Abstract:
Assessment of land and water resources for irrigation is significant their use with efficiency and proper crop production to boost food security. But there is no such information associated thereto water and land resource, its agricultural system doesn’t nonetheless completely productive. Therefore, assessment of irrigation potential can play a necessary role for better food production. The present study was carried out with the objective of assessing the land and water resources potential of river basins in upper Nile State of South Sudan for irrigation development and development of geo-referenced map of land resources exploitation using Geographic information system (GIS). To identify potential irrigable land, irrigation quality factors like soil type, slope, land cover/use, and distance from installation (sources) has been taken into consideration. These factors were classified as per Food and Agriculture Organization (FAO) guidelines for land analysis suitability classes one by one. The suitableness analysis of these factors indicated that 97.9% slope, 89.04% soil, and 79.82% land use/cover of the area were categorized as potential land for irrigation development within the study area. By weight of these factors 27.36% of the study area is grouped as highly suitable for irrigation; 61.48% is moderate suitable for irrigation and 11.16% of the area was sorted as not suitable for irrigation. Irrigation water requirements (IWR) of four selected crops were calculated from climate information inputs using FAO Penman-Montheith in CROPWAT 8.0 software. Looking into the suitableness map of the study area, most of the area was identified as highly to marginally suitable categories and since water availability is throughout the year from the Nile River there is no limit on the irrigable land. Integration of GIS and weighted overlay approach has been applied to work out the potential irrigable land. The GIS and Remote Sensing techniques verified to be a convenient and powerful platform to integrate spatially complicate land attributes for caring out land quality analysis
