Current and future assessments of soil erosion by water on the Tibetan Plateau based on RUSLE and CMIP5 climate models

被引:184
作者
Teng, Hongfen [1 ]
Liang, Zongzheng [1 ]
Chen, Songchao [2 ,3 ]
Liu, Yong [1 ]
Rossel, Raphael A. Viscarra [4 ]
Chappell, Adrian [5 ]
Yu, Wu [6 ]
Shi, Zhou [1 ]
机构
[1] Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou 310058, Zhejiang, Peoples R China
[2] INRA, Unite InfoSol, F-45075 Orleans, France
[3] Agrocampus Ouest, INRA, UMR SAS, F-35042 Rennes, France
[4] CSIRO Land & Water, Bruce E Butler Lab, POB 1700, Canberra, ACT 2601, Australia
[5] Cardiff Univ, Sch Earth & Ocean Sci, Cardiff CF10 3XQ, S Glam, Wales
[6] Tibet Agr & Anim Husb Coll, Dept Resources & Environm, Linzhi 860000, Peoples R China
基金
中国国家自然科学基金;
关键词
Soil erosion by water; Future erosion; Tibetan Plateau; Climate change; RUSLE; FREEZE-THAW EROSION; LAND-USE CHANGE; WIND EROSION; RAINFALL EROSIVITY; ORGANIC-CARBON; LOESS PLATEAU; SOURCE REGION; PATTERNS; CHINA; RIVER;
D O I
10.1016/j.scitotenv.2018.04.146
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil erosion by water is accelerated by a warming climate and negatively impacts water security and ecological conservation. The Tibetan Plateau (TP) has experienced warming at a rate approximately twice that observed globally, and heavy precipitation events lead to an increased risk of erosion. In this study, we assessed current erosion on the TP and predicted potential soil erosion by water in 2050. The study was conducted in three steps. During the first step, we used the Revised Universal Soil Equation (RUSLE), publicly available data, and the most recent earth observations to derive estimates of annual erosion from 2002 to 2016 on the TP at 1-km resolution. During the second step, we used a multiple linear regression (MLR) model and a set of climatic covariates to predict rainfall erosivity on the TP in 2050. The MLR was used to establish the relationship between current rainfall erosivity data and a set of current climatic and other covariates. The coefficients of the MLR were generalised with climate covariates for 2050 derived from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) models to estimate rainfall erosivity in 2050. During the third step, soil erosion by water in 2050 was predicted using rainfall erosivity in 2050 and other erosion factors. The results show that the mean annual soil erosion rate on the TP under current conditions is 2.76 t ha(-1) y(-1), which is equivalent to an annual soil loss of 559.59 x 10(6) t. Our 2050 projections suggested that erosion on the TP will increase to 3.17 t ha(-1) y(-1) and 3.91 t ha(-1) y(-1) under conditions represented by RCP2.6 and RCP8.5, respectively. The current assessment and future prediction of soil erosion by water on the TP should be valuable for environment protection and soil conservation in this unique region and elsewhere. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:673 / 686
页数:14
相关论文
共 85 条
[51]  
National Soil Survey Office (NSSO), 1995, SOIL SPEC CHIN, V5
[52]   Soil Erosion in Steep Road Cut Slopes in Palencia (Spain) [J].
Navarro-Hevia, Joaquin ;
Lima-Farias, Teresa Raquel ;
de Araujo, Jose Carlos ;
Osorio-Pelaez, Catalina ;
Pando, Valentin .
LAND DEGRADATION & DEVELOPMENT, 2016, 27 (02) :190-199
[53]   The topographic controls on the decadal-scale erosion rates in Qilian Shan Mountains, NW China [J].
Pan, Bao-tian ;
Geng, Hao-peng ;
Hu, Xiao-fei ;
Sun, Ran-hao ;
Wang, Chao .
EARTH AND PLANETARY SCIENCE LETTERS, 2010, 292 (1-2) :148-157
[54]   The new assessment of soil loss by water erosion in Europe [J].
Panagos, Panos ;
Borrelli, Pasquale ;
Poesen, Jean ;
Ballabio, Cristiano ;
Lugato, Emanuele ;
Meusburger, Katrin ;
Montanarella, Luca ;
Alewell, Christine .
ENVIRONMENTAL SCIENCE & POLICY, 2015, 54 :438-447
[55]   The third pole [J].
Qiu, Jane .
NATURE, 2008, 454 (7203) :393-396
[56]  
Renard KG., 1997, PREDICTING SOIL EROS, DOI DOI 10.1201/9780203739358-5
[57]   Wind as the primary driver of erosion in the Qaidam Basin, China [J].
Rohrmann, Alexander ;
Heermance, Richard ;
Kapp, Paul ;
Cai, Fulong .
EARTH AND PLANETARY SCIENCE LETTERS, 2013, 374 :1-10
[58]   Digitally mapping the information content of visible-near infrared spectra of surficial Australian soils [J].
Rossel, R. A. Viscarra ;
Chen, C. .
REMOTE SENSING OF ENVIRONMENT, 2011, 115 (06) :1443-1455
[59]  
Sharpley A. N., 1990, Technical Bulletin - United States Department of Agriculture
[60]  
Shi X. Z., 2004, Soil Survey Horizons, V45, P129