Search Results (42)

Maize (Zea mays L.) is the dominant cereal of continental Hungary, yet the Pannonian belt lost one-third of its planted area over the last decade (1150 kha to 770 kha in 2025). This study quantified how supplemental irrigation and biostimulants affect maize transpiration. Fourteen Dynamax Flow32-1K stem-heat-balance sensors recorded sap flow at 15 min resolution on the Sushi FAO 340 hybrid across seven irrigated–rainfed plot pairs at Karcag, Hungary. Measurements spanned a dry 2024 season (irrigation: 253 mm; precipitation: 7.9 mm; VPD_max: 1.71 kPa) and a wetter 2025 season (120 mm irrigation; 62.9 mm precipitation; mean VPD_max: 1.33 kPa). A Control-only mixed-effects model returned a year × irrigation interaction F(1, 84) = 106 (p < 10⁻¹⁵): irrigation raised transpiration by 77% in 2024 and lowered it by 12% in 2025. The VPD_max–transpiration coupling was inverted in 2024, the field signature of stomatal closure under soil-water limitation. The irrigated Big Compost plot reached a grain-based WUE of 97.5 kg mm⁻¹ versus 41.6 kg mm⁻¹ for the matched Control. This was a 2.3-fold within-2025 separation at similar per-plant transpiration. The irrigation response differed sharply between seasons. However, the amendment classes were tested in different years, and the irrigation dose differed between seasons (253 mm in 2024 versus 120 mm in 2025). The cross-class contrast is therefore exploratory, and every cross-year comparison is provisional. With one sensor per plot, the amendment ranking remains a hypothesis for a replicated, same-season, and same-dose follow-up. Full article

Against the backdrop of accelerated terrestrial hydrological cycling and the increasing concurrence of drought-heatwave compound extremes under global warming, regional land-atmosphere coupling has emerged as a central mechanism shaping climate feedbacks and trajectories of ecosystem carbon uptake. However, prior studies spanning climatic regimes, observational scales, and data sources have often yielded contradictory conclusions. Here, we challenge these fragmented perspectives by constructing an integrated LST-SM-ET-GPP chain that jointly represents land surface temperature, soil moisture, evapotranspiration, and gross primary productivity, thereby linking water availability, surface energy balance, and plant physiological processes within a unified framework. We synthesize a conceptual diagnostic roadmap for interpreting land-atmosphere coupling across observations and models. When ecosystems operate in humid, energy-limited environments, radiative and advective controls should be prioritized to diagnose system forcing. By contrast, as the system becomes water-depleted, attribution must shift to a nonlinear regime transition framework governed by a critical soil moisture threshold. This threshold mechanism implies that, once the system enters the moisture-limited regime, even modest declines in soil moisture can trigger a rapid weakening of evaporative cooling, substantially amplifying LST anomalies and strongly suppressing GPP. The competitive regulation of stomatal conductance by atmospheric demand (vapor pressure deficit, VPD) and terrestrial supply (rootzone soil moisture) further explains why the “dominant” controlling factor can dynamically reverse across hydrothermal states, timescales, and stages of extreme-event evolution. Notably, the steady-state coupling assumption may break down under flux “flooring” during extreme drought, or when structural buffering such as deep root water uptake is present, delineating strict applicability bounds for existing diagnostic frameworks. Finally, current assessments remain constrained by multiple uncertainties, particularly the lack of ET partitioning constraints, representativeness biases arising from clear-sky observations and sampling-depth limitations, and systematic errors in Earth system model simulations during the warm season. Full article

Grasslands, covering over 40% of terrestrial land surfaces, play a critical role in regional water cycling through their greening processes. However, the decoupling mechanisms between grassland greening and water availability (WA) changes across the Northern Hemisphere, along with their future trajectories, remain poorly understood. Here, we integrated multi-source satellite observations with CMIP6 model ensembles to systematically assess the spatiotemporal evolution and trend divergence of leaf area index (LAI) and WA across Northern Hemisphere grasslands from 2000 to 2100. Our results showed that grassland LAI exhibited sustained growth during 2000–2020, with 55.28% of regions showing significant increasing trends. However, 73.67% of grassland regions experienced declining WA during the historical period, revealing widespread decoupling between grassland greening and water deficit. Future scenario projections indicated a reversal to increasing WA trends, with 57.51% of regions showing significant increases under SSP5–8.5. Furthermore, 61.87% of grasslands exhibited greening-driven drying (GDD) characteristics during the historical period, while greening-driven wetting (GDW) regions were projected to expand to 72.44% in the future. Analysis along aridity gradients revealed that humid zones contributed most prominently to LAI and WA changes. Mechanistic decomposition demonstrated that grassland WA changes shifted from precipitation-dominated control (53.60%) in the historical period toward a regime jointly governed by precipitation dominance and coupled precipitation–evapotranspiration drivers in the future. Concurrently, the dominant factor controlling grassland greening transitioned from vapor-pressure deficit (VPD) to temperature (TEM) control. Additionally, driving factors exhibited pronounced differentiation patterns along aridity gradients during the historical phase: arid zones were dominated by soil moisture (SM) and semi-arid zones displayed dual control by SM and VPD, while humid zones were governed by coupled TEM-VPD regulation. This study reveals the divergent trends between grassland greening and WA and unravels their driving mechanisms, offering important scientific evidence for formulating regionally differentiated ecological water resource management strategies. Full article

This systematic review synthesizes passive and passive-first cooling strategies for greenhouses in hot–arid climates, organizing evidence across four domains: Airflow & Ventilation, Shading & Radiative Control, Thermal Storage & Ground Coupling, and Structural Design & Geometry. Drawing on the project corpus, we analyze 10–13 distinct techniques including ridge and side natural ventilation, windcatchers and solar chimneys, external shade nets, NIR-selective and transparent radiative-cooling films, and dynamic PV shading; earth-to-air heat exchangers (EAHE/GAHT), rock-bed sensible storage, phase-change materials (PCMs), and sunken or buried envelopes; as well as roof slope and shape, span number, and orientation. Across studies, cooling outcomes are reported as peak or daytime indoor air temperature reductions, defined relative either to outdoor conditions or to a control greenhouse, with the reference frame and temporal aggregation specified in the synthesis. Typical outcomes include ≈3–7 °C daytime reduction for optimized ventilation, ≈2–4 °C for shading and spectral covers while preserving PAR, ≈5–7 °C intake cooling for EAHE with winter pre-heating, and up to ≈14 °C peak attenuation for rock-bed storage under favorable conditions. Structural choices consistently amplify these effects by sustaining pressure head and limiting thermal heterogeneity. Performance is strongly context-dependent—governed by wind regime, diurnal amplitude, dust and UV exposure, and crop-specific light and temperature thresholds—and the most robust results arise from stacked, site-specific designs that combine skin-level radiative rejection, buoyancy-supportive geometry, and ground or latent buffering with minimal active backup. Smart controllers that modulate vents, shading, and targeted fogging or fans based on VPD or temperature differentials improve stability and reduce water and energy use by engaging actuation only when passive capacity is exceeded. We recommend standardized composite metrics encompassing temperature moderation, humidity stability, PAR availability, and water and energy use per unit yield to enable fair cross-study comparison, multi-season validation, and policy adoption. Collectively, the synthesized techniques provide a practical palette for improved greenhouse climate management under hot and arid conditions. Full article

TENS constitutes a critical ecological barrier on the southeastern margin of the Qinghai–Tibet Plateau, providing essential services such as water conservation and biodiversity protection and helping to safeguard water security in the upper reaches of the Yangtze and Yellow Rivers. Thus, elucidating its vulnerability dynamics is paramount for regional security. Integrating multi-source spatiotemporal data with an interpretable XGBoost–SHAP framework, we quantified interannual variation in vulnerability and the nonlinear threshold responses of key drivers. The results showed pronounced nonlinear phase changes in vulnerability, with 47.96% of the area experiencing abrupt shifts. Notably, 37.89% of TENS reversed from decreasing to increasing vulnerability. TENS underwent an intensive transition during 2010–2015. Interannual variability was dominated by the coupled influence of human disturbance, soil moisture, and atmospheric water, accounting for nearly 60% of the variation, and showed distinct thresholds. Grazing intensity < 0.90 SU/ha was a moderate disturbance, reducing vulnerability, but it became a stressor above this level. Soil moisture showed an inflection point at 79 mm, while vapor pressure deficit (VPD) < 0.39 kPa enhanced resilience, revising the view of VPD as solely a stress factor. Different ecosystems exhibited distinct driving mechanisms. Grasslands were controlled by shallow soil moisture and grazing, forests by hydrothermal balance, and wetlands by low-intensity anthropogenic disturbance (NTL as a proxy; e.g., tourism development or urban expansion). These findings highlight the risk of abrupt shifts in vulnerability regimes (turning points and trend reversals) and support management that emphasizes quality improvement and threshold-based risk management. Full article

Evapotranspiration (ET) links the water cycle with the energy balance and serves as a key driving process for ecosystem functioning and water resource management. Canopy conductance (Gc) plays a central role in regulating transpiration, but many models inadequately represent its regulatory mechanisms and show varying applicability across different land cover types. This study develops a remote-sensing ET estimation approach suitable for large scales and diverse land cover types and proposes an improved canopy conductance model for daily latent heat flux (LE) estimation. By integrating the canopy radiation transfer concept from the K95 model into the multiplicative Jarvis framework, an improved canopy conductance model is developed that includes limiting effects from photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T), and soil moisture (θ). Eighteen combinations of limiting functions are designed to evaluate structural performance differences. Using observations from 79 global flux sites during 2015–2023 and integrating multi-source datasets, including ERA5, MODIS, and SMAP, a two-stage parameter optimization was applied to determine the optimal limiting function combination for each land cover type. And nine sites from nine different land cover types were selected for independent spatial validation. Temporal validation within the optimization sites shows that, at the daily scale, the model achieves a Kling–Gupta efficiency (KGE) of 0.82, a correlation coefficient (R) of 0.82, and a Root Mean Square Error (RMSE) of 27.83 W/m², demonstrating strong temporal stability. Spatial validation over independent holdout sites achieved KGE = 0.84, R = 0.84, and RMSE = 22.53 W/m². At the 8-day scale, when evaluated over the holdout sites, the model achieves KGE = 0.87, R = 0.88, and RMSE = 18.74 W/m². Compared with the K95 and Jarvis models, KGE increases by about 34% and 15%, while RMSE decreases by about 38% and 12%, respectively. Relative to the MOD16 and PML-V2 products, KGE increases by about 32% and 16%, while RMSE decreases by about 33% and 17%, respectively. Comprehensive comparisons show that explicitly coupling canopy structure with multiple environmental constraints within the Jarvis framework, together with structure optimization across land cover types, can markedly improve large-scale remote-sensing ET retrieval accuracy while maintaining physical consistency and physiological rationality. This provides an effective pathway and parameterization scheme for producing ET products applicable across ecosystems. Full article

In the context of global climate change, solar-induced chlorophyll fluorescence (SIF), a robust proxy for gross primary productivity, is modulated by the coupled effects of soil moisture (SM) and vapor pressure deficit (VPD). However, fine-scale spatial heterogeneity in the SM–VPD–SIF interactions and their modulation by land use/cover change (LUCC) remain inadequately explored, particularly in transitional agricultural zones. This study utilized growing-season data (2001–2020) from Henan Province, China, and applied an integrated analytical framework combining Random Forest with GeoShapley analysis, alongside threshold detection and sensitivity modeling. The analysis was stratified by three dominant LUCC types: cropland, natural land, and built-up area. The key findings are as follows: (1) VPD and its geographic interaction terms (VPD × Longitude, VPD × Latitude) dominated the variability in SIF, exhibiting a combined contribution (Shapley value) over six times greater than that of SM and its geographic interactions. (2) LUCC-specific thresholds were identified: croplands exhibited the lowest SM threshold (approx. 0.231 m³/m³) and the highest sensitivity to VPD (−0.234 ± 0.018); natural lands displayed a shift from SM-dominated to VPD-dominated regulation at a VPD threshold of approximately 0.7 kPa; built-up areas showed weak environmental coupling. (3) The co-occurrence of high SM and high VPD induced significant SIF suppression in croplands, whereas natural lands demonstrated greater hydraulic resilience. This study provides a quantitative framework for understanding spatially explicit SM–VPD–SIF interactions and offers actionable thresholds (e.g., VPD of 0.7–0.8 kPa) to inform precision irrigation and drought risk management in transitional agricultural climates under future climate scenarios. Full article

Understanding how cultivated xerophytic shrubs physiologically regulate canopy water loss under anomalously wet conditions is crucial for predicting ecohydrological responses and for providing practical guidance in landscape restoration under the ongoing warming–wetting trend on the northern Loess Plateau. This study tested hypotheses concerning the hierarchy of atmospheric and soil-water controls on canopy transpiration (E_c), stomatal conductance (g_s), the strength of canopy–atmosphere coupling, and species-specific soil-water sensitivities and water-use strategies in Caragana korshinskii and Salix psammophila. Concurrent measurements of branch-level sap flow, meteorological variables, and soil water content (SWC) at multiple depths were conducted in two adjacent stands during the wet season of a climatically wet year (July–September 2017). Meteorological factors, particularly vapor pressure deficit (VPD), were the dominant drivers of daily E_c and g_s, whereas SWC exerted secondary but species-specific influences. Both shrubs were strongly coupled to the atmosphere, with consistently low decoupling coefficients (Ω ≈ 0.11–0.15) on daily scales. C. korshinskii maintained stable water use through access to deeper soil, whereas S. psammophila responded sensitively to fluctuations in shallow SWC. These contrasting patterns indicate depth-partitioned water-use strategies and a context-dependent continuum between isohydric and anisohydric behavior rather than fixed species traits. The findings support improved parameterization of shrub water use in ecohydrological models, more effective water-use management, and informed species selection and nursery practices for landscape restoration in semi-arid regions experiencing warming–wetting climatic shifts. Full article

The On-Load Tap Changer (OLTC) in power transformers is a critical component responsible for regulating the output voltage, and the early detection of OLTC faults is essential for maintaining power grid stability. In this paper, we propose a one-class deep learning anomaly detection model named “U-AttentionFlow” based on acoustic signals from the OLTC operation. The proposed model is trained exclusively on normal operating data to accurately model normal patterns and identify anomalies when new signals deviate from the learned patterns. To enhance the ability of the model to focus on significant features, we integrate the squeeze-and-excitation (SE) block and Convolutional Block Attention Module (CBAM) into the network architecture. Furthermore, static positional encoding and multihead self-attention (MHSA) are employed to effectively learn the temporal characteristics of time-series acoustic signals. We also adopted a U-Flow-style invertible multiscale coupling structure, which integrates features across multiple scales while ensuring the invertibility of the model. Experimental validation was conducted using acoustic data collected under realistic voltage and load conditions from actual ECOTAP VPD OLTC equipment, resulting in an anomaly detection accuracy of 99.15%. These results demonstrate the outstanding performance and practical applicability of the U-AttentionFlow model for OLTC anomaly detection. Full article

Canopy conductance (G_c) is an important biological constant for quantifying the water vapor flux at the canopy-atmosphere interface, reflecting the coupling strength between crop transpiration and microclimate. To elucidate how mulching modulates G_c dynamics under varying environments, we measured the transpiration of maize based on thermal equilibrium method from 2020 and 2021, synchronously recording solar radiation (R_s), temperature (T), relative humidity (RH), and vapor pressure deficit (VPD) under no-mulching (NM), transparent film (TFM), black film (BM), and straw mulching (SM) treatments in the North China Plain. The results showed that in the near-surface microenvironment, at early stages (seedling-jointing), compared to the NM treatment, TFM and BM treatments unexpectedly reduced temperature by 0.1–1.1% while increasing humidity by 0.2–4.0%, lowering VPD by 0.7–15.5%, contradicting presumed warming effects. During tasseling-filling stages, both plastic films elevated temperature by 3.5–5.2%, decreased humidity by 5.2–6.9%, and sharply increased VPD by 23.4–27.6%, inducing heat-VPD coupling stress. Throughout the entire growth period, SM treatment resulted in an initial increase followed by a decrease in temperature, but the decrease in humidity and increase in VPD occurred earlier and smoothly compared to film mulching treatment in the near-surface microenvironment. All treatments increased average temperature but decreased average humidity in the near-ground microenvironment throughout growth stages, ultimately leading to an increase in average VPD. In addition, all treatments increased G_c at noon by 10.3–81.2%. Under different solar radiation conditions, TFM, BM, and SM treatments increased the reference conductance (G_cR) but did not always increase G_c sensitivity to VPD (m). We propose a specific mulching strategy: Using black or transparent plastic film mulching in arid/cold regions and straw mulching in high-temperature and drought-prone/rain-fed agricultural areas can reconcile the trade-off between microclimate optimization and physiological adaptation, advancing precision water management in arid-prone croplands. Full article

Solar-induced chlorophyll fluorescence (SIF) is a powerful tool for the estimation of gross primary productivity (GPP), but the relationship between SIF and GPP under drought stress remains incompletely understood. Elucidating the response of the relationship between SIF and GPP to drought stress is essential in order to enhance the precision of GPP estimation in forests. In this study, we obtained SIF in the red (SIF₆₈₇) and far-red (SIF₇₆₀) bands and GPP data from tower flux observations in a Chinese cork oak plantation to explore the response of the diurnal GPP-SIF relationship to drought stress. The plant water stress index (PWSI) was used to quantify drought stress. The results show that drought reduced SIF and GPP, but GPP was more sensitive to drought stress than SIF. The diurnal non-linear relationship of GPP-SIF (R²) decreased with the increase in drought stress, but a significant non-linear correlation remained for GPP-SIF (R²_GPP-SIF₇₆₀ = 0.30, R²_GPP-SIF₆₈₇ = 0.23) under severe drought stress (PWSI_bin: 0.8–0.9). Physiological coupling strengthened the GPP-SIF relationship under drought, while canopy structure effects were negligible. Random forest and path analyses revealed that VPD was the key factor reducing the GPP-SIF correlation during drought. Incorporating VPD into the GPP-SIF relationship improved the GPP estimation accuracy by over 48% under severe drought stress. The red SIF allowed for more accurate GPP estimations than the far-red SIF under drought conditions. Our results offer important perspectives on the GPP-SIF relationship under drought conditions, potentially helping to improve GPP model predictions in the face of climate change. Full article

Vegetation water-use efficiency (WUE), which represents the trade-off between carbon assimilation and water consumption, is a key indicator of ecosystem adaptation to environmental change. While previous studies have addressed the climatic controls on WUE in alpine ecosystems, the quantitative response mechanisms along elevation gradients remain insufficiently explored. This study investigated the growing season WUE patterns of alpine grasslands across elevation zones on the Qinghai–Tibetan Plateau by integrating partial correlation analysis and structural equation modeling (SEM). The findings revealed a clear triphasic pattern in WUE variation: a modest increase below 3000 m, a pronounced peak near 3700 m, and a steady decline at higher elevations. The dominant hydrothermal drivers shift with elevation. At lower altitudes, WUE was primarily influenced by the vapor pressure deficit (VPD), whereas soil temperature (ST) and VPD jointly govern WUE at mid-to-high altitudes. The SEM results indicated that the total effect of temperature on WUE increased from 0.51 at low elevations to 0.95 at high elevations, while the total effect of precipitation rose from −0.36 to −0.18. ST and VPD mediate the effects of temperature and precipitation on WUE, reflecting indirect and nonlinear regulatory pathways. Moreover, contribution rate analysis showed an elevation-dependent shift in WUE control: evapotranspiration (ET) exerted a dominant influence at low elevations (contribution rate: −82.50%), while net primary productivity (NPP) became the primary driver at high elevations (contribution rate: 54.71%). These findings demonstrate that alpine vegetation’s carbon–water coupling exhibits threshold-like behavior along altitudinal gradients, governed by differentiated hydrothermal constraints, offering new insights into ecosystem resilience under climate change. Full article

Water use efficiency (WUE), as an important metric for ecosystem resilience, has been identified to play a significant role in the coupling of carbon and water cycles. The farming–pastoral ecotone of Northern China (FPENC), which is highly susceptible to drought due to water scarcity, has long been recognized as an ecologically fragile zone. The ecological restoration projects in China have mitigated land degradation and maintain the sustainability of dryland. However, the process of greening in drylands has the potential to impact water availability. A comprehensive analysis of the WUE in the FPENC can help to understand the carbon absorption and water consumption. Using gross primary production (GPP) and evapotranspiration (ET) data from a MODerate resolution Imaging Spectroradiometer (MODIS), alongside biophysical variables data and land cover information, the spatio-temporal variations in WUE from 2003 to 2022 were examined. Additionally, its driving force and the ecosystem resilience were also revealed. Results indicated that the annual mean of WUE fluctuated between 0.52 and 2.60 gC kgH₂O⁻¹, showing a non-significant decreasing trend across the FPENC. Notably, the annual averaged WUE underwent a significant decline before 2012 (p < 0.05), and then showed a slight increased trend (p = 0.14) during the year afterward (i.e., 2013–2022). In terms of climatic controls, temperature (Temp) and soil volumetric water content (VSWC) dominantly affected WUE from 2003 to 2012; VPD (vapor pressure deficit), VSWC, and Temp showed comprehensive controls from 2013 to 2022. The findings suggest that a wetter atmosphere and increased soil moisture contribute to the decline in WUE. In total, 59.2% of FPENC was shown to be non-resilient, as grassland occupy the majority of the area, located in Mu Us Sandy land and Horqin Sand Land. These results underscore the importance of climatic factors in the regulation WUE over FPENC and highlight the necessity for focused research on WUE responses to climate change, particularly extreme events like droughts, in the future. Full article

Ecosystem water use efficiency (WUE) is a key indicator of the coupling between carbon and water cycles. With the increasing frequency of extreme climate events, WUE may also show trends of extremization. Understanding the dominant drivers behind extreme WUE variations is crucial for assessing the impact of climate variability on WUE. We investigate the main drivers and regional sensitivity of extreme WUE variations across seven geographical regions in China. The results reveal that extreme WUE variations are collectively influenced by gross primary productivity (GPP) and evapotranspiration (ET) (43.72%). GPP controls extreme WUE variations in 36.00% of the areas, while ET controls 20.17%. Furthermore, as the climate shifts from arid to humid regions, the area where GPP dominates extreme WUE variations increases, while the area dominated by ET decreases, suggesting a relationship with precipitation. Ridge regression analysis shows that vapor pressure deficit (VPD) is the primary driver of interannual WUE variation in China, with an average relative contribution of 38.64% and an absolute contribution of 0.025 gC·m⁻²·mm⁻¹·a⁻¹. We studied the changes in WUE and its driving mechanisms during extreme disaster events, providing a perspective focused on extreme conditions. In the future, these results may help regulate the carbon–water cycle in different regions, such as by guiding vegetation planting and land use planning based on the spatial characteristics of the dominant factors influencing extreme WUE variations to improve vegetation WUE. Full article

In this study of constructing gross primary production (GPP) based on solar-induced chlorophyll fluorescence (SIF) and analyzing its spatial–temporal characteristics and influencing factors, numerous challenges are encountered, especially in arid regions with fragile ecologies. Coupling SIF with other factors to construct the GPP and elucidating the influencing mechanisms of environmental factors could offer a novel theoretical method for the comprehensive analysis of GPP in arid regions. Therefore, we used the GPP station data from three different ecosystems (grasslands, farmlands, and desert vegetation) as well as the station and satellite data of environmental factors (including photosynthetically active radiation (PAR), a vapor pressure deficit (VPD), the air temperature (Tair), soil temperature (Tsoil), and soil moisture content (SWC)), and combined these with the TROPOMI SIF (RTSIF, generated through the reconstruction of SIF from the Sentinel-5P sensor), whose spatiotemporal precision was improved, the mechanistic light reaction model (MLR model), and different weather conditions. Then, we explored the spatiotemporal characteristics of GPP and its driving factors in local areas of Xinjiang. The results indicated that the intra-annual variation of GPP showed an inverted “U” shape, with the peak from June to July. The spatial attributes were positively correlated with vegetation coverage and sun radiation. Moreover, inverting GPP referred to the process of estimating the GPP of an ecosystem through models and remote sensing data. Based on the MLR model and RTSIF, the inverted GPP could capture more than 80% of the GPP changes in the three ecosystems. Furthermore, in farmland areas, PAR, VPD, Tair, and Tsoil jointly dominate GPP under sunny, cloudy, and overcast conditions. In grassland areas, PAR was the main influencing factor of GPP under all weather conditions. In desert vegetation areas, the dominant influencing factor of GPP was PAR on sunny days, VPD and Tair on cloudy days, and Tair on overcast days. Regarding the spatial correlation, the high spatial correlation between PAR, VPD, Tair, Tsoil, and GPP was observed in regions with dense vegetation coverage and low radiation. Similarly, the strong spatial correlation between SWC and GPP was found in irrigated farmland areas. The characteristics of a low spatial correlation between GPP and environmental factors were the opposite. In addition, it was worth noting that the impact of various environmental factors on GPP in farmland areas was comprehensively expressed based on a linear pattern. However, in grassland and desert vegetation areas, the impact of VPD on GPP was expressed based on a linear pattern, while the impact of other factors was more accurately represented through a non-linear pattern. This study demonstrated that SIF data combined with the MLR model effectively estimated GPP and revealed its spatial patterns and driving factors. These findings may serve as a foundation for developing targeted carbon reduction strategies in arid regions, contributing to improved regional carbon management. Full article