Desert Ecosystem Engineering

Desert Ecosystem Engineering

Simulating the Effect of Climate Change on Soil Erosion Risk in Two Regions, Tal Siah and Anar Sheitan Forest (Kerman Province, Iran)

Document Type : Original Article

Authors
Saeed Barkhori 1
Arezoo Sharifi 2
Hossein Asadi 3
Maryam Nasabpour Molaei 4
Jaber Saleh Poor 5
1 Assistant professor, Department of Range and Watershed Management, University of Jiroft, Jiroft, Iran.
2 Ph.D. Student in Soil Physics and Conservation, Department of Soil Science and Engineering, Vali-e-Asr University of Rafsanjan, Iran
3 Departmment of Soil Science, University of Tehran, Karaj Iran
4 Forest and watershed management of Southeastern Kerman Province, Iran
5 Department of water engineering, University of Guilan, Iran
Abstract
Soil erosion is an important environmental problem worldwide. Climate change can affect soil erosion by changing the rainfall pattern; hence, it is essential to assess climate change and its effect on soil erosion in different regions. This study aimed to predict the effect of climate change on soil erosion risk using the RUSLE model in Anar Sheitan forest and Tal Siah area in Jiroft region. For this purpose, meteorological station data, remote sensing images, and GIS techniques were used to prepare the necessary model inputs. Three climate change scenarios, RCP2.6, RCP4.5 and RCP8.5, were simulated in three 2006-2025, 2046-2065, and 2080-2099 periods. The rainfall erosivity factor was estimated for these periods in order to assess the impact of climate change on soil erosion risk using existing meteorological data. Other factors of the RUSLE model were considered constant, and soil erosion risk was calculated for each scenario in each period using the ArcGIS software. The analysis of results under RCP8.5 scenario during 2006-2025 period and RCP8.5 scenario during 2080-2099 period indicated that the average soil erosion risk dropped from 0.8 to 1.2 ton ha-1 year-1 in Anar Sheitan forest, reflecting an surge of 0.4 ton ha-1year-1. Furthermore, soil erosion risk spiked from 0.23 to 0.35 ton ha-1 year-1 in Tal Siah, suggesting a surge of 0.1 ton ha-1year-1. Overall, the results suggest that the soil loss will be higher in the future, which may be partly prevented by watershed management and soil conservation practices.
Keywords
Statistical downscaling model (SDSM)
soil conservation
remote sensing
climate change scenario
Sentinel-2
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Desert Ecosystem Engineering
Volume 9, Issue 5
September 2020
Pages 40-25