Search Results (442)

Soft soils, characterized by high compressibility, low shear strength, and high water sensitivity, pose serious challenges to geotechnical engineering in infrastructure projects. Traditional stabilization methods such as lime and cement face limitations, including environmental concerns and poor durability under chemical or cyclic loading. Ionic soil stabilizers (ISSs), which operate through electrochemical mechanisms, offer a promising alternative. However, their long-term performance—particularly under environmental stressors such as acid/alkali exposure and cyclic wetting–drying—remains insufficiently explored. This study evaluates the strength and durability of ISS-modified soil through a comprehensive experimental program, including direct shear tests, permeability tests, and cyclic wetting–drying experiments under neutral, acidic (pH = 4), and alkaline (pH = 10) environments. The results demonstrate that ISS treatment increases soil cohesion by up to 75.24% and internal friction angle by 9.50%, particularly under lower moisture conditions (24%). Permeability decreased by 88.4% following stabilization, resulting in only a 10–15% strength loss after water infiltration, compared to 40–50% in untreated soils. Under three cycles of wetting–drying, ISS-treated soils retained high shear strength, especially under acidic conditions, where degradation was minimal. In contrast, alkaline conditions caused a cohesion reduction of approximately 26.53%. These findings confirm the efficacy of ISSs in significantly improving both the mechanical performance and environmental durability of soft soils, offering a sustainable and effective solution for soil stabilization in chemically aggressive environments. Full article

Precipitation, as a key input in the water cycle, directly influences the formation and change process of runoff. Meanwhile, the return runoff intuitively reflects the available quantity of water resources in a river basin. An in-depth analysis of the evolution laws and response relationships between precipitation and return runoff over a long time scale serves as an important support for exploring the evolution of hydrometeorological conditions and provides an accurate basis for the scientific planning and management of water resources. Taking Lanzhou Station on the upper Yellow River as a typical case, this study proposes the VSSL (LSTM Fusion Method Optimized by SSA with VMD Decomposition) deep learning precipitation element series extension method and the SSVR (SVR Fusion Method Optimized by SSA) machine learning runoff element series extension method. These methods achieve a reasonable extension of the missing data and construct 100-year precipitation and return runoff series from 1921 to 2020. The research results showed that the performance of machine learning and deep learning methods in the precipitation and return runoff test sets is better than that of traditional statistical methods, and the fitting effect of return runoff is better than that of precipitation. The 100-year precipitation and return runoff series of Lanzhou Station from 1921 to 2020 show a non-significant upward trend at a rate of 0.26 mm/a and 0.42 × 10⁸ m³/a, respectively. There is no significant mutation point in precipitation, while the mutation point of return runoff occurred in 1991. The 100-year precipitation series of Lanzhou Station has four time-scale alternations of dry and wet periods, with main periods of 60 years, 20 years, 12 years, and 6 years, respectively. The 100-year return runoff series has three time-scale alternations of dry and wet periods, with main periods of 60 years, 34 years, and 26 years, respectively. During the period from 1940 to 2000, an approximately 50-year cycle, precipitation and runoff not only have strong common-change energy and significant interaction, but also have a fixed phase difference. Precipitation changes precede runoff, and runoff responds after a fixed time interval. Full article

Climate change presents urgent and complex challenges to agricultural sustainability and food security, particularly in regions reliant on resource-intensive staple crops. Smart agriculture—through the integration of crop modeling, satellite remote sensing, and artificial intelligence (AI)—offers data-driven strategies to enhance productivity, optimize input use, and mitigate greenhouse gas (GHG) emissions. This study introduces Farmdee-Mesook, a mobile-first smart agriculture platform designed specifically for Thai rice farmers. The platform leverages AquaCrop simulation, open-access satellite data, and localized agronomic models to deliver real-time, field-specific recommendations. Usability-focused design and no-cost access facilitate its widespread adoption, particularly among smallholders. Empirical results show that platform users achieved yield increases of up to 37%, reduced agrochemical costs by 59%, and improved water productivity by 44% under alternate wetting and drying (AWD) irrigation schemes. These outcomes underscore the platform’s role as a scalable, cost-effective solution for operationalizing climate-smart agriculture. Farmdee-Mesook demonstrates that digital technologies, when contextually tailored and institutionally supported, can serve as critical enablers of climate adaptation and sustainable agricultural transformation. Full article

Aiming at the economic problems of industrial users with wind power, photovoltaic, and small hydropower resources in clean energy consumption and trading with superior power grids, this paper proposes a distributed pumped storage capacity optimization configuration method considering clean energy systems. First, considering the maximization of the investment benefit of distributed pumped storage as the upper goal, a configuration scheme of the installed capacity is formulated. Second, under the two-part electricity price mechanism, combined with the basin hydraulic coupling relationship model, the operation strategy optimization of distributed pumped storage power stations and small hydropower stations is carried out with the minimum operation cost of the clean energy system as the lower optimization objective. Finally, the bi-level optimization model is solved by combining the alternating direction multiplier method and CPLEX solver. This study demonstrates that distributed pumped storage implementation enhances seasonal operational performance, improving clean energy utilization while reducing industrial electricity costs. A post-implementation analysis revealed monthly operating cost reductions of 2.36, 1.72, and 2.13 million RMB for wet, dry, and normal periods, respectively. Coordinated dispatch strategies significantly decreased hydropower station water wastage by 82,000, 28,000, and 52,000 cubic meters during corresponding periods, confirming simultaneous economic and resource efficiency improvements. Full article

Heavy metal contamination in paddy fields poses serious risks to food safety and crop productivity. This study evaluated the potential of native soil fungi as bioinoculants to reduce metal uptake in rice cultivated under contaminated conditions. Eight fungal strains—four indigenous and four allochthonous—were selected based on their plant growth-promoting traits, including siderophore production and phosphate solubilization. Additional metabolic analysis confirmed the production of bioactive secondary metabolites. In a greenhouse experiment, three rice cultivars were grown under permanent flooding (PF) and alternate wetting and drying (AWD) in soil enriched with arsenic, cadmium, chromium, and copper. Inoculation with indigenous fungi under AWD significantly reduced the arsenic accumulation in rice shoots by up to 75%. While AWD increased cadmium uptake across all cultivars, fungal inoculation led to a moderate reduction in cadmium accumulation—ranging from 15% to 25%—in some varieties. These effects were not observed under PF conditions. The results demonstrate the potential of native fungi as a nature-based solution to mitigate heavy metal stress in rice cultivation, supporting both environmental remediation and sustainable agriculture. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

This work investigated the effect of experimental conditions of dry and wet torrefaction on the properties of olive leaves and olive pomace. Torrefaction improved the fuel properties of olive waste. According to Van Krevelen parameters (O/C and H/C ratios), torrefied biomass, tested as solid biofuel, achieved a similar quality threshold to lignite. For example, dry torrefaction conducted at 230 °C for 80 min reduced the O/C and H/C ratios of olive leaves from 0.51 and 1.51 for raw biomass to 0.25 and 1.17 for torrefied biomass, respectively. Under the same conditions, the O/C and H/C ratios of olive pomace were also reduced from 0.34 and 1.60 to 0.27 and 1.36, respectively. Calorific values of raw olive leaves and olive pomace amounted to 18.0 and 23.2 MJ/kg, respectively. Following dry torrefaction and biomass conversion into biochar, calorific values of olive leaves and olive pomace increased by 24% and 14% up to 22.2 and 26.3 MJ/kg through dry torrefaction, compared with 17% and 23% increments up to 21.1 and 28.5 MJ/kg through wet torrefaction, respectively. Interestingly, biomass processing through wet torrefaction performed in a fluidized bed powered by superheated steam could be completed 8- to 12-fold more rapidly than dry torrefaction. SEM analysis indicated a breakdown of the surface structure of olive waste following the torrefaction process. According to the Brunauer–Emmett–Teller (BET) method, total pore surface areas of biochar obtained from wet torrefaction of olive pomace and olive leaves amounted to 3.6 m²/g and 0.8 m²/g, with total pore volumes amounting to 0.0225 cm³/g and 0.0103 cm³/g, respectively. Maximal contents of 5-hydroxymethylfurfural and furfural in liquid by-products from dry torrefaction amounted to 1930 and 1880 mg/1 kg, respectively. Alternately, in liquid by-products from wet torrefaction, concentrations of these high-value compounds remained very low. Full article

In arid agricultural production, exploring suitable water-saving irrigation strategies and analyzing their water-saving mechanisms are of great significance. Alternating partial root-zone drying irrigation (APRI), a water-saving strategy, enhances the water use efficiency (WUE) of alfalfa (Medicago sativa L.) This paper aims to clarify the physiological mechanisms by which the APRI method enhances the physiological WUE of alfalfa, as well as the differences between this water-saving irrigation strategy, conventional irrigation (CI), and their water deficit adjustments, in order to seek higher water use efficiency for alfalfa production in arid regions. In this experiment, alfalfa was used as the research subject, and three irrigation methods, CI, fixed partial root-zone drying (FPRI), and APRI, were set up, each paired with three decreasing moisture supply gradients of 90% water holding capacity (WHC) (W1), 70% WHC (W2), and 50% WHC (W3). Samples were taken and observed once after every three complete irrigation cycles. Through a comparative analysis of the growth status, leaf water status, antioxidant enzyme activity, and osmotic adjustment capabilities of alfalfa under different water supplies for the three irrigation strategies, the following conclusions were drawn: First, the APRI method, through artificially created periodic wet–dry cycles in the rhizosphere soil, provides pseudo-drought stress that enhances the osmotic adjustment capabilities and antioxidant enzyme activity of alfalfa leaves during the early to middle phases of irrigation treatment compared to CI and FPRI methods, resulting in healthier leaf water conditions. Secondly, the stronger drought tolerance and superior growth conditions of alfalfa under the APRI method due to reduced water availability are key factors in enhancing the water use efficiency of alfalfa under this strategy. Full article

Accelerating climate change poses significant risks to water security and ecological stability in arid regions due to the increasing frequency and intensity of extreme precipitation events. As a climate-sensitive area, the inland river basin (IRB) of Northwest China—a critical water source for local ecosystems and socioeconomic activities—remains insufficiently studied in terms of future extreme precipitation dynamics. This study evaluated the spatiotemporal evolution of extreme precipitation in the IRB under a new low radiative forcing scenario (SSP1-1.9) by employing four global climate models (GCMs: GFDL-ESM4, MRI-ESM2, MIROC6, and IPSL-CM6A-LR). Eight core extreme precipitation indices were analyzed to quantify changes during the near future (NF: 2021–2050) and far future (FF: 2071–2100) periods. Our research demonstrated that all four models were capable of capturing seasonal patterns and exhibited inherent uncertainty. The annual total precipitation (PRCPTOT) in mountainous regions showed minimal variation, while desert areas were projected to experience a 2-6-fold increase in precipitation in the NF and FF. The Precipitation Intensity Index (SDII) weakened by approximately −10% in mountainous areas but strengthened by around +10% in desert regions. Most mountainous areas showed an increase in the maximum consecutive dry days (CDD), whereas desert regions exhibited extended maximum consecutive wet days (CWD). Moderate rainfall (P1025) variations primarily ranged between −5% and +20%, with greater fluctuations in desert areas. Heavy rainfall (PG25) fluctuated between −40% and +40%, reflecting stark contrasts in extreme precipitation between arid basins and mountainous zones. The maximum 1-day precipitation (Rx1day) and maximum 5-day precipitation (Rx5day) both showed significant increases, which indicated heightened risks from extreme rainfall events in the future. Moreover, the IRB region experienced increased total precipitation, enhanced rainfall intensity, more frequent alternations between drought and precipitation, more frequent moderate-to-heavy rainfall days, and higher daily precipitation extremes in both the NF and FF periods. These findings provide critical data for regional development planning and emergency response strategy formulation. Full article

This study aimed to evaluate the performance and robustness of the GR2m “Génie Rural à 2 paramètres au pas du temps Mensuel” rainfall–runoff model for simulating streamflow under past and future hydrometeorological shifts in the Medjerda, a data-scarce Mediterranean catchment in northern Tunisia characterized by limited hydrometeorological records and high climate variability. The evaluation was conducted across three subcatchments characterized by contrasting climatic conditions and representing the hydrometeorological pattern of the Medjerda catchment. To assess the model’s robustness, a calibration–validation process was applied. This method alternated between dry and wet periods and evaluated model performance through various criteria. Subsequently, GR2m was adopted to simulate projected discharge, using projections from the “Model for Interdisciplinary Research on Climate 5” (MIROC5) under Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. Standardized climate indices (SCIs) were employed to assess climate change impacts. The results demonstrate that GR2m performs well in simulating streamflow across different climatic conditions within the Medjerda catchment and maintains satisfactory performance when calibrated over a non-stationary climate period. The findings indicate a continuous decline in projected runoff and suggest a significant increase in extreme drought events. Full article

Given the worsening global climate change that drives drought frequency and irrigation water shortages, implementing water-conserving practices like alternate wetting and drying (AWD) is now critically urgent. Biochar is widely used for soil carbon sequestration. However, there is limited information on the effects of biochar on soil organic carbon (SOC) and its labile fractions in paddy fields, especially under AWD. A two-year field experiment was conducted with two irrigation regimes (CF: continuous flooding irrigation; AWD) as the main plots and 0 (B₀) and 20 t ha⁻¹ (B₁) biochar as sub-plots. AWD had no effect on the SOC and particulate organic carbon (POC) content, but increased the dissolved organic carbon (DOC), microbial biomass carbon (MBC), easily oxidizable organic carbon (EOC), light fraction organic carbon (LFOC), and carbon pool management index (CPMI) at 0–10 cm depths, by 24.4–56.4%, 12.6–17.7%, 9.2–16.8%, 25.6–28.1%, and 11.3–18.6%, respectively. Biochar increased SOC while also increasing DOC, MBC, EOC, LFOC, POC, and CPMI at 0–20 cm depths, by 18.4–53.3%, 14.7–70.2%, 17.4–22.3%, 10.2–27.6%, 95.2–188.3%, 46.6–224%, and 5.6–27.2, respectively, making SOC more labile under AWD. Our results highlight that biochar still holds great potential for improving soil quality and carbon sequestration under AWD, and the combination of biochar and AWD can achieve the synergistic optimization of the food–water–carbon sequestration trade-off, which is beneficial to sustainable agricultural production. Full article

Intergovernmental Panel on Climate Change (IPCC) guidelines have been standardized and widely used to calculate methane (CH₄) emissions from paddy fields. The emission factor (EF) is a key parameter in these guidelines, and it is different for each location globally and regionally. However, limited studies have been conducted to measure locally specific EFs (EFlocal) through on-site assessments and modeling their spatial distribution effectively. This study aims to investigate the potential of multisensor satellite data to develop a spatial model of CH₄ emission estimation on rice paddy fields under different water management practices, i.e., continuous flooding (CF) and alternate wetting and drying (AWD) in Subang, West Java, Indonesia. The model employed the national EF (EFnational) and EFlocal using the IPCC guidelines. In this study, we employed the multisensor satellite data to derive the key parameters for estimating CH₄ emission, i.e., rice cultivation area, rice age, and EF. Optical high-resolution images were used to delineate the rice cultivation area, Sentinel-1 SAR imagery was used for identifying transplanting and harvesting dates for rice age estimation, and ALOS-2/PALSAR-2 was used to map the water regime for determining the scaling factor of the EF. The closed-chamber method has been used to measure the daily CH₄ flux rate on the local sites. The results revealed spatial variability in CH₄ emissions, ranging from 1–5 kg/crop/season to 20–30 kg/crop/season, depending on the water regime. Fields under CF exhibited higher CH₄ emissions than those under AWD, underscoring the critical role of water management in mitigating CH₄ emissions. This study demonstrates the feasibility of combining remote sensing data with the IPCC model to spatially estimate CH₄ emissions, providing a robust framework for sustainable rice cultivation and greenhouse gas (GHG) mitigation strategies. Full article

Despite the essential role of phosphorus (P) in rice growth, P-use efficiency (PUE) remains low due to limited bioavailable P in soils and an over-reliance on chemical fertilizers, leading to resource waste and environmental risks, such as eutrophication. This study investigates whether and how alternating wetting and moderate drying (AWMD) irrigation promotes P absorption and transport in rice. This study was conducted over two years using a pot experiment. Conventional flooding (CF) irrigation was applied throughout the growing season, while AWMD irrigation was imposed from two weeks after transplanting to one week before harvest. AWMD improved shoot biomass by 8.7–9.4% and the photosynthetic rate by 12–15%, significantly enhanced PUE, and optimized root traits and enzyme activities related to P uptake. It also promoted leaf acid phosphatase and ribonuclease activities, facilitating P remobilization to grains. In conclusion, AWMD enhanced the ability of roots to absorb P and optimized the redistribution of P between vegetative organs and grains, synergistically increasing grain yield and PUE in rice. Full article

Climate-induced wetting and drying (WD) cycles significantly affect the long-term performance of geotechnical structures. This study explores expansive Oxford clay’s mechanical and volumetric responses stabilised with ordinary Portland cement (OPC) and guar gum (GG) under repeated WD cycles. We prepared 108 samples in total—36 untreated, 36 treated with OPC, and 36 treated with GG. These samples were compacted to 90% of their maximum dry density and subjected to 1, 5, 10, and 15 WD cycles, with nine samples for each treatment at each cycle. During the WD cycles, we monitored volumetric strain and moisture content. Mechanical performance was assessed through unconsolidated undrained triaxial tests conducted at matric suctions of −1500 kPa, −33 kPa, and under saturated conditions. We evaluated the undrained shear strength (S_u), secant modulus of elasticity (E₅₀), and modulus of toughness (U_t). The results showed that OPC-treated samples consistently exhibited the highest S_u at −1500 kPa across all WD cycles, followed by untreated and GG-treated samples. At −33 kPa, OPC-treated samples again outperformed the others in S_u, while GG-treated samples performed better than the untreated ones. Under saturated conditions, GG-treated samples displayed a similar S_u to OPC-treated samples, significantly higher than untreated samples. Energy absorption capacity, measured through U_t, peaked for OPC-treated samples at −1500 kPa but favoured GG treatment at −33 kPa and under saturation. X-ray computed tomography (CT) revealed severe degradation in untreated samples, characterised by extensive cracking, minor cracking in OPC-treated samples, and minimal damage in GG-treated samples. This highlights the superior resilience of guar gum to wetting–drying cycles. These findings underscore the potential of guar gum as a sustainable alternative to cement for enhancing the WD resilience of expansive soils, particularly under low-suction or saturated conditions. Full article

With climate warming, the global precipitation patterns have undergone significant changes, which will profoundly impact flood–drought disaster regimes and socioeconomic development in key regions of human activity worldwide. The convergence zone of the Indian Ocean monsoon and Pacific monsoon in China covers most of the middle and lower reaches of the Yangtze River (MLRYR), which is located in the transitional area of the second and third steps of China’s terrain. Changes in precipitation patterns in this region will significantly impact flood and drought control in the MLRYR, as well as the socioeconomic development of the MLRYR Economic Belt. In this study, Huaihua area in China was selected as the study area to study the characteristics of regional precipitation change, and to analyze the evolution in the trends in annual precipitation, extreme precipitation events, and their spatiotemporal distribution, so as to provide a reference for the study of precipitation change patterns in the intersection zone. This study utilizes precipitation data from meteorological stations and the China Meteorological Forcing Dataset (CMFD) reanalysis data for the period 1979–2023 in Huaihua region. The spatiotemporal variation in precipitation in the study area was analyzed by using linear regression, the Mann–Kendall trend test, the moving average method, the Mann–Kendall–Sneyers test, wavelet analysis, and R/S analysis. The results demonstrate the following: (1) The annual precipitation in the study area is on the rise as a whole, the climate tendency rate is 9 mm/10 a, and the precipitation fluctuates greatly, showing an alternating change of “dry–wet–dry–wet”. (2) Wavelet analysis reveals that there are 28-year, 9-year, and 4-year main cycles in annual precipitation, and the precipitation patterns at different timescales are different. (3) The results of R/S analysis show that the future precipitation trend will continue to increase, with a strong long-term memory. (4) Extreme precipitation events generally show an upward trend, indicating that their intensity and frequency have increased. (5) Spatial distribution analysis shows that the precipitation in the study area is mainly concentrated in the northeast and south of Jingzhou and Tongdao, and the precipitation level in the west is lower. The comprehensive analysis shows that the annual precipitation in the study area is on the rise and has a certain periodic precipitation law. The spatial distribution is greatly affected by other factors and the distribution is uneven. Extreme precipitation events show an increasing trend, which may lead to increased flood risk in the region and downstream areas. In the future, it is necessary to strengthen countermeasures to reduce the impact of changes in precipitation patterns on local and downstream economic and social activities. Full article