Extreme rainfall erosivity: Research advances and future perspectives

被引：22

作者：

Zhao, Yingshan ^{[1
,2
]}

Zhu, Dayun ^{[1
,2
]}

Wu, Zhigao ^{[3
]}

Cao, Zhen ^{[1
,2
]}

机构：

[1] Guizhou Normal Univ, Sch Karst Sci, Guiyang 550001, Peoples R China

[2] State Engn Technol Inst Karst Desertificat Control, Guiyang 550001, Peoples R China

[3] Southeast Univ, Sch Architecture, Nanjing 210096, Peoples R China

来源：

SCIENCE OF THE TOTAL ENVIRONMENT | 2024年 / 917卷

基金：

中国国家自然科学基金;

关键词：

Rainfall erosivity; Extreme rainfall; Soil erosion; Rainfall erosivity models; Influencing mechanisms; Future trends; REGIONAL CLIMATE-MODEL; TROPICAL CYCLONE RAINFALL; SPATIAL-TEMPORAL CHANGES; LONG-TERM TRENDS; SOIL-EROSION; PRECIPITATION EXTREMES; HEAVY PRECIPITATION; EL-NINO; LOESS PLATEAU; NE SPAIN;

D O I：

10.1016/j.scitotenv.2024.170425

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Extreme rainfall erosivity, the capacity of intense rainfall to induce soil erosion, is vital for anticipating future impacts on soil conservation. Despite extensive research, significant differences persist in terms of understanding influencing mechanisms, potential impacts, estimation models and future trends of extreme rainfall erosivity. Quantitatively describing extreme rainfall erosivity remains a key issue in existing research. In this study, we comprehensively reviewed the literature to assess the relationships between extreme rainfall characteristics and rainfall erosivity, between extreme rainfall erosivity and soil erosion, estimation models and trend prediction. The aim was to summarize previous related research and achievements, providing a better understanding of the generation, impacts and future trends of extreme rainfall erosivity. Future research directions should include identifying the thresholds of extreme rainfall events, increasing research attention on tropical cyclones in terms of rainfall erosivity, considering on the impact of extreme rainfall erosivity on soil erosion, and improving rainfall erosivity estimation and simulation prediction methods. This study could contribute to adapting to global climate change and aiding in formulating soil erosion prevention and environmental protection recommendations.

引用

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