Prioritization of Watersheds across Mali Using Remote Sensing Data and GIS Techniques for Agricultural Development Planning

Implementing agricultural water management programs over appropriate spatial extents can have positive effects on water access and erosion management. Lack of access to water for domestic and agricultural uses represents a major constraint on agricultural productivity and perpetuates poverty and hunger in sub-Saharan Africa (SSA). This lack of access is the result of erratic precipitation, poor water management, limited knowledge of hydrological systems, and inadequate investment in water infrastructure. Water management programs should be made by multi-disciplinary teams that consider the interrelationship between hydraulic and anthropogenic factors. This paper proposes a method to prioritize watersheds for water management and agricultural development across Mali (Western Africa) using remote sensing data and GIS tools. The method involves deriving a set of relevant thematic layers from satellite imagery. Satellite images from Landsat ETM+ were used to generate thematic layers such as land use/land cover. Slope and drainage density maps were derived from Shuttle RADAR Topography Mission (SRTM) Digital Elevation Model (DEM) at 90 m spatial resolution. Population grids were available from the Global rural-urban mapping project (GRUMP) database for the year 2000 and mean rainfall maps were extracted from Tropical rainfall measuring mission (TRMM) grids for each year between 1988 and 2014. Each thematic layer was divided into classes that were assigned a rank for agriculture and livelihoods development provided by experts in the relevant field (e.g., Soil scientist ranking the soil classes) and published literature on those themes. Zones of priority were delineated based on the combination of high scoring ranks from each thematic layer. Five categories of priority zones ranging from “very high” to “very low” were determined based on total score percentages. Field verification was then undertaken in selected categories to check the priority assigned to each class using a random sampling method. Watershed boundaries were prepared at 1000 ha scale and overlaid on the priority map to identify watersheds that were in a very high priority zone. The importance and efficiency of using remote sensing to prioritize watershed interventions across countries is critical due to the limited technical and financial resources available in sub-Saharan Africa (SSA).