotranspiration. Local calibration of the parameter value (in this order) is key to obtaining a symmetric CR: α, wet environment air temperature (Twea), and wind function. Also, present symmetric CR contradicts previous research that used default parameter values for claiming an asymmetric CR in arid and semi‐arid regions of the TP. The effectiveness of estimating the daily ETa via symmetric CR was greatly improved when local calibrations were implemented. At the same time, an asymmetric CR was found between the observed daily ETa and pan evaporation rates (Epan), both for D20 above‐ground and E601B sunken pans. The daily ETa could also be estimated by coupling the Epan of D20 above‐ground and/or E601B sunken pan through CR. The former provided good descriptors for observed ETa, while the latter still tended to overestimate it to some extent. This article is protected by copyright. All rights reserved.
- Testing a simple model of gas bubble dynamics in porous media
- Authors: Jorge A. Ramirez; Andy J. Baird, Tom J. Coulthard, J. Michael Waddington
Pages: n/a - n/a
Abstract: Bubble dynamics in porous media are of great importance in industrial and natural systems. Of particular significance is the impact that bubble‐related emissions (ebullition) of greenhouse gases from porous media could have on global climate (e.g., wetland methane emissions). Thus predictions of future changes in bubble storage, movement and ebullition from porous media are needed. Methods exist to predict ebullition using numerical models, but all existing models are limited in scale (spatial and temporal) by high computational demands or represent porous media simplistically. A suitable model is needed to simulate ebullition at scales beyond individual pores or relatively small collections (< 10−4 m3) of connected pores. Here we present a cellular automaton model of bubbles in porous media that addresses this need. The model is computationally efficient, and could be applied over large spatial and temporal extent without sacrificing fine scale detail. We test this cellular automaton model against a physical model and find a good correspondence in bubble storage, bubble size and ebullition between both models. It was found that porous media heterogeneity alone can have a strong effect on ebullition. Furthermore, results from both models suggest that the frequency distributions of number of ebullition events per time and the magnitude of bubble loss are strongly right skewed, which partly explains the difficulty in interpreting ebullition events from natural systems. This article is protected by copyright. All rights reserved.
- Breakthrough curve moments scaling in hyporheic exchange
- Authors: A. Bellin; D. Tonina, A. Marzadri
Pages: n/a - n/a
Abstract: The interaction between stream flow and bedforms creates an uneven distribution of near‐bed energy heads, which is the driving force of hyporheic exchange. Owing to the large disparity of advection characteristic times in the stream and within the hyporheic zone, solute mass exchange is often modeled by considering the latter as an immobile region. In a recent contribution Gónzalez‐Pinzón et al.  showed that existing models employing this hypothesis are structurally inconsistent with the scaling revealed by the analysis of 384 breakthrough curves collected in 44 stream across five continents. Motivated by this result, we analyze the scaling characteristics of a model that we recently developed by combining the analytical solution of the advective flow within the hyporheic zone with a Lagrangian solute transport model. Results show that similarly to the experimental data our model predicts breakthrough curves showing a constant skewness, irrespective of the stream size, and that the scaling of the first three moments observed by Gónzalez‐Pinzón et al.  is also respected. Moreover, we propose regression curves that relate the first three moments of the residence time distribution with the alternate bar dimensionless depth (), a quantity that is easily measurable in the field. The connection between BTC moments and opens new possibilities for modeling transport processes at the catchment scale. This article is protected by copyright. All rights reserved.
- Challenges in modeling unstable two‐phase flow experiments in porous
- Authors: Andrea Ferrari; Joaquin Jimenez‐Martinez, Tanguy Le Borgne, Yves Méheust, Ivan Lunati
Pages: n/a - n/a
Abstract: The simulation of unstable invasion patterns in porous media flow is very challenging because small perturbations are amplified, so that slight differences in geometry or initial conditions result in significantly different invasion structures at later times. We present a detailed comparison of pore‐scale simulations and experiments for unstable primary drainage in porous micromodels. The porous media consist of Hele‐Shaw cells containing cylindrical obstacles. By means of soft lithography, we have constructed two experimental flow cells, with different degrees of heterogeneity in the grain size distribution. As the defending (wetting) fluid is the most viscous, the interface is destabilized by viscous forces, which promote the formation of preferential flow paths in the form of a branched finger structure. We model the experiments by solving the Navier‐Stokes equations for mass and momentum conservation in the discretized pore space and employ the Volume of Fluid (VOF) method to track the evolution of the interface. We test different numerical models (a 2D vertical integrated model and a full‐3D model) and different initial conditions, studying their impact on the simulated spatial distributions of the fluid phases. To assess the ability of the numerical model to reproduce unstable displacement, we compare several statistical and deterministic indicators. We demonstrate the impact of three main sources of error: i) the uncertainty on the pore space geometry, ii) the fact that the initial phase configuration cannot be known with an arbitrarily small accuracy, and iii) three dimensional effects. Although the unstable nature of the flow regime leads to different invasion structures due to small discrepancies between the experimental setup and the numerical model, a pore‐by‐pore comparison shows an overall satisfactory match between simulations and experiments. Moreover, all statistical indicators used to characterized the invasion structures are in excellent agreement. This validates the modeling approach, which can be used to complement experimental observations with information about quantities that are difficult or impossible to measure, such as the pressure and velocity fields in the two fluid phases. This article is protected by copyright. All rights reserved.
- Pore‐scale and multiscale numerical simulation of flow and transport
in a laboratory‐scale column
- Authors: Timothy D. Scheibe; William A. Perkins, Marshall C. Richmond, Matthew I. McKinley, Pedro D. J. Romero‐Gomez, Mart Oostrom, Thomas W. Wietsma, John A. Serkowski, John M. Zachara
Pages: n/a - n/a
Abstract: Pore‐scale models are useful for studying relationships between fundamental processes and phenomena at larger (i.e., Darcy) scales. However, the size of domains that can be simulated with explicit pore‐scale resolution is limited by computational and observational constraints. Direct numerical simulation of pore‐scale flow and transport is typically performed on millimeter‐scale volumes at which X‐ray computed tomography (XCT), often used to characterize pore geometry, can achieve micrometer resolution. In contrast, laboratory experiments that measure continuum properties are typically performed on decimeter‐scale columns. At this scale, XCT resolution is coarse (tens to hundreds of micrometers) and prohibits characterization of small pores and grains. We performed simulations of pore‐scale processes over a decimeter‐scale volume of natural porous media with a wide range of grain sizes, and compared to results of column experiments using the same sample. Simulations were conducted using high‐performance codes executed on a supercomputer. Two approaches to XCT image segmentation were evaluated, a binary (pores and solids) segmentation and a ternary segmentation that resolved a third category (porous solids with pores smaller than the imaged resolution). We used a multiscale Stokes‐Darcy simulation method to simulate the combination of Stokes flow in large open pores and Darcy‐like flow in porous solid regions. Flow and transport simulations based on the binary segmentation were inconsistent with experimental observations because of overestimation of large connected pores. Simulations based on the ternary segmentation provided results that were consistent with experimental observations, demonstrating our ability to successfully model pore‐scale flow over a column‐scale domain. This article is protected by copyright. All rights reserved.
- A Bayesian kriging approach for blending satellite and ground
- Authors: Andrew Verdin; Balaji Rajagopalan, William Kleiber, Chris Funk
Pages: n/a - n/a
Abstract: Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite‐derived precipitation data is an attractive alternative, though it also tends to underestimate the magnitude of wet events due to its dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here, we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation (CHIRP) satellite‐derived precipitation estimate for Central America and Colombia. First, the gauge observations are modeled as a linear function of satellite‐derived estimates and any number of other variables – for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo (MCMC) sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. It is shown that this blending method significantly improves upon the satellite‐derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution of the “true” observed precipitation value at each grid cell. This article is protected by copyright. All rights reserved.
- Three‐dimensional quantification of soil hydraulic properties using
X‐ray Computed Tomography and image‐based modeling
- Authors: Saoirse R. Tracy; Keith R. Daly, Craig J. Sturrock, Neil M. J. Crout, Sacha J. Mooney, Tiina Roose
Pages: n/a - n/a
Abstract: We demonstrate the application of a high‐resolution X‐ray Computed Tomography (CT) method to quantify water distribution in soil pores under successive reductive drying. We focus on the wet end of the water release characteristic (WRC) (0 to ‐75 kPa) to investigate changes in soil water distribution in contrasting soil textures (sand and clay) and structures (sieved and field structured), to determine the impact of soil structure on hydraulic behaviour. The 3D structure of each soil was obtained from the CT images (at a 10 µm resolution). Stokes equations for flow were solved computationally for each measured structure to estimate hydraulic conductivity. The simulated values obtained compared extremely well with the measured saturated hydraulic conductivity values. By considering different sample sizes we were able to identify that the smallest possible representative sample size which is required to determine a globally valid hydraulic conductivity. This article is protected by copyright. All rights reserved.
- Untangling the effects of urban development on subsurface storage in
- Authors: Aditi S. Bhaskar; Claire Welty, Reed M. Maxwell, Andrew J. Miller
Pages: n/a - n/a
Abstract: The impact of urban development on surface flow has been studied extensively over the last half century, but effects on groundwater systems are still poorly understood. Previous studies of the influence of urban development on subsurface storage have not revealed any consistent pattern, with results showing increases, decreases, and negligible change in groundwater levels. In this paper we investigated the effects of four key features that impact subsurface storage in urban landscapes. These include reduced vegetative cover, impervious surface cover, infiltration and inflow (I&I) of groundwater and stormwater into wastewater pipes, and other anthropogenic recharge and discharge fluxes including water supply pipe leakage and well and reservoir withdrawals. We applied the integrated groundwater‐surface water‐land surface model ParFlow.CLM to the Baltimore metropolitan area. We compared the base case (all four features) to simulations in which an individual urban feature was removed. For the Baltimore region, the effect of infiltration of groundwater into wastewater pipes had the greatest effect on subsurface storage (I&I decreased subsurface storage 11.1% relative to precipitation minus evapotranspiration after one year), followed by the impact of water supply pipe leakage and lawn irrigation (combined anthropogenic discharges and recharges led to a 7.4% decrease) and reduced vegetation (1.9% increase). Impervious surface cover led to a small increase in subsurface storage (0.56% increase) associated with decreased groundwater discharge as baseflow. The change in subsurface storage due to infiltration of groundwater into wastewater pipes was largest despite the smaller spatial extent of surface flux modifications, compared to other features. This article is protected by copyright. All rights reserved.
- A faster numerical scheme for a coupled system modeling soil erosion and
- Authors: M.‐H. Le; S. Cordier, C. Lucas, O. Cerdan
Pages: n/a - n/a
Abstract: Overland flow and soil erosion play an essential role in water quality and soil degradation. Such processes, involving the interactions between water flow and the bed sediment, are classically described by a well‐established system coupling the shallow water equations and the Hairsine‐Rose model. Numerical approximation of this coupled system requires advanced methods to preserve some important physical and mathematical properties; in particular the steady states and the positivity of both water depth and sediment concentration. Recently, finite volume schemes based on Roe's solver have been proposed by Heng et al.  and Kim et al.  for one and two‐dimensional problems. In their approach, an additional and artificial restriction on the time step is required to guarantee the positivity of sediment concentration. This artificial condition can lead the computation to be costly when dealing with very shallow flow and wet/dry fronts. The main result of this paper is to propose a new and faster scheme for which only the CFL condition of the shallow water equations is sufficient to preserve the positivity of sediment concentration. In addition, the numerical procedure of the erosion part can be used with any well‐balanced and positivity preserving scheme of the shallow water equations. The proposed method is tested on classical benchmarks and also on a realistic configuration. This article is protected by copyright. All rights reserved.
- Multiporosity flow in fractured low‐permeability rocks
- Authors: Kristopher L. Kuhlman; Bwalya Malama, Jason E. Heath
Pages: n/a - n/a
Abstract: A multiporosity extension of classical double and triple porosity fractured rock flow models for slightly compressible fluids is presented. The multiporosity model is an adaptation of the multirate solute transport model of Haggerty and Gorelick  to viscous flow in fractured rock reservoirs. It is a generalization of both pseudo‐steady‐state and transient interporosity flow double porosity models. The model includes a fracture continuum and an overlapping distribution of multiple rock matrix continua, whose fracture‐matrix exchange coefficients are specified through a discrete probability mass function. Semi‐analytical cylindrically symmetric solutions to the multiporosity mathematical model are developed using the Laplace transform to illustrate its behavior. The multiporosity model presented here is conceptually simple, yet flexible enough to simulate common conceptualizations of double and triple porosity flow. This combination of generality and simplicity makes the multiporosity model a good choice for flow in low‐permeability fractured rocks. This article is protected by copyright. All rights reserved.
- A data‐driven approach to develop physically sound predictors:
Application to depth‐averaged velocities on flows through submerged
arrays of rigid cylinders
- Authors: R. O. Tinoco; E. B. Goldstein, G. Coco
Pages: n/a - n/a
Abstract: We use a machine learning approach to seek an accurate, physically sound predictor, to estimate the mean velocity for open‐channel flow when submerged arrays of rigid cylinders (model vegetation) are present. A genetic programming routine is used to find a robust relationship between relevant properties of the model vegetation and flow parameters. We use published data from laboratory experiments covering a broad range of conditions to obtain an equation that matches the performance of other predictors from recent literature in terms of accuracy, while showing a less complex structure. We also investigate how different criteria for data selection, as well as the size of the data set used to train the algorithm, influences the accuracy of the resulting predictors. Our results show that a proper use of Machine‐Learning techniques does not only provide empirical correlations, but can yield physically sound models as representative of the physical processes involved. We provide a clear, thorough example of the application of GP, its advantages and shortcomings, to encourage the use of data‐driven techniques as part of the data analysis process, and to address common misconceptions of machine learning as simple correlation techniques or physically senseless statistical analysis. This article is protected by copyright. All rights reserved.
- Comment on “Objective extraction of channel heads from
high‐resolution topographic data” by F. J. Clubb, S. M. Mudd,
D. T. Milodowski, M. D. Hurst, and L. J. Slater
- Authors: Paola Passalacqua; Efi Foufoula‐Georgiou
Pages: n/a - n/a
- Reply to comment by P. Passalacqua and E. Foufoula‐Georgiou on
“Objective extraction of channel heads from high‐resolution
- Authors: Fiona Clubb; Simon Mudd, David Milodowski
Pages: n/a - n/a
- Water and entrapped air redistribution in heterogeneous sand sample:
Quantitative neutron imaging of the process
- Authors: Michal Snehota; Vladimira Jelinkova, Martina Sobotkova, Jan Sacha, Peter Vontobel, Jan Hovind
Pages: n/a - n/a
Abstract: Saturated flow in soil with the occurrence of preferential flow often exhibits temporal changes of saturated hydraulic conductivity even during the time scale of a single infiltration event. These effects, observed in a number of experiments done mainly on heterogeneous soils, are often attributed to the changing distribution of water and air in the sample. We have measured the variation of the flow rates during the steady state stage of the constant head ponded infiltration experiment conducted on a packed sample composed of three different grades of sand. The experiment was monitored by quantitative neutron imaging, which provided information about the spatial distribution of water in the sample. Measurements were taken during i) the initial stages of infiltration by neutron radiography and ii) during the steady state flow by neutron tomography. A gradual decrease of the hydraulic conductivity has been observed during the first four hours of the infiltration event.
A series of neutron tomography images taken during the quasi‐steady state stage showed the trapping of air bubbles in coarser sand. Furthermore, the water content in the coarse sand decreased even more while the water content in the embedded fine sand blocks gradually increased. The experimental results support the hypothesis that the effect of the gradual hydraulic conductivity decrease is caused by entrapped air redistribution and the build‐up of bubbles in preferential pathways. The trapped air thus restricts the preferential flow pathways and causes lower hydraulic conductivity. This article is protected by copyright. All rights reserved.
- Hydrophobic organic contaminant transport property heterogeneity in the
- Authors: Richelle M. Allen‐King; Indra Kalinovich, David F. Dominic, Guohui Wang, Reid Polmanteer, Dana Divine
Pages: n/a - n/a
Abstract: We determined that the spatial heterogeneity in aquifer properties governing the reactive transport of volatile organic contaminants is defined by the arrangement of lithofacies. We measured permeability (k) and perchloroethene sorption distribution coefficient (Kd) for lithofacies that we delineated for samples from the Canadian Forces Base Borden Aquifer. We compiled existing data and collected 57 new cores to characterize a 30 m section of the aquifer near the test location of Mackay et al. . The k and Kd were measured for samples taken at six elevations from all cores to create a data set consisting of nearly 400 co‐located measurements. Through analysis of variance (corrected for multiple comparisons), we determined that the twelve originally mapped lithofacies could be grouped into five relatively distinct chemohydrofacies that capture the variability of both transport properties. The mean of ln k by lithofacies was related to the grain size and the variance was relatively consistent. In contrast, both the mean and variance of ln Kd were greater for more poorly sorted lithofacies, which were also typically more coarse‐grained. Half of the aquifer sorption capacity occurred in the three highest‐sorbing lithofacies but comprised only 20% of its volume. The model of the aquifer that emerged is that of discontinuous scour‐fill deposits of medium sand, generally characterized by greater Kd and k, within laterally extensive fine‐ to very‐fine grained sands of lower Kd and k. Our findings demonstrate the importance of considering source rock composition, transport and deposition processes when constructing conceptual models of chemohydrofacies. This article is protected by copyright. All rights reserved.
- Efficient Bayesian experimental design for contaminant source
- Authors: Jiangjiang Zhang; Lingzao Zeng, Cheng Chen, Dingjiang Chen, Laosheng Wu
Pages: n/a - n/a
Abstract: In this study, an efficient full Bayesian approach is developed for the optimal sampling well location design and source parameters identification of groundwater contaminants. An information measure, i.e., the relative entropy, is employed to quantify the information gain from concentration measurements in identifying unknown parameters. In this approach, the sampling locations that give the maximum expected relative entropy are selected as the optimal design. After the sampling locations are determined, a Bayesian approach based on Markov Chain Monte Carlo (MCMC) is used to estimate unknown parameters. In both the design and estimation, the contaminant transport equation is required to be solved many times to evaluate the likelihood. To reduce the computational burden, an interpolation method based on the adaptive sparse grid is utilized to construct a surrogate for the contaminant transport equation. The approximated likelihood can be evaluated directly from the surrogate, which greatly accelerates the design and estimation process. The accuracy and efficiency of our approach are demonstrated through numerical case studies. It is shown that the methods can be used to assist in both single sampling location and monitoring network design for contaminant source identifications in groundwater. This article is protected by copyright. All rights reserved.
- A physically based surface resistance model for evaporation from bare
- Authors: Chenming Zhang; Ling Li, David Lockington
Pages: n/a - n/a
Abstract: The resistance to vapor transfer across the soil‐air interface, termed surface resistance, plays an important role in determining the evaporation rate from unsaturated bare soils. A physically based analytical model is developed to describe the surface resistance under varying liquid water saturation. When the vaporization plane remains in the topmost soil layer (TSL), the model considers the vapor transport through the external diffusive layer (EDL), and the hydraulic connection between the capillary water in the TSL and underneath water source for evaporation. When the vaporization plane develops below the TSL, the model predicts the surface resistance by taking into account the development of the dry soil layer, the major barrier for vapor transport at the this soil‐drying stage. With the consideration of the soil pore size distribution, the model is applicable to different soil types. The model was validated against six sets of laboratory experiments on the drying process of initially water‐saturated soil columns under non‐isothermal conditions. These experiments were conducted using different soil types and/or heat intensities above the soil surface. The model was found to perform well over intermediate and low liquid water saturation ranges while underestimating the surface resistance for the high liquid water saturation range. The results suggest that the model overall represents reasonably well the processes underlying the vapor transfer across the soil‐air interface. Future model improvement may be gained by considering the hydraulic connection between the capillary water and film water in the TSL. This article is protected by copyright. All rights reserved.
- Predicting DNAPL mass discharge and contaminated site longevity
probabilities—Conceptual model and high‐resolution stochastic
- Authors: J Koch; W. Nowak
Pages: n/a - n/a
Abstract: Improper storage and disposal of non‐aqueous‐phase liquids (NAPLs) has resulted in widespread contamination of the subsurface, threatening the quality of groundwater as a freshwater resource. The high frequency of contaminated sites and the difficulties of remediation efforts demand rational decisions based on a sound risk assessment. Due to sparse data and natural heterogeneities, this risk assessment needs to be supported by appropriate predictive models with quantified uncertainty. This study proposes a physically and stochastically coherent model concept to simulate and predict crucial impact metrics for DNAPL contaminated sites, such as contaminant mass discharge and DNAPL source longevity. To this end, aquifer parameters and the contaminant source architecture are conceptualized as random space functions. The governing processes are simulated in a three‐dimensional, highly‐resolved, stochastic, and coupled model that can predict probability density functions of mass discharge and source depletion times. While it is not possible to determine whether the presented model framework is sufficiently complex or not, we can investigate whether and to which degree the desired model predictions are sensitive to simplifications often found in the literature. By testing four commonly made simplifications, we identified aquifer heterogeneity, groundwater flow irregularity, uncertain and physically‐based contaminant source zones, and their mutual interlinkages as indispensable components of a sound model framework. This article is protected by copyright. All rights reserved.
- Projected changes in snowfall extremes and interannual variability of
snowfall in the western U.S
- Authors: A. C. Lute; J. T. Abatzoglou, K. C. Hegewisch
Pages: n/a - n/a
Abstract: Projected warming will have significant impacts on snowfall accumulation and melt, with implications for water availability and management in snow‐dominated regions. Changes in snowfall extremes are confounded by projected increases in precipitation extremes. Downscaled climate projections from 20 global climate models were bias corrected to montane Snowpack Telemetry stations across the western United States to assess mid‐21st century changes in the mean and variability of annual snowfall water equivalent (SFE) and extreme snowfall events, defined by the 90th percentile of cumulative 3‐day SFE amounts. Declines in annual SFE and number of snowfall days were projected for all stations. Changes in the magnitude of snowfall event quantiles were sensitive to historical winter temperature. At climatologically cooler locations, such as in the Rocky Mountains, changes in the magnitude of snowfall events mirrored changes in the distribution of precipitation events, with increases in extremes and less change in more moderate events. By contrast, declines in snowfall event magnitudes were found for all quantiles in warmer locations. Common to both warmer and colder sites was a relative increase in the magnitude of snowfall extremes compared to annual SFE and a larger fraction of annual SFE from snowfall extremes. The coefficient of variation of annual SFE increased up to 80% in warmer montane regions due to projected declines in snowfall days and the increased contribution of snowfall extremes to annual SFE. In addition to declines in mean annual SFE, more frequent low snowfall years and less frequent high snowfall years were projected for every station. This article is protected by copyright. All rights reserved.
- Assessment of surface water chloride and conductivity trends in areas of
unconventional oil and gas development—Why existing national data
sets can not tell us what we would like to know
- Authors: Zachary H. Bowen; Gretchen P. Oelsner, Brian S. Cade, Tanya J. Gallegos, Aida M. Farag, David N. Mott, Christopher J. Potter, Peter J. Cinotto, Melanie L. Clark, William M. Kappel, Timothy M. Kresse, Cynthia P. Melcher, Suzanne S. Paschke, David D. Susong, Brian A. Varela
Pages: n/a - n/a
Abstract: Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged but the few studies on this topic are limited in geographic scope. Here, we evaluate the potential utility of national and publicly available water‐quality datasets for addressing questions regarding unconventional oil and gas development. We used existing US Geological Survey and US Environmental Protection Agency datasets to increase understanding of the spatial distribution of unconventional oil and gas development in the US and broadly assess surface‐water quality trends in these areas. Based on sample size limitations we were able to estimate trends in specific conductance (SC) and chloride (Cl‾) from 1970–2010 in 16% (n=155) of the watersheds with unconventional oil and gas resources. We assessed these trends relative to spatiotemporal distributions of hydraulically fractured wells. Results from this limited analysis suggest no consistent and widespread trends in surface‐water quality for SC and Cl‾ in areas with increasing unconventional oil and gas development and highlight limitations of existing national databases for addressing questions regarding unconventional oil and gas development and water quality. This article is protected by copyright. All rights reserved.
- A generalized regression model of arsenic variations in the shallow
groundwater of Bangladesh
- Authors: Mohammad Shamsudduha; Richard G. Taylor, Richard E. Chandler
Pages: n/a - n/a
Abstract: Localized studies of arsenic (As) in Bangladesh have reached disparate conclusions regarding the impact of irrigation‐induced recharge on As concentrations in shallow (≤50 m below ground level) groundwater. We construct generalized regression models (GRMs) to describe observed spatial variations in As concentrations in shallow groundwater both (i) nationally, and (ii) regionally within Holocene deposits where As concentrations in groundwater are generally high (>10 µg L‐1). At these scales, the GRMs reveal statistically significant inverse associations between observed As concentrations and two covariates: (1) hydraulic conductivity of the shallow aquifer and (2) net increase in mean recharge between pre‐developed and developed groundwater‐fed irrigation periods. Further, the GRMs show that the spatial variation of groundwater As concentrations is well explained by not only surface geology but also statistical interactions (i.e., combined effects) between surface geology and mean groundwater recharge, thickness of surficial silt and clay, and well depth. Net increases in recharge result from intensive groundwater abstraction for irrigation, which induces additional recharge where it is enabled by a permeable surface geology. Collectively, these statistical associations indicate that irrigation‐induced recharge serves to flush mobile As from shallow groundwater. This article is protected by copyright. All rights reserved.
- On the upscaling of mass transfer rate expressions for interpretation of
source zone partitioning tracer tests
- Authors: Ali Boroumand; Linda M. Abriola
Pages: n/a - n/a
Abstract: Analysis of partitioning tracer tests conducted in dense nonaqueous phase liquid (DNAPL) source zones relies on conceptual models that describe mass exchange between the DNAPL and aqueous phases. Such analysis, however, is complicated by the complex distribution of entrapped DNAPL mass and formation heterogeneity. Due to parameter uncertainty in heterogeneous regions and the desire to reduce model complexity, the effect of mass transfer limitations is, thus, often neglected, and an equilibrium‐based model is typically used to interpret test results. This work explores the consequences of that simplifying assumption on test data interpretation and develops an alternative upscaled modeling approach to quantify effective mass transfer rates. To this end, a series of partitioning tracer tests is numerically simulated in heterogeneous two‐dimensional PCE‐DNAPL source zones, representative of a range of hydraulic conductivity and DNAPL mass distribution characteristics. The effective mass transfer coefficient corresponding to each test is determined by fitting an upscaled model to the simulated data, and regression analysis is performed to explore the correlation between various source zone metrics and the effective mass transfer coefficient. Results suggest that vertical DNAPL spreading, Reynolds number, pool fraction, and the effective organic phase saturation are the most significant parameters controlling tracer partitioning rates. Finally, a correlation for prediction of the effective (upscaled) mass transfer coefficient is proposed and verified using existing experimental data. The developed upscaled model incorporates the influence of physical heterogeneity on the rate of tracer partitioning and, thus, can be used for the estimation of source zone mass distribution characteristics from tracer test results. This article is protected by copyright. All rights reserved.
- Determining groundwater‐surface water exchange from temperature time
series: Combining a local polynomial method with a maximum likelihood
- Authors: G. Vandersteen; U. Schneidewind, C. Anibas, C. Schmidt, P. Seuntjens, O. Batelaan
Pages: n/a - n/a
Abstract: The use of temperature‐time series measured in streambed sediments as input to coupled water flow and heat transport models has become standard when quantifying vertical groundwater‐surface water exchange fluxes. We develop a novel methodology, called LPML, to estimate the parameters for 1D water flow and heat transport by combining a local polynomial (LP) signal processing technique with a maximum likelihood (ML) estimator. The LP method is used to estimate the frequency response functions (FRFs) and their uncertainties between the streambed top and several locations within the streambed from measured temperature‐time series data. Additionally, we obtain the analytical expression of the FRFs assuming a pure sinusoidal input. The estimated and analytical FRFs are used in an ML estimator to deduce vertical groundwater‐surface water exchange flux and its uncertainty as well as information regarding model quality. The LPML method is tested and verified with the heat transport models STRIVE and VFLUX. We demonstrate that the LPML method can correctly reproduce a priori known fluxes and thermal conductivities and also show that the LPML method can estimate averaged and time‐variable fluxes from periodic and non‐periodic temperature records. The LPML method allows for a fast computation of exchange fluxes as well as model and parameter uncertainties from many temperature sensors. Moreover, it can utilize a broad frequency spectrum beyond the diel signal commonly used for flux calculations. This article is protected by copyright. All rights reserved.
- Drivers of atmospheric nitrate processing and export in forested
- Authors: Lucy A. Rose; Stephen D. Sebestyen, Emily M. Elliott, Keisuke Koba
Pages: n/a - n/a
Abstract: Increased deposition of reactive atmospheric N has resulted in the nitrogen saturation of many forested catchments worldwide. Isotope‐based studies from multiple forest sites report low proportions (mean = ~10%) of unprocessed atmospheric nitrate in streams during baseflow, regardless of N deposition or nitrate export rates. Given similar proportions of atmospheric nitrate in baseflow across a variety of sites and forest types, it is important to address the post‐depositional drivers and processes that affect atmospheric nitrate transport and fate within catchments. In a meta‐analysis of stable isotope‐based studies, we examined the influence of methodological, biological, and hydrologic drivers on the export of atmospheric nitrate from forests. The δ18O‐NO3‐ values in stream waters may increase, decrease, or not change with increasing discharge during stormflow conditions, and δ18O‐NO3‐ values are generally higher in stormflow than baseflow. However, δ18O‐NO3‐ values tended to increase with increasing baseflow discharge at all sites examined. To explain these differences, we present a conceptual model of hydrologic flowpath characteristics (e.g., saturation overland flow versus subsurface stormflow) and the influence of topography on landscape‐stream hydrologic connectivity and delivery of unprocessed atmospheric nitrate to streams. Methodological biases resulting from differences in sampling frequency and stable isotope analytical techniques may further influence the perceived degree of unprocessed atmospheric nitrate export. Synthesis of results from numerous isotope‐based studies shows that small proportions of unprocessed atmospheric nitrate are common in baseflow. However, hydrologic, topographic, and methodological factors are important drivers of actual or perceived elevated contributions of unprocessed atmospheric nitrate to streams. This article is protected by copyright. All rights reserved.
- SWOT data assimilation for operational reservoir management on the upper
Niger River Basin
- Authors: S. Munier; A. Polebistki, C. Brown, G. Belaud, D. P. Lettenmaier
Pages: n/a - n/a
Abstract: The future Surface Water and Ocean Topography (SWOT) satellite mission will provide two‐dimensional maps of water elevation for rivers with width greater than 100 m globally. We describe a modeling framework and an automatic control algorithm that prescribe optimal releases from the Selingue dam in the Upper Niger River Basin, with the objective of understanding how SWOT data might be used to the benefit of operational water management. The modeling framework was used in a twin experiment to simulate the “true” system state and an ensemble of corrupted model states. Virtual SWOT observations of reservoir and river levels were assimilated into the model with a repeat cycle of 21 days. The updated state was used to initialize a Model Predictive Control (MPC) algorithm that computed the optimal reservoir release that meets a minimum flow requirement 300 km downstream of the dam. The data assimilation results indicate that the model updates had a positive effect on estimates of both water level and discharge. The “persistence”, which describes the duration of the assimilation effect, was clearly improved (greater than 21 days) by integrating a smoother into the assimilation procedure. We compared performances of the MPC with SWOT data assimilation to an open‐loop MPC simulation. Results show that the data assimilation resulted in substantial improvements in the performances of the Selingue dam management with a greater ability to meet environmental requirements (the number of days the target is missed falls to zero) and a minimum volume of water released from the dam. This article is protected by copyright. All rights reserved.
- A bivariate extension of the Hosking and Wallis
goodness‐of‐fit measure for regional distributions
- Authors: T. R. Kjeldsen; I. Prosdocimi
Pages: n/a - n/a
Abstract: This study presents a bivariate extension of the goodness‐of‐fit measure for regional frequency distributions developed by Hosking and Wallis  for use with the method of L‐moments. Utilising the approximate joint normal distribution of the regional L‐skewness and L‐kurtosis, a graphical representation of the confidence region on the L‐moment diagram can be constructed as an ellipsoid. Candidate distributions can then be accepted where the corresponding theoretical relationship between the L‐skewness and L‐kurtosis intersects the confidence region, and the chosen distribution would be the one that minimises the Mahalanobis distance measure. Based on a set of Monte Carlo simulations it is demonstrated that the new bivariate measure generally selects the true population distribution more frequently than the original method. Results are presented to show that the new measure remains robust when applied to regions where the level of inter‐site correlation is at a level found in real world regions. Finally the method is applied to two different case studies involving annual maximum peak flow data from Italian and British catchments to identify suitable regional frequency distributions. This article is protected by copyright. All rights reserved.
- Integrating multiple scales of hydraulic conductivity measurements in
training image‐based stochastic models
- Authors: K. Mahmud; G. Mariethoz, A. Baker, A. Sharma
Pages: n/a - n/a
Abstract: Hydraulic conductivity is one of the most critical and at the same time one of the most uncertain parameters in many groundwater models. One problem commonly faced is that the data are usually not collected at the same scale as the discretized elements used in a numerical model. Moreover, it is common that different types of hydraulic conductivity measurements, corresponding to different spatial scales, coexist in a studied domain, which have to be integrated simultaneously. Here we address this issue in the context of Image Quilting, one of the recently developed multiple‐point geostatistics methods.
Based on a training image that represents fine‐scale spatial variability, we use the simplified renormalization upscaling method to obtain a series of upscaled training images that correspond to the different scales at which measurements are available. We then apply Image Quilting with such a multi‐scale training image to be able to incorporate simultaneously conditioning data at several spatial scales of heterogeneity. The realizations obtained satisfy the conditioning data exactly across all scales, but it can come at the expense of a small approximation in the representation of the physical scale relationships. In order to mitigate this approximation, we iteratively apply a kriging‐based correction to the finest scale that ensures local conditioning at the coarsest scales. The method is tested on a series of synthetic examples where it gives good results and shows potential for the integration of different measurement methods in real‐case hydrogeological models. This article is protected by copyright. All rights reserved.
- Long‐term oscillations in rainfall extremes in a 268 year daily time
- Authors: Marco Marani; Stefano Zanetti
Pages: n/a - n/a
Abstract: We analyze long‐term fluctuations of rainfall extremes in 268 years of daily observations (Padova, Italy, 1725‐2006), to our knowledge the longest existing instrumental time series of its kind. We identify multidecadal oscillations in extremes estimated by fitting the GEV distribution, with approximate periodicities of about 17‐21 years, 30‐38 years, 49‐68 years, 85‐94 years, and 145‐172 years. The amplitudes of these oscillations far exceed the changes associated with the observed trend in intensity. This finding implies that, even if climatic trends are absent or negligible, rainfall and its extremes exhibit an apparent non‐stationarity if analyzed over time intervals shorter than the longest periodicity in the data (about 170 years for the case analyzed here). These results suggest that, because long‐term periodicities may likely be present elsewhere, in the absence of observational time series with length comparable to such periodicities (possibly exceeding one century), past observations cannot be considered to be representative of future extremes. We also find that observed fluctuations in extreme events in Padova are linked to the North Atlantic Oscillation: increases in the NAO Index are on average associated with an intensification of daily extreme rainfall events. This link with the NAO global pattern is highly suggestive of implications of general relevance: long‐term fluctuations in rainfall extremes connected with large‐scale oscillating atmospheric patterns are likely to be widely present, and undermine the very basic idea of using a single stationary distribution to infer future extremes from past observations. This article is protected by copyright. All rights reserved.
- Quantifying the economic importance of irrigation water reuse in a Chilean
watershed using an integrated agent‐based model
- Authors: R. T. Arnold; Christian Troost, Thomas Berger
Pages: n/a - n/a
Abstract: Irrigation with surface water enables Chilean agricultural producers to generate one of the country's most important economic exports. The Chilean water code established tradable water rights as a mechanism to allocate water amongst farmers and other water‐use sectors. It remains contested whether this mechanism is effective and many authors have raised equity concerns regarding its impact on water users. For example, speculative hoarding of water rights in expectations of their increasing value has been described. This paper demonstrates how farmers can hoard water rights as a risk management strategy for variable water supply, for example due to the cycles of El Niño or as consequence of climate change. While farmers with insufficient water rights can rely on unclaimed water during conditions of normal water availability, drought years over‐proportionally impact on their supply of irrigation water and thereby farm profitability.
This study uses a simulation model that consists of a hydrological balance model component and a multi‐agent farm decision and production component. Both model components are parameterized with empirical data, while uncertain parameters are calibrated. The study demonstrates a thorough quantification of parameter uncertainty, using global sensitivity analysis and multiple behavioral parameter scenarios. This article is protected by copyright. All rights reserved.
- Gas bubble transport and emissions for shallow peat from a northern
peatland: The role of pressure changes and peat structure
- Authors: Xi Chen; Lee Slater
Pages: n/a - n/a
Abstract: Gas bubbles are an important pathway for methane release from peatlands. The mechanisms controlling gas bubble transport and emission in peat remain uncertain. The effects of hydrostatic pressure and peat structure on the dynamics of gas bubbles in shallow peat were therefore tested in laboratory experiments. A peat monolith was retrieved from a raised bog and maintained in a saturated state. Three distinct layers were identified from non‐invasive permittivity measurements supported by soil physical properties (porosity, bulk density). Phase I of the experiment involved monitoring for the accumulation of gas bubbles under steady pressure and temperature conditions. The data showed evidence for gas bubbles being impeded by a shallow semi‐confining layer at depths between 10 and 15 cm. Visible gas bubbles observed on the side of the sample box were recorded over time to estimate changes in the vertical distribution of volumetric gas content. Porosity estimates derived using the Complex Refraction Index Model (CRIM) suggest that gas bubbles enlarge the pore space when the exerted pressure is high enough. Phase II involved triggering release of trapped bubbles by repeatedly increasing and decreasing hydrostatic pressure in an over‐saturated condition. Comparison of changes in pressure head and methane density in the head space confirmed that the increasing buoyancy force during drops in pressure is more important for triggering ebullition than increasing mobility during increases in pressure. Our findings demonstrate the importance of changes in hydrostatic pressure on bubble size and variations in resistance of the peat fabric in regulating methane releases from peatlands. This article is protected by copyright. All rights reserved.
- Irrigation with desalinated water: A step toward increasing water saving
and crop yields
- Authors: Avner Silber; Yair Israeli, Idan Elingold, Menashe Levi, Irit Levkovitch, David Russo, Shmuel Assouline
Pages: n/a - n/a
Abstract: We examined the impact of two different approaches to managing irrigation water salinity: salt leaching from the field (“conventional” management) and water desalination before field application (“alternative” management). Fresh water commonly used for irrigation (FW) and desalinated water (DS) were applied to the high‐water‐demanding crop banana at four different rates.
Both irrigation rate and water salinity significantly affected yield. DS application consistently produced higher yields than FW, independently of irrigation rate. The highest yield for FW irrigation was achieved with the highest irrigation rate, whereas the same yield was obtained in the case of DS irrigation with practically half the amount of water. Yield decreased with FW irrigation, even when the water salinity, ECi, was lower than the limit considered safe for soil and crops
Irrigating with FW provided a massive amount of salt which accumulated in the rhizosphere, inducing increased osmotic potential of the soil solution and impairing plant water uptake. Furthermore, applying the “conventional” management, a significant amount of salt is leached from the rhizosphere, accumulating in deeper soil layers, and eventually reaching groundwater reservoirs, thus contributing to the deterioration of both soil and water quality. Removal of salt excess from the water before it reaches the field by means of DS irrigation may save significant amounts of irrigation water by reducing the salt leaching requirements while increasing yield and improving fruit quality, and decreasing salt load in the groundwater. This article is protected by copyright. All rights reserved.
- Regional flood frequency analysis at the global scale
- Authors: Andrew Smith; Christopher Sampson, Paul Bates
Pages: n/a - n/a
Abstract: The characterisation of flood behaviour in data poor regions has been receiving considerable attention in recent years. In this context, we present the results of regional flood frequency analyses (RFFA) conducted using a global database of discharge data. A hybrid‐clustering approach is used in conjunction with a flood‐index methodology to provide a regionalised discharge estimates with global coverage. The procedures are implemented with varying complexity, with results indicating that catchment area and average annual rainfall explain the bulk of variability in flood frequency; a split‐sample validation procedure revealed median errors in the estimation of the 100 year flood to be around 56%. However, far larger errors were also found, with performance varying between climate regions and estimation of the index‐flood found to be the dominant source of uncertainty. Moreover, the RFFA procedure is utilised to provide insights on the statistical characteristics of floods across different climates and catchments. This article is protected by copyright. All rights reserved.
- Application of nonequilibrium fracture matrix model in simulating reactive
contaminant transport through fractured porous media
- Authors: Nitin Joshi; C.S.P. Ojha, P.K. Sharma, Chandra A. Madramootoo
Pages: n/a - n/a
Abstract: Non‐equilibrium and non‐linear sorption of the contaminants in the fractured porous media could significantly influence the shape of the breakthrough curve (BTC). For the fracture‐matrix system there are very few studies which consider these processes. In this study, the non‐equilibrium fracture‐matrix model with two different non‐linear sorption isotherms, namely non‐linear Freundlich and Langmuir sorption isotherms were developed. The effect of sorption non‐linearity and non equilibrium conditions on the shape of the BTC was studied using the temporal moments. The developed models along with the linear equilibrium, linear non‐equilibrium fracture matrix models and the multi rate mass transfer model were used to simulate the BTC, which were compared with the experimental data available in the literature. Both sorption non‐equilibrium and non‐linearity were found to significantly influence the shape of the BTC. Presence of sorption non‐linearity reduces the solute spreading, whereas presence of non‐equilibrium conditions increases the solute spreading. Considering the sorption non‐equilibrium along with the sorption non‐linearity leads to an improved simulation of the BTC. The non‐equilibrium non‐linear sorption models could simulate the extended BTC tailing resulting from sorption non‐linearity and rate limited interaction in the fracture‐matrix system. This article is protected by copyright. All rights reserved.
- Supply based dynamic Ramsey pricing: Avoiding water shortages
- Authors: Yiğit Sağlam
Pages: n/a - n/a
Abstract: In many countries, current water‐pricing policies are dictated by the sole objective of financial breaking‐even. This results in large withdrawals, which are not sustainable in the long‐run, hence not optimal. In this paper, we derive the optimal dynamic pricing policy, which targets efficient distribution while breaking‐even through a rebate scheme. Using data from Turkey, we estimate the demand for water by user groups. We carry out simulations to compare the effects of the current and optimal pricing policies on the frequency and severity of shortages. We find that, under the policy of break‐even prices, the supplier runs into a shortage every eight years. In contrast, if the prices were to set optimally, shortages would be practically nonexistent over the next century. This article is protected by copyright. All rights reserved.
- Hydroclimatic variables and acute gastro‐intestinal illness in
British Columbia, Canada: A time series analysis
- Authors: L.P. Galway; D.M. Allen, M.W. Parkes, L. Li, T.K. Takaro
Pages: n/a - n/a
Abstract: Using epidemiologic time‐series analysis, we examine associations between three hydroclimatic variables (temperature, precipitation, and streamflow) and waterborne acute gastro‐intestinal illness (AGI) in two communities in the province of British Columbia (BC), Canada. The communities were selected to represent the major hydroclimatic regimes that characterize BC: rainfall‐dominated and snowmelt‐dominated. Our results show that the number of monthly cases of AGI increased with increasing temperature, precipitation, and streamflow in the same month in the context of a rainfall‐dominated regime, and with increasing streamflow in the previous month in the context of a snowfall‐dominated regime. These results suggest that hydroclimatology plays a role in driving the occurrence and variability of AGI in these settings. Further, this study highlights that the nature and magnitude of the effects of hydroclimatic variability on AGI are different in the context of a snowfall‐dominated regime versus a rainfall‐dominated regimes. We conclude by proposing that the watershed may be an appropriate context for enhancing our understanding of the complex linkages between hydroclimatic variability and waterborne illness in the context of a changing climate. This article is protected by copyright. All rights reserved.
- Predicting hydrofacies and hydraulic conductivity from direct‐push
data using a data‐driven relevance vector machine approach:
Motivations, algorithms, and application
- Authors: Daniel Paradis; René Lefebvre, Erwan Gloaguen, Alfonso Rivera
Pages: n/a - n/a
Abstract: The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a non‐parametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12‐km2 sub‐watershed, where relations between K and multi‐parameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training dataset representative of the study area that includes K data from slug tests and CPT/SMR data up‐scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross‐validation with data withheld from the training dataset and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM‐based learning machine proved to be powerful and efficient for the characterization of high‐resolution K heterogeneity for unconsolidated aquifers. This article is protected by copyright. All rights reserved.
- Helical Flow in Three‐Dimensional Non‐Stationary Anisotropic
Heterogeneous Porous Media
- Authors: Gabriele Chiogna; Olaf A. Cirpka, Massimo Rolle, Alberto Bellin
Pages: n/a - n/a
Abstract: Characterizing the topology of three‐dimensional steady‐state flow fields is useful to describe the physical processes controlling the deformation of solute plumes and, consequently, obtain helpful information on mixing processes without solving the transport equation. In this work, we study the topology of flow in three‐dimensional non‐stationary anisotropic heterogeneous porous media. In particular, we apply a topological metric, i.e., the helicity density, and two complementary kinematic descriptors of mixing, i.e., stretching and folding, to investigate: i) the flow field resulting from applying a uniform‐in‐the‐average hydraulic gradient within a fully‐resolved heterogeneous three‐dimensional porous medium with a non‐stationary anisotropic covariance function of the locally isotropic hydraulic log‐conductivity; ii) the flow field obtained by averaging a set of Monte Carlo realizations of the former field; iii) the flow field obtained considering the blockwise uniform anisotropic effective conductivity tensor computed for the fully‐resolved case. While in the fully‐resolved case the local helicity density is zero as a consequence of the local isotropy of hydraulic conductivity, it differs from zero in the other two cases. We show, therefore, that this topological metric is scale dependent and should be computed at the appropriate scale to be informative about the leading patterns of plume deformation. Indeed, streamlines are helical in all three cases at scales larger than the characteristic scale of spatial variability. We apply stretching and folding metrics to investigate the scales at which plume deformation is more influenced by helical motion than by the effect of small scale spatial heterogeneity in the hydraulic conductivity field. Under steady‐state flow conditions, stretching, which quantifies the increasing length of an interface, dominates at short distances from a given starting plane, while folding, which describes how this interface is bent to fill a finite volume of space, dominates further downstream and can be correlated with the appearance of large scale secondary motion. We conclude that three‐dimensional flows in porous media may show a complex topology whose analysis is relevant for the description of plume deformation. These results have important implications for the understanding of mixing processes, as shown in detail in the companion paper focusing on solute transport [Cirpka et al., submitted]. This article is protected by copyright. All rights reserved.
- Electrical permittivity and resistivity time‐lapses of
multi‐phase DNAPLs in a lab test
- Authors: Luciana Orlando; Beatrice Renzi
Pages: n/a - n/a
Abstract: Dense Non‐Aqueous Phase Liquids (DNAPLs) induce variation in electromagnetic characteristics of the ground e.g. electric permittivity and resistivity. The most used indirect methods in the mapping of these physical characteristics are electrical resistivity and ground penetrating radar. To better understand the effect of DNAPL release on electrical permittivity and resistivity in a water saturated medium, we carried out a controlled laboratory experiment where the host material was simulated by glass beads and the DNAPL by HFE‐7100 (hydrofluoroether). The experiment measured the electric resistivity and permittivity of each fluid, the multi‐phase fluid system, and the host material, along with time‐lapse electrical resistivity and GPR measurements in a controlled cell. We found that the different phases of DNAPL within a saturated medium (free, dissolved and gaseous phase) affect the physical characteristics differently. The reflection pull‐up behind contaminated sediments, which is normally detected by GPR, was mainly inferred from the HFE free phase. The dissolved phase causes small variations in electric permittivity not usually readily detected by GPR measurements. Both the dissolved and free HFE phases induce variation in resistivity. This article is protected by copyright. All rights reserved.
- Upstream water resource management to address downstream pollution
concerns: A policy framework with application to the Nakdong River basin
in South Korea
- Authors: Taeyeon Yoon; Charles Rhodes, Farhed A. Shah
Pages: n/a - n/a
Abstract: An empirical framework for assisting with water quality management is proposed that relies on open‐source hydrologic data. Such data are measured periodically at fixed water stations and commonly available in time‐series form. To fully exploit the data, we suggest that observations from multiple stations should be combined into a single long‐panel data set, and an econometric model developed to estimate upstream management effects on downstream water quality. Selection of the model's functional form and explanatory variables would be informed by rating curves, and idiosyncrasies across and within stations handled in an error term by testing contemporary correlation, serial correlation, and heteroskedasticity. Our proposed approach is illustrated with an application to the Nakdong River Basin in South Korea. Three alternative policies to achieve downstream BOD level targets are evaluated: upstream water treatment, greater dam discharge, and development of a new water source. Upstream water treatment directly cuts off incoming pollutants, thereby presenting the smallest variation in its downstream effects on BOD levels. Treatment is advantageous when reliability of water quality is a primary concern. Dam discharge is a flexible tool, and may be used strategically during a low‐flow season. We consider development of a new water corridor from an extant dam as our third policy option. This turns out to be the most cost‐effective way for securing lower BOD levels in the downstream target city. Even though we consider a relatively simple watershed to illustrate the usefulness of our approach, it can be adapted easily to analyze more complex upstream‐downstream issues. This article is protected by copyright. All rights reserved.
- A general reactive transport modeling framework for simulating and
interpreting groundwater 14C age and δ13C
- Authors: S.U. Salmon; H. Prommer, J. Park, K.T. Meredith, J.V. Turner, J. L. McCallum
Pages: n/a - n/a
Abstract: A reactive transport modeling framework is presented that allows simultaneous assessment of groundwater flow, water quality evolution including δ13C, and 14C activity or “age”. Through application of this framework, simulated 14C activities can be directly compared with measured 14C activities. This bypasses the need for interpretation of a 14C age prior to flow simulation through factoring out processes other than radioactive decay, which typically involves simplifying assumptions regarding spatial and temporal variability in reactions, flow, and mixing. The utility of the approach is demonstrated for an aquifer system with spatially variable carbonate mineral distribution, multiple organic carbon sources, and transient boundary conditions for 14C activity in the recharge water. In this case the simulated 14C age was shown to be relatively insensitive to isotopic fractionation during DOC oxidation and variations in assumed DOC degradation behaviour. We demonstrate that the model allows quantitative testing of hypotheses regarding controls on groundwater age and water quality evolution for all three carbon isotopes. The approach also facilitates incorporation of multiple environmental tracers and combination with parameter optimization techniques. This article is protected by copyright. All rights reserved.
- Grower demand for sensor‐controlled irrigation
- Authors: Erik Lichtenberg; John Majsztrik, Monica Saavoss
Pages: n/a - n/a
Abstract: Water scarcity is likely to increase in the coming years, making improvements in irrigation efficiency increasingly important. An emerging technology that promises to increase irrigation efficiency substantially is a wireless irrigation sensor network that uploads sensor data into irrigation management software, creating an integrated system that allows real‐time monitoring and control of moisture status that has been shown in experimental settings to reduce irrigation costs, lower plant loss rates, shorten production times, decrease pesticide application, and increase yield, quality, and profit. We use an original survey to investigate likely initial acceptance, ceiling adoption rates, and profitability of this new sensor network technology in the nursery and greenhouse industry. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. Adoption rates for a base system and demand for expansion components are increasing in specialization in ornamental production: Growers earning greater shares of revenue from greenhouse and nursery operations are willing to pay more for a base system and are willing to purchase larger numbers of expansion components at any given price. We estimate that growers who are willing to purchase a sensor network expect investment in this technology to generate significant profit, consistent with findings from experimental studies. This article is protected by copyright. All rights reserved.
- Impact of velocity correlation and distribution on transport in fractured
media: Field evidence and theoretical model
- Authors: Peter K. Kang; Tanguy Le Borgne, Marco Dentz, Olivier Bour, Ruben Juanes
Pages: n/a - n/a
Abstract: Flow and transport through fractured geologic media often leads to anomalous (non‐Fickian) transport behavior, the origin of which remains a matter of debate: whether it arises from variability in fracture permeability (velocity distribution), connectedness in the flow paths through fractures (velocity correlation), or interaction between fractures and matrix. Here we show that this uncertainty of distribution‐ vs. correlation‐controlled transport can be resolved by combining convergent and push‐pull tracer tests because flow reversibility is strongly dependent on velocity correlation, whereas late‐time scaling of breakthrough curves is mainly controlled by velocity distribution. We build on this insight, and propose a Lagrangian statistical model that takes the form of a continuous time random walk (CTRW) with correlated particle velocities. In this framework, velocity distribution and velocity correlation are quantified by a Markov process of particle transition times that is characterized by a distribution function and a transition probability. Our transport model accurately captures the anomalous behavior in the breakthrough curves for both push‐pull and convergent flow geometries, with the same set of parameters. Thus, the proposed correlated CTRW modeling approach provides a simple yet powerful framework for characterizing the impact of velocity distribution and correlation on transport in fractured media. This article is protected by copyright. All rights reserved.
- Hydraulic response in flooded stream networks
- Authors: Anna Åkesson; Anders Wörman, Andrea Bottacin‐Busolin
Pages: n/a - n/a
Abstract: Average water travel times through a stream network were determined as a function of stage (discharge) and stream network properties. Contrary to most previous studies on the topic, the present work allowed for stream flow velocities to spatially (for most of the analyses) as well as temporally. The results show that different stream network mechanisms and properties interact in a complex and stage‐dependent manner, implying that the relative importance of the different hydraulic properties varies in space and over time. Theoretical reasoning, based on the central temporal moments derived from the kinematic‐diffusive wave equation in a semi‐2D formulation including the effects of flooded cross‐sections, shows that the hydraulic properties in contrast to the geomorphological properties will become increasingly important as the discharge increases, stressing the importance of accurately describing the hydraulic mechanisms within stream networks. ‘
Using the physically based, stage‐dependent response function as a parameterization basis for the stream flow routing routine (a linear reservoir) of a hydrological model, discharge predictions were shown to improve in two Swedish catchments, compared to when using a conventional, statistically based parameterization scheme. Predictions improved for a wide range of modeled scenarios, for the entire discharge series as well as for peakflow conditions.
The foremost novelty of the study lies in that the physically based response function for a streamflow routing routine has successfully been determined independent of calibration i.e. entirely through process based hydraulic stream network modelling. This article is protected by copyright. All rights reserved.
- The effect of streambed heterogeneity on groundwater‐surface water
exchange fluxes inferred from temperature time series
- Authors: Dylan J. Irvine; Roger H. Cranswick, Craig T. Simmons, Margaret A. Shanafield, Laura K. Lautz
Pages: n/a - n/a
Abstract: One–dimensional analytical heat transport equations based on temperature time series data have become popular tools to quantify groundwater–surface water interactions. The influence of non–ideal field conditions on the use of these equations has been assessed for non–sinusoidal stream temperature signals, uncertainty in thermal parameters, sensor accuracy and multidimensional flow. Given that streambeds are often highly heterogeneous, the influence of streambed heterogeneity on flux estimates from temperature time series requires further investigation. Synthetic streambed temperatures were generated using two–dimensional numerical models with heterogeneous hydraulic conductivity distributions. Streambed temperatures were used to calculate fluxes using methods based on amplitude ratios (Ar), phase shifts (ΔΦ) and both (ArΔΦ). Calculated fluxes were compared to known fluxes from the numerical models for flow fields analogous to losing streams. The influence of streambed structure, degree of heterogeneity, depth of the sensor pair, and location along a flow path were assessed. Errors in calculated fluxes increased with sensor pair depth, position along a flow path, and with the degree of heterogeneity. These errors were larger for streambeds with isotropic structures compared with anisotropic structures, and of the three methods tested; the ΔΦ method produced the largest errors. The simultaneous estimation of strong fluxes using ΔΦ, and an inability to obtain a flux estimate from Ar can suggest the presence of low hydraulic conductivity zones. Given the large errors and inability to determine flow direction from the ΔΦ method, the Ar and ArΔΦ methods are recommended for downwelling fluxes. This article is protected by copyright. All rights reserved.
- Maximum likelihood parameter estimation for fitting bed load rating curves
- Authors: David Gaeuman; Craig R. Holt, Kristin Bunte
Pages: n/a - n/a
Abstract: Fluvial sediment loads are frequently calculated with rating curves fit to measured sediment transport rates. Rating curves are often treated as statistical representations in which the fitted parameters have little or no physical meaning. Such models, however, may produce large errors when extrapolation is needed, and they provide no insight into the sediment transport process. It is shown that log‐linear least squares, the usual method for fitting rating curves, does not generally produce physically meaningful parameter values. In addition, it cannot accommodate data that include zero‐transport samples. Alternative fitting methods based non‐linear least squares and on maximum likelihood parameter estimation are described and evaluated. The maximum likelihood approach is shown to fit synthetic data better than linear or non‐linear least squares, and to perform well with data that include zero‐transport samples. In contrast, non‐linear least squares methods produce large errors in the parameter estimates when zero‐transport samples are present or when the variance structure of the data is incorrectly specified. Analyses with fractional bedload data from a mountain stream suggest that bedload transport rates are gamma distributed, that the arrivals of bedload particles in a sampler conform to a Poisson distribution, and that the variance of non‐zero samples can be expressed as a power function of the mean. Preliminary physical interpretations of variations in the rating curve parameters fit to fractional bedload data with the maximum likelihood method are proposed, and their relation to some previous interpretations of rating curve parameters are briefly discussed. This article is protected by copyright. All rights reserved.
- Comparison of fluvial suspended‐sediment concentrations and
particle‐size distributions measured with in‐stream laser
diffraction and in physical samples
- Authors: Jonathan A. Czuba; Timothy D. Straub, Christopher A. Curran, Mark N. Landers, Marian M. Domanski
Pages: n/a - n/a
Abstract: Laser‐diffraction technology, recently adapted for in‐stream measurement of fluvial suspended‐sediment concentrations (SSCs) and particle‐size distributions (PSDs), was tested with a streamlined (SL), isokinetic version of the Laser In‐Situ Scattering and Transmissometry (LISST) for measuring volumetric SSCs and PSDs ranging from 1.8‐415 µm in 32 log‐spaced size classes. Measured SSCs and PSDs from the LISST‐SL were compared to a suite of 22 datasets (262 samples in all) of concurrent suspended‐sediment and streamflow measurements using a physical sampler and acoustic Doppler current profiler collected during 2010‐12 at 16 U.S. Geological Survey streamflow‐gaging stations in Illinois and Washington (basin areas: 38 – 69,264 km2). An unrealistically low computed effective density (mass SSC / volumetric SSC) of 1.24 g/ml (95% confidence interval: 1.05‐1.45 g/ml) provided the best‐fit value (R2 = 0.95; RMSE = 143 mg/L) for converting volumetric SSC to mass SSC for over 2 orders of magnitude of SSC (12‐2,170 mg/L; covering a substantial range of SSC that can be measured by the LISST‐SL) despite being substantially lower than the sediment particle density of 2.67 g/ml (range: 2.56‐2.87 g/ml, 23 samples). The PSDs measured by the LISST‐SL were in good agreement with those derived from physical samples over the LISST‐SL's measureable size range. Technical and operational limitations of the LISST‐SL are provided to facilitate the collection of more accurate data in the future. Additionally, the spatial and temporal variability of SSC and PSD measured by the LISST‐SL is briefly described to motivate its potential for advancing our understanding of suspended‐sediment transport by rivers. This article is protected by copyright. All rights reserved.
- The quantity and quality of information in hydrologic models
- Authors: Grey S. Nearing; Hoshin V. Gupta
Pages: n/a - n/a
Abstract: The role of models in science is to facilitate predictions from hypotheses. Although the idea that models provide information is widely reported and has been used as the basis for model evaluation, benchmarking and updating strategies, this intuition has not been formally developed and current benchmarking strategies remain ad hoc at a fundamental level. Here we interpret what it means to say that a model provides information in the context of the formal inductive philosophy of science. We show how information theory can be used to measure the amount of information supplied by a model, and derive standard model benchmarking and evaluation activities in this context. We further demonstrate that, via a process of induction, dynamical models store information from hypotheses and observations about the systems that they represent, and that this stored information can be directly measured. This article is protected by copyright. All rights reserved.
- High‐resolution modeling of the spatial heterogeneity of soil
moisture: Applications in network design
- Authors: Nathaniel W. Chaney; Joshua K. Roundy, Julio E. Herrera‐Estrada, Eric F. Wood
Pages: n/a - n/a
Abstract: The spatial heterogeneity of soil moisture remains a persistent challenge in the design of in situ measurement networks, spatial downscaling of coarse estimates (e.g. satellite retrievals), and hydrologic modeling. To address this challenge, we analyze high‐resolution (~9 meters) simulated soil moisture fields over the Little River Experimental Watershed (LREW) in Georgia, USA to assess the role and interaction of the spatial heterogeneity controls of soil moisture. We calibrate and validate the TOPLATS distributed hydrologic model with high to moderate resolution land and meteorological datasets to provide daily soil moisture fields between 2004 and 2008. The results suggest that topography and soils are the main drivers of spatial heterogeneity over the LREW. We use this analysis to introduce a novel network design method that uses land datasets as proxies of the main drivers of local heterogeneity (topography, land cover, and soil properties) to define unique and representative hydrologic similar units (subsurface, surface, and vegetation) for probe placement. The calibration of the hydrologic model and network design method illustrate how the use of hydrologic similar units in hydrologic modeling could minimize computation and guide efforts towards improved macroscale land surface modeling. This article is protected by copyright. All rights reserved.
- Transverse mixing in three‐dimensional nonstationary anisotropic
heterogeneous porous media
- Authors: Olaf A. Cirpka; Gabriele Chiogna, Massimo Rolle, Alberto Bellin
Pages: n/a - n/a
Abstract: Groundwater plumes originating from continuously emitting sources are typically controlled by transverse mixing between the plume and reactants in the ambient solution. In two‐dimensional domains, heterogeneity causes only weak enhancement of transverse mixing in steady‐state flows. In three‐dimensional domains, more complex flow patterns are possible because streamlines can twist. In particular, spatially varying orientation of anisotropy can cause steady‐state groundwater whirls. We analyze steady‐state solute transport in three‐dimensional locally isotropic heterogeneous porous media with block‐wise anisotropic correlation structure, in which the principal directions of anisotropy differ from block to block. For this purpose, we propose a transport scheme that relies on advective transport along streamlines and transverse‐dispersive mass exchange between them based on Voronoi tessellation. We compare flow and transport results obtained for a non‐stationary anisotropic log‐hydraulic conductivity field to an equivalent stationary field with identical mean, variance, and two‐point correlation function disregarding the non‐stationarity. The non‐stationary anisotropic field is affected by mean secondary motion and causes neighboring streamlines to strongly diverge, which can be quantified by the two‐particle semivariogram of lateral advective displacements. An equivalent kinematic descriptor of the flow field is the advective folding of plumes, which is more relevant as precursor of mixing than stretching. The separation of neighboring streamlines enhances transverse mixing when considering local dispersion. We quantify mixing by the flux‐related dilution index, which is substantially larger for the non‐stationary anisotropic conductivity field than for the stationary one. We conclude that non‐stationary anisotropy in the correlation structure has a significant impact on transverse plume deformation and mixing. In natural sediments, contaminant plumes most likely mix more effectively in the transverse directions than predicted by models that neglect the non‐stationarity of anisotropy. This article is protected by copyright. All rights reserved.
- Agricultural virtual water flows within U.S.
- Authors: Qian Dang; Xiaowen Lin, Megan Konar
Pages: n/a - n/a
Abstract: Trade plays an increasingly important role in the global food system, which is projected to be strained by population growth, economic development, and climate change. For this reason, there has been a surge of interest in the water resources embodied in international trade, referred to as ‘global virtual water trade’. In this paper, we present a comprehensive assessment of virtual water flows within the USA, a country with global importance as a major agricultural producer and trade power. This is the first study of domestic virtual water flows based upon intra‐national food transfer empirical data and it provides insight into how the properties of virtual water transfers vary across scales. We find that the volume of virtual water flows within the USA is equivalent to 51\% of international flows, which is slightly higher than the USA food value and mass shares, due to the fact that water‐intensive meat commodities comprise a much larger fraction of food transfers within the USA. The USA virtual water flow network is more social, homogeneous, and equitable than the global virtual water trade network, although it is still not perfectly equitable. Importantly, a core group of U.S. States is central to the network structure, indicating that both domestic and international trade may be vulnerable to disruptive climate or economic shocks in these U.S. States. This article is protected by copyright. All rights reserved.
- Spatiotemporal interpolation of discharge across a river network by using
synthetic SWOT satellite data
- Authors: Rodrigo C. D. Paiva; Michael T. Durand, Faisal Hossain
Pages: n/a - n/a
Abstract: Recent efforts have sought to estimate river discharge and other surface water related quantities using spaceborne sensors, with better spatial coverage but worse temporal sampling as compared with in situ measurements. The Surface Water and Ocean Topography (SWOT) mission will provide river discharge estimates globally from space. However, questions on how to optimally use the spatially distributed but asynchronous satellite observations to generate continuous fields still exist. This paper presents a statistical model (River Kriging‐RK), for estimating discharge time series in a river network in the context of the SWOT mission. RK uses discharge estimates at different locations and times to produce a continuous field using spatiotemporal kriging. A key component of RK is the space‐time river discharge covariance, which was derived analytically from the diffusive wave approximation of Saint‐Venant's equations. The RK covariance also accounts for the loss of correlation at confluences. The model performed well in a case study on Ganges‐Brahmaputra‐Meghna (GBM) River system in Bangladesh using synthetic SWOT observations. The correlation model reproduced empirically‐derived values. RK (R2=0.83) outperformed other kriging‐based methods (R2=0.80), as well as a simple time series linear interpolation (R2=0.72). RK was used to combine discharge from SWOT and in situ observations, improving estimates when the latter is included (R2=0.91). The proposed statistical concepts may eventually provide a feasible framework to estimate continuous discharge time series across a river network based on SWOT data, other altimetry missions and/or in situ data. This article is protected by copyright. All rights reserved.
- A soil moisture accounting procedure with a Richard's equation‐based
soil texture‐dependent parameterization
- Authors: Simon A. Mathias; Todd H. Skaggs, Simon A. Quinn, Sorcha N. C. Egan, Lucy E. Finch, Corinne D. Oldham
Pages: n/a - n/a
Abstract: Given a time‐series of potential evapotranspiration and rainfall data, there are at least two approaches for estimating vertical percolation rates. One approach involves solving Richards' equation (RE) with a plant uptake model. An alternative approach involves applying a simple soil moisture accounting procedure (SMAP) based on a set of conceptual stores and conditional statements. It is often desirable to parameterize distributed vertical percolation models using regional soil texture maps. This can be achieved using pedotransfer functions when applying RE. However, robust soil texture based parameterizations for more simple SMAPs have not previously been available. This article presents a new SMAP designed to emulate the response of a one‐dimensional homogenous RE model. Model parameters for 231 different soil textures are obtained by calibrating the SMAP model to 20 year time‐series from equivalent RE model simulations. The results are then validated by comparing to an additional 13 years of simulated RE model data. The resulting work provides a new simple two parameter (% sand and % silt) SMAP, which provides consistent vertical percolation data as compared to RE based models. Results from the 231 numerical simulations are also found to be qualitatively consistent with intuitive ideas concerning soil texture and soil moisture dynamics. Vertical percolation rates are found to be highest in sandy soils. Sandy soils are found to provide less water for evapotranspiration. Surface runoff is found to be more important in soils with high clay content. This article is protected by copyright. All rights reserved.
- Ecohydrology in semiarid urban ecosystems: Modeling the relationship
between connected impervious area and ecosystem productivity
- Authors: Catherine Shields; Christina Tague
Pages: n/a - n/a
Abstract: In water‐stressed, semi‐arid urban environments, connections between impervious surfaces and drainage networks may strongly impact the water use and ecosystem productivity of neighboring vegetated areas. We use an ecohydrologic model, the Regional Hydro‐Ecological Simulation System (RHESSys), to quantify the sensitivity of vegetation water use and net primary productivity (NPP) to fine‐scale impervious surface connectivity. We develop a set of very fine‐scale (2m2) scenarios that vary both the percentage of impervious surface and fraction of this impervious surface with direct hydrologic connections to urban drainage systems for a small hillslope. When driven by Mediterranean climate forcing, model estimates suggest that total vegetation water use declines with increasing impervious area. However, when impervious area is hydrologically disconnected from the urban drainage network, declines in water and carbon fluxes with decreased vegetated area can be partially, or in some cases even completely, offset by increased transpiration and NPP in the remaining vegetation. Relative increases in water use and NPP of remaining vegetation are much greater for deeply rooted shrubs and trees and negligible for shallow rooted grasses. We extrapolate our findings to the catchment scale by developing a first‐order approximation of fine‐scale impervious connection impacts on aggregate watershed water and carbon flux estimates. Our approach offers a computationally and data‐efficient method for estimating the impact of impervious area connectivity on these ecohydrologic fluxes. For our only partially urbanized Santa Barbara watershed, estimates of water use and NPP that account for fine‐scale impervious connection differed by more than 10% from those that did not. This article is protected by copyright. All rights reserved.
- Bayesian inversion of Mualem‐van Genuchten parameters in a
multilayer soil profile: A data‐driven, assumption‐free
- Authors: Matthew W. Over; Ute Wollschläger, Carlos Andres Osorio‐Murillo, Yoram Rubin
Pages: n/a - n/a
Abstract: This paper introduces a hierarchical simulation and modeling framework that allows for inference and validation of the likelihood function in Bayesian inversion of vadose zone hydraulic properties. The likelihood function or its analogs (objective functions and likelihood measures) are commonly assumed to be multivariate Gaussian in form, however this assumption is not possible to verify without a hierarchical simulation and modeling framework. In this paper, we present the necessary statistical mechanisms for utilizing the hierarchical framework. We apply the hierarchical framework to the inversion of the vadose zone hydraulic properties within a multi‐layer soil profile conditioned on moisture content observations collected in the uppermost four layers. The key result of our work is that the goodness‐of‐fit validated likelihood function form provides empirical justification for the assumption of multivariate Gaussian likelihood functions in past and future inversions at similar sites. As an alternative, the likelihood function needs not be assumed to follow a parametric statistical distribution and can be computed directly using non‐parametric methods. The non‐parametric methods are considerably more computationally demanding and to demonstrate this approach we present a smaller dimension synthetic case study of evaporation from a soil column. The main drawback of our work is the increased computational expense of the inversion. This article is protected by copyright. All rights reserved.
- Tree‐grass competition for soil water in arid and semiarid savannas:
The role of rainfall intermittency
- Authors: Donatella D'Onofrio; Mara Baudena, Fabio D'Andrea, Max Rietkerk, Antonello Provenzale
Pages: n/a - n/a
Abstract: Arid and semiarid savannas are characterized by the coexistence of trees and grasses in water limited conditions. As in all drylands, also in these savannas rainfall is highly intermittent. In this work we develop and use a simple implicit‐space model to conceptually explore how precipitation intermittency influences tree‐grass competition and savanna occurrence. The model explicitly includes soil moisture dynamics, and life‐stage structure of the trees. Assuming that water availability affects the ability of both plant functional types to colonize new space and that grasses outcompete tree seedlings, the model is able to predict the expected sequence of grassland, savanna and forest along a range of mean annual rainfall. In addition, rainfall intermittency allows for tree‐grass coexistence at lower mean annual rainfall values than for constant precipitation. Comparison with observations indicate that the model, albeit very simple, is able to capture some of the essential dynamical processes of natural savannas. The results suggest that precipitation intermittency affects savanna occurrence and structure, indicating a new point of view for reanalyzing observational data from the literature. This article is protected by copyright. All rights reserved.
- Time‐variable transit time distributions and transport: theory and
application to storage‐dependent transport of chloride in a
- Authors: Ciaran J. Harman
Pages: n/a - n/a
Abstract: Transport processes and pathways through many hydrodynamic systems vary over time, often driven by variations in total water storage. This paper develops a very general approach to modeling unsteady transport through an arbitrary control volume (such as a watershed) that accounts for temporal variability in the underlying transport dynamics. Controls on the selection of discharge from stored water are encapsulated in probability distributions ΩQ(ST,t) of age‐ranked storage ST (the volume of water in storage ranked from youngest to oldest). This framework is applied to a long‐term record of rainfall and streamflow chloride in a small, humid watershed at Plynlimon, UK. While a time‐invariant gamma distribution for ΩQ produced a good fit to data, the fit was significantly improved when the distribution was allowed to vary with catchment storage. However the variation was inverse to that of a ‘well‐mixed’ system where storage has a pure dilution effect. Discharge at high storage was predicted to contain a larger fraction of recent event water than at low storage. The effective volume of storage involved in transport was 3411 mm at mean catchment wetness, but declined by 71 millimeters per 1 mm of additional catchment storage, while the fraction of event water in discharge increased by 1.4%. This ‘inverse storage effect’ is sufficient to reproduce the observed long‐memory 1/f fractal spectral structure of stream chloride. Metrics quantifying the strength and direction of storage effects are proposed as useful signatures, and point toward a unified framework for observing and modeling coupled watershed flow and transport. This article is protected by copyright. All rights reserved.
- Robust Stochastic Optimization for Reservoir Operation
- Authors: Limeng Pan; Mashor Housh, Pan Liu, Ximing Cai, Xin Chen
Pages: n/a - n/a
Abstract: Optimal reservoir operation under uncertainty is a challenging engineering problem. Application of classic stochastic optimization methods to large‐scale problems is limited due to computational difficulty. Moreover, classic stochastic methods assume that the estimated distribution function or the sample inflow data accurately represents the true probability distribution, which may be invalid and the performance of the algorithms may be undermined. In this study, we introduce a Robust Optimization (RO) approach, Iterative Linear Decision Rule (ILDR), so as to provide a tractable approximation for a multi‐period hydropower generation problem. The proposed approach extends the existing LDR method by accommodating nonlinear objective functions. It also provides users with the flexibility of choosing the accuracy of ILDR approximations by assigning a desired number of piecewise linear segments to each uncertainty. The performance of the ILDR is compared with benchmark policies including the Sampling Stochastic Dynamic Programming (SSDP) policy derived from historical data. The ILDR solves both the single and multi‐reservoir systems efficiently. The single reservoir case study results show that the RO method is as good as SSDP when implemented on the original historical inflows and it outperforms SSDP policy when tested on generated inflows with the same mean and covariance matrix as those in history. For the multi‐reservoir case study, which considers water supply in addition to power generation, numerical results show that the proposed approach performs as well as in the single reservoir case study in terms of optimal value and distributional robustness. This article is protected by copyright. All rights reserved.
- Valuing recreational fishing quality at rivers and streams
- Authors: Richard T. Melstrom; Frank Lupi, Peter C. Esselman, R. Jan Stevenson
Pages: n/a - n/a
Abstract: This paper describes an economic model that links the demand for recreational stream fishing to fish biomass. Useful measures of fishing quality are often difficult to obtain. In the past, economists have linked the demand for fishing sites to species presence‐absence indicators or average self‐reported catch rates. The demand model presented here takes advantage of a unique dataset of statewide biomass estimates for several popular game fish species in Michigan, including trout, bass and walleye. These data are combined with fishing trip information from a 2008‐2010 survey of Michigan anglers in order to estimate a demand model. Fishing sites are defined by hydrologic unit boundaries and information on fish assemblages so that each site corresponds to the area of a small sub‐watershed, about 100‐200 square miles in size. The random utility model choice set includes nearly all fishable streams in the state. The results indicate a significant relationship between the site choice behavior of anglers and the biomass of certain species. Anglers are more likely to visit streams in watersheds high in fish abundance, particularly for brook trout and walleye. The paper includes estimates of the economic value of several quality change and site loss scenarios. This article is protected by copyright. All rights reserved.
- Are we unnecessarily constraining the agility of complex
- Authors: Pablo A. Mendoza; Martyn P. Clark, Michael Barlage, Balaji Rajagopalan, Luis Samaniego, Gab Abramowitz, Hoshin Gupta
Pages: n/a - n/a
Abstract: In this commentary we suggest that hydrologists and land‐surface modelers may be unnecessarily constraining the behavioral agility of very complex physics‐based models. We argue that the relatively poor performance of such models can occur due to restrictions on their ability to refine their portrayal of physical processes, in part because of strong a‐priori constraints in: (i) the representation of spatial variability and hydrologic connectivity, (ii) the choice of model parameterizations, and (iii) the choice of model parameter values. We provide a specific example of problems associated with strong a‐priori constraints on parameters in a land surface model. Moving forward, we assert that improving hydrological models requires integrating the strengths of the “physics‐based” modeling philosophy (which relies on prior knowledge of hydrologic processes) with the strengths of the “conceptual” modeling philosophy (which relies on data driven inference). Such integration will accelerate progress on methods to define and discriminate among competing modeling options, which should be ideally incorporated in agile modeling frameworks and tested through a diagnostic evaluation approach. This article is protected by copyright. All rights reserved.
- Characterization of water content dynamics and tracer breakthrough by
3‐D electrical resistivity tomography (ERT) under transient
- Authors: Markus Wehrer; Lee D. Slater
Pages: n/a - n/a
Abstract: Characterization of preferential flow and transport is still a major challenge but may be improved employing non‐invasive, tomographic methods. In this study, 3D time lapse electrical resistivity tomography (ERT) was employed during infiltration on an undisturbed, unsaturated soil core in a laboratory lysimeter. A tracer breakthrough was conducted during transient conditions by applying a series of short‐term infiltrations, simulating natural precipitation events. The electrical response was quantitatively validated using data from a multicompartment suction sampler. Water content probes were also installed for ground‐truthing of ERT responses. Water content variations associated with an infiltration front dominated the electrical response observed during individual short term infiltration events, permitting analysis of water content dynamics from ERT data. We found that, instead of the application of an uncertain petrophysical function, shape measures of the electrical conductivity response might be used for constraining hydrological models. Considering tracer breakthroughs, the ERT observed voxel responses from time lapse tomograms at constant water contents in between infiltration events were used to quantitatively characterize the breakthrough curve. Shape parameters of the breakthrough derived from ERT, such as average velocity, were highly correlated with the shape parameters derived from local tracer breakthrough curves observed in the compartments of the suction plate. The study demonstrates that ERT can provide reliable quantitative information on both, tracer breakthroughs and water content variations under the challenging conditions of variable background electrical conductivity of the pore solution and non‐steady‐state infiltration. This article is protected by copyright. All rights reserved.
- Economic costs incurred by households in the 2011 Bangkok flood
- Authors: Orapan Nabangchang; Maura Allaire, Prinyarat Leangcharoen, Rawadee Jarungrattanapong, Dale Whittington
Pages: n/a - n/a
Abstract: This paper presents the first comprehensive estimates of the economic costs experienced by households in the 2011 Bangkok flood. More generally, it contributes to the literature by presenting the first estimates of flood costs based on primary data collected from respondents of flooded homes using in‐person interviews. Two rounds of interviews were conducted with 469 households in three of the most heavily affected districts of greater Bangkok. The estimates of economic costs include preventative costs, ex‐post losses, compensation received, and any new income generated during the flood. Median household economic costs were US$3,089, equivalent to about half of annual household expenditures (mean costs were US$5,261). Perhaps surprisingly given the depth and duration of the flood, most houses incurred little structural damage (although furniture, appliances, and cars were damaged). Median economic costs to poor and non‐poor households were similar as a percentage of annual household expenditures (53% and 48%, respectively). Compensation payments received from government did little to reduce the total economic losses of the vast majority of households. Two flood‐related deaths were reported in our sample – both in low‐income neighborhoods. Overall, ex post damage was the largest component of flood costs (66% of total). These findings are new, important inputs for the evaluation of flood control mitigation and preventive measures that are now under consideration by the Government of Thailand. The paper also illustrates how detailed microeconomic data on household costs can be collected and summarized for policy purposes. This article is protected by copyright. All rights reserved.
- Incorporation of groundwater pumping in a global land surface model with
the representation of human impacts
- Authors: Yadu N. Pokhrel; Sujan Koirala, Pat J.‐F. Yeh, Naota Hanasaki, Laurent Longuevergne, Shinjiro Kanae, Taikan Oki
Pages: n/a - n/a
Abstract: Observations indicate that groundwater levels are declining in many regions around the world. Simulating such depletion of groundwater at the global scale still remains a challenge because most global land surface models (LSMs) lack the physical representation of groundwater dynamics in general and well pumping in particular. Here, we present an integrated hydrologic model, which explicitly simulates groundwater dynamics and pumping within a global LSM that also accounts for human activities such as irrigation and reservoir operation. The model is used to simulate global water fluxes and storages with a particular focus on groundwater withdrawal and depletion in the High Plains Aquifer (HPA) and Central Valley Aquifer (CVA). Simulated global groundwater withdrawal and depletion for the year 2000 are 570 and 330 km3 yr‐1, respectively; the depletion agrees better with observations than our previous model result without groundwater representation, but may still contain certain uncertainties and is on the higher side of other estimates. Groundwater withdrawals from the HPA and CVA are ~22 and ~9 km3 yr‐1 respectively, which are also consistent with the observations of ~24 and ~13 km3 yr‐1. The model simulates a significant decline in total terrestrial water storage in both regions as caused mainly by groundwater storage depletion. Groundwater table declined by ~14 cm yr‐1 in the HPA during 2003‐2010; the rate is even higher (~71 cm yr‐1) in the CVA. These results demonstrate the potential of the developed model to study the dynamic relationship between human water use, groundwater storage, and the entire hydrologic cycle. This article is protected by copyright. All rights reserved.
- Water demand management in times of drought: What matters for water
- Authors: Elena Maggioni
Pages: n/a - n/a
Abstract: Southern California is subject to long droughts and short wet spells. Its water agencies have put in place voluntary, mandatory, and market based conservation strategies since the 1980s. By analyzing water agencies' data between 2005 and 2010, this research studies whether rebates for water efficient fixtures, water rates or water ordinances have been effective, and tests whether structural characteristics of water agencies have affected the policy outcome. It finds that mandates to curb outdoor water uses are correlated with reductions in residential per capita water usage, while prices and subsidies for water saving devices are not. It also confirms that size is a significant policy implementation factor. In a policy perspective, the transition from a water supply to a water demand management oriented strategy appears guided by mandates and by contextual factors such as the economic cycle and the weather, that occur outside the water governance system. Three factors could improve the conservation effort: using prices as a conservation tool, not only as a cost recovering instrument; investing in water efficient tools only when they provide significant water savings; supporting smaller agencies in order to give them opportunities to implement conservation strategies more effectively or to help them consolidate. This article is protected by copyright. All rights reserved.
- A conceptual model of people's vulnerability to floods
- Authors: Luca Milanesi; Marco Pilotti, Roberto Ranzi
Pages: n/a - n/a
Abstract: Hydraulic risk maps provide the baseline for land use and emergency planning. Accordingly, they should convey clear information on the potential physical implications of the different hazards to the stakeholders. This paper presents a vulnerability criterion focused on human stability in a flow specifically devised for rapidly evolving floods where life, before than economic values, might be threatened. The human body is conceptualized as a set of cylinders and its stability to slipping and toppling is assessed by forces and moments equilibrium. Moreover, a depth threshold to consider drowning is assumed. In order to widen its scope of application, the model takes the destabilizing effect of local slope (so far disregarded in the literature) and fluid density into account. The resulting vulnerability classification could be naturally subdivided in three levels (low, medium and high) that are limited by two stability curves for children and adults respectively. In comparison with the most advanced literature conceptual approaches, the proposed model is weakly parameterised and the computed thresholds fit better the available experimental data sets. A code that implements the proposed algorithm is provided. This article is protected by copyright. All rights reserved.
- Relating relative hydraulic and electrical conductivity in the unsaturated
- Authors: Chloe Mawer; Rosemary Knight, Peter K. Kitanidis
Pages: n/a - n/a
Abstract: Numerical modeling was used to generate pore‐scale structures with different structural properties. They were partially saturated according to wetting and drainage regimes using morphological operations for a range of saturations. The hydraulic and electrical conductivities of the resulting partially saturated grain packs were numerically computed to produce relative hydraulic conductivity versus saturation and relative electrical conductivity versus saturation curves. The relative hydraulic conductivities were then compared to the relative electrical conductivities for the same saturations and it was found that relative hydraulic conductivity could be expressed as relative electrical conductivity to a power law exponent, β. This exponent β was not correlated to porosity, specific surface area, or tortuosity. It did change according to whether the soil was wetting or draining. However, a β value of 2.1 reproduced relative hydraulic conductivity from relative electrical conductivity with little added error. The effects of surface conduction on the observed power‐law relationship due to either low fluid electrical conductivity or increased clay content were analyzed. The relationship was found to hold for fluid conductivities typical of groundwater and for clay content of less than 5% if the clays were layered perpendicular to electrical flow. The relationship breaks down for electrical flow parallel to clay layers, which makes the choice of electrode arrangement important in cases where clay may be present. This relationship can be used with secondary pressure or saturation data to characterize a soil's hydraulic conductivity curve. This article is protected by copyright. All rights reserved.
- Quantifying stream thermal regimes at multiple scales: Combining thermal
infrared imagery and stationary stream temperature data in a novel
- Authors: Shane J. Vatland; Robert E. Gresswell, Geoffrey C. Poole
Pages: n/a - n/a
Abstract: Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every ~100 m of stream length) over a large extent of stream (~100 km of stream) during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system (validation RMSEs < 1 °C). Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.
- A method for characterizing desiccation‐induced consolidation and
permeability loss of organic soils
- Authors: Chelsea L. Arnold; Teamrat A. Ghezzehei
Pages: n/a - n/a
Abstract: A new method was developed to measure soil consolidation by capillary suction in organic soils. This method differs from previous methods of measuring soil consolidation in that no external load is utilized and only the forces generated via capillary suction consolidate the soil matrix. This limits the degree of consolidation that can occur, but gives a more realistic ecological perspective on the response of organic soils to desiccation in the field. This new method combines the principles behind a traditional triaxial cell (for measurements of volume change), a pressure plate apparatus, (to facilitate drainage by capillary suction), and the permeameter, (to measure saturated hydraulic conductivity), and allows for simultaneous desaturation of the soil while monitoring desiccation induced volume change in the soil. This method also enables detection of historic limit of dryness. The historic limit of dryness is a novel concept that is unique to soils that have never experienced drying since their formation. It is fundamentally equivalent to the pre‐compression stress of externally loaded soils. This method is particularly important for forecasting structural and hydrologic changes that may occur in soils that were formed in very wet regimes (e.g., wet meadows at the foot of persistent snow packs and permafrost peats) as they respond to a changing climate.
- On consumers’ attitudes and willingness to pay for improved drinking
water quality and infrastructure
- Authors: Eftila Tanellari; Darrell Bosch, Kevin Boyle, Elton Mykerezi
Pages: n/a - n/a
Abstract: This paper examines the determinants of consumers’ willingness to pay for improvement programs for three drinking water issues: water quality, pinhole leaks in home plumbing infrastructure and aging public infrastructure. The research is based on a mail survey of consumers in Northern Virginia and the Maryland suburbs of Washington D.C. The analysis focuses on the relationship between information, risk perceptions and willingness to pay. An alternative specific conditional logit model is used to model consumers’ willingness to pay for improvements. Results indicate that the willingness to pay for any of the programs is negatively affected by the cost of the proposed improvement. Consumers’ risk perceptions, the external information provided in the survey and whether they read the annual report from their water utility affect consumers’ willingness to pay for improvement programs.
- CO2 wettability of seal and reservoir rocks and the implications for
- Authors: Stefan Iglauer; C.H. Pentland, A. Busch
Pages: n/a - n/a
Abstract: We review the literature data published on the topic of CO2 wettability of storage and seal rocks. We first introduce the concept of wettability and explain why it is important in the context of carbon geo‐sequestration (CGS) projects, and review how it is measured. This is done to raise awareness of this parameter in the CGS community, which, as we show later on in this text, may have a dramatic impact on structural and residual trapping of CO2. These two trapping mechanisms would be severely and negatively affected in case of CO2‐wet storage and/or seal rock.
Overall, at the current state‐of‐the‐art, a substantial amount of work has been completed, and we find that:
sandstone and limestone, plus pure minerals such as quartz, calcite, feldspar and mica are strongly water wet in a CO2‐water system.
oil‐wet limestone, oil‐wet quartz or coal is intermediate‐wet or CO2‐wet in a CO2‐water system.
the contact angle alone is insufficient for predicting capillary pressures in reservoir or seal rocks.
the current contact angle data has a large uncertainty.
solid theoretical understanding on a molecular level of rock‐CO2‐brine interactions is currently limited.
in an ideal scenario all seal and storage rocks in CGS formations are tested for their CO2‐wettability.
achieving representative subsurface conditions (especially in terms of the rock surface) in the laboratory is of key importance but also very challenging.