Fengjie Fan, Xingli Gu, Jun Luo, Bin Zhang, Hui Liu, Haiqing Yang, Lei Wang
{"title":"沟谷侵蚀活动及其影响因素的识别:孙水河流域案例研究。","authors":"Fengjie Fan, Xingli Gu, Jun Luo, Bin Zhang, Hui Liu, Haiqing Yang, Lei Wang","doi":"10.1371/journal.pone.0309672","DOIUrl":null,"url":null,"abstract":"<p><p>Gully erosion is one of the most severe forms of land degradation and poses a serious threat to regional food security, biodiversity, and human survival. However, there are few methods for the quantitative evaluation of gully activity, and the relationships between gully activity and influencing factors require further in-depth study. This study takes the Sunshui River Basin, as a case study. Based on field investigation, unmanned aerial vehicle (UAV) photography and remote sensing images, 71 typical gullies were identified. The vegetation coverage (VC), slope and main-branch gully ratio (MBGR) were used as evaluation indicators, and the gully activity was calculated using the fuzzy mathematics membership degree and then evaluated quantitatively. The factors influencing different active gullies were also analyzed. The results showed that (1) the fuzzy comprehensive evaluation method can be used to identify gully activity. Different levels of gully activity were defined based on the gully activity index. The active indices of stable gullies ranged from 0-0.25, those of semiactive gullies ranged from 0.25-0.75, and those of active gullies ranged from 0.75-1. (2) The activity indices of the 71 gullies ranged from 0.054 to 0.999, with an average value of 0.656. There are 31 active gullies, and 31 semiactive gullies. A total of 87.32% of the gullies in the study area were in the early or middle stage of gully development. Gully erosion was intense, which is consistent with the serious reality of soil erosion. (3) Gully activity was affected by multiple factors. It was significantly positively correlated with topographic relief (TR) (r = 0.64, P<0.01) and surface curvature (SC) (r = 0.51, P<0.01), while it was significantly negatively correlated with land use type (LUT) (r = -0.5, P<0.01). Surface roughness (SR) (r = 0.2, P<0.01) was positively correlated with gully activity; but not significantly. There was no significant correlation between aspect (As) and gully activity. The results of this study are helpful for quantitatively determining the level of gully activity and understanding the development process and mechanism controlling gullies, providing a reference for research on related regions and geomorphologic information.</p>","PeriodicalId":20189,"journal":{"name":"PLoS ONE","volume":"19 11","pages":"e0309672"},"PeriodicalIF":2.9000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11581266/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of gully erosion activity and its influencing factors: A case study of the Sunshui River Basin.\",\"authors\":\"Fengjie Fan, Xingli Gu, Jun Luo, Bin Zhang, Hui Liu, Haiqing Yang, Lei Wang\",\"doi\":\"10.1371/journal.pone.0309672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Gully erosion is one of the most severe forms of land degradation and poses a serious threat to regional food security, biodiversity, and human survival. However, there are few methods for the quantitative evaluation of gully activity, and the relationships between gully activity and influencing factors require further in-depth study. This study takes the Sunshui River Basin, as a case study. Based on field investigation, unmanned aerial vehicle (UAV) photography and remote sensing images, 71 typical gullies were identified. The vegetation coverage (VC), slope and main-branch gully ratio (MBGR) were used as evaluation indicators, and the gully activity was calculated using the fuzzy mathematics membership degree and then evaluated quantitatively. The factors influencing different active gullies were also analyzed. The results showed that (1) the fuzzy comprehensive evaluation method can be used to identify gully activity. Different levels of gully activity were defined based on the gully activity index. The active indices of stable gullies ranged from 0-0.25, those of semiactive gullies ranged from 0.25-0.75, and those of active gullies ranged from 0.75-1. (2) The activity indices of the 71 gullies ranged from 0.054 to 0.999, with an average value of 0.656. There are 31 active gullies, and 31 semiactive gullies. A total of 87.32% of the gullies in the study area were in the early or middle stage of gully development. Gully erosion was intense, which is consistent with the serious reality of soil erosion. (3) Gully activity was affected by multiple factors. It was significantly positively correlated with topographic relief (TR) (r = 0.64, P<0.01) and surface curvature (SC) (r = 0.51, P<0.01), while it was significantly negatively correlated with land use type (LUT) (r = -0.5, P<0.01). Surface roughness (SR) (r = 0.2, P<0.01) was positively correlated with gully activity; but not significantly. There was no significant correlation between aspect (As) and gully activity. 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Identification of gully erosion activity and its influencing factors: A case study of the Sunshui River Basin.
Gully erosion is one of the most severe forms of land degradation and poses a serious threat to regional food security, biodiversity, and human survival. However, there are few methods for the quantitative evaluation of gully activity, and the relationships between gully activity and influencing factors require further in-depth study. This study takes the Sunshui River Basin, as a case study. Based on field investigation, unmanned aerial vehicle (UAV) photography and remote sensing images, 71 typical gullies were identified. The vegetation coverage (VC), slope and main-branch gully ratio (MBGR) were used as evaluation indicators, and the gully activity was calculated using the fuzzy mathematics membership degree and then evaluated quantitatively. The factors influencing different active gullies were also analyzed. The results showed that (1) the fuzzy comprehensive evaluation method can be used to identify gully activity. Different levels of gully activity were defined based on the gully activity index. The active indices of stable gullies ranged from 0-0.25, those of semiactive gullies ranged from 0.25-0.75, and those of active gullies ranged from 0.75-1. (2) The activity indices of the 71 gullies ranged from 0.054 to 0.999, with an average value of 0.656. There are 31 active gullies, and 31 semiactive gullies. A total of 87.32% of the gullies in the study area were in the early or middle stage of gully development. Gully erosion was intense, which is consistent with the serious reality of soil erosion. (3) Gully activity was affected by multiple factors. It was significantly positively correlated with topographic relief (TR) (r = 0.64, P<0.01) and surface curvature (SC) (r = 0.51, P<0.01), while it was significantly negatively correlated with land use type (LUT) (r = -0.5, P<0.01). Surface roughness (SR) (r = 0.2, P<0.01) was positively correlated with gully activity; but not significantly. There was no significant correlation between aspect (As) and gully activity. The results of this study are helpful for quantitatively determining the level of gully activity and understanding the development process and mechanism controlling gullies, providing a reference for research on related regions and geomorphologic information.
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