基于最大熵模型的土耳其Karapınar地区空间天坑发生预测

F. Sarı, M. Yalcin
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引用次数: 0

摘要

Karapınar的天坑及其迅速增加的发生率被认为是威胁耕地和人类生命的主要危害之一。天坑的突发性和不可避免性使其更加危险和具有挑战性。土耳其科尼亚省Karapınar地区记录了300多个天坑。该地区有密集的农业活动,因此使用了6万多口水井来满足需求。因此,干旱、气候变化的影响和降水率的减少表明,该地区的地质构造和自古以来火山历史导致的高陷落倾向对陷落发生有压力。本研究的主要目的是根据历史事件预测Konya, Karapınar地区可能发生天坑的概率,并向当局报告以提高对这一问题的认识。通过对影响天坑发生的气象、地形、环境和地质等17个变量进行评价,将最大熵(MaxEnt)模型应用于天坑敏感性制图。结果表明:研究区有458.52 km2(2.48%)为陷落高易感区;100个天坑作为样本数据,45个天坑作为MaxEnt模型的测试数据。训练数据的AUC值为0.978,测试数据的AUC值为0.963,相关性较好。计算了年平均气温、降水季节性(变异系数)、地质和降水这三个主要影响天坑形成的变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximum entropy model-based spatial sinkhole occurrence prediction in Karapınar, Turkey
Sinkholes in Karapınar and their rapidly increasing occurrence rate are considered one of the main hazards that threaten arable lands and human life. The sudden occurrence and unavoidable characteristics of sinkholes make them more dangerous and challenging to avoid. More than 300 sinkholes have been recorded in the Karapınar region of Konya province in Turkey. There are intensive agricultural activities in the region, and therefore over 60,000 water wells are used to meet the demand. Thus, drought, the effects of climate change and decreasing precipitation rate reveal stress on sinkhole occurrence due to the geological structure of the region and its high tendency to sinkholes since ancient times due to its volcanic history. The primary purpose of this study is to predict possible sinkhole occurrence probabilities in Konya, Karapınar region based on historical occurrences and to report to the authorities to raise awareness about this problem. The Maximum Entropy (MaxEnt) model is applied for sinkhole susceptibility mapping by evaluating 17 variables affecting sinkhole occurrence in meteorological, topographic, environmental, and geological aspects. The results indicated that 458.52 km2 (2.48%) of the study area is highly susceptible to sinkholes. 100 sinkholes were assigned as sample data, and 45 sinkholes were set as test data for the MaxEnt model. The AUC values of training data with 0.978 and test data with 0.963 were calculated where a good correlation was provided. The variables Annual Mean Temperature, Precipitation Seasonality (Coefficient of Variation) Geology, and precipitation, which are mostly responsible for sinkhole formations, have been calculated.
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来源期刊
Kuwait Journal of Science & Engineering
Kuwait Journal of Science & Engineering MULTIDISCIPLINARY SCIENCES-
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