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Spatiotemporal Variability in Rainfall Erosivity and Its Teleconnection with Atmospheric Circulation Indices in China

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  • Chenxi Liu

    (Beijing Key Laboratory of Traditional Chinese Medicine Protection and Utilization, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Natural Medicine, Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Manyu Dong

    (Beijing Key Laboratory of Traditional Chinese Medicine Protection and Utilization, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Natural Medicine, Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Qian Liu

    (Beijing Key Laboratory of Traditional Chinese Medicine Protection and Utilization, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Natural Medicine, Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Zhihua Chen

    (Beijing Key Laboratory of Traditional Chinese Medicine Protection and Utilization, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Natural Medicine, Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Yulian Wang

    (Beijing Key Laboratory of Traditional Chinese Medicine Protection and Utilization, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Engineering Research Center of Natural Medicine, Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

Rainfall erosivity (RE) is a critical factor influencing soil erosion, and soil erosion is closely related to land ecosystem health and long-term sustainable utilization. To ensure regional stable food supply and ecological balance, it is crucial to study the spatiotemporal distribution and influencing factors of RE. This study focuses on China and its three natural regions using daily precipitation data from 611 stations from 1960 to 2020. The study analyses the spatiotemporal changes in RE. Rainfall events were classified as moderate, large, and heavy based on rainfall intensity. The RE contribution from different rainfall levels to the total RE was analyzed, and the key climatic drivers closely linked to RE were identified using random forest. The results demonstrate that (1) on a national scale, RE shows a significant increasing trend, marked by an 81.67 MJ·mm·ha −1 ·h −1 /decade. In the subregions, the Eastern Monsoon Region (EMR) and Qinghai–Tibet Plateau Region (QTR) show a significant increasing trend, with a greater change rate in EMR of 108.54 MJ·mm·ha −1 ·h −1 /decade, and the Northwest Arid Region (NAR) shows a nonsignificant upwards trend. (2) The average RE increases northwest–southeast nationwide, ranging from 60.15 MJ·mm·ha −1 ·h −1 to 31,418.52 MJ·mm·ha −1 ·h −1 . The RE contribution generated by different rainfall levels to the total RE exhibits spatial variations. The dominant types show that EMR is influenced by heavy RE, NAR is dominated by large RE, and QTR is affected by moderate RE. (3) The REs are associated with teleconnection indices, but the impact of these indices varies in different regions. The Western Hemisphere Warm Pool has the greatest impact on the EMR, while the North Atlantic Oscillation and Atlantic Multidecadal Oscillation are the factors influencing RE in NAR and QTR, respectively. (4) On a national scale, for every 1 mm increase in annual total rainfall, the RE increased by 8.54 MJ·mm·ha −1 ·h −1 , a sensitivity of 8.54 MJ·mm·ha −1 ·h −1 /mm. For the three subregions, there are differences in the sensitivity of RE to changes in annual precipitation. The highest sensitivity is found in EMR, at 8.71 MJ·mm·ha −1 ·h −1 /mm, which is greater than the sensitivity indices in NAR (6.19 MJ·mm·ha −1 ·h −1 /mm) and QTR (3.60 MJ·mm·ha −1 ·h −1 /mm). This study can provide theoretical references for future regional soil erosion prediction and sustainable agricultural development in China.

Suggested Citation

  • Chenxi Liu & Manyu Dong & Qian Liu & Zhihua Chen & Yulian Wang, 2023. "Spatiotemporal Variability in Rainfall Erosivity and Its Teleconnection with Atmospheric Circulation Indices in China," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
  • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:111-:d:1305106
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    References listed on IDEAS

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    1. Nan Jiang & Fojun Yao & Tao Liu & Zhuo Chen & Chen Hu & Xinxia Geng, 2023. "Estimating the Soil Erosion Response to Land-Use Change Using GIS-Based RUSLE and Remote Sensing: A Case Study of Heilongjiang Province, China," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    2. Tanja Micić Ponjiger & Tin Lukić & Biljana Basarin & Maja Jokić & Robert L. Wilby & Dragoslav Pavić & Minučer Mesaroš & Aleksandar Valjarević & Miško M. Milanović & Cezar Morar, 2021. "Detailed Analysis of Spatial–Temporal Variability of Rainfall Erosivity and Erosivity Density in the Central and Southern Pannonian Basin," Sustainability, MDPI, vol. 13(23), pages 1-31, December.
    3. Nuaman Ejaz & Mohamed Elhag & Jarbou Bahrawi & Lifu Zhang & Hamza Farooq Gabriel & Khalil Ur Rahman, 2023. "Soil Erosion Modelling and Accumulation Using RUSLE and Remote Sensing Techniques: Case Study Wadi Baysh, Kingdom of Saudi Arabia," Sustainability, MDPI, vol. 15(4), pages 1-14, February.
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