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<p>Floods are the most common natural disasters worldwide, causing massive economic damage and loss of life. Global warming and climate change are pivotal contributing factors towards flooding. Deforestation, low infiltration, lack of sufficient reservoirs leading to uncontrolled rivers flows and increasing the flood risk, socioeconomic losses, challenges effective flood management, and lack of awareness are also the critical factors behind flooding and its devastating effects in Pakistan. Nowshera is one of the most flood-affected district in Pakistan, thus this research points to provide a flood susceptibility map for the district. The study uses an analytic hierarchy process (AHP) and a geographic information system (GIS) to generate a flood susceptibility index. To create an encompassing flood hazard assessment model, the study included spatial data from a variety of sources, including a digital elevation model (DEM), Land Use/Land Cover (LULC) information, the Normalized Difference Vegetation Index (NDVI), soil, and rainfall data. The study analyzed nine key flood-causing parameters: distance to the river, rainfall, slope, LULC, TWI (topographic wetness index), NDVI, elevation, soil type, and curvature. The flood risk levels were classified into 5 different classes: very high, high, moderate, low and very low. Utilizing the combination of GIS and AHP, higher weights were given to distance from river, rainfall, slope, LULC as compared to TWI, NDVI, Elevation, soil type and curvature. The weights of each parameter determined by AHP was accompanied with geospatial data using GIS to produce a flood susceptibility map. The flood hazard map was reclassified for each parameter in GIS. After overlaying these maps, it was concluded that 0.33% of the overall region is classified as extremely high flood danger, 53.5% as high risk, 46.16% as moderate risk, and 0.01% as low risk. The software modelling is accompanied by a social survey seeking the degree of flood related awareness among the people of Nowshera consisting of 68 responses.</p>

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GIS and AHP-based flood susceptibility mapping of Nowshera, Pakistan with an associated social survey

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月1日

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  • Waheed Ali Khoso,
  • Muhammad Atta Ur Rehman,
  • Muhammad Waseem,
  • Zeeshan Asghar,
  • Faisal Baig

摘要

Floods are the most common natural disasters worldwide, causing massive economic damage and loss of life. Global warming and climate change are pivotal contributing factors towards flooding. Deforestation, low infiltration, lack of sufficient reservoirs leading to uncontrolled rivers flows and increasing the flood risk, socioeconomic losses, challenges effective flood management, and lack of awareness are also the critical factors behind flooding and its devastating effects in Pakistan. Nowshera is one of the most flood-affected district in Pakistan, thus this research points to provide a flood susceptibility map for the district. The study uses an analytic hierarchy process (AHP) and a geographic information system (GIS) to generate a flood susceptibility index. To create an encompassing flood hazard assessment model, the study included spatial data from a variety of sources, including a digital elevation model (DEM), Land Use/Land Cover (LULC) information, the Normalized Difference Vegetation Index (NDVI), soil, and rainfall data. The study analyzed nine key flood-causing parameters: distance to the river, rainfall, slope, LULC, TWI (topographic wetness index), NDVI, elevation, soil type, and curvature. The flood risk levels were classified into 5 different classes: very high, high, moderate, low and very low. Utilizing the combination of GIS and AHP, higher weights were given to distance from river, rainfall, slope, LULC as compared to TWI, NDVI, Elevation, soil type and curvature. The weights of each parameter determined by AHP was accompanied with geospatial data using GIS to produce a flood susceptibility map. The flood hazard map was reclassified for each parameter in GIS. After overlaying these maps, it was concluded that 0.33% of the overall region is classified as extremely high flood danger, 53.5% as high risk, 46.16% as moderate risk, and 0.01% as low risk. The software modelling is accompanied by a social survey seeking the degree of flood related awareness among the people of Nowshera consisting of 68 responses.