Articles | Volume 378
Proc. IAHS, 378, 11–16, 2018
https://doi.org/10.5194/piahs-378-11-2018
Proc. IAHS, 378, 11–16, 2018
https://doi.org/10.5194/piahs-378-11-2018

Post-conference publication 29 May 2018

Post-conference publication | 29 May 2018

Parameter and input data uncertainty estimation for the assessment of water resources in two sub-basins of the Limpopo River Basin

Nadia Oosthuizen et al.

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Modelling of channel transmission loss processes in semi-arid catchments of southern Africa using the Pitman Model
Vuyelwa Mvandaba, Denis Hughes, Evison Kapangaziwiri, Jean-Marc Mwenge Kahinda, and Nadia Oosthuizen
Proc. IAHS, 378, 17–22, https://doi.org/10.5194/piahs-378-17-2018,https://doi.org/10.5194/piahs-378-17-2018, 2018
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Cited articles

Beven, K.: Casual models as multiple working hypotheses about environmental processes, Comptes Rendus – Geoscience, 344, 77–88, 2012. 
Busari, O.: Groundwater in the Limpopo Basin: occurrence, use and impact, Environmental Development and Sustainability, 10, 943–957, 2008. 
DAFF (Department of Agriculture, Forestry and Fisheries): RSA Irrigation Data, Department of Agriculture, Forestry and Fisheries, Pretoria, South Africa, 2015. 
Hughes, D. and Mantel, S. K.: Estimating the uncertainty in simulating the impacts of small farm dams on streamflow regimes in South Africa, Hydrol. Sci. J., 55, 578–592, 2010. 
Hughes, D. A.: Southern Africa FRIEND – The Application of Rainfall-Runoff Models in the SADC Region, Water Research Commission Report No. 235/1/97, Pretoria, South Africa, 1997. 
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Short summary
Input data (and model parameters) are significant sources of uncertainty that should be quantified. In southern Africa, water use data are among the most unreliable sources of model input data because available databases generally consist of only licensed information and actual use is generally unknown. The study assesses how uncertainty impacts the estimation of surface water resources of the Mogalakwena and Shashe sub-basins when using the databases that are currently available.