The Appalachian Mountain region of eastern Kentucky is unique and contains high proportions of forestland along with coal and natural gas depositaries. Landscape changes due to extreme mining activities can eventually threaten the downstream ecosystems, including soil and water quality, resulting in excessive runoff and sedimentation. The purpose of this study is to assess the impacts of land-use and land-cover (LULC) changes in streamflow and sediment yield in Yellow Creek Watershed, Kentucky, USA, between 1992 and 2016. LULC, digital elevation model, soil, and weather data were inputted into the Soil and Water Assessment Tool (SWAT) to simulate discharge and sediment yield. The model output was evaluated on several statistical parameters, such as the Nash-Sutcliffe efficiency coefficient (NSE), RMSE-observations standard deviation ratio (RSR), percent bias (PBIAS), and the coefficient of determination (R²). In addition, two indices, P-factor and R-factor, were used to measure the prediction uncertainty. The calibrated model showed an increase in surface runoff and sediment yield due to changes in LULC in the Yellow Creek Watershed. The results provided important insights for studying water management strategies to make more informed land management decisions and adaptive practices.

In-stream watershed level evaluations confirm that application of recommended forestry best management practices (BMPs) can minimize sedimentation following management, while on-site erosion research shows that BMPs reduce erosion from individual forest operations, thus implying watershed-level sediment reductions. Assessments of forest operations and sediment have developed very few sediment delivery ratios (SDR). Linking BMP levels (low, standard recommendation, high) within specific forest operations to sedimentation could enable managers to evaluate BMP effects. Reported data regarding forest operations, erosion rates and SDR by forest operation, and BMP implementation levels were sufficient within the Piedmont region to allow approximations of sediment delivery and BMP efficiency. Existing United States Department of Agriculture (USDA) Forest Service reports and published erosion and sediment research were used to comprise the following method. For regional annual harvests, estimated sediment deliveries (Mg year⁻¹) = annual harvest area (ha year⁻¹) × weighted average erosion rate from all forest operations (Mg ha⁻¹ year⁻¹) × SDR (unitless ratio). Weighted average erosion rates for all forest operations were determined by applying areas in each operational activity (%) × estimated erosion per operation (Mg ha⁻¹ year⁻¹). In comparing published data, standard BMPs reduced estimated sedimentation by 75% compared to low BMP implementation levels. This supports forestry BMP efficiency findings reported for sediment removals in watershed studies. Higher levels of BMP implementation were estimated to potentially remove nearly all forest operation-produced sediment. Values of this pilot study should be viewed cautiously, as estimates were based on limited data, estimated operations, and limited SDRs; are based on BMP categories that vary between states; and address only one year following harvests. However, the approach provided approximations that facilitate BMP evaluations and can be improved with additional data. This methodology highlights the importance of accurate estimates of erosion rates, SDRs, sediment masses, and area for operations. This supports the importance of state programs, which have increased BMP implementation rates and compliance options with BMP program maturation.