Assessing the response of agricultural watershed non-point source pollution to the dual impacts of climate change and human activities

To effectively manage water resources and safeguard food security, it is essential to comprehend the impact of climate change and human activities on non-point source (NPS) pollution within agricultural watersheds. This study utilized SWAT+ to model the water balance and nutrient balance of the Xiaowei River Basin (XRB) in Shaanxi Province, China. Different scenarios were used to quantify the effects of human activities and climate on NPS pollution loads. Model validation achieved <i>R</i>² values of 0.87 (streamflow) and 0.71 (total nitrogen load), indicating good performance. The baseline period (1998-2023) was divided into four evolution scenarios. Results showed climate dominated total nitrogen (TN) load contributions (average 93.6%), while human activities contributed 6.4%. However, human activities increased from 4.5% (1998-2003) to 9.7% (2018-2023), increasing TN load. TN loads decreased relative to the initial scenario, due to reduced precipitation. Future pollution loads were simulated using CMIP6 data (five GCMs) and projected population and LULC. Under SSP2-4.5, TN loads increased (2024-2040) and then decreased. Under SSP5-8.5, TN loads exhibited a consistent upward trend, driven by agricultural land expansion and reduced precipitation. Human activities' contribution is continually increasing. Projections indicate TN load under Best Management Practices (BMPs) is lower than that in other scenarios across all timeframes. Notably, in the long term (2071-2100), TN load under BMPs is lower than the baseline. Relevant decision-makers may consider implementing Best Management Practices (BMPs) such as precision fertilization and the establishment of vegetative buffer strips, which can help mitigate the effects of human activities.