Abstract

Abstract The North-Western Coast of Egypt (NWCE) represents one of the high priority regions for future development in the country. El-Hammam area is located in the NWCE with an area of 94752 acres and is one of the main challenging regions for sustaianble development. In this study, we have used remote sensing and soil data in combination with GIS tools, for land use sustainable analysis (SLU) in El-Hammam area. The SLU was established based on various factors such as: land capability and suitability, water resources availability, economic return from water and financial return from land and water. A physiographic soil map for the study area was prepared using remote sensing and GIS. Multiple field surveys were carried out for collecting information on various soil map units (SMUs) and their profiles. Laboratory analysis for the collected samples was performed, and then the soil properties were stored as attributes in a geographical soil database linked with the SMUs. Furthermore, land capability assessment was done to define the suitable areas for agricultural production using a capability model built in ALES software. Results indicate that the area currently lacks high capability and moderate capability classes. By improving the soil properties, the soil can attain potential capability; and 55630 acres will become marginally capable. The assessment of soil physical suitability for different land use types (LUTs) were analysed in ALES software, in order to generate the most suitable areas. The results from the land suitability analysis indicated that, 17114 acres are moderately suitable for wheat and sorghum; whereas 15823 acres are moderately suitable for barley and 12752 acres are moderately suitable for maize, olive and figs. Finally, the SLU was investigated based on two scenarios; (1) the most SLU under the conditions of shortage of irrigation water: clover, barley and sorghum against figs, as the irrigation requirements for barley and sorghum are low; (2) the most sustainable land use in the conditions of irrigation availability will be wheat and maize against figs and guava. From the results it is quite evident that GIS combined with modeling approaches are powerful tools for decision making in the study area.

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