Shereif H. Mahmoud

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities.

GIS methods for sustainable stormwater harvesting and storage using remote sensing for land cover data - location assessment

Identification of potential sites for rainwater harvesting (RWH) is an important step toward maximizing water availability and land productivity in arid semiarid regions. Characterised as a “water scarce” country, Egypt has limited fresh water supplies, and is expected to suffer from water stress by the year 2030. Therefore, it is important to develop any means available to supply water and maintain human habitability in a sustainable manner. Practiced or simply indispensable in many countries around the world, rainwater harvesting (RWH) promotes a sustainable and efficient manner of exploiting water resources. In the present study, suitable areas for sustainable stormwater harvesting and storage in Egypt were identified using remote sensing for land cover data - location assessment linked to a decision support system (DSS). The DSS took into consideration a combination of thematic layers such as rainfall surplus, slope, potential runoff coefficient (PRC), land cover/use, and soil texture. Taking into account five thematic layers, the spatial extents of RWH suitability areas were identified by an analytical hierarchy process (AHP). The model generated a RWH map with five categories of suitability: excellent, good, moderate, poor and unsuitable. The spatial distribution of these categories in the area investigated was such that 4.8% (47910 km2) and 14% (139739 km2) of the study area was classified as excellent or good in terms of RWH, respectively, while 30.1% (300439 km2), 47.6% (474116 km2) and 3.5% (34935 km2) of the area were classified as moderate, unsuitable and poor, respectively. Most of the areas with excellent to good suitability had slopes of between 2% and 8% and were intensively cultivated areas. The major soil type in the excellent suitability areas was loam, while rainfall ranged from 100 to 200 mm yr−1. The use of a number of RWH sites in the excellent areas is recommended to ensure successful implementation of RWH systems.