A New Framework to Spatial and Temporal Drought Analysis for 1990–2020 Period with Mann–Kendall and Innovative Trend Analysis Methods in Turkey

Abstract

As a result of globally intensifying climate change effects, drought is becoming more prevalent and poses a threat to many areas, especially in water supply, agriculture, transportation, energy, and public health. Therefore, drought should be observed and analyzed regularly and effectively. A new approach has been put forward to make a temporal and spatial drought analysis based on provinces and regions in Turkey within the scope of the present study. In this context, 12-month Standardized Precipitation Index (SPI) values ​​were calculated according to precipitation data from 1990–2020 in Turkey and processed spatially in the Geographic Information System (GIS) environment. After the areal sizes of the annual SPI data based on provinces were calculated, drought trends were revealed by applying both Mann–Kendall and innovative trend analysis tests on percentile areas. In the trend analysis of drought areas, five different drought classes were taken into account, and a separate trend analysis was performed for each drought class. Significance levels of 1%, 5%, and 10% were applied in both trend tests. Drought trends at the scale of provinces and regions were evaluated after province-based areal trend maps were produced. According to the results, a decreasing trend was observed in humid categories in the Black Sea and Mediterranean Regions' coastal areas and the provinces located in the inner parts of the Eastern Anatolia Region. An areal change was also detected from relatively more humid or drier classes to near-normal classes. This study's results will positively contribute to long-term drought evaluation and monitoring studies on national and regional scales.

BIPLOT Logístico Ponderado Espacio Temporal (TSWLB): una aplicación a datos de mortalidad por cáncer de mama en el Ecuador

“…La prueba Man-Kendall, ha sido aplicada en distintos ámbitos pero mayormente en datos ambientales, climatológicos, imágenes de tipo ráster y de salud. (Ozocak et al, 2023) (Sodagari & Varga, 2023), a continuación se presentan algunas aplicaciones y modificaciones: (Hamed & Ramachandra Rao, 1998) propone una modificación a la prueba de tendencia Mann-Kendall cuando existe autocorrelación en los datos. (Neeti & Eastman, 2011) propone un enfoque de Mann-Kendall para evaluar la tendencia en series temporales de imágenes de tipo ráster; (Drápela & Drápelová, 2011) propone una aplicación de la prueba Mann-Kendall y las estimaciones de la pendiente de Sen. (Mondal et al, 2012) realizó un análisis de tendencia de precipitaciones mediante la prueba de Mann-Kendall: un estudio de caso del distrito de Cuttack, Orissa.…”