Rainfall-runoff generation patterns and key influencing factors in the plain of the Taihu Lake Basin, China

Abstract

Study Region

The two field runoff experimental sites, Baitaqiao and Wangmuguan, are located in the plains of the Taihu Basin, China.

Study Focus

This study investigates the hydrological cycle mechanisms in the Taihu Basin plains, aiming to support the development of next-generation, physically-based, refined hydrological models. Two experimental sites were established to comprehensively monitor hydrometeorological variables, including rainfall, evaporation, groundwater depth, soil water content, outlet flow, and other hydrological and meteorological factors. The study analyzes runoff processes and patterns under varying rainfall amounts and intensities, and examines the impacts of rainfall, groundwater depth, and micro-topography on runoff generation. Additionally, existing Taihu Basin models were used to simulate the rainfall-runoff process, with a focus on model errors and the significant role of rainfall-runoff patterns and micro-topography in the hydrological cycle.

New Hydrological Insights for the Region

This study provides a comprehensive clarification of the parameters for the saturation-excess runoff model in humid agricultural plains, offering valuable references for the calibration of hydrological models in similar regions. While the saturation-excess runoff model predominates in the Taihu Basin, the research also identifies the occurrence of infiltration-excess and mixed runoff mechanisms under specific conditions, thus highlighting the limitations of relying solely on the saturation-excess runoff model. Furthermore, the study demonstrates the significant impacts of rainfall amount, rainfall intensity, groundwater depth, and microtopography on rainfall-runoff processes. Through a mechanistic analysis of these factors, the findings provide a theoretical foundation for the refinement of physically based, fine-scale hydrological cycle models, advancing the understanding of hydrological processes and supporting future model development in plain areas.