Photovoltaic-powered groundwater pumping offers a transformative solution for water services in underserved areas. However, without proper regulation, this technology could overexploit groundwater resources, threatening groundwater-dependent ecosystems (GDEs) which rely on them. Often overlooked in development planning and water allocation, GDEs yet hold significant socio-economic and environmental importance. This study maps the risk to sub-Saharan GDEs from uncontrolled access to photovoltaic groundwater pumping using the Analytic Hierarchy Process (AHP). It evaluates risks using data on irradiance, groundwater, population, and novel data on GDEs. Two scenarios are analysed to improve the robustness of the findings. Results show that 91% of sub-Saharan Africa’s GDEs risk overexploitation if photovoltaic water pumping is implemented without proper controls. GDEs in southern and eastern Africa, particularly South Africa and Namibia, are found to face higher risks, while those in Gabon, Congo, and southern Nigeria tend to be less at risk. Comparing these results with populations relying on unimproved water sources highlights regions like southern Nigeria and South Sudan which could be prioritized for potential photovoltaic water pumping system investments due to their higher groundwater development needs and lower risks to GDEs. Conversely, areas like Namibia and South Africa, with lower groundwater development needs but higher risks to GDEs, should require targeted investments and very close groundwater monitoring. These findings can help policymakers in targeting investments on PVWPS and identifying regions needing careful monitoring to ensure sustainable groundwater use and minimal impact on GDEs.
Repository name | URI |
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Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
– OS: Windows 10 Enterprise
– Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz 2.90 GHz (2 processors)
– Memory available: 32 GB
– Software version: Matlab 2024a, QGIS 3.38 (replicators), QGIS 3.26.3 (authors)
~ 60 minutes
To successfully run this package, follow these steps:
getGHI
code in MatLab Map_construction
Map_construction
with QGIS and run the model. Further details are provided in the README file. Main_AHP
in MatLab Plot_results
Open the project Plot_results
with QGIS and follow the point-and-click instructions detailed in the README file.All data sources are publicly available and included in the reproducibility package.
Author | Affiliation | |
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Guillaume Zuffinetti | Université Paris-Saclay | guillaume.zuffinetti@centralesupelec.fr |
Simon Meunier | Sorbonne Université | simon.meunier@centralesupelec.fr |
2024-12
Location | Code |
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Sub-Saharan Africa | SSA |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/the World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
Name | URI |
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Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
Name | Affiliation | |
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Guillaume Zuffinetti | Université Paris-Saclay | guillaume.zuffinetti@centralesupelec.fr |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
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Reproducibility WBG | DIME | World Bank - Development Impact Department | Verification and preparation of metadata |
2024-01-08
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