Due to climate change the drop in spring-water discharge poses a serious issue in the Himalayan region, especially in the higher of Himachal Pradesh. This study used different climatic factors along with long-term rainfall data to understand the decreasing trend in spring-water discharge. It was determined which climate parameter was most closely correlated with spring discharge volumes using a general as well as partial correlation plot. Based on 40 years (1981-2021) of daily average rainfall data, a rainfall-runoff model was utilised to predict and assess trends in spring-water discharge using the MIKE 11 NAM hydrological model. The model's effectiveness was effectively proved by the validation results (NSE = 0.79, R2 = 0.944, RMSE = 0.23, PBIAS = 32%). Model calibration and simulation revealed that both observed and simulated spring-water runoff decreased by almost 29%, within the past 40 years. Consequently, reduced spring-water discharge is made sensitive to the hydrological (groundwater stress, base flow, and stream water flow) and environmental entities (drinking water, evaporation, soil moisture, and evapotranspiration). This study will help researchers and policymakers to think and work on the spring disappearance and water security issues in the Himalayan region.

Rainfall can alter the hydrothermal state of permafrost, subsequently affecting organic carbon decomposition and CO2 transport. However, the mechanisms by which rainfall influences organic carbon decomposition and carbon dioxide transport processes in permafrost remain unclear. In this study, a coupled permafrost water-heatvapor-carbon model, based on the surface energy-water balance theory, is employed to explore the effects of increased precipitation on permafrost moisture, temperature, organic carbon decomposition, and carbon dioxide transport through numerical simulations. The results are as follows: (1) with increased rainfall, surface latent heat flux rises while surface sensible heat flux declines, leading to a reduction in surface heat flux. The annual mean surface heat fluxes for the three precipitation conditions of no change in precipitation (zP = 0 mm), 50 mm increase in precipitation (zP = 50 mm) and 100 mm increase in precipitation (zP = 100 mm) are -0.1 W/m2, -0.2 W/m2 and -0.4 W/m2 respectively; and (2) as rainfall increases, soil moisture content increases significantly, but the impact of rainfall on soil moisture content diminishes with increasing soil depth; and (3) increased rainfall results in a decrease in soil carbon fluxes, soil organic matter decomposition rates, and CO2 concentrations. Compared to the case of constant precipitation, the surface carbon fluxes decreased by 0.04 mu mol center dot m-2s-1 and 0.08 mu mol center dot m-2s-1 under zP = 50 mm and zP = 100 mm, respectively. Additionally, the decomposition rate of soil organic matter at 10 cm depth decreased by 3.2 E-8 mol center dot m-2s-1 and 6.3 E-8 mol center dot m-2s-1, respectively, while the soil carbon concentration decreased by 3 mu mol/mol and 5 mu mol/mol, respectively.

Seasonally frozen ground (SFG) is a significant component of the cryosphere, and its extent is gradually increasing due to climate change. The hydrological influence of SFG is complex and varies under different climatic and physiographic conditions. The summer rainfall dominant climate pattern in Qinghai Lake Basin (QLB) leads to a significantly different seasonal freeze-thaw process and groundwater flow compared to regions with winter snowfall dominated precipitation. The seasonal hydrological processes in QLB are not fully understood due to the lack of soil temperature and groundwater observation data. A coupled surface and subsurface thermal hydrology model was applied to simulate the freeze-thaw process of SFG and groundwater flow in the QLB. The results indicate that SFG begins to freeze in early November, reaches a maximum freezing depth of approximately 2 meters in late March, and thaws completely by June. This freeze-thaw process is primarily governed by the daily air temperature variations. During the early rainy season from April to June, the remaining SFG in deep soil hinders the majority of rainwater infiltration, resulting in a two-month delay in the peak of groundwater discharge compared to scenario with no SFG present. Colder conditions intensify this effect, delaying peak discharge by 3 months, whereas warmer conditions reduce the lag to 1 month. The ice saturation distribution along the hillslope is affected by topography, with a 10 cm deeper ice saturation distribution and 3 days delay of groundwater discharge in the steep case compared to the flat case. These findings highlight the importance of the freeze-thaw process of SFG on hydrological processes in regions dominated by summer rainfall, providing valuable insights into the hydro-ecological response. Enhanced understanding of these dynamics may improve water resource management strategies and support future research into climate-hydrology interactions in SFG-dominated landscapes.

Rock-ice avalanches have frequently occurred in the Eastern Himalayan Syntaxis region due to climate change and active tectonic movements. These events commonly trigger catastrophic geohazard chains, including debris flows, river blockages, and floods. This study focuses on the Zelongnong Basin, analyzing the geomorphic and dynamic characteristics of high-altitude disasters. The basin exhibits typical vertical zonation, with disaster sources initiating at elevations exceeding 4000 m and runout distances reaching up to 10 km. The disaster chain movement involves complex dynamic effects, including impact disintegration, soil-rock mixture arching, dynamic erosion, and debris deposition, enhancing understanding of the flow behavior and dynamic characteristics of rock-ice avalanches. The presence of ice significantly increases mobility due to lubrication and frictional melting. In the disaster event of September 10, 2020, the maximum flow velocity and thickness reached 40 m/s and 43 m, respectively. Furthermore, continuous deformation of the Zelongnong glacier moraine was observed, with maximum cumulative deformations of 44.68 m in the distance direction and 25.96 m in the azimuth direction from March 25, 2022, to August 25, 2022. In the future, the risk of rock-ice avalanches in the Eastern Himalayan Syntaxis region will remain extremely high, necessitating a focus on early warning and risk mitigation strategies for such basin disasters.

In the context of global research in snow-affected regions, research in the Australian Alps has been steadily catching up to the more established research environments in other countries. One area that holds immense potential for growth is hydrological modelling. Future hydrological modelling could be used to support a range of management and planning issues, such as to better characterise the contribution of the Australian Alps to flows in the agriculturally important Murray-Darling Basin despite its seemingly small footprint. The lack of recent hydrological modelling work in the Australian Alps has catalysed this review, with the aim to summarise the current state and to provide future directions for hydrological modelling, based on advances in knowledge of the Australian Alps from adjacent disciplines and global developments in the field of hydrologic modelling. Future directions proffered here include moving beyond the previously applied conceptual models to more physically based models, supported by an increase in data collection in the region, and modelling efforts that consider non-stationarity of hydrological response, especially that resulting from climate change.

Background The bacterial mechanisms responsible for hydrogen peroxide (H2O2) scavenging have been well-reported, yet little is known about how bacteria isolated from cold-environments respond to H2O2 stress. Therefore, we investigated the transcriptional profiling of the Planomicrobium strain AX6 strain isolated from the cold-desert ecosystem in the Qaidam Basin, Qinghai-Tibet Plateau, China, in response to H2O2 stress aiming to uncover the molecular mechanisms associated with H2O2 scavenging potential. Methods We investigated the H2O2-scavenging potential of the bacterial Planomicrobium strain AX6 isolated from the cold-desert ecosystem in the Qaidam Basin, Qinghai-Tibet Plateau, China. Furthermore, we used high-throughput RNA-sequencing to unravel the molecular aspects associated with the H2O2 scavenging potential of the Planomicrobium strain AX6 isolate. Results In total, 3,427 differentially expressed genes (DEGs) were identified in Planomicrobium strain AX6 isolate in response to 4 h of H2O2 (1.5 mM) exposure. Besides, Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses revealed the down- and/or up-regulated pathways following H2O2 treatment. Our study not only identified the H2O2 scavenging capability of the strain nevertheless also a range of mechanisms to cope with the toxic effect of H2O2 through genes involved in oxidative stress response. Compared to control, several genes coding for antioxidant proteins, including glutathione peroxidase (GSH-Px), Coproporphyrinogen III oxidase, and superoxide dismutase (SOD), were relatively up-regulated in Planomicrobium strain AX6, when exposed to H2O2. Conclusions Overall, the results suggest that the up-regulated genes responsible for antioxidant defense pathways serve as essential regulatory mechanisms for removing H2O2 in Planomicrobium strain AX6. The DEGs identified here could provide a competitive advantage for the existence of Planomicrobium strain AX6 in H2O2-polluted environments.

Quantifying the impact of climate change on hydrologic features is essential for the scientific planning, management and sustainable use of water resources in Northwest China. Based on hydrometeorological data and glacier inventory data, the Spatial Processes in Hydrology (SPHY) model was used to simulate the changes of hydrologic processes in the Upper Shule River (USR) from 1971 to 2020, and variations of runoff and runoff components were quantitatively analyzed using the simulations and observations. The results showed that the glacier area has decreased by 21.8% with a reduction rate of 2.06 km(2)/a. Significant increasing trends in rainfall runoff, glacier runoff (GR) and baseflow indicate there has been a consistent increase in total runoff due to increasing rainfall and glacier melting. The baseflow has made the largest contribution to total runoff, followed by GR, rainfall runoff and snow runoff, with mean annual contributions of 38%, 28%, 18% and 16%, respectively. The annual contribution of glacier and snow runoff to the total runoff shows a decreasing trend with decreasing glacier area and increasing temperature. Any increase of total runoff in the future will depend on an increase of rainfall, which will exacerbate the impact of drought and flood disasters.

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.

Absorbing aerosols and their impact on the Indian monsoon system is highly complex and demands more scientific understanding. Our study using a chemistry-coupled regional climate model (RegCM 4.5) with idealized experiments observed that natural and anthropogenic absorbing aerosols (i.e., dust and carbonaceous aerosols) reduce monsoon precipitation in a seasonal time scale. More than 1 mm day(-1) decline in mean summertime rainfall was observed over parts of the central Indian region and Indo-Gangetic plane for dust aerosol. A substantial reduction in the land-sea pressure gradient and lower tropospheric moisture distribution were found to control the observed modulation in rainfall. Near-surface wind circulation responded distinctly to natural (dust) and anthropogenic (carbonaceous) aerosols. The dust forcing weakened the monsoon trough by creating an anomalous anticyclonic circulation. The Northern Arabian Sea acted as a moisture source for the carbonaceous aerosol forcing. Intraseasonal rainfall over central India appeared to have a sharp reduction for dust forcing during early June, with a moderate increase for carbonaceous aerosols. Such quantification is essential for understanding the impact of aerosol forcing on regional climate change and the water cycle and has implications for emissions management and mitigation policies.

The size of snow grains is an important parameter in cryosphere studies. It is the main parameter affecting snow albedo and can have a feedback effect on regional climate change, the water cycle and ecological security. Larger snow grains increase the likelihood of light absorption and are important for passive microwave remote sensing, snow physics and hydrological modelling. Snow models would benefit from more observations of surface grain size. This paper uses an asymptotic radiative transfer model (ART model) based on MOD09GA ground reflectance data. A simulation of snow grain size (SGS) in northeast China from 2001 to 2019 was carried out using a two-channel algorithm. We verified the accuracy of the inversion results by using ground-based observations to obtain stratified snow grain sizes at 48 collection sites in northeastern China. Furthermore, we analysed the spatial and temporal trends of snow grain size in Northeastern China. The results show that the ART model has good accuracy in inverting snow grain size, with an RMSD of 65 mu m, which showed a non-significant increasing trend from 2001 to 2019 in northeast China. The annual average SGS distribution ranged from 430.83 to 452.38 mu m in northeast China, 2001-2019. The mean value was 441.78 mu m, with an annual increase of 0.26 mu m/a, showing a non-significant increasing trend and a coefficient of variation of 0.014. The simulations show that there is also intermonth variation in SGS, with December having the largest snow grain size with a mean value of 453.92 mu m, followed by January and February with 450.77 mu m and 417.78 mu m, respectively. The overall spatial distribution of SGS in the northeastern region shows the characteristics of being high in the north and low in the south, with values ranging from 380.248 mu m to 497.141 mu m. Overall, we clarified the size and distribution of snow grains over a long time series in the northeast. The results are key to an accurate evaluation of their effect on snow-ice albedo and their radiative forcing effect.