West Africa

Floods are the most frequent disaster causing global economic losses in billions and pose a significant threat to modern civilization. The UNDRR strongly advocates for flood early warning system (FEWS) with scientific rationale for all nations by 2027, acknowledging that developing countries face financial and human resource challenges in adopting advanced FEWS infrastructure. This study is focused on the development of a FEWS for the Black Volta Basin (BVB) in West Africa with free data resources and open-source modeling infrastructure. It is based on the approach of integrating the Deltares wflow_sbm hydrologic model and the LISFLOOD-FP hydrodynamic model for forecasting flood and inundation maps. The wflow_sbm is calibrated (1990–1997, NSE value = 0.71) and validated (1998–2007, NSE value = 0.72) by using station-based gridded rainfall from the West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) and discharge time series from Global Runoff Data Centre (GRDC) portals. Based on the calibrated parameters, wflow_sbm model is utilized to produce hydrograph for the years 2001–2022 with raw and bias-corrected GPM-IMERG rainfall inputs, where the discharge with the latter is found to outperform that from the former. The peak flood event from the produced hydrograph by the wflow model is fed into a 2D hydraulic model, LISFLOOD-FP model, to simulate the flood extent. Evaluation of modeled inundation modeling by comparing with satellite inundation observation during flood 2022 case resulted in an acceptable range (F = 0.527). Hydrograph for the flood 2022 case is overlapped with hydrographs from GEFSv12 weather forecast inputs in 1 day, 2 days, and 3 days. It is found that the absolute error percentage for 1 day throughout most of the season is forecasted under 10% including the peak of the flood. Forecasts lead time of 2 and 3 days are observed to have degraded accuracy as compared to 1-day forecasts due to higher uncertainties. Identification of the onset of hydrograph inclination is also found to underperform by GEFSv12 inputs and possible causes are discussed. The aim of this work is to promote FEWS with limited resources in African river basins, considering the problem of data scarcity.

The study explores the evolving land use patterns and their implications for sustainable development in Ghana and neighboring megacities. Using 15 years of historical Land Use and Land Cover (LULC) data combined with Land-Use Harmonization datasets, the study applies the Future Land Use Simulation (FLUS) model to project future LULC dynamics under Shared Socioeconomic Pathway (SSP) scenarios in the densely urbanized Greater Accra Region (GAR) of West Africa. Analyzing historical and current land use dynamics in the GAR revealed notable shifts, notably a decrease in Rangeland and an increase in Built-up areas. Future projections of LULC under SSP scenarios show continuous expansion of Built-up areas, particularly under SSP245 (middle of the road scenario) and SSP370 (Regional Rivalry scenario). This is consistent with results from the urban growth analysis using Urban Expansion Intensity Index (UEII), indicating high-speed expansion in baseline periods and shifts towards medium to high-speed expansion under SSP245 and SSP370 with low-speed expansion under the SSP126 (Sustainability scenario). Shannon entropy analysis shows dispersed urban sprawl, especially under SSP245 and SSP370, with rapid increases in Built-up areas and declines in green areas. For instance, the analysis of the landscape metrics reveal that built-up and green areas are projected to increase and decrease up to 87% and 12% respectively, under these scenarios. The decline in urban green areas was significantly influenced by proximity to the central business district (CBD), with green spaces diminishing more as distance to the CBD decreased. Therefore, relevant local legislation, such as the 2016 Land Use and Spatial Planning Act (Act 925) must be enforced, along with integrating urban initiatives and policies that promote green areas, is essential for ensuring the sustainability of urban ecosystems for the well-being of both humans and the environment. This enables West Africa to achieve its Global commitments as reflected in the UN SDGs, towards the New Urban Agenda (NUA) and the Africa Urban Agenda 2063.

This study interrogates the state of social-ecological landscapes (SEL) in West Africa, focusing on two case studies: the Mankran SEL in Ghana (case study 1) and the Doma–Rutu SEL in Nigeria (case study 2). Using a mix of methods, the assessment was framed by the Drivers Pressure State Impact Response (DPSIR) model tailored for SEL evaluation (DPSIR-SEL). In the Mankran landscape, land use patterns shifted significantly from 2008 to 2018, with cash crop cultivation peaking at 30% in 2015 before declining to 14.5% by 2018. Water quality assessments in the Mankran micro-watershed indicated that several parameters, including Total Suspended Solids (TSS) at 914.41 1974 mg/L, lead at 18.73 17.26 g/L, and arsenic at 53.41 86.66 g/L, exceeded World Health Organization (WHO) standards, raising concerns about potential contamination. In contrast, the Doma–Rutu landscape in Nigeria experienced land use and land cover (LULC) changes from 2000 to 2022, characterized by the expansion of residential and agricultural areas alongside modifications to natural water bodies and vegetation. Water quality issues have emerged, with elevated levels of electrical conductivity, total dissolved solids, and salinity. Furthermore, Focus Group Discussions (FGDs) revealed persistent herder-farmer conflicts in Nigeria, which have historically constrained crop production due to various environmental and social factors. The intertwined challenges faced by both the Mankran and Doma–Rutu landscapes underscore the urgent need for sustainable and inclusive resource management, adaptive land-use strategies, and proactive measures to safeguard water quality.

This study compares the performance of satellite precipitation products (SPPs) and soil moisture-based rainfall products (SM2RPPs) in capturing rainfall patterns in Burkina Faso, West Africa. The findings indicate that SPPs outperform SM2RPPs at daily to annual timescales. The decomposition of total bias reveals that hit bias are dominant, but are larger in magnitude in SM2RPPs. Systematic errors are the major component of hit biases, suggesting they could be further treated through bias-correction. Wavelet analysis indicates that SPPs and SM2RPPs well capture seasonal and annual rainfall variability. All products struggle to accurately represent the most extreme rainfall indices, with SPPs performing better than SM2RPPs. For meteorological droughts, RFE2 and CHIRPS show the strongest correlations with observed SPI values across 1- to 12-month timescales. Although SM2RPPs perform less than SPPs in Burkina Faso, they appear mature for hydrometeorological applications and could further benefit from bias-correction to attain similar or better performance than SPPs.