Study region: Urumqi River headwater region in eastern Tianshan, central Asia. Study focus: Climate change is anticipated to accelerate glacier shrinkage and alter hydrological conditions, causing variations in the runoff patterns in the catchment and significantly threatening the regional water resources. However, few models exhibit adequate performance to simulate both surface alterations and glacier/snow runoff. Therefore, this study combined the glacier module with the Soil and Water Assessment Tool (SWAT) model to estimate the effect of climate change on the streamflow in the Urumqi River headwater region. The Urumqi River Headwater region is representative because of its long data series, viatal location, and local water availability, and it contains the longest-observed reference glacier (Urumqi Glacier No.1) in China, which spans the period from 1958 to the present. New hydrological insights for the region: The SWAT model performed satisfactorily for both calibration (1983-2005) and validation (2006-2016) periods with a Nash-Sutcliffe efficiency (NSE) greater than 0.80. The water balance analysis suggested that the snow/glacier melt contributed approximately 25% to the water yield. At the end of the 21st century, the temperature would increase by 2.4-3.8 degrees C while the precipitation would decrease by 1-2% under two future scenarios (ssp245 and ssp585). Thus, a 34-36% reduction in streamflow was projected due to above climate change impacts. This information would contribute to the development of adaptation strategies for sustainable water resource management.

There is 78 % permafrost and seasonal frozen soil in the Yangtze River's Source Region (SRYR), which is situated in the middle of the Qinghai-Xizang Plateau. Three distinct scenarios were developed in the Soil and Water Assessment Tool (SWAT) to model the effects of land cover change (LCC) on various water balance components. Discharge and percolation of groundwater have decreased by mid-December. This demonstrates the seasonal contributions of subsurface water, which diminish when soil freezes. During winter, when surface water inputs are low, groundwater storage becomes even more critical to ensure water supply due to this periodic trend. An impermeable layer underneath the active layer thickness decreases GWQ and PERC in LCC + permafrost scenario. The water transport and storage phase reached a critical point in August when precipitation, permafrost thawing, and snowmelt caused LATQ to surge. To prevent waterlogging and save water for dry periods, it is necessary to control this peak flow phase. Hydrological processes, permafrost dynamics, and land cover changes in the SRYR are difficult, according to the data. These interactions enhance water circulation throughout the year, recharge of groundwater supplies, surface runoff, and lateral flow. For the region's water resource management to be effective in sustaining ecohydrology, ensuring appropriate water storage, and alleviating freshwater scarcity, these dynamics must be considered.

Flash floods represent a significant threat, triggering severe natural disasters and leading to extensive damage to properties and infrastructure, which in turn results in the loss of lives and significant economic damages. In this study, a comprehensive statistical approach was applied to future flood predictions in the coastal basin of North Al-Abatinah, Oman. In this context, the initial step involves analyzing eighteen General Circulation Models (GCMs) to identify the most suitable one. Subsequently, we assessed four CMIP6 scenarios for future rainfall analysis. Next, different Machine Learning (ML) algorithms were employed through H2O-AutoML to identify the best model for downscaling future rainfall predictions. Forty distribution functions were then fitted to the future daily rainfall, and the best-fit model was selected to project future Intensity-Duration-Frequency (IDF) curves. Finally, the Soil and Water Assessment Tool (SWAT) model was utilized with sub-daily time steps to make accurate flash flood predictions in the study area. The findings reveal that IITM-ESM is the most effective among GCM models. Additionally, the application of stacked ensemble ML model proved to be the most reliable in downscaling future rainfall. Furthermore, this study highlighted that floods entering urbanized areas could reach 20.33 and 20.70 m(3)/s under pessimistic scenarios during rainfall events with 100 and 200-year return periods, respectively. This hierarchical comprehensive approach provides reliable results by utilizing the most effective model at each step, offering in-depth insight into future flash flood prediction.

Climate change and rapid socioeconomic development have exacerbated the damage caused by hydrological droughts. To ensure effective drought defense and infrastructure development, it is essential to investigate variations in hydrological droughts. The primary objective of this study is to reconstruct the natural streamflow by using Soil and Water Assessment Tool (SWAT) hydrological modeling. The hydrological drought at different time scales (1, 3, 6, and 12 months) were measured using the streamflow drought index (SDI). The statistical parameters, including Nash-Sutcliffe Efficiency and the Coefficient of Determination, which yielded values of 0.84 and 0.82 during the calibration period and 0.78 and 0.76 during the validation period, respectively, showed a satisfactory SWAT model performance. Additionally, the Pettit test was used to identify a change point in streamflow within the 1991-2015 timeframe, leading to the division of the study period into two distinct phases: an undisturbed period (1991-1998) and a disturbed period (1999-2015). The SDI index-based analysis revealed 9.39% moderate drought and 3.13% severe drought during the undisturbed period, while 11.76% moderate drought and 7.35% severe drought may happen due to the human influences that occurred in the disturbed period. These findings enhance the understanding of the hydrological drought variations in the Soan River basin for optimizing the water resources management system and effectively preventing and mitigating drought-related damages.

The Yangtze River Source Region (YaRSR) is located in the third polar region, the most threatened zone by global warming after the Arctic. Permafrost covers eighty percent of the total area of YaRSR, while the rest is seasonally frozen ground. Due to a significant rise in air temperature, degradation of the permafrost could occur. Permafrost coverage in a river basin greatly controls its hydrology. This study focuses on hydrological modeling in this permafrost environment using the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated (1985-2000) and validated (2001-2015) on a daily time step. The results were also compared on a monthly time scale. An impermeable layer was introduced within the SWAT model to represent the permafrost conditions. The streamflow is strongly dependent on the seasonal variation of precipitation and temperature, and the rising limb of the hydrograph shows the melting of snow, the contribution of soil water, and thawing of permafrost during the spring-summer season. The permafrost layer well restricted the deep percolation of water. During the spring season, streamflow mainly consists of surface runoff because of the frozen soils. Permafrost and frozen ground thawing lead to an increase in the contribution of groundwater flow to streamflow. Ultimately, the frozen ground depletes as the temperature gets close to the freezing point. This study also describes the SWAT model appli-cation to better analyze and understand the hydrology of the permafrost/frozen ground with limited data availability.