Despite the Sahara being one of the most arid regions on Earth, it has experienced rainfall conditions in the past and could hold plentiful groundwater resources. Thus, groundwater is one of the most precious water resources in this region, which suffers from water shortage due to the limited rainfall caused by climatic conditions. This article will assess the knowledge-driven techniques employed to develop a model to integrate the multicriteria derived from geologic, geomorphic, structural, seismic, hydrologic, and remotely sensed data. This model was tested on the defunct Kom Ombo area of Egypt's Nile river basin in the eastern Sahara, which covers ~28,200 km², to reveal the promising areas of groundwater resources. To optimize the output map, we updated the model by adding the automated depression resulting from a fill-difference approach and seismic activity layers combined with other evidential maps, including slope, topography, geology, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics, after assigning a weight for each using a Geographic Information System (GIS)-based knowledge-driven approach. The paleochannels and soil characteristics were visualized using Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR) data. Several hydromorphic characteristics, sinks/depressions, and sub-basin characteristics were extracted using Shuttle Radar Topography Mission (SRTM) data. The results revealed that the assessed groundwater potential zones (GPZs) can be arranged into five distinctive groups, depending on their probability for groundwater, namely very low (6.56%), low (22.62%), moderate (30.75%), high (29.71%), and very high (10.34%). The downstream areas and Wadi Garara have very high recharge and storage potential. Interferometry Synthetic Aperture Radar (InSAR) coherence change detection (CCD) derived from Sentinel-1 data revealed a consistency between areas with high InSAR CCD (low change) that received a plausible amount of surface water and those with very low InSAR CCD values close to 0 (high change). Landsat data validated the areas that received runoff and are of high potentiality. The twenty-nine groundwater well locations overlaid on the GPZs, to assess the predicted model, indicated that about 86.17% of the wells were matched with very good to moderate potential zones.

中文翻译：

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使用知识驱动方法和GIS分析绘制地下水潜在地带

尽管撒哈拉沙漠是地球上最干旱的地区之一，但它过去曾经历过降雨条件，并可能拥有丰富的地下水资源。因此，地下水是该地区最宝贵的水资源之一，由于气候条件导致降雨有限，因此水资源短缺。本文将评估知识驱动技术，该技术用于开发模型，以整合从地质，地貌，结构，地震，水文和遥感数据中得出的多准则。该模型在撒哈拉沙漠东部埃及尼罗河流域已灭绝的Kom Ombo地区进行了测试，该地区覆盖〜28,200 km ²，以揭示有希望的地下水资源领域。为了优化输出图，我们通过添加由填充差异法和地震活动层产生的自动压降以及其他证据图（包括坡度，地形，地质，排水密度，线质密度，土壤特征，降雨，在使用基于地理信息系统（GIS）的知识驱动方法为每个对象分配权重之后，再确定形态特征。使用高级陆地观测卫星（ALOS）/相控阵型L波段合成孔径雷达（PALSAR）数据可视化古河道和土壤特征。使用航天飞机雷达地形任务（SRTM）数据提取了一些水力形态特征，下沉/凹陷和次盆地特征。结果表明，所评估的地下水潜在区（GPZs）可以分为五个不同的组，具体取决于它们的地下水概率，即极低（6.56％），低（22.62％），中度（30.75％），高（29.71） ％）和很高（10.34％）。下游地区和瓦迪加拉拉（Wadi Garara）具有很高的补给和储存潜力。从Sentinel-1数据得出的干涉测量合成孔径雷达（InSAR）相干变化检测（CCD）结果表明，在InSAR CCD高（低变化）区域接收到合理的地表水的区域与InSAR CCD值非常低的区域（接近）之间存在一致性0（高变化）。Landsat数据验证了径流区域，并且具有很高的潜力。为了评估预测模型，GPZ上覆盖了29个地下水井位置，表明大约有86个。