Abstract
This study explores the opportunities for irrigated agriculture in Khyber District of Former Federally Administered Tribal Area (FATA). Agriculture continues to be most important economic activity in Pakistan and former FATA is no exception. However, agriculture in the semi-arid Khyber District continues to suffer a decline due to excessive reliance on rainfall, which is drastically insufficient. Khyber District have large expanses of fertile land; however, farmers depend on unpredictable rain-fed agriculture, which has low productivity and food insecurity. There are a number of rivers in the region where great prospects exist for irrigated farming. Geographical information systems (GIS)-based multi-criteria analysis can be used to map areas with irrigation potential. The current study focused on different variables including soil texture, perennial rivers, land cover, topography, and dams. For this study, data was collected from diverse sources which include Google earth images, top sheets, land use land cover, soil texture map of FATA, and SRTM 30 Meter. The collected data was analyzed by using multi-criteria analysis in Arc GIS 10.2.2 by using MIF technique. The results of this research indicate that there is great potential for irrigated farming in the study area. Potential land for this purpose were divided into three categories, i.e., highly suitable which consisted of 678 km2, or 26% of the total area; 1044 km2 representing 40% were moderately suitable to irrigation; while the remaining 698 km2 representing 27% were considered least suitable for irrigation. Likewise, 204 km2 representing 7% were deemed unsuitable for irrigated agriculture mostly consisting of barren rocks. The results also illustrate how GIS as a tool can be used in the exploration of water resources in a scientific approach, thus making decision-making easier and more accurate.
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Waleed, M., Ahmad, S.R., Javed, M.A. et al. Identification of irrigation potential areas, using multi-criteria analysis in Khyber District, Pakistan. Environ Sci Pollut Res 27, 39832–39840 (2020). https://doi.org/10.1007/s11356-020-08967-y
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DOI: https://doi.org/10.1007/s11356-020-08967-y