Spatiotemporal evolutionary analysis of rainfall erosivity during 1901–2017 in Beijing, China

被引:0
作者
Yanlin Li
Yi He
Yaru Zhang
Liping Jia
机构
[1] Northwest University,Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences
[2] Northwest University,Institute of Qinling Mountains
[3] Yellow River Institute of Shaanxi Province,undefined
来源
Environmental Science and Pollution Research | 2022年 / 29卷
关键词
Rainfall erosivity; Spatiotemporal evolutionary; Beijing; Soil erosion; MK trend test; R/S analysis method; Pettitt test; Wavelet analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Rainfall erosivity is regarded as one of the main factors affecting soil erosion. Based on 117-year monthly precipitation data of Beijing from 1901 to 2017, the  spatiotemporal evolutionary analysis of rainfall erosivity in Beijing were analyzed by using Theil-Sen median analysis (Sen), the Mann–Kendall (MK) trend test, R/S analysis method, cumulative anomaly method, MK mutation test method, Pettitt test, and wavelet analysis. The results showed that the average annual rainfall erosivity in Beijing ranged from 1080.6 to 6432.78 MJ • mm/(hm2 • h • a), with an average value of 3465.06 MJ • mm/(hm2 • h • a), showing a gradual decrease from the southeast to northwest. Regarding seasonal distribution, 86% of rainfall erosivity was mainly concentrated in summer. In the past 117 years, the annual rainfall erosivity in most areas of Beijing showed a downward trend, but its future trend also showed an increasing trend, indicating that Beijing, especially the northern part, was facing greater potential pressure from soil erosion. Through cross-validation of various methods, the abrupt change interval of rainfall erosivity in Beijing from 1901 to 2017 was from 1994 to 1997. The change in rainfall erosivity in Beijing had a strong oscillation in 32 years and a small periodic change in 15 and 7 years. The results will provide a decision-making basis for soil erosion control and water/soil conservation planning. Additionally, they will benefit and ensure national agricultural and food security.
引用
收藏
页码:2510 / 2522
页数:12
相关论文
共 105 条
[21]  
Zhang ZX(2020)Quantifying the impacts of lithology on vegetation restoration using a random forest model in a karst trough valley, China Ecol Eng 156 105973-26
[22]  
Xu CY(1991)RUSLE: Revised universal soil loss equation Soil Water Conserv 46 30-undefined
[23]  
Huang J(2016)Periodicity analysis of delta O-18 in precipitation over Central Europe: time-frequency considerations of the isotopic ‘temperature’ effect J Hydrol 534 150-undefined
[24]  
Zhang F(1968)Estimates of the regression coefficient based on Kendall’s tau Publ Am Stat Assoc 63 1379-undefined
[25]  
Hu Z(2020)Evaluating the rainfall erosivity (R-factor) from daily rainfall data: an application for assessing climate change impact on soil loss in Westrapti River basin, Nepal Model Earth Syst Environ 6 1741-undefined
[26]  
Chen ST(2018)Spatial and temporal variations of rainfall-runoff erosivity (R) factor in Kakheti, Georgia Ann Agrar Sci 16 226-undefined
[27]  
Jiang Y(2020)Estimating Current and Future Rainfall Erosivity in Greece Using Regional Climate Models and Spatial Quantile Regression Forests Water 12 687-undefined
[28]  
Xu ZX(2006)Analysis on the spatio-temporal distribution of precipitation in Beijing Arid Land Geogr 29 186-undefined
[29]  
Wang J(2007)Simple Method of Estimating Rainfall Erosivity Under Different Rainfall Amount of Beijing Res Soil Water Conserv 14 398-undefined
[30]  
Jiao YM(2020)Climatic characteristics of precipitation in North China from 1961 to 2017 Scientia Geographica Sinica 40 1573-undefined