HYDROLOGICAL MODELING OF THE IROQUOIS RIVER WATERSHED USING HSPF AND SWAT1

ABSTRACT: The performance of two popular watershed scale simulation models — HSPF and SWAT — were evaluated for simulating the hydrology of the 5,568 km² Iroquois River watershed in Illinois and Indiana. This large, tile drained agricultural watershed provides distinctly different conditions for model comparison in contrast to previous studies. Both models were calibrated for a nine‐year period (1987 through 1995) and verified using an independent 15‐year period (1972 through 1986) by comparing simulated and observed daily, monthly, and annual streamflow. The characteristics of simulated flows from both models are mostly similar to each other and to observed flows, particularly for the calibration results. SWAT predicts flows slightly better than HSPF for the verification period, with the primary advantage being better simulation of low flows. A noticeable difference in the models' hydrologic simulation relates to the estimation of potential evapotranspiration (PET). Comparatively low PET values provided as input to HSPF from the BASINS 3.0 database may be a factor in HSPF's overestimation of low flows. Another factor affecting baseflow simulation is the presence of tile drains in the watershed. HSPF parameters can be adjusted to indirectly account for the faster subsurface flow associated with tile drains, but there is no specific tile drainage component in HSPF as there is in SWAT. Continued comparative studies such as this, under a variety of hydrologic conditions and watershed scales, provide needed guidance to potential users in model selection and application.     

HYDROLOGIC CALIBRATION OF THE SWAT MODEL IN A WATERSHED CONTAINING FRAGIPAN SOILS1

ABSTRACT: The Soil and Water Assessment Tool (SWAT) model, designed for use on rural ungaged basins and incorporating a GRASS GIS interface, was used to model the hydrologic response of the Ariel Creek watershed of northeastern Pennsylvania. Model evaluation of daily flow prior to calibration revealed a deviation of runoff volumes (D_v) of 68.3 percent and a Nash-Sutcliffe coefficient of-0.03. Model performance was affected by unusually large observed snowmelt events and the inability of the model to accurately simulate baseflow, which was influenced by the presence of fragipans. Seventy-five percent of the soils in the watershed contain fragipans. Model calibration yielded a D_v of 39.9 percent and a Nash-Sutcliffe coefficient of 0.04, when compared on a daily basis. Monthly comparisons yielded a Nash-Sutcliffe coefficient of 0.14. Snowmelt events in the springs of 1993 and 1994, which were unusually severe, were not adequately simulated. Neglecting these severe events, which produced the largest and third largest measured flows for the period of record, a D_v of 4.1 percent and Nash-Sutcliffe coefficient of 0.20 were calculated on a daily comparison, while on a monthly basis the Nash-Sutciffe coefficient was 0.55. These results suggest that the SWAT model is better suited to longer period simulations of hydrologic yields. Baseflow volumes were accurately simulated after calibration (D_v= -0.2 percent). Refinements made to the algorithms controlling subsurface hydrology and snowmelt, to better represent the presence of fragipans and snowmelt events, would likely improve model performance.     

WATERSHED SCALE MODELING OF CRITICAL SOURCE AREAS OF RUNOFF GENERATION AND PHOSPHORUS TRANSPORT1

ABSTRACT: A curve number based model, Soil and Water Assessment Tool (SWAT), and a physically based model, Soil Moisture Distribution and Routing (SMDR), were applied in a headwater watershed in Pennsylvania to identify runoff generation areas, as runoff areas have been shown to be critical for phosphorus management. SWAT performed better than SMDR in simulating daily streamflows over the four‐year simulation period (Nash‐Sutcliffe coefficient: SWAT, 0.62; SMDR, 0.33). Both models varied streamflow simulations seasonally as precipitation and watershed conditions varied. However, levels of agreement between simulated and observed flows were not consistent over seasons. SMDR, a variable source area based model, needs further improvement in model formulations to simulate large peak flows as observed. SWAT simulations matched the majority of observed peak flow events. SMDR overpredicted annual flow volumes, while SWAT underpredicted the same. Neither model routes runoff over the landscape to water bodies, which is critical to surface transport of phosphorus. SMDR representation of the watershed as grids may allow targeted management of phosphorus sources. SWAT representation of fields as hydrologic response units (HRUs) does not allow such targeted management.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Improving watershed decisions using run-off and yield models at different simulation scales

Water managers face the daunting task of balancing limited water resources with over-subscribed water users among competing demands. They face the additional challenge of taking water planning decisions in an uncertain environment with limited and sometimes inaccurate observed and simulated hydrological data. Within South African watersheds, spatial parameterization data for hydrological models are now available at two different basin management resolutions (termed quaternary and quinary). Currently, water management decisions in the Crocodile River watershed are often made at a more coarse resolution, which may exclude crucial insights into the data. This research has the following aims (1) to explore whether model performance is improved by parameterization using a more detailed quinary-scale watershed data and (2) to explore whether quinary-scale models reduce uncertainty in allocation or restriction decisions to provide better informed water resources management and decision outcomes. This study used the Agricultural Catchments Research Unit (ACRU) agro-hydrological watershed model, to evaluate the effects of spatial discretization at the quaternary and quinary scales on watershed hydrological response and runoff within the Crocodile River basin. Model performance was evaluated using statistical comparisons of results using traditional goodness-of-fit measures such as the coefficient of efficiency (C _eff), root mean square of the error and the coefficient of determination (R ²) to compare simulated monthly flows and observed flows in six subcatchments. Traditional interpretation of these goodness-of-fit measures may be inadequate as they can be subjectively interpreted and easily influenced by the number of data points, outliers and model bias. This research utilizes a recently released model evaluation program (FITEVAL) which presents probability distributions of R ²and C _eff derived by bootstrapping, graphical representation of observed and simulated stream flows, incorporates statistical significance to detect the sufficiency of the R ²and C _eff and determines the presence of outliers and bias. While analyses indicate that the ACRU model performs marginally better when parameterized and calibrated at the quinary scale, the measurements at both scales show significant variability in predictions for both high and low flows that are endemic to southern African hydrology. The improved evaluation methods also allow for the analysis of data collection errors at monitoring sites and help determine the effect of data quality on adaptive water planning management decisions. Given that many water resource challenges are complex adaptive systems, these expanded performance analysis tools help provide deeper insights into matching watershed decision metrics and model-derived predictions.     

EVALUATION OF THE APPLICABILITY OF THE SWAT MODEL FOR COASTAL WATERSHEDS IN SOUTHEASTERN LOUISIANA1

ABSTRACT: The Soil and Water Assessment Tool (SWAT) has been used for hydrologic analyses at various watershed scales. However, little is known about the model's performance in coastal watersheds. In this study SWAT was evaluated for its applicability in three Louisiana coastal watersheds: the Amite, Tickfaw, and Tangipahoa River watersheds. The model was calibrated with daily discharge from 1976 to 1977 and validated from 1979 to 1999 for the Amite and Tangipahoa and with daily discharge from 1979 to 1989 for the Tickfaw. Deviation of mean discharge and the Nash‐Sutcliffe model efficiency were used to evaluate model behavior. The study found that Manning's roughness coefficient for the main channel, SCS curve number, and soil evaporation compensation factor were the most sensitive parameters for these coastal watersheds. The Manning's roughness coefficient showed the greatest effect on the response time of surface runoff, suggesting the critical role of channel routing in hydrologic modeling for lowland watersheds. The SWAT model demonstrated an excellent performance, with Nash‐Sutcliffe efficiencies of 0.935, 0.940, and 0.960 for calibrations of the Amite, Tickfaw, and Tangipahoa watersheds, respectively, and of 0.851, 0.811, and 0.867 for validations. The modeling results demonstrate that SWAT is capable of simulating hydrologic processes for medium scale to large scale coastal lowland watersheds in Louisiana.     

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 PARAMETERIZATION OF WATERSHEDS FOR RUNOFF PREDICTION USING SWAT1

ABSTRACT: The use of continuous time, distributed parameter hydrologic models like SWAT (Soil and Water Assessment Tool) has opened several opportunities to improve watershed modeling accuracy. However, it has also placed a heavy burden on users with respect to the amount of work involved in parameterizing the watershed in general and in adequately representing the spatial variability of the watershed in particular. Recent developments in Geographical Information Systems (GIS) have alleviated some of the difficulties associated with managing spatial data. However, the user must still choose among various parameterization approaches that are available within the model. This paper describes the important parameterization issues involved when modeling watershed hydrology for runoff prediction using SWAT with emphasis on how to improve model performance without resorting to tedious and arbitrary parameter by parameter calibration. Synthetic and actual watersheds in Indiana and Mississippi were used to illustrate the sensitivity of runoff prediction to spatial variability, watershed decomposition, and spatial and temporal adjustment of curve numbers and return flow contribution. SWAT was also used to predict stream runoff from actual watersheds in Indiana that have extensive subsurface drainage. The results of this study provide useful information for improving SWAT performance in terms of stream runoff prediction in a manner that is particularly useful for modeling ungaged watersheds wherein observed data for calibration is not available.     

Modeling sediment and nitrogen export from a rural watershed in eastern Canada using the soil and water assessment tool

Watershed simulation models can be used to assess agricultural nonpoint-source pollution and for environmental planning and improvement projects. However, before application of any process-based watershed model, the model performance and reliability must be tested with measured data. The Soil and Water Assessment Tool version 2005 (SWAT2005) was used to model sediment and nitrogen loads from the Thomas Brook Watershed, which drains a 7.84 km rural landscape in the Annapolis Valley of Nova Scotia, Canada. The Thomas Brook SWAT model was comprised of 28 subbasins and 265 hydrologic response units, most of them containing agricultural land use, which is the main nonpoint nitrogen source in the watershed. Crop rotation schedules were incorporated into the model using field data collected within Agriculture and Agri-Food Canada's Watershed Evaluation of Beneficial Management Practices program. Model calibration (2004-2006) and validation (2007-2008) were performed on a monthly basis using continuous stream flow, sediment, and nitrogen export measurements. Model performance was evaluated using the coefficient of determination, Nash-Sutcliff efficiency (NSE), and percent bias (PBIAS) statistics. Study results show that the model performance was satisfactory (NSE > 0.4; > 0.5) for stream flow, sediment, nitrate-nitrogen, and total nitrogen simulations. Annual corn, barley, and wheat yields were also simulated well, with PBIAS values ranging from 0.3 to 7.2%. This evaluation of SWAT demonstrated that the model has the potential to be used as a decision support tool for agricultural watershed management in Nova Scotia.     

SENSITIVITY ANALYSIS,CALIBRATION, AND VALIDATIONS FOR A MULTISITE AND MULTIVARIABLE SWAT MODEL1

The ability of a watershed model to mimic specified watershed processes is assessed through the calibration and validation process. The Soil and Water Assessment Tool (SWAT) watershed model was implemented in the Beaver Reservoir Watershed of Northwest Arkansas. The objectives were to: (1) provide detailed information on calibrating and applying a multisite and multivariable SWAT model; (2) conduct sensitivity analysis; and (3) perform calibration and validation at three different sites for flow, sediment, total phosphorus (TP), and nitrate‐nitrogen (NO₃‐N) plus nitrite‐nitrogen (NO₂‐N). Relative sensitivity analysis was conducted to identify parameters that most influenced predicted flow, sediment, and nutrient model outputs. A multi objective function was defined that consisted of optimizing three statistics: percent relative error (RE), Nash‐Sutcliffe Coefficient (R_NS²), and coefficient of determination (R²). This function was used to successfully calibrate and validate a SWAT model of Beaver Reservoir Watershed at multi‐sites while considering multivariables. Calibration and validation of the model is a key factor in reducing uncertainty and increasing user confidence in its predictive abilities, which makes the application of the model effective. Information on calibration and validation of multisite, multivariable SWAT models has been provided to assist watershed modelers in developing their models to achieve watershed management goals.     

Modeling riverine nitrate export from an East-Central Illinois watershed using SWAT

Reliable water quality models are needed to forecast the water quality consequences of different agricultural nutrient management scenarios. In this study, the Soil and Water Assessment Tool (SWAT), version 2000, was applied to simulate streamflow, riverine nitrate (NO(3)) export, crop yield, and watershed nitrogen (N) budgets in the upper Embarras River (UER) watershed in east-central Illinois, which has extensive maize-soybean cultivation, large N fertilizer input, and extensive tile drainage. During the calibration (1994-2002) and validation (1985-1993) periods, SWAT simulated monthly and annual stream flows with Nash-Sutcliffe coefficients (E) ranging from 0.67 to 0.94 and R(2) from 0.75 to 0.95. For monthly and annual NO(3) loads, E ranged from -0.16 to 0.45 and R(2) from 0.36 to 0.74. Annual maize and soybean yields were simulated with relative errors ranging from -10 to 6%. The model was then used to predict the changes in NO(3) output with N fertilizer application rates 10 to 50% lower than original application rates in UER. The calibrated SWAT predicted a 10 to 43% decrease in NO(3) export from UER and a 6 to 38% reduction in maize yield in response to the reduction in N fertilizer. The SWAT model markedly overestimated NO(3) export during major wet periods. Moreover, SWAT estimated soybean N fixation rates considerably greater than literature values, and some simulated changes in the N cycle in response to fertilizer reduction seemed to be unrealistic. Improving these aspects of SWAT could lead to more reliable predictions in the water quality outcomes of nutrient management practices in tile-drained watersheds.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

A Simple Process‐Based Snowmelt Routine to Model Spatially Distributed Snow Depth and Snowmelt in the SWAT Model1

Abstract: We present a method to integrate a process‐based (PB) snowmelt model that requires only daily temperature and elevation information into the Soil and Water Assessment Tool (SWAT) model. The model predicts the spatiotemporal snowpack distribution without adding additional complexity, and in fact reduces the number of calibrated parameters. To demonstrate the utility of the PB model, we calibrate the PB and temperature‐index (TI) SWAT models to optimize agreement with stream discharge on a 46‐km² watershed in northwestern Idaho, United States, for 10 individual years and use the calibrated parameters for the year with the best agreement to run the model for 15 remaining years. Stream discharge predictions by the PB and TI model were similar, although the PB model simulated snowmelt more accurately than the TI model for the remaining 15‐year period. Spatial snow distributions predicted by the PB model better matched observations from LandSat imagery and a SNOTEL station. Results for this watershed show that including PB snowmelt in watershed models is feasible, and calibration of TI‐based watershed models against discharge can incorrectly predict snow cover.     

Spatial Calibration and Temporal Validation of Flow for Regional Scale Hydrologic Modeling1

Abstract: Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validation is performed at the river basin outlet without accounting for spatial variations in hydrological parameters within the subunits. In this study, we calibrated the model to capture the spatial variations in runoff at subwatershed level to assure local water balance, and validated the streamflow at key gaging stations along the river to assure temporal variability. Ohio and Arkansas‐White‐Red River Basins of the United States were modeled using Soil and Water Assessment Tool (SWAT) for the period from 1961 to 1990. R² values of average annual runoff at subwatersheds were 0.78 and 0.99 for the Ohio and Arkansas Basins. Observed and simulated annual and monthly streamflow from 1961 to 1990 is used for temporal validation at the gages. R² values estimated were greater than 0.6. In summary, spatially distributed calibration at subwatersheds and temporal validation at the stream gages accounted for the spatial and temporal hydrological patterns reasonably well in the two river basins. This study highlights the importance of spatially distributed calibration and validation in large river basins.     

Hydrologic and atrazine simulation of the Cedar Creek Watershed using the SWAT model

One of the major factors contributing to surface water contamination in agricultural areas is the use of pesticides. The Soil and Water Assessment Tool (SWAT) is a hydrologic model capable of simulating the fate and transport of pesticides in an agricultural watershed. The SWAT model was used in this study to estimate stream flow and atrazine (2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine) losses to surface water in the Cedar Creek Watershed (CCW) within the St. Joseph River Basin in northeastern Indiana. Model calibration and validation periods consisted of five and two year periods, respectively. The National Agricultural Statistics Survey (NASS) 2001 land cover classification and the Soil Survey Geographic (SSURGO) database were used as model input data layers. Data from the St. Joseph River Watershed Initiative and the Soil and Water Conservation Districts of Allen, Dekalb, and Noble counties were used to represent agricultural practices in the watershed which included the type of crops grown, tillage practices, fertilizer, and pesticide application rates. Model results were evaluated based on efficiency coefficient values, standard statistical measures, and visual inspection of the measured and simulated hydrographs. The Nash and Sutcliffe model efficiency coefficients (E(NS)) for monthly and daily stream flow calibration and validation ranged from 0.51 to 0.66. The E(NS) values for atrazine calibration and validation ranged from 0.43 to 0.59. All E(NS) values were within the range of acceptable model performance standards. The results of this study indicate that the model is an effective tool in capturing the dynamics of stream flow and atrazine concentrations on a large-scale agricultural watershed in the midwestern USA.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

EVALUATING HSPF IN AN ARID,URBANIZED WATERSHED1

ABSTRACT: The Hydrologic Simulation Program‐FORTRAN (HSPF) is a powerful time variable hydrologic model that has rarely been applied in arid environments. Here, the performance of HSPF in southern California was assessed, testing its ability to predict annual volume, daily average flow, and hourly flow. The model was parameterized with eight land use categories and physical watershed characteristics. It was calibrated using rainfall and measured flow over a five‐year period in a predominantly undeveloped watershed and it was validated using a subsequent 4‐year period. The process was repeated in a separate, predominantly urbanized watershed over the same time span. Annual volume predictions correlated well with measured flow in both the undeveloped and developed watersheds. Daily flow predictions correlated well with measured flow following rain events, but predictions were poor during extended dry weather periods in the developed watershed. This modeling difficulty during dry‐weather periods reflects the large influence of, and the poor accounting in the model for, artificially introduced water from human activities, such as landscape overwatering, that can be important sources of water in urbanized arid environments. Hourly flow predictions mistimed peak flows, reflecting spatial and temporal heterogeneity of rainfall within the watershed. Model correlation increased considerably when predictions were averaged over longer time periods, reaching an asymptote after an 11‐hour averaging window.     

Using Multiple Watershed Models to Predict Water,Nitrogen, and Phosphorus Discharges to the Patuxent Estuary1

Boomer, Kathleen M.B., Donald E. Weller, Thomas E. Jordan, Lewis Linker, Zhi‐Jun Liu, James Reilly, Gary Shenk, and Alexey A. Voinov, 2012. Using Multiple Watershed Models to Predict Water, Nitrogen, and Phosphorus Discharges to the Patuxent Estuary. Journal of the American Water Resources Association (JAWRA) 1‐25. DOI: 10.1111/j.1752‐1688.2012.00689.x Abstract: We analyzed an ensemble of watershed models that predict flow, nitrogen, and phosphorus discharges. The models differed in scope and complexity and used different input data, but all had been applied to evaluate human impacts on discharges to the Patuxent River or to the Chesapeake Bay. We compared predictions to observations of average annual, annual time series, and monthly discharge leaving three basins. No model consistently matched observed discharges better than the others, and predictions differed as much as 150% for every basin. Models that agreed best with the observations in one basin often were among the worst models for another material or basin. Combining model predictions into a model average improved overall reliability in matching observations, and the range of predictions helped describe uncertainty. The model average was not the closest to the observed discharge for every material, basin, and time frame, but the model average had the highest Nash–Sutcliffe performance across all combinations. Consistently poor performance in predicting phosphorus loads suggests that none of the models capture major controls. Differences among model predictions came from differences in model structures, input data, and the time period considered, and also to errors in the observed discharge. Ensemble watershed modeling helped identify research needs and quantify the uncertainties that should be considered when using the models in management decisions.     

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.