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Lake Urmia is one of the largest hypersaline lakes on earth with a unique biodiversity. over the past two decades the lake water level declined dramatically, threatening the functionality of the lake's ecosystems. there is a controversial debate about the reasons for this decline, with either mismanagement of the water resources, or climatic changes assumed to be the main cause. in this study we quantified the water budget components of Lake Urmia and analyzed their temporal evolution and interplay over the last five decades. With this we can show that variations of Lake Urmia's water level during the analyzed period were mainly triggered by climatic changes. However, under the current climatic conditions agricultural water extraction volumes are significant compared to the remaining surface water inflow volumes. Changes in agricultural water withdrawal would have a significant impact on the lake volume and could either stabilize the lake, or lead to its complete collapse. Scientific RepoRtS | (2020) 10:236 | https://doi.org/10.1038/s41598-019-57150-y www.nature.com/scientificreports www.nature.com/scientificreports/ for the uncertainty of the presented approach. Being aware of the existence of more accurate concepts, we still consider the applied approach appropriate as it does not require additional and, in our case, not continuously available data such as water temperature and humidity directly above the lake surface.Statistics. The 12-months standardized precipitation evaporation index (SPEI) 34 and the 12-months standardized runoff index (SRI) 35 are calculated individually for all 132 runoff stations 44 . Here, for the SPEI the closest available weather station, based on Thiessen polygons, is used. Subsequently, for each month during the test period from 1965 to 2016, the runoff-weighted averages for the indices are calculated (Fig. 3a). In order to investigate the temporal development of both time series, they are split into the six periods, which characterize the general trends in lake volume evolution (Fig. 2). For each of these periods and for both indices a seasonal Mann-Kendall test is performed and the Sens slope is calculated 45,46 . The significance level for the seasonal Mann-Kendall test is 0.01 and the starting month for the 12-months interval is October (start of the hydrological year). Bootstrap sampling of the slope of the simple linear regression model of the SRI-SPEI relationship for the six periods is performed with a number of 1000 data samples (Fig. 3c).

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