Search

AbstractLanduse changes and rainfall intensity from natural vegetation to cultivated fields both impact on river streamflows and sediment dynamics. Assessing the magnitude of these flow and sediment changes is important to water management. However, many rivers are still under-studied/monitored and data sparse. Fully distributed rainfall-runoff models, such as JAMS/J2000, allow for simulation of streamflow, its flow components and potential sediment yield given landuse and hydrological changes. This study demonstrates the use of this method in the Bot River, a data-scarce catchment in South Africa. A hydrological model was implemented, and sediment yield was estimated under three landuse and two hydrological flow component scenarios. The model reported Nash-Sutcliffe efficiencies (E2) of 0.64 and 0.32 (for streamflow) for model calibration and validation periods, respectively. Modelled mean annual sediment yield increased from 423 t/km2/yr in 1990 to 490 t/km2/yr in 2018, attributable to landuse changes. [ABSTRACT FROM AUTHOR]

The MUSLE is used within hydrological models to estimate sediment yields from catchments of various sizes, but the spatial scale dependency issues associated with estimating the MUSLE parameters have not been adequately addressed. In the absence of detailed observed data on both hydrological response and sediment yield, some analytical approaches and hypothetical examples are presented to identify the key issues. The results suggest that methods used to estimate both the erosivity and topographic factors are scale dependent, particularly if a lumped or semi-distributed modelling approach is used. The conclusion is that spatial scale dependencies will add to the uncertainties inherent in the use of the MUSLE if not carefully understood and appropriately addressed. One suggested approach is to apply the erosivity equation to a fixed (small) representative area and then scale up to the total catchment, an approach that recognizes the variability of averaged parameters across different spatial scales. [ABSTRACT FROM AUTHOR]