Search Results (3,292)

Inland depression irrigation districts in the arid regions of Xinjiang, owing to the absence of natural drainage conditions, exhibit unique groundwater-salt dynamics and face prominent risks of soil salinization, thus necessitating clarification of their water-salt transport mechanisms to ensure sustainable agricultural development. This study takes the Karamay Agricultural Comprehensive Development Zone as the research subject. The study examines the distribution characteristics of soil salinity, groundwater depth, and Total Dissolved Solids (TDS) of groundwater across diverse soil textures, elucidates the correlative relationships between groundwater dynamics and soil salinity, and forecasts the evolutionary trajectory of groundwater levels within the irrigation district. The findings reveal that groundwater depth in silty soil regions (3.24–3.11 m) substantially exceeds that in silty clay regions (2.43–2.61 m), whereas TDS of groundwater demonstrates marginally elevated concentrations in silty clay areas (19.05–16.78 g L⁻¹) compared to silty soil zones (18.18–16.29 g L⁻¹). Soil salinity exhibits pronounced surface accumulation phenomena and considerable inter-annual seasonal variations: manifesting a “spring-peak, summer-trough” pattern in 2023, which inversely transitioned to a “summer-peak, spring-trough” configuration in 2024, with salinity hotspots predominantly concentrated in silty clay distribution zones. A significant sigmoid functional relationship emerges between soil salinity and groundwater depth (R² = 0.73–0.77), establishing critical depth thresholds of 2.44 m for silty soil and 2.72 m for silty clay, beneath which the risk of secondary salinization escalates dramatically. The XGBoost model demonstrates robust predictive capability for groundwater levels (R² = 0.8545, MAE = 0.4428, RMSE = 0.5174), with feature importance analysis identifying agricultural irrigation as the predominant influencing factor. Model projections indicate that mean groundwater depths across the irrigation district will decline to 2.91 m, 2.76 m, 2.62 m, and 2.36 m over the ensuing 1, 3, 5, and 10 years, respectively. Within a decade, 73.33% of silty soil regions and 92.31% of silty clay regions will experience groundwater levels below critical thresholds, subjecting the irrigation district to severe secondary salinization threats. Consequently, comprehensive mitigation strategies encompassing precision irrigation management and enhanced drainage infrastructure are imperative. Full article

Agricultural production remains highly susceptible to water-related risks, such as drought and flooding. Although hydrologic forecasting systems, such as the National Water Model (NWM), have advanced considerably, their outputs are rarely used for real-time agricultural decision-making. This study developed the Agricultural Water Risk Indicator (AWRI), a framework that translates NWM streamflow forecasts into crop-specific risk assessment indicators. The AWRI framework has three key components: (1) the hydrological threat and exposure characterization based on NWM streamflow forecasts (B1); (2) crop sensitivity by growth stage and water needs (B2); and (3) adaptive capacity reflecting the presence of irrigation or drainage infrastructure (B3). The AWRI was evaluated across three NWM reach IDs covering five farm sites in the Black Belt region of Alabama, USA. The results show that the AWRI captured variations in hydrologic conditions, risk, and crop tolerance across the research sites within the one- to four-week forecast range. Crops in the reproductive stage were especially sensitive. Without resilience measures, up to 55% of the crops simulated at some sites had high-risk AWRI categories. Including irrigation or drainage decreased risk scores by one to two levels. The AWRI tool provides farmers and stakeholders with critical information to support proactive agricultural water management. Full article

Wheat (Triticum aestivum L.) is a strategic food crop for arid, hot regions such as the Arabian Peninsula, the Middle East, and North Africa. In these areas, production is limited by extreme environmental and agronomic conditions, leading to heavy dependence on imported wheat. Irrigation is often essential for successful cultivation, but available water sources are frequently saline. This study evaluated the comparative effects of irrigation salinity and genotype on agronomic performance, physiological responses, and grain quality. Nine Syrian wheat genotypes and one French bread-making cultivar, Florence Aurora, were grown in sandy soil under three irrigation salinity levels (2.6, 10, and 15 dS m⁻¹) across two seasons at the International Center for Biosaline Agriculture (Dubai, UAE). Salinity strongly negatively impacted yield, which decreased by 61% from the control to 15 dS m⁻¹, along with key yield components such as thousand grain weight and total biomass. Physiological traits, including carbon isotope composition (δ¹³C) and Na concentrations in roots, shoots and grains, increased significantly with salinity, while chlorophyll content showed a modest decline. Effects on grain quality were relatively minor: total nitrogen concentration and most mineral levels increased slightly, mainly due to a passive concentration effect associated with reduced TGW. Genotypes varied significantly in yield, biomass, TGW, physiological traits, and grain quality. The highest-yielding genotypes under control conditions (ACSAD 981 and ACSAD 1147) also performed best under saline conditions, and no trade-off was observed between yield and grain quality parameters (TGW, nitrogen, zinc, and iron concentrations). Separate analyses conducted for control and saline treatments identified different drivers of genotypic variability. Under control conditions, chlorophyll content, closely linked with δ¹³C, was the best predictor of genotypic differences and was positively correlated with yield across genotypes. Under salinity stress, grain magnesium (Mg) concentration was the strongest predictor, followed by grain δ¹³C, with both traits positively correlated with yield. These findings highlight key physiological traits linked to salinity tolerance and offer insights into the mechanisms underlying genotypic variability under both optimal and saline irrigation conditions. Full article

This study analyzed the carbon reduction effects of water-saving irrigation based on panel data of Chinese provinces from 2010 to 2020. Carbon emissions from irrigation were calculated and decomposed using the Malmquist index and LMDI. Results indicate that, first, the accounting results show a downward trend in estimated agricultural irrigation carbon emissions over the study period under a fixed-parameter framework. The average irrigation carbon intensity exhibits a declining pattern, particularly after the mid-2010s, with differences between provinces narrowing. Second, water-saving irrigation is associated with lower levels of estimated agricultural irrigation carbon emissions within the accounting framework by improving water-use efficiency and reducing irrigation water consumption per unit area, ultimately leading to a decrease in total carbon emissions. Finally, the carbon reduction effects are more pronounced and stable in major grain-producing regions. This study highlights regional heterogeneity in the emission-accounting outcomes associated with water-saving irrigation, which may provide descriptive evidence for discussions on region-specific irrigation management under different regional contexts. Full article

The Arid Region of Northwest China (ARNC) functions as a critical ecological barrier for the Eurasian hinterland. To clarify the non-linear drivers of eco-environmental dynamics, a long-term (2000–2024) Remote Sensing Ecological Index (RSEI) time series was constructed and analyzed using an interpretable machine learning framework (XGBoost-SHAP). The analysis reveals pronounced spatial asymmetry in ecological evolution: improvements are concentrated in localized, human-managed areas, while degradation occurs as a diffuse process driven by geomorphological inertia. The ARNC exhibits low-level stability (mean RSEI 0.25–0.30) and marked unbalanced dynamics, with significant degradation (19.9%) affecting more than twice the area of improvement (6.5%). Attribution analysis identifies divergent driving mechanisms: ecological improvement (R² = 0.559) is primarily anthropogenic (58.3%), whereas degradation (R² = 0.692) is mainly governed by natural constraints (58.4%), particularly structural topographic factors, where intrinsic landscape vulnerability is exacerbated by human activities. SHAP analysis corroborates a “Greenness-Quality Paradox” in stable agroecosystems, where high vegetation cover coincides with reduced evaporative cooling and secondary salinization from irrigation, resulting in declining Eco-Environmental Quality (EEQ). A zero-threshold effect for grazing intensity is also identified, indicating that any increase beyond the baseline immediately initiates ecological decline. In response, a Resist-Accept-Direct (RAD) framework is proposed: direct salt-water balance regulation in oases, resist hydrological cutoff in ecotones, and accept natural dynamics in the desert matrix. These findings provide a scientific basis for reconciling artificial greening initiatives with hydrological sustainability in water-limited regions. Full article

The use of unconventional water sources, such as those from marine desalination plants, is challenging for agriculture due to boron concentrations exceeding 0.5 mg L⁻¹, which can impact crop yield and quality. To ensure sustainability, it is crucial to understand crop responses to high boron levels and to develop strategies to mitigate its toxic effects. This study evaluated the impact of irrigation with a nutrient solution containing 15 mg L⁻¹ of boron on tomato plants (Solanum lycopersicum L.). To modulate the physiological effects of boron toxicity, two biostimulant products based on an extract from the brown alga Laminaria digitata and other active ingredients were applied foliarly. Agronomic, nutritional, and metabolic parameters were analyzed, including total yield, number of fruits per plant, and fruit quality. Additionally, mineral analysis and metabolomic profiling of leaves and fruits were performed, focusing on amino acids, organic acids, sugars, and other metabolites. A control treatment was irrigated with a nutrient solution containing 0.25 mg L⁻¹ of boron. The results showed that a boron concentration of 15 mg L⁻¹ significantly reduced total yield by 45% and significantly decreased fruit size and firmness. Mineral and metabolomic analyses showed significant reductions in Mg and Ca concentrations, significant increases in P and Zn levels, excessive boron accumulation in leaves and fruits, and significant changes in metabolites associated with nitrogen metabolism and the Krebs cycle. Biostimulant application did not significantly improve agronomic performance, likely due to high boron accumulation in the leaves, although significant changes were detected in leaf nutritional status and metabolic profiles. Full article

In Europe, due to reduced availability and efficacy of active ingredients, strategies against grapevine pests based on alternative tools to synthetic pesticides need to be developed. So far, attention has been mainly focused on biological control (arthropod natural enemies and entomopathogens) and mating disruption, but other means can also help keep pests below economic injury levels. This paper aims to review information on the direct effects of farmers’ choices on grapevine pest populations, ranging from vineyard design (e.g., growing habitat, grapevine cultivar, and training system) to annual agronomic practices (e.g., fertilization, irrigation, and pruning), and specific cultural and physical methods. Information was based on the CABI Digital Library, websites and books on grapevine pests. The data presentation is based on control strategies rather than pests, as it was considered more important to focus on the mode of action of different practices and to know which pests they affect simultaneously. The widespread availability of insecticides has long led to the neglect of the potential of cultural practices, which can effectively integrate other pest control tools. Full article

This study investigates the effects of nitrogen application and sprinkler irrigation on winter wheat growth, water use efficiency (WUE), and yield formation under dry-hot wind stress. The primary aim was to understand how nitrogen levels influence canopy structure, soil water–nitrogen coupling, and yield components under varying irrigation conditions. Field experiments were conducted with different nitrogen rates (N1, N2, N3, N4, N5) and sprinkler irrigation under heat stress. Plant height, leaf area index (LAI), canopy interception, and stemflow were measured, along with soil moisture and nitrogen content in the root zone. Results indicate that moderate nitrogen application (212 kg N ha⁻²) optimized yield and WUE, with a significant enhancement in canopy structure and water interception. High nitrogen levels resulted in increased water consumption but decreased nitrogen use efficiency (NUE), while lower nitrogen treatments showed reduced yield stability under heat stress. The findings suggest that balanced nitrogen management, in combination with timely irrigation, is essential for improving winter wheat productivity under climate stress. This study highlights the importance of optimizing water and nitrogen inputs to achieve sustainable wheat production in regions facing increasing climate variability. Full article

This study investigates a water–energy investment in the Consorzio di Bonifica della Romagna Occidentale (Northern Italy) over the period 2015–2022, analysing how integrated irrigation and energy infrastructures can support agricultural resilience. In this area, pressurised irrigation systems are increasingly replacing traditional gravity-fed networks, enabling precise water distribution. However, their energy intensity raises operational costs and exposure to volatile electricity prices. To address these challenges, the research evaluates the coupling of pressurised irrigation with floating photovoltaic (PV) systems on irrigation reservoirs. Using plot-level economic data for vineyards and orchards, the analysis shows that, although pressurised systems entail higher costs in terms of Relative Water Cost (RWC) and Economic Water Productivity Ratio (EWPR), integrating them with PV production significantly improves economic performance. The findings show an average reduction in RWC of 1.44% for vineyards and 5.52% for orchards, and an average increase in EWPR of 38.51 units for vineyards and 24.81 units for orchards. This suggests that combining efficient irrigation systems with renewable energy could represent a viable pathway toward more sustainable water management. Policy implications may concern incentives for joint water–energy investments, adjustments to zero-injection rules, and broader reforms in agricultural, energy, and environmental policies. Full article

Efficient irrigation planning in data-scarce regions remains challenging due to limited access to localized meteorological data, reliance on complex computer-based models, and the technical knowledge required to deploy them at the field scale. Hence, the need for accessible, smartphone-based tools that simplify soil water balance calculations using public data to support practical decision-making in resource-limited contexts. This smartphone-based application estimates Net and Gross Irrigation Requirements using a Soil Water Balance (SWB) framework. The app combines region-specific empirical formulations for Effective Rainfall (Pe) calculation. The application utilizes user-supplied crop and irrigation parameters and meteorological data available in the public domain and operates at multiple temporal scales (daily, 10-day, weekly, and monthly), thereby supporting flexible irrigation schedules. The performance of app was evaluated through simulation-based benchmarking against FAO-CROPWAT 8.0 using harmonized inputs across five representatives agro-climatic region: Central India, Southern Vietnam, Northern Thailand, Western Bangladesh, and Central Sri Lanka. Quantitative comparison showed deviations within ±5% for Effective Rainfall, crop evapotranspiration, Net Irrigation, and Gross Irrigation, and low mean bias values (−2.8% to +3.3%) show the absence of systematic over- or under-estimation compared to CROPWAT model. The application also demonstrated responsiveness to climatic variability. Although the validation is limited to few representative locations and assumed minimal runoff conditions, the results suggest that the proposed method is technically consistent and feasible in practice. This study demonstrates smartphone-based application as a decision support for field-level irrigation planning and water resource management, particularly in data-limited agricultural contexts. Full article

A two-factor experiment was conducted using the cultivar ‘Xin you No. 2’ (Citrullus lanatus) to identify an efficient and green production model for drip-irrigated watermelon under plastic mulch in Southern Xinjiang. A basal organic fertilizer was applied at 2250 kg·ha⁻¹. The experimental design comprised three irrigation levels, maintaining soil moisture at 60–70% (W1), 70–80% (W2), and 80–90% (W3) of field capacity, and three nitrogen application rates: 180 (N1), 240 (N2), and 300 (N3) kg·ha⁻¹. This study systematically investigated the effects of water–nitrogen coupling on watermelon yield, quality, water use efficiency, and nitrogen partial factor productivity. The W2N2 treatment achieved the highest yield of 64,617.59 kg·ha⁻¹. Vine length, stem diameter, and dry matter accumulation increased with increasing nitrogen application under the W1 and W2 irrigation levels, but exhibited an initial increase followed by a decrease under the W3 condition. Water restriction combined with increased nitrogen application significantly enhanced the central sugar content, with the W1N3 treatment increasing it by 15.69% compared to CK. Conversely, the W1N1 treatment was most conducive to vitamin C accumulation, showing a 49.88% increase over CK. The total water consumption across the different treatments ranged from 362.12 to 493.92 mm. Both water use efficiency and irrigation water use efficiency reached their maximum values under the W1N3 treatment, at 21.94 kg·m⁻³ and 35.05 kg·m⁻³, respectively. In contrast, the highest partial factor productivity of nitrogen (NPFP) was observed under W3N1, reaching 239.33 kg·kg⁻¹. A comprehensive multi-index evaluation using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method indicated that the W1N3 treatment achieved the highest relative closeness (0.669), identifying it as the optimal water–nitrogen combination. Full article

Addressing the challenges of low resource-use efficiency and supply–demand mismatch in Hami melon production, this study investigated the interactive effects of irrigation and fertilization to identify an optimal regime that balances yield, water conservation, and resource-use efficiency (i.e., water use efficiency and fertilizer partial factor productivity). A greenhouse experiment was conducted in Hami, Xinjiang, employing a two-factor design with five irrigation levels (W1–W5: 60–100% of full irrigation) and three fertilization levels (F1–F3: 80–100% of standard rate), replicated three times. Growth parameters, yield, water use efficiency (WUE), and partial factor productivity of fertilizer (PFP) were evaluated and comprehensively analyzed using the entropy-weighted TOPSIS method, regression analysis, and the NSGA-II multi-objective genetic algorithm. Results demonstrated that irrigation volume was the dominant factor influencing growth and yield. The W4F3 treatment (90% irrigation with 100% fertilization) achieved the optimal outcome, yielding 75.74 t ha⁻¹—a 9.71% increase over the control—while simultaneously enhancing WUE and PFP. Both the entropy-weighted TOPSIS evaluation (C = 0.998) and regression analysis (optimal irrigation level at w = 0.79, ~90% of full irrigation) identified W4F3 as superior. NSGA-II optimization further validated this, generating Pareto-optimal solutions highly consistent with the experimental optimum. The model-predicted optimal regime for greenhouse Hami melon in Xinjiang is an irrigation amount of 3276 m³ ha⁻¹ and a fertilizer application rate of 814.8 kg ha⁻¹. This regime facilitates a 10% reduction in irrigation water and a 5% reduction in fertilizer input without compromising yield, alongside significantly improved resource-use efficiencies. Full article

Maize is one of the top three crops globally, ranking only behind rice and wheat, making it an important crop of interest. Aboveground biomass is a key indicator for assessing maize growth and its yield potential. This study developed an efficient and stable biomass prediction model to estimate the aboveground biomass (AGB) of spring maize (Zea mays L.) under subsurface drip irrigation in arid regions, based on UAV multispectral remote sensing and machine learning techniques. Focusing on typical subsurface drip-irrigated spring maize in arid Xinjiang, multispectral images and field-measured AGB data were collected from 96 sample points (selected via stratified random sampling across 24 plots) over four key phenological stages in 2024 and 2025. Sixteen vegetation indices were calculated and 40 texture features were extracted using the gray-level co-occurrence matrix method, while an integrated feature-selection strategy combining Elastic Net and Random Forest was employed to effectively screen key predictor variables. Based on the selected features, six machine learning models were constructed, including Elastic Net Regression (ENR), Gradient Boosting Decision Trees (GBDT), Gaussian Process Regression (GPR), Partial Least Squares Regression (PLSR), Random Forest (RF), and Extreme Gradient Boosting (XGB). Results showed that the fused feature set comprised four vegetation indices (GRDVI, RERVI, GRVI, NDVI) and five texture features (R_Corr, NIR_Mean, NIR_Vari, B_Mean, B_Corr), thereby retaining red-edge and visible-light texture information highly sensitive to AGB. The GPR model based on the fused features exhibited the best performance (test set R² = 0.852, RMSE = 2890.74 kg ha⁻¹, MAE = 1676.70 kg ha⁻¹), demonstrating high fitting accuracy and stable predictive ability across both the training and test sets. Spatial inversions over the two growing seasons of 2024 and 2025, derived from the fused-feature GPR optimal model at four key phenological stages, revealed pronounced spatiotemporal heterogeneity and stage-dependent dynamics of spring maize AGB: the biomass accumulates rapidly from jointing to grain filling, slows thereafter, and peaks at maturity. At a constant planting density, AGB increased markedly with nitrogen inputs from N0 to N3 (420 kg N ha⁻¹), with the high-nitrogen N3 treatment producing the greatest biomass; this successfully captured the regulatory effect of the nitrogen gradient on maize growth, provided reliable data for variable-rate fertilization, and is highly relevant for optimizing water–fertilizer coordination in subsurface drip irrigation systems. Future research may extend this integrated feature selection and modeling framework to monitor the growth and estimate the yield of other crops, such as rice and cotton, thereby validating its generalizability and robustness in diverse agricultural scenarios. Full article

This study investigates the effects of saline reclaimed water recharge on soil salt accumulation and water migration in Xinjiang, China, aiming to provide scientific guidance for the sustainable utilization of reclaimed water in arid regions. Indoor vertical infiltration simulation experiments were conducted using reclaimed water with varying salinity levels (0, 1, 2, 3, and 4 g L⁻¹) to evaluate their impacts on soil water–salt distribution and infiltration dynamics. Results showed that irrigation with saline reclaimed water increased soil pH and significantly enhanced both the infiltration rate and wetting front migration velocity, while causing only minor changes in the moisture content of the wetted zone. When the salinity was 2 g L⁻¹, the observed improvement effect was the most significant. Specifically, the cumulative infiltration increased by 22.73% after 180 min, and the time required for the wetting peak to reach the specified depth was shortened by 21.74%. At this salinity level, the soil’s effective water storage capacity reached 168.19 mm, with an average moisture content increase of just 6.20%. Soil salinity increased with the salinity of the irrigation water, and salts accumulated at the wetting front as water moved downward, resulting in a characteristic distribution pattern of desalination in the upper layer and salt accumulation in the lower layer. Notably, reclaimed water recharge reduced soil salinity in the 0–30 cm layer, with salinity in the 0–25 cm layer decreasing below the crop salt tolerance threshold. When the salinity of the reclaimed water was ≤2 g L⁻¹, the salt storage in the 0–30 cm layer was less than 7 kg ha⁻¹, achieving a desalination rate exceeding 60%. Reclaimed water with a salinity of 2 g L⁻¹ enhanced infiltration (wetting front depth increased by 27.78%) and desalination efficiency (>60%). These findings suggest it is well suited for urban greening and represents an optimal choice for the moderate reclamation of saline-alkali soils in arid environments. Overall, this study provide a reference for the water quality threshold and parameters of reclaimed water for urban greening, farmland irrigation, and saline land improvement. Full article

The imbalance between water supply and demand in the arid and semi-arid regions of northwest China has become increasingly severe, highlighting the urgent need to develop and utilize unconventional water resources. Return flow, originating from canal leakage and field drainage, is widely distributed in these regions. However, as it contains a certain amount of salts, long-term use of return flow can lead to soil salinization and degradation of soil structure. Therefore, the scientific utilization of return flow has become a key issue for achieving sustainable agricultural development and efficient water use in arid areas. This study was conducted in the Yinbei Irrigation District, Ningxia, northwest China. Water samples were collected from the main and branch drainage ditches and analyzed to evaluate the feasibility of using return flow irrigation in the area. In addition, based on two years of continuous field monitoring and HYDRUS model simulations, the long-term dynamics of soil salinity under moderate return flow irrigation over the next 20 years were predicted. The results show that the total salinity of the main return ditches consistently remained below the agricultural irrigation water quality standard of 2000 mg/L, with Na⁺ and SO₄²⁻ as the predominant ions. Seasonal variations in return flow salinity were notable, with higher levels observed in spring compared to summer. Simulation results based on field trial data indicated that soil salinity displayed regular seasonal fluctuations. During the rice-growing season, strong leaching kept the salinity in the plough layer (0–40 cm) low. However, after irrigation ceased, evaporation in autumn and winter led to an increase in surface soil salinity, creating annual peaks. Long-term simulations showed that soil salinity throughout the entire profile (0–100 cm) followed a pattern of “slight increase—gradual decrease—dynamic stability.” Specifically, winter salinity peaks slightly increased during the first two years but then gradually declined, stabilizing after approximately 15 years. This indicates that long-term return-flow irrigation does not result in the accumulation of soil salinity in the plough layer. Full article