Monitoring soil erosion in support of achieving SDGs: A special focus on rainfall variation and farming systems vulnerability

Publisher:
Elsevier
Publication Type:
Journal Article
Citation:
Catena, 2024, 234, pp. 107537
Issue Date:
2024-01-01
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The Sustainable Development Goals (SDGs) and soil-related activities are closely intertwined. Healthy soil ecosystems promote the survival of life on Earth and uplift agricultural productivity. One of the issues that is putting healthy soil ecosystems at risk is soil erosion. The Central Highlands of Sri Lanka were chosen because it is a humid, tropical nation that is particularly susceptible to climate threats. Soil erosion was tracked and predicted in connection to rainfall variation in order to reduce soil erosion in farming systems and in supporting the achievement of the SDGs. A revised universal soil loss equation (RUSLE) was executed to determine soil loss. Rainfall variance was calculated using trend analyses of extreme rainfall indices and rainfall erosivity. Soil erosions for the year 2040 under the Representative Concentration Pathways (RCP) 2.6 and 8.5 scenarios were predicted using a variety of machine learning techniques, including artificial neural networks (ANN), support vector machines (SVM), and adaptive network-based fuzzy inference system (ANFIS). Results indicated a positive trend in rainfall erosivity and several other extreme indices. In addition, soil erosion rates increased, with October recording the highest monthly erosion rates. Based on 2020 soil erosion rates, soil erosion model forecasts suggest that erosion may range from 4 % to 22 % in 2040. Under the RCP 2.6 and 8.5 climate scenarios, the rate of soil erosion can be raised from 10.5 t/ha/yr to 12.4 t/ha/yr, respectively. These facts indicate that rainfall-induced soil erosion will increase the vulnerability of the Central Highlands and pose a severe danger to the achievement of the SDGs. In order to ensure the well-being of the soil ecosystem, this research offered strategies to monitor and anticipate soil erosion in support of achieving the SDGs to protect the healthy soil ecosystem. This methodology can be replicated to minimize soil erosion in farming systems elsewhere.
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