Integrated modeling of blue and green water evolution in a headwater region of Chaohu Lake: Impacts of climate and surface environmental factors

• GW-to-BW ratios in spring, summer, autumn, and winter were 4.6, 2.3, 4.4, and 11.4, respectively. • BW is more spatially clustered than GW. • The dominant drivers are precipitation (+) and ET (−) for BW, and ET (+) and slope (−) for GW. Understanding the dynamic changes of blue water (BW, surface and groundwater) and green water (GW, soil-stored rainfall used by plants via evapotranspiration) is essential for assessing water resource sustainability. Although their roles in the hydrological cycle have been widely recognized, the long-term spatial partitioning patterns and influencing mechanisms of BW and GW in river basins with significant spatial heterogeneity still lack quantitative research. To improve the theoretical framework, this study analyzed the dynamics of BW and GW over multiple decades in the Hangbu River Basin (HRB). A semi-distributed hydrological modeling framework was developed using multi-year hydrometeorological data to simulate BW and GW. The results showed that both BW and GW generally exhibited a “decline–recovery” trend, with BW decreasing rapidly from 1959 to 1968 (slope = −37.61) and gradually recovering from 1969 to 2023 (slope = 1.48), while GW declined from 1959 to 1995 (slope = −1.54) and recovered after 1996 (slope = 2.17). The GW-to-BW ratios in spring, summer, autumn, and winter were 4.6, 2.3, 4.4, and 11.4, respectively. Spatially, BW showing a more pronounced spatial agglomeration than GW. For BW, precipitation is the main positive driver, while evapotranspiration (ET) is the main negative one. For GW, ET contributes most positively, whereas slope has the strongest negative effect. These findings contribute to a deeper understanding of the distribution patterns and formation mechanisms of BW and GW in complex basins, and provide scientific support for sustainable water resource management and land-use policy in similar regions.