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Impacted by ongoing climate change and anthropogenic activities, large seasonal lakes experience water regime evolution, which raises challenges for the management of water resources and environment. The water regime evolution refers to the spatial and temporal alterations in the hydrological features of lakes. Characterizing the lake water regime and its alteration may help policymakers design effective adaption strategies. Therefore, total 47 hydrological indicators were proposed, considering intra-annual fluctuations, flood and drought features, and rate and frequency of water level variations. Combined with Mann-Kendall algorithm and Sen&rsquo, s slope, the indicators were applied in Poyang Lake, a typically large seasonal lake in China, as a case study. The results revealed temporal and spatial variations in different hydrological indicators. The most dramatic alteration was the water level decline in October and November over the entire study phase, especially over the past 30 years. This was an urgent environmental problem that Poyang Lake faced, partially caused by the increased hydraulic gradient between southern and northern lake. It could trigger the drought occurring earlier, prolong the drought duration, and impair the wetland ecosystem. Environmental water requirements of both Poyang Lake and Yangtze River were suggested for regional sustainable development. The application in Poyang Lake showed the practicability and reliability of the indicators, which are applicable in international seasonal lakes. The series of indicators can be used in whole or in part, determined by the ecohydrological characters of a specific lake and the research objectives.

This paper aims to detect climate change points and compare the extreme temperature changes with the average-value changes in the Amur River basin. The daily air temperatures of 44 stations in the Amur River basin were collected from April 1, 1954, to March 31, 2013. The change points for annual mean and extreme temperature in 44 individual stations and their average were detected by the Mann-Kendall test, respectively. The annual mean temperature changed during 1980s in terms of increased mean value and relative stable standard deviation. The annual maximum temperature from 31 stations mostly located in the central and northwest basin changed significantly, and their change points occurred mainly in 1990s. For the annual minimum temperature, 32 stations mainly located in the central basin had significant changes. The generalized extreme value distribution was fitted to the postchange point subseries of annual extreme temperature and the parameters were estimated by the maximum likelihood method. The 10/50/100-year return levels were estimated by the method of profile likelihood. For the areas in the central and Northwestern basin, the probability of occurrence of hot extremes increased, while the occurrence probability of cold extremes was decreased in the central basin under climate change.

As the largest tributary of the Ob River, the Irtysh River is an international river partially joining the territories of China, Kazakhstan, and Russia. Four meteorological stations in the Irtysh Basin were selected and the long-term observed daily temperature data were collected. The extreme temperature change was analyzed considering climate change. Detected by the heuristic segmentation by histogram comparison approach, climate was changed during the first half of the 1970s in terms of the increased mean value and decreased standard deviation of the daily temperature series. The noticeable change of the monthly mean temperature was the warmer winter. After climate change, the annual maximum temperature was little changed and its series was not segmented. However, the annual minimum temperature was significantly changed in terms of the increased mean value by more than 2°C, so its series was segmented to the pre- and post-change point subseries. The generalized extreme value distribution was fitted to the annual extreme temperature and the parameters were estimated by the maximum likelihood method. The return levels for 10/50/100-year return periods estimated by the profile likelihood method were obtained for the annual extreme temperature. The probability of occurrence of the cold extremes was decreased after 1970s.

Hydrological changes of the Ili River were analyzed concerning the changes of annual runoff and its distribution features within a year measured by coefficient of variation and concentration degree. Abrupt changes were detected by the heuristic segmentation method. Possible causes of the hydrological changes were investigated considering climate changes and human activities (especially the reservoir operation and irrigation extension). The Mann-Kendall method was applied to estimate whether the temperature and precipitation were changed. The increased temperature and the decreased precipitation in the flood season may decrease the runoff. At the middle reaches, the impact of the reservoir is significant and may be the main factor leading to the abrupt decreases in annual runoff and its intra-annual variability and concentration. The increased water surface area of the reservoir aggravates the evaporation and leads to annual runoff reduction. The reservoir regulates runoff by storing water in the f...

The streamflow and water level complexity of the Poyang Lake basin has been investigated over multiple time-scales using daily observations of the water level and streamflow spanning from 1954 through 2013. The composite multiscale sample entropy was applied to measure the complexity and the Mann-Kendall algorithm was applied to detect the temporal changes in the complexity. The results show that the streamflow and water level complexity increases as the time-scale increases. The sample entropy of the streamflow increases when the timescale increases from a daily to a seasonal scale, also the sample entropy of the water level increases when the time-scale increases from a daily to a monthly scale. The water outflows of Poyang Lake, which is impacted mainly by the inflow processes, lake regulation, and the streamflow processes of the Yangtze River, is more complex than the water inflows. The streamflow and water level complexity over most of the time-scales, between the daily and monthly scales, is dominated by the increasing trend. This indicates the enhanced randomness, disorderliness, and irregularity of the streamflows and water levels. This investigation can help provide a better understanding to the hydrological features of large freshwater lakes. Ongoing research will be made to analyze and understand the mechanisms of the streamflow and water level complexity changes within the context of climate change and anthropogenic activities.

Hydrological changes of the Irtysh River were analyzed concerning the changes of annual runoff and its distribution features within a year measured by coefficient of variation and concentration degree. Abrupt changes were detected by the heuristic segmentation method. Possible causes of the hydrological changes were investigated considering climate changes and human activities (especially the reservoir operation). The Mann-Kendall method was applied to estimate whether the temperature and precipitation was changed. The increased precipitation in winter may increase the runoff of April. The increased temperature and the decreased precipitation in the flood season may decrease the runoff. At the middle reaches, the impact of the reservoirs at the upper reaches is significant and may be the main factor leading to the abrupt decreases in annual runoff and its intra-annual variability and concentration. The increased water surface area of the reservoirs aggravates the evaporation and leads to annual runoff reduction. The reservoirs regulate runoff by storing water in the flood season and releasing water in the dry season. While at the lower reaches, the annual runoff remained steady and its intra-annual variation and concentration were reduced gradually because the impact of the reservoirs is relative small and the climatic impact may be more relevant.

Based on the daily data of temperature (T) and precipitation (P) of Heilongjiang River basin, Mann–Kendall test method, the linear least-squares regression model and hydrological statistical analysis methods were selected to analyze the variations of temperature, precipitation, and extreme events in Heilongjiang River. The results revealed that T had significant increasing trends, and annual P increased only in the lower reaches. The annual extreme low temperature (ELT) increased obviously. Both the annual extreme high temperature (EHT) had noticeable increasing trends. The outputs can provide a valuable theoretical basis for sustainable development and utilization of water resources in Heilongjiang River.