- 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.
- Issue Information
- Pages: i - v
- 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.
- A simple modeling approach to elucidate the main transport processes and
predict invasive spread: River‐mediated invasion of Ageratina
adenophora in China
- Authors: Nir Horvitz; Rui Wang, Min Zhu, Fang‐Hao Wan, Ran Nathan
Pages: n/a - n/a
Abstract: A constantly increasing number of alien species invade novel environments and cause enormous damage to both biodiversity and economics worldwide. This global problem is calling for better understanding of the different mechanisms driving invasive spread, hence quantification of a range of dispersal vectors. Yet, methods for elucidating the mechanisms underlying large‐scale invasive spread from empirical patterns have not yet been developed. Here we propose a new computationally efficient method to quantify the contribution of different dispersal vectors to the spread rate of invasive plants. Using data collected over 30 years regarding the invasive species Ageratina adenophora since its detection at the Sichuan province, we explored its spread by wind and animals, rivers and roads into 153 sub‐counties in the Sichuan, Chongqingshi and Hubei provinces of China. We found that rivers are the most plausible vector for the rapid invasion of this species in the study area. Model explorations revealed robustness to changes in key assumptions and configuration. Future predictions of this ongoing invasion process project that the species will quickly spread along the Yangtze River and colonize large areas within a few years. Further model developments would provide a much needed tool to mechanistically and realistically describe large scale invasive spread, providing insights into the underlying mechanisms and an ability to predict future spatial invasive dynamics. 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.
- Analytical steady state solutions for water‐limited cropping systems
using saline irrigation water
- Authors: T. H. Skaggs; R. G. Anderson, D. L. Corwin, D. L. Suarez
Pages: n/a - n/a
Abstract: Due to the diminishing availability of good quality water for irrigation, it is increasingly important that irrigation and salinity management tools be able to target submaximal crop yields and support the use of marginal quality waters. In this work, we present a steady‐state irrigated systems modeling framework that accounts for reduced plant water uptake due to root zone salinity. Two explicit, closed‐form analytical solutions for the root zone solute concentration profile are obtained, corresponding to two alternative functional forms of the uptake reduction function. The solutions express a general relationship between irrigation water salinity, irrigation rate, crop salt tolerance, crop transpiration, and (using standard approximations) crop yield. Example applications are illustrated, including the calculation of irrigation requirements for obtaining targeted submaximal yields, and the generation of crop‐water production functions for varying irrigation waters, irrigation rates, and crops. Model predictions are shown to be mostly consistent with existing models and available experimental data. Yet the new solutions possess advantages over available alternatives, including: (i) the solutions were derived from a complete physical‐mathematical description of the system, rather than based on an ad hoc formulation; (ii) the analytical solutions are explicit and can be evaluated without iterative techniques; (iii) the solutions permit consideration of two common functional forms of salinity induced reductions in crop water uptake, rather than being tied to one particular representation; and (iv) the utilized modeling framework is compatible with leading transient‐state numerical models. 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.
- Wavelet‐based multiscale performance analysis: An approach to assess
and improve hydrological models
- Authors: Maheswaran Rathinasamy; Rakesh Khosa, Jan Adamowski, Sudheer ch, Partheepan G, Jatin Anand, Boini Narsimlu
Pages: n/a - n/a
Abstract: The temporal dynamics of hydrological processes are spread across different time timescales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multi‐scale analysis, and have been shown to be very reliable and useful in understanding dynamics across timescales and as these evolve in time. In this paper, a wavelet based multi‐scale performance measure for hydrological models is proposed and tested (i.e. Multiscale Nash Sutcliffe Criteria, and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different timescales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the a trous wavelet transform), and performance measures of the model are obtained at each time scale.The applicability of the proposed method was explored using various case studies ‐ both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet‐Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) was used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the choice of the wavelets in multi‐scale model evaluation. It was found that the proposed wavelet based performance measures, namely the MNSC (Multiscale Nash Sutcliffe Criteria) and MNRMSE (Multiscale Normalized Root Mean Square Error), are a more reliable measure than traditional performance measures such as the Nash Sutcliffe Criteria (NSC), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). Further, the proposed methodology can be used to: i) compare different hydrological models (both physical and statistical models), and ii) help in model calibration. This article is protected by copyright. All rights reserved.
- Regional frequency analysis conditioned on large‐scale atmospheric
or oceanic fields
- Authors: Benjamin Renard; Upmanu Lall
Pages: n/a - n/a
Abstract: Many studies report that hydrologic regimes are modulated by large‐scale modes of climate variability such as the El Niño Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO). Climate‐informed frequency analysis models have therefore been proposed to condition the distribution of hydrologic variables on climate indices. However, standard climate indices may be poor predictors in some regions. This paper therefore describes a regional frequency analysis framework that conditions the distribution of hydrologic variables directly on atmospheric or oceanic fields, as opposed to predefined climate indices.
This framework is based on a 2‐level probabilistic model describing both climate and hydrologic data. The climate dataset (predictor) is typically a time series of atmospheric of oceanic fields defined on a grid over some area, while the hydrologic dataset (predictand) is typically a regional dataset of station data (e.g. annual average flow at several gauging stations). A Bayesian estimation framework is used, so that a natural quantification of uncertainties affecting hydrologic predictions is available.
A case study aimed at predicting the number of autumn flood events in 16 catchments located in Mediterranean France using geopotential heights at 500 hPa over the North‐Atlantic region is presented. The temporal variability of hydrologic data is shown to be associated with a particular spatial pattern in the geopotential heights. A cross‐validation experiment indicates that the resulting probabilistic climate‐informed predictions are skillful: their reliability is acceptable and they are much sharper than predictions based on standard climate indices and baseline predictions that ignore climate information. 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.
- Retrieval of river discharge solely from satellite imagery and
at‐many‐stations hydraulic geometry: Sensitivity to river form
and optimization parameters
- Authors: Colin J. Gleason; Laurence C. Smith, Jinny Lee
Pages: n/a - n/a
Abstract: Knowledge of river discharge is critically important for water resource management, climate modeling, and improved understanding of the global water cycle, yet discharge is poorly known in much of the world. Remote sensing holds promise to mitigate this gap, yet current approaches for quantitative retrievals of river discharge require in situ calibration or a priori knowledge of river hydraulics, limiting their utility in unmonitored regions. Recently, Gleason and Smith  demonstrated discharge retrievals within 20‐30% of in situ observations solely from Landsat TM satellite images through discovery of a river‐specific geomorphic scaling phenomenon termed at‐many‐stations hydraulic geometry (AMHG). This paper advances the AMHG discharge retrieval approach via additional parameter optimizations and validation on 34 gauged rivers spanning a diverse range of geomorphic and climatic settings. Sensitivity experiments reveal that discharge retrieval accuracy varies with river morphology, reach averaging procedure, and optimization parameters. Quality of remotely sensed river flow widths is also important. Recommended best practices include a proposed global parameter set for use when a priori information is unavailable. Using this global parameterization, AMHG discharge retrievals are successful for most investigated river morphologies (median RRMSE 33% of in situ gauge observations), except braided rivers (median RRMSE 74%), rivers having low at‐a‐station hydraulic geometry b exponents (reach‐averaged b < 0.1, median RRMSE 86%), and arid rivers having extreme discharge variability (median RRMSE >1000%). Excluding such environments, 26‐41% RRMSE agreement between AMHG discharge retrievals and in‐situ gauge observations suggests AMHG can meaningfully address global discharge knowledge gaps solely from repeat satellite imagery. This article is protected by copyright. All rights reserved.
- An error analysis of the Budyko hypothesis for assessing the contribution
of climate change to runoff
- Authors: Hanbo Yang; Dawen Yang, Qingfang Hu
Pages: n/a - n/a
Abstract: Many previous studies have evaluated the hydrologic response to climate change using the first‐order approximation (first‐order Taylor expansion) of the Mezentsev‐Choudhury‐Yang equation (formulating the Budyko hypothesis), which has a parameter n representing catchment characteristics. However, no studies have paid attention to the error due to the first‐order approximation. This study therefore estimates this error to improve the theoretical framework for assessing the contribution of climate change to runoff based on the Budyko hypothesis. Specifically, the error increases when precipitation (P) decreases and potential evaporation (E0) increases, and n increases. Therefore, increasing P or decreasing E0 lead to an underestimate of the climatic contributions, while a decreasing P or increasing E0 lead to an overestimate. In addition, we suggest a new method to accurately estimate the contribution of climate change to runoff. This article is protected by copyright. All rights reserved.
- Morphodynamics of river‐influenced back‐barrier tidal basins:
The role of landscape and hydrodynamic settings
- Authors: Z. Zhou; G. Coco, M. Jiménez, M. Olabarrieta, M. van der Wegen, I. Townend
Pages: n/a - n/a
Abstract: We investigate the morphodynamics of river‐influenced barrier basins numerically, with a particular emphasis on the effects of landscape and hydrodynamic settings. The simulated morphologies are qualitatively comparable to natural systems (e.g., tidal inlets along the East Coast of the U.S.). Model results suggest that the basin morphology is governed by the relative importance of tidal and fluvial forcing which is reflected, to the first‐order approximation, in the ratio (rQ) between the mean tidal and river discharge. In agreement with empirical knowledge, the model indicates that riverine influence can be neglected when rQ is larger than 20. On the other hand, the river may dominate when rQ is smaller than 5.
Pronounced differences in morphodynamic evolution are observed for different landscape settings (i.e., initial basin bathymetries and river inflow locations), indicating their fundamental importance in governing the evolution of barrier basins. Model results also show that the addition of a river tends to compensate the flood dominance in the tidal basin. Overall, the river flow has limited influence on the volumetric change of tidal flats, while it plays a more important role in determining the depth of the tidal channels and the size of the ebb delta. The riverine sediment source appears to be more important in shaping the basin morphology when the fluvial forcing is stronger. Last, we show that the presence of a large river in a tidal inlet system influences the performance of the widely‐adopted relation between tidal prism and inlet cross‐sectional area. 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.
- The daily mean zero‐flux plane during soil‐controlled
evaporation: A Green's function approach
- Authors: Wilfried Brutsaert
Pages: n/a - n/a
Abstract: A solution is presented of the linearized Richards equation with inclusion of gravity and with appropriate boundary conditions describing the combined soil‐controlled surface evaporation and the downward infiltration, following the application of a given amount of precipitation or irrigation. This solution is shown to agree with available field measurements, namely the evolution with time of the zero‐flux plane depth and of the rate of soil‐controlled evaporation from the bare soil surface. The problem is solved by means of the Green's function method; the result is general enough to be also applicable to flow problems in linear soils with boundary conditions substantially different from the ones considered herein.
- A modified Holly‐Preissmann scheme for simulating sharp
- Authors: Zhao‐wei Liu; De‐jun Zhu, Yong‐can Chen, Zhi‐gang Wang
Pages: n/a - n/a
Abstract: RIV1Q is the stand‐alone water quality program of CE‐QUAL‐RIV1, a hydraulic and water quality model developed by U.S. Army Corps of Engineers Waterways Experiment Station. It utilizes an operator‐splitting algorithm and the advection term in governing equation is treated using the explicit two‐point, fourth‐order accurate, Holly‐Preissmann scheme, in order to preserve numerical accuracy for advection of sharp gradients in concentration. In the scheme, the spatial derivative of the transport equation, where the derivative of velocity is included, is introduced to update the first derivative of dependent variable. In the stream with larger cross sectional variation, steep velocity gradient can be easily found and should be estimated correctly. In the original version of RIV1Q, however, the derivative of velocity is approximated by a finite difference which is first‐order accurate. Its leading truncation error leads to the numerical error of concentration which is related with the velocity and concentration gradients and increases with the decreasing Courant number. The simulation may also be unstable when a sharp velocity drop occurs. In the present paper, the derivative of velocity is estimated with a modified second‐order accurate scheme and the corresponding numerical error of concentration decreases. Additionally, the stability of the simulation is improved. The modified scheme is verified with a hypothetical channel case and the results demonstrate that satisfactory accuracy and stability can be achieved even when the Courant number is very low. Finally, the applicability of the modified scheme is discussed.
- 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.
- Modeling and Mitigating Natural Hazards: Stationarity is Immortal!
- Authors: Alberto Montanari; Demetris Koutsoyiannis
Pages: n/a - n/a
Abstract: Environmental change is a reason of relevant concern as it is occurring at an unprecedented pace and might increase natural hazards. Moreover, it is deemed to imply a reduced representativity of past experience and data on extreme hydroclimatic events. The latter concern has been epitomized by the statement that “stationarity is dead”. Setting up policies for mitigating natural hazards, including those triggered by floods and droughts, is an urgent priority in many countries, which implies practical activities of management, engineering design and construction. These latter necessarily need to be properly informed and therefore the research question on the value of past data is extremely important. We herein argue that there are mechanisms in hydrological systems that are time invariant, which may need to be interpreted through data inference. In particular, hydrological predictions are based on assumptions which should include stationarity, as any hydrological model, including deterministic and non‐stationary approaches, is affected by uncertainty and therefore should include a random component that is stationary. Given that an unnecessary resort to non‐stationarity may imply a reduction of predictive capabilities, a pragmatic approach, based on the exploitation of past experience and data is a necessary prerequisite for setting up mitigation policies for environmental risk.
- Inverse modeling of geochemical and mechanical compaction in sedimentary
basins through Polynomial Chaos Expansion
- Authors: G. Porta; L. Tamellini, V. Lever, M. Riva
Pages: n/a - n/a
Abstract: We present an inverse modeling procedure for the estimation of model parameters of sedimentary basins subject to compaction driven by mechanical and geochemical processes. We consider a sandstone basin whose dynamics are governed by a set of unknown key quantities. These include geophysical and geochemical system attributes as well as pressure and temperature boundary conditions. We derive a reduced (or surrogate) model of the system behavior based on generalized Polynomial Chaos Expansion (gPCE) approximations, which are directly linked to the variance‐based Sobol indices associated with the selected uncertain model parameters. Parameter estimation is then performed within a Maximum Likelihood (ML) framework. We then study the way the ML inversion procedure can benefit from the adoption of anisotropic polynomial approximations (a‐gPCE) in which the surrogate model is refined only with respect to selected parameters according to an analysis of the nonlinearity of the input‐output mapping, as quantified through the Sobol sensitivity indices. Results are illustrated for a one‐dimensional setting involving quartz cementation and mechanical compaction in sandstones. The reliability of gPCE and a‐gPCE approximations in the context of the inverse modeling framework is assessed. The effects of (a) the strategy employed to build the surrogate model, leading either to a gPCE or a‐gPCE representation, and (b) the type and quality of calibration data on the goodness of the parameter estimates is then explored.
- Integration of altimetric lake levels and GRACE gravimetry over Africa:
Inferences for terrestrial water storage change 2003–2011
- Authors: P Moore; S D P Williams
Pages: n/a - n/a
Abstract: Terrestrial water storage (TWS) change for 2003‐2011 is estimated over Africa from GRACE gravimetric data. The signatures from change in water of the major lakes are removed by utilising kernel functions with lake heights recovered from retracked ENVISAT satellite altimetry. In addition, the contribution of gravimetric change due to soil moisture and biomass is removed from the total GRACE signal by utilising the GLDAS land surface model. The residual TWS time series, namely ground water and the surface waters in rivers, wetlands and small lakes, are investigated for trends and the seasonal cycle using linear regression. Typically, such analyses assume the data is temporally uncorrelated but this has been shown to lead to erroneous inferences in related studies concerning the linear rate and acceleration. In this study, we utilise autocorrelation and investigate the appropriate stochastic model. The results show the proper distribution of TWS change and identify the spatial distribution of significant rates and accelerations. The effect of surface water in the major lakes is shown to contribute significantly to the trend and seasonal variation in TWS in the lake basin. Lake Volta, a managed reservoir in Ghana, is seen to have a contribution to the linear trend that is a factor of three greater than that of Lake Victoria despite having a surface area one eighth of that of Lake Victoria. Analysis also shows the confidence levels of the deterministic trend and acceleration identifying areas where the signatures are most likely due to a physical deterministic cause and not simply stochastic variations.
- Sub‐second pore scale displacement processes and relaxation dynamics
in multiphase flow
- Authors: Ryan T. Armstrong; Holger Ott, Apostolos Georgiadis, Alex Schwing, Steffen Berg, Maja Rücker
Pages: n/a - n/a
Abstract: With recent advances at X‐ray micro‐computed tomography (μCT) synchrotron beam lines, it is now possible to study pore‐scale flow in porous rock under dynamic flow conditions. The collection of 4 dimensional data allows for the direct 3D visualization of fluid‐fluid displacement in porous rock as a function of time. However, even state‐of‐the‐art fast‐μCT scans require between one and a few seconds to complete and the much faster fluid movement occurring during that time interval is manifested as imaging artifacts in the reconstructed 3D volume. We present an approach to analyze the 2D radiograph data collected during fast‐μCT to study the pore‐scale displacement dynamics on the time scale of 40 milliseconds which is near the intrinsic time scale of individual Haines jumps. We present a methodology to identify the time intervals at which pore scale displacement events in the observed field of view occur and hence, how reconstruction intervals can be chosen to avoid fluid‐movement induced reconstruction artifacts. We further quantify the size, order, frequency, and location of fluid‐fluid displacement at the millisecond time scale. We observe that after a displacement event, the pore scale fluid distribution relaxes to (quasi‐) equilibrium in cascades of pore‐scale fluid re‐arrangements with an average relaxation time for the whole cascade between 0.5 and 2.0 seconds. These findings help to identify the flow regimes and intrinsic time and length scales relevant to fractional flow. While the focus of the work is in the context of multiphase flow, the approach could be applied to many different μCT applications where morphological changes occur at a time scale less than that required for collecting a μCT scan.
- Improved Bayesian Multi‐modeling: Integration of Copulas and
Bayesian Model Averaging
- Authors: Shahrbanou Madadgar; Hamid Moradkhani
Pages: n/a - n/a
Abstract: Bayesian Model Averaging (BMA) is a popular approach to combine hydrologic forecasts from individual models, and characterize the uncertainty induced by model structure. In the original form of BMA, the conditional probability density function (PDF) of each model is assumed to be a particular probability distribution (e.g. Gaussian, gamma, etc.). If the predictions of any hydrologic model do not follow certain distribution, a data transformation procedure is required prior to model averaging. Moreover, it is strongly recommended to apply BMA on unbiased forecasts, whereas it is sometimes difficult to effectively remove bias from the predictions of complex hydrologic models. To overcome these limitations, we develop an approach to integrate a group of multivariate functions, the so‐called copula functions, into BMA. Here, we introduce a copula‐embedded BMA (Cop‐BMA) method that relaxes any assumption on the shape of conditional PDFs. Copula functions have a flexible structure and do not restrict the shape of posterior distributions. Furthermore, copulas are effective tools in removing bias from hydrologic forecasts. To compare the performance of BMA with Cop‐BMA, they are applied to hydrologic forecasts from different rainfall‐runoff and land‐surface models. We consider the streamflow observation and simulations for ten river basins provided by the Model Parameter Estimation Experiment (MOPEX) project. Results demonstrate that the predictive distributions are more accurate and reliable, less biased, and more confident with small uncertainty after Cop‐BMA application. It is also shown that the post‐processed forecasts have better correlation with observation after Cop‐BMA application.
- A new method for analysis of variance of the hydraulic and reactive
attributes of aquifers as linked to hierarchical and multiscaled
- Authors: Mohamad Reza Soltanian; Robert W. Ritzi
Pages: n/a - n/a
Abstract: This technical note presents a useful methodology for studying how the variance of hydraulic and/or reactive attributes of an aquifer are linked to the multi‐scaled and hierarchical sedimentary architecture of the aquifer. A new recursive equation is derived which quantitatively describes how the variance is related to sedimentary facies defined at all scales across an entire stratal hierarchy. As compared to prior published equations that emphasize differences in means among facies populations within a hierarchical level, it emphasizes differences across levels. Because of the hierarchical relationships among the terms of the equation, we find it to be useful for conducting a holistic analysis of the relative contributions to the variance arising from all facies types defined across all scales. The methodology is demonstrated using appropriate field data, and is shown to be useful in defining parsimonious classification systems.
- Soil water storage, rainfall, and runoff relationships in a tropical dry
- Authors: Kegan K. Farrick; Brian A. Branfireun
Pages: n/a - n/a
Abstract: In forested catchments the exceedance of rainfall and antecedent water storage thresholds is often required for runoff generation, yet to our knowledge these threshold relationships remain undescribed in tropical dry forest catchments. We therefore identified the controls of streamflow activation and the timing and magnitude of runoff in a tropical dry forest catchment near the Pacific coast of central Mexico. During a 52 day transition phase from the dry to wet season, soil water movement was dominated by vertical flow which continued until a threshold soil moisture content of 26% was reached at 100 cm below the surface. This satisfied a 162 mm storage deficit and activated streamflow, likely through lateral subsurface flow pathways. High antecedent soil water conditions were maintained during the wet phase but had a weak influence on stormflow. We identified a threshold value of 289 mm of summed rainfall and antecedent soil water needed to generate >4 mm of stormflow per event. Above this threshold, stormflow response and magnitude was almost entirely governed by rainfall event characteristics and not antecedent soil moisture conditions. Our results show that over the course of the wet season in tropical dry forests the dominant controls on runoff generation changed from antecedent soil water and storage to the depth of rainfall.
- 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.
- Sensitivity of snowpack storage to precipitation and temperature using
spatial and temporal analog models
- Authors: Charles H. Luce; Viviana Lopez‐Burgos, Zachary Holden
Pages: n/a - n/a
Abstract: Empirical sensitivity analyses are important for evaluation of the effects of a changing climate on water resources and ecosystems. Although mechanistic models are commonly applied for evaluation of climate effects for snowmelt, empirical relationships provide a first‐order validation of the various postulates required for their implementation. Previous studies of empirical sensitivity for April 1 snow water equivalent (SWE) in the western United States were developed by regressing interannual variations in SWE to winter precipitation and temperature. This offers a temporal analog for climate change, positing that a warmer future looks like warmer years. Spatial analogs are used to hypothesize that a warmer future may look like warmer places, and are frequently applied alternatives for complex processes, or states/metrics that show little interannual variability (e.g. forest cover). We contrast spatial and temporal analogs for sensitivity of April 1 SWE and the mean residence time of snow (SRT) using data from 524 Snowpack Telemetry (SNOTEL) stations across the western US. We built relatively strong models using spatial analogs to relate temperature and precipitation climatology to snowpack climatology (April 1 SWE, R2=0.87, and SRT, R2=0.81). Although the poorest temporal analog relationships were in areas showing the highest sensitivity to warming, spatial analog models showed consistent performance throughout the range of temperature and precipitation. Generally, slopes from the spatial relationships showed greater thermal sensitivity than the temporal analogs, and high elevation stations showed greater vulnerability using a spatial analog than shown in previous modeling and sensitivity studies. The spatial analog models provide a simple perspective to evaluate potential futures and may be useful in further evaluation of snowpack with warming.
- An integrated modeling framework for exploring flow regime and water
quality changes with increasing biofuel crop production in the US Corn
- Authors: Mary A. Yaeger; Mashor Housh, Ximing Cai, Murugesu Sivapalan
Pages: n/a - n/a
Abstract: To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the co‐evolution of coupled human‐nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern US agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future co‐evolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multi‐scale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future co‐evolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past co‐evolutionary history in predicting future trajectories of change.
- Model selection on solid ground: Rigorous comparison of nine ways to
evaluate Bayesian model evidence
- Authors: Anneli Schöniger; Thomas Wöhling, Luis Samaniego, Wolfgang Nowak
Pages: n/a - n/a
Abstract: Bayesian model selection or averaging objectively ranks a number of plausible, competing conceptual models based on Bayes' theorem. It implicitly performs an optimal tradeoff between performance in fitting available data and minimum model complexity. The procedure requires determining Bayesian model evidence (BME), which is the likelihood of the observed data integrated over each model's parameter space. The computation of this integral is highly challenging because it is as high‐dimensional as the number of model parameters. Three classes of techniques to compute BME are available, each with its own challenges and limitations: 1) Exact and fast analytical solutions are limited by strong assumptions. 2) Numerical evaluation quickly becomes unfeasible for expensive models. 3) Approximations known as information criteria (ICs) such as the AIC, BIC, or KIC (Akaike, Bayesian or Kashyap information criterion, respectively) yield contradicting results with regard to model ranking. Our study features a theory‐based intercomparison of these techniques. We further assess their accuracy in a simplistic synthetic example where for some scenarios an exact analytical solution exists. In more challenging scenarios, we use a brute‐force Monte Carlo integration method as reference. We continue this analysis with a real‐world application of hydrological model selection. This is a first‐time benchmarking of the various methods for BME evaluation against true solutions. Results show that BME values from ICs are often heavily biased and that the choice of approximation method substantially influences the accuracy of model ranking. For reliable model selection, bias‐free numerical methods should be preferred over ICs whenever computationally feasible.
- Functional approach to exploring climatic and landscape controls of runoff
generation: 1. Behavioral constraints on runoff volume
- Authors: Hong‐Yi Li; Murugesu Sivapalan, Fuqiang Tian, Ciaran Harman
Pages: n/a - n/a
Abstract: Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid‐scale responses. It is found, firstly, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage and drainage functions underlying the catchment responses, and in this way provide a quantitative approximation of the conceptual Dunne diagram. Secondly, only a subset of all hypothetical catchment/climate combinations is found to be “behavioral”, in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear inter‐relationships amongst the “behavioral” climate, soil and topography parameter combinations, implying these catchment properties may be constrained to be co‐dependent in order to satisfy the Budyko curve.
- Functional approach to exploring climatic and landscape controls on runoff
generation: 2. Timing of runoff storm response
- Authors: Hong‐Yi Li; Murugesu Sivapalan
Pages: n/a - n/a
Abstract: Hortonian overland flow, Dunne overland flow and subsurface stormflow are the three most dominant mechanisms contributing to both the volume and timing of streamflow in headwater catchments. In this paper, guided by the Dunne diagram, we explore the impacts of climate, soil and topography on estimated probability distributions of the travel times of each of these three runoff components. In each case, these are expressed in terms of the Connected Instantaneous Response Functions (CIRF) and account for the dynamics of their individual partial effective contributing areas that retain the connectivity to the outlet (instead of the whole catchment area). A spatially distributed hydrological model is used to derive the CIRFs numerically under multiple combinations of climate, soil and topographic properties. The mean travel times and dimensionless forms of the CIRFs (i.e., scaled by their respective mean travel times) are used to examine both advective and dispersive aspects of catchment's runoff routing response. It is found that the CIRFs, upon non‐dimensionalization, collapsed to common characteristic shapes, which could be explained in terms of the relative contributions of hillslope and channel network flows, and the size of runoff contributing areas. The contributing areas, particularly for the Dunne overland flow, are themselves found to be governed by the competition between drainage of and recharge to the water table, and could be explained by a dimensionless drainage index which quantifies this competition. The study also reveals simple indicators based on landscape properties that can explain the magnitude of travel times in different catchments.
- Heterogeneity‐Enhanced Gas Phase Formation in Shallow Aquifers
During Leakage of CO2‐Saturated Water from Geologic Sequestration
- Authors: Michael Plampin; Rune Lassen, Toshihiro Sakaki, Mark Porter, Rajesh Pawar, Karsten H. Jensen, Tissa Illangasekare
Pages: n/a - n/a
Abstract: A primary concern for geologic carbon storage is the potential for leakage of stored carbon dioxide (CO2) into the shallow subsurface where it could degrade the quality of groundwater and surface water. In order to predict and mitigate the potentially negative impacts of CO2 leakage, it is important to understand the physical processes that CO2 will undergo as it moves through naturally heterogeneous porous media formations. Previous studies have shown that heterogeneity can enhance the evolution of gas phase CO2 in some cases, but the conditions under which this occurs have not yet been quantitatively defined, nor tested through laboratory experiments. This study quantitatively investigates the effects of geologic heterogeneity on the process of gas phase CO2 evolution in shallow aquifers through an extensive set of experiments conducted in a column that was packed with layers of various test sands. Soil moisture sensors were utilized to observe the formation of gas phase near the porous media interfaces. Results indicate that the conditions under which heterogeneity controls gas phase evolution can be successfully predicted through analysis of simple parameters, including the dissolved CO2 concentration in the flowing water, the distance between the heterogeneity and the leakage location, and some fundamental properties of the porous media. Results also show that interfaces where a less permeable material overlies a more permeable material affect gas phase evolution more significantly than interfaces with the opposite layering.
- Technological change in irrigated agriculture in a semi‐arid region
- Authors: Jean‐Marc Philip; Julio Sánchez‐Chóliz, Cristina Sarasa
Pages: n/a - n/a
Abstract: Technological change plays a decisive role in irrigated agriculture, which is particularly challenging in semi‐arid regions. The main objective of this paper is to assess four kinds of alternative technological improvements aimed at dealing with future water availability, especially in the case of extreme events like drought. We evaluate these technologies for a better understanding of what form should be applied in irrigated agriculture in a context of limits on natural resources.
We develop a dynamic computable general equilibrium (CGE) model, whose production structure distinguishes between rainfed and irrigated crops, and between a variety of irrigated crops. Land use changes are also evaluated. As well as technological change, we consider the Water Framework Directive (EC 2000/60), which establishes water cost recovery as a key goal. Thus, we assess strategies that combine irrigation water pricing strategies and improved technology. Our results show that policy strategies that focus on fostering technical progress can mitigate the long‐term economic effects of downward trends in water supplies, even in drought years. The study also confirms that the absence of price volatility achieved through a water pricing strategy could improve the sustainable use of water.
- Heat and mass transport during a groundwater replenishment trial in a
highly heterogeneous aquifer
- Authors: Simone Seibert; Henning Prommer, Adam Siade, Brett Harris, Mike Trefry, Michael Martin
Pages: n/a - n/a
Abstract: Changes in subsurface temperature distribution resulting from the injection of fluids into aquifers may impact physiochemical and microbial processes as well as basin resource management strategies. We have completed a two year field trial in a hydrogeologically and geochemically heterogeneous aquifer below Perth, Western Australia in which highly treated wastewater was injected for large‐scale groundwater replenishment. During the trial, chloride and temperature data were collected from conventional monitoring wells and by time‐lapse temperature logging. We used a joint inversion of these solute tracer and temperature data to parameterize a numerical flow and multi‐species transport model and to analyze the solute and heat propagation characteristics that prevailed during the trial. The simulation results illustrate that while solute transport is largely confined to the most permeable lithological units, heat transport was also affected by heat exchange with lithological units that have a much lower hydraulic conductivity. Heat transfer by heat conduction was found to significantly influence the complex temporal and spatial temperature distribution, especially with growing radial distance and in aquifer sequences with a heterogeneous hydraulic conductivity distribution. We attempted to estimate spatially varying thermal transport parameters during the data inversion to illustrate the anticipated correlations of these parameters with lithological heterogeneities, but estimates could not be uniquely determined on the basis of the collected data.
- Channeling, channel density and mass recovery in aquifer transport, with
application to the MADE experiment
- Authors: A. Fiori
Pages: n/a - n/a
Abstract: Channeling effects in heterogeneous formations are studied through a new quantity denoted as channel density a (x,t). Focusing on advection only, a (x,t) is defined as the relative number of streamtubes (or channels) containing solute between x and x + dx at a given time t, regardless of the mass that they carry. The channel density generally differs from the widely employed longitudinal mass distribution m(x,t), and their difference increases with time and the degree of heterogeneity. The difference between a and m reflects the nonuniformity of mass distribution relative to the plume geometry. In particular, the “fast” channels typically carry a larger fraction of mass than their share in their relative volume, which in turn can be rather small. Detecting such channels by a network of monitoring wells may be a challenging task, which might explain the poor solute recovery of some field experiments at increasing times. After application of the proposed concepts to the simple case of stratified formations, we model the channel density and mass distribution pertaining to the MADE experiment, which exhibited poor mass recovery at large times. The results presented in this study emphasize the possible channeling effects at MADE and the general difficulty in sampling the leading edge of the plume, which in turn may contain a significant fraction of the plume mass.
- Root zone salinity and sodicity under seasonal rainfall due to feedback of
decreasing hydraulic conductivity
- Authors: S.E.A.T.M. van der Zee; S.H.H. Shah, R.W. Vervoort
Pages: n/a - n/a
Abstract: Soil sodicity, where the soil cation exchange complex is occupied for a significant fraction by Na+, may lead to vulnerability to soil structure deterioration. With a root zone flow and salt transport model, we modeled the feedback effects of salt concentration (C) and exchangeable sodium percentage (ESP) on saturated hydraulic conductivity Ks(C,ESP) for different groundwater depths and climates, using the functional approach of McNeal . We assume that a decrease of Ks is practically irreversible at a time scale of decades. Representing climate with a Poisson rainfall process, the feedback hardly affects salt and sodium accumulation compared with the case that feedback is ignored. However, if salinity decreases, the much more buffered ESP stays at elevated values, while Ks decreases. This situation may develop if rainfall has a seasonal pattern where drought periods with accumulation of salts in the root zone alternate with wet rainfall periods in which salts are leached. Feedback that affects both drainage/leaching and capillary upwards flow from groundwater, or only drainage, leads to opposing effects. If both fluxes are affected by sodicity induced degradation, this leads to reduced salinity (C) and sodicity (ESP), which suggests that the system dynamics and feedback oppose further degradation. Experiences in the field point in the same direction.
- The influence of spatially variable stream hydraulics on reach scale
solute transport modeling
- Authors: Noah M. Schmadel; Bethany T. Neilson, Justin E. Heavilin, David K. Stevens, Anders Wörman
Pages: n/a - n/a
Abstract: Within the context of reach scale transient storage modeling, there is limited understanding of how best to establish reach segment lengths that represent the effects of spatially variable hydraulic and geomorphic channel properties. In this paper, we progress this understanding through the use of channel property distributions derived from high‐resolution imagery that are fundamental for hydraulic routing. We vary the resolution of reach segments used in the model representation and investigate the minimum number necessary to capture spatially variable influences on downstream predictions of solute residence time probability density functions while sufficiently representing the observed channel property distributions. We also test if the corresponding statistical moments of the predictions provide comparable results and, therefore, a method for establishing appropriate reach segment lengths. We find that the predictions and the moment estimates begin to represent the majority of the variability at reach segment lengths coinciding with distances where observed channel properties are spatially correlated. With this approach, reach scales where the channel properties no longer significantly change predictions can be established, which provides a foundation for more focused transient storage modeling efforts.
- 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.
- Incorporating spatial dependence in regional frequency analysis
- Authors: Zhuo Wang; Jun Yan, Xuebin Zhang
Pages: n/a - n/a
Abstract: The efficiency of regional frequency analysis (RFA) is undermined by intersite dependence, which is usually ignored in parameter estimation. We propose a spatial index flood model where marginal generalized extreme value distributions are joined by an extreme‐value copula characterized by a max‐stable process for the spatial dependence. The parameters are estimated with a pairwise likelihood constructed from bivariate marginal generalized extreme value distributions. The estimators of model parameters and return levels can be more efficient than those from the traditional index flood model when the max‐stable process fits the intersite dependence well. Through simulation, we compared the pairwise likelihood method with an L‐moment method and an independence likelihood method under various spatial dependence models and dependence levels. The pairwise likelihood method was found to be the most efficient in mean squared error if the dependence model was correctly specified. When the dependence model was misspecified within the max‐stable models, the pairwise likelihood method was still competitive relative to the other two methods. When the dependence model was not a max‐stable model, the pairwise likelihood method led to serious bias in estimating the shape parameter and return levels, especially when the dependence was strong. In an illustration with annual maximum precipitation data from Switzerland, the pairwise likelihood method yielded remarkable reduction in the standard errors of return level estimates in comparison to the L‐moment method.
- Comments on “Capabilities and limitations of tracing spatial
temperature patterns by fiber‐optic distributed temperature
sensing” by L. Rose, S. Krause, and N. J. Cassidy
- Authors: Francisco Suárez
Pages: n/a - n/a
- Ecogeomorphic feedbacks and flood loss of riparian tree seedlings in
meandering channel experiments
- Authors: Li Kui; John Stella, Anne Lightbody, Andrew C. Wilcox
Pages: n/a - n/a
Abstract: During floods, fluvial forces interact with riparian plants to influence evolution of river morphology and floodplain plant community development. Understanding of these interactions, however, is constrained by insufficient precision and control of drivers in field settings, and insufficient realism in laboratory studies. We completed a novel set of flume experiments using woody seedlings planted on a sandbar within an outdoor meandering stream channel. We quantified effects on local sedimentation and seedling loss to scour and burial across realistic ranges of woody plant morphologies (Populus versus Tamarix species), densities (240 plants m‐2 versus 24 m‐2), and sediment supply (equilibrium versus deficit). Sedimentation was higher within Tamarix patches than Populus patches, reflecting Tamarix‘s greater crown frontal area and lower maximum crown density. Plant dislodgement occurred rarely (1% of plants) and was induced in plants with shorter roots. Complete burial was most frequent for small Tamarix that occurred at high densities. Burial risk decreased 3% for Populus and 13% for Tamarix for every centimeter increment in stem height, and was very low for plants >50 cm tall. These results suggest that Tamarix are proportionally more vulnerable than Populus when small (
- Pore‐scale study of dissolution‐induced changes in hydrologic
properties of rocks with binary minerals
- Authors: Li Chen; Qinjun Kang, Hari S. Viswanathan, Wen‐Quan Tao
Pages: n/a - n/a
Abstract: A pore‐scale numerical model for reactive transport processes based on the Lattice Boltzmann method is used to study the dissolution‐induced changes in hydrologic properties of a fractured medium and a porous medium. The solid phase of both media consists of two minerals, and a structure reconstruction method called quartet structure generation set is employed to generate the distributions of both minerals. Emphasis is put on the effects of undissolved minerals on the changes of permeability and porosity under different Peclet and Damkohler numbers. The simulation results show porous layers formed by the undissolved mineral remain behind the dissolution reaction front. Due to the large flow resistance in these porous layers, the permeability increases very slowly or even remains at a small value although the porosity increases by a large amount. Besides, due to the heterogeneous characteristic of the dissolution, the chemical, mechanical and hydraulic apertures are very different from each other. Further, simulations in complex porous structures demonstrate that the existence of the porous layers of the nonreactive mineral suppresses the wormholing phenomena observed in the dissolution of mono‐mineralic rocks.
- Empirical assessment of theory for bankfull characteristics of alluvial
- Authors: S. M. Trampush; S. Huzurbazar, B. McElroy
Pages: n/a - n/a
Abstract: We compiled a dataset of 541 bankfull measurements of alluvial rivers (see supplemental material) and used Bayesian linear regression to examine empirical and theoretical support for the hypothesis that alluvial channels adjust to a predictable condition of basal shear stress as a function of sediment transport mode. An empirical closure based on channel slope, bankfull channel depth, and median grain size is proposed and results in the scaling of bankfull Shields stress with the inverse square root of particle Reynolds number. The empirical relationship is sufficient for purposes of quantifying paleohydraulic conditions in ancient alluvial channels. However, it is not currently appropriate for application to alluvial channels on extraterrestrial bodies because it depends on constant‐valued, Earth‐based coefficients.
- The influence of geomorphology on large wood dynamics in a
low‐gradient headwater stream
- Authors: Dixon Simon J; Sear David. A.
Pages: n/a - n/a
Abstract: Understanding large wood dynamics is critical for a range of disciplines including flood risk management, ecology and geomorphology. Despite the importance of wood in rivers, our understanding of the mobility of large wood remains limited. In this study individual pieces of large wood were tagged and surveyed over a 32 month period within a third and fourth order lowland forest river. Individual pieces of wood were found to be highly mobile, with 75% of pieces moving during the survey period, and a maximum transport distance of 5.6km. Multivariate analyses of data from this study and two other published studies identified dimensionless wood length as the important factor in explaining likelihood of movement. A length threshold of 2.5 channel widths is identified for near functional immobility, with few pieces above this size moving. In addition, for this study, wood type, branching complexity, location and dimensionless wood diameter were found to be important in determining mobility only for sinuous reaches with readily inundated floodplains. Where logjams persist over multiple years they were shown to be reworked, with component pieces being transported away and replaced by newly trapped pieces. The findings of this study have implications for river management and restoration. The high mobility observed in this study demonstrates that only very large pieces of wood of length greater than 2.5 channel widths should be considered functionally immobile. For pieces of wood of length less than the channel width the possibility of high rates of mobility and long transport distances should be anticipated.
- Regional patterns of interannual variability of catchment water balances
across the continental U.S.: A Budyko framework
- Authors: Alejandra M. Carmona; Murugesu Sivapalan, Mary A. Yaeger, Germán Poveda
Pages: n/a - n/a
Abstract: Patterns of inter‐annual variability of the annual water balance are explored using data from 190 MOPEX catchments across the continental United States. This analysis has led to the derivation of a quantitative, dimensionless, Budyko‐type framework to characterize the observed inter‐annual variability of annual water balances. The resulting model is expressed in terms of a humidity index that measures the competition between water and energy availability at the annual time scale, and a similarity parameter (α) that captures the net effects of other short‐term climate features and local landscape characteristics. This application of the model to the 190 study catchments revealed the existence of space‐time symmetry between spatial (between‐catchment) variability and general trends in the temporal (between‐year) variability of the annual water balances. The MOPEX study catchments were classified into eight similar catchment groups on the basis of magnitudes of the similarity parameter α. Interesting regional trends of α across the continental U.S. were brought out through identification of similarities between the spatial positions of the catchment groups with the mapping of distinctive ecoregions that implicitly take into account common climatic and vegetation characteristics. In this context, this study has introduced a deep sense of similarity that is evident in observed space‐time variability of water balances that also reflect the co‐dependence and co‐evolution of climate and landscape properties.
- Subsurface lateral preferential flow network revealed by time‐lapse
ground‐penetrating radar in a hillslope
- Authors: Li Guo; Jin Chen, Henry Lin
Pages: n/a - n/a
Abstract:  Subsurface lateral preferential flow (LPF) has been observed to contribute substantially to hillslope and catchment runoff. However, the complex nature of LPF and the lack of an appropriate investigation method have hindered direct LPF observation in the field. Thus, the initiation, persistence, and dynamics of LPF networks remain poorly understood. This study explored the application of time‐lapse ground‐penetrating radar (GPR) together with an artificial infiltration to shed light on the nature of LPF and its dynamics in a hillslope. Based on the enhanced field experimental set‐up and carefully‐refined GPR data post‐processing algorithms, we developed a new protocol to reconstruct LPF networks with centimeter resolution. This is the first time that a detailed LPF network and its dynamics have been revealed non‐invasively along a hillslope. Real‐time soil water monitoring and field soil investigation confirmed the locations of LPF in the deeper BC horizon mapped by time‐lapse GPR surveys. Our results indicated the following: 1) Increased spatial variations of radar signals after infiltration suggested heterogeneous soil water changes within the studied soil, which reflected the generation and dynamics of LPF; 2) Two types of LPF networks were identified, the network at the location of soil permeability contrasts and that formed via a series of connected preferential flow paths; and 3) The formation and distribution of LPF networks were influenced by antecedent soil water condition. Overall, this study demonstrates clearly that carefully designed time‐lapse GPR surveys with enhanced data post‐processing offer a practical and nondestructive way of mapping LPF networks in the field, thereby providing a potentially significant enhancement in our ability to study complex subsurface flow processes across the landscape.
- 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.
- Reply to comment by L. Rose, S. Krause, and N.J. Cassidy on
“Capabilities and limitations of tracing spatial temperature
patterns by fiber‐optic distributed temperature sensing”
- Authors: S. Krause; L. Rose, N.J. Cassidy
Pages: n/a - n/a
- Simultaneous measurement of unfrozen water content and ice content in
frozen soil using Gamma ray attenuation and TDR
- Authors: Xiaohai Zhou; Jian Zhou, Wolfgang Kinzelbach, Fritz Stauffer
Pages: n/a - n/a
Abstract: The freezing temperature of water in soil is not constant, but varies over a range determined by soil texture. Consequently, the amounts of unfrozen water and ice change with temperature in frozen soil, which in turn affects hydraulic, thermal and mechanical properties of frozen soil. In this paper, an Am‐241 gamma ray source and TDR were combined to measure unfrozen water content and ice content in frozen soil simultaneously. The gamma ray attenuation was used to determine total water content. The TDR was used to determine the dielectric constant of the frozen soil. Based on a four‐phase mixing model, the amount of unfrozen water content in the frozen soil could be determined. The ice content was inferred by the difference between total water content and unfrozen water content. The gamma ray attenuation and the TDR were both calibrated by a gravimetric method. Water contents measured both by gamma ray attenuation and TDR separately in an unfrozen silt column under infiltration were compared and showed that the two methods have the same accuracy and response to changes of water content. Unidirectional column freezing experiments were performed to apply the combined method of gamma ray attenuation and TDR for measuring unfrozen water content and ice content. The measurement error of the gamma ray attenuation and TDR was, around 0.02 m3/m3 and 0.01 m3/m3, respectively. The overestimation of unfrozen water in frozen soil by TDR alone was quantified and found to depend on the amount of ice content. The higher the ice content, the larger the overestimation. The study confirmed that the combined method could accurately determine unfrozen water content and ice content in frozen soil. The results of soil column freezing experiments indicated that total water content distribution is affected by available pore space and the freezing front advance rate. It was found that there is similarity between soil water characteristic curve and soil freezing characteristic curve of variably‐saturated soil. Unfrozen water content is independent of total water content and affected only by temperature when the freezing point is reached.
- A two stage Bayesian stochastic optimization model for cascaded hydropower
systems considering varying uncertainty of flow forecasts
- Authors: Wei Xu; Chi Zhang, Yong Peng, Guangtao Fu, Huicheng Zhou
Pages: n/a - n/a
Abstract: This paper presents a new Two Stage Bayesian Stochastic Dynamic Programming (TS‐BSDP) model for real time operation of cascaded hydropower systems to handle varying uncertainty of inflow forecasts from Quantitative Precipitation Forecasts. In this model, the inflow forecasts are considered as having increasing uncertainty with extending lead time, thus the forecast horizon is divided into two periods: the inflows in the first period are assumed to be accurate, and the inflows in the second period assumed to be of high uncertainty. Two operation strategies are developed to derive hydropower operation policies for the first and the entire forecast horizon using TS‐BSDP. In this paper, the newly developed model is tested on China's Hun River cascade hydropower system and is compared with three popular stochastic dynamic programming models. Comparative results show that the TS‐BSDP model exhibits significantly improved system performance in terms of power generation and system reliability due to its explicit and effective utilization of varying degrees of inflow forecast uncertainty. The results also show that the decision strategies should be determined considering the magnitude of uncertainty in inflow forecasts. Further, this study confirms the previous finding that the benefit in hydropower generation gained from the use of a longer horizon of inflow forecasts is diminished due to higher uncertainty and further reveals that the benefit reduction can be substantially mitigated through explicit consideration of varying magnitudes of forecast uncertainties in the decision making process.
- Falling head ponded infiltration in the nonlinear limit
- Authors: D. Triadis
Pages: n/a - n/a
Abstract: The Green and Ampt infiltration solution represents only an extreme example of behaviour within a larger class of very nonlinear, delta function diffusivity soils. The mathematical analysis of these soils is greatly simplified by the existence of a sharp wetting front below the soil surface. Solutions for more realistic delta function soil models have recently been presented for infiltration under surface saturation without ponding.
After general formulation of the problem, solutions for a full suite of delta function soils are derived for ponded surface water depleted by infiltration. Exact expressions for the cumulative infiltration as a function of time, or the drainage time as a function of the initial ponded depth may take implicit or parametric forms, and are supplemented by simple asymptotic expressions valid for small times, and small and large initial ponded depths.
As with surface saturation without ponding, the Green–Ampt model overestimates the effect of the soil hydraulic conductivity. At the opposing extreme a low‐conductivity model is identified that also takes a very simple mathematical form and appears to be more accurate than the Green–Ampt model for larger ponded depths. Between these two, the nonlinear limit of Gardner's soil is recommended as a physically valid first approximation. Relative discrepancies between different soil models are observed to reach a maximum for intermediate values of the dimensionless initial ponded depth, and in general are smaller than for surface saturation without ponding.
- Climate change, water rights, and water supply: The case of irrigated
agriculture in Idaho
- Authors: Wenchao Xu; Scott E. Lowe, Richard M. Adams
Pages: n/a - n/a
Abstract: We conduct a hedonic analysis to estimate the response of agricultural land use to water supply information under the Prior Appropriation Doctrine by using Idaho as a case study. Our analysis includes long‐term weather trends and water supply conditions as well as seasonal water supply forecasts. A farm‐level panel data set, which accounts for the priority effects of water rights and controls for diversified crop mixes and rotation practices, is used. Our results indicate that farmers respond to long‐term surface and ground water conditions as well as to the seasonal water supply variation. Climate change‐induced variations in weather and water supply conditions could lead to substantial damages to irrigated agriculture. We project substantial losses (up to 32%) of the average crop revenue for major agricultural areas under future climate scenarios in Idaho. Finally, farmers demonstrate significantly varied responses given their water rights priorities, which implies that the distributional impact of climate change is sensitive to institutions such as the Prior Appropriation Doctrine.