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In this paper, wavelet transform coherence is implemented to examine the impacts of hydroclimatological variables on water level fluctuations in two large saline lakes in the Middle East with a similar geographical location, namely, Urmia Lake in north-west Iran, which has an extremely simple ecological pyramid where water level decrease produces a very sensitive ecosystem, and Van Lake in north-east Turkey. The present study investigates trends in higher order moments of hydrological time series. The aim of this paper is to investigate the complexity of Urmia Lake water level time series which could lead to decrease fluctuations of time series. To this end, the strength and relationships between five hydroclimatological variables, including rainfall, runoff, temperature, relative humidity, as well as evaporation and water level fluctuations in the lakes were determined and discussed in terms of high common power region, phase relationships, and local multi-scale correlations. The results showed that among the hydroclimatological variables, runoff has the most coherencies (0.9–1) with water level fluctuations in the lakes. Although both lakes are located in a similar climatic region, for the recent 15 years, adverse trend in water level fluctuations of Urmia Lake indicates a critical condition for this lake.

Investigating the effect of hydroclimatological variables on Urmia Lake water level using wavelet coherence measure