Nethengwe, N. S.Kapangaziwiri, E.Mugari, M. E.Gumbo, Anesu Dion2026-06-302026-06-302026-05-19Gumbo, A.D. 2026. Environmental Flow Determination in Headwater Catchments of Luvuvhu River in Limpopo Province, South Africa. . .https://univendspace.univen.ac.za/handle/11602/3316Ph. D. in GeographyDepartment of Geography and Environmental SciencesSouth Africa’s national water legislation officially integrates ecological flow allocation within its legal framework, yet implementation in data-scarce, ecologically sensitive headwaters remains uneven and/or underdeveloped. This study addresses the absence of defensible environmental flow requirements (EFRs) in the upper Luvuvhu River Catchment, a biodiversity-rich yet hydrologically compromised system within the Vhembe Biosphere Reserve. Based on a functional flow paradigm, the study aimed to develop and apply a functional flow-based environmental water management framework for headwater catchments in South Africa, to promote sustainable river rehabilitation amid elevated water needs. The research establishes grounded, first derivative, hydrology-based, spatially transferable, and resource-efficient ERF benchmarks using two complementary models: the Revised Desktop Reserve Model (RDRM) and the Global Environmental Flow Calculator (GEFC). The study area encompassed the quaternary sub-catchments A91A to A91D, which are part of the water source area catchment for the upper Luvuvhu River. These sub-catchments are characterised by sharp elevational gradients, seasonal flow discontinuity, and anthropogenic flow alteration. The study applied a multi-layered methodology. Bibliometric and systematic reviews identified knowledge gaps, a site selection protocol combining expert judgment and exploratory factor analysis to isolate representative study zones, spatial characterisation of catchment attributes using GIS and remote sensing, and stakeholder-participatory mapping to co-inform flow target development. Functional flow simulations were run using naturalised flow datasets, with present-day flow datasets used to quantify the impacts of water uses. The RDRM results showed total flow requirements of 46.28 million cubic meters per year (MCM/year) with low-flow thresholds of 19.63 MCM/year for the outlet the Albasini dam (i.e., referred to as point A91AB_Out in the thesis), and 59.42 MCM/year and 25.17 MCM/year respectively, at combined outlet of quaternary A91C and A91D in the Luvuvhu farming region (referred to as A91CD_out in the thesis) under Class D environmental management class (EMC). Monthly distributions and variations of these flow regimes were generated by the RDRM in the SPATSIM framework. The GEFC model results, when applied with global datasets, produced identical e-flow values for both A91AB_Out and A91CD_Out, highlighting its unsuitability for small catchments due to the coarse spatial resolution of input data. In contrast, user-defined datasets provided more realistic differentiation. EMC F, which reflects heavily modified systems, categorised the EFRs and prescribed 21.1% of the naturalised mean annual runoff (MAR) for A91AB_Out and 19.1% for A91CD_Out. A stakeholder-informed framework for determining EFRs emerged from the findings, linking flow targets to default ecological function, hydrological condition, land use stressors, and governance interventions (which would be subject to refinement in further technical stakeholder engagements). The RDRM shows significant applicability within South Africa based on the current resources available (naturalised streamflow datasets). In data-constrained catchments, the GEFC can be used, with caution, as a baseline for EFRs. Recommendations included mainstreaming functional flows into national reserve assessments, expanding climate-informed flow modelling in upland systems, and integrating community-derived ecological knowledge into official flow classification regimes. The study concludes that ecologically meaningful EFR determinations can be achieved in structurally marginalised catchments if methodological flexibility is matched by institutional willingness to accommodate pluralistic, available resource-aware modelling approaches.enUniversity of VendaUCTD346.0469168257Water -- Law and legislation -- South Africa -- LimpopoWater rights -- South Africa -- LimpopoWatersheds -- South Africa -- LimpopoLandforms -- South Africa -- LimpopoLuvuvhu River Watersheds (South Africa)ThesisGumbo AD. Environmental Flow Determination in Headwater Catchments of Luvuvhu River in Limpopo Province, South Africa. []. , 2026 [cited yyyy month dd]. Available from:Gumbo, A. D. (2026). <i>Environmental Flow Determination in Headwater Catchments of Luvuvhu River in Limpopo Province, South Africa</i>. (). . Retrieved fromGumbo, Anesu Dion. <i>"Environmental Flow Determination in Headwater Catchments of Luvuvhu River in Limpopo Province, South Africa."</i> ., , 2026.TY - Thesis AU - Gumbo, Anesu Dion AB - South Africa’s national water legislation officially integrates ecological flow allocation within its legal framework, yet implementation in data-scarce, ecologically sensitive headwaters remains uneven and/or underdeveloped. This study addresses the absence of defensible environmental flow requirements (EFRs) in the upper Luvuvhu River Catchment, a biodiversity-rich yet hydrologically compromised system within the Vhembe Biosphere Reserve. Based on a functional flow paradigm, the study aimed to develop and apply a functional flow-based environmental water management framework for headwater catchments in South Africa, to promote sustainable river rehabilitation amid elevated water needs. The research establishes grounded, first derivative, hydrology-based, spatially transferable, and resource-efficient ERF benchmarks using two complementary models: the Revised Desktop Reserve Model (RDRM) and the Global Environmental Flow Calculator (GEFC). The study area encompassed the quaternary sub-catchments A91A to A91D, which are part of the water source area catchment for the upper Luvuvhu River. These sub-catchments are characterised by sharp elevational gradients, seasonal flow discontinuity, and anthropogenic flow alteration. The study applied a multi-layered methodology. Bibliometric and systematic reviews identified knowledge gaps, a site selection protocol combining expert judgment and exploratory factor analysis to isolate representative study zones, spatial characterisation of catchment attributes using GIS and remote sensing, and stakeholder-participatory mapping to co-inform flow target development. Functional flow simulations were run using naturalised flow datasets, with present-day flow datasets used to quantify the impacts of water uses. The RDRM results showed total flow requirements of 46.28 million cubic meters per year (MCM/year) with low-flow thresholds of 19.63 MCM/year for the outlet the Albasini dam (i.e., referred to as point A91AB_Out in the thesis), and 59.42 MCM/year and 25.17 MCM/year respectively, at combined outlet of quaternary A91C and A91D in the Luvuvhu farming region (referred to as A91CD_out in the thesis) under Class D environmental management class (EMC). Monthly distributions and variations of these flow regimes were generated by the RDRM in the SPATSIM framework. The GEFC model results, when applied with global datasets, produced identical e-flow values for both A91AB_Out and A91CD_Out, highlighting its unsuitability for small catchments due to the coarse spatial resolution of input data. In contrast, user-defined datasets provided more realistic differentiation. EMC F, which reflects heavily modified systems, categorised the EFRs and prescribed 21.1% of the naturalised mean annual runoff (MAR) for A91AB_Out and 19.1% for A91CD_Out. A stakeholder-informed framework for determining EFRs emerged from the findings, linking flow targets to default ecological function, hydrological condition, land use stressors, and governance interventions (which would be subject to refinement in further technical stakeholder engagements). The RDRM shows significant applicability within South Africa based on the current resources available (naturalised streamflow datasets). In data-constrained catchments, the GEFC can be used, with caution, as a baseline for EFRs. Recommendations included mainstreaming functional flows into national reserve assessments, expanding climate-informed flow modelling in upland systems, and integrating community-derived ecological knowledge into official flow classification regimes. The study concludes that ecologically meaningful EFR determinations can be achieved in structurally marginalised catchments if methodological flexibility is matched by institutional willingness to accommodate pluralistic, available resource-aware modelling approaches. DA - 2026-05-19 DB - ResearchSpace DP - Univen LK - https://univendspace.univen.ac.za PY - 2026 T1 - Environmental Flow Determination in Headwater Catchments of Luvuvhu River in Limpopo Province, South Africa TI - Environmental Flow Determination in Headwater Catchments of Luvuvhu River in Limpopo Province, South Africa UR - ER -