An Index-Based Approach to Assess the Water Availability for Irrigated Agriculture in Sub-Saharan Africa

Abstract

Agriculture is a major economic sector in sub-Saharan African (SSA) countries, where it contributes 32 percent of the gross domestic product (GDP) and employs 65 percent of the population. However, SSA countries are farming only a small percentage of their potential cultivable area and are using only a fraction of their renewable water resources. Moreover, despite the importance of land and water resources in SSA, especially in rural areas, there has been little research on their potential. In this study, an index was developed to assess the potential for agriculture, considering renewable water availability of both surface water and groundwater. The index-based approach was then used to assess the potential increase in arable land area in 15 selected SSA countries. The selected countries were classified using the index, based on the availability of renewable water resources nationwide. We also assessed the future water demand by employing three scenarios and combining different rain-fed and irrigated options. The results show that, except for Zimbabwe, the current available surface water or groundwater resources could be sufficient to farm all of the potential cultivable areas in the selected countries when both rain-fed and irrigated systems are fully operational. The findings also indicate that targeted infrastructure projects (e.g., reservoirs, channels), crop management, and water saving techniques could improve surface and groundwater availability in the SSA region.

Unsustainability Syndrome—From Meteorological to Agricultural Drought in Arid and Semi-Arid Regions

“…Insecurity in groundwater resources and unsustainability in agriculture led to increasing internal migration and decreasing cultivated area. There were also environmental impacts, such as desiccation of lakes and wetlands, land subsidence, and desertification [64][65][66].…”

Adaptive Prediction of Water Droplet Infiltration Effectiveness of Sprinkler Irrigation Using Regularized Sparse Autoencoder–Adaptive Network-Based Fuzzy Inference System (RSAE–ANFIS)

“…To quantify the applicability and efficiency of the RSAE-ANFIS approach with alternative ones, such frequently used approaches as genetic optimization, simulated annealing-genetic algorithm (SA-GA), Taguchi parameter estimation, artificial neural network-simulated annealing (ANN-SA) prediction, and genetically optimized neural network (GONN) have been employed in the experimental conditions prearranged by Tables 1 and 2 [34][35][36][37][38]. Figure 9a-d showed the value comparisons of θ, e a , e t and C u between the predicted and actual measured results in tests A-K.…”

Agricultural Productivity and Climate Change: An Evidence of a Non-linear Relationship in Sub-Saharan Africa

“…Most African agricultural yields depend on improvements made by foreign agricultural research on fertilizers, selected seeds, technical practices, and mechanization (Adetutu and Ajayi, 2020). As an example of poor technical practices in SSA, statistics of irrigated land for agriculture show a low proportion (6%) compared to other developing countries in Asia (38%) and America (12%) (Abou Zaki et al, 2018). These poor statistics are explained by a low level of investments in the irrigation of agricultural land.…”