Dual-source Model Research Articles

Design and preparation of Ta33W35Cr15V17 /Al2O3 nano multilayer film based on multi-level construction strategy and its radiation resistance behavior

The microstructure and mechanical properties of Ta33W35Cr15V17/Al2O3 nano-multilayer films with preset defects after He+ ion irradiation were studied to understand the effects of layer interfaces and nano-defects. After irradiation, the growth of He bubbles in the alumina layer was confined to the nanovoids without aggregations. The nanochannel in the high-entropy alloy layer absorbed the deposited energy of He+ and shrank to disappear. In addition, the film was softened after irradiation due to the presence of presetting defects. Based on which a dual absorption source model of interface and pre-set defects was proposed to explain the enhancement of radiation tolerance.

Estimating crop coefficients and water use of a full-bearing mango orchard in north-eastern South Africa using the fraction of vegetation cover and a dual source evapotranspiration model

In semi-arid countries like South Africa, commercially produced mango (Mangifera Indica L.) are grown entirely under irrigation. However, there is little accurate quantitative information on the water use of mango orchards, and few accurate water use models currently exist. In this study, we evaluated the performance of the FAO 56 method of estimating crop evapotranspiration (ETc) and a dual source water use model against measurements of actual consumptive water use of a commercial mango orchard. The FAO approach calculates ETc as the product of a crop coefficient (Kc) and the reference evapotranspiration (ETo). We derived Kc for well-watered orchards from readily available data including the fraction of vegetation cover, average tree height, and a stomatal control coefficient. The dual-source model calculated orchard evapotranspiration as the sum of tree transpiration and orchard floor evaporation derived from the modified Shuttleworth and Wallace model. Actual evapotranspiration was measured using an open path eddy covariance system, while tree transpiration was measured using the heat ratio method of monitoring sap flow. Data were collected in a mature ‘Tommy Atkins’ mango orchard grown with micro-sprinkler irrigation in north-eastern South Africa. Results show that the reference evapotranspiration explained most of the variation in orchard transpiration (R2 ∼ 0.78) compared to the solar radiation (R2 ∼ 0.66) and the vapour pressure deficit of the air (R2 ∼ 0.66). Compared with field measured water use data, the FAO method gave relatively accurate estimates of transpiration (R2 = 0.74, NRMSE = ±18.00 %, NMAE = ±15.00 %, NSE = 0.70) and evapotranspiration (R2 = 0.58, NRMSE = ±19.00 %, NMAE = ±16.00 %, NSE = 0.55). NSE is the Nash-Sutcliffe Efficiency. The dual-source model yielded slightly less accurate estimates of transpiration (R2 = 0.61, NRMSE = ±22.00 %, NMAE = ±20.00 %, NSE = 0.39) and evapotranspiration (R2 = 0.52, NRMSE = ±23.00 %, NMAE = ±25.00 %, NSE = 0.51). The basal crop coefficient (Kcb) showed small seasonal fluctuations, varying between 0.40 and 0.60 throughout the year. In contrast, Kc showed clear seasonality varying between 0.59–0.64 at flowering and fruit set and rising to 0.81–0.90 during the fruit growing phase. Estimates of the annual total transpiration (686 mm) from the FAO method were within 5 % of the actual measured values (677 mm) while the dual source model estimated 612 mm of transpiration, which was almost 10 % lower than the measured values. The results highlight that even though the FAO method requires fewer input parameters, it is potentially more accurate in estimating water use in mango orchards than the dual-source model.

Estimating and partitioning evapotranspiration in a film mulched cropland with shallow groundwater by the improved dual source model

Evapotranspiration (ET) is a key link in terrestrial water cycle and influenced by complex environmental factors in cropland. Accurate assessment of crop ET over heterogeneous underlying surfaces remains challenging. In this study, the dual source Shuttleworth-Wallace (SW) model was modified to estimate λET (latent heat corresponding to ET) through incorporating the effects of film mulching and shallow groundwater. λET and latent heat from transpiration (λT) were measured in a maize field in northwest China during 2017 and 2018 to assess the performance of the original (SW) and modified (SWM) models. Results indicate that the overestimation of latent heat from soil evaporation (λE) due to ignoring film mulching could be obviously mitigated by SWM. Besides, considering capillary rise from shallow groundwater in SWM improved not only λET estimates but also the accuracy of canopy resistance parameter. The SWM model outperformed the SW model that the slopes of fitting lines for λET and λT increased from 0.60 to 0.79 to 0.77–0.99 at daily scale and Nash-Sutcliffe Efficiency coefficient exceeded 0.86. Relative error and RMSE were decreased to below 0.15 and 19.88 W m−2, respectively. The estimations of λET and λT by SWM were also improved at hourly scale. Seasonal variation and partition of λET between two years were comparable and average T/ET for the entire growing season was about 78 %-84 %, which was largest at the heading stage. Path analysis on the responses of λET to the environmental factors recognized the greatest direct effect of crop height or leaf area index, and identified the significantly direct control of shallow groundwater on λT in this area. The study presented an improved dual source model to better quantify λET, which would benefit water resources management for film mulched croplands with shallow groundwater.

Intelligent monitoring of surface evapotranspiration in the Heihe River Basin based on SEBS modelling

[Objective] The Heihe River Basin, located in northwestern China, is the second largest inland basin in China, and its water resources play a crucial role in the ecology, agriculture and human life of the region. The aim of this study is to investigate the spatial and temporal variations of surface evapotranspiration in the Heihe River Basin and the potential impacts of these variations on water resource management. [Methods] To achieve this goal, we applied the PM-based dual-source model, a meteorological model for estimating global surface ET, which takes into account a variety of factors such as temperature, humidity, wind speed and downward solar shortwave radiation. By analysing the meteorological data and remote sensing data of the Black River Basin, we first investigated the spatial and temporal distribution of surface evapotranspiration. [Conclusion] The results show that surface evapotranspiration shows obvious seasonal and regional variations and is significantly affected by meteorological conditions. The inversion of surface ET in the Heihe River Basin by this dual-source model needs to be improved, and the trend of ET values calculated by the model is relatively small compared with the actual values.

Oilfield Reservoir Parameter Inversion Based on 2D Ground Deformation Measurements Acquired by a Time-Series MSBAS-InSAR Method

Time-series ground deformation monitoring and reservoir parameter inversion are crucial for the dynamic assessment of oilfield resources and sustainable exploitation in oilfields. As some of the regions with the richest oil reserves in China, the oilfield areas in the western Qaidam Basin were selected as a typical study area. Firstly, we used SAR images collected by the Sentinel-1A satellite from January 2021 to December 2022 and applied the multidimensional small baseline subset (MSBAS) method to obtain vertical and east–west deformation measurements. On this basis, a nonlinear Bayesian inversion method was applied to model the shallow reservoir in a series of complex deformation areas, based on a single-source model and a multi-source model, respectively. As a result, the ground deformation monitoring results obtained by long time-series InSAR clearly reflect the uneven ground deformation caused by the oil extraction and water injection operation processes. There was slight subsidence in the Huatugou oilfield, while significant uplift deformation occurred in the Ganchaigou oilfield and the Youshashan oilfield, with a maximum uplift rate of 48 mm/year. Further analysis indicated that the introduction of the 2D deformation field helps to improve the robustness of oilfield reservoir parameter inversion. Moreover, the dual-source model is more suitable than the single-source model for inverting reservoir parameters of complex deformation. This study not only fills the gap of InSAR deformation monitoring for the oilfields in the western Qaidam Basin but also provides a theoretical reference for the model and method selection of reservoir parameter inversion in other oilfields.

A two-stage capacity reservation contract model with backup sourcing considering supply side disruptions

ABSTRACT To deal with disruption at the supply side, the use of backup suppliers is among the commonly employed strategies. In this research, we derived a dual sourcing model using capacity reservation contracts for a supply chain consisting of a retailer, a primary supplier who may experience disruption, and a reliable backup supplier. This dual sourcing model is a reactive strategy that balances flexibility and redundancy to improve supply chain resilience. The aim of the proposed model is to help find optimal solutions for the reserved capacities of the retailer to the suppliers and the constructed capacities of the suppliers. It has been derived in this research that the above-mentioned reserved/constructed capacities exist uniquely. Sensitivity analyses were also conducted to examine the impact of contract parameters on decision variables. This research contributes to existing knowledge by providing deeper insights into the application of the capacity reservation contract to handle supply disruption.

FE-trans-net: Feature enhancement based single branch deep learning model for surface roughness detection

Real-time surface roughness measurement is crucial for modern manufacturing. Machine vision-based roughness measurement algorithms have the advantages of non-contact, high efficiency and adaptability. Light source is important for online machine vision-based roughness measurement. And different materials may need different light sources to extract more features. From the previous study, dual light sources are better than single light source for surface roughness prediction. However, it is inconvenient to assign two light sources for online detection equipment, and the two-branch model structure for dual light sources doubles the size of the model. To fully utilize the advantages of dual light sources, and avoid its disadvantages, a feature enhancement based single branch deep learning model FE-Trans-Net is proposed in this paper for surface roughness detection. Firstly, a dataset of different materials (Cu, Zn, Al, and Fe) shined with different light sources (white, red, green, red laser and green laser) is collected. Two most suitable light sources for different materials are chosen for dual light sources model as offline pre-training. In this model, lightweight cross-attention fusion (CAF-Trans) and graph convolutional channel attention (GCC-Atten) modules are designed to fuse the feature information of different light sources from the spatial and channel perspectives respectively, enabling the single-branch model to acquire the feature learning capability of different light sources. Then a single-branch network layer is remained as the online prediction. With the feature enhancement, it preserves the advantages of dual light source images, and has only half size of the dual light source model. Extensive experiments validate the effectiveness and generalization performance of the CAF-Trans and GCC-Atten modules, and the proposed FE-Trans-Net network achieves the best accuracy-efficiency tradeoff compared to other popular deep neural networks.

Dual sourcing models with stock-out dependent substitution

Companies use different criteria such as lead time, cost and quality to evaluate suppliers; often using multiple suppliers with the aim of reducing stockout risk. But in many industries there may be significant differences between the quality levels of different suppliers. Thus quality-sensitive companies may prefer an item from a primary supplier, but be forced to accept substitute products of lesser quality in case of a stock-out. Motivated by an example in the aviation industry, we introduce a Dual Sourcing problem With Stock-out dependent substitution (DSWS) which includes quality differences. Due to nonconvexity of the multi-period model, analytical characterization of the optimal policy appears intractable. To overcome this problem, we prove a relation between the optimal cost of DSWS and costs of three other problems - dual sourcing without substitution and single sourcing problems with and without backlogging. This leads us to propose the use of the dual index policy (and a variant) as heuristics for DSWS, and to develop an algorithm for parameter optimization of our heuristics. Extensive numerical experiments show that the dual index policy outperforms all other candidate solutions from the literature by at least 8%. Our experiments show that the utilization of the back-up supplier leads to substantial cost savings and service rate increase, especially in case of high differences between holding cost rates of different quality items.

Geodetic imaging of ground deformation and reservoir parameters at the Yangbajing Geothermal Field, Tibet, China

SUMMARYMonitoring and modeling ground surface deformation are crucial for the dynamic assessment of geothermal resources and sustainable exploitation in a geothermal field. In this study, we extract the deformation in the Yangbajing geothermal field by the small baseline-synthetic aperture radar interferometry (SBAS-InSAR) method using 141 Sentinel-1A images collected between March 2017 and November 2021. The InSAR result indicates both uplift and subsidence in the geothermal field. Subsequently, we use a dual-source model combining a dipping ellipsoid and a rectangular surface to model the shallow reservoir that contracted to cause the complex subsidence field in the north of the geothermal field. The shallow reservoir that expanded to cause the uplift in the south is modeled by an ellipsoid source. The parameters inversion is processed by the nonlinear Bayesian inversion method which has been applied to search the optimal parameters setting in a priori space and evaluate the uncertainties by the confidence intervals. To validate our inversion results, we collect the data from 31 wells including extraction and injection wells, detailed tectonic survey data and geothermal isotherms of the Yangbajing geothermal field. The modeled shallow reservoir in the north is within a 140 °C ground isotherm and a 160 °C underground isotherm. The thickness and depth of the reservoir slightly exceed the data from producing wells, probably due to the structural subsidence of the reservoir. The geometric structure is consistent with the channel faults that control the formation and development of the shallow reservoirs. The modeled reservoir under the rebound area in the south is also validated by comparing the data. Furthermore, we estimate the volume loss and recovery of the contracting and expanding reservoirs. We analyse the deformation mechanisms by considering the tectonic formation, the reservoir structure, and the extraction and rechargeability of the reservoirs. This research suggests the deformation pattern of shallow porous reservoirs that have similar layer composition and tectonic structure elsewhere in the world. Moreover, it provides a theoretical model to explore the parameters and volume change of geothermal reservoirs in plateau-embedded basins around the world. Our work is significant for the conservation and development of geothermal energy in geothermal fields that experience deformation, both subsidence and uplift.

A unified theoretical model for spatiotemporal development of Rayleigh–Taylor and Richtmyer–Meshkov fingers

An initially perturbed interface between two fluids of different densities is usually unstable when driven by an acceleration or a shock wave; it is known as a Rayleigh–Taylor instability or a Richtmyer–Meshkov instability. One of the most significant issues in these instabilities is the spatiotemporal development of fingers generated at the interface, which plays an important role in both scientific research (e.g. supernova explosion) and engineering applications (e.g. inertial confinement fusion). Accurate theoretical solution of these interfacial fingers remains as an unsolved and challenging problem since Taylor's seminal work more than seven decades ago. This paper reports a unified theory established for such phenomena by combining the classical potential-flow theory and a dual-source model to address the long-standing difficulty highlighted by the initial-value sensitivity and strong nonlinearity. It is the first time for a theory to accurately predict the long-time developments in both growth rate and shape curvature of interfacial fingers at all density ratios in two and three dimensions. Moreover, the new theory clearly reveals the nonlinear coupling mechanism for interfacial evolution, and especially explains the origin of overshot in the growth rate curve.

The efficient and stable planning for interrupted supply chain with dual‐sourcing strategy: a robust optimization approach considering decision maker's risk attitude

• Proposing an efficient and robust dual-sourcing model for disrupted supply chain • Considering various risk attitudes and interruption uncertain situations • Processing supply interruption uncertainty with robust optimization method • Applying the real case study to analyze validity and stability of model • Providing useful managerial implications for interrupted supply chain sourcing In the face of the complex market environment and the in-depth development of globalization, ensuring the supply chain's stability and cost leadership by developing a differentiated dual-source procurement strategy is extremely important. The present study contemplates the supply chain as the research object. It also considers disruption uncertainty and decision-makers’ risk attitudes. To minimize costs and shortages, we build a dual-objective robust optimization model for a dual-sourcing strategy under interruption risk. The authors aim to explore efficient and robust planning under supply disruption uncertainty in dual-sourcing strategies by different risk attitudes. The research employs the augmented ε-constraint method to solve the proposed model by transforming the model into a single-objective mixed-integer programming model. Additionally, our study uses enterprise examples to prove the feasibility and effectiveness of the model. Moreover, it conducts risk attitude analysis, dual objective function trade-off analysis, and superiority analysis of procurement strategies. Finally, we put forward some management insights to provide a new decision-making idea for real supply chain enterprises in the case of supply interruption risk.

A new dual earthquake and submarine landslide source model for the 28 September 2018 Palu (Sulawesi), Indonesia tsunami

ABSTRACT The September 2018 Palu (Sulawesi, Indonesia) tsunami has been a heavily debated event because multiple source models of three different types have been proposed for this tsunami: (i) The Mw 7.5 earthquake, (ii) landslides, and (iii) dual earthquake and landslide. Surprisingly, all of these three types of models were reported as being successful in the literature in terms of reproducing the existing tsunami observations. This can be partly attributed to the limited observations available for this tsunami. This study is motivated by the results of a marine bathymetric survey, which identified evidence for submarine landslides within the Palu Bay. Our modeling shows that the tsunami cannot be exclusively attributed to the Mw 7.5 earthquake. Inspired by the results of the marine survey, we propose a dual source model including a submarine landslide although most of the existing models include subaerial coastal landslides. Our dual model comprises an earthquake model, which has a length of 264 km, a width of 37 km, and a slip of 0–8.5 m, combined with a submarine landslide with a length of 1.0 km, a width of 2.0 km, and a thickness of 80.0 m located at 119.823°E and −0.792°S.

Remote sensing-based evapotranspiration determination: A review of single-source energy balance models

Remote Sensing evapotranspiration models are critical in order to understand the cycling of water in the environment. Initially, an outline of the concepts related to evapotranspiration, as well as the shortcomings of land-based methods, is presented. The aim of the study was based on reviewing remote sensing evapotranspiration models which provide an alternative data source. These models have proved to be a cheaper alternative to mapping and estimating spatiotemporal evapotranspiration measurements across local and regional scales. This paper reviews the single-source energy balance model, which differs from the two-source model, for estimating spatiotemporal measurements of evapotranspiration. The single-source energy balance model is underpinned by mathematical equations which differentiate the various single-source evapotranspiration models (Surface Energy Balance Systems, Simplified Surface Energy Systems, Surface Energy Balance Algorithm, and Mapping Evapotranspiration at high Resolution and with Internalised Calibration). The soil surface and forest canopy components were observed to be the major difference between the single and dual-source models. Further advice was discussed on the implementation of the OpenET tool, which provides an open and accessible satellite-based estimation of evapotranspiration for improved water management.

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real-time adaptive workflow.

PurposeThis study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real‐time adaptive photon radiotherapy. With this objective in view, the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability.Materials and methodsA dual‐source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6‐MV flattened and 6‐MV flattening filter‐free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity‐modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution‐superposition dose calculation within RayStation.ResultsFor simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients.ConclusionsThe phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real‐time adaptive setting.

Volume flexibility at responsive suppliers in reshoring decisions: Analysis of a dual sourcing inventory model

AbstractWe investigate how volume flexibility, defined by a sourcing cost premium beyond a base capacity, at a local responsive supplier impacts the decision to reshore supply. The buyer also has access to a remote supplier that is cheaper with no restrictions on volume flexibility. We show that with unit lead time difference between both suppliers, the optimal dual sourcing policy is a modified dual base‐stock policy with three base‐stock levels , , and . The replenishment orders are generated by first placing a base order from the fast supplier of at most units to raise the inventory position to , if that is possible. After this base order, if the adjusted inventory position is still below , additional units are ordered from the fast supplier at an overtime premium to reach . Finally, if the adjusted inventory position is below , an order from the slow supplier is placed to bring the final inventory position to . Surprisingly, in contrast to single sourcing with limited volume flexibility, a more complex dual sourcing model often results in a “simpler” policy that replaces demand in each period. The latter allows analytical insights into the sourcing split between the responsive and the remote supplier. Our analysis shows how increased volume flexibility at the responsive supplier promotes the decision to reshore operations and effectively serves as a cost benefit. It also shows how investing in base capacity or additional volume flexibility act as strategic substitutes.

Analysis of Multispectral Drought Indices in Central Tunisia

Surface water stress remote sensing indices can be very helpful to monitor the impact of drought on agro-ecosystems, and serve as early warning indicators to avoid further damages to the crop productivity. In this study, we compare indices from three different spectral domains: the plant water use derived from evapotranspiration retrieved using data from the thermal infrared domain, the root zone soil moisture at low resolution derived from the microwave domain using the Soil Water Index (SWI), and the active vegetation fraction cover deduced from the Normalized Difference Vegetation Index (NDVI) time series. The thermal stress index is computed from a dual-source model Soil Plant Atmosphere and Remote Evapotranspiration (SPARSE) that relies on meteorological variables and remote sensing data. In order to extend in time the available meteorological series, we compare the use of a statistical downscaling method applied to reanalysis data with the use of the unprocessed reanalysis data. Our study shows that thermal indices show comparable performance overall compared to the SWI at better resolution. However, thermal indices are more sensitive for a drought period and tend to react quickly to water stress.

Assessment of an extended SPARSE model for estimating evapotranspiration from directional thermal infrared data

The spatial distribution of evapotranspiration is often obtained from dual source energy balance models forced by surface temperature data. The use of multi-angular remotely-sensed thermal data in such methods makes them susceptible to directional-anisotropy/thermal-radiation directionality effects that may result from the satellite's position, relative to the Sun, at overpass time. It is therefore important to have these effects accounted for to ensure realistic flux retrievals irrespective of sensor viewing position. At present, dual source models generally interpret surface temperature according to two sources, representing the soil surface and the vegetation. This may be insufficient to adequately represent the limiting temperature conditions that not only depend on the source type but also on their exposure to the Sun. Here, we present a modified version of the SPARSE (Soil Plant Atmosphere Remote Sensing Evapotranspiration) model, wherein the original SPARSE is modified to incorporate sunlit/shaded soil/vegetation elements and coupled with a radiative transfer model that links these four component emissions to out-of-canopy directional radiances as observed by remote sensors. An initial evaluation is carried out to check the model's capability in retrieving surface fluxes over diverse environments instrumented with in-situ thermo-radiometers. When run with nadir-acquired thermal data, both algorithms show no observable difference in their retrieval of total fluxes. We nonetheless show that by incorporating the solar direction and discriminating between sunlit and shaded elements, the partitioning of these overall fluxes between the soil and vegetation can be improved especially in water-stressed environments. We also test the sensitivity of flux and component temperature estimates to the viewing direction of the thermal sensor by using two sets of TIR data (nadir and oblique) acquired simultaneously to force the models and show that sensitivity to viewing direction is significantly reduced. This is an important aspect particularly when using high resolution spatial and temporal data from Earth observation missions that inherently have to consider a wide-range of viewing angles in their design.

Isolating two sources of variability of subcortical stimulation to quantify fluctuations of corticospinal tract excitability

ObjectiveInvestigate the variability previously found with cortical stimulation and handheld transcranial magnetic stimulation (TMS) coils, criticized for its high potential of coil position fluctuations, bypassing the cortex using deep brain electrical stimulation (DBS) of the corticospinal tract with fixed electrodes where both latent variations of the coil position of TMS are eliminated and cortical excitation fluctuations should be absent. MethodsTen input–output curves were recorded from five anesthetized cats with implanted DBS electrodes targeting the corticospinal tract. Goodness of fit of regressions with a conventional single variability source as well as a dual variability source model was quantified using a Schwarz Bayesian Information approach to avoid overfitting. ResultsMotor evoked potentials (MEPs) through DBS of the corticospinal tract revealed short-term fluctuations in excitability of the targeted neuron pathway reflecting endogenous input-side variability at similar magnitude as TMS despite bypassing cortical networks. ConclusionInput-side variability, i.e., variability resulting in changing MEP amplitudes as if the stimulation strength was modulated, also emerges in electrical stimulation at a similar degree and is not primarily a result of varying stimulation, such as minor coil movements in TMS. More importantly, this variability component is present, although the cortex is bypassed. Thus, it may be of spinal origin, which can include cortical input from spinal projections. Further, the nonlinearity of the compound variability entails complex heteroscedastic non-Gaussian distributions and typically does not allow simple linear averages in statistical analysis of MEPs. As the average is dominated by outliers, it risks bias. With appropriate regression, the net effects of excitatory and inhibitory inputs to the targeted neuron pathways become noninvasively observable and quantifiable. SignificanceThe neural responses evoked by artificial stimulation in the cerebral cortex are variable. For example, MEPs in response to repeated presentations of the same stimulus can vary from no response to saturation across trials. Several sources of such variability have been suggested, and most of them may be technical in nature, but localization is missing.

Estimation of Evapotranspiration and its Components of Greenhouse Grapevines Under Drip Irrigation in the Cold Region of Northeast China Using Dual-Source Models

Estimation of Evapotranspiration and its Components of Greenhouse Grapevines Under Drip Irrigation in the Cold Region of Northeast China Using Dual-Source Models

Estimation of evapotranspiration of “soil-vegetation” system with a scheme combining a dual-source model and satellite data assimilation

Evapotranspiration (ET) is a key variable linking the energy and water exchanges between the land surface and the atmosphere. The strong energy exchanges between the soil and vegetation in the “soil-vegetation” system and the lack of reliable soil moisture products at fine spatial scales, especially for root zone soil moisture, to directly model the effects of water stress on ET estimates, make it difficult to estimate actual ET and its components (soil evaporation Es, vegetation transpiration Tc and rainfall interception Ei). In this paper, we presented a “Soil-Vegetation” EvapoTranspiration framework (SVET) by combining the dual-source Shuttleworth and Wallace (SW) physical model and satellite soil moisture data assimilation procedure. In the SVET model, net radiation for the soil-vegetation system was first partitioned among soil evaporation, vegetation transpiration and rainfall interception; then, soil moisture was simulated for different soil layers based on the water balance, providing a first guess estimate of soil moisture; after that, simulated soil moisture was improved by assimilating remotely sensed surface soil moisture to reduce the uncertainty of the simulated soil moisture; finally, Es, Tc and Ei estimates were obtained. The ET estimates by the SVET were evaluated against in situ measurements at three stations in the Heihe River Basin with different vegetation cover types (crop, grassland and forest). The overall correlation coefficient (R), root mean square error (RMSE) and bias were 0.931, 0.67 mm d−1 and 0. 07 mm d−1, respectively. For the ET components, the bias of the estimated ratio of Tc/(Es + Tc) is −11.4%. In addition, the SVET model showed outstanding performance, especially over irrigated areas, compared with the results from the original SW model without a soil moisture data assimilation scheme. The SVET model is very promising for applications of water use monitoring of ecosystem, especially for irrigated areas.