Abstract
Over the past decades, low flow has been highly impacted by climate change across Turkey, and it is important to investigate low flow trends and drivers of this change to guide water resources management. The standard normal homogeneity test (SNHT), the Pettitt test, and the Buishand range test were used for homogeneity analysis. A comprehensive assessment of trends and variability in low flows from 88 flow stations located in 26 river basins across Turkey and their attributions in a changing climate were presented. The Mann–Kendall (MK) and modified Mann–Kendall test (mMK) were utilized to detect the significance of trends, while Sen’s slope method was used to identify the magnitude of trends. According to the trend test results, the low flow records of 34 stations indicated statistically decreasing trends, whereas those of four stations indicated a statistically increasing trend. We also analyzed how climate variables affect low flow variations. Correlations between climate variables (temperature and precipitation) and large-scale climate models with low flow were determined by Spearman's Rho test. North Atlantic Oscillation (NAO), Western Mediterranean Oscillation (WeMO), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO) were investigated for their relation with the low flow variability. The results showed that low flow data were generally positively correlated with precipitation, and this result was particularly pronounced on the annual scale. Unlike precipitation, low flow series have a negative correlation with temperature data, and correlations are clearer during dry periods. In most areas, NAO and SO were negatively correlated with low flow patterns in Turkey, while PDO and WeMO were positively correlated with low flow series. The results indicate that low flows in most regions are more sensitive to precipitation than temperature and large-scale climate models. In addition, this research reported that the use of seasonal indices made some seasonal correlations more pronounced than their annual counterparts. These results suggest that seasonal climate indices can be potential candidates for low flow prediction.
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Data availability
Streamflow data set has been downloaded from https://www.dsi.gov.tr/.
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The authors acknowledge the General Directorate of State Hydraulic Works, Turkey, for providing the daily streamflow data records used in this study.
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Yılmaz, M., Tosunoğlu, F. Assessing the main drivers of low flow series in Turkey. Nat Hazards 115, 1927–1953 (2023). https://doi.org/10.1007/s11069-022-05621-3
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DOI: https://doi.org/10.1007/s11069-022-05621-3