Intelligent identification of flood risks and resilience planning in piedmont areas with nature-based solutions

Global warming has led to frequent rainfall and flood disasters. The presence of warm and humid air currents significantly contributes to the intensity of rainfall in piedmont areas, thereby exposing them to heightened risks of waterlogging and flash floods. In response, there is a growing inclination towards adopting nature-based solutions (NbS) for effective flood regulation. This study proposes a kind of NbS for flood management in the piedmont area: using the SCS-CN hydrological model to measure the supply of flood regulation ecosystem service (FRES) in the study area, while employing the random forest model to enhance the accuracy of FRES demand assessment. The matching degree between FRES supply and demand was analyzed at two granularities of sub-catchments and grids. Ultimately, the supply–demand relationship was optimized in terms of both in-situ services and directional services. Taking Fangshan District and Zhuozhou City in China as a case study, the findings demonstrate that: (1) The random forest model can accurately predict the inundation probability across the entire domain using limited data, with areas of highest hazard typically characterized by high construction intensity, low vegetation cover, and low topography. (2) At the sub-catchment granularity, the low supply-high demand areas exhibit a faceted distribution within urban built-up areas and the transition area between mountains and plains. At the grid granularity, the low supply-high demand areas are distributed in a point-like manner in high-intensity development lots. (3) Based on the results of supply–demand matching, a zoning management scheme integrating NbS for ecological protection, restoration, and flood control interventions is proposed. A total of 31 flood regulation service flow corridors were identified along with optimization strategies provided. The results of the study can inform flood resilience planning in piedmont areas from the perspective of promoting a balance between FRES supply and demand.