Monte Carlo analysis of the effect of spatial distribution of storms on prioritization of flood source areas

Bahram Saghafian (), Saeed Golian (), Mohammad Elmi () and Ruhangiz Akhtari ()

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2013, vol. 66, issue 2, 1059-1071

Abstract: Implementation of structural and non-structural flood control measures in flood-prone watersheds is on increasing demand. Different watershed areas are not necessarily hydrologically similar and impose variable effects on the outlet flow hydrograph. Meanwhile, prioritization of watershed areas in terms of flood generation is essential for economic flood control planning. Previous works have focused on the definition of a flood index that quantifies the contribution of each subwatershed unit or grid cell to the outlet flood hydrograph through the application of unit flood response (UFR) approach. In the present research, for the first time, the effect of spatial pattern of storm events on the flood index variation was assessed via a Monte Carlo uncertainty analysis. To do so, the UFR approach was carried out for a large number of randomly generated rainfall spatial pattern. The proposed methodology was adopted to the Tangrah watershed in northern Iran. The watershed is frequently hit by floods that have historically caused loss of life and properties. The results indicated that for the more frequent flood events, the flood index is quite sensitive to the spatial distribution of rainfall such that for the highest ranked subwatershed (SW6), the standardized variation of the flood index values (i.e., the uncertainty range) decreases from 1.0 to 0.5 when the rainfall depth increases from 20 to 150 mm, respectively. The results further revealed that increasing the rainfall depth from 20 to 150 mm would cause the effect of rainfall spatial distribution on subwatersheds’ flood indices to diminish. The implications are that if flood control measures are designed for more frequent floods with lower return periods, an uncertainty analysis is required to identify the range of flood index variations. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Flood source; UFR method; Uncertainty; Rainfall spatial distribution (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s11069-012-0537-2

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