Determining Potential Sites for Runoff Water Harvesting using Remote Sensing and Geographic Information Systems-Based Modeling in Sinai
Hossam H. Elewa, Atef A. Qaddah and Ayman A. El-Feel
DOI : 10.3844/ajessp.2012.42.55
American Journal of Environmental Sciences
Volume 8, Issue 1
Problem statement: Sinai is increasingly suffering from an overwhelming water crisis. Runoff Water Harvesting (RWH) could be a solution for this problem. The determined promising drainage basins for RWH could be used by the decision makers to propose appropriate controlling systems to overcome the problem of water scarcity and for implementing runoff farming and rain-fed agriculture. Approach: Remote sensing, geographic information systems, watershed modeling system were integrated to extract a multi-criteria-decision support system of nine thematic layers, namely; volume of annual flood, lineaments frequency density, drainage frequency density, maximum flow distance, basin area, basin slope, basin length, average overland flow distance and soil infiltration. These criteria were used for conducting a Weighted Spatial Probability Modeling (WSPM) to determine the potential areas for the RWH. The potential runoff available for harvesting was estimated by applying Finkel-SCS rainfall-runoff methods. Results: The WSPM classified Sinai into four classes that graded from high (3,201-6,695 km2), moderate (35,923-35,896 km2), low (13,185-16,652 km2), very low (1.38-5.57 km2) for RWH. Promising watersheds like those of Abu Taryfya, Hamma El Hassana, Gerafi, Watir, Geraia, Heridien, Sidri, Feiran and Alaawag, are categorized as high-moderate RWH potential basins. Conclusion: These basins could be investigated in detail with larger scale to determine the appropriate locations for implementing the RWH structures and techniques. Implementing systems and techniques of RWH in the potential watersheds could open new opportunities for sustainable development in the area.
© 2012 Hossam H. Elewa, Atef A. Qaddah and Ayman A. El-Feel. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.