بررسي خشكسالي حوضه درياچه اروميه با ديدگاه نامانا

The increase in climate change and the emergence of unexpected phenomena have intensified the necessity for comprehensive and accurate studies on drought. Accordingly, this study has taken a holistic approach to examining drought in the Urmia Basin, one of Iranʹs most challenging catchment areas. In this context, the study area of the Urmia Lake basin was divided into three sub-regions: eastern, western, and southern. Using the SPEI index at three temporal scales short-term, medium-term, and long-terma comprehensive spatial, temporal, risk, and drought analysis with a non-stationary perspective was developed. In general, according to the results of the Severity-Area-Frequency (SAF) analysis in spatial drought analysis, high-intensity droughts in the eastern basin experience a long er return period compared to the other two regions. The most severe events in the eastern basin occur on a short-term and medium-term scale. Similarly, in the southern region, the most severe events occur in short-term and long-term droughts, while in the western basin, medium-term and long-term droughts are usually reported with the highest intensity. Regarding the temporal analysis of drought, the Mann-Kendall test shows that the trend of droughts has a larger magnitude over longer time scales. Similarly, based on Senʹs slope criterion, the highest increasing trend in droughts (slope more than 0.001) is observed in long-term droughts in the southern and eastern regions of the basin. The results of the risk analysis for the Urmia Lake basin regarding the SPEI12 index indicate that the eastern region, with a vulnerability of 17.97, shows the highest vulnerability compared to other regions (15.62 and 14.28 for the western and southern regions, respectively). Additionally, resilience to medium-term and long-term drought events in the western and eastern parts of the basin (more than about 0.70) is higher than resilience in the southern part (around 0.14). Similarly, the exposure coefficient indicates that for all three types of drought indices, the western and southern regions have similar conditions when facing drought (between 0.26 and 0.29), which are lower than their values in the eastern basin (about 0.22). In the non-stationary analysis, using the GEV probabilistic distribution and the SPEI drought index, other auxiliary variables, including the Southern Oscillation Index (SOI), monthly precipitation, and maximum monthly temperature from 1986 to 2020, were eva‎luated. Based on the Akaike Information Criterion (AIC), the best model was selected between one stationary and 14 non-stationary models. From the examination of the SPEI3 index in all stations, the auxiliary parameter of the SOI climate index is present in the superior models, highlighting the importance of this index in influencing short-term droughts. Additionally, the presence of the two components, SOI and precipitation, in models related to medium-term droughts and the maximum temperature variable in all selected non-stationary models based on long-term droughts (SPEI12) indicates the effectiveness of these variables in studying this type of drought. On the other hand, it is generally evident that drought analysis from a non-stationary perspective is associated with a reduction in the drought return period and, accordingly, an increase in the risk of extreme events. In short-term droughts, the effect of reducing the return period of the most severe drought from a stationary to a non-stationary state in the Urmia and Sarab stations, with a decrease of about 93% (from about 20 years to less than 1.5 years), is significant. This result for medium-term droughts shows the highest reduction in the return period (more than 77%) in Saghez and Maragheh stations, and for long-term droughts, in Sahand and Saghez stations, it shows more than 90% (from 30 years to about three years).

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