通过整合先进的地理空间分析技术和山洪潜力指数,评估 Kratovska Reka 流域(北马其顿)的风险易发区

IF 1.7 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Bojana Aleksova, Ivica Milevski, Risto Mijalov, Slobodan B. Marković, Vladimir M. Cvetković, Tin Lukić
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引用次数: 0

摘要

本研究综合了地理信息系统、遥感和实地调查数据,对北马其顿东北部 Kratovska Reka 流域的山洪易发性进行了全面分析。研究了影响山洪动态的关键因素,包括坡度、岩性、土地利用和植被指数,以制定山洪潜势指数(FFPI)。利用 5 米数字高程模型(DEM)绘制的坡度变化图显示,东部支流的坡度高于西部支流。根据易受侵蚀过程影响的程度对岩性单元进行了分类,发现碎屑沉积物最易引发山洪。土地利用分析显示,非灌溉农业地表和植被稀疏地区极易受到侵蚀。将这些因素整合到 FFPI 模型中,可以深入了解山洪的易发性,结果表明整个流域的风险为中等。考虑到 FFPI 值在 1 到 5 之间,其平均值为 1.9。此外,易受山洪影响的地形占 49.34%,属于中等风险。实地调查数据验证了这一模型,显示山洪热点地区与 FFPI 确定的高风险地区存在明显重叠。Kratovska Reka 的每条支流(子流域)都计算了平均 FFPI 系数。根据该模型,Latišnica 对潜在山洪的平均易感性系数最高,为 2.16。这些发现为空间规划和洪水风险管理提供了宝贵的见解,对地方和国家级应用都有影响。未来的研究方向包括采用机器学习技术来提高建模的准确性,并减少分配权重系数时的主观性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing risk-prone areas in the Kratovska Reka catchment (North Macedonia) by integrating advanced geospatial analytics and flash flood potential index
This study presents a comprehensive analysis of flash flood susceptibility in the Kratovska Reka catchment area of Northeastern North Macedonia, integrating Geographic Information System, remote sensing, and field survey data. Key factors influencing flash flood dynamics, including Slope, Lithology, Land use, and Vegetation index, were investigated to develop the Flash Flood Potential Index (FFPI). Mapping slope variation using a 5-m Digital Elevation Model (DEM) revealed higher slopes in eastern tributaries compared to western counterparts. Lithological units were classified based on susceptibility to erosion processes, with clastic sediments identified as most prone to flash floods. Land use analysis highlighted non-irrigated agricultural surfaces and areas with sparse vegetation as highly susceptible. Integration of these factors into the FFPI model provided insights into flash flood susceptibility, with results indicating a medium risk across the catchment. The average value of the FFPI is 1.9, considering that the values range from 1 to 5. Also, terrains susceptible to flash floods were found to be 49.34%, classified as medium risk. Field survey data validated the model, revealing a significant overlap between hotspot areas for flash floods and high-risk regions identified by the FFPI. An average FFPI coefficient was calculated for each tributary (sub-catchment) of the Kratovska Reka. According to the model, Latišnica had the highest average coefficient of susceptibility to potential flash floods, with a value of 2.16. These findings offer valuable insights for spatial planning and flood risk management, with implications for both local and national-scale applications. Future research directions include incorporating machine learning techniques to enhance modeling accuracy and reduce subjectivity in assigning weighting factors.
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来源期刊
Open Geosciences
Open Geosciences GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
3.10
自引率
10.00%
发文量
63
审稿时长
15 weeks
期刊介绍: Open Geosciences (formerly Central European Journal of Geosciences - CEJG) is an open access, peer-reviewed journal publishing original research results from all fields of Earth Sciences such as: Atmospheric Sciences, Geology, Geophysics, Geography, Oceanography and Hydrology, Glaciology, Speleology, Volcanology, Soil Science, Palaeoecology, Geotourism, Geoinformatics, Geostatistics.
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