Scholarlink

<p>Flash flooding stands as a pervasive and economically devastating natural hazard worldwide. Yet, the intricate interplay of methodological constraints and sparse observational data poses challenges in precisely delineating flood-prone areas. Leveraging an amalgamation of Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS), and Remote Sensing (RS), this study conducts a comprehensive flash flood susceptibility zonation analysis within the Pishin district of Balochistan, Pakistan. Incorporating nine thematic layers encompassing variables such as elevation, slope, drainage density, topographic wetness index (TWI), modified normalized difference water index (MNDWI), stream power index (SPI), and distance to rivers, a flood susceptibility zonation (FSZ) map is meticulously formulated. Rigorous model performance is ensured through multicollinearity analysis for disentangling correlated variables and sensitivity analysis to evaluate the resilience of the AHP model. Findings reveal that the ‘low’ flood susceptibility zonation class dominates the landscape (27.41%), trailed by the ‘medium’ class (23.39%). Conversely, the ‘high’ and ‘very high’ flood susceptibility zonation classes encompass lesser extents, at 16.33% and 13.37%, respectively. Validation of the model showcases its robustness, underscored by a notable Area Under the Curve (AUC) score of 0.993 from Receiver Operating Characteristics (ROC) analysis. This study’s insights offer invaluable guidance to planners, hydrologists, and water resource managers in discerning flood-vulnerable zones and implementing effective flood mitigation strategies for the governments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Assessing hazardous flash flood susceptibility using multivariate zonation mapping techniques in Pishin District, Balochistan province of Pakistan

  • 期刊论文

  • 发表日期：

    2025年10月13日

查看全文
  • Muhammad Ashraf,
  • Qahir Shah,
  • Adnan Arshad,
  • Ghulam Murtaza

摘要

Flash flooding stands as a pervasive and economically devastating natural hazard worldwide. Yet, the intricate interplay of methodological constraints and sparse observational data poses challenges in precisely delineating flood-prone areas. Leveraging an amalgamation of Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS), and Remote Sensing (RS), this study conducts a comprehensive flash flood susceptibility zonation analysis within the Pishin district of Balochistan, Pakistan. Incorporating nine thematic layers encompassing variables such as elevation, slope, drainage density, topographic wetness index (TWI), modified normalized difference water index (MNDWI), stream power index (SPI), and distance to rivers, a flood susceptibility zonation (FSZ) map is meticulously formulated. Rigorous model performance is ensured through multicollinearity analysis for disentangling correlated variables and sensitivity analysis to evaluate the resilience of the AHP model. Findings reveal that the ‘low’ flood susceptibility zonation class dominates the landscape (27.41%), trailed by the ‘medium’ class (23.39%). Conversely, the ‘high’ and ‘very high’ flood susceptibility zonation classes encompass lesser extents, at 16.33% and 13.37%, respectively. Validation of the model showcases its robustness, underscored by a notable Area Under the Curve (AUC) score of 0.993 from Receiver Operating Characteristics (ROC) analysis. This study’s insights offer invaluable guidance to planners, hydrologists, and water resource managers in discerning flood-vulnerable zones and implementing effective flood mitigation strategies for the governments.