Document Type
Thesis - Open Access
Award Date
2026
Degree Name
Master of Science (MS)
Department / School
Agricultural and Biosystems Engineering
First Advisor
Sushant Mehan
Abstract
Water-quality impairment from sediment, nutrients, and microbial contamination motivated implementation of the Seasonal Riparian Area Management (SRAM) program in the Skunk Creek watershed of eastern South Dakota. SRAM restricts livestock grazing within floodplain pastures during the growing season to promote vegetation recovery and reduce pollutant transport. This study evaluated SRAM effectiveness using an integrated framework combining remote sensing, water-quality trend analysis, land-use change assessment, economic evaluation, and watershed-scale modeling with SWAT+. Vegetation analysis using satellite-derived indices showed significant post-enrollment improvement, with 24, 25, and 26 polygons showing increases in Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index-2 (EVI2), respectively, and 19 polygons improving across all three. Median annual increases were 0.065 (NDVI), 0.057 (SAVI), and 0.060 (EVI2). Water-quality trend analysis detected significant changes between late 2016 and late 2017, with declining trends in TDS, TSS, E. coli, and nitrate + nitrite. Interrupted time-series analysis showed improved model fit when SRAM and vegetation indicators were included, with adjusted R² for E. coli increasing from 0.20 to 0.34. Land-use analysis showed Pastureland expanded in 73 of 114 enrolled polygons, with a cumulative gain of 205.68 acres. Economic evaluations indicated favorable outcomes, with public and private benefit-cost ratios of 1.3 and 1.8 (with incentive payments), respectively. SWAT+ model performance was satisfactory, with Nash-Sutcliffe Efficiency (NSE) values of 0.67 and 0.80 for streamflow, 0.48 and 0.61 for sediment, and 0.47 and 0.66 for nitrate during calibration and validation. Targeted conversion within sediment critical source areas (CSAs) reduced mean annual sediment loads by 25%, 40%, and >50% across Tiers 1, 1+2, and 1+2+3. Targeting nitrate CSAs reduced loads by 8%, 16%, and 30%, with sediment reductions of 10%, 17%, and 34%. Restricting conversion to non-urban, non-wetland floodplain nitrate CSAs (0.45–13.19% of watershed area) resulted in nitrate reductions of approx. 5% to >50%, with smaller sediment reductions (< 5% to approx. 15%). Overall, SRAM contributes to improved riparian vegetation and favorable economic outcomes. Watershed-scale water-quality improvements are most effective when conservation practices target critical pollutant source areas, demonstrating the value of integrating remote sensing, monitoring data, and hydrologic modeling for riparian conservation evaluation.
Publisher
South Dakota State University
Recommended Citation
Pokhrel, Tulsi Ram, "Evaluating Seasonal Riparian Area Management as a Nature-Based Solution for Protecting Stream Water Quality Using Remote Sensing, Time-Series Analysis, and Hydrologic Modeling" (2026). Electronic Theses and Dissertations. 2023.
https://openprairie.sdstate.edu/etd2/2023
Rights Statement
