Hydrological models have been increasingly used for the effect of land cover change and forest management operations on hydrological processes. In the Sierra Nevada, where timber harvest and prescribed fire are commonly employed for forest management, hydrological models have rarely been used, especially in small watersheds. In this research, the SWAT model (Soil Water and Assessment Tool) was used to simulate streamflow on a daily time-step in P301, a small headwater mountain watershed located in the southern Sierra Nevada. The watershed is 1 km2, where about 72% of the land is covered by a dense mixed-conifer forest. SWAT performs satisfactorily with a coefficient of determination (R2) of 0.59 and a Nash-Sutcliffe efficiency value (NSE) of 0.59. This is important to know given the complexity arising from model uncertainty and the intricacies of Sierra Nevada hydrology. Although SWAT performed "satisfactory", the model still missed two key hydrological processes: the timing of snowmelt and isolated peak flow events. In addition, simulating streamflow on the daily time-step is good for understanding watershed processing and functioning but is not as useful for forest and land management. SWAT will need further model adjustments as well as monthly and yearly water yield estimates in order to be considered for the evaluation of forest management operations in P301.

This is a comprehensive resource that integrates the application of innovative remote sensing techniques and geospatial tools in modeling Earth systems for environmental management beyond customary digitization and mapping practices. It identifies the most suitable approaches for a specific environmental problem, emphasizes the importance of physically based modeling, their uncertainty analysis, advantages, and disadvantages. The case studies on the Himalayas with a complex topography call for innovation in geospatial techniques to find solutions for various environmental problems. Features: Presents innovative geospatial methods in environmental modeling of Earth systems. Includes case studies from South Asia and discusses different processes and outcomes using spatially explicit models. Explains contemporary environmental problems through the analysis of various information layers. Provides good practices for developing countries to help manage environmental issues using low-cost geospatial approaches. Integrates geospatial modeling with policy and analysis its direct implication in decision making. Using a systems’ approach analysis, Geospatial Modeling for Environmental Management: Case Studies from South Asia shall serve environmental managers, students, researchers, and policymakers.

The deterioration of water quality due to human-driven alternations has an adverse effect on the environment. More than 50% of surveyed surface water bodies in the United States (US) are classified as impaired waters as per the Clean Water Act. The pollutants affecting the water quality in the US are classified as point and non-point sources. Pollutant mitigation strategies such as the selective implementation of best management practices (BMPs) based on the severity of the pollution could improve water quality by reducing the amounts of pollutants. Quantifying the efficiency of a specific management practice can be difficult for large watersheds. Complex hydrologic models are used to assess water quality and quantity at watershed scales. This study used a Soil and Water Assessment Tool (SWAT) that can simulate a longer time series for hydrologic and water quality assessments in the Yazoo River Watershed (YRW). This research aims to estimate streamflow, sediment, and nutrient load reductions by implementing various BMPs in the watershed. BMPs such as vegetative filter strips (VFS), riparian buffers, and cover crops were applied in this study. Results from these scenarios indicated that the combination of VFS and riparian buffers at the watershed scale had the highest reduction in sediment and nutrient loads. Correspondingly, a comparative analysis of BMP implementation at the field and watershed scale showed the variability in the reduction of streamflow, sediment, and nutrient loads. The results indicated that combining VFS and CC at the field scale watershed had a greater nutrient reduction than at the watershed scale. Likewise, this study investigated the soil-specific sediment load assessments for predominant soils in the YRW, which resulted in soil types of Alligator, Sharkey, and Memphis soils being highly erodible from the agricultural-dominant region. This study also included the effect of historical land use and land-cover (LULC) change on water quality. The analysis revealed that there was a significant decrease in pastureland and a simultaneous increase in forest and wetlands, which showed a decreasing trend in hydrologic and water quality outputs. Results from this study could be beneficial in decision-making for prescribing appropriate conservation practices

Distributed watershed hydrologic/water quality (H/WQ) models are ubiquitous tools for watershed management. Despite advancements, there remain impediments for end-users. This study presents a practical framework for use of the soil and water assessment tool (SWAT). Results show variable accuracy across scales and evaluation methods using 20 model configurations based on two watershed subdivisions, two soil datasets, and five climate datasets. Nine goodness-of-fit indicators were tested, including four new indices (R-RMSE, R-MAE, R-NSE, and R-NSE1) designed to quantify model fit with flow distribution. Sixteen of 20 configurations achieved satisfactory monthly streamflow fit (NSE [greater than] 0.5, PBIAS [lesser than] 25%) without calibration. Watershed and soil resolution had negligible impact; climate input had considerable impact. Single climate station input is best used for applications requiring monthly predictions; distributed climate station input is needed for daily predictions. SWAT multi-objective auto-calibration better predicted monthly flow (PBIAS=1%, NSE=0.8) than single-objective calibration (PBIAS=16%, NSE=0.5). SWAT performs well in Central U.S. urbanizing watersheds. Accuracy can improve with auto-calibration as presented and continued model development.

Precipitation changes and urban growth are two factors altering the state of water quality. Changes in precipitation will alter the amount and timing of flows, and the corresponding sediment and nutrient dynamics. Meanwhile, densification associated with urban growth will create more impervious surfaces which will alter sediment and nutrient loadings. Land and water managers often rely on models to develop possible future scenarios and devise management responses to these projected changes. We use the Soil and Water Assessment Tool (SWAT) to assess the sensitivities of stream flow, sediment, and nutrient loads in two urbanizing watersheds in Northwest Oregon, USA to various climate and urbanization scenarios. We evaluate the spatial patterns climate change and urban growth will have on water, sediment and nutrient yields. We also identify critical source areas (CSAs) and investigate how implementation of vegetative filter strips (VFS) could ameliorate the effects of these changes. Our findings suggest that: 1) Water yield is tightly coupled to precipitation. 2) Large increases in winter and spring precipitation provide enough sub-surface storage to increase summertime water yields despite a moderate decrease in summer precipitation. 3) Expansion of urban areas increases surface runoff and has mixed effects on sediment and nutrients. 4) Implementation of VFS reduces pollutant loads helping overall watershed health. This research demonstrates the usefulness of SWAT in facilitating informed land and water management decisions.

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, used the Soil and Water Assessment Tool to simulate streamflow and nitrate loads within the Cedar River Basin, Iowa. The goal was to assess the ability of the Soil and Water Assessment Tool to estimate streamflow and nitrate loads in gaged and ungaged basins in Iowa. The Cedar River Basin model uses measured streamflow data from 12 U.S. Geological Survey streamflowgaging stations for hydrology calibration. The U.S. Geological Survey software program, Load Estimator, was used to estimate annual and monthly nitrate loads based on measured nitrate concentrations and streamflow data from three Iowa Department of Natural Resources Storage and Retrieval/Water Quality Exchange stations, located throughout the basin, for nitrate load calibration.