使用集合极端梯度提升(XGBoost)算法进行形态评估和土壤侵蚀易感性绘图:对巴基斯坦北部洪扎-纳加尔集水区的研究

IF 2.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Hilal Ahmad, Zhang Yinghua, Majid Khan, Mehtab Alam, Sajid Hameed, Prabhat Man Sing Basnet, Aboubakar Siddique, Zia Ullah
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引用次数: 0

摘要

水土流失和地下水资源是全球关注的两个基本问题,它们通过各种水文和形态测量过程错综复杂地联系在一起。形态计量学与土壤侵蚀评估对于管理水文过程和实施预防战略至关重要。利用地理信息系统和遥感技术,对构造活跃的 Hunza-Nagar 集水区的形态测量、形态构造和土壤侵蚀敏感性进行了研究,该集水区面积为 1455.05 平方公里,海拔高度为 1763-7697 米。在此基础上,对线性、面积和地形形态变量进行了调查。对线性方面的分析表明,溪流从 1 级到 4 级依次排列,形成了近似于树枝状的排水模式。计算参数记录了巨大的变化,包括溪流长度 384.92 km,分叉率 1.65,排水密度 2.65 km/km2,排水强度 0.25 km-1,排水质地 0.49,溪流频率 0.07 km-2 和形态因子 0.41。环流比为 0.46,表明该流域受结构影响较大;伸长比为 0.72,表明该流域坡度适中至陡峭,洪水流量较小;1.33 千米的过流长度表明该流域具有较高的下渗能力;2.47 的形状指数则表明该流域的水土流失风险较高。土壤侵蚀易发性分析采用了 XGBoost 模型,该模型在预测建模和分类任务方面享有盛誉。该模型在包含土壤侵蚀动态相关因素的数据集上进行了训练和测试。随后,将训练有素的模型用于评估整个研究区域的土壤侵蚀易感性。最终绘制出的易受侵蚀区地图被划分为低易受侵蚀区和高易受侵蚀区。混淆矩阵和接收操作特征曲线(ROC)用于验证模型。这些结果为了解地质水文特征提供了重要依据,有助于全球保护自然资源和土壤的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Morphometric assessment and soil erosion susceptibility maping using ensemble extreme gradient boosting (XGBoost) algorithm: a study for Hunza-Nagar catchment, Northern Pakistan

Soil erosion and groundwater resources are two fundamental global concerns intricately linked through various hydrological and morphometric processes. Morphometrics with soil erosion assessment is crucial for managing hydrological processes and implementing preventative strategies. Utilizing Geographical Information system and Remote Sensing techniques, morphometric, morphotectonic, and soil erosion susceptibility in the tectonically active Hunza-Nagar catchment were explored, spanning 1455.05 km2 with elevations from 1763–7697 m above sea level. With this motive, linear, areal, and relief morphometric variables were investigated. Analysis of the linear aspects indicated the sub-dendritic drainage pattern with streams ordered from 1 to 4th order. The calculated parameters recorded huge variations, including stream length of 384.92 km, bifurcation ratio of 1.65, drainage density of 2.65 km/km2, drainage intensity of 0.25 km−1, drainage texture of 0.49, stream frequency of 0.07 km−2 and form factor of 0.41, respectively. The circulatory ratio of 0.46 indicates structural influence, elongation ratio of 0.72 reflects moderate to steep slopes with low flood regimes, length of overland flow of 1.33 km shows high infiltration and shape index of 2.47 underscores a higher risk of soil erosion in the catchment. Soil erosion susceptibility analysis was conducted using the XGBoost model, renowned for its proficiency in predictive modeling and classification tasks. The model was trained and tested on a dataset comprising factors pertinent to soil erosion dynamics. Subsequently, the trained model was applied to assess soil erosion susceptibility across the study area. The final Susceptibility map was classified from low to very high susceptible zones. Confusion matrix and Receiving operative characteristic curve (ROC) were used to validate the model. These results offer crucial insights into geohydrological characteristics, supporting global conservation efforts in conservation of natural resources and soil practices.

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来源期刊
Environmental Earth Sciences
Environmental Earth Sciences 环境科学-地球科学综合
CiteScore
5.10
自引率
3.60%
发文量
494
审稿时长
8.3 months
期刊介绍: Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth: Water and soil contamination caused by waste management and disposal practices Environmental problems associated with transportation by land, air, or water Geological processes that may impact biosystems or humans Man-made or naturally occurring geological or hydrological hazards Environmental problems associated with the recovery of materials from the earth Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials Management of environmental data and information in data banks and information systems Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.
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