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.

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.

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.

Rapid socio-economic development has precipitated substantial transformations in land use and land cover (LUCC) within the Yanhe River basin, significantly impacting production dynamics, confluence mechanisms, and the basin's runoff response processes. To elucidate the runoff response patterns under varying land use/land cover change conditions, this study analyzed the land use change characteristics from 1980 to 2020. Employed the SWAT (Soil and Water Assessment Tool) model, and simulated the precipitation-runoff dynamics under five distinct land use scenarios to scrutinize the basin's runoff response to varying land use conditions. The results demonstrated the applicability of the SWAT model to the Yanhe River basin, with R-2 and Ens values for monthly runoff at two hydrological stations exceeding 0.6 during both calibration and validation periods. Between 1980 and 2020, the area of farmland decreased by 27.96%, whereas the areas of woodland and grassland by 36.59% and 16.2%, respectively. Scenario analysis revealed that the primary contributors to the increased runoff in the study area, in descending order, were grassland, farmland, and woodland. The results indicated that converting farmland to woodland would reduce the runoff depth by 0.26 mm, while converting farmland to grassland would increase the runoff depth by 0.39 mm in the watershed. The conversions exhibited pronounced seasonal effects, with varying degrees of runoff depth changes observed across different seasons. The contribution order of different hydrological years to runoff depth change rates was median flow year > low flow year > high flow year. Land use conversion, particularly among farmland, grassland, and woodland, exerts diversified impacts on runoff depth across different water periods.

Major earthquakes in mountainous areas usually exert negative impacts on vegetation cover and growth due the numerous coseismic landslides. However, understanding of the duration of these impacts and spatiotemporal dynamics of vegetation recovery dominated by environmental factors remains limited. The present study aimed to investigate the spatiotemporal dynamics of natural vegetation restoration and associated mechanisms in a mountainous basin in southwestern China after the 2008 Wenchuan Ms 8.0 earthquake. The results showed that the normalized difference vegetation index (NDVI) substantially decreased from 0.70 to 0.47 after the earthquake and then gradually increased at an average rate of 0.020 yr(- 1). By 2023, vegetation had been restored to its pre-earthquake levels in 84.9% of the total area. And 15.1% of the land remains unrecovered, with 11.7% covered by landslide slump mass. Approximately 4.16% of the entire basin is projected to recover in the future (theta(slope) > 0, H > 0.5) over a seven-year period. Elevation was the most crucial factor influencing both the damage and recovery of vegetation in the basin, followed by landslide slump mass and soil type. The overall vegetation recovery potential is limited, with an average vegetation restoration potential index (VRPI) of 0.21 in 2023. Notably, 11.2% of the basin exhibited a VRPI > 0.4, mainly situated in the northernmost part, characterized by high altitude (> 3000 m), carbonate-cinnamon soil, and dense distribution of landslide slump mass. The results indicate that natural vegetation has a robust capacity for recovery, albeit hindered by active landslides and fragile high-altitude habitats, where human intervention should be implemented. The results provide valuable information to guide future vegetation restoration planning and layout in Wenchuan earthquake-stricken areas.

Flash floods are one of the most dangerous hydrometeorological events in the world. The current study investigates flash floods on the northern Black Sea Coast. The data about stochastic and relatively stable factors of flash flood formation (such as hydrological, meteorological, lithological, geomorphological, and anthropogenic parameters) were collected for 22 events. The main trigger of flash floods is heavy rainfall of high intensity in the region but in some cases flash flood occurrence is connected with combinations of several non-critical factors. The small watershed area (<351 km(2)) of river basins experiencing flash floods promotes very rapid flow concentration. Analysis of extreme precipitation demonstrates significant increasing trends in river basins on the Crimean Peninsula and decreasing a maximum precipitation amount in 5 days (r5d) and 1 day (r1d) in river basins in the Caucasus Black Sea Coast in the 21st century as determined by processing of Integrated Multi-satellite Retrievals for Global precipitation measurement (IMEGR) satellite data. At the same time land network data indicates increasing r5d at the Anapa and r1d at the Tuapse meteorological stations in 1961-2020. More frequent occurrence of flash floods has been suggested in the area due to statistical analysis of the longest precipitation ranges. The main reason for significant social and economic damage is uncontrolled human activity in flooded areas on the northern Black Sea Coast. (c) 2024 International Research and Training Centre on Erosion and Sedimentation. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY- NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Covered sinkhole, due to its hidden, uncertain, and sudden characteristics, often becomes a key and difficult issue in the prevention and control of karst geological disasters. This paper takes the sinkhole in Yaoshan Huamu Farm, Guilin City as an engineering case, and uses field investigation, indoor and outdoor experiments, and theoretical analysis to systematically analyze the main patterns, influencing factors, and evolution laws of sinkhole. The results show that: (1) High-density resistivity tests show that there are many significant low-resistance anomalies at different locations and depths in the study area, indicating that karst fissures are developed in the study area. This is the basic condition for the occurrence of sinkhole. (2) Drilling results show that the groundwater level in the study area is shallow and groundwater is abundant. Groundwater changes the state and strength of the soil, or dissolves the mineral components of the soil layer and dissolves and transports the soil particle aggregates through subsurface erosion and seepage. Therefore, groundwater destroys the soil structure, resulting in the formation of soil caves or sinkholes. (3) Rainfall monitoring shows that the rainy season from May to July each year provides abundant groundwater for the karst area and changes the physical and mechanical properties of the rock and soil mass; while the small rainfall peak around November may trigger the occurrence of sinkhole through mechanisms such as groundwater level fluctuations and enhanced seepage. (4) The vibrations caused by long-term pumping irrigation, surface water leakage, and planting activities in the study area provide important external dynamic conditions for sinkhole. This study can provide theoretical basis and technical support for the prevention and control of collapse disasters in karst areas.

In recent years, frequent flood disasters have posed significant threats to human life and property. From 28 July to 1 August 2023, a basin-wide extreme flood occurred in the Haihe River Basin (23.7 flood). The Gravity Recovery and Climate Experiment satellite can effectively detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA) and has been widely used in flood disaster monitoring. However, flood events usually occur on a submonthly scale. This study first utilizes near-real-time precipitation data to illustrate the evolution of the 23.7 extreme flood. We then reconstruct daily TWSA to improve the issues of coarse temporal resolution and data latency and further calculate wetness index (WI) to explore its flood warning. In addition, we analyze soil moisture storage anomalies to provide a comprehensive understanding of flood mechanisms. The study also compares the 2023 floods to a severe flood event in 2021. Results indicate that reconstructed daily TWSA increases by 143.43 mm in 6 days during the 23.7 flood, highlighting the high sensitivity of our approach to extreme events. Moreover, compared to daily runoff data, the WI consistently exceeds warning thresholds 2-3 days in advance, demonstrating the flood warning capability. The flood event 2021 is characterized by long duration and large precipitation extremes, whereas the 2023 flood affects a wider area. This study provides a reference for using daily TWSA to monitor short-term flood events and evaluate the flood warning potential of WI, aiming to enhance near-real-time flood monitoring and support flood prevention and damage mitigation efforts.