- Antecedent moisture conditions control mercury and dissolved organic
carbon concentration dynamics in a boreal headwater catchment
- Authors: Claire J. Oswald; Brian A. Branfireun
Pages: n/a - n/a
Abstract: The fate and transport of mercury (Hg) deposited on forested upland soils depends on the biogeochemical and hydrological processes occurring in the soil landscape. In this study, total Hg (THg) and dissolved organic carbon (DOC) concentrations were measured in streamwater from a 7.75 ha upland subcatchment of the METAALICUS watershed in northwestern Ontario, Canada. THg and DOC concentration‐discharge relationships were examined at the seasonal‐scale and event‐scale to assess the role of antecedent moisture conditions on the mobilization of these solutes to receiving waters. At the seasonal‐scale, subcatchment discharge poorly explained THg and DOC concentration dynamics; however, the inclusion of antecedent water storage and precipitation metrics in a multiple regression model improved the prediction of THg and DOC concentrations significantly. At the event‐scale, a comparison of THg and DOC concentrations for two small summer storms with similar total discharge showed that the storm following the wet snowmelt period had a significantly lower total flux of THg and DOC than the storm following warm and dry conditions in late summer due to a distinct shift in the concentration‐discharge relationship. Measurements of soil water and groundwater THg and DOC concentrations, as well as a three‐component mixing analysis, suggest that there was an accumulation of potentially‐mobile DOC‐bound THg in the well‐humified organic soil layer in the catchment during the warm and dry summer period and that as the catchment became wetter in the autumn, there was an increase in soil water THg and DOC concentrations and these solutes were subsequently flushed during the autumn storm.
- Economic analysis of the water demand in the hotels and restaurants
sector: Shadow prices and elasticities
- Authors: Ana Angulo; Majed Atwi, Ramón Barberán, Jesús Mur
Pages: n/a - n/a
Abstract: Despite the growing economic importance of tourism, and its impact on relative water shortage, little is known about the role that water plays in the productive process of hotels and restaurants and, therefore, the possible implications of water demand management policy for this sector. This study aims to fill this gap. It is based on the microdata of 676 firms in the sector, operating in the city of Zaragoza (Spain) for a 12 year period. Based on the Translog cost function, we estimate the shadow price of water in the short run and, from a long‐run perspective, its direct price elasticity, its cross elasticities relative to labor, capital, and supplies, and its elasticity with respect to the level of output. The results obtained show that water provides sector firms returns that are on average higher than its price, although in the case of hotels the margin is really narrow. This situation provides policy makers with a margin for applying price increases without affecting the sector's viability, with some caution in the case of hotels. Water demand elasticity equals −0.38 in the case of hotels, but it is not significant in the case of restaurants and bar‐cafes; hence, only in hotels is there potential for influencing water use patterns, encouraging the resource's conservation through pricing policy. Moreover, capital is a substitutive factor of water, and the elasticity of water with respect to output is 0.40, all of which should also be considered by policy makers in water resource management.
- Assessing the value of seasonal climate forecast information through an
end‐to‐end forecasting framework: Application to U.S. 2012
drought in central Illinois
- Authors: Majid Shafiee‐Jood; Ximing Cai, Ligang Chen, Xin‐Zhong Liang, Praveen Kumar
Pages: n/a - n/a
Abstract: This study proposes an end‐to‐end forecasting framework to incorporate operational seasonal climate forecasts to help farmers improve their decisions prior to the crop growth season, which are vulnerable to unanticipated drought conditions. The framework couples a crop growth model with a decision‐making model for rainfed agriculture and translates probabilistic seasonal forecasts into more user‐related information that can be used to support farmers' decisions on crop type and some market choices (e.g., contracts with ethanol refinery). The regional Climate‐Weather Research and Forecasting model (CWRF) driven by two operational general circulation models (GCMs) is used to provide the seasonal forecasts of weather parameters. To better assess the developed framework, CWRF is also driven by observational reanalysis data, which theoretically can be considered as the best seasonal forecast. The proposed framework is applied to the Salt Creek watershed in Illinois that experienced an extreme drought event during 2012 crop growth season. The results show that the forecasts cannot capture the 2012 drought condition in Salt Creek and therefore the suggested decisions can make farmers worse off if the suggestions are adopted. Alternatively, the optimal decisions based on reanalysis‐based CWRF forecasts, which can capture the 2012 drought conditions, make farmers better off by suggesting “no‐contract” with ethanol refineries. This study suggests that the conventional metric used for ex ante value assessment is not capable of providing meaningful information in the case of extreme drought. Also, it is observed that institutional interventions (e.g., crop insurance) highly influences farmers' decisions and, thereby, the assessment of forecast value.
- Bed load fluctuations in a steep channel
- Authors: Tamara Ghilardi; Mário J. Franca, Anton J. Schleiss
Pages: n/a - n/a
Abstract: Bed load transport rate fluctuations have been observed over time in steep rivers and flumes with wide grain size distributions even under constant sediment feeding and water discharge. The observed bed load transport rate pulses are periodic and a consequence of grain sorting. Moreover, the presence of large, relatively immobile boulders, such as erratic stones, which are often present in mountain streams, has an impact on flow conditions. The detailed analysis of a 13 h laboratory experiment is presented in this paper. Boulders were randomly placed in a flume with a steep slope (6.7%), and water and sediment were constantly supplied to the flume. Along with the sediment transport and bulk mean flow velocity, the boulder protrusion, boulder surface, and number of hydraulic jumps, which are indicators of the channel morphology, were measured regularly during the experiment. Periodic bed load transport rate pulses are clearly visible in the data collected during this long‐duration experiment, along with correlated fluctuations in the flow velocity and bed morphology. The links among the bulk velocity, the time evolution of the morphology variables, and the bed load transport rate are analyzed via correlational analysis, showing that the fluctuations are strongly related. A phase analysis of all observed variables is performed, and the average shapes of the time cycles of the fluctuations are shown. Observations indicate that the detected periodic fluctuations correspond to different bed states. Furthermore, the grain size distribution through the channel, which varies in time and space, clearly influences these bed load transport rate pulses. Finally, known bed load transport rate formulae are tested, showing that only the application of a drag shear stress allows a correct estimation of the time fluctuations.
- Robust, low‐cost data loggers for stream temperature, flow
intermittency, and relative conductivity monitoring
- Authors: Thomas P. Chapin; Andrew S. Todd, Matthew P. Zeigler
Pages: n/a - n/a
Abstract: Water temperature and streamflow intermittency are critical parameters influencing aquatic ecosystem health. Low‐cost temperature loggers have made continuous water temperature monitoring relatively simple but determining streamflow timing and intermittency using temperature data alone requires significant and subjective data interpretation. Electrical resistance (ER) sensors have recently been developed to overcome the major limitations of temperature‐based methods for the assessment of streamflow intermittency. This technical note introduces the STIC (Stream Temperature, Intermittency, and Conductivity logger); a robust, low‐cost, simple to build instrument that provides long‐duration, high‐resolution monitoring of both relative conductivity (RC) and temperature. Simultaneously collected temperature and RC data provide unambiguous water temperature and streamflow intermittency information that is crucial for monitoring aquatic ecosystem health and assessing regulatory compliance. With proper calibration, the STIC relative conductivity data can be used to monitor specific conductivity.
- Discontinuous Galerkin flood model formulation: Luxury or necessity?
- Authors: Georges Kesserwani; Yueling Wang
Pages: n/a - n/a
Abstract: The finite volume Godunov‐type flood model formulation is the most comprehensive amongst those currently employed for flood risk modeling. The local Discontinuous Galerkin method constitutes a more complex, rigorous, and extended local Godunov‐type formulation. However, the practical merit associated with such an increase in the level of complexity of the formulation is yet to be decided. This work makes the case for a second‐order Runge‐Kutta Discontinuous Galerkin (RKDG2) formulation and contrasts it with the equivalently accurate finite volume (MUSCL) formulation, both of which solve the Shallow Water Equations (SWE) in two space dimensions. The numerical complexity of both formulations are presented and their capabilities are explored for wide‐ranging diagnostic and real‐scale tests, incorporating all challenging features relevant to flood inundation modeling. Our findings reveal that the extra complexity associated with the RKDG2 model pays off by providing higher‐quality solution behavior on very coarse meshes and improved velocity predictions. The practical implication of this is that improved accuracy for flood modeling simulations will result when terrain data are limited or of a low resolution.
- Modeling spatiotemporal impacts of hydroclimatic extremes on groundwater
recharge at a Mediterranean karst aquifer
- Authors: Andreas Hartmann; Matías Mudarra, Bartolomé Andreo, Ana Marín, Thorsten Wagener, Jens Lange
Pages: n/a - n/a
Abstract: Karst aquifers provide large parts of the water supply for Mediterranean countries, though climate change is expected to have a significant negative impact on water availability. Recharge is therefore a key variable that has to be known for sustainable groundwater use. In this study, we present a new approach that combines two independent methods for karst recharge estimation. The first method derives spatially distributed information of mean annual recharge patterns through GIS analysis. The second is a process‐based karst model that provides spatially lumped but temporally distributed information about recharge. By combining both methods, we add a spatial reference to the lumped simulations of the process‐based model. In this way, we are able to provide spatiotemporal information of recharge and subsurface flow dynamics also during varying hydroclimatic conditions. We find that there is a nonlinear relationship between precipitation and recharge rates resulting in strong decreases of recharge following even moderate decreases of precipitation. This is primarily due to almost constant actual evapotranspiration amounts despite varying hydroclimatic conditions. During the driest year in the record, almost the entire precipitation was consumed as actual evapotranspiration and only little diffuse recharge took place at the high altitudes of our study site. During wettest year, recharge constituted a much larger fraction of precipitation and occurred at the entire study site. Our new method and our findings are significant for decision makers in similar regions that want to prepare for possible changes of hydroclimatic conditions in the future.
- A simple inverse method for the interpretation of pumped flowing fluid
electrical conductivity logs
- Authors: R. S. Moir; A. H. Parker, R. T. Bown
Pages: n/a - n/a
Abstract: Pumped flowing fluid electrical conductivity (FFEC) logs, also known as pumped borehole dilution testing, is an experimentally easy‐to‐perform approach to evaluating vertical variations in the hydraulic conductivity of an aquifer. In contrast to the simplicity of the logging equipment, analysis of the data is complex and laborious. Current methods typically require repeated solution of the advection‐dispersion equation (ADE) for describing the flow in the borehole and comparison with the experimental results. In this paper, we describe a direct solution for determining borehole fluid velocity that bypasses the need for complex numerical computation and repetitive optimization. The method rests on the observation that, while solving the ADE for concentration profile in the borehole (as required for modeling and combined methods) is computationally challenging, the solution for flow distribution along the length of the borehole given concentration data is straightforward. The method can accommodate varying borehole diameters, and uses the fact that multiple profiles are taken in the standard logging approach to reduce the impact of noise. Data from both a simulated borehole and from a field test are successfully analyzed. The method is implemented in a spreadsheet, which is available as supporting information material to this paper.
- Epidemiology of urban water distribution systems
- Authors: Jean‐Pierre Bardet; Richard Little
Pages: n/a - n/a
Abstract: Urban water distribution systems worldwide contain numerous old and fragile pipes that inevitably break, flood streets and damage property, and disrupt economic and social activities. Such breaks often present dramatically in temporal clusters as occurred in Los Angeles during 2009. These clustered pipe breaks share many characteristics with human mortality observed during extreme climatological events such as heat waves or air pollution. Drawing from research and empirical studies in human epidemiology, a framework is introduced to analyze the time variations of disruptive pipe breaks that can help water agencies better understand clustered pipe failures and institute measures to minimize the disruptions caused by them. It is posited that at any time, a cohort of the pipes comprising the water distribution system will be in a weakened state due to fatigue and corrosion. This frail cohort becomes vulnerable during normal operations and ultimately breaks due to rapid increase in crack lengths induced by abnormal stressors. The epidemiological harvesting model developed in this paper simulates an observed time series of monthly pipe breaks and has both explanatory and predictive power. It also demonstrates that models from nonengineering disciplines such as medicine can provide improved insights into the performance of infrastructure systems.
- Comparing vertical profiles of natural tracers in the Williston Basin to
estimate the onset of deep aquifer activation
- Authors: M. Jim Hendry; Glenn A. Harrington
Pages: n/a - n/a
Abstract: Comparing high‐resolution depth profiles of different naturally occurring environmental tracers in aquitards should yield consistent and perhaps complementary information about solute transport mechanisms and the timing of major hydrogeological and climatological events. This study evaluated whether deep, continuous profiles of aquitard pore water chloride concentration could provide further insight into the paleohydrology of the Williston Basin, Canada, than possible using high‐resolution depth profiles of stable H/O isotopes of water (δ18O, δ2H). Pore water samples were obtained from extracts of cores taken over 392 m of the thick Cretaceous shale aquitard. Water samples were also collected from wells installed in the underlying regional sandy aquifer (Mannville Group; 93 m thick) and from seepage inflows into potash mine shafts (to 825 m below ground). Numerical modeling of the 1‐D vertical Cl− profile supported diffusion dominated solute transport in the shales. The modeling also showed a similar time frame for development of the Cl− profile prior to activation of the aquifer as determined from the δ18O profile (20–25 Ma); however, it provided a significantly longer and potentially better‐constrained time frame for evolution of the profile during the activation phase of the aquifer (0.5–1 Ma). The dominant paleoevent reflected in present‐day profiles of both tracers is the introduction of glaciogenic meteoric water to the Mannville aquifer underlying the shale during the Pleistocene. The source area of this water remains to be determined.
- Nonequilibrium water dynamics in the rhizosphere: How mucilage affects
water flow in soils
- Authors: Eva Kroener; Mohsen Zarebanadkouki, Anders Kaestner, Andrea Carminati
Pages: n/a - n/a
Abstract: The flow of water from soil to plant roots is controlled by the properties of the narrow region of soil close to the roots, the rhizosphere. In particular, the hydraulic properties of the rhizosphere are altered by mucilage, a polymeric gel exuded by the roots. In this paper we present experimental results and a conceptual model of water flow in unsaturated soils mixed with mucilage. A central hypothesis of the model is that the different drying/wetting rate of mucilage compared to the bulk soil results in nonequilibrium relations between water content and water potential in the rhizosphere. We coupled this nonequilibrium relation with the Richards equation and obtained a constitutive equation for water flow in soil and mucilage. To test the model assumptions, we measured the water retention curve and the saturated hydraulic conductivity of sandy soil mixed with mucilage from chia seeds. Additionally, we used neutron radiography to image water content in a layer of soil mixed with mucilage during drying and wetting cycles. The radiographs demonstrated the occurrence of nonequilibrium water dynamics in the soil‐mucilage mixture. The experiments were simulated by numerically solving the nonequilibrium model. Our study provides conceptual and experimental evidences that mucilage has a strong impact on soil water dynamics. During drying, mucilage maintains a greater soil water content for an extended time, while during irrigation it delays the soil rewetting. We postulate that mucilage exudation by roots attenuates plant water stress by modulating water content dynamics in the rhizosphere.
- Comment on “Traveling wave solution of the Boussinesq equation for
groundwater flow in horizontal aquifers” by H.A. Basha (pages
- Authors: Jeffrey Olsen; Jeff Mortensen, Aleksey S. Telyakovskiy
Pages: n/a - n/a
Abstract: This article is a comment on Basha  doi:10.1002/wrcr.20168
- A new selection metric for multiobjective hydrologic model calibration
- Authors: Masoud Asadzadeh; Bryan Tolson, Donald H. Burn
Pages: n/a - n/a
Abstract: A novel selection metric called Convex Hull Contribution (CHC) is introduced for solving multi‐objective (MO) optimization problems with Pareto fronts that can be accurately approximated by a convex curve. The hydrologic model calibration literature shows that many bi‐objective calibration problems with a proper setup result in such Pareto fronts. The CHC selection approach identifies a subset of archived non‐dominated solutions whose map in the objective space forms convex approximation of the Pareto front. The optimization algorithm can sample solely from these solutions to more accurately approximate the convex shape of the Pareto front.
It is empirically demonstrated that CHC improves the performance of Pareto Archived Dynamically Dimensioned Search (PA‐DDS) when solving MO problems with convex Pareto fronts. This conclusion is based on the results of several benchmark mathematical problems and several hydrologic model calibration problems with two or three objective functions. The impact of CHC on PA‐DDS performance is most evident when the computational budget is somewhat limited. It is also demonstrated that 1,000 solution evaluations (limited budget in this study) is sufficient for PA‐DDS with CHC‐based selection to achieve very high quality calibration results relative to the results achieved after 10,000 solution evaluations.
- Issue Information
- Pages: i - vi
- Life in a fishbowl: Prospects for the endangered Devils Hole pupfish
(Cyprinodon diabolis) in a changing climate
- Authors: Mark B. Hausner; Kevin P. Wilson, D. Bailey Gaines, Francisco Suárez, G. Gary Scoppettone, Scott W. Tyler
Pages: n/a - n/a
Abstract: The Devils Hole pupfish (Cyprinodon diabolis) is a federally listed endangered species living solely within the confines of Devils Hole, a geothermal pool ecosystem in the Mojave Desert of the American Southwest. This unique species has suffered a significant, yet unexplained, population decline in the past two decades, with a record low survey of 35 individuals in early 2013. The species survives on a highly variable seasonal input of nutrients and has evolved in a thermal regime lethal to other pupfish species. The short lifespan of the species (approximately 1 year), makes annual recruitment in Devils Hole critical to the persistence of the species, and elevated temperatures on the shallow shelf that comprises the optimal spawning habitat in the ecosystem can significantly reduce egg viability and increase larval mortality. Here we combine computational fluid dynamic modeling and ecological analysis to investigate the timing of thresholds in the seasonal cycles of food supply and temperature. Numerical results indicate a warming climate most impacts the heat loss from the water column, resulting in warming temperatures and reduced buoyancy‐driven circulation. Observed climate change is shown to have already warmed the shallow shelf, and climate change by 2050 is shown to shorten the window of optimum conditions for recruitment by as much as two weeks. While there are many possible reasons for the precipitous decline of this species, the changing climate of the Mojave region is shown to produce thermal and nutrient conditions likely to reduce the success of annual recruitment of young C. diabolis in the future, leading to continued threats to the survival of this unique and enigmatic species.
- Oscillatory pumping wells in phreatic, compressible, and homogeneous
- Authors: G. Dagan; A. Rabinovich
Pages: n/a - n/a
Abstract: Oscillatory well pumping was proposed recently as a tool for hydraulic tomography. Periodic pumping at a few frequencies is carried out through vertical intervals along the pumping well and the periodic head is measured along a few piezometers. The paper presents an analytical solution for the head field in an unconfined aquifer of finite depth under the common assumptions of a linearized water table condition, different horizontal and vertical constant permeabilities, constant specific storativity and water table drainable porosity and small well radius to length ratio. The solution provides the expressions of the amplitude and phase of the head as a function of coordinates, frequency and the problem parameters. The solution simplifies to one pertaining to an upper constant head condition and a rigid aquifer for a wide range of the dimensionless frequency values.
- Blind source separation for groundwater pressure analysis based on
nonnegative matrix factorization
- Authors: Boian S. Alexandrov; Velimir V. Vesselinov
Pages: n/a - n/a
Abstract: The identification of the physical sources causing spatial and temporal fluctuations of aquifer water levels is a challenging, yet a very important hydrogeological task. The fluctuations can be caused by variations in natural and anthropogenic sources such as pumping, recharge, barometric pressures, etc. The source identification can be crucial for conceptualization of the hydrogeological conditions and characterization of aquifer properties. We propose a new computational framework for model‐free inverse analysis of pressure transients based on Non‐negative Matrix Factorization (NMF) method for Blind Source Separation (BSS) coupled with k‐means clustering algorithm, which we call NMFk. NMFk is capable of identifying a set of unique sources from a set of experimentally measured mixed signals, without any information about the sources, their transients, and the physical mechanisms and properties controlling the signal propagation through the subsurface flow medium.Our analysis only requires information about pressure transients at a number of observation points, m, where m ≥ r, and r is the number of unknown unique sources causing the observed fluctuations. We apply this new analysis on a dataset from the Los Alamos National Laboratory site. We demonstrate that the sources identified by NMFk have real physical origins: barometric pressure and water‐supply pumping effects. We also estimate the barometric pressure efficiency of the monitoring wells. The possible applications of the NMFk algorithm are not limited to hydrogeology problems; NMFk can be applied to any problem where temporal system behavior is observed at multiple locations and an unknown number of physical sources are causing these fluctuations.
- Water resources management in a homogenizing world: Averting the growth
and underinvestment trajectory
- Authors: Ali Mirchi; David W Watkins, Casey J Huckins, Kaveh Madani, Peder Hjorth
Pages: n/a - n/a
Abstract: Biotic homogenization, a de facto symptom of a global biodiversity crisis, underscores the urgency of reforming water resources management to focus on the health and viability of ecosystems. Global population and economic growth, coupled with inadequate investment in maintenance of ecological systems, threaten to degrade environmental integrity and ecosystem services that support the global socio‐economic system, indicative of a system governed by the Growth and Underinvestment (G&U) archetype. Water resources management is linked to biotic homogenization and degradation of system integrity through alteration of water systems, ecosystem dynamics, and composition of the biota. Consistent with the G&U archetype, water resources planning primarily treats ecological considerations as exogenous constraints rather than integral, dynamic and responsive parts of the system. It is essential that the ecological considerations be made objectives of water resources development plans to facilitate the analysis of feedbacks and potential trade‐offs between socio‐economic gains and ecological losses. We call for expediting a shift to ecosystem‐based management of water resources, which requires a better understanding of the dynamics and links between water resources management actions, ecological side‐effects, and associated long‐term ramifications for sustainability. To address existing knowledge gaps, models that include dynamics and estimated thresholds for regime shifts or ecosystem degradation need to be developed. Policy levers for implementation of ecosystem‐based water resources management include shifting away from growth‐oriented supply management, better demand management, increased public awareness, and institutional reform that promotes adaptive and transdisciplinary management approaches.
- Continuous estimation of baseflow in snowmelt‐dominated streams and
rivers in the Upper Colorado River Basin: A chemical hydrograph separation
- Authors: Matthew P. Miller; David D. Susong, Christopher L. Shope, Victor M. Heilweil, Bernard J. Stolp
Pages: n/a - n/a
Abstract: Effective science‐based management of water resources in large basins requires a qualitative understanding of hydrologic conditions and quantitative measures of the various components of the water budget, including difficult to measure components such as baseflow discharge to streams. Using widely available discharge and continuously collected specific conductance (SC) data, we adapted and applied a long established chemical hydrograph separation approach to quantify daily and representative annual baseflow discharge at fourteen streams and rivers at large spatial (> 1,000 km2 watersheds) and temporal (up to 37 years) scales in the Upper Colorado River Basin. On average, annual baseflow was 21‐58% of annual stream discharge, 13‐45% of discharge during snowmelt, and 40‐86% of discharge during low‐flow conditions. Results suggest that reservoirs may act to store baseflow discharged to the stream during snowmelt and release that baseflow during low‐flow conditions, and that irrigation return flows may contribute to increases in fall baseflow in heavily irrigated watersheds. The chemical hydrograph separation approach, and associated conceptual model defined here provide a basis for the identification of land use, management, and climate effects on baseflow.
- Reply to comment by S. Iden and W. Durner on “Simple consistent
models for water retention and hydraulic conductivity in the complete
- Authors: A. Peters
Pages: n/a - n/a
- Comment to “Simple consistent models for water retention and
- Authors: Sascha C. Iden; Wolfgang Durner
Pages: n/a - n/a
- One‐dimensional soil temperature simulation with Common Land Model
by assimilating in situ observations and MODIS LST with the ensemble
- Authors: Zhongbo Yu; Xiaolei Fu, Lifeng Luo, Haishen Lü, Qin Ju, Di Liu, Dresden A. Kalin, Dui Huang, Chuanguo Yang, Lili Zhao
Pages: n/a - n/a
Abstract: Soil temperature plays an important role in hydrology, agriculture, and meteorology. In order to improve the accuracy of soil temperature simulation, a soil temperature data assimilation system was developed based on the Ensemble Particle Filter (EnPF) and the Common Land Model (CLM), and then applied in the Walnut Gulch Experimental Watershed (WGEW) in Arizona, United States. Surface soil temperature in situ observations and Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST) data were assimilated into the system. In this study, four different assimilation experiments were conducted: 1) assimilating in situ observations of instantaneous surface soil temperature each hour, 2) assimilating in situ observations of instantaneous surface soil temperature once per day, 3) assimilating verified MODIS LST once per day, and 4) assimilating original MODIS LST once per day. These four experiments reflect a transition from high quality and more frequent in situ observations to lower quality and less frequent remote sensing data in the data assimilation system. The results from these four experiments show that the assimilated results are better than the simulated results without assimilation at all layers except the bottom layer, while the superiority gradually diminishes as the quality and frequency of the observations decrease. This demonstrates that remote sensing data can be assimilated using the ensemble particle filter in poorly gauged catchments to obtain highly accurate soil variables (e.g., soil moisture, soil temperature). Meanwhile, the results also demonstrate that the ensemble particle filter is effective in assimilating soil temperature observations to improve simulations, but the performance of the data assimilation method is affected by the frequency of assimilation and the quality of the input data.
- Assessing the impacts of fiscal reforms on investment in
village‐level irrigation infrastructure
- Authors: Christine E. Boyle; Qiuqiong Huang, Jinxia Wang
Pages: n/a - n/a
Abstract: This paper investigates investment trends into village‐level irrigation projects and assesses the impact of fiscal reforms including the tax‐for‐fee reform and the elimination of agricultural tax on irrigation investment. The China Water Institutions and Management Panel Survey data show that village leaders, water user associations, farmers, and upper level governments have all contributed to irrigation investment in villages throughout the study period between 1996 and 2007. Both descriptive and multivariate analyses suggest that changes brought by fiscal reforms have significantly reduced village collectives' capacity to fund irrigation infrastructure in villages. There was a significant drop in upper level government investment during the posttax‐for‐fee period (2002–2004 in the sample areas). Since 2005, upper level government has increased its investment to prereform levels and partly filled the public investment void in irrigation infrastructure. Fiscal reforms had the least impact on farmers' investment, which has been the most stable source of funding for village‐level irrigation projects.
- The benefits of using remotely sensed soil moisture in parameter
identification of large‐scale hydrological models
- Authors: N. Wanders; M.P.F. Bierkens, S.M. de Jong, A. de Roo, D. Karssenberg
Pages: n/a - n/a
Abstract: Large‐scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large‐scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter ensemble Kalman filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR‐E, SMOS and ASCAT.
Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land surface processes. For the Upper Danube upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10‐30% in the RMSE for discharge simulations, compared to calibration on discharge alone.
The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas.
- Hydrologic routing using nonlinear cascaded reservoirs
- Authors: Dong Ha Kim; Aris P. Georgakakos
Pages: n/a - n/a
Abstract: A key element of hydrologic routing models is the discharge‐storage relationship assumed to follow a certain mathematical form, usually a linear or a power function, with parameters calibrated based on existing inflow‐outflow data. This assumption simplifies the model calibration process, but it also constrains the models to operate by the same function throughout the flow range and is prone to introducing errors. We present a new nonlinear hydrologic river routing approach that only requires that functions are non‐decreasing. River reaches are modeled as conceptual reservoir cascades, with discharge‐storage and loss/gain functions identified by the data. A novel parameter estimation approach is developed to identify these functions and other model parameters within a dynamical optimization framework. It is shown that these functions indeed exhibit different mathematical forms at different regions of their active range and that the new approach is reliable, efficient, and robust under observational uncertainty. The model is demonstrated in lake and river routing applications for the Nile River, but it is also applicable for the estimation of nonlinear, non‐decreasing functional relationships for general dynamic systems in state‐space form.
- Flood forecasting for the Mekong with data‐based models
- Authors: Khurram M. Shahzad; Erich J. Plate
Pages: n/a - n/a
Abstract: In many regions of the world the task of flood forecasting is made difficult because only a limited data base is available for generating a suitable forecast model. This paper demonstrates that in such cases parsimonious data based hydrological models for flood forecasting can be developed if the special conditions of climate and topography are used to advantage. As an example the middle reach of River Mekong in South East Asia is considered, where a data base of discharges from 7 gaging stations on the river and 31 rainfall stations on the sub‐catchments between gaging stations is available for model calibration. Special conditions existing for River Mekong are identified and used in developing first a network connecting all discharge gages, and then models for forecasting discharge increments between gaging stations. Our final forecast model (Model 3) is a linear combination of two structurally different basic models: a model (Model 1) using linear regressions for forecasting discharge increments, and a model (Model 2) using rainfall – runoff models. Although the model based on linear regressions works reasonably well for short times, better results are obtained with rainfall runoff modeling. However, forecast accuracy of model 2 is limited by the quality of rainfall forecasts. For best results both models are combined by taking weighted averages to form Model 3. Model quality is assessed by means of both persistence index PI and standard deviation of forecast error.
- Mapping variability of soil water content and flux across 1–1000 m
scales using the actively heated fiber optic method
- Authors: Chadi Sayde; Javier Benitez Buelga, Leonor Rodriguez‐Sinobas, Laureine El Khoury, Marshall English, Nick van de Giesen, John S. Selker
Pages: n/a - n/a
Abstract: The Actively Heated Fiber Optic (AHFO) method is shown to be capable of measuring soil water content several times per hour at 0.25 m spacing along cables of multiple kilometers in length. AHFO is based on distributed temperature sensing (DTS) observation of the heating and cooling of a buried fiber optic cable resulting from an electrical impulse of energy delivered from the steel cable jacket. The results presented were collected from 750 m of cable buried in three 240 m co‐located transects at 30, 60, and 90 cm depths in an agricultural field under center pivot irrigation. The calibration curve relating soil water content to the thermal response of the soil to a heat pulse of 10 W m‐1 for 1 minute duration was developed in the lab. This calibration was found applicable to the 30 and 60 cm depths cables, while the 90 cm depth cable illustrated the challenges presented by soil heterogeneity for this technique. This method was used to map with high resolution the variability of soil water content and fluxes induced by the non‐uniformity of water application at the surface.
- Assessing the impacts of reservoir operation to floodplain inundation by
combining hydrological, reservoir management, and hydrodynamic models
- Authors: Cherry May Mateo; Naota Hanasaki, Daisuke Komori, Kenji Tanaka, Masashi Kiguchi, Adisorn Champathong, Thada Sukhapunnaphan, Dai Yamazaki, Taikan Oki
Pages: n/a - n/a
Abstract: A catastrophic flood event which caused massive economic losses occurred in Thailand, in 2011. Several studies have already been conducted to analyze the Thai floods but none of them have assessed the impacts of reservoir operation on flood inundation. This study addresses this gap by combining physically‐based hydrological models to explicitly simulate the impacts of reservoir operation on flooding in the Chao Phraya River Basin, Thailand. H08, an integrated water resources model with a reservoir operation module, was combined with CaMa‐Flood, a river routing model for the representation of flood dynamics. The combined H08‐CaMa model was applied to simulate and assess the historical and alternative reservoir operation rules in the two largest reservoirs in the basin. The combined H08‐CaMa model effectively simulated the 2011 flood: regulated flows at a major gauging station have high daily NSE‐coefficient of 92% as compared with observed discharge; spatiotemporal extent of simulated flood inundation match well with those of satellite observations. Simulation results show that through the operation of reservoirs in 2011, flood volume was reduced by 8.6 billion m3 and both flood depth and flood area were reduced by 40% on the average. Nonetheless, simple modifications in reservoir operation proved to further reduce the flood volume by 2.4 million m3 and the flood depth and flood area by 20% on the average. A more realistic simulation of the 2011 Thai flood was made possible by modeling reservoir operation with a hydrodynamic model; the possibility of reducing flood inundation through improved reservoir management was quantified.
- Behavioral response to contamination risk information in a spatially
explicit groundwater environment: Experimental evidence
- Authors: Jingyuan Li; Holly A. Michael, Joshua M. Duke, Kent D. Messer, Jordan F. Suter
Pages: n/a - n/a
Abstract: This paper assesses the effectiveness of aquifer monitoring information in achieving more sustainable use of a groundwater resource in the absence of management policy. Groundwater user behavior in the face of an irreversible contamination threat is studied by applying methods of experimental economics to scenarios that combine a physics‐based, spatially explicit, numerical groundwater model with different representations of information about an aquifer and its risk of contamination. The results suggest that the threat of catastrophic contamination affects pumping decisions: pumping is significantly reduced in experiments where contamination is possible compared to those where pumping cost is the only factor discouraging groundwater use. The level of information about the state of the aquifer also affects extraction behavior. Pumping rates differ when information that synthesizes data on aquifer conditions (a “risk gauge”) is provided, despite invariant underlying economic incentives, and this result does not depend on whether the risk information is location‐specific or from a whole aquifer perspective. Interestingly, users increase pumping when the risk gauge signals good aquifer status compared to a no‐gauge treatment. When the gauge suggests impending contamination, however, pumping declines significantly, resulting in a lower probability of contamination. The study suggests that providing relatively simple aquifer condition guidance derived from monitoring data can lead to more sustainable use of groundwater resources.
- Modeling irrigation behavior in groundwater systems
- Authors: Timothy Foster; Nicholas Brozović, Adrian P. Butler
Pages: n/a - n/a
Abstract: Integrated hydro‐economic models have been widely applied to water management problems in regions of intensive groundwater‐fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.
- Single‐parameter model of vegetated aquatic flows
- Authors: Ilenia Battiato; Simonetta Rubol
Pages: n/a - n/a
Abstract: Coupled flows through and over permeable layers occur in a variety of natural phenomena including turbulent flows over submerged vegetation. In this work, we employ a two‐domain approach to model flow through and over submerged canopies. The model, amenable of a closed‐form solution, couples the log‐law and the Darcy‐Brinkman equation, and is characterized by a novel representation of the drag force which does not rely on a parametrization through an unknown drag coefficient. This approach limits to one, i.e., the obstruction permeability, the number of free parameters. Analytical expressions for the average velocity profile through and above the canopies, volumetric flow rate, penetration length, and canopy shear layer parameter are obtained in terms of the canopy layer effective permeability. The model suggests that appropriately rescaled velocities in the canopy and surface layers follow two different scaling laws. The analytical predictions match with the experimental data collected by Ghisalberti and Nepf (2004) and Nepf et al. (2007).
- Extrapolating active layer thickness measurements across Arctic polygonal
terrain using LiDAR and NDVI data sets
- Authors: Chandana Gangodagamage; Joel C. Rowland, Susan S. Hubbard, Steven P. Brumby, Anna K. Liljedahl, Haruko Wainwright, Cathy J. Wilson, Garrett L. Altmann, Baptiste Dafflon, John Peterson, Craig Ulrich, Craig E. Tweedie, Stan D. Wullschleger
Pages: n/a - n/a
Abstract: Landscape attributes that vary with microtopography, such as active layer thickness (ALT), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high‐resolution remotely sensed data for estimating centimeter‐scale ALT in a 5 km2 area of ice‐wedge polygon terrain in Barrow, Alaska. We use a simple regression‐based, machine learning data‐fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView‐2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground‐based measurements, indicates the accuracy (r2 = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT, consistent with prior studies, our findings using high‐resolution LiDAR and WorldView‐2 data, show that smaller‐scale variability in ALT is controlled by local eco‐hydro‐geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land‐surface processes from readily available remote sensing data.
- Capillary pinning and blunting of immiscible gravity currents in porous
- Authors: Benzhong Zhao; Christopher W. MacMinn, Herbert E. Huppert, Ruben Juanes
Pages: n/a - n/a
Abstract: Gravity‐driven flows in the subsurface have attracted recent interest in the context of geological carbon dioxide (CO2) storage, where supercritical CO2 is captured from the flue gas of power plants and injected underground into deep saline aquifers. After injection, the CO2 will spread and migrate as a buoyant gravity current relative to the denser, ambient brine. Although the CO2 and the brine are immiscible, the impact of capillarity on CO2 spreading and migration is poorly understood. We previously studied the early‐time evolution of an immiscible gravity current, showing that capillary pressure hysteresis pins a portion of the macroscopic fluid‐fluid interface and that this can eventually stop the flow. Here, we study the full lifetime of such a gravity current. Using table‐top experiments in packings of glass beads, we show that the horizontal extent of the pinned region grows with time, and that this is ultimately responsible for limiting the migration of the current to a finite distance. We also find that capillarity blunts the leading edge of the current, which contributes to further limiting the migration distance. Using experiments in etched micromodels, we show that the thickness of the blunted nose is controlled by the distribution of pore‐throat sizes and the strength of capillarity relative to buoyancy. We develop a theoretical model that captures the evolution of immiscible gravity currents and predicts the maximum migration distance. By applying this model to representative aquifers, we show that capillary pinning and blunting can exert an important control on gravity currents in the context of geological CO2 storage.
- Calibration of seawater intrusion models: Inverse parameter estimation
using surface electrical resistivity tomography and borehole data
- Authors: J. Beaujean; F. Nguyen, A. Kemna, A. Antonsson, P. Engesgaard
Pages: n/a - n/a
Abstract: Electrical resistivity tomography (ERT) can be used to constrain seawater intrusion models because of its high sensitivity to total dissolved solid contents (TDS) in groundwater and its relatively high lateral coverage. However, the spatial variability of resolution in electrical imaging may prevent the correct recovery of the desired hydrochemical properties such as salt mass fraction. This paper presents a sequential approach to evaluate the feasibility of identifying hydraulic conductivity and dispersivity in density‐dependent flow and transport models from surface ERT‐derived mass fraction. In the course of this study geophysical inversion was performed by using a smoothness constraint Tikhonov approach, whereas the hydrological inversion was performed using a gradient‐based Levenberg‐Marquardt algorithm. Two synthetic benchmarks were tested. They represent a pumping experiment in a homogeneous and heterogeneous coastal aquifer, respectively. These simulations demonstrated that only the lower salt mass fraction of the seawater‐freshwater transition zone can be recovered for different times. This ability has here been quantified in terms of cumulative sensitivity and our study has further demonstrated that the mismatch between the targeted and the recovered salt mass fraction occurs from a certain threshold. We were additionally able to explore the capability of sensitivity‐filtered ERT images using ground surface data only to recover (in both synthetic cases) the hydraulic conductivity while the dispersivity is more difficult to estimate. We attribute the latter mainly to the lack of ERT‐derived data at depth (where resolution is poorer) as well as to the smoothing effect of the ERT inversion.
- Risk‐based water resources planning: Incorporating probabilistic
nonstationary climate uncertainties
- Authors: Edoardo Borgomeo; Jim W. Hall, Fai Fung, Glenn Watts, Keith Colquhoun, Chris Lambert
Pages: n/a - n/a
Abstract: We present a risk‐based approach for incorporating non‐stationary probabilistic climate projections into long‐term water resources planning. The proposed methodology uses non‐stationary synthetic time series of future climates obtained via a stochastic weather generator based on the UK Climate Projections (UKCP09) to construct a probability distribution of the frequency of water shortages in the future. The UKCP09 projections extend well beyond the range of current hydrological variability, providing the basis for testing the robustness of water resources management plans to future climate‐related uncertainties. The non‐stationary nature of the projections combined with the stochastic simulation approach allows for extensive sampling of climatic variability conditioned upon climate model outputs. The probability of exceeding planned frequencies of water shortages of varying severity (defined as Levels of Service for the water supply utility company) is used as a risk metric for water resources planning. Different sources of uncertainty, including demand‐side uncertainties, are considered simultaneously and their impact on the risk metric is evaluated. Supply‐side and demand‐side management strategies can be compared based on how cost‐effective they are at reducing risks to acceptable levels. A case study based on a water supply system in London (UK) is presented to illustrate the methodology. Results indicate an increase in the probability of exceeding the planned Levels of Service across the planning horizon. Under a 1% per annum population growth scenario, the probability of exceeding the planned Levels of Service is as high as 0.5 by 2040. The case study also illustrates how a combination of supply and demand management options may be required to reduce the risk of water shortages.
- Water banking, conjunctive administration, and drought: The interaction of
water markets and prior appropriation in southeastern Idaho
- Authors: Sanchari Ghosh; Kelly M. Cobourn, Levan Elbakidze
Pages: n/a - n/a
Abstract: Despite recognition of the potential economic benefits and increasing interest in developing marketing instruments, water markets have remained thin and slow to evolve due to high transactions costs, third‐party effects, and the persistence of historical institutions for water allocation. Water banks are a marketing instrument that can address these obstacles to trade, allowing irrigators within a region to exchange water in order to mitigate the short‐term effects of drought. Water banks coexist with the institutions governing water allocation, which implies that rule changes, such as adoption of a system of conjunctive surface water‐groundwater administration, carry implications for the economic impacts of banking. This paper assesses and compares the welfare and distributional outcomes for irrigators in the Eastern Snake River Plain of Idaho under a suite of water management and drought scenarios. We find that water banking can offset irrigators’ profit losses during drought, but that its ability to do so depends on whether it facilitates trade across groundwater and surface water users. With conjunctive administration, a bank allowing trade by source realizes 22.23 percent of the maximum potential efficiency gains from trade during a severe drought, while a bank that allows trade across sources realizes 93.47 percent of the maximum potential gains. During drought, conjunctive administration redistributes welfare from groundwater to surface water producers, but banking across sources allows groundwater irrigators to recover 88.4 percent of the profits lost from drought at a cost of 2.2 percent of the profit earned by surface water irrigators.
- Characterization of flow parameters and evidence of pore clogging during
limestone dissolution experiments
- Authors: L. Luquot; T. S. Roetting, J. Carrera
Pages: n/a - n/a
Abstract: Rock dissolution induces changes in texture (porosity, pore‐size distribution, or tortuosity) which modify multiphase flow and transport properties (permeability, diffusion coefficient, retention curve). Limestone dissolution will occur during CO2 storage or acid injection for well stimulation. Therefore, characterizing those changes is essential for understanding flow and transport during and after the CO2 injection because they can affect the storage capacity, injectivity, and trapping mechanisms. Yet, few published studies evaluate the changes of hydrodynamic properties due to fluid‐rock interactions. We report seven dissolution experiments performed on four limestone samples by injecting water with pH ranging from 3.5 to 5.0. Sample porosity, diffusion coefficient, and pore‐size distribution were measured before and after each rock attack, which was repeated twice on three of the samples. Permeability was monitored continuously and chemical samples were taken to evaluate calcite dissolution. We find that overall porosity increases over time as expected. But the increase is nonuniform along the sample. At the samples inlets, large pores increase significantly while small pores remain unchanged, which is consistent with wormhole initiation. However, the size of largest pores is reduced at the outlet, which we attribute to clogging by particles dragged from the inlet. As a result, the overall permeability is reduced. Particle dragging is unlikely during supercritical CO2 storage because head gradients are small, but may be expected in the case of dissolved CO2 injection or during well stimulation by acid injection. Our results imply that dissolution is highly localized, which will result in a significant increase in capillary trapping.
- Including adaptation and mitigation responses to climate change in a
multiobjective evolutionary algorithm framework for urban water supply
systems incorporating GHG emissions
- Authors: F. L. Paton; H. R. Maier, G. C. Dandy
Pages: n/a - n/a
Abstract: Cities around the world are increasingly involved in climate action and mitigating greenhouse gas (GHG) emissions. However, in the context of responding to climate pressures in the water sector, very few studies have investigated the impacts of changing water use on GHG emissions, even though water resource adaptation often requires greater energy use. Consequently, reducing GHG emissions, and thus focusing on both mitigation and adaptation responses to climate change in planning and managing urban water supply systems, is necessary. Furthermore, the minimization of GHG emissions is likely to conflict with other objectives. Thus, applying a multiobjective evolutionary algorithm (MOEA), which can evolve an approximation of entire trade‐off (Pareto) fronts of multiple objectives in a single run, would be beneficial. Consequently, the main aim of this paper is to incorporate GHG emissions into a MOEA framework to take into consideration both adaptation and mitigation responses to climate change for a city's water supply system. The approach is applied to a case study based on Adelaide's southern water supply system to demonstrate the framework's practical management implications. Results indicate that trade‐offs exist between GHG emissions and risk‐based performance, as well as GHG emissions and economic cost. Solutions containing rainwater tanks are expensive, while GHG emissions greatly increase with increased desalinated water supply. Consequently, while desalination plants may be good adaptation options to climate change due to their climate‐independence, rainwater may be a better mitigation response, albeit more expensive.
- Numerical assessment of potential impacts of hydraulically fractured
Bowland Shale on overlying aquifers
- Authors: Zuansi Cai; Ulrich Ofterdinger
Pages: n/a - n/a
Abstract: Natural gas extracted from hydraulically fractured shale formations potentially has a big impact on the global energy landscape. However, there are concerns of potential environmental impacts of hydraulic fracturing of the shale formations, particularly those related to water quality. To evaluate the potential impact of hydraulically fractured shale on overlying aquifers, we conduct realizations of numerical modeling simulations to assess fluid flow and chloride transport from a synthetic Bowland Shale over a period of 11,000 years. The synthetic fractured shale was represented by a three‐dimensional discrete fracture model that was developed by using the data from a Bowland Shale gas exploration in Lancashire, UK. Chloride mass exchange between fractures and the rock matrix was fully accounted for in the model. The assessment was carried out to investigate fluid and chloride mass fluxes before, during, and after hydraulic fracturing of the Bowland Shale. Impacts of the upward fracture height and aperture, as well as hydraulic conductivity of the multilayered bedrock system, are also included this assessment. This modeling revealed that the hydraulically fractured Bowland Shale is unlikely to pose a risk to its overlying groundwater quality when the induced fracture aperture is ≤200 µm. With the fracture aperture ≥1000 µm, the upward chloride flux becomes very sensitive to the upward fracture height growth and hydraulic conductivity of the multilayered bedrock system. In the extremely unlikely event of the upward fracture growth directly connecting the shale formation to the overlying Sherwood Sandstone aquifer with the fracture aperture ≥1000 µm, the upward chloride mass flux could potentially pose risks to the overlying aquifer in 100 years. The model study also revealed that the upward mass flux is significantly intercepted by the horizontal mass flux within a high permeable layer between the Bowland Shale and its overlying aquifers, reducing further upward flux toward the overlying aquifers.
- Modeling hydrologic and ecologic responses using a new
eco‐hydrological model for identification of droughts
- Authors: Yohei Sawada; Toshio Koike, Patricia Ann Jaranilla‐Sanchez
Pages: n/a - n/a
Abstract: Drought severely damages water and agricultural resources, and both hydrological and ecological responses are important for its understanding. First, precipitation deficit induces soil moisture deficiency and high plant water stress causing agricultural droughts. Second, hydrological drought characterized by deficit of river discharge and groundwater follows agricultural drought. However, contributions of vegetation dynamics to these processes at basin scale have not been quantified. To address this issue, we develop an eco‐hydrological model that can calculate river discharge, groundwater, energy flux, and vegetation dynamics as diagnostic variables at basin scale within a distributed hydrological modeling framework. The model is applied to drought analysis in the Medjerda River basin. From model inputs and outputs, we calculate drought indices for different drought types. The model shows reliable accuracy in reproducing observed river discharge in long‐term (19 year) simulation. Moreover, the drought index calculated from the model‐estimated annual peak of leaf area index correlates well (correlation coefficient r = 0.89) with the drought index from nationwide annual crop production, which demonstrates that the modeled leaf area index is capable of representing agricultural droughts related to historical food shortages. We show that vegetation dynamics have a more rapid response to meteorological droughts than river discharge and groundwater dynamics in the Medjerda basin because vegetation dynamics are sensitive to soil moisture in surface layers, whereas soil moisture in deeper layers strongly contributes to streamflow and groundwater level. Our modeling framework can contribute to analyze drought progress, although analyses for other climate conditions are needed.
- A semianalytical solution for the Boussinesq equation with nonhomogeneous
constant boundary conditions
- Authors: Nelson L. Dias; Tomás L. Chor, Ailín Ruiz de Zárate
Pages: n/a - n/a
Abstract: The Boussinesq groundwater equation is widely used in hydrology to predict streamflow from an unconfined aquifer and derive the aquifer’s saturated hydraulic conductivity and drainable porosity, and to predict water table height in drainage engineering. In this work, we solve this equation in an unconfined horizontal aquifer for non‐homogeneous boundary conditions for the water table height. The solution is found in the form of a Taylor series that has a finite radius of convergence which is different for each initial condition. We also present an expression for the flux boundary condition at the origin as a function of the depth of the adjoining stream that automatically satisfies the boundary condition at infinity, and thus eliminates the need for a trial and error approach for the solution, which is accurate to 10‐7. In order to obtain an approximation for the water table height in the region where the series solution diverges, first we computed a diagonal Padé approximation from the series coefficients, which converges in a larger interval than the series, and then we matched it with a new asymptotic approximation for large values of the independent variable. We found that the proposed matched solution is better suited to cases where the water head at the origin is close to the initial water head in the aquifer.
- Accuracy of travel time distribution (TTD) models as affected by TTD
complexity, observation errors, and model and tracer selection
- Authors: Christopher T. Green; Yong Zhang, Bryant C. Jurgens, J. Jeffrey Starn, Matthew K. Landon
Pages: n/a - n/a
Abstract: Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic data sets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for 1 public‐supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (
NO3−) concentrations. Analytical models included a new, scale‐dependent dispersivity model (SDM) for two‐dimensional transport from the water table to a well and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for
NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.
- Comparison of effects of inset floodplains and hyporheic exchange induced
by in‐stream structures on solute retention
- Authors: David L. Azinheira; Durelle T. Scott, W. Hession, Erich T. Hester
Pages: n/a - n/a
Abstract: The pollution of streams and rivers is a growing concern, and environmental guidance increasingly suggests stream restoration to improve water quality. Solute retention in off‐channel storage zones, such as hyporheic zones and floodplains, is typically necessary for significant reaction to occur. Yet, the effects of two common restoration techniques, in‐stream structures and inset floodplains, on solute retention have not been rigorously compared. We used MIKE SHE to model hydraulics and solute transport in the channel, on inset floodplains, and in structure‐induced hyporheic zones of a third‐order stream. We varied hydraulic conditions (winter base flow, summer base flow, and stormflow), geology (hydraulic conductivity), and stream restoration design parameters (inset floodplain length and presence of in‐stream structures). The in‐stream structures induced hyporheic exchange for approximately 20% of the year (during summer base flow) while inset floodplains were active for approximately 1% of the year (during stormflow). Flow onto inset floodplains and residence times in both the channel and on the floodplains increased nonlinearly with the fraction of bank with floodplains installed. The fraction of streamflow that flowed onto the inset floodplains was 1–3 orders of magnitude higher than that which flowed through the structure‐induced hyporheic zone. Yet, residence times and mass storage in the hyporheic zone were 1–5 orders of magnitude larger than that on individual inset floodplains. In our modeling, neither in‐stream structures nor inset floodplains had sufficient percent flow and residence times simultaneously to have a substantial impact on dissolved contaminants flowing downstream.
- Optimization of canopy conductance models from concurrent measurements of
sap flow and stem water potential on Drooping Sheoak in South Australia
- Authors: Hailong Wang; Huade Guan, Zijuan Deng, Craig T. Simmons
Pages: n/a - n/a
Abstract: Canopy conductance (gc) is a critical component in hydrological modeling for transpiration estimate. It is often formulated as functions of environmental variables. These functions are climate and vegetation specific. Thus, it is important to determine the appropriate functions in gc models and corresponding parameter values for a specific environment. In this study, sap flow, stem water potential, and microclimatic variables were measured for three Drooping Sheoak (Allocasuarina verticillata) trees in year 2011, 2012, and 2014. Canopy conductance was calculated from the inversed Penman-Monteith (PM) equation, which was then used to examine 36 gc models that comprise different response functions. Parameters were optimized using the DiffeRential Evolution Adaptive Metropolis (DREAM) model based on a training data set in 2012. Use of proper predawn stem water potential function, vapor pressure deficit function, and temperature function improves model performance significantly, while no pronounced difference is observed between models that differ in solar radiation functions. The best model gives a correlation coefficient of 0.97, and root-mean-square error of 0.0006 m/s in comparison to the PM-calculated gc. The optimized temperature function shows different characteristics from its counterparts in other similar studies. This is likely due to strong interdependence between air temperature and vapor pressure deficit in the study area or Sheoak tree physiology. Supported by the measurements and optimization results, we suggest that the effects of air temperature and vapor pressure deficit on canopy conductance should be represented together.
- Continuous streamflow prediction in ungauged basins: The effects of
equifinality and parameter set selection on uncertainty in regionalization
- Authors: Richard Arsenault; François P. Brissette
Pages: n/a - n/a
Abstract: This paper focuses on evaluating the uncertainty of three common regionalization methods for predicting continuous streamflow in ungauged basins. A set of 268 basins covering 1.6 million km2 in the province of Quebec was used to test the regionalization strategies. The multiple linear regression, spatial proximity, and physical similarity approaches were evaluated on the catchments using a leave-one-out cross-validation scheme. The lumped conceptual HSAMI hydrological model was used throughout the study. A bootstrapping method was chosen to further estimate uncertainty due to parameter set selection for each of the parameter set/regionalization method pairs. Results show that parameter set selection can play an important role in regionalization method performance depending on the regionalization methods (and their variants) used and that equifinality does not contribute significantly to the overall uncertainty witnessed throughout the regionalization methods applications. Regression methods fail to consistently assign behavioral parameter sets to the pseudoungauged basins (i.e., the ones left out). Spatial proximity and physical similarity score better, the latter being the best. It is also shown that combining either physical similarity or spatial proximity with the multiple linear regression method can lead to an even more successful prediction rate. However, even the best methods were shown to be unreliable to an extent, as successful prediction rates never surpass 75%. Finally, this paper shows that the selection of catchment descriptors is crucial to the regionalization strategies' performance and that for the HSAMI model, the optimal number of donor catchments for transferred parameter sets lies between four and seven.
- An entropy-based surface velocity method for estuarine discharge
- Authors: Adam J. Bechle; Chin H. Wu
Pages: n/a - n/a
Abstract: An entropy-based method is developed to estimate estuarine river discharge from surface velocity measurements. A two-dimensional velocity profile based on the principle of maximum entropy is employed to express the mean velocity as a function of average surface velocity. The entropy-based flow profile is parameterized by the location of maximum velocity in the channel and the shape of the velocity distribution. The entropy parameters are quantified over the tidal cycle to account for the unsteady nature of estuarine flow. The method was tested using experiments conducted at the Danshui River, the largest estuarine system in Taiwan. Surface velocities were measured using an Automated River-Estuary Discharge Imaging System (AREDIS), and full-channel velocity profiles were measured with a moving-boat ADP survey. Entropy parameters were calibrated over the tidal cycle and linearly correlated with the average surface velocity to facilitate estimation from AREDIS measurements. The discharge calculated from average surface velocity and entropy relationships exhibits a 7.7% relative error compared to the ADP velocity profiles. The error nearly doubles when the mean values for entropy parameters are used instead of the variable parameters, indicating the importance of accounting for the unsteady nature of estuarine flows. Furthermore, the effects of measurement coverage area, types of entropy distribution, and wind-induced drift current on the surface velocity-based discharge measurement are evaluated and discussed. Overall, surface velocity measurements in conjunction with the entropy profiles well represent the flow in a complex estuarine environment to provide a reliable estimate of discharge.
- Inference of reactive transport model parameters using a Bayesian
- Authors: Luca Carniato; Gerrit Schoups, Nick van de Giesen
Pages: n/a - n/a
Abstract:  Parameter estimation of subsurface transport models from multi-species data requires the definition of an objective function that includes different types of measurements. Common approaches are weighted least squares (WLS), where weights are specified a priori for each measurement, and weighted least squares with weight estimation (WLS(we)) where weights are estimated from the data together with the parameters. In this study, we formulate the parameter estimation task as a multivariate Bayesian inference problem. The WLS and WLS(we) methods are special cases in this framework, corresponding to specific prior assumptions about the residual covariance matrix. The Bayesian perspective allows for generalizations to cases where residual correlation is important and for efficient inference by analytically integrating out the variances (weights) and selected covariances from the joint posterior. Specifically, the WLS and WLS(we) methods are compared to a multivariate (MV) approach that accounts for specific residual correlations without the need for explicit estimation of the error parameters. When applied to inference of reactive transport model parameters from column-scale data on dissolved species concentrations, the following results were obtained: (1) accounting for residual correlation between species provides more accurate parameter estimation for high residual correlation levels whereas its influence for predictive uncertainty is negligible, (2) integrating out the (co)variances leads to an efficient estimation of the full joint posterior with a reduced computational effort compared to the WLS(we) method, and (3) in the presence of model structural errors, none of the methods is able to identify the correct parameter values.
- Comment on “A blueprint for process-based modeling of uncertain
hydrological systems” by Montanari and Koutsoyiannis
- Authors: Grey Nearing
Pages: n/a - n/a
- Interplay of climate seasonality and soil moisture – Rainfall
- Authors: Jun Yin; Amilcare Porporato, John Albertson
Pages: n/a - n/a
Abstract: The soil moisture-rainfall feedback (SMRF) may significantly impact hydro-climatic dynamics, inducing persistent weather conditions that are responsible for prolonged droughts or abnormally wet states. However, externally driven seasonal variability in rainfall and potential evapotranspiration, with the associated patterns of wet and dry conditions, may both interact with such SMRF. In this study, seasonal variations in radiation and precipitation forcing are included in a stochastic SMRF model with the assumption of a soil moisture-dependent average rainfall frequency to explore their effects on the soil moisture probabilistic structure. The theoretical model results, based on a parameterization using data for soil moisture and climate in Illinois, show that average rainfall frequency peaks in late spring when both the soil condition and the SMRF strength favor convective rainfall triggering. Under such conditions, the soil moisture tends to exhibit bimodal behavior until the SMRF strength becomes weak again towards the end of the growing season. Such behavior is reminiscent of the dynamics of a system undergoing a periodic, stochastically forced pitchfork bifurcation. The presence of bimodal soil moisture behavior is also verified using nonparametric statistical tests on soil moisture data. The analysis of wet-to-wet and dry-to-dry soil moisture transitions in the joint probability distribution of soil moisture further corroborates the presence of hydro-climatic persistence in the spring-to-summer transition.
- Reply to comment by G. Nearing on “A blueprint for process-based
modeling of uncertain hydrological systems”
- Authors: Alberto Montanari; Demetris Koutsoyiannis
Pages: n/a - n/a
- Scale-dependent energy conservation and its connection to flow field
instability in porous media
- Authors: M.R. Deinert
Pages: n/a - n/a
Abstract: It has been known for decades that isothermal flow fields in porous media can become unstable, resulting in the growth of preferential flow paths and non-monotonic moisture profiles. The standard approach to modeling isothermal fluid transport in a porous systems is to use Richards equation with equilibrium relationships for the driving potential and monotonic transport coefficients. However, it is well known that under these conditions, solutions to Richards' equation are unconditionally stable. This has left open the question of whether Richards' equation could predict the onset of flow field instability, and what is required to model it. Importantly, past work has shown that pore scale processes can actually cause non-equilibrium driving potentials to arise in unsaturated media. How these can lead to flow field instability can be understood using a form of spectral perturbation theory. Here the driving potential is represented using a Fourier expansion, which is then substituted into Richards equation. The results show that the evolution of perturbations to the flow field are affected by the interaction between different wavelength components in the Fourier expansion. In particular, there are situations where non-equilibrium driving potentials can set up conditions that would allow the onset of instability in solutions to Richards' equation.
- Optimal plant water‐use strategies under stochastic rainfall
- Authors: Stefano Manzoni; Giulia Vico, Gabriel Katul, Sari Palmroth, Amilcare Porporato
Pages: 5379 - 5394
Abstract: Plant hydraulic traits have been conjectured to be coordinated, thereby providing plants with a balanced hydraulic system that protects them from cavitation while allowing an efficient transport of water necessary for photosynthesis. In particular, observations suggest correlations between the water potentials at which xylem cavitation impairs water movement and the one at stomatal closure, and between maximum xylem and stomatal conductances, begging the question as to whether such coordination emerges as an optimal water‐use strategy under unpredictable rainfall. Here mean transpiration is used as a proxy for long‐term plant fitness and its variations as a function of the water potentials at 50% loss of stem conductivity due to cavitation and at 90% stomatal closure are explored. It is shown that coordination between these hydraulic traits is necessary to maximize , with rainfall patterns altering the optimal range of trait values. In contrast, coordination between ecosystem‐level conductances appears not necessary to maximize . The optimal trait ranges are wider under drier than under mesic conditions, suggesting that in semiarid systems different water use strategies may be equally successful. Comparison with observations across species from a range of ecosystems confirms model predictions, indicating that the coordinated functioning of plant organs might indeed emerge from an optimal response to rainfall variability.
- Increased evaporation following widespread tree mortality limits
- Authors: J. A. Biederman; A. A. Harpold, D. J. Gochis, B. E. Ewers, D. E. Reed, S. A. Papuga, P. D. Brooks
Pages: 5395 - 5409
Abstract: A North American epidemic of mountain pine beetle (MPB) has disturbed over 5 million ha of forest containing headwater catchments crucial to water resources. However, there are limited observations of MPB effects on partitioning of precipitation between vapor loss and streamflow, and to our knowledge these fluxes have not been observed simultaneously following disturbance. We combined eddy covariance vapor loss (V), catchment streamflow (Q), and stable isotope indicators of evaporation (E) to quantify hydrologic partitioning over 3 years in MPB‐impacted and control sites. Annual control V was conservative, varying only from 573 to 623 mm, while MPB site V varied more widely from 570 to 700 mm. During wet periods, MPB site V was greater than control V in spite of similar above‐canopy potential evapotranspiration (PET). During a wet year, annual MPB V was greater and annual Q was lower as compared to an average year, while in a dry year, essentially all water was partitioned to V. Ratios of 2H and 18O in stream and soil water showed no kinetic evaporation at the control site, while MPB isotope ratios fell below the local meteoric water line, indicating greater E and snowpack sublimation (Ss) counteracted reductions in transpiration (T) and sublimation of canopy‐intercepted snow (Sc). Increased E was possibly driven by reduced canopy shading of shortwave radiation, which averaged 21 W m−2 during summer under control forest as compared to 66 W m−2 under MPB forest. These results show that abiotic vapor losses may limit widely expected streamflow increases.
- Large‐scale hydraulic tomography and joint inversion of head and
tracer data using the Principal Component Geostatistical Approach (PCGA)
- Authors: J. Lee; P. K. Kitanidis
Pages: 5410 - 5427
Abstract: The stochastic geostatistical inversion approach is widely used in subsurface inverse problems to estimate unknown parameter fields and corresponding uncertainty from noisy observations. However, the approach requires a large number of forward model runs to determine the Jacobian or sensitivity matrix, thus the computational and storage costs become prohibitive when the number of unknowns, m, and the number of observations, n increase. To overcome this challenge in large‐scale geostatistical inversion, the Principal Component Geostatistical Approach (PCGA) has recently been developed as a “matrix‐free” geostatistical inversion strategy that avoids the direct evaluation of the Jacobian matrix through the principal components (low‐rank approximation) of the prior covariance and the drift matrix with a finite difference approximation. As a result, the proposed method requires about K runs of the forward problem in each iteration independently of m and n, where K is the number of principal components and can be much less than m and n for large‐scale inverse problems. Furthermore, the PCGA is easily adaptable to different forward simulation models and various data types for which the adjoint‐state method may not be implemented suitably. In this paper, we apply the PCGA to representative subsurface inverse problems to illustrate its efficiency and scalability. The low‐rank approximation of the large‐dimensional dense prior covariance matrix is computed through a randomized eigen decomposition. A hydraulic tomography problem in which the number of observations is typically large is investigated first to validate the accuracy of the PCGA compared with the conventional geostatistical approach. Then the method is applied to a large‐scale hydraulic tomography with 3 million unknowns and it is shown that underlying subsurface structures are characterized successfully through an inversion that involves an affordable number of forward simulation runs. Lastly, we present a joint inversion of head and tracer test data using MODFLOW and MT3DMS as coupled black‐box forward simulation solvers. These applications demonstrate the advantages of the PCGA, i.e., the scalability to high‐dimensional inverse problems and the ability to utilize multiple forward models as black boxes.
- Principal Component Geostatistical Approach for large‐dimensional
- Authors: P. K. Kitanidis; J. Lee
Pages: 5428 - 5443
Abstract: The quasi‐linear geostatistical approach is for weakly nonlinear underdetermined inverse problems, such as Hydraulic Tomography and Electrical Resistivity Tomography. It provides best estimates as well as measures for uncertainty quantification. However, for its textbook implementation, the approach involves iterations, to reach an optimum, and requires the determination of the Jacobian matrix, i.e., the derivative of the observation function with respect to the unknown. Although there are elegant methods for the determination of the Jacobian, the cost is high when the number of unknowns, m, and the number of observations, n, is high. It is also wasteful to compute the Jacobian for points away from the optimum. Irrespective of the issue of computing derivatives, the computational cost of implementing the method is generally of the order of m2n, though there are methods to reduce the computational cost. In this work, we present an implementation that utilizes a matrix free in terms of the Jacobian matrix Gauss‐Newton method and improves the scalability of the geostatistical inverse problem. For each iteration, it is required to perform K runs of the forward problem, where K is not just much smaller than m but can be smaller that n. The computational and storage cost of implementation of the inverse procedure scales roughly linearly with m instead of m2 as in the textbook approach. For problems of very large m, this implementation constitutes a dramatic reduction in computational cost compared to the textbook approach. Results illustrate the validity of the approach and provide insight in the conditions under which this method perform best.
- The role of tributary relative timing and sequencing in controlling large
- Authors: Ian Pattison; Stuart N. Lane, Richard J. Hardy, Sim M. Reaney
Pages: 5444 - 5458
Abstract: Hydrograph convolution is a product of tributary inputs from across the watershed. The time‐space distribution of precipitation, the biophysical processes that control the conversion of precipitation to runoff and channel flow conveyance processes, are heterogeneous and different areas respond to rainfall in different ways. We take a subwatershed approach to this and account for tributary flow magnitude, relative timing, and sequencing. We hypothesize that as the scale of the watershed increases so we may start to see systematic differences in subwatershed hydrological response. We test this hypothesis for a large flood (T > 100 years) in a large watershed in northern England. We undertake a sensitivity analysis of the effects of changing subwatershed hydrological response using a hydraulic model. Delaying upstream tributary peak flow timing to make them asynchronous from downstream subwatersheds reduced flood magnitude. However, significant hydrograph adjustment in any one subwatershed was needed for meaningful reductions in stage downstream, although smaller adjustments in multiple tributaries resulted in comparable impacts. For larger hydrograph adjustments, the effect of changing the timing of two tributaries together was lower than the effect of changing each one separately. For smaller adjustments synergy between two subwatersheds meant the effect of changing them together could be greater than the sum of the parts. Thus, this work shows that while the effects of modifying biophysical catchment properties diminishes with scale due to dilution effects, their impact on relative timing of tributaries may, if applied in the right locations, be an important element of flood management.
- Hydrodynamic parameters of a sandy soil determined by
ground‐penetrating radar inside a single ring infiltrometer
- Authors: Emmanuel Léger; Albane Saintenoy, Yves Coquet
Pages: 5459 - 5474
Abstract: This study shows how Mualem‐van Genuchten (M‐vG) parameters can be obtained from GPR data acquired during water infiltration from a single ring infiltrometer in the case of a sandy soil. Water content profiles were generated at various time steps using HYDRUS‐1D, based on particular values of the M‐vG parameters and were converted to dielectric permittivity profiles using the Complex Refractive Index Method. The GprMax suite of programs was used to generate radargrams and to follow the wetting front progression in depth using the arrival time of the electromagnetic waves recorded by a ground‐penetrating radar (GPR). Theoretically, the 1‐D time convolution between reflectivity and GPR signal at any infiltration time step is related to the peak of the reflected signal recorded in the corresponding trace in the radargram. We used this relationship to invert the M‐vG parameters for constant and falling head infiltrations using the Shuffled Complex Evolution (SCE‐UA) algorithm. The method is presented on synthetic examples and on experiments carried out for a sandy soil. The parameters inverted are compared with values obtained in laboratory on soil samples and with disk infiltrometer measurements.
- Analytical optimization of demand management strategies across all urban
water use sectors
- Authors: Kenneth Friedman; James P. Heaney, Miguel Morales, John Palenchar
Pages: 5475 - 5491
Abstract: An effective urban water demand management program can greatly influence both peak and average demand and therefore long‐term water supply and infrastructure planning. Although a theoretical framework for evaluating residential indoor demand management has been well established, little has been done to evaluate other water use sectors such as residential irrigation in a compatible manner for integrating these results into an overall solution. This paper presents a systematic procedure to evaluate the optimal blend of single family residential irrigation demand management strategies to achieve a specified goal based on performance functions derived from parcel level tax assessor's data linked to customer level monthly water billing data. This framework is then generalized to apply to any urban water sector, as exponential functions can be fit to all resulting cumulative water savings functions. Two alternative formulations are presented: maximize net benefits, or minimize total costs subject to satisfying a target water savings. Explicit analytical solutions are presented for both formulations based on appropriate exponential best fits of performance functions. A direct result of this solution is the dual variable which represents the marginal cost of water saved at a specified target water savings goal. A case study of 16,303 single family irrigators in Gainesville Regional Utilities utilizing high quality tax assessor and monthly billing data along with parcel level GIS data provide an illustrative example of these techniques. Spatial clustering of targeted homes can be easily performed in GIS to identify priority demand management areas.
- Spatiotemporal flood sensitivity to annual precipitation: Evidence for
- Authors: Rui A. P. Perdigão; Günter Blöschl
Pages: 5492 - 5509
Abstract: This study investigates the sensitivity of floods to annual precipitation in space and time and evaluates quantitative signs of landscape‐climate coevolution. For that purpose, a spatiotemporal sensitivity analysis is performed at regional scale using data from 804 catchments in Austria from 1976 to 2008. Results show that flood peaks are more responsive to spatial (regional) than to temporal (decadal) variability. Space‐wise a 10% increase in precipitation leads to a 23% increase in flood peaks in Austria, whereas time‐wise a 10% increase in precipitation leads to an increase of just 6% in flood peaks. Catchments from dry lowlands and high wetlands exhibit similarity between the spatial and temporal sensitivities (spatiotemporal symmetry) and low landscape‐climate codependence. This suggests that such regions are not coevolving significantly. However, intermediate regions show differences between those sensitivities (symmetry breaks) and higher landscape‐climate codependence, suggesting undergoing coevolution. A new coevolution index is then proposed relating spatiotemporal symmetry with relative characteristic celerities. The descriptive assessment of coevolution is complemented by a simple dynamical model of landscape‐climate coevolution, in which landform evolution processes take place at the millennial scale (slow dynamics), and climate adjusts in years to decades (fast dynamics). Coevolution is expressed by the interplay between slow and fast dynamics, represented, respectively, by spatial and temporal characteristics. The model captures key features of the joint landscape‐climate distribution, supporting the descriptive assessment. This paper ultimately brings to light that coevolution needs to be taken into account through characteristic celerities in space‐time trading of regional hydrology.
- Analytical model for flow duration curves in seasonally dry climates
- Authors: Marc F. Müller; David N. Dralle, Sally E. Thompson
Pages: 5510 - 5531
Abstract: Flow duration curves (FDC) display streamflow values against their relative exceedance time. They provide critical information for watershed management by representing the variation in the availability and reliability of surface water to supply ecosystem services and satisfy anthropogenic needs. FDCs are particularly revealing in seasonally dry climates, where surface water supplies are highly variable. While useful, the empirical computation of FDCs is data intensive and challenging in sparsely gauged regions, meaning that there is a need for robust, predictive models to evaluate FDCs with simple parameterization. Here, we derive a process‐based analytical expression for FDCs in seasonally dry climates. During the wet season, streamflow is modeled as a stochastic variable driven by rainfall, following the stochastic analytical model of Botter et al. (2007a). During the dry season, streamflow is modeled as a deterministic recession with a stochastic initial condition that accounts for the carryover of catchment storage across seasons. The resulting FDC model is applied to 38 catchments in Nepal, coastal California, and Western Australia, where FDCs are successfully modeled using five physically meaningful parameters with minimal calibration. A Monte Carlo analysis revealed that the model is robust to deviations from its assumptions of Poissonian rainfall, exponentially distributed response times and constant seasonal timing. The approach successfully models period‐of‐record FDCs and allows interannual and intra‐annual sources of variations in dry season streamflow to be separated. The resulting median annual FDCs and confidence intervals allow the simulation of the consequences of interannual flow variations for infrastructure projects. We present an example using run‐of‐river hydropower in Nepal as a case study.
- Annual bank and point bar morphodynamics of a meandering river determined
by high‐accuracy multitemporal laser scanning and flow data
- Authors: E. Lotsari; M. Vaaja, C. Flener, H. Kaartinen, A. Kukko, E. Kasvi, H. Hyyppä, J. Hyyppä, P. Alho
Pages: 5532 - 5559
Abstract: The knowledge has been insufficient concerning the effects of peak flows, and local bend and flow characteristics on annual morphodynamics of consecutive bends in meandering rivers. Therefore, it was determined how flow peak magnitude and duration affect morphodynamics, how the short‐term spatial evolution of a given meander bend associates with the neighboring bends, and how local bend and flow characteristics affect morphodynamics. The annual bank and point bar morphodynamics of eight consecutive bends of a subarctic meandering river were analyzed between 2009 and 2012 on the basis of high‐accuracy multitemporal data, measured by mobile and terrestrial laser scanning and an Acoustic Doppler Current Profiler. According to the results, multiple years of highly accurate data are crucial for a broader picture of meandering channel evolution. The results showed for the first time in detail that none of the years were similar in terms of point bar and bank morphodynamics. The duration of point bar submergence and maximum water stage was more important for evolution of the meandering channel than the local effects of each bend. The detailed topographical data of the present study confirmed that the higher the flow and water stage peak the more deposition occurred on point bars. More importantly, the independence of the short‐term spatial evolution of meander bends from the association with neighboring bends was confirmed. Erosion patterns did not relate particularly to the sinuosity or radius of curvature. A clear relation between velocity and bend curvature, on which some meander migration models rely, was not found.
- Absolute versus temporal anomaly and percent of saturation soil moisture
spatial variability for six networks worldwide
- Authors: L. Brocca; G. Zucco, H. Mittelbach, T. Moramarco, S. I. Seneviratne
Pages: 5560 - 5576
Abstract: The analysis of the spatial‐temporal variability of soil moisture can be carried out considering the absolute (original) soil moisture values or relative values, such as the percent of saturation or temporal anomalies. Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum absolute values, even though in relative terms their temporal patterns are very similar. In these cases, the analysis considering absolute compared with percent of saturation or temporal anomaly soil moisture values can provide very different results with significant consequences for their use in hydrological applications and climate science. In this study, in situ observations from six soil moisture networks in Italy, Spain, France, Switzerland, Australia, and United States are collected and analyzed to investigate the spatial soil moisture variability over large areas (250–150,000 km2). Specifically, the statistical and temporal stability analyses of soil moisture have been carried out for absolute, temporal anomaly, and percent of saturation values (using two different formulations for temporal anomalies). The results highlight that the spatial variability of the soil moisture dynamic (i.e., temporal anomalies) is significantly lower than that of the absolute soil moisture values. The spatial variance of the time‐invariant component (temporal mean of each site) is the predominant contribution to the total spatial variance of absolute soil moisture data. Moreover, half of the networks show a minimum in the spatial variability for intermediate conditions when the temporal anomalies are considered, in contrast with the widely recognized behavior of absolute soil moisture data. The analyses with percent saturation data show qualitatively similar results as those for the temporal anomalies because of the applied normalization which reduces spatial variability induced by differences in mean absolute soil moisture only. Overall, we find that the analysis of the spatial‐temporal variability of absolute soil moisture does not apply to temporal anomalies or percent of saturation values.
- Catchments as simple dynamical systems: A case study on methods and data
requirements for parameter identification
- Authors: L. A. Melsen; A. J. Teuling, S. W. Berkum, P. J. J. F. Torfs, R. Uijlenhoet
Pages: 5577 - 5596
Abstract: In many rainfall‐runoff models, at least some calibration of model parameters has to take place. Especially for ungauged or poorly gauged basins this can be problematic, because there is little or no data available for calibration. A possible solution to overcome the problems caused by data scarcity is to set up a measurement campaign for a limited time period. In this study, we determine the minimum amount of data required to determine robust parameter values for a simple model with two parameters. The model is constructed such that the parameters can be determined not only with automatic calibration, but also by recession analysis and a priori from Boussinesq theory. The model has been applied to a research catchment in Switzerland. For automatic calibration and recession analysis, one season (5 months) is found to be sufficient to give robust parameters for simulation of high flows over the full observation period. For automatic calibration, this should be the season with the highest precipitation, for recession analysis the season with least evapotranspiration. The Boussinesq equation is able to give good parameter estimates for modeling high flows, but detailed in situ knowledge of the catchment is required. Automatic calibration outperforms recession analysis and Boussinesq theory by far when it comes to parameter estimation with a focus on prediction of low flows. It was shown that a single set of parameters cannot simultaneously describe high and low flows with a reasonable accuracy, suggesting that more than two parameters are needed to characterize subsurface properties.
- A diameter‐sensitive flow entropy method for reliability
consideration in water distribution system design
- Authors: Haixing Liu; Dragan Savić, Zoran Kapelan, Ming Zhao, Yixing Yuan, Hongbin Zhao
Pages: 5597 - 5610
Abstract: Flow entropy is a measure of uniformity of pipe flows in water distribution systems. By maximizing flow entropy one can identify reliable layouts or connectivity in networks. In order to overcome the disadvantage of the common definition of flow entropy that does not consider the impact of pipe diameter on reliability, an extended definition of flow entropy, termed as diameter‐sensitive flow entropy, is proposed. This new methodology is then assessed by using other reliability methods, including Monte Carlo Simulation, a pipe failure probability model, and a surrogate measure (resilience index) integrated with water demand and pipe failure uncertainty. The reliability assessment is based on a sample of WDS designs derived from an optimization process for each of the two benchmark networks. Correlation analysis is used to evaluate quantitatively the relationship between entropy and reliability. To ensure reliability, a comparative analysis between the flow entropy and the new method is conducted. The results demonstrate that the diameter‐sensitive flow entropy shows consistently much stronger correlation with the three reliability measures than simple flow entropy. Therefore, the new flow entropy method can be taken as a better surrogate measure for reliability and could be potentially integrated into the optimal design problem of WDSs. Sensitivity analysis results show that the velocity parameters used in the new flow entropy has no significant impact on the relationship between diameter‐sensitive flow entropy and reliability.
- Snowpack regimes of the Western United States
- Authors: Ernesto Trujillo; Noah P. Molotch
Pages: 5611 - 5623
Abstract: Snow accumulation and melt patterns play a significant role in the water, energy, carbon, and nutrient cycles in the montane environments of the Western United States. Recent studies have illustrated that changes in the snow/rainfall apportionments and snow accumulation and melt patterns may occur as a consequence of changes in climate in the region. In order to understand how these changes may affect the snow regimes of the region, the current characteristics of the snow accumulation and melt patterns must be identified. Here we characterize the snow water equivalent (SWE) curve formed by the daily SWE values at 766 snow pillow stations in the Western United States, focusing on several metrics of the yearly SWE curves and the relationships between the different metrics. The metrics are the initial snow accumulation and snow disappearance dates, the peak snow accumulation and date of peak, the length of the snow accumulation season, the length of the snowmelt season, and the snow accumulation and snowmelt slopes. Three snow regimes emerge from these results: a maritime, an intermountain, and a continental regime. The maritime regime is characterized by higher maximum snow accumulations reaching 300 cm and shorter accumulation periods of less than 220 days. Conversely, the continental regime is characterized by lower maximum accumulations below 200 cm and longer accumulation periods reaching over 260 days. The intermountain regime lies in between. The regions that show the characteristics of the maritime regime include the Cascade Mountains, the Klamath Mountains, and the Sierra Nevada Mountains. The intermountain regime includes the Eastern Cascades slopes and foothills, the Blue Mountains, Northern and Central basins and ranges, the Columbia Mountains/Northern Rockies, the Idaho Batholith, and the Canadian Rockies. Lastly, the continental regime includes the Middle and Southern Rockies, and the Wasatch and Uinta Mountains. The implications of snow regime classification are discussed in the context of possible changes in accumulation and melt patterns associated with regional warming.
- Cholera in the Lake Kivu region (DRC): Integrating remote sensing and
spatially explicit epidemiological modeling
- Authors: Flavio Finger; Allyn Knox, Enrico Bertuzzo, Lorenzo Mari, Didier Bompangue, Marino Gatto, Ignacio Rodriguez‐Iturbe, Andrea Rinaldo
Pages: 5624 - 5637
Abstract: Mathematical models of cholera dynamics can not only help in identifying environmental drivers and processes that influence disease transmission, but may also represent valuable tools for the prediction of the epidemiological patterns in time and space as well as for the allocation of health care resources. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. They have been ravaging the shore of Lake Kivu in the east of the country repeatedly during the last decades. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of the lake. Remotely sensed data sets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multiyear data set of reported cholera cases. The best fourteen models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via proper cross validation. Among these, the one accounting for seasonality, El Niño Southern Oscillation, precipitation and human mobility outperforms the others in cross validation. Some drivers (such as human mobility and rainfall) are retained only by a few models, possibly indicating that the mechanisms through which they influence cholera dynamics in the area will have to be investigated further.
- Patterns of similarity of seasonal water balances: A window into
streamflow variability over a range of time scales
- Authors: Wouter R. Berghuijs; Murugesu Sivapalan, Ross A. Woods, Hubert H. G. Savenije
Pages: 5638 - 5661
Abstract: Recent hydrologic synthesis efforts have presented evidence that the seasonal water balance is at the core of overall catchment responses, and understanding it will assist in predicting signatures of streamflow variability at other time scales, including interannual variability, the flow duration curve, low flows, and floods. In this study, we group 321 catchments located across the continental U.S. into several clusters with similar seasonal water balance behavior. We then delineate the boundaries between these clusters on the basis of a similarity framework based on three hydroclimatic indices that represent aridity, precipitation timing, and snowiness. The clustering of catchments based on the seasonal water balance has a strong relationship not only with regional patterns of the three climate indices but also with regional ecosystem, soil, and vegetation classes, which point to the strong dependence of these physiographic characteristics on seasonal climate variations and the hydrologic regimes. Building on these catchment clusters, we demonstrate that the seasonal water balance does have an imprint on signatures of streamflow variability over a wide range of time scales (daily to decadal) and a wide range of states (low flows to floods). The seasonal water balance is well integrated into variability at seasonal and longer time scales, but is only partly reflected in the signatures at shorter time scales, including flooding responses. Overall, the seasonal water balance has proven to be a similarity measure that serves as a link between both short‐term hydrologic responses and long‐term adaptation of the landscape with climate.
- Rescuing degrading aquifers in the Central Coastal Plain of North Carolina
(USA): Just process, effective groundwater management policy, and
- Authors: Alex K. Manda; Wendy A. Klein
Pages: 5662 - 5677
Abstract: Strategic management of degrading coastal aquifers in eastern North Carolina (USA) became imperative after a severe imbalance occurred between withdrawal and recharge rates. To ameliorate this growing problem, an aggressive water policy was developed through public input by creating the Central Coastal Plain Capacity Use Area (CCPCUA) to maintain beneficial use of groundwater resources. Insights from social psychology, and socio‐legal studies are used to evaluate how procedural justice and public participation played major roles to resolving groundwater resource management problems. A mixed methods approach uses archival data and interviews with various rule‐making participants to assess the process of stakeholder involvement that led to creation of the policy. In addition, data analysis techniques are utilized to evaluate the effects of the policy on aquifer health (through water levels) over a ∼10 year period. Results suggest that not only did a stakeholder group participate in a process that was deemed fair, understandable, and relatively easy to administer for users and regulators, but public participation resulted in an effective plan that ensures the long‐term sustainable use of groundwater. Declining groundwater withdrawals and recovering water levels suggest that the rule is achieving its intended goal of protecting the aquifers from depletion and degradation. This paper touches on global themes that are essential to water demand and consumption, water management techniques, and water resources protection.
- Modeling biofilm dynamics and hydraulic properties in variably saturated
soils using a channel network model
- Authors: Ravid Rosenzweig; Alex Furman, Carlos Dosoretz, Uri Shavit
Pages: 5678 - 5697
Abstract: Biofilm effects on water flow in unsaturated environments have largely been ignored in the past. However, intensive engineered systems that involve elevated organic loads such as wastewater irrigation, effluent recharge, and bioremediation processes make understanding how biofilms affect flow highly important. In the current work, we present a channel‐network model that incorporates water flow, substrate transport, and biofilm dynamics to simulate the alteration of soil hydraulic properties, namely water retention and conductivity. The change in hydraulic properties due to biofilm growth is not trivial and depends highly on the spatial distribution of the biofilm development. Our results indicate that the substrate mass transfer coefficient across the water‐biofilm interface dominates the spatiotemporal distribution of biofilm. High mass transfer coefficients lead to uncontrolled biofilm growth close to the substrate source, resulting in preferential clogging of the soil. Low mass transfer coefficients, on the other hand, lead to a more uniform biofilm distribution. The first scenario leads to a dramatic reduction of the hydraulic conductivity with almost no change in water retention, whereas the second scenario has a smaller effect on conductivity but a larger influence on retention. The current modeling approach identifies key factors that still need to be studied and opens the way for simulation and optimization of processes involving significant biological activity in unsaturated soils.
- Global‐scale assessment of groundwater depletion and related
groundwater abstractions: Combining hydrological modeling with information
from well observations and GRACE satellites
- Authors: Petra Döll; Hannes Müller Schmied, Carina Schuh, Felix T. Portmann, Annette Eicker
Pages: 5698 - 5720
Abstract: Groundwater depletion (GWD) compromises crop production in major global agricultural areas and has negative ecological consequences. To derive GWD at the grid cell, country, and global levels, we applied a new version of the global hydrological model WaterGAP that simulates not only net groundwater abstractions and groundwater recharge from soils but also groundwater recharge from surface water bodies in dry regions. A large number of independent estimates of GWD as well as total water storage (TWS) trends determined from GRACE satellite data by three analysis centers were compared to model results. GWD and TWS trends are simulated best assuming that farmers in GWD areas irrigate at 70% of optimal water requirement. India, United States, Iran, Saudi Arabia, and China had the highest GWD rates in the first decade of the 21st century. On the Arabian Peninsula, in Libya, Egypt, Mali, Mozambique, and Mongolia, at least 30% of the abstracted groundwater was taken from nonrenewable groundwater during this time period. The rate of global GWD has likely more than doubled since the period 1960–2000. Estimated GWD of 113 km3/yr during 2000–2009, corresponding to a sea level rise of 0.31 mm/yr, is much smaller than most previous estimates. About 15% of the globally abstracted groundwater was taken from nonrenewable groundwater during this period. To monitor recent temporal dynamics of GWD and related water abstractions, GRACE data are best evaluated with a hydrological model that, like WaterGAP, simulates the impact of abstractions on water storage, but the low spatial resolution of GRACE remains a challenge.
- Electrical‐hydraulic relationships observed for unconsolidated
sediments in the presence of a cobble framework
- Authors: Lee Slater; Warren Barrash, Jeanette Montrey, Andrew Binley
Pages: 5721 - 5742
Abstract: Mechanistic models now exist to predict hydraulic conductivity (K) from the spectral‐induced polarization (SIP) response of granular media. We examined the predictions of such a model on unconsolidated coarse fluvial sediments and compared them to those obtained with a modified Kozeny‐Carman (KC) model. Samples were retrieved from the Boise Hydrogeophysical Research Site (BHRS), located on a gravel bar adjacent to the Boise River, Idaho. A sample holder (0.102 m diameter and 0.12 m in length) was designed to include the cobble framework in reconstituted samples representing the primary stratigraphic units defined based on porosity variation at this site. SIP (0.001–1000 Hz) and K (from Darcy tests) measurements were recorded for 12 samples, with SIP measurements made as a function of pore fluid conductivity (3–300 mS/m), grain size distribution (GSD), and total porosity. K prediction with the KC model was improved after discounting of the cobble framework and multiplying by the tortuosity resulting from matrix “capillaries” around the cobbles, resulting in estimates within a factor of 5 of the measurements. K prediction with a mechanistic SIP model based on Stern layer polarization (SLP model) that requires an estimate of the GSD also required discounting for the cobble framework to obtain estimates within 0.5 orders of magnitude of the measurements. Similarly, the SLP model overpredicts the measured imaginary conductivity (
σ″) unless the cobble framework is discounted, which then results in estimates of
σ″ within a factor of 2 of the measurements. This can be explained by the fact that the cobbles polarize at frequencies well below the minimum measurement frequency (0.001 Hz). The SLP model for K prediction parameterized in terms of the formation factor and imaginary conductivity performed well for the 10 samples with a cobble framework without modification as the imaginary conductivity directly senses the matrix grain size characteristics, whereas the formation factor captures the porosity reduction and tortuosity resulting from the presence of the cobble framework (capillary tortuosity). Our findings suggest that the estimation of contrasts in K in coarse sediments may be achievable through measurements of electrical properties after appropriate consideration of the cobble fraction.
- Effects of heterogeneous soil‐water diffusivity on vegetation
- Authors: H. Yizhaq; S. Sela, T. Svoray, S. Assouline, G. Bel
Pages: 5743 - 5758
Abstract: Many mathematical models have been proposed to explain the emergence of vegetation patterns in arid and semiarid environments, but only a few of them take into account the heterogeneity in the system properties. Here we present a rigorous study of the effects of heterogeneous soil‐water diffusivity on vegetation patterns, using two mathematical models. The two models differ in the pattern‐forming feedback that they capture; one model captures the infiltration contrast between vegetated and bare‐soil domains, whereas the other model captures the increased growth rate of denser vegetation due to an enhanced ability to extract water from the soil. In both models, the most significant effect of the heterogeneity on the soil‐water diffusivity is the increased durability of patterned vegetation to a reduced precipitation rate. An additional effect is that the heterogeneity makes the desertification process, namely, the transition from a spotted vegetation pattern to a bare‐soil state, more gradual than in the homogeneous system. Our findings suggest that the heterogeneity cannot be neglected in the study of critical transitions in heterogeneous ecosystems and, particularly, in the study of the desertification process due to climate changes or anthropogenic disturbances.
- Solute transport in aquifers of arbitrary variability: A time‐domain
random walk formulation
- Authors: Vladimir Cvetkovic; Aldo Fiori, Gedeon Dagan
Pages: 5759 - 5773
Abstract: Solute transport in three‐dimensional aquifers, with spatially varying hydraulic conductivity of arbitrary point distribution is investigated. The basis of our study is a multiindicator model (MIM) representation of the heterogeneity, combined with a self‐consistent approximation for groundwater flow and particle transport. A time‐domain random walk (TDRW) approach is presented for computing the expected mass arrival along the longitudinal transport direction that is simple and honors the hydrodynamics of flow for any variability. Using hydraulic conductivity measurements at the MADE site and the MIM, it is shown that the travel time distribution for large variability, cannot be well reproduced by the common distributions used for modeling hydrological transport, such as the log‐normal distribution, or the inverse‐Gaussian distribution. The proposed TDRW approach directly relates to the Lagrangian trajectory formulation and is appropriate for applications where occurrence of negative flow velocities is small. These results open new possibilities for modeling solute transport in aquifers of arbitrary variability by the time‐domain random walk that can readily account for a wide range of mass transfer reactions.
- The delivery of dissolved organic carbon from a forested hillslope to a
headwater stream in southeastern Pennsylvania, USA
- Authors: Yi Mei; George M. Hornberger, Louis A. Kaplan, J. Denis Newbold, Anthony K. Aufdenkampe
Pages: 5774 - 5796
Abstract: Riparian soils, rich in organic carbon, act as a source of dissolved organic carbon (DOC) to the adjacent stream, but the hydrologic factors that control the delivery of DOC are not well characterized. A mechanistic two‐dimensional, variably saturated flow and reactive transport finite element model (FEM) was developed to explore both biodegradable DOC (BDOC) and refractory DOC (RDOC) delivery processes during storms for a hillslope transect in a southeastern Pennsylvania Piedmont watershed. The model indicated that DOC concentrations in outflow from a hillslope peaked on the falling limb of the discharge hydrograph, a temporal sequence consistent with a flushing hypothesis. Factors that control the lag time between the stream water peak discharge and peak DOC concentration were analyzed using a Monte Carlo simulation coupled with a multiple linear regression. The results are consistent with previous studies showing that the majority of DOC delivered to a stream during storms originates from the riparian zone. Further, the model suggests that the duration of the flood wave and hydraulic properties of the riparian soil play important roles in controlling the lag time between peak discharge and peak DOC concentration in outflow from a hillslope.
- On the upscaling of chemical transport in fractured rock
- Authors: Vladimir Cvetkovic; Hrvoje Gotovac
Pages: 5797 - 5816
Abstract: The impact of flow heterogeneity on chemical transport from single to multiple fractures is investigated. The emphasis is on the dynamic nature of the specific surface area (SSA) due to heterogeneity of the flow, relative to a purely geometrical definition. The flow‐dependent SSA is interpreted probabilistically, following inert tracer particles along individual fractures. Upscaling to a fracture network is proposed as a time domain random walk based on the statistics of SSA for single fractures. Statistics of SSA are investigated for three correlation structures of transmissivity: multi‐Gaussian and two non‐multi‐Gaussian. The mean of SSA stabilizes after ∼20 fractures at different values depending on whether the cubic or quadratic hydraulic law is assumed. The results are tested against comprehensive DFN simulations based on site‐specific data but also against direct estimates from a wider range of tracer tests. The proposed time domain random walk methodology sets bounds for SSA in a 75% confidence interval as ∼1800 1/m and 27,000 1/m, with a median of 14,000 1/m; these values capture reasonably well both the DFN simulation and tracer test SSA data. Presented results may be particularly relevant when quantifying uncertainty of reactive transport modeling in fractured rock.
- Coping with model error in variational data assimilation using optimal
- Authors: Lipeng Ning; Francesca P. Carli, Ardeshir Mohammad Ebtehaj, Efi Foufoula‐Georgiou, Tryphon T. Georgiou
Pages: 5817 - 5830
Abstract: Classical variational data assimilation methods address the problem of optimally combining model predictions with observations in the presence of zero‐mean Gaussian random errors. However, in many natural systems, uncertainty in model structure and/or model parameters often results in systematic errors or biases. Prior knowledge about such systematic model error for parametric removal is not always feasible in practice, limiting the efficient use of observations for improved prediction. The main contribution of this work is to advocate the relevance of transportation metrics for quantifying nonrandom model error in variational data assimilation for nonnegative natural states and fluxes. Transportation metrics (also known as Wasserstein metrics) originate in the theory of Optimal Mass Transport (OMT) and provide a nonparametric way to compare distributions which is natural in the sense that it penalizes mismatch in the values and relative position of “masses” in the two distributions. We demonstrate the promise of the proposed methodology using 1‐D and 2‐D advection‐diffusion dynamics with systematic error in the velocity and diffusivity parameters. Moreover, we combine this methodology with additional regularization functionals, such as the
ℓ1‐norm of the state in a properly chosen domain, to incorporate both model error and potential prior information in the presence of sparsity or sharp fronts in the underlying state of interest.
- Analytical solutions for flow in porous media with multicomponent cation
- Authors: Ashwin Venkatraman; Marc A. Hesse, Larry W. Lake, Russell T. Johns
Pages: 5831 - 5847
Abstract: Multicomponent cation exchange reactions have important applications in groundwater remediation, disposal of nuclear wastes as well as enhanced oil recovery. The hyperbolic theory of conservation laws can be used to explain the nature of displacements observed during flow with cation exchange reactions between flowing aqueous phase and stationary solid phase. Analytical solutions have been developed to predict the effluent profiles for a particular case of heterovalent cations (Na+, Ca2+ and Mg2+) and an anion (Cl−) for any combination of constant injection and constant initial composition using this theory. We assume local equilibrium, neglect dispersion and model the displacement as a Riemann problem using mass action laws, the charge conservation equation and the cation exchange capacity equation. The theoretical predictions have been compared with experimental data available at two scales—the laboratory scale and the field scale. The theory agrees well with the experimental data at both scales. Analytical theory predictions show good agreement with numerical model, developed using finite differences.
- Systematic assessment of the uncertainty in integrated surface
water‐groundwater modeling based on the probabilistic collocation
- Authors: Bin Wu; Yi Zheng, Yong Tian, Xin Wu, Yingying Yao, Feng Han, Jie Liu, Chunmiao Zheng
Pages: 5848 - 5865
Abstract: Systematic uncertainty analysis (UA) has rarely been conducted for integrated modeling of surface water‐groundwater (SW‐GW) systems, which is subject to significant uncertainty, especially at a large basin scale. The main objective of this study was to explore an innovative framework in which a systematic UA can be effectively and efficiently performed for integrated SW‐GW models of large river basins and to illuminate how process understanding, model calibration, data collection, and management can benefit from such a systematic UA. The framework is based on the computationally efficient Probabilistic Collocation Method (PCM) linked with a complex simulation model. The applicability and advantages of the framework were evaluated and validated through an integrated SW‐GW model for the Zhangye Basin in the middle Heihe River Basin, northwest China. The framework for systematic UA allows for a holistic assessment of the modeling uncertainty, yielding valuable insights into the hydrological processes, model structure, data deficit, and potential effectiveness of management. The study shows that, under the complex SW‐GW interactions, the modeling uncertainty has great spatial and temporal variabilities and is highly output‐dependent. Overall, this study confirms that a systematic UA should play a critical role in integrated SW‐GW modeling of large river basins, and the PCM‐based approach is a promising option to fulfill this role.
- Water resources of the Black Sea Basin at high spatial and temporal
- Authors: Elham Rouholahnejad; Karim C. Abbaspour, Raghvan Srinivasan, Victor Bacu, Anthony Lehmann
Pages: 5866 - 5885
Abstract: The pressure on water resources, deteriorating water quality, and uncertainties associated with the climate change create an environment of conflict in large and complex river system. The Black Sea Basin (BSB), in particular, suffers from ecological unsustainability and inadequate resource management leading to severe environmental, social, and economical problems. To better tackle the future challenges, we used the Soil and Water Assessment Tool (SWAT) to model the hydrology of the BSB coupling water quantity, water quality, and crop yield components. The hydrological model of the BSB was calibrated and validated considering sensitivity and uncertainty analysis. River discharges, nitrate loads, and crop yields were used to calibrate the model. Employing grid technology improved calibration computation time by more than an order of magnitude. We calculated components of water resources such as river discharge, infiltration, aquifer recharge, soil moisture, and actual and potential evapotranspiration. Furthermore, available water resources were calculated at subbasin spatial and monthly temporal levels. Within this framework, a comprehensive database of the BSB was created to fill the existing gaps in water resources data in the region. In this paper, we discuss the challenges of building a large‐scale model in fine spatial and temporal detail. This study provides the basis for further research on the impacts of climate and land use change on water resources in the BSB.
- Derivation of lowland riparian wetland deposit architecture using
geophysical image analysis and interface detection
- Authors: J. E. Chambers; P. B. Wilkinson, S. Uhlemann, J. P. R. Sorensen, C. Roberts, A. J. Newell, W. O. C. Ward, A. Binley, P. J. Williams, D. C. Gooddy, G. Old, L. Bai
Pages: 5886 - 5905
Abstract: For groundwater‐surface water interactions to be understood in complex wetland settings, the architecture of the underlying deposits requires investigation at a spatial resolution sufficient to characterize significant hydraulic pathways. Discrete intrusive sampling using conventional approaches provides insufficient sample density and can be difficult to deploy on soft ground. Here a noninvasive geophysical imaging approach combining three‐dimensional electrical resistivity tomography (ERT) and the novel application of gradient and isosurface‐based edge detectors is considered as a means of illuminating wetland deposit architecture. The performance of three edge detectors were compared and evaluated against ground truth data, using a lowland riparian wetland demonstration site. Isosurface‐based methods correlated well with intrusive data and were useful for defining the geometries of key geological interfaces (i.e., peat/gravels and gravels/Chalk). The use of gradient detectors approach was unsuccessful, indicating that the assumption that the steepest resistivity gradient coincides with the associated geological interface can be incorrect. These findings are relevant to the application of this approach in settings with a broadly layered geology with strata of contrasting resistivities. In addition, ERT revealed substantial structures in the gravels related to the depositional environment (i.e., braided fluvial system) and a complex distribution of low‐permeability putty Chalk at the bedrock surface—with implications for preferential flow and variable exchange between river and groundwater systems. These results demonstrate that a combined approach using ERT and edge detectors can provide valuable information to support targeted monitoring and inform hydrological modeling of wetlands.
- A simple and effective method for quantifying spatial anisotropy of time
series of precipitation fields
- Authors: Tero J. Niemi; Teemu Kokkonen, Alan W. Seed
Pages: 5906 - 5925
Abstract: The spatial shape of a precipitation event has an important role in determining the catchment's hydrological response to a storm. To be able to generate stochastic design storms with a realistic spatial structure, the anisotropy of the storm has to be quantified. In this paper, a method is proposed to estimate the anisotropy of precipitation fields, using the concept of linear Generalized Scale Invariance (GSI). The proposed method is based on identifying the values of GSI parameters that best describe isolines of constant power on the two‐dimensional power spectrum of the fields. The method is evaluated using two sets of simulated fields with known anisotropy and a measured precipitation event with an unknown anisotropy from Brisbane, Australia. It is capable of accurately estimating the anisotropy parameters of simulated nonzero fields, whereas introducing the rain‐no rain intermittency alters the power spectra of the fields and slightly reduces the accuracy of the parameter estimates. The parameters estimated for the measured event correspond well with the visual observations on the spatial structure of the fields. The method requires minimum amount of decision making and user interaction, making it suitable for analyzing anisotropy of storm events consisting of long time series of fields with a changing spatial structure.
- Modeling intersite dependence for regional frequency analysis of extreme
- Authors: Jérôme Weiss; Pietro Bernardara, Michel Benoit
Pages: 5926 - 5940
Abstract: The duration of observation at a site of interest is generally too low to reliably estimate marine extremes. Regional frequency analysis (RFA), by exploiting the similarity between sites, can help to reduce uncertainties inherent to local analyses. Extreme observations in a homogeneous region are especially assumed to follow a common regional distribution, up to a local index. The regional pooling method, by gathering observations from different sites into a regional sample, can be employed to estimate the regional distribution. However, such a procedure may be highly affected by intersite dependence in the regional sample. This paper derives a theoretical model of intersite dependence, dedicated to the regional pooling method in a “peaks over threshold” framework. This model expresses the tendency of sites to display a similar behavior during a storm generating extreme observations, by describing both the storm propagation in the region and the storm intensity. The proposed model allows the assessment of (i) the regional effective duration of the regional sample and (ii) different regional hazards, e.g., return periods of storms. An application to the estimation of extreme significant wave heights from the numerical sea‐state database ANEMOC‐2 is provided, where different patterns of regional dependence are highlighted.
- Integrated mathematical modeling of hydrological and hydrodynamic response
to rainfall events in rural lowland catchments
- Authors: D. P. Viero; P. Peruzzo, L. Carniello, A. Defina
Pages: 5941 - 5957
Abstract: In rural lowland catchments, negligible topographic gradients and possible interactions between overland and channel flows complicate efforts to predict flood formation, propagation, and inundation. In this study, we demonstrate that an approach in which a two‐dimensional shallow water model is coupled with a two‐dimensional model for the saturated flow in the topsoil layer can accurately reproduce floods in such a lowland catchment. The topsoil porous layer is treated as a confined aquifer where water ponds on the ground surface and as an unconfined aquifer elsewhere. The model includes infiltration from the ground surface into the topsoil layer and downward percolation out of the topsoil layer. The equations of both surface and subsurface models are suitably averaged over a representative elementary area to yield a subgrid model for the coupled surface‐subsurface flow. Field data collected in two rural lowland catchments in the North‐East of Italy are used to evaluate the model performance. The good agreement between computed and measured discharge at the catchments' outlet and the agreement between predicted and surveyed spatial pattern of inundated areas indicate that the model effectively reproduces overland flow and efficiently accounts for the surface‐subsurface flow interaction and the relevant subsurface processes.
- A multimodel regression‐sampling algorithm for generating rich
monthly streamflow scenarios
- Authors: Chao Li; Vijay P. Singh
Pages: 5958 - 5979
Abstract: This paper presents a multimodel regression‐sampling algorithm (MRS) for monthly streamflow simulation. MRS is motivated from the acknowledgment that typical nonparametric models tend to simulate sequences exhibiting too close a resemblance to historical records and parametric models have limitations in capturing complex distributional and dependence characteristics, such as multimodality and nonlinear autocorrelation. The aim of MRS is to generate streamflow sequences with rich scenarios while properly capturing complex distributional and dependence characteristics. The basic assumptions of MRS include: (1) streamflow of a given month depends on a feature vector consisting of streamflow of the previous month and the dynamic aggregated flow of the past 12 months and (2) streamflow can be multiplicatively decomposed into a deterministic expectation term and a random residual term. Given a current feature vector, MRS first relates the conditional expectation to the feature vector through an ensemble average of multiple regression models. To infer the conditional distribution of the residual, MRS adopts the k‐nearest neighbor concept. More precisely, the conditional distribution is estimated by a gamma kernel smoothed density of historical residuals inside the k‐neighborhood of the given feature vector. Rather than obtaining the residuals from the averaged model only, MRS retains all residuals from all the original regression models. In other words, MRS perceives that the original residuals put together would better represent the covariance structure between streamflow and the feature vector. By doing so, the benefit is that a kernel smoothed density of the residual with reliable accuracy can be estimated, which is hardly possible in a single‐model framework. It is the smoothed density that ensures the generation of sequences with rich scenarios unseen in historical record. We evaluated MRS at selected stream gauges and compared with several existing models. Results show that (1) compared with typical nonparametric models, MRS is more apt at generating sequences with richer scenarios and (2) in contrast to parametric models, MRS can reproduce complex distributional and dependence characteristics. Since MRS is flexible at incorporating different covariates, it can be tailored for other potential applications, such as hydrologic forecasting, downscaling, as well as postprocessing deterministic forecasts into probabilistic ones.
- How will increases in rainfall intensity affect semiarid ecosystems?
- Authors: Koen Siteur; Maarten B. Eppinga, Derek Karssenberg, Mara Baudena, Marc F.P. Bierkens, Max Rietkerk
Pages: 5980 - 6001
Abstract: Model studies suggest that semiarid ecosystems with patterned vegetation can respond in a nonlinear way to climate change. This means that gradual changes can result in a rapid transition to a desertified state. Previous model studies focused on the response of patterned semiarid ecosystems to changes in mean annual rainfall. The intensity of rain events, however, is projected to change as well in the coming decades. In this paper, we study the effect of changes in rainfall intensity on the functioning of patterned semiarid ecosystems with a spatially explicit model that captures rainwater partitioning and runoff‐runon processes with simple event‐based process descriptions. Analytical and numerical analyses of the model revealed that rainfall intensity is a key parameter in explaining patterning of vegetation in semiarid ecosystems as low mean rainfall intensities do not allow for vegetation patterning to occur. Surprisingly, we found that, for a constant annual rainfall rate, both an increase and a decrease in mean rainfall intensity can trigger desertification. An increase negatively affects productivity as a greater fraction of the rainwater is lost as runoff. This can result in a shift to a bare desert state only if the mean rainfall intensity exceeds the infiltration capacity of bare soil. On the other hand, a decrease in mean rainfall intensity leads to an increased fraction of rainwater infiltrating in bare soils, remaining unavailable to plants. Our findings suggest that considering rainfall intensity as a variable may help in assessing the proximity to regime shifts in patterned semiarid ecosystems and that monitoring losses of resource through runoff and bare soil infiltration could be used to determine ecosystem resilience.
- Modeling water demand when households have multiple sources of water
- Authors: Lassina Coulibaly; Paul M. Jakus, John E. Keith
Pages: 6002 - 6014
Abstract: A significant portion of the world's population lives in areas where public water delivery systems are unreliable and/or deliver poor quality water. In response, people have developed important alternatives to publicly supplied water. To date, most water demand research has been based on single‐equation models for a single source of water, with very few studies that have examined water demand from two sources of water (where all nonpublic system water sources have been aggregated into a single demand). This modeling approach leads to two outcomes. First, the demand models do not capture the full range of alternatives, so the true economic relationship among the alternatives is obscured. Second, and more seriously, economic theory predicts that demand for a good becomes more price‐elastic as the number of close substitutes increases. If researchers artificially limit the number of alternatives studied to something less than the true number, the price elasticity estimate may be biased downward. This paper examines water demand in a region with near universal access to piped water, but where system reliability and quality is such that many alternative sources of water exist. In extending the demand analysis to four sources of water, we are able to (i) demonstrate why households choose the water sources they do, (ii) provide a richer description of the demand relationships among sources, and (iii) calculate own‐price elasticity estimates that are more elastic than those generally found in the literature.
- Spatial characterization of roughness elements in high‐gradient
channels of the Fraser Experimental Forest, Colorado, USA
- Authors: Steven E. Yochum; Brian P. Bledsoe, Ellen Wohl, Gabrielle C. L. David
Pages: 6015 - 6029
Abstract: We collected high‐resolution LiDAR‐based spatial and reach‐average flow resistance data at a range of flows in headwater stream channels of the Fraser Experimental Forest, Colorado, USA. Using these data, we implemented a random field approach for assessing the variability of detrended bed elevations and flow depths for both the entire channel width and the thalweg‐centered 50% of the channel width (to exclude bank effects). The spatial characteristics of these channels, due to bedforms, large clasts and instream wood, were compared with Darcy‐Weisbach f and stream type through the use of the first four probability density function moments (mean, variance, skewness, kurtosis). The standard deviation of the bed elevations (σz) combined with depth (h), as relative bedform submergence (h/σz), was well correlated with f (R2 = 0.81) for the 50% of channel width. The explained variance decreased substantially (R2 = 0.69) when accounting for the entire width, indicating lesser contribution of channel edges to flow resistance. The flow depth skew also explained a substantial amount of the variance in f (R2 = 0.78). A spectrum of channel types is evident in depth plots of skew versus kurtosis, with channel types ranging from plane bed, transitional, step pool/cascade, to cascade. These results varied when bank effects were included or excluded, although definitive patterns were observed for both analyses. Random field analyses may be valuable for developing tools for predicting flow resistance, as well as for quantifying the spectrum of morphologic change in high‐gradient channel types, from plane bed through cascade.
- A robust multimodel framework for ensemble seasonal hydroclimatic
- Authors: Pablo A. Mendoza; Balaji Rajagopalan, Martyn P. Clark, Gonzalo Cortés, James McPhee
Pages: 6030 - 6052
Abstract: We provide a framework for careful analysis of the different methodological choices we make when constructing multimodel ensemble seasonal forecasts of hydroclimatic variables. Specifically, we focus on three common modeling decisions: (i) number of models, (ii) multimodel combination approach, and (iii) lead time for prediction. The analysis scheme includes a multimodel ensemble forecasting algorithm based on nonparametric regression, a set of alternatives for the options previously pointed, and a selection of probabilistic verification methods for ensemble forecast evaluation. The usefulness of this framework is tested through an example application aimed to generate spring/summer streamflow forecasts at multiple locations in Central Chile. Results demonstrate the high impact that subjectivity in decision‐making may have on the quality of ensemble seasonal hydroclimatic forecasts. In particular, we note that the probabilistic verification criteria may lead to different choices regarding the number of models or the multimodel combination method. We also illustrate how this objective analysis scheme may lead to results that are extremely relevant for the case study presented here, such as skillful seasonal streamflow predictions for very dry conditions.
- Topographic controls on shallow groundwater levels in a steep, prealpine
catchment: When are the TWI assumptions valid?
- Authors: M. Rinderer; H. J. van Meerveld, J. Seibert
Pages: 6067 - 6080
Abstract: Topographic indices like the Topographic Wetness Index (TWI) have been used to predict spatial patterns of average groundwater levels and to model the dynamics of the saturated zone during events (e.g., TOPMODEL). However, the assumptions underlying the use of the TWI in hydrological models, of which the most important is that groundwater level variation can be approximated by a series of steady state situations, are rarely tested. It is also not clear how well findings from existing hillslope studies on sites with transmissive soil can be transferred to entire catchments with less permeable soils. This study, therefore, evaluated the suitability of selected topographic indices to describe spatial groundwater level variations based on time series from 51 groundwater wells in a 20 ha catchment with low‐permeability soils in Switzerland. Results showed that median groundwater levels were correlated to slope, curvature, and TWI, but the strength of correlation depended on whether the indices characterized the local topography or the topography of the upslope contributing area. The correlation between TWI and groundwater levels was not constant over time but decreased at the beginning of rainfall events, indicating large spatial differences in groundwater responses, and increased after peak flow, when groundwater levels could be considered to be spatially in a steady state. Our findings indicate that topographic indices are useful to predict median groundwater levels in catchments with low‐permeability soils and that the TWI assumptions are best met when groundwater levels change slowly.
- Soil moisture and soil properties estimation in the Community Land Model
with synthetic brightness temperature observations
- Authors: Xujun Han; Harrie‐Jan Hendricks Franssen, Carsten Montzka, Harry Vereecken
Pages: 6081 - 6105
Abstract: The Community Land Model (CLM) includes a large variety of parameterizations, also for flow in the unsaturated zone and soil properties. Soil properties introduce uncertainties into land surface model predictions. In this paper, soil moisture and soil properties are updated for the coupled CLM and Community Microwave Emission Model (CMEM) by the Local Ensemble Transform Kalman Filter (LETKF) and the state augmentation method. Soil properties are estimated through the update of soil textural properties and soil organic matter density. These variables are used in CLM for predicting the soil moisture retention characteristic and the unsaturated hydraulic conductivity, and the soil texture is used in CMEM to calculate the soil dielectric constant. The following scenarios were evaluated for the joint state and parameter estimation with help of synthetic L‐band brightness temperature data assimilation: (i) the impact of joint state and parameter estimation; (ii) updating of soil properties in CLM alone, CMEM alone or both CLM and CMEM; (iii) updating of soil properties without soil moisture update; (iv) the observation localization of LETKF. The results show that the characterization of soil properties through the update of textural properties and soil organic matter density can strongly improve with assimilation of brightness temperature data. The optimized soil properties also improve the characterization of soil moisture, soil temperature, actual evapotranspiration, sensible heat flux, and soil heat flux. The best results are obtained if the soil properties are updated only. The coupled CLM and CMEM model is helpful for the parameter estimation. If soil properties are biased, assimilation of soil moisture data with only state updates increases the root mean square error for evapotranspiration, sensible heat flux, and soil heat flux.