Abstract Soil moisture (SM) is a key parameter for irrigation monitoring, scheduling, and supporting precision agriculture. In this study, we used Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical data to estimate SM at high spatial resolution (20 m) in the Lower Chenab Canal Command (LCC) area of Punjab, Pakistan. To achieve this, we applied a semiempirical water cloud model (WCM) using both the VV and VH polarizations from SAR data. Additionally, two widely used machine learning (ML) models, random forest (RF) and support vector machines (SVM), were employed to estimate SM at the field scale. To assess model reliability and transferability, reference data from two field sites were split using two approaches: (1) stratified random sampling, with 50% of data from each site used for training and 50% for validation, and (2) spatial splitting, where one site was used solely for training and the other for validation. Results showed that with random splitting, ML models, particularly SVM, outperformed the WCM, with a coefficient of determination (R²) of 0.58, root mean square error (RMSE) of 6.78 Vol.%, and mean absolute error (MAE) of 5.71 Vol.%. Moreover, VV outperformed VH with an RMSE (R 2 ) of 7.37 Vol.% (0.51), compared with 7.69 Vol.% (0.46) when a stratified random split was used. In contrast, the spatial split yielded lower accuracy, as WCM with VH polarization performed best, achieving an R 2 of 0.45 and RMSE (MAE) of 7.82 (6.23) Vol.%. The high-resolution SM estimates offer practical value for optimizing irrigation management, particularly in agricultural areas challenged by limited water availability.

Climate change intensifies extreme hydrological events, river water stable isotopes serve as sensitive recorders of hydrometeorological changes, yet their controlling factors across scales remain unclear. This study characterized long-term isotope variability and assessed hydrometeorological influences at both site and basin scales in the Xiangjiang River Basin. Based on 13 hydrological years (2010–2022) at Changsha station, we integrated field observations (1668 precipitation events and 929 river water samples) with ERA5 reanalysis, isoGSM2 simulations, and GRACE water storage data. Standardized Runoff Index (SRI) classification and Partial Least Squares Path Modeling (PLS-PM) were applied to analyze 5-day interval variations in river water δ2H (Δδ2HR). Major findings include: (1) Basin-scale data exhibited significantly stronger correlations with Δδ2HR than site-scale data, demonstrating that river water integrated upstream basin information rather than merely reflecting local conditions; (2) Δδ2HR showed distinct non-linear responses to precipitation, with a pronounced “threshold effect” whereby rapid isotopic depletion occurred once basin-scale 5-day precipitation exceeded 70 mm; (3) Basin water storage variation integrated the competing effects of precipitation input and evaporative enrichment, explaining both significant isotopic depletion during water surplus periods and enrichment during deficit periods; (4) PLS-PM revealed a clear seasonal shift in controlling factors: precipitation dominated river water isotopic composition during drought-free periods (SRI > − 0.5), whereas evaporation became the primary controlling factor during drought periods (SRI ≤ − 0.5). These results emphasize the necessity of adopting basin-scale perspectives and incorporating non-linear relationships when interpreting river water isotope dynamics. The findings provide critical scientific insights for paleoclimate reconstruction and offer practical recommendations for improving isotope-enabled hydrological models and regional water resource management in monsoon-influenced river basins.

True triaxial compression experiments were conducted on jointed rock with different Joint Roughness Coefficient (JRC, JRC = 4.78, 9.57, 14.74 and 19.47) or inclined angle (α = 30°, 45°, 60° and 90°) firstly. Then, the adaptive transform a Lagrangian solid element to Discrete Element Sphere particles (adaptive Solid to DES) method was employed to realize the true triaxial compression simulation on jointed rock with various JRC and α. The results show that: (1) The maximum equivalent stress and cracks are firstly concentrated at the joint asperities and develop into the rock matrix with increasing axial stress, resulting in joint-matrix coupled fracture mode. (2) The strength and peak strain of the jointed rock show a decreasing (30 ° ≤ α ≤ 60°) then increasing α = 90°) tendency as the α increased. Increasing JRC weaks the influence of α on strength but amplify on peak strain. (3) When the joint strike parallels to intermediate principal stress, the failure mode are matrix shear (α = 30°), matrix shear-joint sliding (α = 45°), joint sliding (α = 60°), to matrix shear failure (α = 90°), respectively. When the joint strike parallels to minor principal stress, the larger stress on the inclined side inhibits the influence of the joint, resulting in all jointed rock matrix shear fracture.

Drought, a multifaceted natural hazard, arises not only from extended periods of below-average precipitation, but also from anthropogenic exploitation of terrestrial water storage (TWS), and is affecting the agriculturally intensive Ganga-Brahmaputra Basin (GBB). Hence this study explores the drought scenario of GBB using a combined drought index which uses both precipitation and GRACE-derived total water storage anomaly (TWSA) as the indicators. Furthermore, the relative contribution of TWSA and precipitation anomaly is envisaged in this research to quantify the dominant contributor of drought in the basin. The results reveal a marked decline in TWSA across all sub-basins, with the Upper Ganga Basin (UGB) and Yamuna-Chambal Basin (YCB) exhibiting the sharpest declines of -2.622 cm/year and − 2.116 cm/year, respectively, largely driven by unsustainable groundwater extraction and climatic variability. In contrast, the Lower Ganga Basin (LGB) and Brahmaputra Basin (BB) experience slower declines in TWSA, at -0.840 cm/year and − 1.065 cm/year, owing to their distinct aquifer characteristics and higher precipitation levels. The Combined Climatologic Deviation Index (CCDI), used to identify the drought scenario of the basins, showed significant parts of YCB and UGB faced the most severe long-duration droughts. Relative importance analysis underscores the dominant role of TWSA in shaping drought severity, with greater influence than precipitation anomalies in UGB and YCB, while LGB and BB have much influence on precipitation. Drought propagation times representing catchment response vary significantly among basins, with UGB and YCB exhibiting rapid response to input precipitation (5–6 months), while LGB shows a slower response (6–7 months). BB, benefiting from higher rainfall, experiences a much shorter propagation time (2–3 months). This study concludes since TWSA is the dominant contributor in drought manifestations for UGB and YCB, their rapid decline has plunged the basin into long term droughts.

The surface freezing process is a crucial and widespread driver of water chemistry dynamics. This study investigates the hydrochemical changes during seasonal freezing in an urban river-irrigated lake system. Results demonstrate that freezing redistributes solutes, with ion concentrations in ice being significantly lower than in underlying water due to exclusion from the ice lattice. Effective segregation coefficients (Keff) and concentration factors (CF) confirm the persistent solute exclusion, which was stronger in the hydrologically quieter lake than in the river. This exclusion is primarily governed by ion-specific properties (e.g., solubility, hydration energy), while ice thickness was a secondary factor. Although the predominant Ca-Cl and Ca-HCO₃ hydrochemical facies remained unchanged, the ionic composition within ice was distinctly altered. Principal component analysis (PCA) revealed that mineral weathering and dissolution control solute dynamics in the river, while agricultural activities significantly influence the relatively enclosed lake. Our findings underscore that the freezing process acts as a key regulator of winter water chemistry, with important implications for water quality and ecological management in seasonally frozen basins globally.

Ground deformation resulting from strong earthquake fault ruptures can cause significant damage, including the collapse of building structures, garnering considerable research attention. (1) In this study, a large-scale physical model test device was implemented to simulate the loading mode of bedrock dislocation under constant gravity. Based on seismic damage analysis, tests were designed to explore key influencing parameters—bedrock fault dip angle, soil properties, and overburden thickness—on a system comprising strong earthquake normal fault rupture, overburden soil, and independent foundation.(2) The progressive failure of the overburden soil was found to be a dynamic evolution process of the internal rupture zone (IRZ) formed by the tension rupture zone (TRZ) and shear rupture zone (SRZ); this failure process could be divided qualitatively into three stages: the rupture incubation stage (Stage I), development stage (Stage II), and completion stage (Stage III). The failure severity of the independent foundation was reasonably assessed. (3) The setback distance was further refined. This research provides a scientific basis for understanding the failure mechanism and determining the setback distance for buildings in bedrock dislocation sites.

Acid activation of bentonite clay is an effective approach for producing porous sorbents and acid catalysts. In this study, the influence of acid treatment on the structure and sorption properties of montmorillonite (MMT) was examined. Natural MMT was treated with hydrochloric and nitric acids of different concentrations under various thermal conditions. The samples were characterized by XRD, SEM, EPMA, low-temperature N₂ adsorption–desorption, and potentiometric titration. Acid activation resulted in the replacement of interlayer cations with protons and partial leaching of Mg²⁺, Fe³⁺, and Al³⁺ from the lattice, leading to an increase in specific surface area from 89 m²/g to 287 m²/g. The uranium sorption capacity increased from 56 µmol/g to 127 µmol/g due to the formation of new sites for sorption. In contrast, strontium and cesium sorption decreased, except for nitric acid treatment, which enhanced Cs⁺ uptake to 310 µmol/g. The Langmuir model provided the best fit to the sorption data, indicating a predominant monolayer chemisorption mechanism. The type and strength of acid determine the structural stability and selectivity of the sorbent. Mild activation, especially with nitric acid, preserves the clay framework and improves its suitability for uranium removal and further modification in environmental remediation applications.