Remote sensing monitoring of glacier area and volume changes in glacier-fed mountainous watershed on the Northern margin of the Qinghai-Tibet Plateau under climate change.

Steady glacier runoff is related to the security and resilience of water resources in meltwater recharge basins, so the status and change of glaciers and their response to climate change in the upper reaches have received widespread concerns. Here, the spatiotemporal characteristics of glacier wastage in the Upper Reaches of Shule River Basin (URSRB) driven by climate change were analyzed based on multi-source and multi-temporal remotely sensed images. Firstly, we extracted multi-temporal glacier outlines from the Landsat time series data using Google Earth Engine (GEE) for seven different periods every approximately 5 years from 1990 to 2020. The spatiotemporal analysis of URSRB glaciers demonstrates a sustained reduction in glacier area from 481.07 ± 24.24 km2 in 1990 to 384.05 ± 22.71 km2 in 2020, corresponding to a glacier shrinkage rate of - 0.67 ± 0.23%/year, characterized by considerable temporal variability. Secondly, multi-temporal DEMs derived from ASTER stereo imagery spanning from 2000 to 2020 were used to compute the glacier surface elevation changes and determine the glacier mass loss. The overall glacier surface elevation change rate was - 0.32 ± 0.14 m/year, equivalent to a mass balance of - 0.28 ± 0.12 m w.e./year. Lastly, to better apprehend the long-term response of URSRB glaciers to climate change, studies on climate change were carried out based on the EAR5-Land reanalysis dataset. The long-term trend of glacier wastage is attributed to the increase in summer temperature, and the negative effects of increased summer temperature on glaciers exceeded the positive effects of increased annual precipitation. In summary, glaciers in the URSRB have experienced a significant area reduction and accelerated mass loss against the backdrop of climatic warming and humidification.

Redistribution effect of irrigation on shallow groundwater recharge source contributions in an arid agricultural region.

Recharge sources such as precipitation, mountain front recharge, mountain block recharge and confined water are the sources usually considered in quantitative studies of groundwater recharge. Changes in recharge processes caused by irrigation practices need to be fully considered for the accurate budgeting and management of water resources. Here, we put forward a conceptual framework for evaluating the shallow groundwater recharge process in arid irrigated agricultural areas using hydrochemical and stable isotope techniques, combined with an assessment of hydrogeological conditions and quantitative models. In general, the recharge effect of atmospheric precipitation on shallow groundwater in arid areas is relatively small. The contributions made by recharge sources in the studied river irrigated area, from greater to smaller, were confined groundwater (46.98 %), river water (45.48 %) and precipitation (7.55 %). The original range in groundwater recharge levels caused by river leakage also appeared to have expanded in response to the establishment of canal irrigation networks. Lateral groundwater flow and confined groundwater were the main recharge sources of shallow groundwater in areas fed by well irrigation and well-/spring-water irrigation (not taking into account any groundwater irrigation leakage). However, had the recharge of shallow groundwater by groundwater irrigation leakage, which reached 19.8-41.1 %, not been counted as contributing to actual groundwater recharge, the recharge contributions made by lateral groundwater flow and confined groundwater to shallow groundwater would have been significantly overestimated. This is because the groundwater recharge process has been modified by the various irrigation measures employed in arid agricultural areas, leading to a redistribution effect in groundwater recharge source contributions. This study provides a new perspective and intuitive data support for the development and utilization of water resources in arid regions.

New double decomposition deep learning methods for river water level forecasting.

Forecasting river water levels or streamflow water levels (SWL) is vital to optimising the practical and sustainable use of available water resources. We propose a new deep learning hybrid model for SWL forecasting using convolutional neural networks (CNN), bi-directional long-short term memory (BiLSTM), and ant colony optimisation (ACO) with a two-phase decomposition approach at the 7-day, 14-day, and 28-day forecast horizons. The newly developed CBILSTM method is coupled with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD) methods to extract the most significant features within predictor variables to build a hybrid CVMD-CBiLSTM model. We integrate three distinct datasets (satellite-derived, climate mode indices, and ground-based meteorological observations) to improve the forecasting capability of the CVMD-CBiLSTM model, applied at nineteen different gauging stations in the Australian Murray River system. This proposed model returns a significantly accurate performance with ~98% of all prediction errors within less than ±0.020 m and a low relative root mean square of ~0.08%, demonstrating its superiority over several benchmark models. The results show that using the new hybrid deep learning algorithm with ACO feature selection can significantly improve the accuracy of forecasted river water levels, and therefore, the method is attractive for adopting remote sensing data to the model ground-based river flow for strategic water savings planning initiatives and dealing with climate change-induced extreme events such as drought events.

Critical role of groundwater discharge in sustaining streamflow in a glaciated alpine watershed, northeastern Tibetan Plateau.

As the hydrologic buffering capacity of glaciers diminishes on climate warming, groundwater stored in the glaciated alpine watersheds becomes an important source of streamflow, quantifying the groundwater contribution to this streamflow is significant for better predictions of the impact of rapidly disappearing glaciers on regional water resources. However, the role of groundwater in sustaining streams remains unclear. Here, we selected the upper Shule River Basin (USRB) on the northeast Tibetan Plateau (NETP) as a case to address this knowledge gap through a comprehensive study of geochemistry and stable isotopes data, the application of an end member mixing model and the baseflow hydrograph separation program (HYSEP). Our results indicate that even though the potential sources of streamflow exhibited distinct monthly differences during December 2012-December 2013, the groundwater was the dominant contributor to streamflow generation in the USRB. The groundwater contributed 45% to 100% of the monthly mean streamflow, and the annual mean value of 70%. By contrast, the glacier-snow meltwater and precipitation only contributed 12% and 18% of the annual discharge. The volume contributed by groundwater was calculated as 9.93 × 108 m3, approximately six times higher than the input of the glacier-snow meltwater (i.e., 1.63 × 108 m3). From 1954 to 2018, the volume of the groundwater discharge to the streamflow in the USRB continuously increased from 4.83 × 108 m3/a (65% of total streamflow) in the 1950s to 10.34 × 108 m3/a (71% of total streamflow) in the 2010s, an increase of 2.14 times. The retreating glacier, as well as increasing precipitation and temperature, were determined to be the main reasons for the increase in groundwater discharge to the streamflow. Our findings suggest that groundwater contribution is more important than was previously thought in the glaciated alpine watersheds on the NETP.

The role of climate change and vegetation greening on the variation of terrestrial evapotranspiration in northwest China's Qilian Mountains.

Terrestrial evapotranspiration (ETa) reflects the complex interactions of climate, vegetation, soil and terrain and is a critical component in water and energy cycles. However, the manner in which climate change and vegetation greening influence ETa remains poorly understood, especially in alpine regions. Drawing on the Global Land Evaporation Amsterdam Model (GLEAM) ETa data, the interannual variability of ETa and its ties to precipitation (P), potential evaporation (ETp) and vegetation (NDVI) were analysed. The Budyko framework was implemented over the period of 1982 to 2015 to quantify the response of ETa to climate change's direct (P and ETp) and indirect (NDVI) impacts. The ETa, P, ETp and NDVI all showed significant increasing trends from 1981 to 2015 with rates of 1.52 mm yr-1, 3.18 mm yr-1, 0.89 mm yr-1 and 4.0 × 10-4 yr-1, respectively. At the regional level, the positive contribution of increases in P and NDVI offset the negative contribution of ETp to the change in ETa (∆ETa). The positive ∆ETa between 1982 and 2001 was strongly linked with the concomitant increase in NDVI. Increases in vegetation contributing to a positive ∆ETa differed among landscape types: for shrub, meadow and steppe they occurred during both periods, for alpine vegetation between 1982 and 2001, and for desert between 2002 and 2015. Climate change directly contributed to a rise in ETa, with P as the dominant factor affecting forested lands during both periods, and alpine vegetation between 2002 and 2015. Moreover, ETp was a dominant factor for the desert between 1982 and 2001, where the variation of P was not significant. The contributions of factors having an impact on ∆ETa are modulated by both the sensitivity of impact factors acting on ETa as well as the magnitudes of factor changes. The greening of vegetation can influence ETa by increasing vegetation transpiration and rainfall interception in forest, brush and meadow landscapes. These findings can help in developing a better understanding of the interaction of ecosystems and hydrology in alpine regions.

Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China.

The relationship between climate and human society has frequently been investigated to ascertain whether climate variability can trigger social crises (e.g., migration and armed conflicts). In the current study, statistical methods (e.g., correlation analysis and Granger Causality Analysis) are used in a systematic analysis of the potential causality of climate variability on migration and armed conflicts. Specifically, the statistical methods are applied to determine the relationships between long-term fine-grained temperature and precipitation data and contemporary social conditions, gleaned from historical documents covering the last two millennia in China's Hexi Corridor. Results found the region's reconstructed temperature to be strongly coupled with precipitation dynamics, i.e., a warming climate was associated with a greater supply of moisture, whereas a cooling period was associated with more frequent drought. A prolonged cold period tended to coincide with societal instability, such as a shift from unification towards fragmentation. In contrast, a prolonged warm period coincided with rapid development, i.e., a shift from separation to unification. The statistical significance of the causality linkages between climate variability, bio-productivity, grain yield, migration and conflict suggests that climate variability is not the direct causative agent of these phenomena, but that climate reduced food production which gradually lead to migration and conflicts. A conceptual causal model developed through this study describes the causative pathway of climate variability impacts on migration and conflicts in the Hexi Corridor. Applied to current conditions, the model suggests that steady and proactive promotion of the nation's economic buffering capacity might best address the uncertainty brought on by a range of potential future climate scenarios and their potential impacts.

[Spatial and temporal variations of hydrological characteristic on the landscape zone scale in alpine cold region].

There are few studies on the hydrological characteristics on the landscape zone scale in alpine cold region at present. This paper aimed to identify the spatial and temporal variations in the origin and composition of the runoff, and to reveal the hydrological characteristics in each zone, based on the isotopic analysis of glacier, snow, frozen soil, groundwater, etc. The results showed that during the wet season, heavy precipitation and high temperature in the Mafengou River basin caused secondary evaporation which led to isotope fractionation effects. Therefore, the isotope values remained high. Temperature effects were significant. During the dry season, the temperature was low. Precipitation was in the solid state during the cold season and the evaporation was weak. Water vapor came from the evaporation of local water bodies. Therefore, less secondary evaporation and water vapor exchange occurred, leading to negative values of delta18O and deltaD. delta18O and deltaD values of precipitation and various water bodies exhibited strong seasonal variations. Precipitation exhibited altitude effects, delta18O = -0. 005 2H - 8. 951, deltaD = -0.018 5H - 34. 873. Other water bodies did not show altitude effects in the wet season and dry season, because the runoff was not only recharged by precipitation, but also influenced by the freezing and thawing process of the glacier, snow and frozen soil. The mutual transformation of precipitation, melt water, surface water and groundwater led to variations in isotopic composition. Therefore, homogenization and evaporation effect are the main control factors of isotope variations.

Origins of groundwater inferred from isotopic patterns of the Badain Jaran Desert, northwestern China.

There are many viewpoints about the sources of groundwater in the Badain Jaran Desert (BJD), such as precipitation and snowmelt from the Qilian Mountains (the upper reaches [UR] of the Heihe River Basin [HRB]) and precipitation from the BJD and the Yabulai Mountains. To understand the source of the groundwater of the BJD and their possible associations with nearby bodies of water, we analyzed variations of stable isotope ratios (δD and δ(18) O) and the deuterium excess (d-excess) of groundwater and precipitation in the BJD, of groundwater, precipitation, river and spring water in the UR, and of groundwater and river water in the middle and lower reaches (MR and LR) of the HRB. In addition, the climatic condition under which the groundwater was formed in the BJD was also discussed. We found obvious differences in δD, δ(18) O, and d-excess among groundwater in the BJD, nearby water bodies and the HRB. The groundwater δD-δ(18) O equation for the BJD was δD = 4.509δ(18) O-30.620, with a slope and intercept similar to that of nearby areas (4.856 and -29.574), indicating a strong evaporation effect in the BJD and its surrounding areas. The equation's slope of the BJD was significantly lower than those of HRB groundwater (6.634), HRB river water (6.202), precipitation in the BJD and Youqi (7.841), and the UR of the HRB (7.839). The d-excess (-17.5‰) of the BJD was significantly lower than those of nearby groundwater (-7.4‰), HRB groundwater (12.1‰), precipitation in the BJD (5.7‰) and in the UR of the HRB (15.2‰), and HRB river water (14.4‰). The spatial patterns of δ(18) O and d-excess values in the BJD suggest mixing and exchange of groundwater between the BJD and neighboring regions, but no hydraulic relationship between the BJD groundwater and water from more distant regions except Outer Mongolia, which is north of the BJD. Moreover, we conclude that there is little precipitation recharge to groundwater because of the obvious d-excess difference between groundwater and local precipitation, low precipitation, and high evaporation rates. The abnormally negative d-excess values in groundwater of the BJD indicate that this water was formed in the past under higher relative humidity and lower temperatures than modern values.