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<p>Geomatics technologies offer powerful tools for addressing water scarcity challenges intensified by climate change in arid and semi-arid regions. This study presents an integrated geomatics-based framework for optimizing rainwater harvesting in arid environments through the strategic planning of artificial lakes. High-resolution satellite imagery, digital elevation models, and multi-temporal climate datasets were processed within a GIS environment to identify optimal catchment areas and evaluate storage potential. Spatial analysis techniques, including hydrological modelling, terrain analysis, and multi-criteria decision-making, were applied to generate suitability maps that support climate change adaptation strategies. The Wadi El Raml Basin (101.63&#xa0;km²) has been selected as a case study for its geomorphological diversity and runoff potential. Four sites (P1–P4) at the upstream portion of the basin were identified and ranked by means of a combination of Sentinel-2 imagery, SRTM digital elevation data, TRMM and CHIRPS precipitation records, and GIS-based morphometric analysis in a SCS-CN runoff modelling system. Due to the favourable catchment morphology and proximity to cultivated land, the site P1 was selected for a prototype design. According to hydrological simulations, a proposed rectangular lake (20&#xa0;m × 10&#xa0;m × 2&#xa0;m depth) with an integrated sedimentation basin will store up to 400&#xa0;m³ per event, and reduce peak runoff, thereby reducing the risk of flash floods. According to morphometric estimates, the annual water yield across the four sites ranges from 49 × 10<sup>3</sup> to 2225 × 103&#xa0;m³. Sensitivity analyses and satellite precipitation validations confirm the robustness and replicability of this design framework for similar dryland catchments. The proposed methodology demonstrates how remote sensing and GIS can be effectively combined to deliver operational, data-driven solutions for sustainable water resource management in dryland regions.</p>

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Applied geomatics for climate change adaptation: remote sensing and GIS-based planning of artificial lakes in arid environment

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Mohamed Yousif,
  • Mohamed A. Mabrouk

摘要

Geomatics technologies offer powerful tools for addressing water scarcity challenges intensified by climate change in arid and semi-arid regions. This study presents an integrated geomatics-based framework for optimizing rainwater harvesting in arid environments through the strategic planning of artificial lakes. High-resolution satellite imagery, digital elevation models, and multi-temporal climate datasets were processed within a GIS environment to identify optimal catchment areas and evaluate storage potential. Spatial analysis techniques, including hydrological modelling, terrain analysis, and multi-criteria decision-making, were applied to generate suitability maps that support climate change adaptation strategies. The Wadi El Raml Basin (101.63 km²) has been selected as a case study for its geomorphological diversity and runoff potential. Four sites (P1–P4) at the upstream portion of the basin were identified and ranked by means of a combination of Sentinel-2 imagery, SRTM digital elevation data, TRMM and CHIRPS precipitation records, and GIS-based morphometric analysis in a SCS-CN runoff modelling system. Due to the favourable catchment morphology and proximity to cultivated land, the site P1 was selected for a prototype design. According to hydrological simulations, a proposed rectangular lake (20 m × 10 m × 2 m depth) with an integrated sedimentation basin will store up to 400 m³ per event, and reduce peak runoff, thereby reducing the risk of flash floods. According to morphometric estimates, the annual water yield across the four sites ranges from 49 × 103 to 2225 × 103 m³. Sensitivity analyses and satellite precipitation validations confirm the robustness and replicability of this design framework for similar dryland catchments. The proposed methodology demonstrates how remote sensing and GIS can be effectively combined to deliver operational, data-driven solutions for sustainable water resource management in dryland regions.