Abstract
Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion across spatial scales; however, little has been conducted across temporal scales. This study investigates changes in vegetation cover across multiple temporal scales in Eastern Cape, South Africa and how this affects erosion and sediment yield modelling in the Tsitsa River catchment. Earth observation analysis and sediment yield modelling are integrated within this study. Landsat 8 imagery was processed, and Normalised Difference Vegetation Index (NDVI) values were extracted and applied to parameterise the Modified Universal Soil Loss Equation (MUSLE) vegetation (C) factor. Imagery data from 2013–2018 were analysed for an inter-annual trend based on reference summer (March) images, while monthly imagery for the years 2016–2017 was analysed for intra-annual trends. The results indicate that the C exhibits more variation across the monthly timescale than the yearly timescale. Therefore, using a single month to represent the annual C factor increases uncertainty. The modelling shows that accounting for temporal variations in vegetation cover reduces cumulative simulated sediment by up to 85% across the inter-annual and 30% for the intra-annual scale. Validation with observed data confirmed that accounting for temporal variations brought cumulative sediment outputs closer to observations. Over-simulations are high in late autumn and early summer, when estimated C values are high. Accordingly, uncertainties are high in winter when low NDVI leads to high C, whereas dry organic matter provides some protection from erosion. The results of this study highlight the need to account for temporal variations in vegetation cover in sediment yield estimation but indicate the uncertainties associated with using NDVI to estimate C factor.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
This paper explores the impact of different approaches to estimating the C factor on simulated sediment yield, using the Tsitsa River catchment as an example
The findings of [8] support the above result, as they found that vegetation cover and, the C factor, can show high intra-year variability, depending on seasonal effects and land management
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Look-up tables for the USLE to guide the derivation of C values for specific vegetation coverage categories is provided by [3] They warn that these may not be directly applicable to conditions outside the areas in which the estimation methods were developed. The C factor, as defined in the Modified Universal Soil Loss Equation (MUSLE), is generally similar to that defined in the USLE and the revised USLE (RUSLE) [7] Both studies suggest that because the USLE was developed to estimate long-term average soil loss, the factors in the equation (including the C factor) represent an integrated average annual condition. The general application of the MUSLE model is based on fixed C values and this part of the study is designed to assess whether adopting a more detailed approach to the C value estimation methods can be justified in terms of improved results
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