MODELING WATER BALANCE WITH THE ERHYM MODEL ON SOUTH TEXAS RANGELANDS1

ABSTRACT: Understanding the hydrologic processes of rangeland plant communities is essential to determine if water augmentation through shrub management is feasible. Vegetation manipulation studies are costly, difficult to accurately replicate, and often require more than 10 years to determine treatment effect on the water budget. If properly applied, hydrologic simulation models are an attractive alternative for assessing vegetation manipulation practices. The ERHYM-II model was evaluated to determine if it was capable of simulating the water balance for honey mesquite shrub clusters, grass interspaces, and bare soil in south Texas. The simulated water budget was within 2 percent of the measured evapotranspiration for the shrub clusters and grass interspaces. The model underestimated the number of runoff events and overestimated runoff volume for the grass interspace and shrub clusters. Simulated runoff was overestimated by approximately twofold for the grass interspace and threefold for the shrub clusters. Although simulated runoff was substantially overestimated, observed and simulated runoff only accounted for 3 to 6 percent of annual rainfall for the grass and shrub dominated areas, respectively. Simulated evapotranspiration was underestimated by 18 percent and soil water content was overestimated by 82 percent for the bare soil. The model underestimated evapotranspiration for the bare soil as a result of restricting evaporative losses to the first soil layer. Based on our analysis, the ERHYM-II model has the potential for simulating the annual water balance for semiarid rangeland plant communities where runoff and deep drainage are limited components of the water balance.     

Time Series Analysis of Nebraska Daily Rainfall Data to Simulate Atrazine Runoff1

Abstract: Measured atrazine concentrations in Nebraska surface water have been shown to exceed water‐quality standards, posing risks to humans and to the ecosystem. To assess this risk, atrazine runoff was simulated at the field‐scale in Nebraska based on the pesticide component of the AGNPS model. This project’s objective was to determine the frequency that the atrazine concentration at the field outlet exceeded three different atrazine water‐quality criteria. The simulation was conducted for different farm management practices, soil moisture conditions, and five Nebraska topographic regions. If the criteria were exceeded, a risk to the drinking water consumer or freshwater aquatic life was hypothesized to exist. Three pesticide fate and transport processes were simulated with the model. Degradation was simulated using first‐order kinetics. Adsorption/desorption was modeled assuming a linear soil‐water partitioning coefficient. Advection (runoff) was based primarily on the USDA‐NRCS curve number method. Daily rainfall from the National Weather Service was used to compute the soil moisture conditions for the 1985‐2000 growing seasons. After each runoff event, the pesticide runoff concentration was compared with each of the three atrazine water‐quality criteria. The results show that environmental receptors (i.e., freshwater aquatic species) are exposed to unacceptable atrazine runoff concentrations in 20‐50% of the runoff events.     

Mechanistic Simulation of Tree Effects in an Urban Water Balance Model1

Abstract: A semidistributed, physical‐based Urban Forest Effects – Hydrology (UFORE‐Hydro) model was created to simulate and study tree effects on urban hydrology and guide management of urban runoff at the catchment scale. The model simulates hydrological processes of precipitation, interception, evaporation, infiltration, and runoff using data inputs of weather, elevation, and land cover along with nine channel, soil, and vegetation parameters. Weather data are pre‐processed by UFORE using Penman‐Monteith equations to provide potential evaporation terms for open water and vegetation. Canopy interception algorithms modified established routines to better account for variable density urban trees, short vegetation, and seasonal growth phenology. Actual evaporation algorithms allocate potential energy between leaf surface storage and transpiration from soil storage. Infiltration algorithms use a variable rain rate Green‐Ampt formulation and handle both infiltration excess and saturation excess ponding and runoff. Stream discharge is the sum of surface runoff and TOPMODEL‐based subsurface flow equations. Automated calibration routines that use observed discharge has been coupled to the model. Once calibrated, the model can examine how alternative tree management schemes impact urban runoff. UFORE‐Hydro model testing in the urban Dead Run catchment of Baltimore, Maryland, illustrated how trees significantly reduce runoff for low intensity and short duration precipitation events.     

DEVELOPMENT OF A FRACTURED MEDIUM FLOW MODEL FOR A WASTE SITE1

ABSTRACT: A three‐dimensional fractured medium flow model was developed for the Bear Creek Valley (BCV) S‐3 site of the Oak Ridge Reservation (ORR) using SWIFT III. The numerical modeling for this site focused on a conceptual model established through the analysis of heterogeneous geologic units and matrix fracture properties of the subsurface in the BCV area. The SWIFT III modeling analysis was based on the previous modeling studies that used MODFLOW and MODPATH. A rigorous calibration was obtained first by comparing simulated results with the existing data on ground water levels and then by comparing pumping test results with the simulated ground water levels. A satisfactory agreement between observed and simulated results was obtained. The calibrated model was used to determine sustained yield from a ground water interceptor trench. Different withdrawal rates were used to simulate the performance of the trench for the sustained withdrawal of ground water.     

Dynamic floodplain vegetation model development for the Kootenai River, USA

The Kootenai River floodplain in Idaho, USA, is nearly disconnected from its main channel due to levee construction and the operation of Libby Dam since 1972. The decreases in flood frequency and magnitude combined with the river modification have changed the physical processes and the dynamics of floodplain vegetation. This research describes the concept, methodologies and simulated results of the rule-based dynamic floodplain vegetation model "CASiMiR-vegetation" that is used to simulate the effect of hydrological alteration on vegetation dynamics. The vegetation dynamics are simulated based on existing theory but adapted to observed field data on the Kootenai River. The model simulates the changing vegetation patterns on an annual basis from an initial condition based on spatially distributed physical parameters such as shear stress, flood duration and height-over-base flow level. The model was calibrated and the robustness of the model was analyzed. The hydrodynamic (HD) models were used to simulate relevant physical processes representing historic, pre-dam, and post-dam conditions from different representative hydrographs. The general concept of the vegetation model is that a vegetation community will be recycled if the magnitude of a relevant physical parameter is greater than the threshold value for specific vegetation; otherwise, succession will take place toward maturation stage. The overall accuracy and agreement Kappa between simulated and field observed maps were low considering individual vegetation types in both calibration and validation areas. Overall accuracy (42% and 58%) and agreement between maps (0.18 and 0.27) increased notably when individual vegetation types were merged into vegetation phases in both calibration and validation areas, respectively. The area balance approach was used to analyze the proportion of area occupied by different vegetation phases in the simulated and observed map. The result showed the impact of the river modification and hydrological alteration on the floodplain vegetation. The spatially distributed vegetation model developed in this study is a step forward in modeling riparian vegetation succession and can be used for operational loss assessment, and river and floodplain restoration projects.     

CONTINENTAL SCALE SIMULATION OF THE HYDROLOGIC BALANCE1

This paper describes the application of a continuous daily water balance model called SWAT (Soil and Water Assessment Tool) for the conterminous U.S. The local water balance is represented by four control volumes; (1) snow, (2) soil profile, (3) shallow aquifer, and (4) deep aquifer. The components of the water balance are simulated using “storage” models and readily available input parameters. All the required databases (soils, landuse, and topography) were assembled for the conterminous U.S. at 1:250,000 scale. A GIS interface was utilized to automate the assembly of the model input files from map layers and relational databases. The hydrologic balance for each soil association polygon (78,863 nationwide) was simulated without calibration for 20 years using dominant soil and land use properties. The model was validated by comparing simulated average annual runoff with long term average annual runoff from USGS stream gage records. Results indicate over 45 percent of the modeled U.S. are within 50 mm of measured, and 18 percent are within 10 mm without calibration. The model tended to under predict runoff in mountain areas due to lack of climate stations at high elevations. Given the limitations of the study, (i.e., spatial resolution of the data bases and model simplicity), the results show that the large scale hydrologic balance can be realistically simulated using a continuous water balance model.     

SENSITIVITY CONSIDERATIONS WHEN MODELING HYDROLOGIC PROCESSES WITH DIGITAL ELEVATION MODEL1

ABSTRACT: The purpose of this paper is to investigate the sensitivity of a hydrologic models to the type of DEM used. This was done while modeling basin water quality with 1:24,000 and 1:250,000 U.S. Geological Survey DEMs as input to model hydro‐logical processes. The manner in which the model results were sensitive to the choice of raster cell size (scale) is investigated in this study. The Broadhead watershed, located in New Jersey, USA, was chosen as a study area. Curve numbers were estimated by a trial and error to match simulated and observed total discharge. Monthly runoff for the watershed was used in the calibration process. Higher runoff volumes were simulated by the model when the 1:24,000 DEM were used as input data, probably due to the finer resolution which simulated increased average slope and hence higher estimated runoff from the watershed. As the simulated slope of the watershed is flatten with the 1:250,000 DEM, the response of stream flow was delayed and simulated less runoff volume.     

SIMULATION OF INTEGRATED SURFACE WATER AND GROUND WATER SYSTEMS - MODEL FORMULATION1

ABSTRACT: The unique characteristics of the hydrogeologic system of south Florida (flat topography, sandy soils, high water table, and highly developed canal system) cause significant interactions between ground water and surface water systems. Interaction processes involve infiltration, evapotranspiration (ET), runoff, and exchange of flow (seepage) between streams and aquifers. These interaction processes cannot be accurately simulated by either a surface water model or a ground water model alone because surface water models generally oversimplify ground water movement and ground water models generally oversimplify surface water movement. Estimates of the many components of flow between surface water and ground water (such as recharge and ET) made by the two types of models are often inconsistent. The inconsistencies are the result of differences in the calibration components and the model structures, and can affect the confidence level of the model application. In order to improve model results, a framework for developing a model which integrates a surface water model and a ground water model is presented. Dade County, Florida, is used as an example in developing the concepts of the integrated model. The conceptual model is based on the need to evaluate water supply management options involving the conjunctive use of surface water and groundwater, as well as the evaluation of the impacts of proposed wellfields. The mathematical structure of the integrated model is based on the South Florida Water Management Model (SFWMM) (MacVicar et al., 1984) and A Modular Three-Dimensional Finite-Difference Groundwater Flow Model (MODFLOW) (McDonald and Harbaugh, 1988).     

Modeling Hydrology in a Small Rocky Mountain Watershed Serving Large Urban Populations1

Abstract: This article describes the development of a calibrated hydrologic model for the Blue River watershed (867 km²) in Summit County, Colorado. This watershed provides drinking water to over a third of Colorado’s population. However, more research on model calibration and development for small mountain watersheds is needed. This work required integration of subsurface and surface hydrology using GIS data, and included aspects unique to mountain watersheds such as snow hydrology, high ground‐water gradients, and large differences in climate between the headwaters and outlet. Given the importance of this particular watershed as a major urban drinking‐water source, the rapid development occurring in small mountain watersheds, and the importance of Rocky Mountain water in the arid and semiarid West, it is useful to describe calibrated watershed modeling efforts in this watershed. The model used was Soil and Water Assessment Tool (SWAT). An accurate model of the hydrologic cycle required incorporation of mountain hydrology‐specific processes. Snowmelt and snow formation parameters, as well as several ground‐water parameters, were the most important calibration factors. Comparison of simulated and observed streamflow hydrographs at two U.S. Geological Survey gaging stations resulted in good fits to average monthly values (0.71 Nash‐Sutcliffe coefficient). With this capability, future assessments of point‐source and nonpoint‐source pollutant transport are possible.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

Effects of prolonged irrigation with treated municipal effluent on runoff rate

The use of domestic effluents for the irrigation of crops has been widespread in Israel for the past 30 years. The sodium adsorption ratio (SAR) of the standardized domestic effluents ranges between 4 and 6. According to the literature, when soils with SAR levels of 4 to 6 are exposed to direct raindrop impact they are subjected to enhanced aggregate disintegration, leading to sealing processes of the soil surface and subsequent increased runoff and soil erosion. However, these phenomena were not observed in the laboratory and field experiments of this study. On the other hand, a rapid decrease of the soil SAR to its initial values was observed, in laboratory and fieldwork, once the soil was subjected to a simulated rainstorm of distilled water (laboratory) or natural rainstorms (field plots). We can conclude that the process of SAR increase during irrigation with standardized effluent water is reversible. Further investigation in this direction can lead to recommendations regarding the necessary levels of domestic sewage water purification in correlation with soil types, climatic conditions, and hazards to tap water aquifers.     

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1-June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1-December 31), and the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash-Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.     

Impact of Length of Dataset on Streamflow Calibration Parameters and Performance of APEX Model

Due to resource constraints, long‐term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of length of available calibration data on model parameterization and performance. The main objective of this study was to evaluate the impact of length of calibration data (LCD) on parameterization and performance of the Agricultural Policy Environmental eXtender model for predicting daily, monthly, and annual streamflow. Long‐term (1984‐2015) measured daily streamflow data from Rock Creek watershed, an agricultural watershed in northern Ohio, were used for this study. Data were divided into five Short (5‐year), two Medium (15‐year), and one Long (25‐year) streamflow calibration data scenarios. All LCD scenarios were calibrated and validated at three time steps: daily, monthly, and annual. Results showed LCD affected the ability of the model to accurately capture temporal variability in simulated streamflow. However, overall average streamflow, water budgets, and crop yields were simulated reasonably well for all LCD scenarios.     

SOIL-SOILN simulations of water drainage and nitrate nitrogen transport from soil core lysimeters

Water resources protection from nitrate nitrogen (NO3-N) contamination is an important public concern and a major national environmental issue. The abilities of the SOIL-SOILN model to simulate water drainage and nitrate N fluxes from orchardgrass (Dactylis glomerata L.) were evaluated using data from a 3-yr field experiment. The soil is classified as a Hagerstown silt loam soil (fine, mixed, semiactive, mesic Typic Hapludalf). Nitrate losses below the 1-m depth from N-fertilized grazed orchardgrass were measured with intact soil core lysimeters. Five N-fertilizer treatments consisted of a control, urine application in the spring, urine application in the summer, urine application in the fall, and feces application in the summer. The SOIL-SOILN models were evaluated using water drainage and nitrate flux data for 1993-1994, 1994-1995, and 1995-1996. The N rate constants from a similar experiment with inorganic fertilizer and manure treatments under corn (Zea mays L.) were used to evaluate the SOILN model under orchardgrass sod. Results indicated that the SOIL model accurately simulated water drainage for all three years. The SOILN model adequately predicted nitrate losses for three urine treatments in each year and a control treatment in 1994-1995. However, it failed to produce accurate simulations for two control treatments in 1993-1994 and 1995-1996, and feces treatments in all three years. The inaccuracy in the simulation results for the control and feces treatments seems to be related to an inadequate modeling of N transformation processes. In general, the results demonstrate the potential of the SOILN model to predict NO3-N fluxes under pasture conditions using N transformation rate constants determined through the calibration process from corn fields on similar soils.     

Quantitative Assessment of Agricultural Runoff and Soil Erosion Using Mathematical Modeling: Applications in the Mediterranean Region

Three mathematical models, the runoff curve number equation, the universal soil loss equation, and the mass response functions, were evaluated for predicting nonpoint source nutrient loading from agricultural watersheds of the Mediterranean region. These methodologies were applied to a catchment, the gulf of Gera Basin, that is a typical terrestrial ecosystem of the islands of the Aegean archipelago. The calibration of the model parameters was based on data from experimental plots from which edge-of-field losses of sediment, water runoff, and nutrients were measured. Special emphasis was given to the transport of dissolved and solid-phase nutrients from their sources in the farmers' fields to the outlet of the watershed in order to estimate respective attenuation rates. It was found that nonpoint nutrient loading due to surface losses was high during winter, the contribution being between 50% and 80% of the total annual nutrient losses from the terrestrial ecosystem. The good fit between simulated and experimental data supports the view that these modeling procedures should be considered as reliable and effective methodological tools in Mediterranean areas for evaluating potential control measures, such as management practices for soil and water conservation and changes in land uses, aimed at diminishing soil loss and nutrient delivery to surface waters. Furthermore, the modifications of the general mathematical formulations and the experimental values of the model parameters provided by the study can be used in further application of these methodologies in watersheds with similar characteristics.     

APPLICATION OF THE RHESSys MODEL TO A CALIFORNIA SEMIARID SHRUBLAND WATERSHED1

ABSTRACT: Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro‐Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km² watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.     

Simulating nitrogen dynamics in agricultural soils fertilized with pig slurry and urea

Within the framework of an interregional project in the Emilia Romagna region of northern Italy, the coupled MACRO-SOILN model was chosen to estimate soil protective capacity against pollutants. The aim of our study was to evaluate the model to better identify key parameters and processes that influence N losses in agricultural soils. Nitrate N content was monitored in soil under corn (Zea mays L.) fertilized with urea and/or pig slurry, in two field experiments performed on four different soils: a Fienili clay, a Barco-like silt, a Sant'Omobono silt loam, and a La Boaria silty clay soil. Measurements were compared with model predictions. For all soils, nitrate content was underestimated on average by 24 to 88% at lower N rates; it was overestimated by 1 to 104% at higher N rates. The root mean square error (RMSE) was equal to 81.1%. Simulation of crop N uptake and soil water flow, estimation of the ammonia losses at pig slurry spreading, and N transformation parameter setting were considered as possible error sources. The calibration of crop N uptake gave rise to good model efficiency index values. The RMSE for the simulation of soil water content varied between 9.8 and 20.2%. A more accurate setting of the ammonia losses and of the feces transformation parameter values could allow the RMSE for the simulation of soil nitrate content to be reduced by no more than 10 to 15%. It is possible for the model not to include the simulation of processes that could have relevant effects on the soil N dynamics.     

Assessing Surface Water Quality and Its Relation with Urban Land Cover Changes in the Lake Calumet Area, Greater Chicago

Urban land use and land cover change significantly affect spatial and temporal patterns of runoff, which in turn impacts surface water quality. With the exponential growth in urban areas over the past three decades, changes in land use and land cover to cater for the growth of cities has been a conspicuous spectacle in urban spaces. The main goal of this study was to assess the impacts of land cover change on runoff and surface water quality using a partial area hydrology framework. The study employed ArcHydro GIS extension and a modified version of Long-Term Hydrologic and Nonpoint Source Pollution model (L-THIA-NPS) in estimating runoff and nonpoint source pollutant concentration around Lake Calumet between 1992 and 2001. Data employed include National Land Cover Data set, rainfall data, digital elevation model (DEM), Soil Survey Geographic (SSURGO) data, and The United States Environmental Protection Agency’s STORET (storage and retrieval) water quality data. The model was able to predict surface water quality reasonably well over the study period. Sensitivity analysis facilitated a manual calibration of the model. Model validation was executed by comparing simulated results following calibration and observed water quality data for the study area. The study demonstrates that the level of concentration of nonpoint source pollutants in surface water within an urban watershed heavily depends on the spatiotemporal variations in areas that contribute towards runoff compared to the spatial extent of change in major land use/land cover.