Search Results (1,754)

Extreme hydrological events fundamentally alter sediment transport dynamics across grain, reach, and watershed scales, rendering classical equilibrium-based transport formulations inadequate. This review synthesizes recent advances in multiscale sediment transport modeling under highly unsteady and high-magnitude forcing conditions. At the grain scale, particle-resolved simulations demonstrate that sediment entrainment is governed by turbulence intermittency and transient force exceedance rather than mean bed shear stress thresholds, particularly when the hydrograph rise timescale (T_h) becomes comparable to particle response times (T_p). At the reach scale, non-equilibrium transport emerges when the unsteadiness ratio T_h/T_a∼O(1), where T_a is the sediment adaptation timescale representing the time required for sediment flux to adjust toward transport capacity. Under these conditions, pronounced hysteresis between discharge and sediment flux is observed, requiring relaxation-based transport formulations instead of instantaneous equilibrium laws. At the watershed scale, the sediment delivery ratio (SDR), defined as the ratio of sediment yield at the basin outlet to total hillslope erosion, becomes highly time-dependent. Extreme precipitation events can activate hillslope-channel connectivity, increasing SDR by orders of magnitude relative to baseline conditions. A unified dimensionless scaling framework is presented based on mobility intensity (θ/θ_c, where θ is the Shields parameter and θ_c is its critical value for incipient motion), unsteadiness ratio (T_h/T_a), and morphodynamic coupling (T_f/T_m, where T_f is the hydraulic advection timescale and T_m is the morphodynamic adjustment timescale). This framework enables classification of sediment transport regimes ranging from quasi-equilibrium to cascade-dominated states. The synthesis demonstrates that predictive uncertainty increases nonlinearly across scales due to timescale compression, threshold activation, and feedback between flow hydraulics and evolving morphology. Recent developments in hybrid physics-AI approaches show promise in improving predictive capability by enabling dynamic transport closures, surrogate modeling of computationally expensive microscale processes, and data assimilation for real-time forecasting. However, these approaches remain limited by extrapolation uncertainty and the need to enforce physical constraints. Overall, this review concludes that regime-aware multiscale coupling, combined with uncertainty quantification and adaptive modeling strategies, is essential for robust sediment hazard prediction and climate-resilient infrastructure design under intensifying hydrological extremes. Full article

Mountain flood susceptibility in complex mountainous basins is strongly influenced by terrain–climate interactions; however, the linkage between spatial susceptibility patterns and hydrological processes remains poorly understood. This study proposes a process-oriented framework that explicitly links flood susceptibility patterns with hydrological processes, moving beyond conventional approaches that rely on independent model integration. The Baishuijiang River Basin, located in Wenxian County, southern Gansu Province, China, is selected as a representative mountainous watershed for this analysis. The specific conclusions are as follows: (1) Flood susceptibility was mapped using a Particle Swarm Optimization (PSO)-enhanced Maximum Entropy (MaxEnt) model based on multi-source environmental variables, including climatic, terrain, soil, land cover, and vegetation factors. The model achieved high predictive accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.912), identifying precipitation of the driest month (bio14), elevation, and land use as dominant controlling factors. Medium-to-high-susceptibility areas account for approximately 22% of the basin and are mainly distributed along river valleys and flow convergence areas. These patterns are strongly associated with reduced infiltration capacity under dry antecedent conditions and enhanced flow concentration in steep terrain, and they exhibit clear nonlinear responses and threshold effects. (2) Hydrological simulations using Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) show good agreement with observed runoff (Nash–Sutcliffe Efficiency (NSE) = 0.74−0.85). Sensitivity analysis indicates that runoff dynamics are primarily controlled by the Curve Number (CN), recession constant, and ratio to peak, corresponding to infiltration capacity, recession processes, and peak discharge amplification. The spatial consistency between high-susceptibility areas and areas of strong runoff response demonstrates that susceptibility patterns can be physically explained through hydrological processes, providing a process-based interpretation rather than a purely statistical prediction. (3) Future projections indicate that medium–high-susceptibility areas remain generally stable but show a gradual expansion (+5.2% ± 0.8%) and increasing concentration along river corridors under climate change scenarios. This reflects intensified precipitation variability and enhanced runoff concentration processes, suggesting a climate-driven amplification of flood risk in hydrologically connected areas. Overall, this study goes beyond conventional susceptibility assessment by establishing a physically interpretable framework that provides a consistent linkage between environmental controls, susceptibility patterns, and hydrological responses. The proposed approach is transferable to similar mountainous basins with strong terrain–climate interactions, although uncertainties related to data limitations and single-basin application remain and require further investigation. Full article

Aquatic ecosystems worldwide are increasingly threatened by invasive species, with water hyacinth [Eichhornia crassipes (Mart.) Solms] being among the most destructive aquatic weeds. Despite numerous regional studies, a global assessment integrating climatic and hydrological drivers remains lacking. Here, we assessed current and future invasion risks across 55,945 freshwater lakes using the maximum entropy (MaxEnt) model. Climatic variables and key aquatic parameters, including biological oxygen demand (BOD), water depth, and discharge, were incorporated under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). Annual mean temperature, annual precipitation, and BOD were the strongest predictors of habitat suitability. Under current conditions, 5524 lakes, primarily in tropical and subtropical regions, were identified as being suitable habitats, with medium-sized lakes exhibiting the highest proportional suitability (16.54%). Although small lakes were most frequently classified as suitable due to their abundance, larger lakes showed higher suitability intensity. Future projections indicated marked habitat expansion, especially under SSP5-8.5, with suitable lake surface area increasing to 18.12% by 2061–2080. Moreover, 543 currently unsuitable lakes, including Lake Erie, Lake Huron, and Lake Ontario, were projected to face elevated invasion risk, particularly in Africa, South Asia, Southeast Asia, and North America. This global, lake-specific assessment supports early warning, targeted management, and climate-responsive policy planning. Full article

Environmental loading is a major driver of nonlinear GNSS vertical displacements, yet its spatiotemporal heterogeneity remains insufficiently understood in regions with complex topography. In this study, we investigate the environmental loading effects on GNSS vertical motions across Southwest China using observations from a network of 66 stations. Singular Spectrum Analysis (SSA) and Empirical Orthogonal Function (EOF) analysis were applied to extract annual signals, while component-wise RMS reduction quantified hydrological and atmospheric loading contributions. Spatial statistical analysis, cross-wavelet transform, and k-means clustering examined correlation patterns and phase hysteresis between GNSS observations and modeled loads. Results show that hydrological loading dominates seasonal vertical oscillations, but crustal responses exhibit pronounced spatial heterogeneity controlled by regional topography and hydro-climatic gradients. EOF analysis reveals a dipole pattern induced by the Hengduan Mountains’moisture-blocking effect. Atmospheric loading anomalously dominates the eastern Sichuan Basin, whereas Yunnan displays strong amplitudes with high heterogeneity due to karst hydrogeology. Phase analysis identifies three distinct regimes: a rapid elastic response on the Tibetan Plateau, (with the lag of ~20 ± 5 days, correlation coefficient R ≈ 0.65), intermediate delays in Yunnan (~60 ± 5 days, R ≈ 0.58), and pronounced hysteresis in the Sichuan Basin (~105 ± 5 days, R ≈ 0.38) linked to slow groundwater diffusion and poroelastic processes. These findings highlight the critical role of local hydrogeological dynamics in modulating GNSS vertical deformation and provide new insights for improving environmental loading corrections in complex mountainous regions. Full article

Understanding drought and water availability requires integrating multiple components of the hydrological cycle. Satellite observations enable consistent monitoring of water storage, groundwater variability, and water budget components at continental scales. This study synthesises results from several satellite-based analyses to examine hydrological signals across Europe within the Köppen–Geiger climate zones. Indicators were analysed jointly, including the Combined Climatologic Deviation Index (CCDI), Water Budget (WB), Water Storage Deficit Index (WSDI), and Groundwater Drought Index (GDI). The comparison of these indices reveals consistent spatial and temporal patterns of water deficit across Europe, with the strongest drying signals observed in temperate and Mediterranean regions. In contrast, northern climatic zones show higher retention capacity. The integrated approach highlights relationships among groundwater variability, water storage anomalies, climate anomalies, and water budget dynamics, providing a broader perspective on hydrological responses to climate variability. The results demonstrate the value of multi-indicator satellite analysis for large-scale drought monitoring and water resource assessment. Full article

Surface water extent (SWE) is a key indicator of the regional water balance in dryland environments. However, the hydrological processes regulating SWE responses remain poorly constrained. Focusing on the Mu Us Sandy Land (MUSL), this study integrates multi-source remote sensing and hydrological datasets to investigate the long-term evolution of SWE and, critically, to distinguish the hydrological linkages between SWE dynamics and water storage variability in endorheic and exorheic regions during 1987–2024. An improved water extraction method was implemented on the Google Earth Engine platform, and SWE dynamics were interpreted within a water-balance framework supported by attribution analysis using machine learning. The results show that total SWE exhibited a significant increasing trend (7.95 km² yr⁻¹, p < 0.05) during 1987–2024, primarily driven by permanent SWE, while fundamentally different hydrological regimes governed SWE evolution. In the endorheic basin, SWE exhibited strong co-variation with subsurface water storage, with soil moisture and groundwater storage changes occurring concurrently with SWE changes. In contrast, no synchronous increase in SWE with groundwater storage was observed in the exorheic region. Instead, SWE expansion was mainly associated with accelerated groundwater storage depletion and reservoir construction. These contrasting patterns indicated that SWE dynamics in the endorheic basin were primarily controlled by subsurface water storage, whereas in exorheic regions they were largely driven by human-induced water redistribution rather than increases in total water storage. These findings highlight the importance of integrated surface–subsurface water management for sustaining long-term water security under climate change and increasing human water regulation. Full article

Crop planting structure adjustments in irrigated agricultural regions alter irrigation and drainage regimes, with potential consequences for regional surface water dynamics. However, the nature and scale dependence of these linkages remain insufficiently understood. This study investigates the spatiotemporal dynamics of crop planting structure and surface water bodies in the Ningxia Plain from 2004 to 2023, and systematically quantifies their scale-dependent coupling mechanisms. Annual crop maps were generated using a Random Forest classifier (Sentinel-2, 2019–2023) and a Transformer-based model applied to multi-source satellite imagery (2004–2018). Surface water bodies were derived from long-term remote sensing datasets covering the full study period. Results show that the agricultural system underwent a pronounced transition toward maize dominance. Maize area expanded by 50.8%, whereas wheat and rice declined by 74.3% and 44.6%, respectively. Crop diversity also decreased, with the Shannon Diversity Index declining from 1.41 to 1.06 in 2023, indicating progressive system simplification. Meanwhile, surface water bodies exhibited a sustained downward trend, decreasing at an average rate of −5.32 km² per year after 2013 and reaching a minimum in 2022. The Yellow River water surface area also contracted by 14.41% (p = 0.001), indicating a basin-scale reduction in surface water extent. Lake classification results reveal strong scale-dependent hydrological responses. Small lakes (≤18 ha), accounting for 73.2% of lake numbers, are primarily controlled by local irrigation–drainage processes. Medium lakes (18–80 ha) are influenced by both anthropogenic regulation and natural variability. Large lakes (>80 ha), although representing only 4.9% of lake numbers but 62.9% of total water area, are mainly sustained by climatic variability and ecological water supplementation. Principal component analysis explains 84.44% of total variance, highlighting agricultural structural change and irrigation–drainage dynamics as key system drivers. Correlation analysis further reveals strong climate sensitivity of large lakes and the Yellow River (ρ = 0.50, p = 0.031), while small lakes are predominantly influenced by agricultural drainage processes. Overall, crop planting structure affects regional water dynamics through scale-dependent processes, with maize expansion altering irrigation and diversion patterns and local irrigation–drainage processes controlling small water bodies. Full article

Climate change poses an escalating threat to global water resources, with semi-arid regions such as Morocco being particularly vulnerable due to high climatic variability and limited adaptive capacity. In these regions, including the Tassaoute watershed in central Morocco, data scarcity and uncertainties related to data availability and quality frequently hinder robust assessments of climate change impacts. Recent advances in data science and remote sensing offer promising alternatives to overcome these limitations. This study investigates the potential of the PERSIANN-CDR satellite-derived precipitation product for assessing climate change impacts on water resources. The capability of PERSIANN-CDR to reproduce observed precipitation patterns and associated hydrological responses is evaluated through a comparative analysis using observed precipitation data. Results indicate that PERSIANN-CDR generally underestimates peak precipitation events and total rainfall amounts compared to in situ observations. Runoff is simulated using two hydrological models: GR2M (Génie Rural 2 parameters Mensuel) and the Thornthwaite water balance method, both driven by observed meteorological data and PERSIANN-CDR precipitation. The future water availability was assessed using 5 climate models, under two scenarios: RCP4.5 and RCP8.5 for the periods 2030–2060 and 2061–2090. Results show a marked temperature increase of 2–3 °C across all models, accompanied by a general decline in precipitation ranging from −30% to −60% under RCP4.5 and −20% to −80% under RCP8.5. These climatic changes translate into substantial reductions in runoff, with stronger decreases projected under the high-emission scenario and during the dry season. Monthly analyses reveal pronounced seasonal contrasts, highlighting the increased sensitivity of low-flow periods to climate forcing. Overall, runoff is projected to decrease by 50–90%, with model and data-source differences highlighting the importance of multi-model and satellite-derived approaches in data-sparse regions. These results emphasize the utility of satellite precipitation datasets in guiding climate-adaptive water management strategies. Full article

A climatic transition from arid to humid conditions occurred during the deposition of the Permian Pingdiquan Formation in the Shishugou Sag, Junggar Basin, Northwest China. This study reconstructs the paleoenvironmental evolution and organic matter (OM) enrichment mechanisms recorded in six stratigraphic intervals, with emphasis on the two oil shale units formed during the transgressive system tracts (TST1 and TST2). Geochemical, elemental, and biomarker data reveal that climate, salinity, and redox conditions fluctuated significantly and jointly governed OM enrichment, with paleoclimate acting as the primary background control by regulating lake hydrology, salinity, and preservation. During the early stage (SQ1), an arid climate prevailed, the TST1 oil shale formed during a transient freshening event in a deep stratified lake. Dominant algal productivity and minimal terrigenous input favored excellent preservation, yielding the highest TOC and superior hydrocarbon potential. In contrast, during the humid stage (SQ2), the TST2 oil shale was deposited in a moderately deep, weakly reducing, and slightly saline lake. Although preservation was less efficient, enhanced primary productivity under humid conditions compensated for OM loss, producing abundant but slightly lower quality OM. These results establish two depositional models, an arid freshening model (TST1) and a humid salinization model (TST2). Both transient freshening under arid conditions and salinization during humid periods facilitated the accumulation of organic-rich source rocks through different balances between productivity and preservation. This highlights the complex response of lacustrine source rock development to climatic variability. The occurrence of similar organic-rich source rocks can be anticipated under comparable paleoenvironmental transitions, particularly in saline lakes characterized by frequent fluctuations in water salinity and paleoclimate. Full article

The Alborz Mountain range, serving as the strategic water tower of the Iranian Plateau, is experiencing the accelerating impacts of climate change. Given the critical role of snow reserves in this region for water security, understanding the mechanisms of snow degradation in response to warming is essential. Aiming to investigate the divergent responses of snow cover and snow depth to extreme temperature indices, this study analyzes a 23-year time series (2001–2023) of ERA5-Land data and MODIS imagery across 11 elevation bands. To this end, trends and correlations among the Warm Spell Duration Index (WSDI), the Percentage of Warm Days (TX90p), the Normalized Difference Snow Index (NDSI), and Average Snow Depth (ASD) were assessed using the Modified Mann–Kendall (MMK) test, Generalized Linear Modeling (GLM), and Spearman’s rank correlation. The findings reveal elevational heterogeneity in the snow regime of the Alborz. Notably, the decline in spatial snow cover (NDSI) is primarily concentrated in the mid-elevation transition zone (2000 to 3000 m), whereas the reduction in snow depth (ASD) is a widespread phenomenon, observed even at high altitudes above 4000 m. A key innovation of this research is demonstrating the dominant role of heat frequency over heat duration; GLM results indicate that the TX90p index (frequency of warm days) has a much stronger negative correlation with the degradation of snow resources than WSDI. These results confirm the transition of the Alborz hydrological system toward instability, the upward shift in the snowline in the transition zone, and the invisible thinning of the snowpack at higher elevations. Full article

Aquatic–terrestrial ecotones are highly dynamic biogeochemical hotspots where hydrological fluctuations profoundly influence microbial community structure and ecosystem functioning. However, the mechanisms underlying microbial community responses across hydrological gradients remain insufficiently understood. In this study, 16S rRNA gene sequencing was used to comparatively analyze bacterial communities in the waterward and landward zones of the drawdown area of the Danjiangkou Reservoir. The results showed that bacterial community composition differed significantly between the two zones, and waterlogging markedly increased bacterial α-diversity. Community variation was primarily associated with key environmental factors, including total phosphorus (TP), soil moisture content (SMC), and nitrate nitrogen (NO₃⁻-N). Compared with the landward zone, stochastic processes contributed more to community assembly in the waterward zone, which also exhibited higher network complexity and topological stability. In addition, several keystone taxa were identified, suggesting their potential roles in maintaining network structure and ecological stability. Functional prediction further revealed distinct metabolic potentials between zones, with enhanced anaerobic and redox-related functions in the waterward zone and predominantly aerobic metabolism in the landward zone. These findings suggest that hydrological fluctuations reshape bacterial community structure and potential ecological functions by jointly regulating water availability and nutrient dynamics. This study provides new insights into microbial ecological processes in reservoir riparian zones and offers a scientific basis for the management of aquatic–terrestrial ecotone ecosystems. Full article

As a critical link between regional economic development and ecological security, understanding the dynamics of water retention is essential for sustainable water resource management in the Huaihe River Economic Belt. This study explores the spatio-temporal evolution and spatial explanatory factors of water retention across five temporal snapshots (2003, 2008, 2013, 2018, and 2023). Based on the InVEST model, we assessed water retention capacity at both grid and spatial development levels, thereby obtaining the retention characteristics of different land-use types and their responses to land-use transitions. Furthermore, a parameter-optimized geographical detector was employed to quantify the relative contributions of climatic-environmental and social-economic factors to the spatial variance of the modeled water retention index. Results indicate that the total water retention capacity exhibited significant interannual fluctuations, with the net capacity in 2023 being lower than the initial level in 2003. Retention values displayed obvious spatial heterogeneity, with high levels concentrated in the southwest and north and low levels distributed in the central area, closely mirroring precipitation distribution. While forest land exhibited the strongest unit water retention capacity, cropland contributed the most to the total volume (50.49%) due to its predominant areal proportion (73.92%). Notably, the conversion of forest to cropland was spatially associated with the most substantial loss in the modeled retention capacity. Soil saturated hydraulic conductivity and land-use type were identified as the dominant factors explaining the spatial variance of water retention. These findings underscore the methodological utility of coupling the InVEST model with a parameter-optimized geographical detector. For practical ecosystem management, the results suggest that spatial planning policies should strictly limit the conversion of ecological lands to agricultural use and prioritize targeted soil hydrological improvements in the central plains to secure long-term water resources. Full article

Accurate rainfall information is essential for rainfall–runoff modeling in monsoon-influenced basins, where pronounced spatial variability and limited gauge coverage introduce significant uncertainty. Satellite precipitation products provide spatially continuous estimates but are affected by systematic biases, and improvements in statistical rainfall accuracy do not necessarily translate into hydrologically consistent model forcing. This study interpreted satellite rainfall bias correction through a rainfall–runoff framework in the Phetchaburi River Basin, Thailand, using the DWCM-AgWU hydrological model. Simulations were driven by gauge observations and multiple satellite-based rainfall products (GSMaP, CMORPH, CHIRPS, and PERSIANN-CCS), with bias correction applied using Linear Scaling and Quantile Mapping under rainfall-specific calibration. Results showed that bias correction significantly modified rainfall characteristics in distinct ways. Linear Scaling primarily preserved temporal and spatial structure while adjusting rainfall magnitude, whereas Quantile Mapping improved the distributional representation of rainfall intensities. These differences propagated through hydrological processes, leading to systematic variations in runoff responses across multiple metrics, including water balance consistency, peak magnitude, and timing errors. This suggests that each method performs differently depending on the aspect of system response. Rather than identifying a universally optimal method, the findings highlight trade-offs in how rainfall correction strategies influence hydrological system response. Runoff behavior is interpreted as a process-level indicator of rainfall representation, emphasizing that hydrological consistency depends not only on rainfall accuracy but also on its interaction with model structure. These results suggest a process-oriented perspective for interpreting the role of satellite rainfall products in regulated and monsoon-affected basins. Full article

Sub-sag 21 in the eastern Yangjiang Sag, Pearl River Mouth Basin, South China, contains a thick lacustrine source-rock interval within the lower Wenchang Formation and is a major exploration target on the northern margin of the South China Sea. However, the timing of deposition during the early to middle Eocene remains poorly constrained, and the applicability of quantitative palaeoclimate reconstruction methods in low-latitude lacustrine basins requires further evaluation. In this study, we analyzed mudstones from the lower Wenchang Formation in Well E1. Using cyclostratigraphic constraints, we applied AstroGeoFit to construct an astronomically tuned age model, and combined palynological coexistence analysis with geochemical weathering proxies and linear–regression calibration to quantitatively reconstruct and cross-validate mean annual temperature and mean annual precipitation. Within this time-calibrated framework, we further quantified organic-carbon burial to evaluate the relationship between palaeoclimate evolution and organic-matter enrichment. The AstroGeoFit results indicate that the top of the lower Wenchang Formation in Well E1 is constrained to 44.563 Ma, and that the studied succession spans 50.249–44.563 Ma. Palynological coexistence analysis identifies three palaeoclimate phases within this interval. Method evaluation shows that the temperature reconstruction based on major-element geochemistry agrees well with the pollen-based temperature record, whereas one precipitation reconstruction based on weathering proxies shows the most robust agreement and stability relative to the pollen-based precipitation record. Reconstructed mean annual temperature ranges from 10.77 to 22.20 °C, and reconstructed mean annual precipitation ranges from 1188.27 to 1871.89 mm. Correlation analyses on the tuned timescale show that precipitation is more strongly associated than temperature with organic-matter accumulation parameters, including total organic carbon and organic carbon accumulation rate, indicating that organic carbon burial in the eastern Yangjiang Sag lake basin was mainly controlled by hydrological forcing. During the Early Eocene Climatic Optimum, carbon burial in low-latitude lakes was, therefore, not a simple response to elevated temperature, but instead reflected the integrated effects of precipitation, runoff, stratification, material supply, transport, and preservation. The evolutionary sequence further suggests that early high productivity was diluted by rapid sedimentation, reducing total organic carbon; subsequent cooling, lake deepening, and strengthened stratification enhanced organic matter preservation; and finally, tectonic subsidence together with regional humidification promoted the development and long-term preservation of high-quality lacustrine source rocks. Full article

Seismic lines are among the most widespread anthropogenic disturbances in Alberta’s boreal peatlands, where repeated petroleum-exploration surveys can alter surface morphology, hydrology, and recovery potential. Although low-impact seismic (LIS) techniques are designed to minimize ground disturbance, the long-term consequences of re-using existing lines remain poorly understood. This study used remotely piloted aircraft system (RPAS)-based LiDAR and optical imagery to examine how peatland microtopography and hydrology evolve following repeated seismic surveys. We quantified four attributes—ground depression, hummock cover, depth to water, and surface water cover—across new seismic lines (cut in 2021), old seismic lines (cut in 1996), and re-disturbance (cut in 1996, re-cut in 2021) LIS lines, as well as adjacent undisturbed peatland, in a boreal fen of northern Alberta. New disturbances were depressed by approximately 10 cm relative to the surrounding peatland and exhibited reduced microtopographic variability. Hummock cover decreased from 21% in the matrix to 6% on new disturbances. Old disturbances showed greater heterogeneity than new disturbances, with hummock cover partially recovering to 14% and surface water increasing from 7% to 27%, reflecting greater spatial heterogeneity in surface conditions. Re-disturbances exhibited microtopographic conditions similar to or more degraded than old disturbances, with hummock cover reduced to 2% and persistently high surface water cover (27%). These patterns suggest that repeated seismic surveys may limit recovery and maintain altered hydrological and microtopographic conditions. Within the context of this case study, even narrow LIS corridors were associated with persistent alterations when re-used, highlighting the importance of considering re-use effects when developing management strategies for peatland ecosystems. RPAS data provide an effective means to quantify these fine-scale changes and inform peatland restoration and seismic line management. Full article