Kariminejad Narges, Hosseinalizadeh Mohsen, Pourghasemi Hamid Reza, Bernatek-Jakiel Anita, Campetella Giandiego, Ownegh Majid
Department of Watershed and Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan 49189-434, Iran.
Department of Watershed and Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan 49189-434, Iran.
Sci Total Environ. 2019 Aug 10;677:281-298. doi: 10.1016/j.scitotenv.2019.04.306. Epub 2019 Apr 26.
Gully erosion is an important soil degradation process, which under climate changes is projected to increase. Therefore, better understating of factors controlling gully erosion and prediction of gully headcuts' (GHs) location is still highly relevant. This study aimed to examine the spatial distribution of GHs and to assess the importance of pedological (i.e. aggregate stability, organic matter, bulk density, silt, clay, and sand content) and topographical factors (i.e. altitude, slope length, gradient, and aspect) using summary statistics and the maximum entropy (MaxEnt) model. The study was conducted in the loess-covered region of NE Iran. The highly precise data of 287 GHs locations were obtained by extensive fieldwork and the interpretation of UAV images. The spatial distribution of GHs was evaluated by univariate pair correlation function and O-ring statistics. The spatial effect of GHs density controlling factors was assessed by the cumulative density correlation function Cm,K(r). Variable importance was analyzed using the MaxEnt model, which was also for the susceptibility modelling of GHs. The results of univariate tests showed the aggregated distribution of GHs. The Cm,K(r) analyses indicated that the areas characterized by higher values of bulk density, aggregate stability, and organic matter content have lower GHs density, whereas the areas with high silt content and higher slope gradient have higher GHs density. According to the MaxEnt, there is no one single factor responsible for GHs location, but rather the combination of topographical and pedological factors with the predominance of slope gradient (0.86) and silt content (0.57). The MaxEnt modelling of GHs susceptibility has revealed that the best accuracy (0.958) is given when all pedological and topographical factors are used in the model. The susceptibility maps prepared in the study can be used for soil conversation and land use planning and, consequently, for sustainable development in the region.
沟蚀是一种重要的土壤退化过程，预计在气候变化的情况下其会加剧。因此，更好地理解控制沟蚀的因素以及预测沟头侵蚀（GHs）的位置仍然具有高度相关性。本研究旨在研究GHs的空间分布，并使用汇总统计数据和最大熵（MaxEnt）模型评估土壤学因素（即团聚体稳定性、有机质、容重、粉砂、黏土和砂含量）和地形因素（即海拔、坡长、坡度和坡向）的重要性。该研究在伊朗东北部的黄土覆盖地区进行。通过广泛的实地调查和无人机图像解释，获得了287个GHs位置的高精度数据。通过单变量对相关函数和O形环统计评估了GHs的空间分布。通过累积密度相关函数Cm,K(r)评估了GHs密度控制因素的空间效应。使用MaxEnt模型分析了变量重要性，该模型也用于GHs的敏感性建模。单变量测试结果显示了GHs的聚集分布。Cm,K(r)分析表明，容重、团聚体稳定性和有机质含量较高的区域GHs密度较低，而粉砂含量高和坡度较大的区域GHs密度较高。根据MaxEnt模型，没有单一因素决定GHs的位置，而是地形和土壤学因素的组合，其中坡度（0.86）和粉砂含量（0.57）占主导。GHs敏感性的MaxEnt建模表明，当模型中使用所有土壤学和地形因素时，精度最高（0.958）。本研究中绘制的敏感性图可用于土壤保护和土地利用规划，从而促进该地区的可持续发展。
