A High-Resolution Global SWAT+ Hydrological Model for Impact Studies

Abstract. Global hydrological models are essential tools for understanding water resources and assessing climate change impacts at planetary scales, supporting water management, flood risk assessment, and sustainable development initiatives worldwide. The Soil and Water Assessment Tool (SWAT+) has demonstrated robust performance across various environments and scales, from local to continental applications. However, despite its widespread use, a global implementation of SWAT+ is currently lacking due to computational demands and data management challenges, while existing global models often lack the detailed process representation and high spatial resolution needed for comprehensive hydrological analysis. A global SWAT+ model would offer unique advantages through its integrated simulation of water quantity, quality, and land management processes, while supporting multiple UN Sustainable Development Goals and enhancing research opportunities in global hydrology. This study aimed to develop a High-resolution Global SWAT+ Model and establish a reproducible framework for large-scale SWAT+ applications. We developed the Community SWAT (CoSWAT) modeling framework, an open-source solution that automates data retrieval, preprocessing, and model configuration using Python, while maxmising parallel processing for computational efficiency. The global model was then set up using the framework at 2 km resolution using ASTER DEM, ESA land use data, FAO soil data, and ISIMIP climate data, with performance evaluated against GRDC flow data and GLEAM evapotranspiration dataset. Results without calibration showed reasonable spatial patterns in evapotranspiration simulation with 78.54 % of sampled points showing differences within ±100 mm compared to GLEAM data, though river discharge performance was limited due to lack of reservoir implementation with 23.02 % of stations showing positive Kling-Gupta Efficiency values. The development of this first global SWAT+ model demonstrates the feasibility of high-resolution global hydrological modeling using SWAT+, while the CoSWAT framework provides a robust foundation for reproducible large-scale modeling. These advances enable more detailed analysis of global water resources and climate change impacts, though future work should focus on incorporating water management practices, improving process representation with calibration, and enhancing computational efficiency.