MAPPING HYDROLOGIC UNITS FOR THE NATIONAL WATERSHED BOUNDARY DATASET1

ABSTRACT: In 2002, Wyoming became the first state to complete development of a statewide 1:24,000‐scale Watershed Boundary Dataset (WBD) under the new Federal Standards for Delineation of Hydrologic Unit Boundaries. The product was developed through the coordinated efforts of numerous state, federal, and local entities both within Wyoming and in neighboring states. Development of a comprehensive, standardized hydrologic unit boundary dataset in a “headwaters” state such as Wyoming poses a number of unique challenges. This paper details the WBD's development in Wyoming, highlighting technical methodology development and interagency coordination strategies. Evolution of the WBD standard is reviewed, addressing inconsistencies between definitions for hydro‐logic units and “true” watershed delineations. While automated methods are improving, manual and semi‐automated techniques continue to serve as valuable approaches to hydrologic unit boundary delineation given the quality of digital terrain models and the multijurisdictional nature of watershed based management. This case study provides insight on future development and maintenance of the WBD within and across other states and regions of the country and on opportunities for linking the WBD to related water resource geospatial data products like the National Hydrography Dataset.     

A Geospatial Methodology to Identify Locations of Concentrated Runoff from Agricultural Fields

A geospatial methodology has been developed that utilizes high resolution lidar‐derived DEMs to help track runoff from agricultural fields and identify areas of potential concentrated flow through vegetated riparian areas in the Coastal Plain of Virginia. Points of concentrated flow are identified across 74 agricultural fields within the Virginia portion of the Chesapeake Bay watershed. On average, 70% of the surface area of the agricultural fields analyzed drains through less than 20 m of the field margin, and on average 81% of the field surface area drains through 1% or less of the field margin. Within the riparian buffer, locations that were predicted by the geospatial model to have high levels of concentrated flow were found to exhibit evidence of channelization. Results indicate that flow concentration and channelized flow through vegetated riparian areas may be common along the margin of agricultural fields, resulting in vegetated riparian areas that are less effective at sediment trapping than assumed. Additional results suggest that the regulations governing the location and width of vegetated riparian may not be sufficient to achieve goals for reducing sediment and nutrient runoff from nonpoint agricultural sources. Combined with the increasing availability of lidar‐derived DEMs, the geospatial model presented has the potential to advance management practices aimed at reducing nonpoint source pollution leaving agricultural fields.     

A WATER QUALITY‐BASED APPROACH FOR WATERSHED WIDE BMP STRATEGIES1

ABSTRACT: Watershed management strategies generally involve controlling nonpoint source pollution by implementing various best management practices (BMPs). Currently, stormwater management programs in most states use a performance‐based approach to implement onsite BMPs. This approach fails to link the onsite BMP performance directly to receiving water quality benefits, and it does not take into account the combined treatment effects of all the stormwater management practices within a watershed. To address these issues, this paper proposes a water quality‐based BMP planning approach for effective nonpoint source pollution control at a watershed scale. A coupled modeling system consisting of a watershed model (HSPF) and a receiving water quality model (CE‐QUAL‐W2) was developed to establish the linkage between BMP performance and receiving water quality targets. A Monte Carlo simulation approach was utilized to develop alternative BMP strategies at a watershed level. The developed methodology was applied to the Swift Creek Reservoir watershed in Virginia, and the results show that the proposed approach allows for the development of BMP strategies that lead to full compliance with water quality requirements.     

HYDROLOGIC MODELING OF A BIOINFILTRATION BEST MANAGEMENT PRACTICE1

ABSTRACT: The goal of this research was to develop a methodology for modeling a bioinfiltration best management practice (BMP) built in a dormitory area on the campus of Villanova University in Pennsylvania. The objectives were to quantify the behavior of the BMP through the different seasons and rainfall events; better understand the physical processes governing the system's behavior; and develop design criteria. The BMP was constructed in 2001 by excavating within an existing traffic island, backfilling with a sand/soil mixture, and planting with salt tolerant grasses and shrubs native to the Atlantic shore. It receives runoff from the asphalt (0.26 hectare) and turf (0.27 hectare) surfaces of the watershed. Monitoring supported by the hydrologic model shows that the facility infiltrates a significant fraction of the annual precipitation, substantially reducing the delivery of nonpoint source pollution and erosive surges downstream. A hydrologic model was developed using HEC‐HMS to represent the site and the BMP using Green‐Ampt and kinematic wave methods. Instruments allow comparison of the modeled and measured water budget parameters. The model, incorporating seasonally variable parameters, predicts the volumes infiltrated and bypassed by the BMP, confirming the applicability of the selected methods for the analysis of bioinfiltration BMPs.     

Characterizing the Extent of Spatially Integrated Floodplain and Wetland Systems in the White River,Indiana, USA

Floodplain delineation may inform protection of wetland systems under local, state, or federal laws. Nationally available Federal Emergency Management Agency Flood Insurance Rate Maps (FIRMs, “100‐year floodplain” maps) focus on urban areas and higher‐order river systems, limiting utility at large scales. Few other national‐scale floodplain data are available. We acquired FIRMs for a large watershed and compared FIRMs to floodplain and integrated wetland area mapping methods based on (1) geospatial distance, (2) geomorphic setting, and (3) soil characteristics. We used observed flooding events (OFEs) with recurrence intervals of 25‐50 to >100 years to assess floodplain estimate accuracy. FIRMs accurately reflected floodplain areas based on OFEs and covered 32% of river length, whereas soil‐based mapping was not as accurate as FIRMs but characterized floodplain areas over approximately 65% of stream length. Geomorphic approaches included more areas than indicated by OFE, whereas geospatial approaches tended to cover less area. Overall, soil‐based methods have the highest utility in determining floodplains and their integrated wetland areas at large scales due to the use of nationally available data and flexibility for regional application. These findings will improve floodplain and integrated wetland system extent assessment for better management at local, state, and national scales.     

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.     

A Gis‐Based Approach to Watershed Classification for Nebraska Reservoirs1

Abstract: The U.S. Environmental Protection Agency is charged with establishing standards and criteria for assessing lake water quality. It is, however, increasingly evident that a single set of national water quality standards that do not take into account regional hydrogeologic and ecological differences will not be viable as lakes clearly have different inherent capacities to meet such standards. We demonstrate a GIS‐based watershed classification strategy for identifying groups of Nebraska reservoirs that have similar potential capacity to attain a certain level of water quality standard. A preliminary cluster analysis of 78 reservoirs was performed to determine the potential number of Nebraska reservoir groups. Subsequently, a Classification Trees method was used to refine number of classes, describe the structure of reservoir watershed classes, and to develop a predictive model that relates watershed conditions to reservoir classes. Results suggest that Nebraska reservoirs can be represented by nine classes and that soil organic matter content in the watershed is the most important single variable for segregating the reservoirs. The cross‐validation prediction error rate of the Classification Tree model was 26.3%. Because all geospatial data used in this work are available nationally, the method could be adopted throughout the U.S. Hence, this GIS‐based watershed classification approach could provide water resources managers an effective decision‐support tool in managing reservoir water quality.     

Development of a SWAT Patch for Better Estimation of Sediment Yield in Steep Sloping Watersheds1

Abstract: The watershed scale Soil and Water Assessment Tool (SWAT) model divides watersheds into smaller subwatersheds for simulation of rainfall‐runoff and sediment loading at the field level and routing through stream networks. Typically, the SWAT model first needs to be calibrated and validated for accurate estimation through adjustment of sensitive input parameters (i.e., Curve Number values, USLE P, slope and slope‐length, and so on). However, in some instances, SWAT‐simulated results are greatly affected by the watershed delineation and Digital Elevation Models (DEM) cell size. In this study, the SWAT ArcView GIS Patch II was developed for steep sloping watersheds, and its performance was evaluated for various threshold values and DEM cell size scenarios when delineating subwatersheds using the SWAT model. The SWAT ArcView GIS Patch II was developed using the ArcView GIS Avenue program and Spatial Analyst libraries. The SWAT ArcView GIS Patch II improves upon the SWAT ArcView GIS Patch I because it reflects the topographic factor in calculating the field slope‐length of Hydrologic Response Units in the SWAT model. The simulated sediment value for 321 subwatersheds (watershed delineation threshold value of 25 ha) is greater than that for 43 subwatersheds (watershed delineation threshold value of 200 ha) by 201% without applying the SWAT ArcView GIS Patch II. However, when the SWAT ArcView GIS Patch II was applied, the difference in simulated sediment yield decreases for the same scenario (i.e., difference in simulated sediment with 321 subwatersheds and 43 subwatersheds) was 12%. The simulated sediment value for DEM cell size of 50 m is greater than that for DEM cell size of 10 m by 19.8% without the SWAT ArcView GIS Patch II. However, the difference becomes smaller (3.4% difference) between 50 and 10 m with the SWAT ArcView GIS Patch II for the DEM scenarios. As shown in this study, the SWAT ArcView GIS Patch II can reduce differences in simulated sediment values for various watershed delineation and DEM cell size scenarios. Without the SWAT ArcView GIS Patch II, variations in the SWAT‐simulated results using various watershed delineation and DEM cell size scenarios could be greater than those from input parameter calibration. Thus, the results obtained in this study show that the SWAT ArcView GIS Patch II should be used when simulating hydrology and sediment yield for steep sloping watersheds (especially if average slope of the subwatershed is >25%) for more accurate simulation of hydrology and sediment using the SWAT model. The SWAT ArcView GIS Patch II is available at http://www.EnvSys.co.kr/~swat for free download.     

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Stream ecosystems are increasingly at risk for thermal impairment as urbanization intensifies, resulting in more heated runoff from impervious cover that is less likely to be cooled naturally. While several best management practices, including bioretention filters, have been able to reduce thermal pollution, success has been limited. The extent of thermal mitigation required to prevent ecological damage remains unknown. A calibrated runoff temperature model of a case study watershed in Blacksburg, VA was developed to determine the cumulative treatment volume of bioretention filters required to reduce thermal impacts caused by runoff from development in the watershed to regulated biologically acceptable levels. A future build out scenario of the study watershed was also analyzed. Results from this study established that runoff thermal pollution cannot be fully reduced to goal thresholds during all storms using bioretention filter retrofits. While retrofitting significantly decreased temperatures and heat exports relative to the controls, increasing treatment volumes did not really enhance mitigation. Alternate thermal mitigation methods that actively remove runoff volume should be considered where more thermal mitigation is required.     

Locating Existing Best Management Practices Within a Watershed: The Value of Multiple Methods

There is an increasing need to document the impacts of conservation‐related best management practices (BMPs) on water quality within a watershed. However, this impact analysis depends upon accurate geospatial locations of existing practices, which are difficult to obtain. This study demonstrates and evaluates three different methods for obtaining geospatial information for BMPs. This study was focused on the Eagle Creek Watershed, a mixed use watershed in central Indiana. We obtained geospatial information for BMPs through government records, producer interviews, and remote‐sensing aerial photo interpretation. Aerial photos were also used to validate the government records and producer interviews. This study shows the variation in results obtained from the three sources of information as well as the benefits and drawbacks of each method. Using only one method for obtaining BMP information can be incomplete, and this study demonstrates how multiple methods can be used for the most accurate picture.     

Spatiotemporal Variability of Snow Depletion Curves Derived from SNODAS for the Conterminous United States, 2004‐2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental‐scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental‐extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1‐km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed‐scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed‐scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national‐scale categorization of snowmelt processes.     

The Road to NHDPlus — Advancements in Digital Stream Networks and Associated Catchments

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water‐related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium‐resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate‐and‐transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user‐defined applications.     

GIS‐Based Predictive Models of Hillslope Runoff Generation Processes1

Abstract: Successful nonpoint source pollution control using best management practice placement is a complex process that requires in‐depth knowledge of the locations of runoff source areas in a watershed. Currently, very few simulation tools are capable of identifying critical runoff source areas on hillslopes and those available are not directly applicable under all runoff conditions. In this paper, a comparison of two geographic information system (GIS)‐based approaches: a topographic index model and a likelihood indicator model is presented, in predicting likely locations of saturation excess and infiltration excess runoff source areas in a hillslope of the Savoy Experimental Watershed located in northwest Arkansas. Based on intensive data collected from a two‐year field study, the spatial distributions of hydrologic variables were processed using GIS software to develop the models. The likelihood indicator model was used to produce probability surfaces that indicated the likelihood of location of both saturation and infiltration excess runoff mechanisms on the hillslope. Overall accuracies of the likelihood indicator model predictions varied between 81 and 87% for the infiltration excess and saturation excess runoff locations respectively. On the basis of accuracy of prediction, the likelihood indicator models were found to be superior (accuracy 81‐87%) to the predications made by the topographic index model (accuracy 69.5%). By combining statistics with GIS, runoff source areas on a hillslope can be identified by incorporating easily determined hydrologic measurements (such as bulk density, porosity, slope, depth to bed rock, depth to water table) and could serve as a watershed management tool for identifying critical runoff source areas in locations where the topographic index or other similar methods do not provide reliable results.     

CLIMATE CHANGE IMPACTS ON WATER RESOURCES OF THE TSENGWEN CREEK WATERSHED IN TAIWAN1

ABSTRACT: This study presents a methodology to evaluate the vulnerability of water resources in the Tsengwen creek watershed, Taiwan. Tsengwen reservoir, located in the Tsengwen creek watershed, is a multipurpose reservoir with a primary function to supply water for the ChiaNan Irrigation District. A simulation procedure was developed to evaluate the impacts of climate change on the water resources system. The simulation procedure includes a streamflow model, a weather generation model, a sequent peak algorithm, and a risk assessment process. Three climate change scenarios were constructed based on the predictions of three General Circulation Models (CCCM, GFDL, and GISS). The impacts of climate change on streamflows were simulated, and, for each climate change scenario, the agricultural water demand was adjusted based on the change of potential evapotranspiration. Simulation results indicated that the climate change may increase the annual and seasonal streamflows in the Tsengwen creek watershed. The increase in streamflows during wet periods may result in serious flooding. In addition, despite the increase in streamflows, the risk of water deficit may still increase from between 4 and 7 percent to between 7 and 13 percent due to higher agricultural water demand. The simulation results suggest that the reservoir capacity may need to be expanded. In response to the climate change, four strategies are suggested: (1) strengthen flood mitigation measures, (2) enhance drought protection strategies, (3) develop new water resources technology, and (4) educate the public.     

PRISM vs. CFSR Precipitation Data Effects on Calibration and Validation of SWAT Models

Precipitation is one of the most important drivers in watershed models. Our objective was to compare two sources of interpolated precipitation data in terms of their effect on calibration and validation of two Soil and Water Assessment Tool (SWAT) models. One model was a suburban watershed in metropolitan Atlanta, Georgia. The precipitation sources were Parameter‐elevation Relationships on Independent Slopes Model (PRISM) data on a 4‐km grid and climate forecast system reanalysis (CFSR) data on a 38‐km grid. The PRISM data resulted in a better fit to the calibration data (Nash Sutcliffe efficiency [NSE] = 0.64, Kling‐Gupta efficiency [KGE] = 0.74, p‐factor = 0.84, and r‐factor = 0.43) than the CFSR data (NSE = 0.47, KGE = 0.53, p‐factor = 0.67, and r‐factor = 0.39). Validation results were similar. Sensitive parameters were similar in both the PRISM and CFSR models, but fitted values indicated more rapid groundwater flow to the streams with the PRISM data. The same comparison was made in the Big Creek watershed located approximately 1,000 km away, in central Louisiana. Results were similar with a more responsive groundwater system indicating PRISM data may produce better predictions of streamflow because of a more accurate estimate of rainfall within a watershed or because of a denser grid. Our study implies PRISM is providing a better estimate than CFSR of precipitation within a watershed when rain gauge data are not available, resulting in more accurate simulations of streamflows at the watershed outlet. 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 WATERSHED-LEVEL ECOLOGICAL RISK ASSESSMENT METHODOLOGY1

ABSTRACT: We present an ecological risk assessment methodology at the watershed level for freshwater ecosystems. The major component is a pollutant transport and fate model (a modified EUTROMOD) with an integrated uncertainty analysis utilizing a two-phase Monte Carlo procedure. The uncertainty analysis methodology distinguishes between knowledge uncertainty and stochastic variability. The model assesses the ecological risk of lentic (lake) ecosystems in response to the stress of excess phosphorus resulting in eutrophication. The methodology and model were tested on the Wister Lake watershed in Oklahoma with the lake and its trophic state as the endpoint for ecological risk assessment. A geographic information system was used to store, manage, and manipulate spatially referenced data for model input.     

DEVELOPMENT OF WATERSIIED MODELS FOR TWO SIERRA NEVADA BASINS USING A GEOGRAPHIC INFORMATION SYSTEM1

ABSTRACT: Techniques were developed using vector and raster data in a geographic information system (GIS) to define the spatial variability of watershed characteristics in the north-central Sierra Nevada of California and Nevada and to assist in computing model input parameters. The U.S. Geological Survey's Precipitation-Runoff Modeling System, a physically based, distributed-parameter watershed model, simulates runoff for a basin by partitioning a watershed into areas that each have a homogeneous hydrologic response to precipitation or snowmelt. These land units, known as hydrologic-response units (HRU's), are characterized according to physical properties, such as altitude, slope, aspect, land cover, soils, and geology, and climate patterns. Digital data were used to develop a GIS data base and HRIJ classification for the American River and Carson River basins. The following criteria are used in delineating HRU's: (1) Data layers are hydrologically significant and have a resolution appropriate to the watershed's natural spatial variability, (2) the technique for delineating HRU's accommodates different classification criteria and is reproducible, and (3) HRU's are not limited by hydrographic-subbasin boundaries. HRU's so defined are spatially noncontiguous. The result is an objective, efficient methodology for characterizing a watershed and for delineating HRU's. Also, digital data can be analyzed and transformed to assist in defining parameters and in calibrating the model.     

WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.     

Application of Tabu Search Algorithm With a Coupled AnnAGNPS‐CCHE1D Model to Optimize Agricultural Land Use1

Abstract: A principal contributor to soil erosion and nonpoint source pollution, agricultural activities have a major influence on the environmental quality of a watershed. Impact of agricultural activities on the quality of water resources can be minimized by implementing suitable agriculture land‐use types. Currently, land uses are designed (location, type, and operational schedule) based on field study results, and do not involve a science‐based approach to ensure their efficiency under particular regional, climatic, geological, and economical conditions. At present, there is a real need for new methodologies that can optimize the selection, design, and operation of agricultural land uses at the watershed scale by taking into account environmental, technical, and economical considerations, based on realistic simulations of watershed response. In this respect, the present study proposes a new approach, which integrates computational modeling of watershed processes, fluvial processes in the drainage network, and modern heuristic optimization techniques to design cost effective land‐use plans. The watershed model AnnAGNPS and the channel network model CCHE1D are linked together to simulate the sediment and pollutant transport processes. Based on the computational results, a multi‐objective function is set up to minimize soil losses, nutrient yields, and total associated costs, while the production profits from agriculture are maximized. The selected iterative optimization algorithm uses adaptive Tabu Search heuristic to flip (switching from one alternative to another) land‐change variables. USDA’s Goodwin Creek experimental watershed, located in Northern Mississippi, is used to demonstrate the capabilities of the proposed approach. The results show that the optimized land‐use design with BMPs using an integrated approach at the watershed level can provide efficient and cost‐effective conservation of the environmental quality by taking into account both productivity and profitability.