Abstract
Soil erosion-associated sedimentation has become a significant global threat to sustainable land and water resources management. Semi-arid regions that characterise much of southern Africa are particularly at risk due to extreme hydrological regimes and sparse vegetative cover. This study aims to address the need for an erosion and sediment delivery model that successfully incorporates our conceptual understanding of sedimentation processes in semi-arid regions, particularly sediment storage and connectivity within a catchment. Priorities of the Semi-arid Sediment Yield Model (SASYM) were simplicity and practical applicability for land and water resource management while adhering to basic geomorphic and hydrological principles. SASYM was able to represent multiple sediment storages within a catchment to effectively represent a change in landscape connectivity over geomorphic timeframes. SASYM used the Pitman rainfall–runoff model disaggregated to a daily timescale, the Modified Universal Soil Loss Equation (MUSLE), incorporating probability function theory and a representation of sediment storages and connectors across a semi-distributed catchment. SASYM was applied to a catchment in the Karoo, South Africa. Although there were limited observed data, there was a historical dataset available for the catchment through dam sedimentation history. SASYM was able to effectively present this history and provide evidence for landscape connectivity change.
Highlights
In the absence of short interval runoff observations, estimated values for the runoff parameters are uncertain, which will affect the accuracy of peak values used in the erosion model and the simulated erosion values
The Semi-arid Sediment Yield Model (SASYM) is useful as it uses an overarching framework of connectivity to deal with the issue of scale
The SASYM will act as an informative tool for other water quality models
Summary
Soil erosion and sedimentation is a global problem as the world’s population grows and our resource requirements expand This has serious environmental, economic and social consequences, including loss of productive land, sedimentation of reservoirs, reduction of water quality for human use and impacts on aquatic ecosystems [1,2,3,4,5,6,7,8]. The physical characteristics of semi-arid areas, together with poor land management, have meant that the landscape is predestined to high erosion and sedimentation rates [3,4,9] These characteristics linked to the negative impacts on soil productivity have meant that there has been a significant focus on land degradation by land managers. What is lacking is a tool which effectively quantifies sediment yield in these data-poor regions
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