Modeling Effects of Natural Flow Restoration on Metals Fate and Transport in a Mountain Stream Impacted by Mine Waste1

Abstract: The effects of natural flow restoration on metals fate and transport in the Upper Tenmile Creek Watershed, Montana, were modeled using the Water Quality Analysis Simulation Program developed by the U.S. Environmental Protection Agency (USEPA). This 50‐km² watershed has over 150 historic abandoned mines, including mine waste rock and tailings, as well as adits discharging acid mine drainage, and is the primary drinking water supply for the City of Helena. Water supply diversions almost completely dewater some stream reaches during summer low flows, but the city is considering a new drinking water source and restoration of natural flows in Tenmile Creek as part of acid mine drainage remediation and broader aquatic habitat restoration. One dimensional steady‐state simulation of total recoverable cadmium, copper, lead, and zinc in the mainstem was performed, and the model was calibrated to June 2000 base‐flow data. Representative low‐flows in August and high‐flow snowmelt conditions in June were modeled using mean monthly natural flow estimates from the U.S. Geological Survey and representative USEPA metals concentrations data. The modeling showed that total recoverable metals concentrations, and especially loads, can vary significantly among input locations and over time in the watershed. Some data gaps limit evaluation of variability and increase uncertainty in several locations. Model results indicated, however, that natural low‐ and high‐flow restoration by itself can reduce some metals concentrations in the mainstem compared to June 2000 values, which were influenced by significant water diversion. Some values (such as Zn) may still exceed standards during natural August low flow due to the remaining high concentrations and loads in the primary inputs to the mainstem. Others (such as Cu) can increase during high flow due to remaining mine waste sources and loading of particulate Cu associated with erosion and transport of solids. Greater than 50% reduction in concentrations and loads from some of the main tributaries may be necessary to meet all standards, especially for potential particulate loads with higher flows in June.     

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.     

EPA'S BASINS MODEL: GOOD SCIENCE OR SERENDIPITOUS MODELING?1

ABSTRACT: Better Assessment Science Integrating Point and Non‐point Sources (BASINS) is a geographic‐based watershed assessment tool developed by EPA's Office of Water to help states more efficiently target and evaluate water‐bodies that are not meeting water quality standards. BASINS (EPA, 1996a, 1998) brings together data on water quality and quantity, land uses, point source loadings, and other related spatial data with supporting nonpoint and water quality models at a quicker and more effective pace. EPA developed BASINS, to better integrate point and nonpoint source water quality assessments for the Nation's 2100+ watersheds. In its zeal to achieve this endpoint, EPA has initiated a simplistic approach that was expected to grow through scientific enhancements as TMDL developers become more familiar with modeling requirements. BASINS builds upon federal databases of water quality conditions and point source loadings for numerous parameters where quality assurance is suspect in some cases. Its design allows comprehensive assessments and modeling in typical Total Maximum Daily Load (TMDL) computations. While the TMDL utility is the primary reason BASINS was developed, other longer‐range water quality assessments will become possible as the Agency expands the suite of assessment models and databases in future releases. The simplistic approach to modeling and user‐friendly tools gives rise, however, to technical and philosophical concerns related to default data usage. Seamless generation of model input files and the failure of some utilities to work properly suggest to NCASI that serious problems may still exist and prompts the need for a more rigorous peer‐review. Furthermore, sustainable training becomes paramount, as some older modelers will be unfamiliar with Geographic Information System (GIS) technology and associated computer skills. Overall, however, BASINS was judged to be an excellent beginning tool to meet the complex environmental modeling needs in the 21st Century.     

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.     

WALNUT CREEK WATERSHED MONITORING PROJECT,IOWA MONITORING WATER QUALITY IN RESPONSE TO PRAIRIE RESTORATION1

ABSTRACT: Land use and surface water data for nitrogen and pesticides (1995 to 1997) are reported for the Walnut Creek Watershed Monitoring Project, Jasper County Iowa. The Walnut Creek project was established in 1995 as a nonpoint source monitoring program in relation to watershed habitat restoration and agricultural management changes implemented at the Neal Smith National Wildlife Refuge by the U.S. Fish and Wildlife Service. The monitoring project utilizes a paired‐watershed approach (Walnut and Squaw creeks) as well as upstream/downstream comparisons on Walnut for analysis and tracking of trends. From 1992 to 1997, 13.4 percent of the watershed was converted from row crop to native prairie in the Walnut Creek watershed. Including another 6 percent of watershed farmed on a cash‐rent basis, land use changes have been implemented on 19.4 percent of the watershed by the USFWS. Nitrogen and pesticide applications were reduced an estimated 18 percent and 28 percent in the watershed from land use changes. Atrazine was detected most often in surface water with frequencies of detection ranging from 76–86 percent. No significant differences were noted in atrazine concentrations between Walnut and Squaw Creek. Nitrate‐N concentrations measured in both watersheds were similar; both basins showed a similar pattern of detection and an overall reduction in nitrate‐N concentrations from upstream to downstream monitoring sites. Water quality improvements are suggested by nitrate‐N and chloride ratios less than one in the Walnut Creek watershed and low nitrate‐N concentrations measured in the subbasin of Walnut Creek containing the greatest amount of land use changes. Atrazine and nitrate‐N concentrations from the lower portion of the Walnut Creek watershed (including the prairie restoration area) may be decreasing in relation to the upstream untreated component of the watershed. The frequencies of pesticide detections and mean nitrate‐N concentrations appear related to the percentage of row crop in the basins and subbasins. Although some results are encouraging, definitive water quality improvements have not been observed during the first three years of monitoring. Possible reasons include: (1) more time is needed to adequately detect changes; (2) the size of the watershed is too large to detect improvements; (3) land use changes are not located in the area of the watershed where they would have greatest effect; or (4) water quality improvements have occurred but have been missed by the project monitoring design. Longer‐term monitoring will allow better evaluation of the impact of restoration activities on water quality.     

Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program1

Kardos, Josef S. and Christopher C. Obropta, 2011. Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program. Journal of the American Water Resources Association (JAWRA) 47(6):1317–1337. DOI: 10.1111/j.1752‐1688.2011.00591.x Abstract: Water quality modeling is a major source of scientific uncertainty in the Total Maximum Daily Load (TMDL) process. The effects of these uncertainties extend to water quality trading programs designed to implement TMDLs. This study examines the effects of water quality model uncertainty on a nutrient trading program. The study builds on previous work to design a phosphorus trading program for the Nontidal Passaic River Basin in New Jersey that would implement the watershed TMDL for total phosphorus (TP). The study identified how water quality model uncertainty affects outcomes of potential trades of TP between wastewater treatment plants. The uncertainty analysis found no evidence to suggest that the outcome of trades between wastewater treatment plants, as compared with command and control regulation, will significantly increase uncertainty in the attainment of dissolved oxygen surface water quality standards, site‐specific chlorophyll a criteria, and reduction targets for diverted TP load at potential hot spots in the watershed. Each simulated trading scenario demonstrated parity with or improvement from the command and control approach at the TMDL critical locations, and low risk of hot spots elsewhere.     

MODELING THE BIG BLACK RIVER: A COMPARISON OF WATER QUALITY MODELS1

ABSTRACT: The Mississippi Department of Environmental Quality uses the Steady Riverine Environmental Assessment Model (STREAM) to establish effluent limitations. While the U.S. Environmental Protection Agency has approved of its use, questions arise regarding the model's simplicity. The objective of this research was to compare STREAM with the more commonly utilized Enhanced Stream Water Quality Model (QUAL2E). The comparison involved a statistical evaluation procedure based on sensitivity analyses, input probability distribution functions, and Monte Carlo simulation with site‐specific data from a 46‐mile (74‐km) reach of the Big Black River in central Mississippi. Site specific probability distribution functions were derived from measured rates of reaeration, sediment oxygen demand, photosynthesis, and respiration. Both STREAM and QUAL2E reasonably predicted daily average dissolved oxygen (DO) based on a comparison of output probability distributions with observed DO. Observed DO was consistently within 90 percent confidence intervals of model predictions. The STREAM approach generally overpredicted while QUAL2E generally matched observed DO. Using the more commonly assumed lognormal distribution as opposed to a Weibull distribution for two of the sensitive input parameters resulted in minimal differences in the statistical evaluations. The QUAL2E approach had distinct advantages over STREAM in simulating the growth cycle of algae.     

Assessing BMP Effectiveness and Guiding BMP Planning Using Process‐Based Modeling

There is an increasing need for improved process‐based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process‐based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long‐term improvement in water quality of these three watersheds has yet to be completely realized.     

An Open Source GIS‐Based Decision Support System for Watershed Evaluation of Best Management Practices

Economic costs, water quantity/quality benefits, and cost effectiveness of agricultural best management practices (BMPs) at a watershed scale are increasingly examined using integrated economic‐hydrologic models. However, these models are typically complex and not user‐friendly for examining the effects of various BMP scenarios. In this study, an open source geographic information system (GIS)‐based decision support system (DSS), named the watershed evaluation of BMPs (WEBs), was developed for creating BMP scenarios and simulating economic costs and water quantity/quality benefits at farm field, subbasin, and watershed scales. This DSS or WEBs interface integrated a farm economic model, the Soil and Water Assessment Tool (SWAT), and an optimization model within Whitebox Geospatial Analysis Tools (GAT), an open source GIS software. The DSS was applied to the 14.3‐km² Gully Creek watershed, a coastal watershed in southern Ontario, Canada that drains directly into Lake Huron. BMPs that were evaluated included conservation tillage, nutrient management, cover crop, and water and sediment control basins. In addition to assessing economic costs, water quantity/quality benefits, and cost effectiveness of BMPs, the DSS can be also used to examine prioritized BMP types/locations and corresponding economic and water quantity/quality tradeoffs in the study watershed based on environmental targets or budget constraints. Further developments of the DSS including interface transfer to other watersheds are also discussed. 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.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

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.     

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.     

Developing Subseasonal to Seasonal Climate Forecast Products for Hydrology and Water Management

We describe a new effort to enhance climate forecast relevance and usability through the development of a system for evaluating and displaying real‐time subseasonal to seasonal (S2S) climate forecasts on a watershed scale. Water managers may not use climate forecasts to their full potential due to perceived low skill, mismatched spatial and temporal resolutions, or lack of knowledge or tools to ingest data. Most forecasts are disseminated as large‐domain maps or gridded datasets and may be systematically biased relative to watershed climatologies. Forecasts presented on a watershed scale allow water managers to view forecasts for their specific basins, thereby increasing the usability and relevance of climate forecasts. This paper describes the formulation of S2S climate forecast products based on the Climate Forecast System version 2 (CFSv2) and the North American Multi‐Model Ensemble (NMME). Forecast products include bi‐weekly CFSv2 forecasts, and monthly and seasonal NMME forecasts. Precipitation and temperature forecasts are aggregated spatially to a United States Geological Survey (USGS) hydrologic unit code 4 (HUC‐4) watershed scale. Forecast verification reveals appreciable skill in the first two bi‐weekly periods (Weeks 1–2 and 2–3) from CFSv2, and usable skill in NMME Month 1 forecast with varying skills at longer lead times dependent on the season. Application of a bias‐correction technique (quantile mapping) eliminates forecast bias in the CFSv2 reforecasts, without adding significantly to correlation skill.     

Modeling Streamflow and Water Quality Sensitivity to Climate Change and Urban Development in 20 U.S. Watersheds

Watershed modeling in 20 large, United States (U.S.) watersheds addresses gaps in our knowledge of streamflow, nutrient (nitrogen and phosphorus), and sediment loading sensitivity to mid‐21st Century climate change and urban/residential development scenarios. Use of a consistent methodology facilitates regional scale comparisons across the study watersheds. Simulations use the Soil and Water Assessment Tool. Climate change scenarios are from the North American Regional Climate Change Assessment Program dynamically downscaled climate model output. Urban and residential development scenarios are from U.S. Environmental Protection Agency's Integrated Climate and Land Use Scenarios project. Simulations provide a plausible set of streamflow and water quality responses to mid‐21st Century climate change across the U.S. Simulated changes show a general pattern of decreasing streamflow volume in the central Rockies and Southwest, and increases on the East Coast and Northern Plains. Changes in pollutant loads follow a similar pattern but with increased variability. Ensemble mean results suggest that by the mid‐21st Century, statistically significant changes in streamflow and total suspended solids loads (relative to baseline conditions) are possible in roughly 30‐40% of study watersheds. These proportions increase to around 60% for total phosphorus and total nitrogen loads. Projected urban/residential development, and watershed responses to development, are small at the large spatial scale of modeling in this study.     

Spatial and Temporal Evaluation of Hydrological Response to Climate and Land Use Change in Three South Dakota Watersheds

This study analyzed changes in hydrology between two recent decades (1980s and 2010s) with the Soil and Water Assessment Tool (SWAT) in three representative watersheds in South Dakota: Bad River, Skunk Creek, and Upper Big Sioux River watersheds. Two SWAT models were created over two discrete time periods (1981‐1990 and 2005‐2014) for each watershed. National Land Cover Datasets 1992 and 2011 were, respectively, ingested into 1981‐1990 and 2005‐2014 models, along with corresponding weather data, to enable comparison of annual and seasonal runoff, soil water content, evapotranspiration (ET), water yield, and percolation between these two decades. Simulation results based on the calibrated models showed that surface runoff, soil water content, water yield, and percolation increased in all three watersheds. Elevated ET was also apparent, except in Skunk Creek watershed. Differences in annual water balance components appeared to follow changes in land use more closely than variation in precipitation amounts, although seasonal variation in precipitation was reflected in seasonal surface runoff. Subbasin‐scale spatial analyses revealed noticeable increases in water balance components mostly in downstream parts of Bad River and Skunk Creek watersheds, and the western part of Upper Big Sioux River watershed. Results presented in this study provide some insight into recent changes in hydrological processes in South Dakota 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.     

MODELING METALS TRANSPORT AND SEDIMENT/WATER INTERACTIONS IN A MINING IMPACTED MOUNTAIN STREAM1

ABSTRACT: The U.S. Environmental Protection Agency (USEPA) Water Quality Analysis Simulation Program (WASP5) was used to model the transport and sediment/water interactions of metals under low flow, steady state conditions in Tenmile Creek, a mountain stream supplying drinking water to the City of Helena, Montana, impacted by numerous abandoned hard rock mines. The model was calibrated for base flow using data collected by USEPA and validated using data from the U.S. Geological Survey (USGS) for higher flows. It was used to assess metals loadings and losses, exceedances of Montana State water quality standards, metals interactions in stream water and bed sediment, uncertainty in fate and transport processes and model parameters, and effectiveness of remedial alternatives that include leaving contaminated sediment in the stream. Results indicated that during base flow, adits and point sources contribute significant metals loadings to the stream, but that shallow ground water and bed sediment also contribute metals in some key locations. Losses from the water column occur in some areas, primarily due to adsorption and precipitation onto bed sediments. Some uncertainty exists in the metal partition coefficients associated with sediment, significance of precipitation reactions, and in the specific locations of unidentified sources and losses of metals. Standards exceedances are widespread throughout the stream, but the model showed that remediation of point sources and mine waste near water courses can help improve water quality. Model results also indicate, however, that alteration of the water supply scheme and increasing base flow will probably be required to meet all water quality standards.     

Influence of Bioenergy Crop Production and Climate Change on Ecosystem Services

Land use change can significantly affect the provision of ecosystem services and the effects could be exacerbated by projected climate change. We quantify ecosystem services of bioenergy‐based land use change and estimate the potential changes of ecosystem services due to climate change projections. We considered 17 bioenergy‐based scenarios with Miscanthus, switchgrass, and corn stover as candidate bioenergy feedstock. Soil and Water Assessment Tool simulations of biomass/grain yield, hydrology, and water quality were used to quantify ecosystem services freshwater provision (FWPI), food (FPI) and fuel provision, erosion regulation (ERI), and flood regulation (FRI). Nine climate projections from Coupled Model Intercomparison Project phase‐3 were used to quantify the potential climate change variability. Overall, ecosystem services of heavily row cropped Wildcat Creek watershed were lower than St. Joseph River watershed which had more forested and perennial pasture lands. The provision of ecosystem services for both study watersheds were improved with bioenergy production scenarios. Miscanthus in marginal lands of Wildcat Creek (9% of total area) increased FWPI by 27% and ERI by 14% and decreased FPI by 12% from the baseline. For St. Joseph watershed, Miscanthus in marginal lands (18% of total area) improved FWPI by 87% and ERI by 23% while decreasing FPI by 46%. The relative impacts of land use change were considerably larger than climate change impacts in this paper. 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.     

Assessment of Future Drought Conditions in the Chesapeake Bay Watershed

Impacts of climate change on the severity and intensity of future droughts can be evaluated based on precipitation and temperature projections, multiple hydrological models, simulated hydrometeorological variables, and various drought indices. The objective of this study was to assess climate change impacts on future drought conditions and water resources in the Chesapeake Bay (CB) watershed. In this study, the Soil and Water Assessment Tool (SWAT) and the Variable Infiltration Capacity model were used to simulate a Modified Palmer Drought Severity Index (MPDSI), a Standardized Soil Moisture index (SSI), a Multivariate Standardized Drought Index (MSDI), along with Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for both historical and future periods (f1: 2020‐2049, f2: 2050‐2079). The results of the SSI suggested that there was a general increase in agricultural droughts in the entire CB watershed because of increases in surface and groundwater flow and evapotranspiration. However, MPDSI and MSDI showed an overall decrease in projected drought occurrences due to the increases in precipitation in the future. The results of this study suggest that it is crucial to use multiple modeling approaches with specific drought indices that combine the effects of both precipitation and temperature changes.     

Evaluation of SWAT Impoundment Modeling Methods in Water and Sediment Simulations

Worldwide studies show 80%–90% of all sediments eroded from watersheds is trapped within river networks such as reservoirs, ponds, and wetlands. To represent the impact of impoundments on sediment routing in watershed modeling, Soil and Water Assessment Tool (SWAT) developers recommend to model reservoirs, ponds, and wetlands using impoundment tools (ITs). This study evaluates performance of SWAT ITs in the modeling of a small, agricultural watershed dominated by lakes and wetlands. The study demonstrates how to incorporate impoundments into the SWAT model, and discusses and evaluates involved parameters. The study then recommends an appropriate calibration sequence, i.e., landscape parameters calibration, followed by pond/wetlands calibration, then channel parameter calibrations, and lastly, reservoir parameter calibration. Results of this study demonstrate not following SWAT recommendation regarding modeling water land use as an impoundment depreciates SWAT performance, and may lead to misplaced calibration efforts and model over‐calibration. Further, the chosen method to model impoundments’ outflow significantly impacts sediment loads in the watershed, while streamflow simulation is not very sensitive. This study also allowed calculation of mass accumulation rates in modeled impoundments where the annual mass accumulation rate in wetlands (2.3 T/ha/yr) was 39% higher than mass accumulation rate in reservoirs (1.4 T/ha/yr).