Methods for collecting the volume of water necessary for long-term water supply are crucial. The bulk of physical water scarcity occurs in remote rural areas across the world that receive enough rainfall. In these locations, there are insufficient Surface Rainwater Harvesting Systems (SRHS) to collect the requisite water volume. To address this issue, a Surface Rainwater Harvesting Approach (SRHA) based on remote sensing data was provided. The suggested approach was tested on existing surface rainwater harvesting systems (SRHS) in residential and agricultural regions within the research area. The investigation's major goal is to show the importance of remote sensing data in reducing physical water shortage in rural regions. The research region is around 11,000 km2 and is limited by latitudes 11°-12° N and longitudes 33°-34° E. The SRTM90 DEM data in the research region was processed using the QGIS application program's hydrological components. The hydrological model for the area was created, catchment areas were identified, and drainage capacity for specific test sites was calculated. The findings showed that the remote sensing data-based approach can locate places with drainage capacities 82 and 8 times more than traditional systems in the residential and agricultural sectors, respectively. These findings revealed that the suggested technique can make selecting the optimum surface rainwater collection locations in remote rural regions easier, resulting in a more stable water supply and a reduction in physical water shortage.
Gar Al-Nabi Ibrahim Mohamed,
Hydrographic Surveying Department, Faculty of Maritime Studies, King Abduazizi University, KSA.
Please see the link here: https://stm.bookpi.org/RDST-V4/article/view/6861
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