Blue and green water simulation in the river basin using remote sensing data fusion and dual-variable hydrological calibration

Blue water (BW) and green water (GW) are crucial elements that determine watershed water resource availability and ecosystem health; however, constrained by hydrological model uncertainties, their precise simulation and quantitative assessment remain challenging. This study integrates physically-based hydrological models with remote sensing fusion data and observed data to construct seven calibration schemes, with a focus on evaluating the effectiveness of dual-variable blue-green water calibration methods based on remote sensing data fusion in enhancing simulation accuracy, reducing uncertainty, and achieving precise quantification of blue-green water, validated through a case study in the Xiangjiang River Basin. The following main conclusions were drawn: (1) The remote sensing fusion evapotranspiration (ET) data achieved the highest accuracy (R = 0.87, Re = 37.5 %, RMSE = 56.56 mm/month), with spatiotemporal fusion processing enabling a better balance between authenticity and accuracy, outperforming individual ET products; (2) The remote sensing fusion ET data can better support the model in achieving reliable simulation accuracy for both blue-green water, whether it is used as input for single-variable GW calibration or for dual-variable blue-green water calibration. Particularly under the dual-variable calibration scheme, this data significantly improved the simultaneous simulation accuracy of blue-green water; (3) The dual-variable scheme based on remote sensing fusion data significantly outperforms the traditional single-variable BW calibration in GW simulation. This scheme effectively constrains and optimizes vertical flux parameters by utilizing ET data, thereby substantially improving the estimation accuracy of GW. This study exploratorily combined hydrological modeling with remote sensing data fusion methods, providing an effective approach for accurate simulation of blue-green water at the watershed scale. It has application potential in water resources optimal allocation, vegetation water conservation assessment, and ecosystem service function quantification, and can provide scientific support for sustainable management of watershed water resources and ecological protection decision-making. • Proposed a blue–green water simulation framework integrating remote sensing data fusion and bivariate calibration. • Remote sensing ET fusion data underpin improved green water input, calibration, and simulation results. • The framework simultaneously enhances the simulation accuracy of blue and green water.