Flood mitigation measures are aimed at reducing adverse flooding impacts. Flood source control schemes mainly concentrate on biological soil and water conservation measures (SWCMs) including the revival and preservation of soil and land use. Such activities prevent splash erosion, reduce the velocity of surface runof, increase surface roughness that in turn improve infiltration and control soil erosion. Nevertheless, based on technical and budget constraints, uniform implementation of biological SCWMs is neither practical nor optimal. Previous studies on spatial optimization of BMPs (best management practices) have mostly focused on urban structural and/or biological BMPs. Besides, the incorporation of land use/cover and slope maps in source control site selection has not been thoroughly studied. In this research, cover–slope zones are proposed as spatial units for spatial optimization of biological SCWMs. The objective of this study was to determine the optimal spatial distribution of SWCMs using coupled simulation–optimization models. A fully distributed event-based deterministic hydrologic rainfall–runoff model was developed that involved SCS-CN (soil conservation service curve number), ModClark and Muskingum as infiltration, rainfall–runoff and stream routing model, respectively. Genetic algorithm was adopted to search the optimized areas based on two objective functions: minimization of the outlet peak discharge and the cost. Nardin sub-catchment in northern Iran was selected as the case study. For different degrees of food peak reduction under 100-year design rainfall, the optimal patterns identified by the optimization algorithm were a combination of less effective/costly options (exclusion) and the most effective option (transplant). Accordingly, biological SCWMs were assigned from the farthest zone to the outlet, stretching into downstream zones.
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