The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.
Lake Issyk-Kul is an important endorheic lake in arid Central Asia. Climate change, anthropogenic water consumption and a complex basin hydrology with interlocked driving forces have led to a high variability of the water balance and an overall trend of decreasing lake water levels. The main objective of this study was to investigate these main driving forces and their interactions with the lake's water level. Hydro-meteorological and socioeconomic data from 1980 to 2012 were used for a dynamic simulation model, based on the system dynamics (SD) method. After the model calibration and validation with historical data, the model provides accurate simulation results of the water level of Lake Issyk-Kul. The main factors impacting the lake's water level were evaluated via sensitivity analysis and water resource scenarios. Results based on the sensitivity analysis indicated that socio-hydrologic factors had different influences on the lake water level change, with the main influence coming from the water inflow dynamic, namely, the increasing and decreasing water withdrawal from lake tributaries. Land use changes, population increase, and water demand decrease were also important factors for the lake water level variations. Results of four scenario analyses demonstrated that changes in the water cycle components as evaporation and precipitation and the variability of river runoff into the lake are essential parameters for the dynamic of the lake water level. In the future, this SD model can help to better manage basins with water availability uncertainties and can guide policymakers to take necessary measures to restore lake basin ecosystems.
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