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Floods are highly uncertain events, occurring in different regions, withvarying prerequisites and intensities. A highly reliable flood disaster riskmap can help reduce the impact of floods for flood management, disasterdecreasing, and urbanization resilience. In flood risk estimation, the widelyused analytic hierarchy process (AHP) usually adopts pixel as a basic unit, itcannot capture the similar threaten caused by neighborhood source floodingcells at sub-watershed scale. Thus, an extended watershed-based zonalstatistical AHP model constraining runoff converging related indicators bysub-watersheds (WZSAHP-Slope & Stream) is proposed to fill this gap. Taking theChaohu basin as test case, we validated the proposed method with a real-floodarea extracted in July 2020. The results indicate that the WZSAHP-Slope &Stream model using multiple flow direction division watersheds to calculatestatistics of distance from stream and slope by maximum statistic methodoutperformed other tested methods. Compering with pixel-based AHP method, theproposed method can improve the correct ratio by 16% (from 67% to 83%) and fitratio by 1% (from 13% to 14%) as in validation 1, and improve the correct ratioby 37% (from 23% to 60%) and fit ratio by 6% (from 12% to 18%) as in validation2.

An extended watershed-based zonal statistical AHP model for flood risk  estimation: Constraining runoff converging related indicators by  sub-watersheds