Search Results (1,708)

Accurate modeling of dam reservoir sedimentation is crucial for effective reservoir management. Traditional approaches for estimating sedimentation include the Hydraulic Approach (HA) and the Empirical Approach (EA). HA involves complex computations and requires substantial data, while the EA relies on equations like the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE), which use subjective parameters and lead to inaccurate estimations. This study introduces a novel approach called the hydrological approach, which integrates the sediment rating curve (SRC) and the dam reservoir elevation-capacity curve (ECC) to estimate reservoir sedimentation and evolution of the ECC. This HA leads to a newly developed equation for the estimation of the sediment rise and the corresponding sediment volume. The approach is applied to the Wadi Fatimah Dam in Saudi Arabia. By combining rainfall data from 1985 to 2022 and performing rainfall–runoff hydrological modeling combined with the proposed HA, sediment accumulation trends and reservoir capacity reductions are estimated from past to present. Validation through ground survey and geophysical investigations in 2008 confirms model accuracy. Findings reveal significant sediment buildup, with an estimated average of 7.5 m rise from 1985 to 2008. The study’s main findings highlighted the urgent need for effective sediment management strategies in arid regions, where sedimentation rates are notably higher than in other regions. Full article

Wetlands are vital ecosystems that regulate water, store carbon and support biodiversity, but they are highly vulnerable to climate variability and human pressures. In semi-arid South Africa, montane wetlands remain understudied despite their ecological and socioeconomic importance. The study analyzed 1996–2023 climate variability and vegetation response across the Waterberg Mountain Complex (WMC) using station temperature/precipitation, Rainfall Anomaly Index (RAI), 6-month wet-season Standardized Precipitation Index (SPI) and site-level Normalized Difference Vegetation Index (NDVI) for 11 wetlands. Maximum temperatures increased at all stations, led by Warmbath (0.009 °C/month). No statistically significant changes in minimum temperature were detected. Precipitation trajectories diverged, Mokopane exhibited a statistically significant wetting trend whereas Lephalale and Marken experienced progressive drying. ENSO-driven droughts (2002/2003, 2015/2016 and 2019/2020) intensified hydroclimatic stress and shortened wetland hydroperiods. NDVI trends revealed strong coupling with rainfall variability, with high-altitude wetlands demonstrating greater resilience, while lowland systems declined in greenness. These findings highlight topography as a determinant of wetland vulnerability, positioning upland wetlands as potential climate refugia. Site-specific adaptation and conservation strategies are essential to safeguard ecosystem services and biodiversity, contributing to global sustainability goals (SDGs 6, 13 and 15). Full article

Research on centennial-scale precipitation variability within the Australian summer monsoon (AUSM) remains limited, particularly regarding its driving mechanisms and the sustainability-relevant implications for long-term water security and climate adaptation. Here, we use the TraCE-21ka transient simulation, which credibly reproduces the centennial periodicities documented in Holocene proxy records, to attribute the physical drivers of AUSM centennial variability. Attribution is conducted by contrasting the all-forcing (AF) simulation with four single-forcing experiments that isolate the effects of orbital parameters, ice sheets, meltwater flux, and greenhouse gases. Among these experiments, the meltwater-forcing run best reproduces the centennial periodicities found in the AF simulation, indicating that meltwater input is the leading contributor to Holocene AUSM centennial variability. We further identify a dynamical pathway in which Atlantic Meridional Overturning Circulation (AMOC) variability acts as the key mediator linking meltwater perturbations to Australian hydroclimate. The enhanced AMOC amplitude during the meltwater interval (0.14 at 9–8 ka BP), compared with much weaker fluctuations during the non-meltwater interval (0.01 at 4–3 ka BP), is accompanied by a ~200-year periodicity in AUSM precipitation. This periodicity arises through an interhemispheric teleconnection: a strengthened AMOC cools Southern Hemisphere sea surface temperatures, reduces moisture availability for northern Australia, and promotes large-scale subsidence that suppresses monsoon rainfall. By contrast, during 4–3 ka BP, when meltwater forcing was negligible, weaker AMOC variability coincides with warmer Southern Hemisphere sea surface temperature (SST), favoring cyclonic circulation over northwestern Australia, enhanced moisture convergence, and stronger ascent, ultimately intensifying AUSM precipitation. Beyond advancing process understanding, these results provide a sustainability-oriented framework for interpreting low-frequency hydroclimate variability relevant to Australia’s water resources and climate adaptation. Specifically, the identified meltwater–AMOC–SST–AUSM pathway offers a physical basis for developing and evaluating long-horizon indicators of monsoon-driven rainfall variability, informing monitoring strategies and scenario planning for drought–flood risk management, water allocation, and climate-resilient infrastructure. By linking centennial-scale monsoon variability to an identifiable remote driver, this study contributes to quantifying and contextualizing natural hydroclimate variability that can confound near-term trends, thereby supporting more robust sustainability assessments, adaptation policy design, and integrated water-resource management under ongoing climate change. Full article

This study proposes a hybrid landslide displacement prediction model based on multi-strategy integrated optimization to address high nonlinearity and limited accuracy. An improved SFOA with Lévy flight, dynamic exploration adjustment, and stagnation detection enhances global search and convergence. The optimized SFOA (OSFOA) is employed to optimize CEEMDAN using minimum envelope entropy, reducing hyperparameter subjectivity and decomposing cumulative displacement into multi-scale components. The trend term is predicted by a Bayesian-optimized ARIMA, while periodic and stochastic terms are further decomposed by VMD and predicted using Bayesian-optimized SVR. GRA-MIC is applied to select key influencing factors and optimize model inputs. Results show that the proposed method improves accuracy and stability, reducing RMSE by about 82% and 52% compared with SSA-SVR and the baseline single decomposition model, respectively. The study further identifies monthly rainfall change and two-month reservoir level variation as the dominant driving factors for the displacement evolution, providing an effective and interpretable approach for complex landslide early warning. Full article

Land subsidence (LS) is a major global geo-environmental issue that profoundly affects the suitability and safety of land use planning (LUP). However, existing LUP systems generally neglect the dynamic evolution of LS and lack a systematic framework for assessing conflicts between land use and subsidence. To address this gap, this study develops an integrated evaluation framework that combines SBAS-InSAR, GeoDetector, and a spatial conflict detection model. A total of 166 Sentinel-1A images acquired from 2017 to 2024 were processed using SBAS-InSAR to derive the spatiotemporal characteristics of LS. GeoDetector was subsequently applied to identify the dominant driving factors and their interactions. A sensitivity classification scheme for current land use (CLU) and LUP types with respect to LS hazards was then developed, and a spatial conflict detection model was constructed to delineate conflict zones and quantify conflict intensity. Using Huainan City as a case study, the results show the following: (1) from 2017 to 2024, LS was generally characterized by slight or negligible subsidence, with severe subsidence mainly concentrated in coal mining areas; ongoing and recently suspended mines exhibited pronounced LS, whereas early-closed and unmined areas showed an overall uplift trend. (2) LS in Huainan was primarily driven by soil type, annual rainfall, and mining activities, and two-factor interactions generally exhibited enhancement effects. (3) Compared with CLU, LUP has, to some extent, incorporated LS risk considerations and implemented corresponding mitigation measures, although certain areas still insufficiently account for LS risks. (4) The proposed framework demonstrates strong rationality and applicability in LS monitoring, driving factor identification, and spatial conflict assessment, providing scientific support for LS risk management and land use spatial optimization. Full article

The Hulukou-Xiangbiling section of the Jinsha River is located in a typical high-mountain gorge area characterized by a complex geological environment, rendering it highly susceptible to landslide disasters. To reveal the deformation mechanisms of typical landslides in this region under hydrological effects, this study employed the Small Baseline Subset InSAR (SBAS-InSAR) technique to process multi-track Sentinel-1 SAR images acquired between 2021 and 2024. Long-term deformation time series were extracted for the Xiaxiaomidi and Chenjiatian landslides. On this basis, a systematic multi-scale coupling analysis of the deformation characteristics was conducted using trend-cycle decomposition, Continuous Wavelet Transform (CWT), Cross Wavelet Transform (XWT), and Wavelet Coherence (WTC). The results indicate that although the two landslides are located in the same river section, their deformation mechanisms and hydrological response patterns differ significantly. The deformation of the Xiaomidi landslide is mainly concentrated in the lower part of the slope, exhibiting a characteristic of continuous acceleration. The analysis demonstrates that the evolution of this landslide is primarily controlled by hydrodynamic processes such as toe unloading, water body erosion, and water level fluctuations. In contrast, the Chenjiatian landslide displays a distinct dominant cycle of 365 days, manifesting as a composite mode of long-term creep superimposed with seasonal acceleration. Its deformation shows a high correlation with rainfall (correlation coefficient > 0.9), with a lag effect of approximately 1 to 2 months. This reflects the dominant role of rainfall infiltration and pore pressure transfer in the landslide dynamics. Full article

Flood events are major drivers of soil erosion and sediment yield on the Loess Plateau, where extensive ecological restoration has been implemented. This study investigates runoff–sediment dynamics by analyzing 215 flood events recorded in the Chabagou watershed (1959–2022), with a focus on changes under intensifying restoration efforts. Using long-term hydrological and rainfall data, we applied cluster and discriminant analyses to classify flood events based on sediment hysteresis loops and evaluated variations across three management periods (1959–1979, 1980–1999, and 2000–2022), characterized by progressive increases in check dam construction and vegetation recovery. The results show that the floods characterized by short duration, low peak flow, and low sediment concentration were predominant, accounting for 77.7% of the recorded 215 events. A clear decreasing trend was observed, with average sediment yield and peak discharge declining by approximately 68% and 52%, respectively. Anticlockwise hysteresis loops were most common (45.6%), followed by complex (27.9%) and figure-of-eight loops (23.7%). The proportion of figure-of-eight loops increased notably from 17% to 39%, indicating reduced sediment connectivity due to large-scale ecological restoration. Extreme rainfall events consistently produced complex hysteresis patterns, influenced mainly by rainfall intensity but increasingly modulated by human interventions. These results highlight adaptive watershed management strategies that target figure-of-eight and complex flood events to mitigate erosion and flood risks. Full article

Rainfall is recognised as one of the major external factors affecting the stability of retaining walls. The magnitude of rainfall directly influences the overall stability of retaining walls, while rainfall patterns alter the infiltration process and the saturation state of the soil, thereby affecting soil shear strength and retaining wall stability. In order to investigate the effects of rainfall pattern and intensity on the stability of reinforced soil gabion retaining walls, numerical simulations were carried out to examine wall stability under two typical rainfall patterns (uniform and intermittent) and three rainfall intensities (20 mm/d, 50 mm/d, and 80 mm/d). The results indicate that: (1) under uniform rainfall conditions, the extent of the soil pore water pressure response zone is greater than that under intermittent rainfall of the same intensity, and as the uniform rainfall intensity increases from 20 mm/d to 80 mm/d, the pore water pressure response zone expands by approximately four times; (2) the rainfall pattern exerts a certain influence on the distribution characteristics of the time-history curves of lateral displacement of the retaining wall, with the horizontal displacement under intermittent rainfall exhibiting a non-uniform growth pattern associated with the rainfall pattern; (3) uniform heavy rainfall has a more pronounced effect on the horizontal displacement of reinforced soil gabion retaining walls, with the maximum absolute horizontal displacement reaching approximately 12.89 mm; and (4) rainfall pattern affects the evolution of the slope stability coefficient, which gradually decreases and eventually stabilises under uniform rainfall, whereas under intermittent rainfall it shows a continuous decreasing trend characterised by alternating rates of reduction, with a greater reduction observed under uniform rainfall conditions. These findings elucidate the influence of different rainfall patterns and intensities on the displacement behaviour and stability of reinforced soil gabion retaining walls, and provide a reference for risk assessment of reinforced soil gabion retaining walls. Full article

This study presents the development and validation of a consistent rainfall database for Maranhão State, Brazil, covering historical records from 1987 to 2023 obtained from 100 rainfall stations (90 from ANA and 10 from INMET). A total of 314 missing records across 74 stations were corrected using the Regional Weighting method, restricted to stations within the same Homogeneous Precipitation Region (HPR). The consistency of the reconstructed series was verified using the Double Mass method, which yielded coefficients of determination (R²) above 0.97 for all stations, confirming the robustness of the procedure. Statistical analyses with the Mann–Kendall test and Sen’s Slope estimator did not identify significant long-term trends, although weak positive slopes were detected in some regions (e.g., HPR3: +9.98 mm/year; HPR6: +3.70 mm/year), while HPR10 showed a negative slope (−0.99 mm/year). The novelty of this work lies in consolidating the first homogeneous and validated rainfall database for Maranhão, providing a reliable foundation for assessing regional climate variability. The results provide a solid foundation for future applications, including drought monitoring, agricultural planning, water resource management, and adaptation strategies under climate change scenarios. Full article

Soil tillage practices play a key role in controlling soil’s physical properties, water infiltration, and runoff generation, particularly in erosion-prone cropping systems such as maize monocultures. The cultivation of wide-row crops is restricted on erosion-prone land; however, these crops constitute a fundamental basis for livestock feed and represent a key input raw material for biogas plants. This 4-year study evaluated the effects of three tillage practices—conventional ploughing, shallow tillage, and no tillage—on selected soil’s physical and chemical properties and on water infiltration processes in a maize (Zea mays L.) monoculture. Experimental maize stands were established in a field with a silty clay Luvic Chernozem. Field measurements were performed over multiple years and included soil bulk density, macroporosity, cone index, soil organic carbon, soil pH, soil aggregate stability, and water infiltration. Infiltration processes were assessed using a combination of double-ring infiltrometers, rainfall simulation, and dye tracer experiments to characterize water flow patterns under controlled conditions. The results demonstrated that soil tillage significantly influenced the vertical distribution of soil organic carbon and pH, soil aggregate stability, soil compaction, and pore characteristics, with the most pronounced differences observed in the upper soil layers. Soil aggregate stability in the 0–0.10 m layer showed a clear numerical trend, with the highest mean value under ST (0.42) compared with PL (0.28) and no tillage (NT) (0.26). Topsoil Cox was the highest under ST (3.591%) compared with PL (2.838%) and NT (2.634%). Differences among tillage practices were particularly evident during simulated rainfall events, affecting infiltration rates, runoff initiation, and preferential flow patterns. Ring infiltrometer measurements indicated higher infiltration in PL (e.g., 21.1 mm min⁻¹ at minute 1 in PL vs. 11.1/11.9 mm min⁻¹ in ST/NT; 10.9 mm min⁻¹ at minute 10 in PL vs. 5.3/7.6 mm min⁻¹ in ST/NT). However, rainfall simulation showed the highest runoff in PL, including the earliest runoff onset (4.5 min). Despite the soil’s high infiltration capacity due to low bulk density and higher porosity, the decisive factor promoting water infiltration into the soil is the condition of the soil surface, which is influenced by the stability of soil aggregates; this stability was enhanced by the input of organic matter from plant residues. The findings confirm that long-term soil tillage management substantially modifies soil hydraulic behaviour and highlight the importance of tillage system selection for improving soil water infiltration and reducing runoff risk in maize monoculture systems. Full article

Selenium (Se) is an essential trace element for humans, and agricultural soils are a major source of dietary Se. Therefore, identifying the key environmental drivers of Se in farmland is crucial for evaluating the resource base for Se-rich agriculture and improving human health. Although soil Se distribution and its controlling factors have been widely investigated, quantitative assessments of soil Se in small-scale farmland systems under humid monsoon conditions remain limited. Sampling sites were designed to represent different geological types, soil types, and topography, and 314 farmland topsoil (0–20 cm) samples were collected. Total Se was determined after complete HNO₃–HClO₄ wet digestion and quantified by HG–AFS (AFS–830), with certified reference materials showing recoveries of 95.3–101.2%. The spatial patterns were mapped using ordinary kriging. Geographically weighted regression (GWR) and Geodetector were used to explore the impact of environmental factors (geological type, precipitation, etc.) on soil Se from both local and overall perspectives. The findings reveal a mean total soil Se of 1.76 mg/kg (95% CI: 1.540–1.974), and 91.40% (n = 287) of soil samples were classified as Se-rich (0.4–3 mg/kg). Organic matter (OM), elevation, slope, and the topographic wetness index (TWI) exhibited non-stationary spatial relationships with Se. The spatial variation trend of precipitation corresponds with the local R² values between Se and elevation, indicating that precipitation may strengthen the association between elevation and Se distribution. Geological type and rainfall were identified as key driving factors affecting soil Se content within the study area, particularly through their interactions with OM. Overall, the synergistic effects of geological type, precipitation, and OM are responsible for the accumulation of Se in the agricultural soils of Xin’an Town. Full article

This study assessed the carbonation-related durability of an existing reinforced concrete building in Seoul scheduled for demolition to examine the level of durability performance commonly assumed for building structures. The compressive strength of concrete core specimens was compared with the estimated compressive strength derived from the rebound hammer, showing similar overall trends despite noticeable scatter, indicating that rebound testing can serve as a supplementary indicator when interpreted with caution. Carbonation depth measurements revealed that indoor locations tended to exhibit the greatest carbonation depths, likely reflecting higher CO₂ concentrations associated with occupancy and daily activities, as well as indoor ventilation and moisture conditions. For exterior walls, orientation affected carbonation progress; carbonation depths were greater on the southwest-facing wall than on the northwest-facing wall, suggesting that higher solar radiation may promote drying and facilitate CO₂ diffusion, thereby accelerating carbonation. When the carbonation rate coefficients were compared under similar compressive strength conditions, the southeast-facing wall exhibited a coefficient approximately 1.1 times greater than that of the northwest-facing wall. These results indicate that carbonation cannot be explained by strength alone and highlight the importance of incorporating exposure-related factors (e.g., solar radiation, drying, rainfall, and shielding) into carbonation behavior assessment. Full article

Soil moisture is a critical variable in the eco-hydrological processes of arid regions; however, the vertical stratified mechanisms of soil moisture response to meteorological factors in artificial grassland remain inadequately quantified. Based on 10-min interval monitoring data from 2015 to 2024 in the middle reaches of the Heihe River, this study investigated the dynamics of soil moisture within a 0–160 cm depth profile in an arid artificial grassland. By integrating the Mann–Kendall trend test, Pearson correlation, time-lagged cross-correlation, multiple regression analysis and redundancy analysis, we systematically investigated the changing relationships between meteorological factors and soil moisture. The results revealed the following: (1) main meteorological factors driving surface processes (e.g., net radiation, air temperature, vapor pressure deficit) showed significant increasing trends with strong variability, while relative humidity decreased significantly, and these findings collectively point to a general trend of warming and drying in the region; (2) WS, Ta, rainfall, and RH are the principal factors explaining soil moisture variations, wherein temperature and humidity exhibit positive correlations with soil moisture; (3) RDA results showed that shallow soil moisture (0–20 cm) was primarily governed by air temperature and rainfall, whereas deep soil moisture was increasingly regulated by vapor pressure deficit; (4) time-lagged cross-correlation analysis showed that the response time of soil moisture to rainfall almost increased with soil depth, while the correlation coefficient gradually weakened from 0.43 to 0.06. This study quantitatively elucidates the stratified control mechanism of meteorological factors on the vertical pattern of soil moisture, contributing to a deeper understanding of the response of eco-hydrological processes under climate change and providing a scientific basis for water resource management, agricultural planning, and climate prediction. Full article

This study investigates the characteristics of water and sediment evolution under the influence of the Datengxia Water Control Hub Project by analyzing its affected area, with a focus on the driving mechanisms of human activities on these processes. Utilizing hydrological data (1993–2022) from the Wuxuan and Dahuangjiangkou Stations, along with meteorological, land use, and population data, we applied the M–K (Mann–Kendall) trend test, Pettitt change point test, double mass curve method, and a random forest model. These methods were used to quantify the contributions of rainfall and human activities and to identify the dominant controlling factors. Model reliability was verified by comparing predicted and observed P-III (Pearson Type III distribution curve), enabling an assessment of water–sediment changes before and after the project’s construction. The results indicate that (1) both stations showed a non-significant declining trend in runoff and sediment load, with a human activity-induced change point detected in 2003; (2) human activities accounted for 93.18% and 92.38% of the reduction in runoff and sediment load at Wuxuan Station, and 74.44% and 54.33% at Dahuangjiangkou Station, respectively; (3) population density was the dominant factor for water–sediment changes at Wuxuan Station (influence weight: 0.41), while grassland area (0.41) and population density (0.40) primarily controlled runoff and sediment changes, respectively, at Dahuangjiangkou Station; (4) following project construction, the trend of the decreasing flood inundation extent with increasing frequency became more pronounced, and sediment deposition was concentrated mainly in the reservoir area and downstream reaches. The study confirms the dominant role of human activities in the basin’s water–sediment dynamics, and the established methodological framework provides a scientific basis for integrated watershed management and ecological conservation. Full article

Environmental degradation in Iraq is a critical issue that requires strong monitoring. One indication of land degradation is a decrease in or loss of vegetation cover. This study examines changes in vegetation and productivity in the Thi-Qar region from 2001 to 2022, using the normalized difference vegetation index (NDVI) and net primary production (NPP), and their response to climatic and hydrological factors. To address the gap in assessments that simultaneously quantify the influence of streamflow, rainfall, and temperature across distinct land cover classes in arid and semi-arid regions, we developed a replicable multi-source geospatial framework. We used MODIS data within the Google Earth Engine platform to perform spatiotemporal analysis. We applied models to detect NDVI trends on a pixel-by-pixel basis. This study provides the first integrated, data-driven assessment of vegetation sensitivity to streamflow versus climate in the Thi-Qar Governorate using a harmonized multi-source dataset. This combines the FAO WaPOR NPP dataset with hydrological (streamflow) and climatic (CHIRPS rainfall, MODIS LST) variables within an analytical workflow to extract anthropogenic water management from climatic drivers. The results showed variations in the NDVI and productivity in the southern and southwestern regions, indicating areas of both degradation and improvement. The analysis found that 12% of the study area showed improvement, while 56.5% of the area showed degradation. Additionally, we classified the study area as either vegetation (cropland) or non-vegetation (fallow arable land, bare areas, and sand dunes). A multiple regression model was then applied to these categories to examine the relationships between streamflow, precipitation, land surface temperature (LST), and the NDVI. The multiple regression for the entire region showed that these factors explained 45.1% of NDVI variation, with streamflow being the most significant positive driver (p < 0.001). The result showed that the NDVI in cropland and arable land was strongly positively correlated with both precipitation and streamflow (R = 0.78, R = 0.75). In contrast, bare land and dunes showed weaker relationships (R = 0.26 and 0.51, respectively). Of these factors, streamflow had the most significant influence in explaining vegetation change (partial correlation p = 0.53), indicating the importance of human management in addition to climate. Full article