GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan

Abstract

Flood is the most devastating and prevalent disaster among all-natural disasters. Every year, flood claims hundreds of human lives and causes damage to the worldwide economy and environment. Consequently, the identification of flood-vulnerable areas is important for comprehensive flood risk management. The main objective of this study is to delineate floodprone areas in the Panjkora River Basin (PRB), eastern Hindu Kush, Pakistan. An initial extensive field survey and interpretation of Landsat-7 and Google Earth images identified 154 flood locations that were inundated in 2010 floods. Of the total, 70% of flood locations were randomly used for building a model and 30% were used for validation of the model. Eight flood parameters including slope, elevation, land use, Normalized Difference Vegetation Index (NDVI), topographic wetness index (TWI), drainage density, and rainfall were used to map the flood-prone areas in the study region. The relative frequency ratio was used to determine the correlation between each class of flood parameter and flood occurrences. All of the factors were resampled into a pixel size of 30×30 m and were reclassified through the natural break method. Finally, a final hazard map was prepared and reclassified into five classes, i.e., very low, low, moderate, high, very high susceptibility. The results of the model were found reliable with area under curve values for success and prediction rate of 82.04% and 84.74%, respectively. The findings of this study can play a key role in flood hazard management in the target region; they can be used by the local disaster management authority, researchers, planners, local government, and line agencies dealing with flood risk management.

GIS-Based Multi-Criteria Approach for Flood Vulnerability Assessment and Mapping in District Shangla: Khyber Pakhtunkhwa, Pakistan

“…In water-related studies, slope plays a significant role because it manages surface water flow and has power over the surface runoff. The strength of water flow gives rise to attrition of soil and vertical filtration [30,71]. The region comprising flat areas and with moderate slope is further exposed to flood compared to the area having high altitude and sharp slope [71].…”

“…The strength of water flow gives rise to attrition of soil and vertical filtration [30,71]. The region comprising flat areas and with moderate slope is further exposed to flood compared to the area having high altitude and sharp slope [71]. The elevation is one of the key elements that control floods in a region.…”

An Integrated Approach for Post-Disaster Flood Management Via the Use of Cutting-Edge Technologies and UAVs: A Review

“…These technologies have the potential for improving the response in real-time. With the help of images from the disaster site, the authorities can develop maps for the obstacles and other hurdles that are limiting the relief operation to be carried out efficiently [99][100][101][102][103][104][105]. In Baldazo et al [105], researchers monitored floods by applying Deep Q-Networks (DQN) as the optimisation strategy for the trajectory planning; agents were trained over simulated floods in procedurally generated terrain and demonstrated good performance with two different reward schemes.…”

Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility

“…Various factors drive the flash flood susceptibility of a catchment [93,[97][98][99]; seven of the most common were selected for this approach. These factors were classified into three categories: hypsometry, drainage network, and surface properties [92,[100][101][102] (see Table 2), and estimated or averaged over catchment areas (as delineated by HydroSHEDS). A flash flood susceptibility index (FFSI) represents the potential of a catchment to generate a flash flood when significant local rainfall occurs [103][104][105][106].…”