Improving our understanding of streamwater age knowledge is critical for revealing the complex hydrological processes in alpine cryosphere catchments. However, few studies on water age have been conducted in alpine cryosphere catchments due to the complicated and inclement environment. In this study, the Buqu catchment, a typical alpine catchment covered by glaciers and permafrost on the central Tibetan Plateau (TP), was selected as the study area. Using the sine-wave ap-proach anda gamma model based on the seasonal cycle of stable isotopes in water, the young water fraction (Fyw) and mean transit time (MTT) of the Buqu catchment outlet and 23 sub-catchments was estimated to comprehensively reveal the potential driving mechanism of water age variability. The streamwater MTT for the entire catchment was 107 days, and 15.1 % of the streamwater was younger than 41 days on average. The estimated water age showed significant spatial heterogeneity with shorter water ages in high-elevation and glacier catchments and longer water ages in low-elevation and non-glacier catchments. Precipitation was the primary driver for spatial variations in water age, while the thickness of the permafrost active layer may function as an intermediate hub to drive water age variability. Mechanically, the thick-ness of the permafrost active layer controls the water ages by modifying the flow direction and length of water flow path. Spatially, this control mechanism is indirectly driven by the elevation gradient. The TDS concentration in streamwater is significantly related to water age, thus revealing a close link between water quality and hydrology. Our findings suggest that cryosphere retreats likely alter water age, thereby slowing water circulation rates and affecting water quality security under global warming. This study provides insights into the evolution of water ages, thereby deepening our understanding of the hydrological processes and guiding the protection of water resources in alpine headwater catchments.

The current water environment carrying capacity assessment method has a single assessment index and does not constrain the scope of assessment. It is not possible to adaptively assess the water environment carrying capacity layer by layer. In order to solve this problem, in this paper. we propose an adaptive assessment method of urban water environment carrying capacity based on water quality target constraints. This method constructs a new evaluation index system for water environment carrying capacity, which takes water resources and environment, water pollution control, and economic carrying capacity as the criteria, and takes water quality status, pollution discharge, technology management. economic development, and social development as the constraint target layer, and takes the total wastewater discharge, industrial water consumption, and urbanization level as the constraint index layer. Two methods of structural entropy weight and mean square error decision are introduced to realize the adaptive joint weight assignment evaluation of the reference layer and the target layer. Through experimental analysis, the assessed area has a good water environment carrying capacity and foundation, and the overall water environment carrying capacity of the study area from 2016 to 2019 was on the rise.

Analysis of environmental significance and hydrochemical characteristics of river water in mountainous regions is vital for ensuring water security. In this study, we collected a total of 164 water samples in the western region of the Altay Mountains, China, in 2021. We used principal component analysis and enrichment factor analysis to examine the chemical properties and spatiotemporal variations of major ions (including F-, Cl-, NO3-, SO42-, Li+, Na+, NH4+, K+, Mg2+, and Ca2+) present in river water, as well as to identify the factors influencing these variations. Additionally, we assessed the suitability of river water for drinking and irrigation purposes based on the total dissolved solids, soluble sodium percentage, sodium adsorption ratio, and total hardness. Results revealed that river water had an alkaline aquatic environment with a mean pH value of 8.00. The mean ion concentration was ranked as follows: Ca2+>SO42->Na+>NO3->Mg2+>K+>Cl->F->NH4+>Li+. Ca2+, SO42-, Na+, and NO3- occupied 83% of the total ion concentration. In addition, compared with other seasons, the spatial variation of the ion concentration in spring was obvious. An analysis of the sources of major ions revealed that these ions originated mainly from carbonate dissolution and silicate weathering. The recharge impact of precipitation and snowmelt merely influenced the concentration of Cl-, NO3-, SO42-, Ca2+, and Na+. Overall, river water was in pristine condition in terms of quality and was suitable for both irrigation and drinking. This study provides a scientific basis for sustainable management of water quality in rivers of the Altay Mountains.

Trace elements (TEs) in water are crucial parameters for assessing water quality. However, detailed studies are limited on TEs in the hydrological system of the Tibetan plateau (TP). Here, we sampled snow, river water, and groundwater in Yulong Snow Mountain (Mt. Yulong) region, southeast TP, in 2016 and analyzed the concentrations of nine TEs (namely Al, Mn, Fe, Cr, Ni, Cu, Zn, As, and Pb). In snow, the average concentrations of Fe, Zn, and Al were >10 mu g/L, whereas other elements, including Cr, Ni, Cu, As, Hg, and Pb, exhibited average concentrations <1 mu g/L. The concentrations of Al, Mn, Fe, Zn, and As were higher in rivers than in snow. According to enrichment factors (EFs), Zn concentration in snow was highly influenced by anthropogenic activities, whereas Mn, Fe, Cr, and As were uninfluenced. River and lake/reservoir water near human settlements were affected by anthropogenic activities. However, groundwater around Mt. Yulong is not contaminated yet. The increasing EFs in Mt. Yulong snowpit are consistent with those of southern TP snowpits, suggesting that the area has been affected by anthropogenic activities both from local emissions and long-distance transport of pollutants from South Asia. A conceptual model was proposed to show TEs in the water cycle. Although water quality is good overall in Mt. Yulong region, threats to the water environment still exit due to increasing anthropogenic activities and climate warming. The accelerated ablation of cryosphere due to climate warming could be a source of TEs in rivers and groundwater, which should be paid attention to in the future. (C) 2020 Elsevier B.V. All rights reserved.

Improving our understanding of streamwater age knowledge is critical for revealing the complex hydrological processes in alpine cryosphere catchments. However, few studies on water age have been conducted in alpine cryosphere catchments due to the complicated and inclement environment. In this study, the Buqu catchment, a typical alpine catchment covered by glaciers and permafrost on the central Tibetan Plateau (TP), was selected as the study area. Using the sine-wave ap-proach anda gamma model based on the seasonal cycle of stable isotopes in water, the young water fraction (Fyw) and mean transit time (MTT) of the Buqu catchment outlet and 23 sub-catchments was estimated to comprehensively reveal the potential driving mechanism of water age variability. The streamwater MTT for the entire catchment was 107 days, and 15.1 % of the streamwater was younger than 41 days on average. The estimated water age showed significant spatial heterogeneity with shorter water ages in high-elevation and glacier catchments and longer water ages in low-elevation and non-glacier catchments. Precipitation was the primary driver for spatial variations in water age, while the thickness of the permafrost active layer may function as an intermediate hub to drive water age variability. Mechanically, the thick-ness of the permafrost active layer controls the water ages by modifying the flow direction and length of water flow path. Spatially, this control mechanism is indirectly driven by the elevation gradient. The TDS concentration in streamwater is significantly related to water age, thus revealing a close link between water quality and hydrology. Our findings suggest that cryosphere retreats likely alter water age, thereby slowing water circulation rates and affecting water quality security under global warming. This study provides insights into the evolution of water ages, thereby deepening our understanding of the hydrological processes and guiding the protection of water resources in alpine headwater catchments.

Managing water is a top social and economic responsibility and is expected to become even more critical as climate change, in addition to other human activities, alters water availability and quality. Robust indicators reflecting the effects of climate change on the US and global water cycles are needed in order to appropriately manage water resources. Here, we describe a suite of seventeen water cycle and management indicators, which are based on synthesis of available datasets. These indicators include average and heavy precipitation, standardized precipitation index, annual, 7-day low and 3-day high streamflow volume, streamflow timing, snow cover, snow water equivalent, groundwater level, lake water temperature, stream water temperature, dissolved oxygen, salinity, Palmer Drought Severity Index, water withdrawals, and water use. We also identify three indicators that could be included in the suite of water cycle and management indicators with some additional, directed work: snowfall, evapotranspiration, and soil moisture. Our conceptual framework focuses on known water cycle changes in addition to potential effects on management and addresses water quantity and quality, as well as water use and related interactions with freshwater ecosystems, societal impacts, and management. Water cycle indicators are organized into three categories: (1) hydrologic processes, (2) water quality processes, and (3) water quality and quantity impacts. Indicators described here are recommended to serve as critical references for periodic climate assessments. As such, these indicators support analyses of the effects of global change on the natural environment, agriculture, energy, and water resources, among other sectors. Additionally, we identify research gaps and needs that can be addressed to advance the development of future indicators.