Abstract:
Developing countries are largely characterized by rural-based communities often settled in headwater catchments whose livelihoods are dependent on natural resources available. As the climate changes, hydrological regimes are also altered affecting these communities. Assessing available water resources and their management becomes crucial to inform sustainable resources management, planning and development. This study quantified water resources in ten selected headwater sub-catchments of the Pungwe River Basin using the Pitman model in (SPatial And Time Series Information Model) SPATSIM_V3 and ten statistically downscaled climate datasets from the Climate Systems Analysis Group forced with RCP 4.5 and RCP 8.5 emission scenarios. Rainfall and potential evaporation data were used to setup the model while streamflow data was used for model calibration. The calibrated model parameters were used to project future water resources using stochastic rainfall ensembles derived from the delta change method in SPATSIM. Interviews were also carried out with natural resources managers to understand how headwater sub-catchments were being managed using a case of Pungwe Sub-Catchment. The interviews revealed that headwater catchment management is not yet incorporated in the management procedures of water resources in the sub-catchment, but the principles of integrated water resources management are being fully implemented. The Pitman- SPATSIM showed that water resources in the headwater sub-catchments to be adequate to meet ecological and human needs. Near-future (2020-2060) and far-future (2061-2099) projections using RCP 4.5 varied from the current period (1960-2010) with a percentage difference in mean monthly flow within the range of -9% to 7% for all sub-catchments. Under RCP 8.5, the near and far-future had similar projections, with both periods showing a minor reduction in water availability with a few subcatchments showing a reduction as high as 71% (sub-catchment E72) which could possibly be attributed to streamflow datasets used for the calibration process. It was concluded that future water resources availability in the study area will be stable, with the key assumption that climate change is the sole variable driving water availability. To fully understand the water resources availability in the future, other factors such as land use changes need to be incorporated in the simulation of future water resources.
