Search Results (4,571)

Energy balance models using remote sensing imagery can provide reliable, cost-effective estimates of actual evapotranspiration (ET_a) over large areas. This study evaluated the Analytical Land Atmosphere Radiometer Model (ALARM), a one-source energy balance model, for estimating ET_a in Mediterranean orchard systems. The model was applied to almond, olive, citrus, and pomegranate orchards during the 2019–2020 growing seasons using MODIS imagery. Calibration and validation were performed against ET_a estimates from the SIMDualKc and HYDRUS-1D models. Sensitivity analysis showed canopy-related parameters had the greatest influence on ET_a estimates. ALARM successfully reproduced seasonal ET_a dynamics for almond, citrus, and pomegranate orchards, achieving R² values ≥ 0.74 and normalized RMSE ≤ 34.1%. Performance was weaker for olive orchards (R² = 0.47–0.85; NRMSE = 32.4–50.2%), where ET_a was overestimated due to inadequate representation of deficit irrigation. The coarse spatial resolution of MODIS imagery also required an empirical adjustment parameter (β = 0.50–0.92) to address mixed land-cover conditions within pixels. Despite these limitations, ALARM proved promising for large-scale water resource assessments, although its suitability for detailed field-scale irrigation management remains limited. Full article

Accurate crop evapotranspiration (ET_c) estimation at high spatial and temporal resolution remains a major challenge for precision irrigation. This study presents a multi-sensor data fusion framework combining daily MODIS (250 m), Sentinel-2 (10 m), and Landsat 8/9 (30 m) imagery with FAO-56 Penman–Monteith reference evapotranspiration (ET₀) to generate pixel-wise daily ET_c maps for irrigated maize (Zea mays L.) near Nyírbátor, Hungary, over six growing seasons (2020–2025). The proposed Median Time Series Model exploits field-scale MODIS NDVI as a temporal backbone and derives pixel-wise linear transfer functions to reconstruct daily NDVI at 10–30 m resolution. Three gap-filling strategies were compared; the median approach yielded the highest agreement (NDVI reconstruction R² = 0.81; RMSE = 0.19 (NDVI units); pixel-wise correlation 0.70–0.85) and effectively suppressed sub-pixel spectral mixture artefacts. Sentinel-2 consistently outperformed Landsat 8/9 (pixel-wise R² = 0.36–0.78 vs. 0.001–0.91). A nonlinear power crop coefficient model (K_c = a · NDVI^b) proved more robust than linear rescaling (mean validation R² of 0.80 (power) vs. 0.71 (rescale) across Sentinel-2 seasons; both methods were positive in all six seasons after correcting an unconstrained-fit artefact). Seasonal ET_c ranged from 313 to 545 mm, with cumulative water deficits reaching −334 mm during the 2021 drought. Six-year mean seasonal ET_c (428–483 mm for Sentinel-2) falls within the 400–600 mm range published for irrigated maize under comparable continental conditions, with season-integrated ET_c/ET₀ ratios (rescale method mean 0.86; power method mean 0.84) consistent with expected FAO-56 K_c trajectories. Cross-validation against an independent MATLAB implementation confirmed algorithmic consistency (reference ET₀ (R² = 0.88–0.91, Pearson r = 0.97–1.00)) and daily ET_c while identifying meteorological input as the dominant source of absolute ET_c uncertainty (estimated at ±15–30% through first-order error propagation). Plausibility assessment was limited to comparison with published seasonal benchmarks and an independent algorithmic implementation; no eddy covariance or lysimeter measurements were available for direct ET_c validation. Full article

Semi-arid wetlands are highly sensitive to changes in hydrological regimes, as strong evaporation often exceeds limited natural recharge. Ecological water replenishment is widely used to restore these systems, but schemes designed only to meet water-volume targets may cause excessive hydrodynamic disturbance, promote sediment resuspension, and increase the release of internal pollutants. In this study, we developed an ecological water-replenishment assessment framework for Chahannaoer Wetland that incorporates ecological water-demand thresholds, suspended-solids disturbance, and an AHP–entropy weight–TOPSIS decision model. Using hydrological and meteorological data from 2014 to 2024, six replenishment scenarios were evaluated in terms of water-balance recovery, disturbance control, and habitat suitability. The results show that Chahannaoer Wetland experienced a persistent evaporation-dominated water deficit. The mean annual natural recharge was 0.225 × 10⁸ m³, with a mean annual ecological water shortage of 1.03 × 10⁸ m³ and an evapotranspiration-to-recharge ratio of 3.42–4.56. Based on the previous comprehensive water-quality assessment using DO, COD, NH₃-N, TN, and TP, the minimum water volume required to maintain Class IV water quality was 0.86 × 10⁸ m³, whereas the suitable ecological water demand ranged from 1.27 × 10⁸ to 1.56 × 10⁸ m³. With the total replenishment volume held constant, centralized replenishment met the required water volume but substantially increased near-bed disturbance and sediment resuspension risk. By contrast, decentralized uniform replenishment performed best, with the highest relative closeness coefficient of 0.9105, a disturbance index of approximately 0.32, and water depths maintained within the suitable habitat range of 30–50 cm. These findings suggest that ecological restoration in semi-arid wetlands should move beyond volume-based water supplementation and pay greater attention to the timing, pathway, and hydrodynamic effects of replenishment. The proposed framework provides a quantitative basis for optimizing ecological water replenishment in evaporation-dominated wetlands and other inland lakes in arid and semi-arid regions. Full article

In a context of increasing water scarcity in southern Spain, improving water-use efficiency has become essential for sustainable crop production. This study evaluated the effects of two irrigation regimes (100% and 75% of crop evapotranspiration, ETc) on the quality attributes and phenolic compound profile of three goji berry varieties (NQ1, Sweet Lifeberry, and Turgidus) cultivated under organic conditions in southwestern Spain. Key quality parameters including color, sugars, acidity, firmness, moisture, size, and weight were evaluated together with phenolic compounds profiling using UHPLC-MS/MS and antioxidant activity assays. The goji berry varieties studied showed significant differences (p < 0.05) in most of the variables analyzed, confirming the dominant influence of genotype. In contrast, no significant differences were detected in most quality attributes between berries cultivated under full irrigation (100% ETc) and deficit irrigation (75% ETc). However, deficit irrigation promoted the accumulation of hydroxycinnamic and hydroxybenzoic acids, while flavonols and flavan-3-ols showed a decreasing tendency. Despite these compositional shifts, antioxidant capacity was generally higher under full irrigation. Among the varieties, NQ1 berries exhibited the highest total phenolic content and antioxidant activity. Harvesting time further influenced phenolic distribution and antioxidant behavior. These findings suggest that moderate deficit irrigation can be applied as a sustainable water-saving strategy for goji berry cultivation under Mediterranean conditions without compromising fruit quality. Full article

Hydrological processes in dryland urban lakes are jointly shaped by landscape pattern dynamics and water resource scarcity, yet the spatial correspondence between landscape fragmentation and lake ecological water demand remains poorly understood. This study took Yuehai Lake, a typical dryland urban lake in Northwest China, as a case study. Landscape pattern analysis was integrated with a water balance model to quantify ecological water demand and its spatial correspondence with landscape metrics. The model coupled the Penman–Monteith equation, a depth-modified evaporation model, and a Darcy’s Law-based zonal seepage calculation. Results showed that: (1) the landscape structure remained highly stable over 2014–2022, with the Aggregation Index ranging from 95.07% to 95.28% and the Largest Patch Index from 90.20% to 90.70%; (2) the annual ecological water demand for maintaining ecosystem integrity was estimated at 2036.97 × 10⁴ m³, comprising inherent lake water volume of 1138.02 × 10⁴ m³ (55.9%), evapotranspiration of 659.72 × 10⁴ m³ (32.4%), and lakebed seepage of 239.23 × 10⁴ m³ (11.7%); and (3) evapotranspiration was concentrated between May and August, accounting for 80.5% of annual losses, with water surface evaporation dominating the flux at 91.5%. These findings suggest a spatial correspondence between landscape metrics and ecological water demand components, providing quantitative support for differentiated water supplementation strategies in dryland urban lakes. Full article

Understanding how different drought indicators characterise future drought conditions is essential for climate monitoring and adaptation planning. This study quantified annual severe- and extreme-drought occurrence rates at the 1- and 3-month timescales using the Standardised Precipitation Index (SPI), the Standardised Precipitation Evapotranspiration Index (SPEI), and their concurrent signals. Historical conditions during 1951–2010 were compared with projections for 2041–2100 under SSP245 and SSP585 using an ensemble of 12 CMIP6 General Circulation Models. Inter-model uncertainty was assessed using the 5th and 95th ensemble quantiles. The results reveal marked contrasts between precipitation-based and potential-evapotranspiration-sensitive drought indicators. Globally, SPI-based severe-drought occurrence decreases under both scenarios, whereas SPI-based extreme-drought occurrence increases, particularly at the 3-month timescale under SSP585. Stronger and more spatially extensive increases are identified using SPEI. The global mean occurrence rate of SPEI1-based extreme drought increases from 0.231 month/yr historically to 0.791 month/yr under SSP245 and 1.197 month/yr under SSP585. For SPEI3, the corresponding rate increases from 0.207 to 1.090 and 1.716 month/yr, respectively, with approximately 92.3% of land grid cells showing increases under SSP585. Concurrent SPI-SPEI severe-drought occurrence decreases, while concurrent extreme-drought occurrence increases across approximately 70–77% of land grid cells. This contrast indicates a redistribution of concurrent drought months from the severe to the extreme severity class under a mutually exclusive classification scheme, particularly at the 3-month timescale. The Mediterranean region, the Amazon and other parts of South America, southern Africa, parts of West and Central Asia, and Australia consistently emerge as major hotspots. Ensemble-quantile results support the direction of increasing SPEI-based and concurrent extreme-drought occurrence, although substantial uncertainty remains in the magnitude of change. These findings demonstrate the value of jointly considering precipitation-based and evaporative-demand-sensitive indicators in drought monitoring and regional climate adaptation planning. Full article

Water scarcity and environmental degradation have emerged as critical challenges threatening sustainable agricultural development worldwide. This study hypothesized that organic substitution buffers the physiological stress of deficit irrigation on lettuce (Lactuca sativa L.), and that this buffering effect of organic substitution can be quantified using AquaCrop to optimize irrigation schedules. Field experiments were conducted to evaluate the interactive effects of irrigation levels and organic/urea fertilizer rates on soil moisture, lettuce growth and yield during two growing seasons (April to May and September to October 2024) in Songjiang, Shanghai. Six treatments combining two irrigation levels (full irrigation at 100% of crop evapotranspiration (ETc) and deficit irrigation at 60% ETc) with three fertilization levels (300 kg/ha urea, 150 kg/ha urea + 15 t/ha organic fertilizer, and 150 kg/ha urea) were conducted. AquaCrop was calibrated and validated using field observations. The results demonstrated that organic substitution under deficit irrigation preserved soil moisture, canopy development, and fresh yield at levels comparable to full irrigation and nitrogen fertilization, whereas 50% nitrogen alone caused substantial yield reduction. AquaCrop showed satisfactory performance in simulating lettuce growth under organic substitution, with normalized root mean square error (NRMSE) values of 3.07%~21.42%, 5.02%~20.11%, and 8.22%~20.95% for soil water content, canopy cover, and fresh yield, respectively. Using the validated model, scenario analysis across the different precipitation years revealed that lettuce yield was most responsive to irrigation during the seedling stage, followed by the rosette stage and cupping stage. Specifically, 100% ETc during the seedling and rosette stages was suggested for dry years; 100% ETc at the seedling stage combined with 80% to 100% ETc at the rosette stage for normal years; and more flexible strategies (60% to 100% ETc at the seedling stage) for wet years based on model predictions. These irrigation strategies, combined with organic substitution, can achieve above 90% of the potential yield of the full irrigation and nitrogen treatment. These findings offer preliminary guidance for irrigation and fertilization management of lettuce under the experimental climate and soil conditions, while further validation across diverse cultivars and environments is needed before broader application. Full article

Inner Mongolia is the dominant spring wheat production area in northern China and a core commodity grain supply base. Against the background of global warming, meteorological disasters, such as drought, dry-hot winds, and frost, are occurring more frequently and with increasing overlap, posing a threat to stable spring wheat production. This study covers the period 1961–2020 and draws on observational data from 107 meteorological stations alongside agricultural and socioeconomic data. Using the Standardized Precipitation Evapotranspiration Index, dry-hot wind index, and frost index, we constructed a regional disaster index system encompassing drought, dry-hot winds, and frost. Comprehensive risk assessment and zoning were conducted across four dimensions: hazard, exposure, vulnerability, and disaster prevention and mitigation capacity. The results showed that: (1) Temporally, the study area exhibited a significant warm and dry trend, with intensifying aridification across all growth periods and an abrupt change concentrated in the 1990s. The occurrence range of dry-hot wind trended upward, while that of frost trended downward. (2) Spatially, the comprehensive hazard presented a pattern dominated by drought-dry hot wind in the west, drought-frost in the east, and multiple disasters overlapping in the central part. (3) High exposure occurred in major production areas, such as eastern Hulunbuir, Xing’an League, and Bayannur, while vulnerability followed the pattern of central part > eastern > western regions. (4) Comprehensive risk analysis showed that sub-high and high-risk areas were concentrated in central Xilingol League and parts of Hulunbuir, whereas low- and sub-moderate-risk areas occurred in irrigated agricultural regions west of Baotou. The zoning results were consistent with the spatial distributions of yield reduction rate and vulnerability. This study clarifies the spatiotemporal evolution and risk differentiation mechanisms of meteorological disasters affecting spring wheat in Inner Mongolia, providing a scientific basis for disaster prevention, mitigation, and climate-adaptive spring wheat production. Full article

The shift from traditional irrigation methods to pressurized irrigation has become essential, particularly considering the water scarcity in the US Southwest. In this context, this study evaluated the effects of different irrigation systems and rates on crop yield (Y) and water productivity (WP) within a multi-cropping system consisting of cantaloupe (Cucumis melo L.), broccoli (Brassica oleracea var. italica), and silage corn (Zea mays L.) under arid conditions in Arizona. Field experiments compared flood (F) and subsurface drip irrigation (SDI) systems at two crop evapotranspiration (ET_c) replacement levels (100% and 80%), resulting in four treatments: F100, F80, SDI100, and SDI80. Seasonal total water applied (TWA), crop yield, water productivity, and silage corn forage-quality parameters were measured. The effects of irrigation systems varied among crops, whereas cantaloupe achieved the highest yield under flood irrigation, with maximum production observed in F100 (63.8 t ha⁻¹). Meanwhile, cantaloupe yields declined under deficit irrigation and SDI treatments (57.2, 39.8, and 27.4 t ha⁻¹ for F80, SDI100, and SDI80, respectively). In contrast, broccoli and silage corn generally performed better under SDI, where more frequent water applications might have improved root-zone moisture conditions and enhanced water productivity. Deficit irrigation substantially increased WP relative to full irrigation without significantly affecting yield for broccoli and silage corn. Broccoli WP ranged from 3.9 kg m⁻³ (F100) to 6.3 kg m⁻³ (SDI80), while silage corn WP increased from 8.7 to 8.8 kg m⁻³ under flood irrigation to 11.6–12.8 kg m⁻³ under SDI. Silage corn forage-quality parameters were not significantly affected by irrigation system or irrigation rate, indicating that moderate water deficits improved seasonal water use without compromising nutritive value. Overall, deficit irrigation reduced seasonal water use and improved WP, with the greatest benefits observed under subsurface drip irrigation. The results demonstrate distinct crop-specific responses to irrigation management, highlighting the necessity of customized optimization strategies. Moreover, our findings highlight that the SDI with moderate deficit irrigation (80% ET_c) can provide an effective balance between water conservation and productivity, enhancing WP without compromising yield or quality under arid conditions. Full article

Accurate estimation of evapotranspiration (ET) is critical for irrigation management in water-scarce regions such as the Middle East and North Africa (MENA). This study compares sensible heat flux (H), latent heat flux (LE), and ET derived from eddy covariance (EC) and a boundary-layer scintillometer (BLS) operated with an aperture reducer, deployed simultaneously over an irrigated late-season potato field (1.8 ha) in the Beqaa Valley, Lebanon. Satellite NDVI observations indicate that the BLS–EC overlap period (13 October–27 November 2021) sampled the crop from peak canopy (NDVI ≈ 0.85–0.90) through the onset of senescence (NDVI ≈ 0.79). The BLS (Scintec BLS900) operated along a 140 m path. The EC system showed incomplete daytime energy-balance closure, with a regression slope of ≈0.69 and a seasonal Bowen-ratio-preserving correction factor of CF = 1.24 (a ~19% closure deficit) was used. Across the matched period, daily H from the BLS was strongly correlated with EC (r ≈ 0.82) but systematically lower, with a regression slope of ≈0.63 that persisted across timescales; this scale-invariant amplitude compression reflects the path-averaged, similarity-based nature of the scintillometer retrieval rather than the EC closure deficit, which instead governs the mean bias. BLS-derived daily ET showed a systematic positive bias relative to uncorrected EC (mean bias error, MBE = +0.30 mm d⁻¹; +16% cumulative). Applying the Bowen-ratio-preserving correction (CF = 1.24) to EC reduced this to MBE = −0.14 mm d⁻¹ (−6%), and the residual-to-LE correction yielded MBE = −0.15 mm d⁻¹ (−6.4%); the latter comparison is only partly independent, as both methods share the same Rn and G. The Bowen-ratio-preserving method is therefore recommended for this dataset. Overall, the BLS captured the temporal variability of crop water use well, but residual-based ET estimates require careful treatment of the energy-balance-closure gap and are sensitive to the high BLS gap fraction (61.6% of 15 min records over the overlap, exceeding 90% at night). Once EC is closure-corrected to serve as the reference, the BLS offers a cost-effective alternative for field-scale ET monitoring in the MENA region, subject to the conditional agreement documented here. Full article

Precipitation use efficiency (PUE) links ecosystem carbon uptake to precipitation input, but endpoint ratios alone cannot show where carbon–water coupling differs along ecohydrological pathways. This limitation is especially relevant in karst landscapes, where thin soils and heterogeneous hydrological pathways can decouple rainfall, soil moisture, evapotranspiration, and plant carbon gain. Here, we developed a PUE chain decomposition framework based on gross primary productivity (GPP), transpiration (T), evapotranspiration (ET), soil moisture (SM), and precipitation (PRE): PUE = GPP/T × T/ET × ET/SM × SM/PRE. In this framework, GPP/T represents carbon fixation per unit transpiration, T/ET the transpiration fraction of evapotranspiration, ET/SM evapotranspiration output relative to soil moisture, and SM/PRE soil moisture status relative to precipitation input. We used multi-source remote-sensing and reanalysis data from 2003 to 2022 to compare karst and non-karst landscapes in Southwest China, applied variance decomposition to quantify the contributions of chain terms and their interactions, and used Stacking ensemble learning with Shapley additive explanations (SHAP) to interpret model-inferred environmental associations. Mean PUE was 1.16 g C m⁻² mm⁻¹ in non-karst areas and 1.08 g C m⁻² mm⁻¹ in karst areas, and all four chain components differed significantly between landform types. Variance decomposition identified SM/PRE and its interaction terms as the largest contributors to PUE variability, mainly reflecting a precipitation-sensitive diagnostic signal and soil moisture status relative to precipitation input. Machine learning interpretation showed that solar radiation, leaf area index, aridity, and groundwater storage were associated with different chain components; karst areas showed stronger groundwater-storage signals and lower model-inferred response thresholds. These findings indicate that PUE differences in Southwest China arise from multiple linked diagnostic stages rather than from endpoint carbon uptake or precipitation alone. The framework can help locate water-use constraints and support landform-specific ecological restoration and water management. Full article

Maize crop yields are substantially diminished by drought during early phases of kernel development. Kernel development is also affected by stresses which limit photosynthate availability, such as high plant density and shade. To advance our understanding of the mechanisms by which these stresses affect kernel development, we subjected potted maize plants in the greenhouse to water stress and shade from 1 to 9 days after pollination and determined evapotranspiration, root growth in deep pots, carbohydrates and ABA in leaves and kernel tissues, and profiled expression of gene transcripts in kernel tissues with RNA-seq. Root development was decreased by shade, whereas it was increased by severe water stress (WS). Both severe WS and shade increased ABA levels in kernel tissues. A large fraction of differentially expressed genes in pedicel-placenta tissues of kernels were affected similarly by severe WS and shade, including genes involved in synthesis and response to ABA, carbohydrates, trehalose, and ethylene. Differential expression in response to mild WS was intermediate or minimal. In endosperm-nucellus, expression of genes in these categories was strongly affected by shade, but less so by severe WS. We conclude that the similarity of ABA accumulation and gene expression in pedicel-placenta of severe WS and shade indicates that this tissue likely plays a pivotal role in kernel set decisions. Full article

Hydrometeorological changes profoundly influence runoff generation and evolution in river basins. It is of great significance to carry out runoff prediction research to ensure water resources security and improve disaster prevention and mitigation capabilities. In this paper, the Ganhe River Basin in Northeast China was taken as the research object. Based on the hydrometeorological and runoff data from 1980 to 2022, a variety of statistical methods were used to systematically study the climate change, runoff evolution characteristics and driving mechanism of the basin. Combined with BP neural network model and CMIP6 climate scenario data, the future runoff changes were predicted. The results showed that the precipitation and relative humidity showed a downward trend, while the temperature, sunshine and evapotranspiration showed an upward trend during the study period. The runoff showed a non-significant upward trend, and an abrupt change occurred in 2009. After the abrupt change, the runoff increased by 38.7% compared with the baseline period. The change in land use was the most significant from 1990 to 2000, and the area of cultivated land increased significantly. Correlation analysis showed that precipitation was the dominant meteorological factor affecting runoff change, and the contribution rate of human activities was 88.51%, which was much higher than that of climate change. The BP neural network model demonstrated satisfactory simulation performance, and the training set and test set R2 reached 0.88 and 0.82, respectively. In the future, both temperature and precipitation will increase under different SSP scenarios. On this basis, the BP neural network prediction results show that the runoff of the basin is generally increasing, and the increase is the most significant under the high emission scenario, and the risk of extreme hydrological events may be further aggravated. These findings provide scientific support for water resources management and ecological conservation in the Ganhe River Basin. Full article

Forest cover change alters land–atmosphere exchanges of energy, water, and carbon, thereby influencing local and regional climate. This study assessed climatic patterns associated with afforestation in Khyber Pakhtunkhwa, Pakistan, from 2003 to 2023 using remote sensing data and Google Earth Engine. Land surface temperature (LST) was treated as the primary response variable, while evapotranspiration (ET) was analyzed as a secondary response variable. Air temperature; precipitation; vegetation indices, including the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI); and elevation were used as supporting variables to interpret the broader climatic and biophysical responses of afforestation. MODIS land-cover, LST, ET, and vegetation-index products, together with climate research unit (CRU) climate data and ALOS-PALSAR DEM, were used to evaluate spatiotemporal trends and variable relationships. The results showed that mean LST increased by 0.520 ± 0.070 °C across KP during 2003–2023; however, areas classified as forest gain showed a localized cooling pattern of 0.490 ± 0.050 °C during the 2013–2023 forest-cover transition assessment window. Afforested areas also exhibited increased ET, whereas forest-loss areas showed reduced ET and higher LST. Specifically, ET increased by 0.013 ± 0.002 mm/8-day in afforested areas, whereas forest-loss areas showed a decline of 0.005 ± 0.001 mm/8-day. CRU-derived regional air temperature showed an increasing tendency of 0.310 ± 0.050 °C, whereas precipitation showed only a weak and statistically non-significant regional tendency; therefore, precipitation was used only as background climatic context. The NDVI and the EVI were negatively correlated with daytime LST, and elevation showed a strong negative relationship with LST. Overall, the findings indicate that forest-cover gain was associated with localized surface cooling patterns and improved vegetation–climate regulation indicators in the study area. Full article

This study evaluates the spatial variability of hydric stress in the State of Sinaloa, northwestern Mexico, through the integrated analysis of hydroclimatic variables, multispectral remote sensing indicators, and environmental factors. Historical hydroclimatic conditions were analyzed using meteorological records from 1961 to 2020, whereas Landsat 8 imagery acquired on 7 July 2025, was used to evaluate the spatial expression of hydric stress. Reference evapotranspiration (ETo) was estimated using the FAO-56 Penman–Monteith methodology, and hydrological deficit conditions were determined from the relationship between precipitation (P) and ETo. Spectral indicators including land surface temperature ($\overline{T}$_a), the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and the NDWI/MNDWI relationship were used to evaluate vegetation response, surface moisture conditions, and thermal anomalies associated with hydric stress. The results revealed persistent conditions where ETo systematically exceeded P, with hydrological deficit values ranging from approximately −1600 mm·year⁻¹ to localized positive values near 50 mm·year⁻¹. The most severe deficits were concentrated within the northwestern and north-central agricultural valleys of Sinaloa. Statistical validation revealed significant negative relationships between hydrological deficit and all evaluated spectral indicators. The strongest association was observed for MNDWI (R² = 0.387), followed by NDWI/MNDWI (R² = 0.277), NDWI (R² = 0.220), and NDVI (R² = 0.134), confirming the sensitivity of vegetation and moisture-related indicators to long-term hydrological stress conditions. Spatial analyses revealed a strong correspondence among low NDVI, negative NDWI and MNDWI responses, elevated $\overline{T}$_a, and regions characterized by high atmospheric evaporative demand. Additional spatial validation integrating land-use and vegetation-cover changes (1993–2011), regional geology, topography, and the distribution of highly productive agricultural valleys demonstrated that the most severe hydrological deficits coincided with areas affected by vegetation-cover loss, agricultural expansion, and intensive land use. Although these datasets correspond to different observation periods, they collectively reflect the cumulative environmental effects associated with persistent hydrological stress across the region. The combined effects of hydrological imbalance, forest-cover reduction, and agricultural intensification have progressively reduced ecosystem resilience and increased environmental vulnerability throughout one of the most productive agricultural regions of northwestern Mexico. These findings provide a scientific basis for water-resource management, territorial planning, ecosystem restoration, and climate-adaptation strategies under increasing water-scarcity conditions. Full article