RESUMEN
Climate and land-use changes have an overlying impact on non-point source (NPS) pollution in river basins. However, the control effect of Best Management Practices (BMPs) for NPS pollution is not yet clear under future scenarios. The Soil and Water Assessment Tool (SWAT) model was coupled with the entropy-weighted method, global climate patterns and land-use data to explore the dynamic variations in total nitrogen (TN) and total phosphorus (TP) loads in the Jing River Basin during the baseline (2000-2020) and future periods (2021-2065), evaluate the pollution reduction effectiveness of individual and combined BMPs, and propose practical BMP configurations. Results indicate that a future trend of urban land expansion, particularly in the economic scenario (LU_SSP585), leads to weakened environmental ecosystems, while the sustainable scenario (LU_SSP126) exhibits more balanced land development. The MIROC-ES2L model demonstrates higher Taylor skill scores, forecasted significant increases in precipitation, maximum, and minimum temperatures under the SSP585 scenario. Spatial heterogeneity in TN and TP loads is notable, showing an upward trajectory in the future. The interaction between land-use and climate change has complex effects on TN and TP loads, with land-use-induced TN changes being relatively small (4.6 %) and TP changes substantial (24.3 %). The spatial distribution, under overlying effects, leans towards the influence of climate change, emphasizing its dominant role in TN and TP load variations. Distinct differences exist in the reduction of NPS pollution loads among different BMPs, with combined BMPs demonstrating superior effectiveness. The environmental-cost effectiveness trends of BMPs remain consistent across various future scenarios. RG (Return agricultural land to grass), RG + TT (Terracing), and RG + FR10 (Fertilizer reduction: 10 %) + GW (Grassed waterway) + FS (Filter strip) + TT emerge as the most effective single, double, and multiple BMP combinations, respectively. The results offer valuable insights for preventing and mitigating future NPS pollution risks, optimizing land-use layouts, and enhancing watershed management decisions.
RESUMEN
Best management practices (BMPs) have been extensively employed in effective watershed management for non-point source pollution. The weights of objective functions and the restrictive conditions of combined BMPs are the vital requirements for BMPs allocation. Therefore, it is more beneficial to explore that a spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination. Here is the novel framework based on Soil and Water Assessment Tool (SWAT) and the Non-dominated Sorting Genetic Algorithm II (NSGA-â ¡), which considers multiple objectives in deriving watershed-scale pollution control practices by considering BMPs cost and combined reduction rates of total nitrogen (TN) and total phosphorus (TP). The framework also integrates combined Entropy Weight method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the weights of TN and TP, and considers the attributes of the sub-basin itself, which is more local suitability. Four categories of BMPs, tillage management, nutrient management, vegetative filter strips, and landscape management, were evaluated in the Jing River Basin (JRB) and resulted in reduction rates of 9.77%, 10.53%, 16.40%, and 14.27% averagely, respectively. BMP allocation schemes, derived from multi-objective optimization, are stratified into three financial scenarios. Low-cost scenario, costing up to 2 billion RMB, primarily targets the grain for green program in 28.81% of sub-basins. Medium-cost scenario, between 2 and 6 billion RMB, predominantly utilizes the grain for green in areas with a slope greater than 15°, accounting for 20.00% of sub-basins. High-cost scenario exceeds 6 billion RMB, mainly due to the implementation of multiple combination measures. The three configuration scenarios can provide decision-makers with a trade-off between measure costs and reduction efficiency. Overall, the innovative framework not only facilitates cost-effective implementation but provides a beneficial methodology for selecting cost-effective conservation practices in other regions.