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Projected Rainfall Erosivity Over Central Asia Based on CMIP5 Climate Models

1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2
University of Chinese Academy of Science, Beijing 100049, China
3
Institute of Geology, National Academy of Sciences of Kyrgyz Republic, 30 Erkindik, Bishkek 720040, Kyrgyzstan
4
Department of Geography, University of Florida, Gainesville, FL 32611-7315, USA
5
Department of Geography and Environmental Management, University of Port Harcourt, East-West Rd., PMB 5323 Choba, Port Harcourt, Rivers State, Nigeria
6
Applied Geology Department, American University of Central Asia, 7/6 Aaly Tokombaev, Bishkek 720060, Kyrgyzstan
7
Faculty of Geography and Environmental Sciences, Al-Farabi Kazakh National University, Ave. Al-Farabi 71, Almaty 050040, Kazakhstan
8
Institute of Natural Sciences and Geography, Abai Kazakh National Pedagogical University, Ave. Dostyk 13, Almaty 050010, Kazakhstan
9
Research Centre for Ecology and Environment of Central Asia (Almaty), Ave. Al-Farabi 75 V, Almaty 050060, Kazakhstan
*
Author to whom correspondence should be addressed.
Water 2019, 11(5), 897; https://doi.org/10.3390/w11050897
Received: 23 February 2019 / Revised: 23 April 2019 / Accepted: 24 April 2019 / Published: 28 April 2019
(This article belongs to the Special Issue Rainfall Erosivity in Soil Erosion Processes)
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Abstract

Climate change-induced precipitation variability is the leading cause of rainfall erosivity that leads to excessive soil losses in most countries of the world. In this paper, four global climate models (GCMs) were used to characterize the spatiotemporal prediction of rainfall erosivity and assess the effect of variations of rainfall erosivity in Central Asia. The GCMs (BCCCSM1-1, IPSLCM5BLR, MIROC5, and MPIESMLR) were statistically downscaled using the delta method under Representative Concentration Pathways (RCPs) 2.6 and 8.5 for two time periods: “Near” and “Far” future (2030s and 2070s). These GCMs data were used to estimate rainfall erosivity and its projected changes over Central Asia. WorldClim data was used as the present baseline precipitation scenario for the study area. The rainfall erosivity (R) factor of the Revised Universal Soil Loss Equation (RUSLE) was used to determine rainfall erosivity. The results show an increase in the future periods of the annual rainfall erosivity compared to the baseline. For all GCMs, with an average change in rainfall erosivity of about 5.6% (424.49 MJ mm ha−1 h−1 year−1) in 2030s and 9.6% (440.57 MJ mm ha−1 h−1 year−1) in 2070s as compared to the baseline of 402 MJ mm ha−1 h−1 year−1. The magnitude of the change varies with the GCMs, with the largest change being 26.6% (508.85 MJ mm ha−1 h−1 year−1), occurring in the MIROC-5 RCP8.5 scenario in the 2070s. Although annual rainfall erosivity shows a steady increase, IPSLCM5ALR (both RCPs and periods) shows a decrease in the average erosivity. Higher rainfall amounts were the prime causes of increasing spatial-temporal rainfall erosivity. View Full-Text
Keywords: rainfall erosivity; Central Asia; GCMs; soil erosion; climate change rainfall erosivity; Central Asia; GCMs; soil erosion; climate change
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Duulatov, E.; Chen, X.; Amanambu, A.C.; Ochege, F.U.; Orozbaev, R.; Issanova, G.; Omurakunova, G. Projected Rainfall Erosivity Over Central Asia Based on CMIP5 Climate Models. Water 2019, 11, 897.

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