Dynamic changes in water resources and comprehensive assessment of water resource utilization efficiency in the Aral Sea basin, Central Asia.

The Aral Sea Basin in Central Asia faces significant challenges in improving water utilization and treatment because of frequent transboundary river water disputes and shortages of water resources. However, the traditional water resource utilization efficiency (WRUE) assessment models generally have the defect of over-validating evaluation results. To solve this problem, this study used the Coefficient of Variation method to constrain the self-contained weights in the traditional Data Envelopment Analysis (DEA) to construct an improved CV-DEA model, and assessed the WRUE of the Aral Sea Basin countries during 2000-2018 and compared the WRUE with that of the countries in the Mekong River Basin and Northeast Asia, then explored the factors influencing water utilization. The conclusions were drawn: since 1960, the runoff from the upper Amu Darya and Syr Darya rivers increased significantly, while the runoff from the lower Amu Darya River into the Aral Sea declined. Meanwhile, the water area of the Aral Sea shrank from 2.56 × 104 km2 to 0.70 × 104 km2 in 2000-2018, with the Northern Aral Sea remaining stable while the southern part shrinking sharply. The WRUE of the Aral Sea Basin (0.599, on average) was higher than that of the Mekong River Basin (0.547) and lower than that of Northeast Asia (0.885). Kazakhstan and Uzbekistan had the highest WRUE of 0.819 and 0.685 respectively, and the WRUE in both two countries improved from 2000 to 2018. Tajikistan (0.495) and Turkmenistan (0.402) experienced decreases in WRUEs. The high input redundancy of agricultural water consumption was the main driving force affecting WRUE in the basin.

Decreasing trends of mean and extreme snowfall in High Mountain Asia.

Intense warming profoundly alters precipitation phase patterns and intensity in High Mountain Asia (HMA). While snowfall climatology and precipitation extremes have been studied, there is a lack of understanding of snowfall extremes within HMA. Here, we investigate the spatial and temporal variability of non-extreme and extreme snowfall in hydrological years 1979-2020 using multi-source meteorological data, compare weather systems during extreme and non-extreme snowfall events, and identify key circulation factors that influence fluctuations in mean annual snowfall and extreme snowfall. The snowfall amount (-0.13 d/mm), days (-0.56 d/a), and fraction (-0.0012) were significantly reduced in HMA, with a shorter snowfall season (-0.52 d/a). Some extreme snowfall metrics (maximum 1-day snowfall and maximum 3-day snowfall) were insensitive to climate change, whereas the maximum consecutive snowfall days (-0.007 d/a), snowfall amount (-0.0023 mm/a), heavy snowfall days (S95pD; 0.0087 d/a), and extremely heavy snowfall days (S99pD; -0.1019 d/a) showed significant decreases. Synthetic analyses show that extreme snowfall events were more likely to occur within a narrow temperature range (-5 °C to 3 °C) with higher relative humidity and precipitation compared to non-extreme events. A stepwise regression method was used to determine that the fluctuation in the average annual snowfall was closely related to the Atlantic Multidecadal Oscillation, whereas the variation in extreme snowfall was mainly influenced by the Southern Oscillation Index. Our research provides a reference for assessing the potential impacts of climate change on a regional scale for risk management and disaster adaptation.

Shifting in the global flood timing.

Climate change will have an impact on not only flood magnitude but also on flood timing. This paper studies the shifting in flood timing at 6167 gauging stations from 1970 to 2010, globally. The shift in flood timing and its relationship with three influential factors (maximum 7-day precipitation, soil moisture excess, and snowmelt) are investigated. There is a clear global pattern in the mean flooding date: winter (Dec-Feb) across the western Coastal America, western Europe and the Mediterranean region, summer (Jun-Aug) in the north America, the Alps, Indian Peninsula, central Asia, Japan, and austral summer (Dec-Feb) in south Africa and north Australia area. The shift in flood timing has a trend from - 22 days per decade (earlier) to 28 days per decade (delayed). Earlier floods were found extensively in the north America, Europe and northeast Australia while delayed floods were prevailing in the Amazon, Cerrado, south Africa, India and Japan. Earlier flood timing in the north America and Europe was caused by earlier snowmelt while delayed extreme soil moisture excess and precipitation have jointly led to delayed floods around the monsoon zone, including south Africa, India and Japan. This study provides an insight on the shifting mechanism of flood timing, and supports decisions on the global flood mitigation and the impact from future climate change.

Multivariate assessment and attribution of droughts in Central Asia.

While the method for estimating the Palmer Drought Severity Index (PDSI) is now more closely aligned to key water balance components, a comprehensive assessment for measuring long-term droughts that recognizes meteorological, agro-ecological and hydrological perspectives and their attributions is still lacking. Based on physical approaches linked to potential evapotranspiration (PET), the PDSI in 1965-2014 showed a mixture of drying (42% of the land area) and wetting (58% of the land area) that combined to give a slightly wetting trend (0.0036 per year). Despite the smaller overall trend, there is a switch to a drying trend over the past decade (-0.023 per year). We designed numerical experiments and found that PDSI trend responding to the dramatic increase in air temperature and slight change in precipitation. The variabilities of meteorological and agro-ecological droughts were broadly comparable to various PDSI drought index. Interestingly, the hydrological drought was not completely comparable to the PDSI, which indicates that runoff in arid and semi-arid regions was not generated primarily from precipitation. Instead, fraction of glacierized areas in catchments caused large variations in the observed runoff changes.

Changes in Central Asia's Water Tower: Past, Present and Future.

The Tienshan Mountains, with its status as "water tower", is the main water source and ecological barrier in Central Asia. The rapid warming affected precipitation amounts and fraction as well as the original glacier/snowmelt water processes, thereby affecting the runoff and water storage. The ratio of snowfall to precipitation (S/P) experienced a downward trend, along with a shift from snow to rain. Spatially, the snow cover area in Middle Tienshan Mountains decreased significantly, while that in West Tienshan Mountains increased slightly. Approximately 97.52% of glaciers in the Tienshan Mountains showed a retreating trend, which was especially obvious in the North and East Tienshan Mountains. River runoff responds in a complex way to changes in climate and cryosphere. It appears that catchments with a higher fraction of glacierized area showed mainly increasing runoff trends, while river basins with less or no glacierization exhibited large variations in the observed runoff changes. The total water storage in the Tienshan Mountains also experienced a significant decreasing trend in Middle and East Tienshan Mountains, but a slight decreasing trend in West Tienshan Mountains, totally at an average rate of -3.72 mm/a. In future, water storage levels are expected to show deficits for the next half-century.