Growing Spatial Overlap Between Dam-Related Flooding, Cropland and Domestic Water Points: A Water–Energy–Food Nexus Management Challenge in Malawi and Ghana

Abstract

In sub-Saharan Africa, land cover change, expansion of hydropower infrastructure, and increased flooding complicate country-level efforts to meet the Sustainable Development Goal target concerning access to safe water. The Water, Energy and Food (WEF) nexus approach recognises that addressing these complex challenges requires cross-sectoral analyses at multiple scales. Building on such an approach, our study examined the interrelationships between land cover change, dam-related flooding and access to safe water via a national-level spatial analysis with local case studies in Malawi and Ghana. Our assessment of the water–food interactions found that areas of overlap between water points and cropland increased from 2000 to 2020 for both countries at national scale, but overlap extent varied greatly depending on the land cover product used. Local-scale exploration of water point installation patterns in Zomba, Malawi confirmed this pattern, highlighting increasing non-governmental funding of borehole installation programmes. Our assessment of water–energy interactions found that flooding mediated by hydropower dams increased for the White Volta Basin in Ghana, thereby increasing inundation of groundwater points. Local-scale focus group discussions revealed flooding resulted in contaminated water sources and high risk of injury or drowning whilst fetching water. Overall, our study highlights how socio-economic drivers are bringing water points, flooding and cropland into closer proximity, requiring flood mitigation measures at water points and agro-chemical management to minimise potential water quality impacts. Given differences between land cover products, we recommend more robust integration of existing land cover products to better monitor these phenomena.

Land Use Simulation of Shanghai Based on Multi-source Data Integration

“…In order to pursue the optimal model performance and maximize the integration of information from multiple LUCC data products [12] , this study uses the MCE-CA-Markov model [13] based on the voting method to simulate the future land use of Shanghai in 2030, as shown in Figure 3.…”

Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data

“…This study is a component of a wider program that employed a mixed-methods monitoring flooding events and examining its impacts on livelihoods, healthcare utilisation, and water point quality 38 in White Volta catchment in Western Africa. The study area White Volta catchment is located in Ghana (Fig.…”

How Can “Community Voices” from Qualitative Research Illuminate Our Understanding of the Implementation of the SDGs? A Scoping Review

“…We were able to assign 52 of the 54 included studies to a single SDG in this way. However, two papers defied classification because they focussed on the Water-Energy-Food (WEF) nexus, with SDGs 6, 7, and 2 equally represented [6,7]. Table 2 presents the findings of the mapping exercise.…”

“…There were three other insightful papers on trade-offs among the included studies, where community perspectives illustrated the complexity of the journey towards realising the SDGs. Li et al explored the impact of development on communities in Ghana and Malawi that are located downstream from reservoirs and lakes that are liable to flood [6]. Dams were constructed to generate hydro-electric power, resulting in improvements to energy supply (SGD 7).…”

“…Improved agricultural productivity (SDG 2) further exacerbates the impact of the flooding on drinking water supplies because increased animal waste pollutes the water table. Like so many of the qualitative studies in this review, the quotes from local people graphically illustrate the horrific impact of the flooding: "What we do is to use something to tie a sieve on the mouth of the borehole and then we pump the water and sieve out the maggots" [6] (p. 10). In this case, the trade-off for progress towards SDG 7 ("affordable and clean energy") was negative impact on progress towards SDGs 2 and 6 ("end hunger" and "clean water and sanitation").…”