Modelling of basin-scale nutrient loading variations under the synergistic influences of climate change and socioeconomic development

Achieving reasonable and effective nutrient management requires a comprehensive framework that seamlessly integrates modelling outcomes for both present conditions and future projections. Due to the diversity of basin attributes and variations of removal processes in large-scale basins, it remains difficult to understand nutrient budgets in basins with complex stream networks. Additionally, external environmental changes induced by climate change and socioeconomic development, will also bring uncertainty to water management policies based on current assessments. This study develops a new holistic framework based on the SPARROW (SPAtially Referenced Regression On Watershed attributes) model coupling with the interaction of climate change and socioeconomic development. The framework can integrate multi-source information and model present and future scenarios to evaluate the nutrient status comprehensively. The application of this methodology is demonstrated through a case study in the Danjiangkou Reservoir basin (DJKRB) in China. Findings revealed that atmospheric deposition emerged as the predominant total nitrogen (TN) source in the DJKRB, contributing over 60% on average; while total phosphorus (TP) sources were more diversified, with untreated urban wastewater being a significant contributor, accounting for roughly 37%. The analysis of future uncertainties based on scenario simulations and sensitivity analyses further shows the need for prioritising efforts to mitigate atmospheric nitrogen pollution and promote precipitation-induced runoff management within the DJKRB. This study not only serves as a scientific basis for nutrient modelling in the context of evolving environmental conditions but also proposes a practical methodological framework for water resources management in expansive basins through a real-world case study in the DJKRB.