Abstract
Soil erosion is caused by increased agricultural activities and a lack of necessary measures to prevent erosion. This leads to the destruction of soil, which takes thousands of years to regenerate. The study area in the Mediterranean Basin is one of the subbasins most affected by global climate change. Erosion in burned areas, especially after large forest fires, occurs as water can wash away the soil and increase the risk of erosion. Burned vegetation also reduces the soil's erosion resistance. The increase in erosion in burned areas can lead to a series of problems, such as water source pollution, damage to agricultural areas, and environmental pollution. The study aims to determine that the Google Earth Engine (GEE) platform is an effective tool for combating erosion after fire lands. Erosion is predicted using the RUSLE model on GEE in pre-fire (2020) and post-fire (2022). This study determined areas at risk of erosion, and preventative measures were taken to prevent environmental problems like soil loss, water pollution, habitat loss, and biodiversity loss. In the results of the study, it was determined that the average soil loss after forest fires in the Manavgat River Basin was 9.47 ton−1 ha−1 year−1. According to the study, changes in soil loss were found depending on land use during the pre-fire and post-fire periods, and there was a general increase in soil loss of 0.10 ton−1 ha−1 year−1 after the fire. It was found that soil loss was lower before the fires. The study area experienced soil loss higher than the Türkiye average. The RUSLE-GEE method used in the study and other methods for estimating soil loss emphasizes the need to use strategies such as changing agricultural methods, using sediment trap** systems, protecting soil cover, and implementing policies and laws together to reduce soil erosion.
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Demir, S., Dursun, İ. Assessment of pre- and post-fire erosion using the RUSLE equation in a watershed affected by the forest fire on Google Earth Engine: the study of Manavgat River Basin. Nat Hazards 120, 2499–2527 (2024). https://doi.org/10.1007/s11069-023-06291-5
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DOI: https://doi.org/10.1007/s11069-023-06291-5