Spatio‐temporal trend analysis of drought in the GAP Region, Turkey

Veysel Gumus (), Oguz Simsek (), Yavuz Avsaroglu () and Berivan Agun ()
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Veysel Gumus: Harran University
Oguz Simsek: Harran University
Yavuz Avsaroglu: Harran University
Berivan Agun: Harran University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 109, issue 2, No 18, 1759-1776

Abstract: Abstract Drought is considered to be one of the most devastating natural disasters. In recent years, determination of historical droughts has gained more importance. This can be attributed to the fact that once the trend of historical droughts is determined, it should be possible to struggle against drought more effectively. In this study, the drought analysis is performed in the Southeastern Anatolia Project (GAP) region, which is Turkey's biggest integrated project, using the monthly total precipitation data from 15 stations in nine provinces. Standardized precipitation index (SPI), being one of the most frequently used methods in the literature, is used to determine the drought indices. Temporal drought and occurrence of drought are calculated for 3, 6 and 12 month time scales. The non-parametric Mann–Kendall and Mann–Kendall Rank Correlation tests are used to determine the monotonic trends of drought indices and its year of initiation. The “Pre-whitened” method is used to remove serial correlation from time series before analysis. Linear slope of the trend is determined by Sen's Slope method, and Inverse Distance Weighting method is used for the spatial analysis. According to trends of temporal drought of the GAP region, a decreasing trend is found in 30% of the stations for 12-month SPI values with a statistical significance. Based on the results obtained from spatial analysis, there is a decreasing trend in most of the region for almost all time scales, and the slopes of trend are relatively higher in the north and south of the region.

Keywords: Drought analysis; Trend analysis; GAP region; Temporal analysis; Spatial analysis (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11069-021-04897-1

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