{"title":"Effects of rainfall patterns, vegetation cover types and antecedent soil moisture on run‐off and soil loss of typical Luvisol in southern China","authors":"Fei Wang, Pei Tian, Wenzhao Guo, Lin Chen, Yuwei Gong, Yaodong Ping","doi":"10.1002/esp.5871","DOIUrl":null,"url":null,"abstract":"Identifying the effect of precipitation, vegetation cover and underlying surface conditions on run‐off and soil loss is essential for understanding the mechanism of water erosion. The study site is located in the Shiqiaopu watershed of Hubei Province, China. The long‐term (2017–2021) monitoring data for this study included rainfall characteristics, antecedent soil moisture, run‐off and soil loss in four run‐off plots with four vegetation cover types (tea garden, soybean and rape, peanut and rape, and vetiver zizanioides). K‐means clustering and discriminant analysis were used to classify rainfall patterns. The improved redundancy analysis was used to quantitatively explore the relative importance of rainfall characteristics, vegetation cover and antecedent soil moisture to run‐off and soil loss. The results showed that the rainfall patterns were mainly divided into three categories: A (medium duration, small rainfall, medium rain intensity, high frequency), B (long duration, large rainfall, light rain intensity, low frequency) and C (short duration, medium rainfall, heavy rain intensity, medium frequency). The average run‐off coefficient, run‐off depth of different rainfall patterns were C > B > A, and the cumulative run‐off depth and soil loss under the A rainfall pattern were the largest. For the run‐off plots with four vegetation cover types, vetiver zizanioides had the best effect on run‐off and sediment reduction, while peanut and rape had the worst effect. The driving factor that contributed the most to the run‐off depth was vegetation cover (19.36%), and rainfall characteristics explained the most to the soil loss (11.65%). We also found that although antecedent soil moisture had a small explanation rate for soil loss, it was significantly correlated with the run‐off depth under the vegetation cover of the tea garden. Therefore, regional soil erosion should be combined with the importance of driving factors to take comprehensive control measures.","PeriodicalId":11408,"journal":{"name":"Earth Surface Processes and Landforms","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth Surface Processes and Landforms","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1002/esp.5871","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Identifying the effect of precipitation, vegetation cover and underlying surface conditions on run‐off and soil loss is essential for understanding the mechanism of water erosion. The study site is located in the Shiqiaopu watershed of Hubei Province, China. The long‐term (2017–2021) monitoring data for this study included rainfall characteristics, antecedent soil moisture, run‐off and soil loss in four run‐off plots with four vegetation cover types (tea garden, soybean and rape, peanut and rape, and vetiver zizanioides). K‐means clustering and discriminant analysis were used to classify rainfall patterns. The improved redundancy analysis was used to quantitatively explore the relative importance of rainfall characteristics, vegetation cover and antecedent soil moisture to run‐off and soil loss. The results showed that the rainfall patterns were mainly divided into three categories: A (medium duration, small rainfall, medium rain intensity, high frequency), B (long duration, large rainfall, light rain intensity, low frequency) and C (short duration, medium rainfall, heavy rain intensity, medium frequency). The average run‐off coefficient, run‐off depth of different rainfall patterns were C > B > A, and the cumulative run‐off depth and soil loss under the A rainfall pattern were the largest. For the run‐off plots with four vegetation cover types, vetiver zizanioides had the best effect on run‐off and sediment reduction, while peanut and rape had the worst effect. The driving factor that contributed the most to the run‐off depth was vegetation cover (19.36%), and rainfall characteristics explained the most to the soil loss (11.65%). We also found that although antecedent soil moisture had a small explanation rate for soil loss, it was significantly correlated with the run‐off depth under the vegetation cover of the tea garden. Therefore, regional soil erosion should be combined with the importance of driving factors to take comprehensive control measures.
确定降水、植被覆盖和地表底层条件对径流和土壤流失的影响对于了解水土流失的机理至关重要。研究地点位于中国湖北省石桥铺流域。本研究的长期（2017-2021 年）监测数据包括四种植被覆盖类型（茶园、大豆和油菜、花生和油菜、香根草）的四个径流地块的降雨特征、土壤水分、径流和土壤流失。采用 K 均值聚类和判别分析对降雨模式进行分类。改进的冗余分析用于定量探讨降雨特征、植被覆盖和前土壤水分对径流和土壤流失的相对重要性。结果表明，降雨模式主要分为三类：A（持续时间中等，降雨量小，雨强中等，频率高）、B（持续时间长，降雨量大，雨强小，频率低）和 C（持续时间短，降雨量中等，雨强大，频率中等）。不同降雨模式的平均径流系数、径流深度分别为 C > B > A，其中 A 降雨模式下的累积径流深度和土壤流失量最大。在四种植被类型的径流地块中，香根草对径流和泥沙减少的效果最好，而花生和油菜的效果最差。对径流深度影响最大的驱动因素是植被覆盖（19.36%），而降雨特征对土壤流失的影响最大（11.65%）。我们还发现，虽然先期土壤水分对土壤流失的解释率较小，但它与茶园植被覆盖下的径流深度显著相关。因此，区域水土流失应结合驱动因素的重要性采取综合防治措施。
期刊介绍：
Earth Surface Processes and Landforms is an interdisciplinary international journal concerned with:
the interactions between surface processes and landforms and landscapes;
that lead to physical, chemical and biological changes; and which in turn create;
current landscapes and the geological record of past landscapes.
Its focus is core to both physical geographical and geological communities, and also the wider geosciences
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