EGU23-16486, updated on 26 Feb 2023
https://doi.org/10.5194/egusphere-egu23-16486
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Participatory groundwater modelling to build resilience to hydrological extremes in the Limpopo River Basin: Potential and challenges

Syed M. T. Mustafa1,2, Fulvio Franchi3, Alessia Matano4, Anne Van Loon4, Sithabile Tirivarombo3, Oluwaseun Franklin Olabode2, and Jean-Christophe Comte2
Syed M. T. Mustafa et al.
  • 1Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands (syed.mustafa@wur.nl)
  • 2School of Geosciences, University of Aberdeen, Aberdeen, UK
  • 3Department of Earth and Environmental Science, Botswana International University of Science and Technology (BIUST), Palapye, Botswana
  • 4Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

The Limpopo River Basin (LRB) is highly vulnerable to floods and droughts, and these recurrent extreme events seriously threaten the basin's water and food security. Implementing sustainable water management practices is essential to improving resilience to future flood and drought hazards. Identification of such sustainable practices can be done through evaluating alternative management scenarios. It is increasingly recognized that scenario analysis and management strategy identification requires collaboration between scientists and a broad range of stakeholders from local to (trans-) national scales. In this study, we demonstrate and evaluate a real-world application of a basin-scale hydrological model as a decision-support tool based on a multi-sector collaborative modelling approach to co-create management strategies and identify appropriate, inclusive water governance strategies to improve resilience to hydrological extremes in the LRB. To achieve the objectives, an integrated hydro(geo)logical model (WetSpass-MODFLOW) was set up using existing (i) hydro(geo)logical and climatic information and (ii) expert and local community knowledge collected through stakeholders' workshops. After successfully evaluating the model simulation capacity using the groundwater observation datasets, the model was used for evaluating the following management scenarios identified during the stakeholders workshops with inputs from local, national and transboundary governance actors: (1) increase groundwater abstraction; (2) deforestation; (3) afforestation; and (4) managed aquifer recharge (MAR), using (4a) injection well, (4b) rainwater harvesting (local ponds), and (4c) small water reservoirs (e.g. local ponds and sand dams). Though evaluating different identified management scenarios and stakeholder feedback, our results suggest that the most effective strategy is local rainwater harvesting and storage through small-scale (household to village) water reservoirs/ponds or well recharge. It reduces the risk and impact of floods as it can capture and store the excess water during flood into the groundwater aquifer and if upscaled over the entire LRB, can significantly increase the groundwater level across the basin. Additionally, this excess water can be an essential source of water during a drought. The results also show that the multi-sector collaborative modelling approach is effective to co-create management strategies and identify the appropriate and inclusive strategy to improve resilience to hydrological extremes even in data-limiting conditions, provided that the effective stakeholder’s involvement is ensured throughout the modelling study. Finally, the proposed modelling outcomes are helpful in making informed decisions regarding appropriate water management and transboundary cooperation in the LRB. 

How to cite: Mustafa, S. M. T., Franchi, F., Matano, A., Loon, A. V., Tirivarombo, S., Olabode, O. F., and Comte, J.-C.: Participatory groundwater modelling to build resilience to hydrological extremes in the Limpopo River Basin: Potential and challenges, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16486, https://doi.org/10.5194/egusphere-egu23-16486, 2023.