Search Results (112)

Climate change has led to increased extreme weather events, such as severe droughts and intense rainfall, with regions in Portugal, like Alentejo and Algarve, being particularly affected. Understanding the influence of water availability in the concentration of phenolic compounds in autochthonous varieties could be an important tool to know how these varieties adapt to water scarcity. This work has been carried out with the aim to analyze the profile of phenolic compounds by HPLC-DAD in four Portuguese grape varieties (Tinta Gorda, Tinta Miúda, Tinta Caiada, and Moreto), cultivated under three irrigation regimes (water comfort, moderate water deficit, and rainfed). The results reveal that Tinta Gorda, Tinta Miúda, and Tinta Caiada varieties exhibit the higher concentrations of phenolic compounds under rainfed conditions. Among these, Tinta Miúda and Tinta Caiada stand out as the most promising varieties in terms of adaptability to water scarcity. Full article

Global climate changes have led to dramatic increases in drought durations in previously permanent streams, impacting the biodiversity and functioning of river ecosystems. However, the response of benthic diatom communities to hydrological intermittency remains poorly understood. In this study, we compared the taxonomic and functional compositions of the diatom communities between permanent and intermittent sections in two hilly stream systems in southwestern Hungary. Our results showed that both the taxonomic and functional compositions of diatom communities were significantly affected by changes in the hydrological regime, leading to a decline in species richness and diversity and functional richness in intermittent sections. Functional richness and dispersion decreased significantly with declining taxonomic richness, likely as a consequence of species loss driven by flow intermittency. Aquatic–subaerial diatoms with moderate oxygen requirements were indicative of intermittent sections, while large, occasionally aerophilic and oxybiontic diatoms characterized permanent sections. The relative abundance of low-profile diatoms increased in intermittent sections, indicating that the natural successional process of communities was disrupted due to streambed drying. Furthermore, intermittent sections were marked by elevated abundances of α-mesosaprobous and α-meso-polysaprobous diatoms, indicating a reduced self-purification capacity under intermittent-flow conditions. These findings provide detailed insight into the responses of diatom communities to drought and water scarcity in intermittent streams, which are becoming increasingly common in warm temperate regions. Full article

In arid regions, water scarcity and soil potassium destruction are major constraints on the sustainable development of the jujube industry. In this regard, the use of crop models can compensate for time-consuming and costly field trials to screen for better irrigation regimes, but their predictive accuracy is often compromised by parameter uncertainty. To address this issue, we utilized data from a three-year (2022–2024) field trial (with irrigation at 50%, 75%, and 100% of evapotranspiration and potassium applications of 120, 180, and 240 kg/ha) to simulate the growth process of jujube trees in arid regions using the WOFOST model. In this study, parameter sensitivity analyses were conducted to determine that photosynthetic capacity maximization (A_max), the potassium nutrition index (K_status), the water stress factor (SWF), the water–potassium photosynthetic coefficient of synergy (α), and potassium partitioning weight coefficients (β_i) were the important parameters affecting the simulated growth process of the crop. Path analysis using segmented structural equations also showed that water stress factor (SWF) and potassium nutrition index (K_status) indirectly controlled yield by significantly affecting photosynthesis (path coefficients: 0.72 and 0.75, respectively). The ability of the crop model to simulate the growth process and yield of jujube trees was improved by the introduction of water and potassium parameters (R² = 0.94–0.96, NRMSE = 4.1–12.2%). The subsequent multi-objective optimization of yield and crop water productivity of dates under different combinations of water and potassium treatments under a bi-objective optimization model based on the NSGA-II algorithm showed that the optimal strategy was irrigation at 80% ET_c combined with 300 kg/ha of potassium application. This management model ensures yield and maximizes crop water use efficiency (CWP), thus providing a scientific and efficient irrigation and fertilization regime for jujube trees in arid zones. Full article

Water scarcity and spatial variability in soil fertility are key constraints to stable grain production in the Huang-Huai-Hai Plain. However, the interaction mechanisms between regulated deficit irrigation and soil fertility influencing yield formation and water-nitrogen use efficiency in winter wheat remain unclear. In this study, a two-year field experiment (2022–2024) was conducted to investigate the effects of two irrigation regimes—regulated deficit irrigation during the heading to grain filling stage (D) and full irrigation (W)—under four soil fertility levels: F1 (N: P: K = 201.84: 97.65: 199.05 kg ha⁻¹), F2 (278.52: 135: 275.4 kg ha⁻¹), F3 (348.15: 168.75: 344.25 kg ha⁻¹), and CK (no fertilization). The results show that aboveground dry matter accumulation, total nitrogen content, pre-anthesis dry matter and nitrogen translocation, and post-anthesis accumulation significantly increased with fertility level (p < 0.05). Regulated deficit irrigation promoted the contribution of post-anthesis dry matter to grain yield under the CK and F1 treatments, but suppressed it under the F2 and F3 treatments. However, it consistently enhanced the contribution of post-anthesis nitrogen to grain yield (p < 0.05) across all fertility levels. Higher fertility levels prolonged the grain filling duration by 18.04% but reduced the mean grain filling rate by 15.05%, whereas regulated deficit irrigation shortened the grain filling duration by 3.28% and increased the mean grain filling rate by 12.83% (p < 0.05). Grain yield significantly increased with improved fertility level (p < 0.05), reaching a maximum of 9361.98 kg·ha⁻¹ under the F3 treatment. Regulated deficit irrigation increased yield under the CK and F1 treatments but reduced it under the F2 and F3 treatments. Additionally, water use efficiency exhibited a parabolic response to fertility level and was significantly enhanced by regulated deficit irrigation. Nitrogen partial factor productivity (NPFP) declined with increasing fertility level (p < 0.05); Regulated deficit irrigation improved NPFP under the F1 treatment but reduced it under the F2 and F3 treatments. The highest NPFP (41.63 kg·kg⁻¹) was achieved under the DF1 treatment, which was 54.81% higher than that under the F3 treatment. TOPSIS analysis showed that regulated deficit irrigation combined with the F1 fertility level provided the optimal balance among yield, WUE, and NPFP. Therefore, implementing regulated deficit irrigation during the heading–grain filling stage under moderate fertility (F1) is recommended as the most effective strategy for achieving high yield and efficient resource utilization in winter wheat production in this region. Full article

Water scarcity is a key constraint for commercial Eucalyptus plantations, particularly given the increasing frequency of droughts driven by climate change. This study assessed annual transpiration (Tr) and water use efficiency (WUE) across eight genotypes subjected to contrasting irrigation regimes (WR). A split-plot design was implemented, comprising two irrigation levels: high (maintained above 75% of field capacity) and low (approximately 25% above the permanent wilting point). The genotypes included Eucalyptus globulus (EgH, EgL), E. nitens × globulus (EngH, EngL), E. nitens (En), E. camaldulensis × globulus (Ecg), E. badjensis (Eb), and E. smithii (Es). Between stand ages of 7 and 9 years (2020–2023), we measured current annual increment (CAI), leaf area index (LAI), Tr, and WUE. Under high WR, CAI ranged from 8 to 36 m³ ha⁻¹ yr⁻¹, Tr from 520 to 910 mm yr⁻¹, and WUE from 0.7 to 2.9 kg m⁻³. Low irrigation reduced CAI by 5–25% and Tr by 10–35%, while WUE responses varied across genotypes, ranging from a 12% decrease to a 48% increase. Based on their functional responses, genotypes were grouped as follows: (i) stable performers (Es, Ecg, Eb) exhibited high WUE and consistent Tr under both WR; (ii) partially plastic genotypes (EgH, EngH) combined moderate reductions in Tr with improved WUE; and (iii) water-sensitive genotypes (EgL, EngL, En) showed substantial declines in Tr alongside variable WUE gains. These findings underscore the importance of selecting genotypes with adaptive water-use traits to improve the resilience and long-term sustainability of Eucalyptus plantations in Mediterranean environments. Full article

The Angat Reservoir serves as a major water source for Metro Manila, providing most of the region’s domestic, agricultural, and hydropower needs. However, its dependence on rainfall makes it sensitive to climate variability and future climate change. This study assesses potential long-term impacts of climate change on water availability in the Angat watershed using the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS). Historical rainfall data from 1994 to 2023 and projections under both RCP4.5 (moderate emissions) and RCP8.5 (high emissions) scenarios were analyzed to simulate future hydrologic responses. Results indicate projected reductions in wet-season rainfall and corresponding outflows, with declines of up to 18% under the high-emission scenario. Increased variability during dry-season flows suggests heightened risks of water scarcity. While these projections highlight possible changes in the watershed’s hydrologic regime, the study acknowledges limitations, including assumptions in rainfall downscaling and the absence of direct streamflow observations for model calibration. Overall, the findings underscore the need for further investigation and planning to manage potential climate-related impacts on water resources in Metro Manila. Full article

Climate change has intensified drought stress, threatening global food security by affecting sensitive crops like maize (Zea mays). This study evaluated the potential of Antarctic fungal endophytes (Penicillium chrysogenum and P. brevicompactum) to enhance maize drought tolerance under field conditions with different irrigation regimes. Drought stress reduced soil moisture to 59% of field capacity. UAV-based multispectral imagery monitored plant physiological status using vegetation indices (NDVI, NDRE, SIPI, GNDVI). Inoculated plants showed up to two-fold higher index values under drought, indicating improved stress resilience. Physiological analysis revealed increased photochemical efficiency (0.775), higher chlorophyll and carotenoid contents (45.54 mg/mL), and nearly 80% lower lipid peroxidation in inoculated plants. Lower proline accumulation suggested better water status and reduced osmotic stress. Secondary metabolites such as phenolics, flavonoids, and anthocyanins were elevated, particularly under well-watered conditions. Antioxidant enzyme activity shifted: SOD, CAT, and APX were suppressed, while POD activity increased, indicating reprogrammed oxidative stress responses. Yield components, including cob weight and length, improved significantly with inoculation under drought. These findings demonstrate the potential of Antarctic endophytes to enhance drought resilience in maize and underscore the value of integrating microbial biotechnology with UAV-based remote sensing for sustainable crop management under climate-induced water scarcity. Full article

Water scarcity in semiarid regions represents a critical challenge for sustainable agriculture, reducing the availability of forage and affecting livestock systems. The reuse of treated wastewater offers an environmentally friendly alternative to meet water and nutrient needs, supporting the principles of the circular economy. Sweet sorghum, with its remarkable tolerance to abiotic stress, represents a resilient crop option. Evaluating its agronomic and industrial responses to different depths of irrigation using reclaimed water is essential for improving resource-efficient agricultural practices in water-limited environments. This study evaluated the effects of different irrigation regimes with treated wastewater on the growth, productivity, and water use efficiency of sweet sorghum grown in a semiarid region of Brazil. The experiment was conducted in a randomized complete block design, with five irrigation regimes ranging from 50% to 150% of crop evapotranspiration (ETc) and four replications. Irrigation was carried out with treated wastewater using a drip irrigation system. Growth parameters, fresh biomass, water use efficiency, and soluble solids content (°Brix) were analyzed in two consecutive harvests (main and ratoon crop). Deficit irrigation regimes (50% and 75% of ETc) resulted in higher water use efficiency and higher °Brix, whereas regimes above 100% of ETc reduced water use efficiency and biomass productivity. The ratoon crop showed greater sensitivity to water management, with significant productivity responses under irrigation around 100% of ETc. The first harvest was more productive in terms of fresh biomass and plant growth. Reclaimed water is a sustainable and efficient strategy for cultivating sweet sorghum in semiarid regions. Deficit irrigation regimes can be technically viable for maximizing water use efficiency and production quality, while proper irrigation management is crucial to avoiding losses associated with excessive water application. Full article

The potato (Solanum tuberosum L.) is highly dependent on water availability, with physiological sensitivity varying throughout its phenological cycle. In the context of increasing water scarcity and greater climate variability, identifying critical periods where water stress negatively impacts productivity and tuber quality is essential. This study evaluated the physiological response of potatoes under different deficit irrigation strategies in field conditions, and aimed to determine the irrigation reduction thresholds that optimize water use efficiency without significantly compromising yield. Five irrigation regimes were applied: well-watered (T1; irrigation was applied when the volumetric soil moisture content was close to 35% of total water available), 130% of T1 (T2, 30% more than T1), 75% of T1 (T3), 50% of T1 (T4), and 30% of T1 (T5). Key physiological parameters were monitored, including gas exchange (net photosynthesis, stomatal conductance, and transpiration), chlorophyll fluorescence (Fv’/Fm’, ΦPSII, electron transport rate), and photosynthetic pigment content, at three critical phenological phases: tuberization, flowering, and fruit set. The results indicate that water stress during tuberization and flowering significantly reduced photosynthetic efficiency, with decreases in stomatal conductance (gs), effective quantum efficiency of PSII (ΦPSII), and electron transport rate (ETR). In contrast, moderate irrigation reduction (75%) lowered the seasonal application of water by ~25% (≈80 mm ha⁻¹) while maintaining commercial yield and tuber quality comparable to the fully irrigated control. Intrinsic water use efficiency increased by 18 ± 4% under this regime. These findings highlight the importance of irrigation management based on crop phenology, prioritizing water supply during the stages of higher physiological sensitivity and allowing irrigation reductions in less critical phases. In a scenario of increasing water limitations, this strategy enhances water use efficiency while ensuring the production of tubers with optimal commercial quality, promoting more sustainable agricultural management practices. Full article

Water scarcity in arid regions poses a severe threat to agricultural sustainability, necessitating optimized irrigation strategies. This study investigates the cumulative impacts of long-term irrigation deficits on soil quality, microbial diversity, and maize yield in the arid maize fields of Xinjiang, China, where consistent irrigation patterns have been maintained over multiple years. Seven sites were monitored from April 2023 to March 2024, with a single end-of-cycle sampling in March 2024. Using the Irrigation Water Deficit Index (IWDI), the sites were classified into low (LD, 16.37–22.30%), moderate (MD, 30.54–38.10%), and high drought (HD, 47.49–50.00%) categories. The findings reveal that long-term consistent irrigation deficits exacerbate soil salinization, compaction, and nutrient loss, with organic matter declining significantly under HD conditions. Bacterial richness increased by ~6% under HD, driven by stress-tolerant taxa, while fungal diversity decreased by 14–50%, impairing nutrient cycling functions critical for soil health. The Soil Quality Index (SQI) and maize yield declined with drought severity (LD > MD by 26.18% and 21.05%; LD > HD by 45.02% and 13.13%), highlighting the pivotal role of sustained irrigation patterns in maintaining productivity. These results underscore the need for tailored irrigation management in arid regions, such as precision drip irrigation, to mitigate soil degradation and sustain maize yields, providing a scientific foundation for optimizing water use efficiency in water-scarce agroecosystems under long-term irrigation regimes. Full article

The Hetao Plain Irrigation District of Inner Mongolia faces critical agricultural sustainability challenges due to its arid climate, exacerbated by tightening Yellow River water allocations and pervasive water inefficiencies in the current wheat cultivation practices. This study addresses water scarcity by evaluating the impact of regulated deficit irrigation strategies on spring wheat production, with the dual objectives of enhancing water conservation and optimizing yield–quality synergies. Through a two-year field experiment (2020~2021), four irrigation regimes were implemented: rain-fed control (W0), single irrigation at the tillering–jointing stage (W1), dual irrigation at the tillering–jointing and heading–flowering stages (W2), and triple irrigation incorporating the grain-filling stage (W3). A comprehensive analysis revealed that an incremental irrigation frequency progressively enhanced plant morphological traits (height, upper three-leaf area), population dynamics (leaf area index, dry matter accumulation), and physiological performance (flag leaf SPAD, net photosynthetic rate), all peaking under the W2 and W3 treatments. While yield components and total water consumption exhibited linear increases with irrigation inputs, grain yield demonstrated a parabolic response, reaching maxima under W2 (29.3% increase over W0) and W3 (29.1%), whereas water use efficiency (WUE) displayed a distinct inverse trend, with W2 achieving the optimal balance (4.6% reduction vs. W0). The grain quality parameters exhibited divergent responses: the starch content increased proportionally with irrigation, while protein-associated indices (wet gluten, sedimentation value) and dough rheological properties (stability time, extensibility) peaked under W2. Notably, protein content and its subcomponents followed a unimodal pattern, with the W0, W1, and W2 treatments surpassing W3 by 3.4, 11.6, and 11.3%, respectively. Strong correlations emerged between protein composition and processing quality, while regression modeling identified an optimal water consumption threshold (3250~3500 m³ ha⁻¹) that concurrently maximized grain yield, protein output, and WUE. The W2 regime achieved the synchronization of water conservation, yield preservation, and quality enhancement through strategic irrigation timing during critical growth phases. These findings establish a scientifically validated framework for sustainable, intensive wheat production in arid irrigation districts, resolving the tripartite challenge of water scarcity mitigation, food security assurance, and processing quality optimization through precision water management. Full article

The increasing severity of water scarcity in southern Europe, caused by climate change, requires advanced and more efficient approaches to agricultural water management. In particular, in this paper, we address this problem for olive groves—a cornerstone of the region’s economy. We propose a novel framework for generating high-resolution maps of irrigated olive groves that integrates remote sensing imagery and machine learning. Our approach leverages multi-temporal Sentinel-2 data, specifically the Normalized Difference Vegetation Index (NDVI), to capture seasonal vegetation dynamics. For classification, we explore two distinct models: (1) A Dynamic Time Warping (DTW)-based approach (with and without the Sakoe–Chiba Band constraints), where DTW aligns temporal NDVI sequences to enable robust comparisons of irrigation regimes, followed by a K-Nearest Neighbor classifier (KNN) that classifies plots as irrigated or rainfed. (2) An eXtreme Gradient Boosting (XGBoost) model that directly uses temporal NDVI profiles. Additionally, we compare the dependence of model performance on the length of the NDVI time series (ranging from one to seven seasons), finding that XGBoost requires a shorter time series to achieve optimal results, while KNN with DTW can benefit from longer historical records. Indeed, XGBoost nearly reaches its maximum accuracy using only data based on three seasons, achieving 0.79 compared to its peak performance of 0.80. Hence, our results indicate that this approach can accurately differentiate between irrigated and rainfed plots, enabling the generation of high-resolution irrigation maps for southern Spain. Finally, we argue that the results of this paper go beyond mere mapping: they lay the foundation for a comprehensive management guide that can optimize water use, with broad implications. Such implications range from empowering precision agriculture to providing a roadmap for land management, ensuring both the sustainability and productivity of olive groves in drought-affected regions. Full article

Water conservation is critical for global maize production, particularly in arid regions where water scarcity, exacerbated by climate change, threatens conventional irrigation sustainability. Optimizing irrigation strategies to reconcile water productivity and yield remains a key scientific challenge in water-limited agriculture. This four-year study (2018–2021) evaluated integrated irrigation management that combined frequency and volume adjustments. A field experiment compared three strategies: high-frequency limited irrigation (HL: 2400 m³·hm⁻²), low-frequency conventional irrigation (LC: 2400 m³·hm⁻²), and high-frequency conventional irrigation (HC: 4800 m³·hm⁻²). The four-year mean yield showed that HL (10,793.78 kg·hm⁻²) had a non-significant 18.2% numerical advantage over LC (9129.11 kg·hm⁻², p > 0.05). The WUE for HL reached 3.63 kg·m⁻³, representing an 18.6% numerical increase compared to LC (3.06 kg·m⁻³; p > 0.05). Physiological parameters (plant height + 2.6%, leaf area + 9.9%, SPAD + 1.5%) showed marginal improvements in HL, yet lacked both statistical significance (p > 0.05) and strong yield correlation. Multi-year analyses confirmed no statistically distinguishable differences between strategies (p > 0.05), demonstrating that irrigation frequency adjustments alone cannot reliably enhance drought resilience. These findings caution against advocating for HL as a superior practice, given the statistical equivalence between HL and LC despite water savings, and the non-significant yield gap between HL and HC. Future research must establish causality through models integrating real-time soil–crop–climate feedback prior to recommending altered irrigation regimes. Full article

The cotton-growing region in Southern Xinjiang is plagued by perennial drought and water scarcity, and there is a lack of research on the irrigation mechanism for the “one film, three tubes, four rows” new model of dry sowing and wet emergence of cotton. Therefore, this experiment explores the optimal irrigation regime for cotton under the “one film, three tubes, four rows” planting model in Southern Xinjiang, where a two-year field plot experiment was conducted. Three irrigation levels (W1: 360 mm, W2: 450 mm, W3: 540 mm) were set, with three replications each, to study the effects of different irrigation amounts on cotton growth, soil water content (SWC), irrigation water productivity (IWP), water productivity (WP), and yield (Y). Additionally, the AquaCrop model was used to optimize the irrigation regime. The results showed that irrigation amount significantly affected cotton growth, with plant height, stem diameter, and leaf area index following the order of W3 > W2 > W1. Compared to W1 and W2 treatments, the final biomass (B) and average SWC in the W3 treatment increased by 32.71%, 19.59% and 8.26%, 3.23%, respectively. The seed cotton yield under the W3 treatment was significantly higher than other treatments, being 6575.91 kg/ha in 2023 and 7252.16 kg/ha in 2024. IWP and WP were inversely related to irrigation amount. After two years of data calibration and validation, the model showed good simulation performance for canopy cover (CC), B, WP, and Y (with a concordance index d ≥ 0.904 and a coefficient of determination R² ≥ 0.846). Among the 11 simulated irrigation scenarios (ranging from 360 to 660 mm in 30 mm increments), yield increased with irrigation amount but began to decline slowly beyond 570 mm, peaking at 7.45 t/ha, with IWP and WP being 1.307 kg/m³ and 1.294 kg/m³, respectively. Considering both water conservation and yield increase, an irrigation level or amount of 570 mm under the one-film, three-pipe, four-row planting pattern for dry sowing, wet emergence cotton in Southern Xinjiang can achieve good yields, benefiting the sustainable production of the local cotton industry. Full article

Agrivoltaic offers a promising solution to integrate photovoltaic energy production with ongoing agricultural activities. This research investigates the impact of agrivoltaic on food security, using a transdisciplinary approach to study the responses of crop production in terms of biomass and food quality produced. Mainly chicory plants were grown in full sunlight (control plot) and shade plots generated by potential photovoltaic panels. Two water regimes (high and low water supply) were used to analyze variations in food security in both plots. The results showed that agrivoltaic systems effectively mitigate crop water stress caused by high temperatures and heat waves, improving food security by increasing biomass production and preserving food quality. While previous research has attributed the benefits of agrivoltaics primarily to improved soil moisture, this study demonstrates that the positive effects are primarily driven by differences in light intensity and air temperature between the shaded and control plots. The results have strong implications for water resource management, showing that agrivoltaics can reduce water use by approximately 50% compared to traditional agroecosystems without compromising food security. Agrivoltaics can address the challenges of water scarcity due to declining rainfall and reduce production costs associated with water use. Properly designed agrivoltaic systems offer a cleaner, more sustainable alternative to traditional agricultural practices, helping to adapt agriculture to climate change. Full article