Search Results (950)

In arid areas, the combined use of plastic sheeting under gravel-sand mulch on ridge-furrow planting systems is an emerging practice to minimize soil water evaporation and micro-plastic pollution. In this study, we conducted a two-year field experiment near Gobi-Tengger Desert in Ningxia, China, to evaluate the effects of a plastic film underneath a layer of pure sand (MS1), pure gravel (MS2) and mixed gravel-and-sand (MS3) mulch on the soil hydrothermal properties, water use efficiency, yield, and fruit quality of wolfberry, compared to bare soil (CK). The results showed that mulching significantly increased soil temperature and water content in the 0–20 cm surface layer, though the effects varied with soil depth and water availability between a supplemental irrigated year (2022) and a rain-fed year (2023). Mulching markedly altered soil water dynamics, enhancing the capture and retention of light-to-heavy rainfall events. Consequently, all mulches significantly increased seasonal water consumption (ET) and water use efficiency (WUE) compared to CK. The MS1 treatment consistently achieved the highest yield and WUE, and the highest accumulation of beneficial fruit compounds like polysaccharides and flavonoids. However, this treatment also resulted in elevated soil salinity. Our findings demonstrate that combined mulching, especially MS1, is a highly effective strategy for optimizing soil conditions, water productivity, and fruit quality in wolfberry cultivation, although long-term salinity management requires attention. Full article

Cyprus faces mounting pressure on freshwater resources from climate change, recurrent drought, and rising demand. This study evaluates the feasibility of a rain enhancement program through cloud seeding, integrating long-term rain gauge records (1991–2024), lightning climatology (2021–2025), and local X-band weather radar data (30 October 2024–4 January 2025) to quantify the frequency and characteristics of seedable clouds. Rain gauge analysis shows mean monthly rainfall exceeding 20 mm during October to April, with up to 16 rainfall events per month, indicating ample seeding opportunities. Lightning records show between 40–60 annual average thunderstorm occurrences, peaking in December (~10 days) along the Troodos Mountains in the central region and Limassol-Akrotiri in the south. Radar data analysis confirms the presence of both glaciogenic (≥25 dBZ at 5 km MSL) and hygroscopic (≥10 dBZ with ≥4 km depth) seedable cloud structures, with hotspots over the Troodos orography, southern plains, and maritime inflow zone. The combined results support the viability of an initial 7-month (October–April) cloud seeding program demonstration, integrated within a scientific framework, as a complementary and cost-effective freshwater augmentation tool for Cyprus. Full article

Frequent and severe droughts intensify water scarcity in arid and semi-arid regions, creating an urgent need for alternative water resources in agriculture. Treated wastewater (TWW) has emerged as a sustainable option; however, its long-term use may alter soil properties and pose risks if not carefully managed. This study tested the hypothesis that long-term TWW irrigation increases soil salinity, alters fertility, and affects microbial quality, with rainfall partially mitigating these effects. Soil samples (n = 96 at each time point) were collected from two calcareous soils in Jordan, silt loam (Mafraq) and silty clay loam (Ramtha), under four treatments (control and 2, 5, and 10 years of TWW irrigation) at three depths (0–30, 30–60, and 60–90 cm). Sampling was conducted at two intervals, before and after rainfall, to capture the seasonal variation. Soil indicators included the pH, electrical conductivity (EC), sodium (Na⁺), chloride (Cl⁻), calcium (Ca²⁺), magnesium (Mg²⁺), exchangeable sodium percentage (ESP), sodium adsorption ratio (SAR), organic matter (OM), total nitrogen (TN), and microbial parameters (total coliforms (TC), fecal coliforms (FC), and Escherichia coli). Data were analyzed using a linear mixed-effects model with repeated measures, and significant differences were determined using Tukey’s Honest Significant Difference (HSD) test at p < 0.05. The results showed that rainfall reduced Na⁺ by 70%, Cl⁻ by 86%, EC by 73%, the ESP by 28%, and the SAR by 30%. Furthermore, the TC and FC concentrations were diminished by almost 96%. Moderate TWW irrigation (5 years) provided the most balanced outcomes across both sites. This study provides one of the few long-term field-based assessments of TWW irrigation in semi-arid calcareous soils of Jordan, underscoring its value in mitigating water scarcity while emphasizing the need for monitoring to ensure soil sustainability. Full article

Soil secondary salinization is a major limiting factor of sustainable agricultural production in arid and semi-arid irrigation zones, yet predictive tools for regional water–salt dynamics remain limited. The Yichang Irrigation District, located within the Hetao Irrigation Area, has experienced persistent salinity challenges due to shallow groundwater tables and intensive irrigation. In this study, we aimed to simulate long-term soil water–salt dynamics in the Yichang Irrigation District and evaluate the effectiveness of different engineering and management scenarios using the SaltMod model. Field monitoring of soil salinity and groundwater levels during summer and fall (2022–2024) was used to calibrate and validate SaltMod parameters, ensuring accurate reproduction of seasonal soil salinity fluctuations. Based on the calibrated model, ten-year scenario simulations were conducted to assess the effects of changes in soil texture, irrigation water quantity, water quality, rainfall, and groundwater table depth on root-zone salinity. Our results show that under baseline management, soil salinity is projected to decline by 5% over the next decade. Increasing fall autumn leaching irrigation further reduces salinity by 5–10% while conserving 50–300 m³·ha⁻¹ of water. Sensitivity analysis indicated groundwater depth and irrigation water salinity as key drivers. Among the engineering strategies, drainage system improvement and groundwater regulation achieved the highest salinity reduction (15–20%), while irrigation regime optimization provided moderate benefits (~10%). This study offers a quantitative basis for integrated water–salt management in the Hetao Irrigation District and similar regions. Full article

Urban flooding caused by short and high-intensity rainfall events presents increasing challenges for cities, threatening infrastructure, public safety and economic activity. Accurately representing infiltration processes in hydrodynamic models is critical, as oversimplifying infiltration can lead to significant errors in predicted flood extents and water depths. This study systematically compares two widely used infiltration models—Green-Ampt and Curve Number—implemented within two leading 2D hydraulic models, HEC-RAS and IBER, to assess their influence on urban flood predictions. Simulations were conducted for 26 rainfall events, including both observed and synthetic hyetographs, across two urban neighbourhoods in Pamplona metropolitan area, Spain. Model performance was evaluated using root mean square error, mean absolute error and confusion matrix-derived metrics such as precision, accuracy, specificity, sensitivity and negative predictive value. Results indicate that the choice of infiltration method significantly affects both water depths and inundation extents: while Green-Ampt yields more conservative water depth estimates, Curve Number tends to underestimate flood extents. The comparison between the two hydraulic models has shown that IBER simulates broader flood extents and lower water depth errors compared to HEC-RAS. The findings highlight the importance of selecting appropriate infiltration methods and hydraulic models for reliable urban flood risk assessment, as well as providing guidance for model selection in urban inundation studies. Full article

Almonds are one of the major products that are economically competent and compatible with the Mediterranean climate, a key characteristic that distinguishes Lebanon. The present study aims to examine the suitability of land use and land cover on the Lebanese territory for sustainable almond cultivation, based on the FAO land suitability criteria. The research explored the existing areas of almond cultivation and the land possessing the potential for almond cultivation in Lebanon using an analysis model developed on GIS. The evaluation of Land Suitability (LS) based on GIS and Multi-Criteria Evaluation methods (MCE) with Weighted Overlay (WO) was applied, and the almond suitability map was rendered using the seven following parameters: temperature, rainfall, slope, elevation, soil pH, soil texture, and soil depth. These variables were integrated through GIS and were allocated to different weights to each thematic layer, as per its relevance. Ultimately, the almond suitability map was established, comprising four categories: highly suitable, moderately suitable, marginally suitable, and not suitable. The obtained results indicated that almond cultivation areas were around 5500 ha in 2010, while more than 60% of the study area can be planted with almonds in accordance with the almond suitability map. In closing, the targeted decision-makers will potentially deem this study as a valid source of knowledge for planning land use, and a tool to mitigate land degradation. Full article

Accurate real-time information about soil moisture (SM) at a large scale is essential for improving hydrological modeling, managing water resources, and monitoring extreme weather events. This study presents a framework using convolutional long short-term memory (ConvLSTM) network to produce short- (1, 3, and 7 days ahead) and mid-term (14 and 30 days ahead) forecasts of SM at surface (0–10 cm) and subsurface (10–40 and 40–100 cm) soil layers across the contiguous U.S. The model was trained with five-year period (2018–2022) datasets including Soil Moisture Active Passive (SMAP) level 3 ancillary covariables, North American Land Data Assimilation System phase 2 (NLDAS-2) SM product, shortwave infrared reflectance from Moderate Resolution Imaging Spectroradiometer (MODIS), and terrain features (e.g., elevation, slope, curvature), as well as soil texture and bulk density maps from the Soil Landscape of the United States (SOLUS100) database. To develop and evaluate the model, the dataset was divided into three subsets: training (January 2018–January 2021), validation (2021), and testing (2022). The outputs were validated with observed in situ data from the Soil Climate Analysis Network (SCAN) and the United States Climate Reference Network (USCRN) soil moisture networks. The results indicated that the accuracy of SM forecasts decreased with increasing lead time, particularly in the surface (0–10 cm) and subsurface (10–40 cm) layers, where strong fluctuations driven by rainfall variability and evapotranspiration fluxes introduced greater uncertainty. Across all soil layers and lead times, the model achieved a median unbiased root mean square error (ubRMSE) of 0.04 cm³ cm⁻³ with a Pearson correlation coefficient of 0.61. Further, the performance of the model was evaluated with respect to both land cover and soil texture databases. Forecast accuracy was highest in coarse-textured soils, followed by medium- and fine-textured soils, likely because the greater penetration depth of microwave observations improves SM retrieval in sandy soils. Among land cover types, performance was strongest in grasslands and savannas and weakest in dense forests and shrublands, where dense vegetation attenuates the microwave signal and reduces SM estimation accuracy. These results demonstrate that the ConvLSTM framework provides skillful short- and mid-term forecasts of surface and subsurface soil moisture, offering valuable support for large-scale drought and flood monitoring. Full article

Urban pluvial waterlogging has become a major challenge for densely populated cities due to increasingly extreme rainfall events and the rapid expansion of impervious surfaces. In response to the growing demand for localized waterlogging risk assessments, an automated evaluation framework is proposed that integrates high-resolution digital elevation models (DEMs), rainfall scenarios, and classified building data within a GIS-based modeling system. The methodology consists of four modules: (i) design of rainfall scenarios and runoff estimation, (ii) waterlogging depth simulation based on volume-matching algorithms, (iii) construction of depth–damage curves for residential and commercial buildings, and (iv) building-level economic loss estimation though differentiated depth–damage functions for residential/commercial assets—a core innovation enabling sector-specific risk precision. A case study was conducted in the Lixia District, Jinan City, China, involving 15,317 buildings under a 50-year return period rainfall event. The total economic losses were shown to reach approximately USD 327.88 million, with residential buildings accounting for 88.6% of the total. The model achieved a mean absolute percentage error within 5% for both residential and commercial cases. The proposed framework supports high-precision, building-level urban waterlogging damage assessment and demonstrates scalability for use in other high-density urban areas. Note: all monetary values were converted from Chinese Yuan (CNY) to U.S. Dollars (USD) using an average exchange rate of 1 USD = 7.28 CNY. Full article

The growing frequency of extreme rainstorms has increasingly exposed tunnels to flooding risks, underscoring the urgent need for effective flood prevention and drainage measures. In this context, an evaluation framework for tunnel flood hazards was developed based on three criteria—hazard-inducing factors, hazard-formative environment, and disaster-bearing body—encompassing nine specific indicators. This study employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to construct a causal analysis model and assess the interrelationships and influence levels of risk factors associated with tunnel flooding disasters. Rainfall intensity (C1), rainfall duration (C2), ground elevation (C4), road slope (C5), and impervious surface area (C6) exhibit high causal values, acting as external input factors that drive the occurrence of tunnel flooding incidents. Conversely, water depth (C3), tunnel drainage capacity (C7), emergency flood control measures (C8), and infrastructure aging (C9) display high centrality values, serving as internal factors that reflect the tunnel’s flood prevention capability and determine the extent of disaster losses. Simply enhancing tunnel drainage capacity from the perspective of internal factors alone is insufficient; optimizing the tunnel’s flood resilience requires a combined consideration of both internal and external factors. Full article

This study examines the deformation and failure mechanisms of two reservoir bank landslides: the traction-type Baijiabao landslide and the translational Baishuihe landslide. Based on long-term monitoring data and a hydro-mechanical coupled numerical model of rainfall infiltration, we investigate the impact of crack depth on landslide stability. Results show that the Baishuihe landslide exhibits translational failure, initiated at the rear by tension cracks and rear subsidence, followed by toe uplift, whereas the Baijiabao landslide displays traction-type progressive failure, starting with toe erosion and later developing rear-edge cracks. Rainfall induces similar seepage patterns in both landslides, with infiltration concentrated at the crest, toe, and convex terrain areas. As crack depth increases, soil saturation near the cracks decreases nonlinearly, while the base remains saturated. However, displacement responses differ: Traction-type landslides exhibit opposing lateral movements with minimal vertical displacement. In contrast, translational landslides show displacement increasing with crack depth, dominated by gravity. These findings guide targeted mitigation: traction-type landslides require crack control and toe protection, while translational landslides need measures to block thrust transfer and monitor deep slip surfaces. This study offers new insights into the effect of crack depth on landslide stability, contributing to improved landslide hazard assessment and management. Full article

This study examines the impact of recent climatic trends on the preservation of submerged wooden structures at the Gran Carro archaeological site in Lake Bolsena, Italy. Climatic data from the Bolsena Meteorological Station were analysed alongside in situ water quality measurements collected near the archaeological remains at a depth of 4 m. The key parameters included water temperature (Tw), redox potential (Eh), dissolved oxygen (DO), and total dissolved solids (TDS). Trend analyses using the Mann–Kendall test and Sen’s slope revealed significant increases in air and water temperatures, which were strongly correlated. Although precipitation exhibited an upward trend, its negative correlation with temperature suggests greater variability rather than a stable water supply. Despite increased rainfall, lake levels showed a significant decline, likely due to intensified evaporation and water extraction for irrigation. UAV surveys confirmed recent lowering of the lake’s water surface during drought periods. Among the limnological parameters, dissolved oxygen saturation declined significantly, while redox potential increased, indicating shifts toward more anaerobic conditions. These environmental changes could promote the activity of erosive bacteria that degrade submerged wood. Conversely, increased evaporation might also enhance oxygen penetration at depth, potentially activating decay agents such as soft rot fungi and wood-boring bacteria. Overall, the findings suggest that ongoing climatic changes are adversely affecting the preservation of submerged wooden structures, highlighting the need for adaptive management strategies to protect both the lake ecosystem and its archaeological heritage. Full article

Investigating rainfall infiltration mechanisms and slope stability dynamics under varying vegetation cover conditions is essential for advancing ecological slope protection methodologies. This research focuses on large-scale outdoor slope models, with the objective of monitoring soil moisture variations in real-time during rainfall events on four types of slopes: bare, herbaceous, shrub, and mixed herb–shrub planting. Combining direct shear tests for unsaturated soil with numerical simulations, and considering the weakening effect of water on shear strength, this study analyzes slope stability. The findings reveal significant spatial variations in rainfall infiltration rates, with maximum values recorded at a burial depth of 0.2 m, declining as the burial depth increases. Different types of vegetation have distinct impacts on slope infiltration patterns: herbaceous increases cumulative infiltration by 21.32%, while shrub reduces it by 61.06%. The numerically simulated moisture content values demonstrate strong congruence with field-measured data. Compared with monoculture herbaceous or shrub root systems, the mixed herb–shrub root system exhibits the most significant enhancement effects on shear strength parameters. Under high water content conditions, root systems demonstrate substantially greater improvement in cohesion than in internal friction angle. Before rainfall, shrub vegetation contributed the most significant improvement to the safety factor, increasing it from 2.766 to 3.046, followed by herbaceous and mixed herb–shrub vegetation, which raised it to 2.81 and 2.948. After rainfall, mixed herb–shrub vegetation demonstrated the greatest enhancement of the safety factor, elevating it from 1.139 to 1.361, followed by herbaceous and shrub vegetation, which increased it to 1.192 and 1.275. The study offers preliminary insights and a scientific basis for the specific conditions tested for selecting and optimizing eco-friendly slope protection measures. Full article

The reactivation of the Longdongpo ancient colluvial landslide in Sinan County, Guizhou Province represents a typical multi-factor coupled failure. Based on detailed geological investigations and FLAC^3D fluid–solid coupling numerical simulations, this study reveals its complex reactivation mechanisms. The analysis demonstrates that long-term groundwater action has significantly weakened the slip zone at the soil–bedrock interface, causing strength degradation and inducing prolonged quasi-stable creep deformation of the slope. The artificial cut slopes formed in the middle-to-lower sections disrupted the original stress field and induced localized plastic deformation. Crucially, the numerical simulation identified a 5 m rainfall infiltration depth as the threshold triggering abrupt instability; when exceeding this critical value (simulated as 10 m and 16 m infiltration depths), pore water pressure surged (>2.7 MPa) and displacement dramatically increased (>2.2 m), reducing shear strength along the potential failure surface to critical levels. This process culminated in the full connection of the shear surface and the landslide’s catastrophic reactivation. This work quantitatively elucidates the chain-reaction mechanism of “long-term groundwater weakening → engineering disturbance initiation → critical-depth rainfall infiltration triggering”, providing vital quantitative evidence for regional ancient landslide risk prevention. Full article

With climate change, the frequency and severity of localized heavy rainfalls are increasing. Thus, for urban drainage networks (UDNs), particularly those in aging cities such as Seoul, Republic of Korea, flood risk management challenges are mounting. Conventional design standards typically apply uniform roughness coefficients based on new pipe conditions, neglecting the ongoing performance degradation from physical influences. This study introduces a methodology that systematically incorporates pipe age and size into roughness coefficient scenarios for higher-accuracy 1D–2D rainfall–runoff hydrologic–hydraulic simulations. Eleven roughness scenarios (a baseline and ten aging-based scenarios) are applied across seven UDNs using historical rainfall data. The most representative scenario (S3) is identified using a Euclidean distance metric combining the peak water-level error and root mean square error. For two rainfall events, S3 yields substantial increases in the simulated mean flood volumes (75.02% and 76.45%) compared with the baseline, while spatial analysis reveals significantly expanded inundation areas and increased flood depths. These findings underscore the critical impact of pipe deterioration on hydraulic capacity and demonstrate the importance of incorporating aging infrastructure into flood modeling and UDN design. This approach offers empirical support for updating UDN design standards for more resilient flood management. Full article

This study aims to analyse the effect of partially clogged inlets on the behaviour of urban drainage systems at the city scale, particularly regarding intercepted volumes and flood depths. The main challenges were to represent the inlet network in detail at a rather large scale and to avoid the effect of sewer network surcharging on the draining capacity of inlets. This goal has been achieved through a 1D/2D coupled hydraulic model of the whole urban drainage system in La Almunia de Doña Godina (Zaragoza, Spain). The model focuses on the interaction between grated drain inlets and the sewer network under partial clogging conditions. The model is fed with data obtained on field surveys. These surveys identified 948 inlets, classified into 43 types based on geometry and grouped into 7 categories for modelling purposes. Clogging patterns were derived from field observations or estimated using progressive clogging trends. The hydrological model combines a semi-distributed approach for micro-catchments (buildings and courtyards) and a distributed “rain-on-grid” approach for public spaces (streets, squares). The model assesses the impact of inlet clogging on network performance and surface flooding during four rainfall scenarios. Results include inlet interception volumes, flooded surface areas, and flow hydrographs intercepted by single inlets. Specifically, the reduction in intercepted volume ranged from approximately 7% under a mild inlet clogging condition to nearly 50% under severe clogging conditions. Also, the model results show the significant influence of the 2D mesh detail on flood depths. For instance, a mesh with high resolution and break lines representing streets curbs showed a 38% increase in urban areas with flood depths above 1 cm compared to a scenario with a lower-resolution 2D mesh and no curbs. The findings highlight how inlet clogging significantly affects the efficiency of urban drainage systems and increases the surface flood hazard. Further novelties of this work are the extent of the analysis (city scale) and the approach to improve the 2D mesh to assess flood depth. Full article