A natural runoff reconstruction method based on the spreading of hydrological parameters in similar watersheds

ABSTRACT As human activities increasingly impact river runoff, measured runoff often fails to reflect the natural state of surface water resources. This study addresses the limitations of traditional natural runoff reconstruction methods, such as the high workload of the itemized survey method and the difficulty in obtaining data for hydrologic modeling-based methods. An innovative approach is proposed. By establishing a basin-scale Soil and Water Assessment Tool model, calibrating parameters of near-natural sub-basins, analyzing sub-basin similarity, and spreading parameter sets, natural runoff can be reconstructed. In the case of the Upper Yangtze River Basin, significant spatial differences exist in the average annual runoff of its 99 sub-basins. The basin's average annual natural runoff is 438.18 km³, while the measured runoff is 428.91 km³, demonstrating the impact of human activities. Among the sub-basins, the highest average annual runoff in sub-basin 67 is 267.93 km³, and the lowest in sub-basin 16 is only 0.28 km³, indicating a large-scale variation range. The reconstructed natural runoff provides a basis for water resource planning, ecological protection, and adaptation to climate and land-use changes.