Moderate-size earthquakes, and the presence of water saturated soil in the near surface can trigger the liquefaction geohazard causing buildings to settle / tilt or collapse, damaging bridges, dams, and roads. A number of paleo-seismic research have focused on the Himalayan area as a potential site for liquefaction. The present study site is in the south of the tectonically active Himalayan foothills and lies in earthquake Seismic Zone III. Therefore, the region can experience earthquakes from nearby regions and can potentially damage civil infrastructures due to liquefaction. The objective of this paper is to determine the susceptibility of alluvial soil deposits to liquefaction for seismic hazard and risk mitigation. Liquefaction geohazard study of alluvial deposits was carried out using shear wave velocity (Vs) profiling. Preliminary assessment of the soil is made by building the average shear wave velocity map up to 30 m depth (Vs30) and by constructing the corrected shear wave velocity (V-s1) maps. It was observed from the Vs30 map that a major portion of the studied area lies in Site Class CD and only a small portion lies in Site Class D. Moreover, it is also noticed from the V(s1 )map that a smaller of the area has V(s1 )lower than the upper limit of V-s1(& lowast; )(215 m/s) below which liquefaction may occur. The region showing lower values of V(s1 )is further examined for liquefaction hazard as per the guidelines given by Andrus et al. (2004). Resistance of the soil to liquefaction, stated as cyclic resistance ratio (CRR), and the magnitude of cyclic loading on the soil induced by the earthquake shaking, stated as cyclic stress ratio (CSR) are computed for the area. Several maps of factor of safety (FS) for different depths are prepared by taking the ratio of CSR and CRR. When FS < 1, the soil is considered prone to liquefaction. Furthermore, susceptibility of soil to liquefaction against different peak horizontal ground surface acceleration (PHGSA) and varying depth of water table is also evaluated in terms of factor of safety. It is observed from this study that for lower levels of PHGSA (up to 0.175 g) the soil can be considered safe. However, the soil becomes more vulnerable to liquefaction when PHGSA is above 0.175 g and with rising water table. The comparison of the factor of safety (FS) obtained using the SPT-N method and the Vs-derived approach shows consistent results, with both methods confirming the absence of liquefaction in the studied soil layers.

The Upper Silesian Coal Basin faces ongoing challenges with self-heating in coal waste dumps, a problem that leads to dangerous and unpredictable subsurface fires. This study investigates the thermal dynamics and vegetation response in a coal waste dump, expanding on previous research that links waste temperatures with plant health and distribution. The study area-a small, old coal waste dump located in a highly urbanized area-was subjected to comprehensive environmental monitoring focused on various fire determinants. The findings confirm that coal waste dumps, regardless of size and complexity, experience similar fire determinants, with vegetation colonization progressing in bands starting with pioneer species in less heat-affected areas. As the distance from the fire zone increases, plant density and diversity improve, indicating a recovery in thermally stabilized zones. The study also demonstrates the repeatability of relationships between subsurface temperatures and vegetation status across different coal waste dumps, supporting the use of plants as indicators of underground fires. Elevated subsurface temperatures in thermally active zones lead to clear 'dying' and 'death' zones, where excessive heat damages plant roots, causing die-offs. In contrast, areas with moderate temperatures allow vegetation growth, even in winter, due to favourable root-zone conditions. The study highlights the need for improved monitoring and fire mitigation strategies to address thermal activity in reclaimed sites, especially those with limited historical data. These insights are crucial for preventing similar issues in the future and minimizing the long-term impacts on surrounding communities and ecosystems.

Climate change has led to increased frequency, duration, and severity of meteorological drought (MD) events worldwide, causing significant and irreversible damage to terrestrial ecosystems. Understanding the impact of MD on diverse vegetation types is essential for ecological security and restoration. This study investigated vegetation responses to MD through a drought propagation framework, focusing on the Yangtze River Basin in China, which has been stricken by drought frequently in recent decades. By analyzing propagation characteristics, we assessed the sensitivity and vulnerability of different vegetation types to drought. Using Copula modeling, the occurrence probability of vegetation loss (VL) under varying MD conditions was estimated. Key findings include: (1) The majority of the Yangtze River Basin showed a high rate of MD to VL propagation. (2) Different vegetation types exhibited varied responses: woodlands had relatively low sensitivity and vulnerability, grasslands showed medium sensitivity with high vulnerability, while croplands demonstrated high sensitivity and moderate vulnerability. (3) The risk of extreme VL increased sharply with rising MD intensity. This framework and its findings could provide valuable insights for understanding vegetation responses to drought and inform strategies for managing vegetation loss.

Study region: The study focuses on the Indus River Basin and southern Pakistan, severely affected by flooding in 2022. Study focus: This study assessed how land surface temperature, snow cover, soil moisture, and precipitation contributed to the deluge of 2022. This study mainly investigated MODIS-AIRS land surface temperature, MODIS snow cover (NDSI), SMAP soil moisture, and GPM IMERG precipitation accumulation. Furthermore, different flood visualization and mapping techniques were applied to delineate the flood extent map using Landsat 8-9, Sentinel-2 MSI, and Sentinel-1 SAR data. New hydrological insights for the region: The region experienced some of the most anomalous climatic events in 2022, such as prolonged heatwaves as observed with higher-than-average land surface temperatures and subsequent rapid decline in snow cover extent during the spring, increased soil moisture followed by an abnormal amount of extreme monsoon precipitation in the summer. The upper subbasins experienced more than 8 degrees C in positive temperature anomaly, indicating a warmer climate in spring. Subsequently, the snow cover declined by more than 25 % in the upper subbasins. Further, higher surface soil moisture values (> 0.3 m3/m3) were observed in the basin during the spring due to the rapid snow and ice melt. Furthermore, the basin received more than 200 mm of rainfall compared to the long-term average rainfall of about 98 mm, translating to about 300 % more rainfall than usual in July and August. The analysis helps understand the spatial and temporal variability within the basin and facilitates the understanding of factors and their intricate connections contributing to flooding.

Study region: The Qinghai Lake basin, including China's largest saltwater lake, is located on the Qinghai-Tibetan Plateau (QTP). Study focus: This study focuses on the hydrological changes between the past (1971-2010) and future period (2021-2060) employing the distributed hydrological model in the Qinghai Lake basin. Lake evaporation, lake precipitation, and water level changes were estimated using the simulations driven by corrected GCM data. The impacts of various factors on the lake water levels were meticulously quantified. New hydrological insights: Relative to the historical period, air temperatures are projected to rise by 1.72 degrees C under SSP2-4.5 and by 2.21 degrees C under SSP5-8.5 scenarios, and the future annual precipitation will rise by 34.7 mm in SSP2-4.5 and 44.1 mm in SSP5-8.5 in the next four decades. The ground temperature is projected to show an evident rise in the future period, which thickens the active layer and reduces the frozen depth. The runoff into the lake is a pivotal determinant of future water level changes, especially the runoff from the permafrost degradation region and permafrost region dominates the future water level changes. There will be a continuous rapid increase of water level under SSP5-8.5, while the water level rising will slow down after 2045 in the SSP2-4.5 scenario. This study provides an enhanced comprehension of the climate change impact on QTP lakes.

Lakes are commonly accepted as a sensitive indicator of regional climate change, including the Tibetan Plateau (TP). This study took the Ranwu Lake, located in the southeastern TP, as the research object to investigate the relationship between the lake and regional hydroclimatological regimes. The well-known Budyko framework was utilized to explore the relationship and its causes. The results showed air temperature, evapotranspiration and potential evapotranspiration in the Ranwu Lake Basin generally increased, while precipitation, soil moisture, and glacier area decreased. The Budyko space indicated that the basin experienced an obviously drying phase first, and then a slightly wetting phase. An overall increase in lake area appears inconsistent with the drying phase of the basin climate. The inconsistency is attributable to the significant expansion of proglacial lakes due to glacial melting, possibly driven by the Atlantic Multidecadal Oscillation. Our findings should be helpful for understanding the complicated relationships between lakes and climate, and beneficial to water resources management under changing climates, especially in glacier basins.

Landslides are recognized as major natural geological hazards in the mountainous region, and they are accountable for enormous human causalities, damage to properties, and environmental issues in the Teesta River basin, Sikkim, India. GIS approaches are widely used in landslide susceptibility mapping (LSM) that can help relevant authorities to mitigate landslide risk. The binary logistic regression is applied to estimate the landslide susceptibility zonation (LSZ) in the upper Teesta River basin areas. The landslide inventory data are subdivided into training data sets (70%) for applying algorithms in models and testing data sets (30%) for testing model accuracy. The LSZ mapping is designed after analyzing multicollinearity test of 14 landslide CFs and the result shows that the VIF value is less than 10, and TOL is greater than 0.1, respectively. There is no multicollinearity for the 14 conditioning landslides factors. The upper Teesta River basin is categorized into five groups: very low-to-very high landslide susceptibility zones. The results highlighted that most of the middle and southern parts of the study region are highly prone to landslides compared to the other parts. The susceptibility of landslide in the upper Teesta River basin areas validated by performing the Receiver Operating Characteristics (ROC) curve, which showed an 83% confidence level. The present research demonstrated landslide vulnerability circumstances for the Teesta River basin, Sikkim, an area prone to landslides, emphasizing the need for an effective mitigation and management roadmap.

It is important to comprehend the evolution of drought characteristics and the relationships between different kinds of droughts for effective drought mitigation and early warnings. The study area was the Pearl River Basin, where spatiotemporal changes in the multiscale water balance and soil moisture at various depths were analyzed. The meteorological data used in this study were derived from the China Meteorological Forcing Dataset, while the soil moisture data were obtained from the ECMWF ERA5-Land reanalysis dataset. The Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Soil Moisture Index (SSI) were applied to represent meteorological and agricultural droughts, respectively. By using the run theory for drought event identification, the characteristic values of drought events were analyzed. The correlation between the multiscale SPEI and SSI was examined to represent the propagation time from meteorological drought to agricultural drought. This study indicated that while the western part of the Pearl River Basin experienced a worsening atmospheric moisture deficit and the southern part had intensifying dry conditions for soil moisture, the rest of the basin remained relatively moist and stable. Soil conditions were moister in the deeper soil layers. The durations of agricultural droughts have generally been shorter than those of meteorological droughts over the past 40 years. Within the top three soil layers, the severity, duration, and frequency of drought events progressively increased, increased, and decreased, respectively, as soil depth increased. The propagation time scale from a meteorological drought to a four-layer agricultural drought was typically within 1-5 months. This study advanced existing research by systematically analyzing drought propagation times across soil depths and seasons in the Pearl River Basin. The methodology in this study is applicable to other basins to analyze drought complexities under climate change, contributing to global drought resilience strategies. Understanding the spatiotemporal characteristics of meteorological and agricultural droughts and the propagation time between them can help farmers and agricultural departments predict droughts and take appropriate drought-resistant measures to alleviate the damage of droughts on agricultural production.

River riparian basins play a crucial role in mitigating greenhouse gas (GHG) emissions through carbon sequestration and nitrogen sinks. However, increased ecological stresses led to the release of CO2, CH4 and N2O. This study aimed to investigate how extreme temperatures, water levels, moisture content, land use changes and soil composition influence GHG emissions in the riparian corridor and to recommend mitigation techniques. It was carried out at the Yangtze River Riparian zone, China, using soil column testing. It used soil column testing. The results showed that extreme temperatures caused the highest emissions of CO2 (29-45%), CH4 (24-43%) and N2O (27-33%). This was due to increased soil temperatures and accelerated organic carbon/nitrogen decomposition. Conversely, control and wet-dry cycles absorbed CO2 (1-3%), CH4 (3-10%) and N2O (1-21%) by improving soil aeration, increased oxygen availability, soil structure, stable water table and low temperature change. Grasses in riparian areas also improved carbon sinks. Highest water levels had lowest gas concentrations and emissions due to low oxygen level. Adaptive wet-dry cycles, grass cover and better water table management can restore riparian areas, maintain soil moisture, balance soil carbon/nitrogen levels and mitigate climate change by improving soil quality. Dissolved organic matter fluorescence (DOMFluor) components are essential for soil carbon dynamics, aquatic biome safety, nutrient cycling and ecological balance in riparian zones. The study recommends implementing restoration practices, managing soil moisture, afforestation, regulating temperature and monitoring water tables to mitigate GHG emissions and address climate change. Future policies should focus on promoting resilient land use and ecosystems.

In the mountainous headwaters of the Colorado River episodic dust deposition from adjacent arid and disturbed landscapes darkens snow and accelerates snowmelt, impacting basin hydrology. Patterns and impacts across the heterogenous landscape cannot be inferred from current in situ observations. To fill this gap daily remotely sensed retrievals of radiative forcing and contribution to melt were analyzed over the MODIS period of record (2001-2023) to quantify spatiotemporal impacts of snow darkening. Each season radiative forcing magnitudes were lowest in early spring and intensified as snowmelt progressed, with interannual variability in timing and magnitude of peak impact. Over the full record, radiative forcing was elevated in the first decade relative to the last decade. Snowmelt was accelerated in all years and impacts were most intense in the central to southern headwaters. The spatiotemporal patterns motivate further study to understand controls on variability and related perturbations to snow water resources.