Search Results (729)

Accurately estimating latent heat flux (LE) across water-limited grassland ecosystems is critically hampered by strong land-surface heterogeneity and pronounced intra-annual variability. Here, we proposed a ConvTransformer framework by integrating MODIS remote sensing products, China Meteorological Forcing Dataset (CMFD) data, and eddy covariance observations from six grassland sites to estimate daily LE across the Inner Mongolia grasslands. The model was evaluated using a leave-one-site-out cross-validation strategy and compared with three widely used machine learning models, including random forest (RF), gradient boosting regression trees (GBRT), and support vector regression (SVR). Across the six validation sites, the ConvTransformer achieved an average R² of 0.69, an RMSE of 12.56 W m⁻², a Bias of 0.67 W m⁻², and an average KGE of 0.82. Although RF produced slightly higher R² values at several individual sites, the ConvTransformer exhibited the highest overall KGE and the most stable performance, indicating superior cross-site generalization. Based on the trained model, a 1 km daily LE dataset for the Inner Mongolia grasslands during 2003–2018 was generated. The estimated LE revealed a distinct decreasing gradient from southeast to northwest and marked seasonality, with summer dominating the annual latent heat exchange. These results suggest that the ConvTransformer constitutes an effective framework for regional LE estimation, while also offering a valuable alternative for ecohydrological studies and regional water-resource assessment in water-limited grassland ecosystems. Full article

The logarithmic law of the wall is a foundational element in turbulence modeling. Its classical derivation, rooted in Prandtl’s mixing-length theory, is predicated on the existence of a constant shear stress layer. This paper demonstrates that this foundational assumption is not strictly satisfied for two-dimensional, uniform open-channel flows, where the Reynolds shear stress profile exhibits a distinct peak near the bed and never forms a true constant stress zone. We present a novel mechanistic derivation that circumvents this inconsistency. By reframing the bed shear stress as the time-averaged momentum flux from discrete, wall-coherent eddy impacts, we recover the log law through a mechanistic framework. Our model starts from the physical definition of the Reynolds stress at the bed, employs kinematic scaling for the velocity fluctuations, and incorporates the geometric constraint of eddy size. This approach does not require a constant stress layer and provides a more physically defensible explanation for the emergence and robustness of the log-law, directly linking it to the underlying structure of wall turbulence. The derivation resolves the long-standing paradox between the theory’s assumption and the empirical reality in open channel flows. Full article

Given the modernization of power systems in recent years, the quality of electrical energy is changing. With the increasing prevalence of harmonic components and rising current densities, conductor efficiency has become critically important. This study investigates the skin effect as a function of conductor geometry within the framework of electromagnetic field theory. Classical circular cross-section cable geometries and rectangular busbar systems were compared under an AC current of 1350 A (peak) across a frequency range of 50–500 Hz. The findings are comparatively presented, and their electromagnetic and thermal implications are discussed. Numerical modeling and simulation studies were performed using the Finite Element Method. COMSOL Multiphysics^® software AC/DC Module 6.2 version was used for the analyses. In the simulation studies, the magnetic flux density distribution within the conductor and the current concentration induced by eddy currents were analyzed. Frequency-dependent behavioral characteristics were examined in the analyses. The results revealed that the conductor with circular geometry exhibited a more severe skin effect. The rectangular conductor used in busbar systems was found to effectively distribute the current density across its surface area. Thus, rectangular geometry optimizes AC resistance. The analysis results revealed that conductor design and material selection depend not only on the cross-sectional area but also on the geometric shape factor. In this context, it was determined that conductor design has a decisive effect on electromagnetic power losses, which directly govern the heat generation potential within high-current systems. This study serves as a technical guide to evaluate frequency-dependent electromagnetic performance across a 50–500 Hz range—reflecting frequencies relevant to harmonic components—to assist in the design and optimization of high-current energy distribution systems. Full article

The Eddy Covariance station provides observations of agrometeorological variables and surface energy fluxes, collected from 2019 to 2022, in a citrus orchard located in the Souss-Massa plain, Morocco. The present dataset comprises measurements recorded via a set of aboveground and subsurface sensors. The aboveground setup consistently measures air temperature, relative humidity, wind speed, net radiation, and precipitation. Additionally, the subsurface setup continuously tracks soil temperature, moisture, and electrical conductivity at depths from 5 to 80 cm, along with soil heat flux. Moreover, these setups enable the measurement of turbulent fluxes (sensible and latent heat). Given the limited availability of long-term agrometeorological data in semi-arid regions of the Mediterranean, this paper addresses a critical data gap by providing a reliable agrometeorological dataset. The latter consists of two types of data: 30 min interval files and high-frequency files (20 Hz, i.e., one measurement every 50 ms). The processing of this data involved Card Convert, MATLAB EC-Pack, and Excel, with data quality control performed by removing outliers and excluding nighttime fluxes. The dataset is organized in a table and provided in a .csv format with standard metadata. It is designed for a wide range of applications, including evapotranspiration modeling, satellite product validation, agroclimatic monitoring, determining crop irrigation requirements, precision irrigation planning, and water management. Additionally, the dataset can be reused for crop and hydrological model calibration, as well as soil moisture and crop stress prediction using machine learning algorithms. Full article

This study explores the potential of Artificial Neural Networks (ANNs) for the calculation of momentum and sensible heat fluxes. The ANN is applied on idealized Large Eddy Simulation (LES) data. The LES test cases used to train the ANN correspond to convective conditions with partially low wind speeds and heterogeneous surfaces. To enable the ANN to learn the systematics of such conditions, the input variables for the ANN include the variables that are used in Monin Obukhov Similarity Theory (MOST) and an additional variable that accounts for the heterogeneity of the land surface. Simulation data is averaged over 30 min and different spatial scales. Our findings show that the modeling skill is generally higher for momentum flux than for sensible heat flux. Also, the performance increases with larger spatial-averaging scales. The ANN calculates momentum flux with a correlation of 0.81 and a normalized RMSE of 0.59 for a single grid point. On a spatial-averaging scale of 4000 m, the correlation changes to almost 1.00 and the normalized RMSE to 0.05. The importance of each input variable for model performance is determined with a feature importance weighting. Their relative importance depends strongly on the spatial-averaging scale. The importance of the variable that represents the influence of surface heterogeneity is low at smaller spatial-averaging scales, but increases at larger averaging scales. However, its contribution to the modeling skill is small. Reducing the number of input variables to two results in a substantial loss of performance. Although our results demonstrate the potential of this approach to improve the calculation of momentum and sensible heat fluxes, it is also clear that there are simplifications and limitations in the present setup that need to be overcome to assess general applicability. These include the height of analysis (40 m instead of 10 m or less), the exclusion of all latent heat processes, the exclusion of stable conditions, the data coverage of the required parameter space, and the usage of only surface roughness length to define surface heterogeneity. Full article

The carbon budget of maize croplands has been widely studied across the Chinese Maize Belt. However, the effects of drought on ecosystem-scale carbon fluxes in rain-fed maize croplands remain poorly understood in Southwest China. To address this gap, we conducted long-term, continuous eddy covariance measurements of carbon fluxes at a rain-fed maize field in Guizhou Province from 2022 to 2025. During the maize growing season, the mean net ecosystem exchange (NEE) was −310 ± 21 g C m⁻², with over 50% of the total seasonal NEE occurring in July. Interannual variability in the NEE was primarily driven by prolonged dry spells during the reproductive stage. Maize cropland without straw return acted as a net C source when harvest removals were considered. We therefore recommend promoting straw return practices in the region to strengthen soil carbon sequestration capacity and enhance agroecosystem resilience to drought. And further research is needed to evaluate the role of straw return practices on the carbon budget in the area. Full article

Mesoscale eddies play an important role in upper-ocean heat redistribution, yet the mechanisms controlling eddy-induced sea surface temperature anomaly (SSTA) patterns remain incompletely understood. In this study, we investigate how air–sea turbulent heat flux damping modulates eddy-induced SSTA patterns in the Subtropical Countercurrent (STCC) and Kuroshio Extension (KE) regions of the northwestern Pacific. Using satellite observations, reanalysis products, and eddy trajectory data from 2010 to 2019, we composite cyclonic and anticyclonic eddies in different seasons and quantify the relative contributions of monopole and dipole SSTA components. The results show that the STCC region exhibits a larger dipole contribution and a higher normalized SSTA damping rate than the KE region in both warm and cold seasons. This regional contrast suggests that stronger SSTA damping is associated with a more pronounced dipole SSTA pattern, whereas weaker damping favors a more monopole structure. The spatial distribution of the normalized damping rate closely resembles that of the turbulent heat flux response rate, while mixed-layer depth appears to play a secondary role in shaping the large-scale damping pattern. In addition, the damping rate increases with background wind speed, indicating that wind speed may modulate eddy-induced SSTA patterns by enhancing turbulent heat flux feedback. These findings highlight the potential role of air–sea turbulent heat flux damping in shaping regional differences in eddy-induced SSTA patterns and provide a useful perspective for understanding mesoscale air–sea interaction in the northwestern Pacific. Full article

With increasing rail traffic intensity, reliable detection of shallow subsurface rail damage is essential for operational safety. This critical narrative review evaluates non-destructive testing technologies relevant to defects whose active crack front or principal scattering zone lies within the upper approximately 0.5–10 mm of the rail, while treating the 10–15 mm range as a transition to deeper-defect verification. Magnetic flux leakage, magnetic particle inspection, visual inspection, eddy current testing, and conventional ultrasonic testing are first examined as screening or confirmatory comparators. The review then focuses on four ultrasonic surface-wave excitation routes—contact piezoelectric, active air-coupled, electromagnetic acoustic, and laser ultrasonic—and distinguishes source-specific laboratory capability from demonstrated field evidence. Because the cited studies use different defect geometries, rail conditions, sensor configurations, speeds, and decision criteria, their numerical values are reported as source-conditioned evidence rather than as a normalized ranking. An engineering decision matrix links defect depth and size, inspection speed, surface condition, and noise environment to a recommended screening–confirmation workflow. The synthesis identifies contact piezoelectric UT/PAUT as the most mature quantitative confirmation route, while EMAT, air-coupled UT, and laser UT retain method-specific advantages but require stronger natural-defect and in-service validation. Full article

Wide-scale, spatio-temporal quantification of soil CO₂ efflux is essential for understanding terrestrial carbon dynamics, predicting climate change, and evaluating the carbon balance in managed and natural ecosystems. Rising global temperatures, changing land use patterns, and other activities aimed at boosting crop productivity have resulted in an increase in microbial activity, increasing the impact of soil on gas exchange. Therefore, it is important to measure ${\mathrm{CO}}_2$ gas exchange in situ, over wide areas and extended periods without manual intervention. However, current approaches such as remote sensing lacks sufficient spatial and depth resolution, while other direct measurements such as eddy covariance demand expensive infrastructure, limiting wide-scale deployment. In this work, we propose a low-cost, battery-operated ${\mathrm{CO}}_2$ sensing system that provides long-term and scalable monitoring of soil respiration and carbon flux, with the promise for high-resolution measurements. Our innovative design features a PVC-based gas chamber that periodically opens and closes to allow for gas exchange, and a sensor module with low-cost temperature, moisture, pressure, and ${\mathrm{CO}}_2$ sensors, with a low-power wireless LoRa network for real-time monitoring. Our system was rigorously validated through multiple outdoor deployments, over long periods to demonstrate its practicality. We observe that temperature, air pressure, and humidity trends show responsiveness to the environment. We also observe that ${\mathrm{CO}}_2$ emission flux rate vary significantly across different modules, underscoring the need for fine-grained spatial and temporal resolution in monitoring. Full article

We present a machine learning approach for developing subgrid-scale (SGS) parameterizations in coarse simulations of partial differential equations. We utilize structure-preserving neural networks and entropy variables to learn subgrid fluxes in coarse simulations of the Burgers’ equation. In particular, we employ a decoupled neural network architecture explicitly separating the subgrid corrections into two distinct components: a conservative Flux Potential network and an Eddy Viscosity network. We demonstrate that this reduced-order framework maintains high physical fidelity, accurately reproducing the energy spectrum, spatial and temporal correlation functions, and dynamical characteristics of the full-scale system. Furthermore, we show that our approach is robust and applicable to parameters outside the training regime. 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

Metallic probe carriers are commonly used in magnetic flux leakage (MFL) inspection to support sensing elements and maintain lift-off, but a conductive carrier located near the sensor can act as an active electromagnetic boundary. This study investigates the carrier-induced waveform reconstruction caused by such a conductive near-field boundary. A theoretical model is developed to describe the induced current, secondary magnetic field, and relaxation-related downstream memory generated when the carrier moves through a non-uniform leakage field. Transient finite-element simulations are used to examine the effects of carrier material, scanning speed, and concave carrier geometry. Compared with the air reference, aluminum and copper carriers produce stage-dependent waveform reconstruction, including valley modification, peak modulation, feature-position shift, and trailing-side extension. The quantitative waveform-deviation indicators increase with increasing speed and are further regulated by carrier geometry. Experimental results based on repeated magnetic response events confirm amplitude suppression, non-zero residual after amplitude matching, response broadening, and enhanced trailing asymmetry. These results demonstrate that the metallic probe carrier is not an electromagnetically transparent holder but an active near-field conductive boundary that should be considered in probe-carrier design and MFL signal interpretation. Full article

This paper investigates the impact of segmented permanent magnet (PM) configurations on torque production, eddy current loss, and demagnetization in spoke-type flux-intensifying interior permanent magnet (FI-IPM) motors. While PM segmentation has been explored in conventional interior permanent magnet synchronous motors (IPMSMs) for reducing losses, its effect in flux-intensifying (FI) motors, characterized by reverse saliency, remains underexplored. To address this, five rotor designs with segmented PMs are analyzed against a baseline model using finite element analysis, maintaining identical stator and PM volume. Results show that segmentation increases reluctance torque, compensating for reduced PM torque, while simultaneously lowering eddy current loss and enhancing demagnetization resistance. These improvements validate segmented PMs as a viable strategy to enhance the durability and efficiency of FI-IPM motors for electric vehicle applications. Full article

Based on eddy covariance data collected during March to June 2021 in the Gurbantunggut Desert, this study analyzed desert methane (CH₄) flux dynamics. Results show the following: (1) The desert functions as a weak methane sink from March to June in the growing season, with its CH₄ flux showing a U-shaped diurnal variation pattern. The absorption peak occurred in June, reaching −79.1 mg·m⁻²·month⁻¹. (2) Diurnally, CH₄ flux correlated negatively with soil temperature (Tsoil), vapor pressure deficit, and photosynthetically active radiation (r_Tsoil = −0.58, r_VPD = −0.49, r_PAR = −0.49), positively with soil water content (SWC) and relative humidity (RH) (r_RH = 0.53, r_SWC = 0.28). (3) Fixed-effects regression isolated individual and interactive effects of SWC and Tsoil, yielding the model: CH₄ = −0.002 − 0.017SWC − 0.00004Tsoil − 0.002(SWC × Tsoil). The model highlights CH₄ flux sensitivity to hydrothermal factors and underscores the importance of their interaction for accurate flux estimation and understanding arid zone carbon cycle-climate feedbacks. Full article

The La Mancha region (a semi-arid area of southeast Spain) hosts the world’s highest concentration of vineyards and is also one of the regions with the largest areas devoted to almond tree cultivation. Viticulture and nut fruit trees (mainly almonds) are one of the region’s principal sources of economic revenue. The Two-Source Energy Balance (TSEB) model can assist management of water resources. A simplified version of the TSEB approach (STSEB) was previously tested in a vineyard and almonds to estimate sensible heat (H) and latent heat (LE) fluxes using a parallel scheme method based on the Monin–Obukov similarity theory (MOST). This study introduces a method based on Surface Renewal (SR) theory to partition the sensible heat flux using low-frequency measurements as input. The latter was friendlier than the parallel MOST method under unstable conditions and than the series SR and MOST methods. The objective was to compare the MOST and SR models within a parallel scheme method. During the 2014 and 2015 growing season, measurements were collected in a 4 ha row crop drip-irrigated Tempranillo vineyard. Hourly sensible heat flux measured by an eddy covariance (EC) system and evapotranspiration (ET) registered by a 9 m² monolithic large weighting lysimeter were used as a reference. ET estimates were obtained as a residual of the energy balance equation (known as the residual method) using three methods for estimating sensible heat flux, H_SR, H_MOST and H_EC, yielding ET_SR-RE, ET_MOST-RE and ET_EC-RE, respectively. For sensible heat flux, the index of agreement (IA expressed in %) for 2014 and 2015 was 93% and 83%, respectively, using SR, and 84% and 78%, respectively, for MOST. This represents a 6–10% improvement using SR. For evapotranspiration, the ET_SR-RE and ET_MOST-RE IA showed similar performance in both years (around 88%), while ET_EC-RE yielded the best results (92% and 89% for 2014 and 2015, respectively). In addition, half-hourly EC fluxes, during the growing season of 2017, were used as a reference in an almond orchard. The SR sensible heat flux performed better (IA = 93%) than MOST (IA = 86%) in this case, whereas for the latent heat flux, the residual method performed the best, resulting in an IA of 81% for SR and of 78% for MOST. Overall, SR performed better than MOST, particularly under unstable conditions with wind speeds above 1 ms⁻¹. Full article