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<p>Water, a crucial reserve, is reducing fast in both urban and rural areas due to increasing domestic and agriculture need. Groundwater and rainwater now play a significant role in hydrological planning, affecting subsurface water quality and freshwater accessibility. This study aimed to find appropriate rainwater harvesting (RWH) location in the Kohat region applying geospatial methods. Approaches used comprise Geographic Information system, remote sensing, multi influencing factors and weighted overlay analysis considering seven main factors: slope, drainage density, rainfall, geology, lineament density, land use/land cover and soil. Every factor was assigned weight and process in ArcGIS to produce an RWH optimal map, classifying zones, poor, moderate, high, and very high suitability category. Finding show that 60.48% is highly suitable for RWH, whereas 34.92% is moderately suitable, and 4.67% is poorly appropriate. The finding provides valuable insights for viable RWH site selection in Kohat and can be useful to water protection effort locally and globally.</p>

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Optimizing rainwater harvesting potential using geospatial technologies: a case study in Kohat District, Pakistan

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月19日

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  • Anwar Saeed Khan,
  • Abdur Raziq,
  • Muhammad Waqas Khan,
  • Waseem Jalal,
  • Hsu-Wen Vincent Young,
  • Yuei-An Liou

摘要

Water, a crucial reserve, is reducing fast in both urban and rural areas due to increasing domestic and agriculture need. Groundwater and rainwater now play a significant role in hydrological planning, affecting subsurface water quality and freshwater accessibility. This study aimed to find appropriate rainwater harvesting (RWH) location in the Kohat region applying geospatial methods. Approaches used comprise Geographic Information system, remote sensing, multi influencing factors and weighted overlay analysis considering seven main factors: slope, drainage density, rainfall, geology, lineament density, land use/land cover and soil. Every factor was assigned weight and process in ArcGIS to produce an RWH optimal map, classifying zones, poor, moderate, high, and very high suitability category. Finding show that 60.48% is highly suitable for RWH, whereas 34.92% is moderately suitable, and 4.67% is poorly appropriate. The finding provides valuable insights for viable RWH site selection in Kohat and can be useful to water protection effort locally and globally.