Study on the response analysis of LID hydrological process to rainfall pattern based on framework for dynamic simulation of urban floods.

ABSTRACT

An in-depth analysis of the urban flood disaster level in response to different rainfall characteristics and Low Impact Development (LID) measures is of significant importance for addressing unfavorable management conditions and implementing effective flood control measures. This study proposes a dynamic urban flood simulation framework based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS) spatial analysis, incorporating an active inundation seed search algorithm. The framework is calibrated and validated using nine historical urban flood events. Subsequently, the impact of rainfall patterns on urban inundation under LID measures is analyzed based on the dynamic urban flood simulation framework. The results show that the urban flood simulation framework exhibits good applicability, with Nash-Sutcliffe Efficiency (NSE) values of 0.825 and 0.763 during the calibration and validation periods, respectively. The extent of inundation shows little variation for rainfall events with a return period greater than 20 years, and the location of flooding is minimally affected by rainfall patterns. LID measures have a decreasing effect on urban inundation control as the return period of rainfall increases, and there are variations in hydrological responses to different rainfall patterns under the same return period. For single-peak rainfall events with the same return period, the control rates of inundation volume, flow, and infiltration decrease as the rainfall peak coefficient increases, indicating a weakening effect of LID measures on flood control with increasing rainfall peak coefficient. Under the same return period conditions, LID measures exhibit the best runoff control effect for uniform rainfall, while their effectiveness is lower for double-peak rainfall events and single-peak rainfall events with an r = 0.75 coefficient. The findings of this study provide a theoretical basis for urban flood warning and management of Low Impact Development measures.