Search Results (1,831)

Drought is a major climatic hazard affecting agricultural production and water resource management. This study investigates the spatiotemporal evolution of summer drought across nine major agricultural regions in China and quantifies associated uncertainties under historical (1981–2010) and future periods (2041–2070 and 2071–2100). Using multi-model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four SSP scenarios (SSP126, SSP245, SSP370, and SSP585), drought variations were characterized using the Standardized Precipitation Index at a 3-month timescale (SPI-3). Sen’s slope estimator combined with the Mann–Kendall test was applied to detect drought trends, and factorial analysis was used to quantify uncertainty contributions. Results show pronounced regional differences in historical drought conditions, with northern arid and semi-arid regions exhibiting stronger precipitation deficits (mean SPI-3 = −0.435), while the Yangtze River Plain and Northeast China Plain show wetter conditions. Historical trends indicate increasing drought conditions in South China, whereas humidification trends dominate several northern and eastern regions. Under future scenarios, most regions show overall wetting trends, but drying tendencies persist in South China. Factorial analysis reveals that regional differences (58.34%) and climate model uncertainty (31.15%) are the dominant contributors to drought variability. Overall, future summer drought in China is characterized by a general wetting tendency with localized intensification of drought conditions. Full article

In the Neotropical Savanna domain, few equations are available for estimating biomass stocks in Cerrado sensu stricto (CSS), despite the importance of such tools for estimating carbon stocks, understanding ecosystem functioning, and supporting conservation actions. We conducted forest inventories in 40 temporary 1000 m² plots in southeastern Brazil to estimate total and compartmental biomass stocks and to model biomass using structural and edaphic predictors. Total biomass (TB) included aboveground woody biomass (AGWB), necromass, litter, and belowground biomass (BGB). AGWB was estimated for trees with basal diameter ≥ 5 cm using a previously fitted regional equation. Root biomass was sampled using a 1 m³ trench excavated at a single point adjacent to each plot. Necromass was quantified using the line-intersect method along a 50 m transect, considering debris with diameter ≥ 3 cm. Litter was sampled using a 0.25 m² frame placed at the center of each plot. Biomass was modeled on an area basis using a hierarchical approach for TB, total tree biomass (TTB = AGWB + BGB), and AGWB. Mean stocks (Mg ha⁻¹ ± s.d.) were 45.24 ± 17.32 (TB), 20.47 ± 11.26 (AGWB), 18.47 ± 10.88 (BGB), 5.49 ± 4.18 (litter), and 0.81 ± 1.62 (necromass). Models selected using the Akaike Information Criterion (AIC) and validated by repeated k-fold cross-validation achieved rŷy = 0.76, 0.72, and 0.94 and RMSE = 24.40%, 27.06%, and 18.10% for TB, TTB, and AGWB. As the equations were calibrated for CSS under the environmental conditions of the Brazilian semiarid region, their transferability to other Cerrado regions should be considered with caution. The inclusion of soil variables (e.g., Al, Mg, and sand) improved predictions, reducing relative costs and taxonomic dependence, while incorporating nutritional adaptations to the acidic soils characteristic of the biome. Full article

We evaluated moderate cluster-zone warming in field-grown Monastrell grafted onto 110R and 140Ru over two seasons (2020–2021) in a semi-arid vineyard in south-eastern Spain. From pea-size to harvest, an open warming system increased cluster-zone air temperature by 1.15 °C on average. Warming increased cluster-zone mean and maximum temperatures, but berry temperature responses depended on year and rootstock because berry–air temperature differences and also time above thresholds changed. Berry weight increased in harvest in both years, and technological ripening advanced, with higher total soluble solids and maturity index, especially during ripening. Acid composition responded differently between rootstocks: under warming, 140Ru maintained higher malic acid and lower tartaric acid than 110R, resulting in a lower tartaric/malic ratio. Phenolic and colour responses were clearest at mid-ripening. Warming reduced must total phenolic index (TPI), skin-related phenolics, anthocyanins, and must colour more strongly in 140Ru, while 110R retained a more stable phenolic and colour profile. Exposure–response analyses showed that time in the 25–35 °C range and berry thermal time were more closely related to technological and phenolic variation than time above 35 °C. These results suggest that, under the warming conditions imposed in this study, 110R offered a better compromise than 140Ru between ripening advancement and the preservation of phenolic and colour-related traits. Full article

Water scarcity is a major constraint to sustainable horticultural production, particularly in arid and semi-arid regions. This study evaluated the effectiveness of two natural foliar biostimulants, chitosan and Spirulina extract, in improving water productivity, growth performance, biomass production, and drought tolerance of passion fruit (Passiflora edulis Sims) seedlings under deficit irrigation. A factorial experiment was conducted using three irrigation regimes (100%, 85%, and 70% of field capacity, FC) combined with three foliar spray treatments: distilled water (control), chitosan (1 g L⁻¹), and Spirulina extract (1 g L⁻¹). Deficit irrigation significantly reduced chlorophyll content, vegetative growth, biomass production, and water productivity, with the greatest reductions observed at 70% FC. Foliar application of both biostimulants effectively alleviated these adverse effects by enhancing plant growth, biomass production, chlorophyll retention, and water productivity under water-limited conditions. Chitosan consistently outperformed Spirulina, particularly under moderate water deficit, by reducing irrigation water requirements while maintaining seedling growth and physiological performance comparable to those under full irrigation. Multivariate analyses, including Pearson correlation, principal component analysis, and response surface methodology, revealed strong positive relationships among biomass production, chlorophyll content, vegetative growth traits, and water productivity. Among all treatments, foliar application of chitosan at 1 g L⁻¹ combined with 85% FC was identified as the optimum strategy, providing substantial irrigation water savings while maintaining vigorous seedling growth, high biomass production, and superior water productivity. These findings demonstrate that integrating moderate deficit irrigation with chitosan application is an effective and sustainable strategy for improving passion fruit nursery production under conditions of limited water availability. Full article

Lacustrine shales are globally important both as archives of paleoenvironmental change and as unconventional hydrocarbon reservoirs. The first Member of the Upper Cretaceous Qingshankou Formation in the Songliao Basin, NE China, represents a prominent interval of high-quality petroleum source rocks. Despite their significance, the factors governing organic matter accumulation and pore evolution in these lacustrine deposits remain inadequately constrained, especially with respect to the interplay between paleoenvironmental conditions and porosity development. This research explores the geochemical, mineralogical, and pore structure features of lacustrine shales and mudstones from this formation. The samples analyzed display TOC contents between 0.62 and 3.13 wt%, with Rock-Eval pyrolysis results (T_max avg. 439 °C) reflecting thermal maturity spanning the early to peak oil window. Mineralogically, the samples are dominated by quartz (avg. 28 wt%) and clay minerals (avg. 51 wt%), with feldspar as a minor component (avg. 14 wt%). Geochemical proxies suggest deposition under arid to semi-arid climatic conditions, characterized by minimal chemical weathering, elevated paleo-salinity (Sr/Ba avg. 0.89; 100 × Mg/Al avg. 14.94), and predominantly suboxic to oxic bottom-water conditions (U/Th avg. 0.38; Ni/Co avg. 1.77). Organic matter enrichment is primarily driven by high paleoproductivity (Cu/Al avg. 3.77 × 10⁻⁴) and stratified water columns, while detrital input (Zr/Al ratio) is unfavorable for organic matter accumulation. Pore structure analysis reveals micropore volumes averaging 0.0053 cm³/g and meso- and macropore volumes averaging 0.0233 cm³/g. The contents of quartz and clay minerals exhibit no substantial correlation with pore volume, likely due to secondary quartz overgrowth and mechanical compaction. Similarly, the weak negative correlation between TOC and pore volume is attributed to the poorly developed pore networks within kerogen. This study provides new insights into the depositional and diagenetic controls on organic matter accumulation and pore development in the lacustrine Qingshankou Formation, with implications for paleoenvironmental reconstruction and unconventional hydrocarbon exploration in analogous lacustrine basins worldwide. Full article

Panicum turgidum is an important keystone forage grass crucial for ecosystem stability in arid and semi-arid rangelands of Asia and Africa. This study aimed to investigate the use of beneficial bioinoculants for enhancing the growth and acclimatization of micropropagated desert grass under controlled environmental conditions. Tissue-cultured plants were transferred to pots with a sand–soil mixture (1:1, v/v) and kept in a temperature and light-controlled environment (25 ± 2 °C, 100 µmol m⁻²·s⁻¹, and 16/8 light/dark photoperiod) for 10 weeks. We used a factorial approach to investigate the effects of the arbuscular mycorrhizal fungus (AMF) Rhizophagus fasciculatus, Trichoderma harzianum, and Bacillus subtilis on transplanted desert grass plants. Two AMF levels control (AMF, 5%; w/w) or without AMF (NAMF); and three microbial inoculation treatments (T. harzianum, B. subtilis, and a combination of T. harzianum + B. subtilis) were employed. Microscopic investigation indicated the extent of AMF colonization in the roots of micropropagated P. turgidum plantlets during acclimatization. Growth parameters with shoots and roots, chlorophyll and carotenoid content, and nitrogen uptake were all improved in bioinoculants-treated plants. Under non-AMF conditions, co-inoculation with T. harzianum and B. subtilis resulted in the highest biomass and root traits, whereas under AMF conditions, T. harzianum alone or with AMF was generally most effective. In the plants treated with the combination of inoculants, heatmap correlation, principal component analysis, and hierarchical clustering demonstrated positive association between growth and physiological traits and the absorption of mineral nutrients, although these associations varied among treatment combinations. These findings highlight the potential of beneficial bioinoculants to improve the growth and acclimatization of micropropagated desert grass plants, providing a foundation for tailored bioinoculant compositions towards the rehabilitation of degraded grazing lands. Full article

Drought and water deficit have severely restricted melon (Cucumis melo L.) production in Xinjiang, and large-scale systematic evaluations of drought tolerance at the germination stage are still extremely limited. Physiological and biochemical indicators related to the germination stage, including osmotic adjustment substances and antioxidant enzyme activities, have not yet been incorporated into prediction models for the rapid identification of germplasm drought resistance. To address these research gaps, this study selected 60 accessions of local melon germplasm resources in Xinjiang and used polyethylene glycol (PEG) solutions at four different concentrations (0%, 10%, 20% and 30%) to simulate drought stress conditions. Drought tolerance was evaluated to develop a method for the rapid screening of drought-tolerant germplasms. The findings demonstrated that PEG stress significantly suppressed seed germination and had both stimulatory and inhibitory effects on radicle growth. With the increase in PEG concentration, germination indices consistently exhibited a downward trend. Under 10% PEG treatment, the variation among different germplasms was relatively small, while 30% PEG completely inhibited seed germination. Notably, 20% PEG fell within the semi-lethal concentration range for all tested germplasms and yielded the maximum coefficient of variation for germination rate, which could maximally differentiate the drought resistance differences among germplasms. Therefore, 20% PEG was determined to be the optimal screening concentration. Under 20% polyethylene glycol (PEG) stress, the degree of membrane lipid peroxidation (malondialdehyde, MDA), contents of osmotic regulators (proline, Pro; soluble protein, SP), and activities of antioxidant enzymes (superoxide dismutase, SOD; peroxidase, POD; catalase, CAT; ascorbate peroxidase, APX) in the radicles of melon germplasms were universally elevated. However, the variation ranges and trends of biochemical indices among different germplasms exhibited significant differences. The proline content of melon accessions with strong drought resistance increased, the malondialdehyde (a product of membrane damage) was low, and the enzyme activities increased significantly. The proline content of non-drought-tolerant melon accessions increased less, malondialdehyde accumulated in large amounts, and the activity of some protective enzymes decreased. Correlation analysis demonstrated that Pro exerted a synergistic effect in conjunction with antioxidant enzymes (SOD, CAT) to mitigate drought stress. Cluster analysis classified the germplasm into 14 high-tolerance types, 10 medium-tolerance types, and 9 low-tolerance types. Based on extreme germination phenotypes, 27 germplasms were identified as drought-sensitive types. A prediction model for drought tolerance was established via stepwise regression: D = −0.309 + 0.053 × Pro (proline content) + 0.319 × RL (radicle length) + 0.469 × MDA (malondialdehyde) + 0.137 × SOD (superoxide dismutase), with four core indicators (RL, MDA, Pro, SOD) identified. These findings provide a scientific basis and technical support for drought tolerance breeding, parental selection, and large-scale, precise, and rapid drought tolerance screening of melon germplasms in the arid regions of Xinjiang. Full article

This study investigates hydroclimatic variability and water balance dynamics in the Akmola region during 2003–2023 using observations from 16 meteorological stations. The study evaluates changes in air temperature, precipitation, reference evapotranspiration (ET₀), climatic water balance, and drought conditions. Reference evapotranspiration was calculated using the FAO-56 Penman–Monteith method, while drought variability was assessed using the 12-month Standardized Precipitation–Evapotranspiration Index (SPEI-12). Temporal trends were analyzed using the Mann–Kendall test and Sen’s slope estimator. The results revealed significant spatial heterogeneity in hydroclimatic conditions across the region. Air temperature showed a consistent increasing trend at most stations, accompanied by increasing atmospheric evaporative demand. All stations were characterized by a persistently negative climatic water balance, with mean annual values of approximately −750 mm, indicating a regional moisture deficit. Reference evapotranspiration exhibited significant spatial variability, with the highest values observed in the southern and central parts of the region. Precipitation remained the dominant control of water balance variability (r = 0.79–0.96), while increasing temperature intensified moisture deficits through increased evapotranspiration. SPEI-12 indicated recurrent drought episodes and increasing drought vulnerability associated with warming-induced atmospheric water demand. The study demonstrates that increasing evapotranspiration is becoming a major driver of water stress in the Akmola region and highlights the importance of integrating climatic water balance and SPEI indicators for drought monitoring and climate adaptation in semi-arid steppe regions. Full article

Rapid urban expansion and agricultural development have substantially altered land use/land cover (LULC), surface thermal regimes, and ecosystem conditions in semi-arid cities. This study investigates the spatiotemporal dynamics of LULC and evaluates their associations with land surface temperature (LST), vegetation health, soil moisture, and drought conditions in Ghazni City, Afghanistan, between 2013 and 2023 using a Google Earth Engine (GEE)-based framework. Landsat 8 OLI/TIRS imagery was classified using a Random Forest (RF) algorithm, while the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), and LST were derived to evaluate environmental responses. To provide a comprehensive evaluation of urban–climate interactions, monthly Landsat-derived LST time series were analyzed and compared to MODIS and ERA5 datasets through a multi-source consistency assessment framework. The RF classification achieved overall accuracies of 95.56% (2013) and 97.77% (2023), with Kappa coefficients of 0.89 and 0.94, respectively. Results revealed a substantial expansion of built-up areas (5.4%) and vegetation/agricultural land (7.2%), accompanied by a decline in bare land. Urban and barren surfaces consistently exhibited higher LST values, whereas vegetated areas demonstrated a pronounced cooling effect. NDVI and SAVI analyses indicated improving vegetation conditions and soil moisture status over the study period. LST exhibited strong seasonal variability, with summer maxima reaching 49.74 °C and winter minima declining to −8.39 °C. Comparisons among the Landsat, MODIS, and ERA5 datasets demonstrated strong agreement, with a high correlation between Landsat- and MODIS-derived LST (R = 0.84), supporting the reliability of the Landsat-derived LST estimates. Generally, the findings demonstrate the critical role of vegetation in moderating surface temperatures and enhancing urban climate resilience, providing scientific evidence for sustainable land use planning and climate adaptation strategies in semi-arid cities. Full article

Terrestrial carbonates provide important archives for reconstructing paleoenvironmental, paleoclimatic and hydrogeological conditions in semi-arid to arid continental basins. This study investigates the origin, mineralogical characteristics and geochemical properties of calcrete and dolocrete occurrences developed along the Konya Fault Zone within the Konya Closed Basin (Central Türkiye). Field observations, petrography, XRD, SEM–EDS, major and trace element geochemistry, REE analyses, stable isotopes (δ¹³C–δ¹⁸O), geostatistical methods and ESR dating were employed. The results reveal two distinct terrestrial carbonate systems. Dolocretes occur within Quaternary alluvial fan deposits developed on ultramafic–ophiolitic rocks, whereas calcretes developed pedogenically within Quaternary alluvial fan deposits overlying carbonate bedrock. Calcite, dolomite, quartz, palygorskite and smectitic clay minerals constitute the principal mineral phases. Rhizoliths, tubular structures, nodules, microbial filaments and laminated carbonate horizons indicate pedogenic carbonate accumulation. The association of palygorskite with dolomite and smectitic clay minerals suggests alkaline, Mg-rich pore waters under semi-arid conditions. Elevated Sr concentrations indicate prolonged groundwater–carbonate interaction, whereas high Ni and Co contents in the dolocretes reflect the influence of ultramafic source rocks. REE distributions are characterized by LREE enrichment, weak Eu anomalies and locally developed negative Ce anomalies, indicating pedogenic fractionation under oxidizing meteoric conditions. Stable isotope data indicate precipitation from meteoric waters influenced by soil-derived CO₂ under semi-arid climatic conditions dominated by C3 vegetation. ESR ages ranging from approximately 390–217 ka indicate carbonate formation during the Middle Pleistocene (MIS 11–MIS 7). Integrated mineralogical, geochemical, isotopic and chronological evidence indicates that the Konya terrestrial carbonates formed predominantly through pedogenic processes within meteoric vadose-zone conditions controlled by bedrock lithology (carbonate and ultramafic rocks), groundwater circulation and Quaternary climatic variability. These deposits represent important archives of Middle Pleistocene paleoenvironmental and paleohydrological evolution in Central Anatolia. Full article

Tugai forests are intrazonal riparian ecosystems formed along river valleys in arid and semi-arid regions and characterized by high biodiversity and complex vegetation structure. The aim of this study was to assess the phytocenological structure, species composition, and ecological characteristics of tugai forests distributed within the Kura River basin and the Nakhchivan Autonomous Republic of Azerbaijan. The study was conducted using classical geobotanical and phytocenological methods based on the Braun—Blanquet approach. The results revealed clear ecological differentiation among tugai forest formations depending on hydrological regime, groundwater conditions, and soil salinity. High species diversity and a multi-layered vegetation structure were identified within the Populeta—Salicetum—Ulmosum, Ulmeta, Populeta, Saliceta—Alnueta—Populeta, and Tamariceta formation groups, which develop mainly on alluvial soils under conditions of elevated moisture. In the Nakhchivan region, tugai forests adapted to more arid environments are distributed mainly along the Araz River and are dominated by Tamarix ramosissima, Populus euphratica, Populus nigra, and Salix species. Anthropogenic impacts, including grazing, deforestation, and hydrological alterations, were identified as major factors contributing to ecosystem degradation and reduction in vegetation cover. The obtained results confirm the high ecological and conservation significance of tugai forests and emphasize the necessity of their protection, restoration, and sustainable management. Full article

Groundwater is a principal irrigation water source worldwide; however, its quality is increasingly diminished by rapid urbanization, improper agricultural practices, and accelerating industrial activities. Groundwater management is especially important in areas where soil salinization and erosion are more probable, such as arid and semi-arid zones. In view of this, the Armavir region of the Republic of Armenia was selected as the study area, being an intensively cultivated agricultural zone. The objective of this study was to assess and map the quality of groundwater for irrigation using advanced methods, taking into account both climatic conditions and anthropogenic influences. A total of 72 groundwater samples were collected during the irrigation season from 41 unconfined and 31 confined aquifer wells. Key hydrochemical parameters (pH, EC, TDS, Cl⁻, HCO₃⁻, CO₃²⁻, Na⁺, K⁺, Ca²⁺ and Mg²⁺), irrigation indices (SAR, Na%, MH, RSC and PI), and graphical methods (Gibbs, USSL and Wilcox diagrams) were applied to assess groundwater quality. An integrated assessment was performed using the Irrigation Water Quality Index (IWQI), and spatial distribution was evaluated through geostatistical analysis and GIS mapping. Although certain individual hydrochemical parameters indicated limitations for irrigation in localized areas, particularly within the unconfined aquifer, the integrated IWQI assessment revealed that groundwater predominantly falls within the good to excellent categories across the study area, with more favorable conditions observed in the confined aquifer. These findings constitute an essential prerequisite for counteracting soil salinization and promoting sustainable agricultural development. Full article

The Normalized Difference Vegetation Index (NDVI) is widely used as an indicator of irrigation activity in arid and semi-arid agricultural regions. This study evaluates how NDVI extraction scale and statistical metric influence groundwater level prediction accuracy in the irrigated Tadla Plain, MoroccoA total of 96 Long Short-Term Memory (LSTM) models were developed by combining six NDVI extraction scales, from the well pixel to 20,000 m buffers, and four statistical metrics: mean, median, maximum, and minimum. Results demonstrate that extraction scale is a critical factor controlling model performance. Across the four monitored wells, larger buffers (≥2500 m) generally outperformed smaller ones (≤1000 m), with the optimal scale occurring at 15,000 m for three wells, while one well achieved its best performance at the 1000 m scale. The best models achieved RMSE values between 0.09 and 0.625 m and R² values ranging from 0.94 to 0.997. Maximum NDVI provided the highest predictive accuracy for three wells, whereas minimum NDVI performed best for one well. Statistical analyses further confirmed that extraction scale generally exerts a stronger influence on prediction performance than the choice of NDVI metric. Spatial validation revealed that irrigated areas more than doubled between 2001 and 2017, and model performance improved as NDVI captured this broader irrigation footprint. These findings suggest that groundwater level variations in the Tadla Plain are more strongly associated with NDVI signals extracted at broader spatial scales than with strictly local vegetation conditions around individual wells, highlighting the importance of optimizing both NDVI extraction scale and metric for groundwater forecasting in irrigated semi-arid regions. Full article

Estimation of forest biomass and surface fuels is essential for wildfire risk assessment, carbon accounting, and ecosystem management in semi-arid forests. This study evaluated Sentinel-2 spectral indices and Gamma generalized linear models (GLMs) for estimating aboveground live biomass, forest floor biomass, and downed woody debris in oak–pine forests of Northern Mexico. Spectral predictors were grouped according to chlorophyll activity, vegetation vigor, physiological condition, and soil/background correction effects. Measurements of live biomass, forest floor biomass, and downed woody debris were linked to Sentinel-2 spectral information. Aboveground live biomass was most strongly associated with the chlorophyll-related index CIre8A (p < 0.0001), whereas both forest floor biomass and downed woody debris showed stronger relationships with indices associated with red–NIR reflectance gradients, vegetation senescence, and soil/background correction effects, including the Normalized Difference Vegetation Index (NDVI), the Alpha-weighted Red–NIR Vegetation Index (PVIα), the Normalized Pigment Chlorophyll Index (NPCI), and the Atmospherically Resistant Vegetation Index (ARVI) (p < 0.05). Single-index Gamma GLMs showed significant predictive relationships (p < 0.05), supporting the use of individual Sentinel-2 indices as practical predictors of biomass and surface fuels. In contrast, multivariate models combining several spectral indices were affected by collinearity and parameter instability. Principal Component Analysis (PCA) integrated four representative indices into a single orthogonal predictor. The first principal component (Prin1) explained 90.30%–95.25% of total spectral variance, eliminated collinearity effects (VIF = 1), and produced highly significant Gamma GLMs across all biomass components (p ≤ 0.0009). PCA-based models also yielded lower AIC and BIC values, providing the most parsimonious framework when multiple spectral predictors were combined. These results indicate that individual spectral indices offer practical alternatives for biomass estimation, whereas PCA provides a robust approach for integrating complementary spectral information while maintaining model stability. Full article

This study evaluated the individual and interactive effects of straw management, tillage systems, and wheat growth stages on surface energy balance (SEB) dynamics in a semi-arid wheat production system, with particular focus on net radiation (Rn), sensible heat flux (H), latent heat flux (LE), Bowen ratio (β), and energy partitioning (EP). A field experiment was conducted during the 2022–2023 growing season using a split–split plot design with two straw management treatments, four tillage systems, and three growth stages. Surface energy balance components were estimated through field-based micrometeorological measurements. Data were analysed using ANOVA, variance partitioning analysis, and Pearson correlation analysis. All experimental factors significantly affected SEB components, although growth stage represented the dominant source of variability, accounting for 42–58% of total variance. Flowering stage consistently promoted the highest LE values and the lowest β and EP values, indicating enhanced evaporative cooling during maximum crop development. Conservation-oriented tillage systems substantially modified thermal partitioning, with no-tillage (NT) significantly increasing LE and reducing H relative to conventional tillage (CT). The combination of straw incorporation and NT during flowering (IS + NT + S2) produced the highest LE value (129.15 W m⁻²) and one of the lowest H values (18.35 W m⁻²). Bowen ratio progressively decreased from CT (8.57) to NT (1.44), confirming a shift from sensible to latent heat exchange under conservation-oriented management. Crop phenology and conservation-oriented soil management jointly regulated thermal partitioning and evaporative cooling in semi-arid wheat systems. NT combined with straw incorporation substantially enhanced latent heat exchange while reducing sensible heating, particularly during flowering. This study provides novel field-based evidence regarding the combined influence of straw management, tillage systems, and wheat phenology on SEB dynamics under semi-arid conditions, contributing to improved understanding of land–atmosphere interactions and climate-adaptive agricultural management strategies. Full article