Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.     

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 of Sediment Yield From Anjeni-Gauged Watershed,Ethiopia Using SWAT Model1

Setegn, Shimelis G., Bijan Dargahi, Ragahavan Srinivasan, and Assefa M. Melesse, 2010. Modeling of Sediment Yield From Anjeni-Gauged Watershed, Ethiopia Using SWAT Model. Journal of the American Water Resources Association (JAWRA) 46(3):514-526. DOI: 10.1111/j.1752-1688.2010.00431.x Abstract: The Soil and Water Assessment Tool (SWAT) was tested for prediction of sediment yield in Anjeni-gauged watershed, Ethiopia. Soil erosion and land degradation is a major problem on the Ethiopian highlands. The objectives of this study were to evaluate the performance and applicability of SWAT model in predicting monthly sediment yield and assess the impacts of subbasin delineation and slope discretization on the prediction of sediment yield. Ten years monthly meteorological, flow and sediment data were used for model calibration and validation. The annual average measured sediment yield was 24.6 tonnes/ha. The annual average simulated sediment yield was 27.8 and 29.5 tones/ha for calibration and validation periods, respectively. The study found that the observed values showed good agreement with the simulated sediment yield with Nash-Sutcliffe efficiency (NSE) = 0.81, percent bias (PBIAS) = 28%, RMSE-observations standard deviation ratio (RSR) = 0.23, and coefficient of determination (R²) = 0.86 for calibration and NSE = 0.79, PBIAS = 30%, RSR = 0.29, and R² = 0.84 for validation periods. The model can be used for further analysis of different management scenarios that could help different stakeholders to plan and implement appropriate soil and water conservation strategies.     

VALIDATION OF THE SWAT MODEL ON A LARGE RWER BASIN WITH POINT AND NONPOINT SOURCES1

ABSTRACT: The State of Texas has initiated the development of a Total Maximum Daily Load program in the Bosque River Watershed, where point and nonpoint sources of pollution are a concern. Soil Water Assessment Tool (SWAT) was validated for flow, sediment, and nutrients in the watershed to evaluate alternative management scenarios and estimate their effects in controlling pollution. This paper discusses the calibration and validation at two locations, Hico and Valley Mills, along the North Bosque River. Calibration for flow was performed from 1960 through 1998. Sediment and nutrient calibration was done from 1993 through 1997 at Hico and from 1996 through 1997 at Valley Mills. Model validation was performed for 1998. Time series plots and statistical measures were used to verify model predictions. Predicted values generally matched well with the observed values during calibration and validation (R²≥ 0.6 and Nash‐Suttcliffe Efficiency ≥ 0.5, in most instances) except for some underprediction of nitrogen during calibration at both locations and sediment and organic nutrients during validation at Valley Mills. This study showed that SWAT was able to predict flow, sediment, and nutrients successfully and can be used to study the effects of alternative management scenarios.     

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).     

Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed1

Cho, Jaepil, Richard R. Lowrance, David D. Bosch, Timothy C. Strickland, Younggu Her, and George Vellidis, 2010. Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed. Journal of the American Water Resources Association (JAWRA) 46(3):586-602. DOI: 10.1111/j.1752-1688.2010.00436.x Abstract: The Soil and Water Assessment Tool (SWAT) does not fully simulate riparian buffers, but has a simple filter function that is responsive to filter strip width (FILTERW). The objectives of this study were to (1) evaluate SWAT hydrology and water quality response to changes in watershed subdivision levels and different FILTERW configurations and (2) provide guidance for selecting appropriate watershed subdivision for model runs that include the riparian buffer feature through the FILTERW parameter. Watershed subdivision level is controlled by the critical source area (CSA) which defines the minimum drainage area required to form the origin of a stream. SWAT was calibrated on a 15.7 km² subdrainage within the Little River Experimental Watershed, Georgia. The calibrated parameter set was applied to 32 watershed configurations consisting of four FILTERW representations for each of eight CSA levels. Streamflow predictions were stable regardless of watershed subdivision and FILTERW configuration. Predicted sediment and nutrient loads from upland areas decreased as CSA increased when spatial variations of riparian buffers are considered. Sediment and nutrient yield at the watershed outlet was responsive to different combinations of CSA and FILTERW depending on selected in-stream processes. CSA ranges which provide stable sediment and nutrient yields at the watershed outlet was suggested for avoiding significant modifications in selected parameter set.     

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.     

Impact of Watershed Subdivision and Soil Data Resolution on SWAT Model Calibration and Parameter Uncertainty1

Abstract: Impact of watershed subdivision and soil data resolution on Soil Water Assessment Tool (SWAT) model calibration and parameter uncertainty is investigated by creating 24 different watershed model configurations for two study areas in northern Indiana. SWAT autocalibration tool is used to calibrate 14 parameters for simulating seven years of daily streamflow records. Calibrated parameter sets are found to be different for all 24 watershed configurations, however in terms of calibrated model output, their effect is minimal. In some cases, autocalibration is followed by manual calibration to correct for low flows, which were underestimated during autocalibration. In addition to normal validation using four years of streamflow data for each calibrated parameter set, cross‐validation (using a calibrated parameter set from one model configuration to validate observations using another configuration) is performed to investigate the effect of different model configurations on streamflow prediction. Results show that streamflow output during cross‐validation is not affected, thus highlighting the non‐unique nature of calibrated parameters in hydrologic modeling. Finally, parameter uncertainty is investigated by extracting good parameter sets during the autocalibration process. Parameter uncertainty analysis suggests that significant parameters show very narrow range of uncertainty across different watershed configurations compared with nonsignificant parameters. Results from recalibration of some configurations using only six significant parameters were comparable to that from calibration using 14 parameters, suggesting that including fewer significant parameters could reduce the uncertainty arising from model parameters, and also expedite the calibration process.     

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.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Applications of Explicitly Incorporated/Post‐Processing Measurement Uncertainty in Watershed Modeling

In the field of watershed modeling, the impact of measurement uncertainty (MU) on calibration results indicates the potential issue of inaccurate model predictions. It is important to note that MU refers to the uncertainty in measured data such as flow and nutrient values that are used to evaluate model outputs. The calculation of error statistics assuming measured data are deterministic may not be appropriate as has been frequently stated in literature. Although MU can affect model calibration results, it is rarely incorporated in modeling practice. MU can be incorporated in two schemes: explicitly incorporated (MU‐EI) during model calibration and post‐processed (MU‐PP) after calibration is completed. In this study, both schemes are implemented in a case study of the Arroyo Colorado Watershed, Texas. Unexpectedly, no substantial differences were observed between each scheme for flow predictions. Although MU did not cause dramatic differences in most sediment and NH₄‐N predictions, error statistics were affected in cases with MU greater than 50%, especially for sediment and NH₄‐N. Therefore, it is concluded that MU may not exert a significant impact on model predictions until certain threshold is reached. This study demonstrates that high levels of uncertainty in measured calibration/validation data significantly affect parameter estimation, especially in the auto‐calibration process.     

HYDROLOGIC SIMULATION OF THE LITTLE WASHITA RIVER EXPERIMENTAL WATERSHED USING SWAT1

ABSTRACT: Precipitation and streamflow data from three nested subwatersheds within the Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma were used to evaluate the capabilities of the Soil and Water Assessment Tool (SWAT) to predict streamflow under varying climatic conditions. Eight years of precipitation and streamflow data were used to calibrate parameters in the model, and 15 years of data were used for model validation. SWAT was calibrated on the smallest and largest sub‐watersheds for a wetter than average period of record. The model was then validated on a third subwatershed for a range in climatic conditions that included dry, average, and wet periods. Calibration of the model involved a multistep approach. A preliminary calibration was conducted to estimate model parameters so that measured versus simulated yearly and monthly runoff were in agreement for the respective calibration periods. Model parameters were then fine tuned based on a visual inspection of daily hydrographs and flow frequency curves. Calibration on a daily basis resulted in higher baseflows and lower peak runoff rates than were obtained in the preliminary calibration. Test results show that once the model was calibrated for wet climatic conditions, it did a good job in predicting streamflow responses over wet, average, and dry climatic conditions selected for model validation. Monthly coefficients of efficiencies were 0.65, 0.86, and 0.45 for the dry, average, and wet validation periods, respectively. Results of this investigation indicate that once calibrated, SWAT is capable of providing adequate simulations for hydrologic investigations related to the impact of climate variations on water resources of the LWREW.     

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.     

A Question of Boundaries: The Importance of “Revenuesheds” for Watershed Protection1

Patterson, Lauren A., Jeffrey Hughes, Glenn Barnes, and Stacey I. Berahzer, 2012. A Question of Boundaries: The Importance of “Revenuesheds” for Watershed Protection. Journal of the American Water Resources Association (JAWRA) 48(4): 838‐848. DOI: 10.1111/j.1752‐1688.2012.00655.x Abstract: Watersheds transcend jurisdictional boundaries; raising important questions of who should pay for watershed protection, and how can watershed governance be funded? The responsibility and cost for watershed protection has progressively devolved to local governments, resulting in additional negative externalities and financing challenges. Watershed governance structures have formed at the scale of the watershed, but they often lack the financing mechanisms needed to achieve policy goals. Financing mechanisms via local governments provide a reliable source of revenue and the flexibility to address watershed specific issues. We develop a “revenueshed” approach to access the initial challenges local governments face when seeking to finance trans‐jurisdictional watershed governance. The revenueshed approach engages local governments into discussion and implementation of financial strategies for collaborative watershed governance. Legislation places water quality regulations primarily on local governments inside the watershed. The revenueshed approach extends the financial and stewardship discussion to include local governments outside the watershed that benefit from the watershed. We applied the revenueshed approach to the Mills River and Upper Neuse watersheds in North Carolina. Mills River had a partnership governance seeking revenue for specific projects, whereas the Upper Neuse sought long‐term financial stability to meet new water quality legislation.     

Large‐Scale Fine‐Resolution Hydrological Modeling Using Parameter Regionalization in the Missouri River Basin

This study simulated crop and water yields in the Missouri River Basin (MRB; 1,371,000 km²), one of the largest river basins in the United States, using the Soil and Water Assessment Tool (SWAT) at a fine resolution of 12‐digit Hydrological Unit Codes (HUCs) using the regionalization calibration approach. Very few studies have simulated the entire MRB, and those that have developed were at a coarser resolution of 8‐digit HUCs and were minimally calibrated. The MRB was first divided into three subbasins and was further divided into eleven regions. A “head watershed” was selected in each region and was calibrated for crop and water yields. The parameters from the calibrated head watershed were extrapolated to other subwatersheds in the region to complete comprehensive spatial calibration. The simulated crop yields at the head watersheds were in close agreement with observed crop yields. Spatial validation of the aggregated crop yields resulted in reasonable predictions for all crops except dryland corn in a few regions. Simulated and observed water yields in head watersheds and also in the validation locations were in close agreement in naturalized streams and poor agreement in streams with high groundwater‐surface water interactions and/or reservoirs found upstream of the gauges. Overall, the SWAT model was able to reasonably capture the hydrological and crop growth dynamics occurring in the basin despite some limitations.     

Automatic Calibration of Hydrologic Models With Multi‐Objective Evolutionary Algorithm and Pareto Optimization1

Abstract: In optimization problems with at least two conflicting objectives, a set of solutions rather than a unique one exists because of the trade‐offs between these objectives. A Pareto optimal solution set is achieved when a solution cannot be improved upon without degrading at least one of its objective criteria. This study investigated the application of multi‐objective evolutionary algorithm (MOEA) and Pareto ordering optimization in the automatic calibration of the Soil and Water Assessment Tool (SWAT), a process‐based, semi‐distributed, and continuous hydrologic model. The nondominated sorting genetic algorithm II (NSGA‐II), a fast and recent MOEA, and SWAT were called in FORTRAN from a parallel genetic algorithm library (PGAPACK) to determine the Pareto optimal set. A total of 139 parameter values were simultaneously and explicitly optimized in the calibration. The calibrated SWAT model simulated well the daily streamflow of the Calapooia watershed for a 3‐year period. The daily Nash‐Sutcliffe coefficients were 0.86 at calibration and 0.81 at validation. Automatic multi‐objective calibration of a complex watershed model was successfully implemented using Pareto ordering and MOEA. Future studies include simultaneous automatic calibration of water quality and quantity parameters and the application of Pareto optimization in decision and policy‐making problems related to conflicting objectives of economics and environmental quality.     

MODELING THE HYDROCHEMISTRY OF THE CANNONSVILLE WATERSHED WITH GENERALIZED WATERSHED LOADING FUNCTIONS (GWLF)1

ABSTRACT: A previous modeling study used the Generalized Watershed Loading Functions (GWLF) model to simulate stream‐flow, and nutrient and sediment loads to Cannonsville Reservoir from the West Branch Delaware River (WBDR). We made several model revisions, calibrated key parameters, and tested the original GWLF model and a revised GWLF model using more recent data. Model revisions included: addition of unsaturated leakage between unsaturated and saturated subsurface reservoirs; revised timing of sediment export; inclusion of urban sediments and dissolved nutrients; tracking of particulate nutrients from point sources; and revised timing of septic system loads. The revision of sediment yield timing resulted in significant improvements in monthly sediment and particulate phosphorus predictions as compared to the original model. Addition of unsaturated leakage improved hydrologic predictions during low flow months. The other model changes improve realism without adding significant model complexity or data requirements. Goodness of fit of revised model predictions versus stream measurements, as measured by the Nash‐Sutcliff coefficient of model efficiency, exceeded 0.8 for streamflow‐0.7 for sediment yield and dissolved nitrogen (N) and 0.6 for particulate and dissolved phosphorus (P). The revised GWLF model, with limited calibration, provides reasonable estimates of monthly streamflow, and nutrient and sediment loads in the Cannonsville watershed.