An extended watershed-based zonal statistical AHP model for flood risk estimation: Constraining runoff converging related indicators by sub-watersheds
Floods are highly uncertain events, occurring in different regions, with varying prerequisites and intensities. A highly reliable flood disaster risk map can help reduce the impact of floods for flood management, disaster decreasing, and urbanization resilience. In flood risk estimation, the widely used analytic hierarchy process (AHP) usually adopts pixel as a basic unit, it cannot capture the similar threaten caused by neighborhood source flooding cells at sub-watershed scale. Thus, an extended watershed-based zonal statistical AHP model constraining runoff converging related indicators by sub-watersheds (WZSAHP-Slope & Stream) is proposed to fill this gap. Taking the Chaohu basin as test case, we validated the proposed method with a real-flood area extracted in July 2020. The results indicate that the WZSAHP-Slope & Stream model using multiple flow direction division watersheds to calculate statistics of distance from stream and slope by maximum statistic method outperformed other tested methods. Compering with pixel-based AHP method, the proposed method can improve the correct ratio by 16% (from 67% to 83%) and fit ratio by 1% (from 13% to 14%) as in validation 1, and improve the correct ratio by 37% (from 23% to 60%) and fit ratio by 6% (from 12% to 18%) as in validation 2.
- Pub Date:
- July 2021
- Statistics - Applications;
- Computer Science - Computers and Society;
- This paper is a research paper, it contains 40 pages and 8 figures. This paper is a modest contribution to the ongoing discussions the accuracy of flood risk estimation via AHP model improved by adopting pixels replaced with sub-watersheds as basic unit