{"title":"利用地质探测器识别中国东北黑土区沟壑侵蚀风险的条件因素","authors":"Donghao Huang , Xinrui Zhao , Zhe Yin , Wei Qin","doi":"10.1016/j.iswcr.2024.07.004","DOIUrl":null,"url":null,"abstract":"<div><div>In the black soil region of Northeast China, the issue of gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation of the black soil, and decreased productivity. It is therefore of utmost importance to accurately identify areas that are susceptible to gully erosion to effectively prevent and control its negative impact. This study tried to utilize geographical detectors (geodetectors) as a means to identify the factors that contribute to the distribution of gullies and assess the risk of gully erosion (GER) in five catchments within the region, with areas ranging from approximately 80 km<sup>2</sup>–200 km<sup>2</sup>. By employing the geodetectors method, fourteen geo-environmental factors were analyzed, including topographic attributes (such as aspect, catchment area, convergence index, elevation, plan curvature, profile curvature, slope length, slope, stream power index, and topographic wetness index), channel network distance, vegetation index (NDVI and EVI), as well as land use/land cover (LULC). The modeling of GER was conducted using the random forest algorithm (RFA). Out of the fourteen examined geo-environmental factors, only a subset, comprising less than or equal to 50%, demonstrated a significant (<em>p</em> < 0.05) influence on the spatial distribution of gullies. These selected factors were sufficient in assessing GER, with LULC (mean q-value = 0.270) and elevation (mean q-value = 0.113) identified as the two most important factors. Furthermore, the RFA exhibited satisfactory performance across all catchments, achieving AUC values ranging from 0.712 to 0.933 (mean = 0.863) in predicting GER. Overall, the catchment areas were classified into high, moderate, low, and very low-risk levels, representing 9.67%–15.95%, 19.28%–26.08%, 24.59%–30.55%, and 30.54%–39.08% of the total area, respectively. Importantly, a significant positive linear relationship (r<sup>2</sup> = 0.722, <em>p</em> < 0.05) was observed between the proportion of cropland area and the occurrence of high-level GER. Although the primary risk levels were categorized as low and very low, the proportion of high-risk levels exceeded the existing gully coverage (0.34%–3.69%). These findings highlight the substantial potential for gully erosion and underscore the necessity for intensified efforts in the prevention and control of gully erosion within the black soil region of Northeast China.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":null,"pages":null},"PeriodicalIF":7.3000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Utilizing geodetectors to identify conditioning factors for gully erosion risk in the black soil region of northeast China\",\"authors\":\"Donghao Huang , Xinrui Zhao , Zhe Yin , Wei Qin\",\"doi\":\"10.1016/j.iswcr.2024.07.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In the black soil region of Northeast China, the issue of gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation of the black soil, and decreased productivity. It is therefore of utmost importance to accurately identify areas that are susceptible to gully erosion to effectively prevent and control its negative impact. This study tried to utilize geographical detectors (geodetectors) as a means to identify the factors that contribute to the distribution of gullies and assess the risk of gully erosion (GER) in five catchments within the region, with areas ranging from approximately 80 km<sup>2</sup>–200 km<sup>2</sup>. By employing the geodetectors method, fourteen geo-environmental factors were analyzed, including topographic attributes (such as aspect, catchment area, convergence index, elevation, plan curvature, profile curvature, slope length, slope, stream power index, and topographic wetness index), channel network distance, vegetation index (NDVI and EVI), as well as land use/land cover (LULC). The modeling of GER was conducted using the random forest algorithm (RFA). Out of the fourteen examined geo-environmental factors, only a subset, comprising less than or equal to 50%, demonstrated a significant (<em>p</em> < 0.05) influence on the spatial distribution of gullies. These selected factors were sufficient in assessing GER, with LULC (mean q-value = 0.270) and elevation (mean q-value = 0.113) identified as the two most important factors. Furthermore, the RFA exhibited satisfactory performance across all catchments, achieving AUC values ranging from 0.712 to 0.933 (mean = 0.863) in predicting GER. Overall, the catchment areas were classified into high, moderate, low, and very low-risk levels, representing 9.67%–15.95%, 19.28%–26.08%, 24.59%–30.55%, and 30.54%–39.08% of the total area, respectively. Importantly, a significant positive linear relationship (r<sup>2</sup> = 0.722, <em>p</em> < 0.05) was observed between the proportion of cropland area and the occurrence of high-level GER. Although the primary risk levels were categorized as low and very low, the proportion of high-risk levels exceeded the existing gully coverage (0.34%–3.69%). These findings highlight the substantial potential for gully erosion and underscore the necessity for intensified efforts in the prevention and control of gully erosion within the black soil region of Northeast China.</div></div>\",\"PeriodicalId\":48622,\"journal\":{\"name\":\"International Soil and Water Conservation Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.3000,\"publicationDate\":\"2024-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Soil and Water Conservation Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2095633924000534\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Soil and Water Conservation Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2095633924000534","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Utilizing geodetectors to identify conditioning factors for gully erosion risk in the black soil region of northeast China
In the black soil region of Northeast China, the issue of gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation of the black soil, and decreased productivity. It is therefore of utmost importance to accurately identify areas that are susceptible to gully erosion to effectively prevent and control its negative impact. This study tried to utilize geographical detectors (geodetectors) as a means to identify the factors that contribute to the distribution of gullies and assess the risk of gully erosion (GER) in five catchments within the region, with areas ranging from approximately 80 km2–200 km2. By employing the geodetectors method, fourteen geo-environmental factors were analyzed, including topographic attributes (such as aspect, catchment area, convergence index, elevation, plan curvature, profile curvature, slope length, slope, stream power index, and topographic wetness index), channel network distance, vegetation index (NDVI and EVI), as well as land use/land cover (LULC). The modeling of GER was conducted using the random forest algorithm (RFA). Out of the fourteen examined geo-environmental factors, only a subset, comprising less than or equal to 50%, demonstrated a significant (p < 0.05) influence on the spatial distribution of gullies. These selected factors were sufficient in assessing GER, with LULC (mean q-value = 0.270) and elevation (mean q-value = 0.113) identified as the two most important factors. Furthermore, the RFA exhibited satisfactory performance across all catchments, achieving AUC values ranging from 0.712 to 0.933 (mean = 0.863) in predicting GER. Overall, the catchment areas were classified into high, moderate, low, and very low-risk levels, representing 9.67%–15.95%, 19.28%–26.08%, 24.59%–30.55%, and 30.54%–39.08% of the total area, respectively. Importantly, a significant positive linear relationship (r2 = 0.722, p < 0.05) was observed between the proportion of cropland area and the occurrence of high-level GER. Although the primary risk levels were categorized as low and very low, the proportion of high-risk levels exceeded the existing gully coverage (0.34%–3.69%). These findings highlight the substantial potential for gully erosion and underscore the necessity for intensified efforts in the prevention and control of gully erosion within the black soil region of Northeast China.
期刊介绍:
The International Soil and Water Conservation Research (ISWCR), the official journal of World Association of Soil and Water Conservation (WASWAC) http://www.waswac.org, is a multidisciplinary journal of soil and water conservation research, practice, policy, and perspectives. It aims to disseminate new knowledge and promote the practice of soil and water conservation.
The scope of International Soil and Water Conservation Research includes research, strategies, and technologies for prediction, prevention, and protection of soil and water resources. It deals with identification, characterization, and modeling; dynamic monitoring and evaluation; assessment and management of conservation practice and creation and implementation of quality standards.
Examples of appropriate topical areas include (but are not limited to):
• Conservation models, tools, and technologies
• Conservation agricultural
• Soil health resources, indicators, assessment, and management
• Land degradation
• Sustainable development
• Soil erosion and its control
• Soil erosion processes
• Water resources assessment and management
• Watershed management
• Soil erosion models
• Literature review on topics related soil and water conservation research