AUTHOR(S): Mohammad Zare, Thomas Panagopoulos
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ABSTRACT Global climate change will induce changes in rainfall patterns and increase in rainfall events and consequently increase rainfall erosivity. In this study, simulating future rainfall erosivity was considered under different statistical downscaling model (SDSM) scenarios in the North of Iran. Rainfall erosivity (R-factor) until the end of the 21st century and during the current period were compared under four scenarios. With regard to regression equation between R-factor and daily rainfall, annual rainfall and modified fournier index (MFI), it was found that annual rainfall and R-factor had the highest correlation (R2=0.812) and thus, it was extended for future periods. Annual rainfall erosivity in the Kasilian watershed indicated a high degree of variability from year to year (139 years of study), ranging from 302 to 693 MJ ha-1mmh-1. Although, in the early 21st century and at the end of it, rainfall erosivity is greater than the mid-21st century, rainfall erosivity will be higher than the current period in all studied periods. Current rainfall erosivity was 388.18 MJ mm ha-1 h-1 y-1, which, under the effect of climate change will be increased 6-31% under the HadCM3 scenario and rainfall mean will increase 2-5%. The results reveal that rainfall with extreme intensity and less duration will occur. The spatial interpolation method indicated that the R-factor will increase towards the highlands, therefore, future rainfall erosivity changes will have significant impacts on soil and water resources in the North of Iran. |
KEYWORDS Erosion, rainfall erosivity, climate change, Iran |
REFERENCES [1] Wischmeier, W., Smith, D. Predicting rainfall erosion losses. A guide to conservation planning. USDA. Agr. Res. Serv. Handbook. 1978. [1] Wischmeier, W., Smith, D. Predicting rainfall erosion losses. A guide to conservation planning. USDA. Agr. Res. Serv. Handbook. 1978. |
Cite this paper Mohammad Zare, Thomas Panagopoulos. (2017) Spatial and Temporal Rainfall Erosivity Change throughout the 21st Century by Statistical Downscaling Model. International Journal of Environmental Science, 2, 217-222 |
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