This study aims to monitor the flash flood response of Vidor/Wadore hill torrent in Pakistan by the integration of Personal Computer Storm Water Management Model PCSWMM (hydrologic) and HEC-RAS 5.x (hydraulic) models. The method leverages remote sensing and GIS derive estimates of measured and inferred parameters of Vidor rural catchment to quantify the flash flood events of the last four years: 2014–2017. The calibration of the PCSWMM is performed using the sensitivity-based radio tuning calibration (SRTC) tool. The Nash–Sutcliffe efficiency (NSE), coefficient of determination (R2), and relative error (RE) values were found between 0.75–0.97, 0.94–0.98, and −0.22–−0.09 respectively. The statistical indicators prove the accuracy of PCSWMM for rural catchments. The runoff response of Vidor torrent is also analyzed for 0.5/12.7, 1.5/38.1, and 2.0/50.8-inch/mm rainfall hyetographs. The generated hydrographs are used to simulate 2D-module in HEC-RAS 5.x for floodplain demarcation in the piedmont area. The accuracy of the flood extent is analyzed using spatial overlay analogy in the ArcGIS environment by comparing simulated and historically available flood extents. The simulated flood extent shows 76% accuracy with historic flood extent. The impact of flash flood events shows wheat, maize, and fruit orchards are the most effected agriculture in piedmont area. The results revealed that the integration of hydrological, hydraulic, and geospatial modeling approaches can be used to model a full picture of catchment response during flash flood events.
In this study, a relation-based dam suitability analysis (RDSA) technique is developed to identify the most suitable sites for dams. The methodology focused on a group of the most important parameters/indicators (stream order, terrain roughness index, slope, multiresolution valley bottom flatness index, closed depression, valley depth, and downslope gradient difference) and their relation to the dam wall and reservoir suitability. Quantitative assessment results in an elevation-area-capacity (EAC) curve substantiating the capacity determination of selected sites. The methodology also incorporates the estimation of soil erosion (SE) using the Revised Universal Soil Loss Equation (RUSLE) model and sediment yield at the selected dam sites. The RDSA technique identifies two suitable dam sites (A and B) with a maximum collective capacity of approximately 1202 million m3. The RDSA technique was validated with the existing dam, Gomal-Zam, in the north of Sanghar catchment, where RDSA classified the Gomal-Zam Dam in a very high suitability class. The SE estimates show an average of 75 t-ha−1y−1 of soil loss occurs in the study area. The result shows approximately 298,073 and 318,000 tons of annual average sediment yield (SY) will feed the dam A and B respectively. The SE-based sediment yield substantiates the approximate life of Dam-A and Dam-B to be 87 and 90 years, respectively. The approach is dynamic and can be applied for any other location globally for dam site selection and SE estimation.
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