Testing of Drought Exceedance Probability Index (DEPI) for Turkey using PERSIANN data for 2000-2021 period

IF 1.6 4区 农林科学 Q2 AGRONOMY
E. Topçu
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引用次数: 1

Abstract

Drought is a climatic event that threatens the environment and human life with an ambiguity of location and time. Recently, droughts can be analyzed for different periods with the help of different mathematical methods and developing technology. This study aims to perform a drought analysis in 126 designated study points of Turkey. The analyzed data includes monthly total precipitation values between March 2000 and February 2021, obtained from PERSIANN system (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). Monthly precipitation totals of these designated points were used as input parameters in the Drought Exceedance Probability Index (DEPI) which is a new drought analysis method. The analysis was conducted separately for the whole of Turkey from January to December. Moreover, the findings were compared with the Standardized Precipitation Index (SPI), a globally accepted and commonly used drought index, to measure the drought detection performance of DEPI. SPI was calculated for periods of 6, 12 and 24 months. Pearson correlation coefficients between drought values of SPI-6, SPI-12 and SPI-24 and DEPI results were calculated. The second part of the study includes possible trend of drought determined by the Mann-Kendall trend analysis method. Both DEPI and SPI results and trend analysis results were mapped and visualized with the help of ArcGIS package program. The highest correlation is between DEPI and SPI-12 with 0.75, while the lowest correlation is between DEPI and SPI-24 with a value of 0.62. SPI monthly drought maps indicated the wettest months were January and February, while the driest months were March and July. Besides the DEPI monthly drought maps, the wettest months were October and November, while the driest months were May and June. The Mann-Kendall trend maps showed a significant increase in drought for summer.
使用2000-2021年期间PERSIANN数据对土耳其干旱异常概率指数(DEPI)进行测试
干旱是一种威胁环境和人类生活的气候事件,具有地点和时间的模糊性。近年来,利用不同的数学方法和发展技术,可以对不同时期的干旱进行分析。本研究旨在对土耳其126个指定的研究点进行干旱分析。分析的数据包括2000年3月至2021年2月的月总降水量,数据来自PERSIANN系统(使用人工神经网络的遥感信息降水估计)。将这些指定点的月降水总量作为干旱超过概率指数(DEPI)的输入参数,这是一种新的干旱分析方法。该分析是在1月至12月期间对整个土耳其单独进行的。并将研究结果与标准化降水指数(SPI)进行了比较,以衡量DEPI的干旱检测性能。分别计算6、12和24个月的SPI。计算了SPI-6、SPI-12和SPI-24干旱值与DEPI结果之间的Pearson相关系数。研究的第二部分包括利用Mann-Kendall趋势分析法确定的干旱可能趋势。利用ArcGIS包程序对DEPI、SPI结果和趋势分析结果进行制图和可视化。DEPI与SPI-12的相关性最高,为0.75,与SPI-24的相关性最低,为0.62。SPI月度干旱图显示,最潮湿的月份是1月和2月,而最干燥的月份是3月和7月。除了DEPI的月度干旱图外,最潮湿的月份是10月和11月,而最干燥的月份是5月和6月。曼-肯德尔趋势图显示,夏季干旱显著增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.10
自引率
8.30%
发文量
6
期刊介绍: Among the areas of specific interest of the journal there are: ecophysiology; phenology; plant growth, quality and quantity of production; plant pathology; entomology; welfare conditions of livestocks; soil physics and hydrology; micrometeorology; modeling, simulation and forecasting; remote sensing; territorial planning; geographical information systems and spatialization techniques; instrumentation to measure physical and biological quantities; data validation techniques, agroclimatology; agriculture scientific dissemination; support services for farmers.
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