Utilizing geodetectors to identify conditioning factors for gully erosion risk in the black soil region of northeast China

IF 7.3 1区 农林科学 Q1 ENVIRONMENTAL SCIENCES
Donghao Huang , Xinrui Zhao , Zhe Yin , Wei Qin
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引用次数: 0

Abstract

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.
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
在中国东北黑土区,沟壑水土流失问题一直是一个重大威胁,造成农田大面积破坏、黑土地严重退化和生产力下降。因此,准确识别沟蚀易发区,有效预防和控制沟蚀的负面影响至关重要。本研究试图利用地理探测器(geodetectors)来确定导致沟壑分布的因素,并评估该地区五个集水区的沟壑侵蚀风险(GER),这些集水区的面积约为 80 平方公里至 200 平方公里。通过采用地质探测器方法,分析了 14 个地质环境因素,包括地形属性(如纵向、流域面积、汇聚指数、海拔高度、平面曲率、剖面曲率、坡长、坡度、溪流动力指数和地形湿润指数)、沟道网络距离、植被指数(NDVI 和 EVI)以及土地利用/土地覆盖(LULC)。采用随机森林算法(RFA)对 GER 进行建模。在所研究的 14 个地理环境因子中,只有一个子集(小于或等于 50%)对沟壑的空间分布有显著影响(p < 0.05)。这些选定因素足以评估 GER,其中 LULC(平均 q 值 = 0.270)和海拔(平均 q 值 = 0.113)被认为是两个最重要的因素。此外,RFA 在所有流域都表现出令人满意的性能,在预测 GER 方面的 AUC 值介于 0.712 到 0.933 之间(平均值 = 0.863)。总体而言,集水区被划分为高、中、低和极低风险等级,分别占总面积的 9.67%-15.95%、19.28%-26.08%、24.59%-30.55% 和 30.54%-39.08%。重要的是,在耕地面积比例与高级别 GER 发生率之间观察到了明显的正线性关系(r2 = 0.722,p <0.05)。虽然主要风险等级被划分为低和极低,但高风险等级的比例超过了现有的沟壑覆盖率(0.34%-3.69%)。这些发现凸显了沟蚀的巨大潜力,并强调了在中国东北黑土区加强沟蚀防治工作的必要性。
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来源期刊
International Soil and Water Conservation Research
International Soil and Water Conservation Research Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
12.00
自引率
3.10%
发文量
171
审稿时长
49 days
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
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