Maximum Entropy Production Model Research Articles

Changed evapotranspiration and its components induced by greening vegetation in the Three Rivers Source of the Tibetan Plateau

The Three Rivers Source (TRS), that is, the source of the Yangtze (SYZ), Yellow (SYE), and Lancang (SLC) Rivers in the Tibetan Plateau, is the water tower of Asia. Harsh climates, complex topography, and limited ground-based observations hinder our understanding of hydrological processes in this region, especially in a changing climate. Over the past two decades, the vegetation in the TRS has undergone significant greening as a result of the implementation of ecological restoration projections, which in turn has changed the hydrological process in this region. However, the impact of vegetation greening on evapotranspiration (ET) and its components is still unclear. Here, we investigate the response of ET and its components to vegetation changes in the TRS based on the maximum entropy production (MEP) model and detrending attribution analysis. The results show that the MEP model can well capture changes in ET at both the site and watershed scales. The multi-year-average ET of the TRS is 411.7 mm/a, of which the relative contributions of soil evaporation (Es), vegetation transpiration (Et), and canopy interception evaporation (Ei) are 68.21 %, 23.57 %, and 8.21 %, respectively. The annual ET has increased significantly, with a trend of 0.23 mm/a2 (p < 0.05). The contributions of vegetation greening to ET and its three components (Es, Et, and Ei) are 1.95 mm/a, −2.41 mm/a, 1.33 mm/a, and 3.03 mm/a, respectively. The findings are expected to provide guidance for the management of water resources and the implementation of ecological restoration in the TRS.

The spatiotemporal variation of land surface heat fluxes in Tibetan Plateau during 2001–2022

The surface energy budget is important for understanding of energy and water cycle processes in the Tibetan Plateau (TP). In this study, the daily sensible (SH) and latent (LE) heat fluxes at the horizontal resolution of 1° are first estimated using the maximum entropy production (MEP) model (hereinafter SHMEP and LEMEP) in the entire TP during 2001–2022. The MEP model is built on physical and statistical principles to simulate surface heat fluxes. The surface net radiation, soil moisture (SM), and land surface temperature (LST) are the main driving variables for MEP model. To select the relatively accurate MEP input data, the merged surface net radiation (Rn–merged) under all-sky conditions are generated from CERES, ISCCP-FH, and ERA5 using the Bayesian Model Averaging scheme. Besides, the TP SM and LST from various data sources are evaluated using the in-situ observations at site scale. Based on the daily Rn–merged, ERA5 SM, CERES LST, and the MEP model, the daily SH and LE are estimated in the entire TP. The results show the daily SHMEP and LEMEP perform well at the validation sites, with the regional mean correlation coefficient (R) above 0.7, root-mean-square error (RMSE) of <19 W m−2, absolute value of bias and mean absolute error (MAE) below 11 W m−2. The monthly SHMEP has the regional mean R of 0.96 and RMSE of 6.30 W m−2 at all the measurement stations. For LEMEP, the regional mean R and RMSE values are 0.93 and 10.01 W m−2, respectively. The MEP simulation results are superior to the SH and LE in ERA5, ERA-Interim, MERRA-2, and JRA-55 reanalysis datasets and previous studies, especially for LE. Based on this new dataset, the spatial and temporal varying characteristics of SH and LE in the TP are analyzed. The annual mean SHMEP value are large in the western TP, the Qaidam Basin in the northern TP, and the Himalaya ranges, and small in the southeastern TP. The annual mean LEMEP has the maximum value in southeastern TP, and minimum value in western TP and the Qaidam Basin. The annual mean SHMEP and LEMEP over the entire TP are 34.79 W m−2 and 20.16 W m−2, with the significant declining trends of −0.17 W m−2 year−1 and − 0.052 W m−2 year−1 during the study period, respectively. The spatial distributions of the MEP surface heat fluxes and their trends are mainly influenced by the model inputs of Rn and SM in the TP.

An Application of the Maximum Entropy Production Method in the WRF Noah Land Surface Model

AbstractThe calculation of surface sensible heat (SH) and latent heat (LE) fluxes using the bulk transfer models for complex terrains, tall vegetation regions, and morning and evening transition periods remains a challenging problem in numerical weather and climate models. The maximum entropy production (MEP) model, a new method of calculating surface heat fluxes, is coupled with the Noah land surface model (LSM) in the Weather Research and Forecasting (WRF) model. Surface heat fluxes and meteorological variables including air temperature, relative humidity, soil temperature, and precipitation data at nine intensive observation stations and 453 routine meteorological operational observation stations in the Tibetan Plateau (TP) from 1 June to 31 August 2015 are used to evaluate the coupled model. The results show that the MEP method improves the nonclosure of the surface energy balance in the WRF (with an energy residual from 24.3 to 1.9 W m−2), reducing the overestimations of SH and LE and the underestimation of the surface ground heat flux over the complex terrain of TP (with the bias decreases of 50.6% and 117.1% for SH and LE in turn), especially during the daytime. The improved SH and LE reduce the cold and wet biases in the TP by 29.4% and 51.7%, respectively. The MEP model also reduces the overestimated soil temperature by 63%. Moreover, the overestimated daily precipitation is reduced by 3% over the TP. The successful application of the MEP method demonstrates its advantage over the bulk transfer method, providing a new approach for reducing the overestimation of surface heat fluxes and wet and cold biases in numerical forecast models in complex terrains.

An R package of maximum entropy production model to estimate 41 years of global evapotranspiration

An accurate estimation of evapotranspiration (ET) is vital for understanding the global hydrological cycle. However, large uncertainties in the present global ET products originate from the distinct model structures, assumptions, and inputs. The maximum entropy production (MEP) model provides a novel method for modeling ET based on parsimonious inputs and energy conservation. In this study, an R package for MEP (RMEP) was presented to facilitate MEP model implementation. Based on RMEP, a global ET analysis was conducted using inputs from the Global Land Data Assimilation System (GLDAS) and Global Land Surface Satellite (GLASS) products during 1978–2018, and the Mann-Kendall and Theil–Sen’s methods were employed to detect the ET trends. The MEP-estimated average annual global land ET was 517 mm yr−1 during 1978–2018, and showed a close agreement with eddy-covariance (EC) measurements from 475 flux sites, with a correlation coefficient of 0.74 and root-mean-square error of 26.99 mm mon−1. The overall performance of MEP was evaluated across various land covers, and a higher ET accuracy was revealed for forestlands, wetlands, and cropland land covers. The MEP-derived ET trend corresponded well with the EC-observed ET trend, and the results indicated that the global land ET declined continuously during 1999–2018. Overall, the MEP model provided an accurate ET estimate with parsimonious inputs, which outperformed the GLDAS-Noah ET product and can serve as a global analytical method for the hydrological cycle and climate change.

Quantifying the effect of vegetation greening on evapotranspiration and its components on the Loess Plateau

As one of the largest revegetation projects in China, the Grain for Green Project has dramatically increased vegetation greenness (greening) on the Loess Plateau. Large-scale greening inevitably changed the spatiotemporal pattern of water availability on the Loess Plateau by increasing evapotranspiration (ET). Quantifying the effect of greening on ET is critical for regional water resources management and planning. This study uses the maximum entropy production (MEP) model and two attribution methods (the detrending and extending methods) to quantify the effect of greening on ET and its components (soil evaporation (Es) and transpiration (Et)) on the Loess Plateau from 2001 to 2018. The ensemble-averaged results of two attribution methods are used to reduce the potential uncertainty caused by the choice of attribution methods. The MEP model performs well in capturing the spatiotemporal variability of ET on both the site and basin scales. Greening significantly (p < 0.05) increases Et and decreases Es for the Loess Plateau, and the magnitude of increase in Et exceeds the magnitude of decrease in Es, leading to a nonsignificant (p > 0.05) increase in ET. The contribution of greening to mean annual Es, Et, and ET for the Loess Plateau is −16.6, 20.7, and 4.1 mm/yr, respectively. An increase in ET may further exacerbate water scarcity for the Loess Plateau.

Assessment of long-term water stress for ecosystems across China using the maximum entropy production theory-based evapotranspiration product

Water demand growth coupled with its high spatial-temporal mismatch of water resources will lead to an increasing water scarcity worldwide. In order to investigate a robust long-term water stress for ecosystems and regions across China, the improved maximum entropy production (MEP) method was utilized to obtain a reliable evapotranspiration (ET) product during 1982–2015. Afterwards four water stress indices were constructed based on the MEP, Penman, Priestley-Taylor and complementary relationship model. The MEP estimated ET showed a close agreement with measurements at eddy covariance sites, with R2 = 0.89 and RMSE ranged from 5 to 12 mm/month. All ecosystems were indicated to suffer from a high risk of water stress, and were ranked by desert (0.67–0.93), grassland (0.60–0.78), settlement (0.49–0.63), farmland (0.48–0.63), and forest ecosystem (0.45–0.58) with four indices. Patterns of water stress at the provincial levels were revealed. Provinces including Xinjiang, Qinghai, Inner Mongolia, and Gansu in the northern regions displayed the highest water stress, and months from December to February were most vulnerable to extreme water stress. Overall, results revealed that the MEP model-based water stress index can well characterize the water stress footprints for all ecosystems and regions in China. This study can support the policy-making for improving water use efficiency and optimizing water resource management to alleviate water stress on large scales.

A Non‐Gradient Model of Turbulent Gas Fluxes Over Land Surfaces

AbstractA non‐gradient model is formulated for estimating gas fluxes using single‐level time‐series data of near‐surface gas concentration over land surfaces. When the vertical turbulent transport process in the atmospheric surface layer is described by a one‐dimensional diffusion equation, a gas flux is expressed as a weighted integral of the time‐history of single‐level gas concentration. The eddy‐diffusivity may be parameterized as a function of sensible heat flux based on the Monin‐Obukhov similarity theory without explicit dependence on wind speed and surface roughness. Sensible heat flux may be estimated from net radiation and surface temperature using the maximum entropy production model. Case studies at six sites with diverse vegetation covers, geographic and climatic conditions at sub‐daily and seasonal scales demonstrate the model's capability of simulating water vapor and CO2fluxes using fewer inputs than other models. The proposed method provides an alternative modeling tool for the study of water and carbon cycles over vegetated land surfaces.

Sensitivity Analysis of the Maximum Entropy Production Method to Model Evaporation in Boreal and Temperate Forests

AbstractThe maximum entropy production (MEP) approach has been little used to simulate evaporation in forests and its sensitivity to input variables has yet to be systematically evaluated. This study addresses these shortcomings. First, we show that the MEP model performed well in simulating evaporation during snow‐free periods at six sites in temperate and boreal forests (0.68 ≤ NSE ≤ 0.82). Second, we computed a sensitivity coefficient S representing the proportion of change in the input variable transferred to the latent heat flux (λE). Net radiation (Rn) was the most influential variable (S ≈ 1) at all sites, indicating that an increase in Rn translates into an equivalent increase in λE. The MEP model avoided the issue of oversensitivity to air temperature (S &lt; 0.5 at peak evaporation) and captured limitations to transpiration associated with the atmospheric evaporative demand. Overall, the MEP model offers a promising tool for climate change studies.

Analysis of Water Vapor Fluxes Over a Seasonal Snowpack Using the Maximum Entropy Production Model

AbstractSnow cover plays a key role in the water and energy budgets over cold regions. Understanding and parameterizing water and heat exchange over snow surfaces in hydrologic models remains a major challenge. An innovative approach based on the theory of maximum entropy production (MEP) was developed for modeling energy budgets for snow‐covered surfaces. This study generalizes the MEP model to simulate surface water vapor (latent heat) fluxes over an entire snowpack lifecycle, including snow accumulation and melting during the early growing season. The expanded MEP model combines soil evaporation, canopy transpiration, and snow sublimation to evaluate snow water loss during the lifecycle of the snowpack. Two hypotheses are tested: (1) sublimation becomes negligible during snowmelt when snowpack is isothermal (0°C) and (2) transpiration is progressively activated as a function of the air temperature during vegetation awakening. The proposed approach is shown to be effective for modeling the total surface water vapor fluxes over the snowpack's lifecycle. Both the hypotheses are supported by field observations.

The Long-Term Change of Latent Heat Flux over the Western Tibetan Plateau

The Tibetan Plateau (TP) has been experiencing warming and wetting since the 1980s. Under such circumstances, we estimated the summer latent heat flux (LE) using the maximum entropy production model driven by the net radiation, surface temperature, and soil moisture of three reanalysis datasets (ERA5, JRA-55, and MERRA-2) at the Ali site over the western TP during 1980–2018. Compared with the observed LE of the Third Tibetan Plateau Atmospheric Scientific Experiment, the coefficient of determination, root-mean-square error, and mean bias error of the estimated summer LE are 0.57, 9.3 W m−2, and −2.25 W m−2 during 2014–2016, respectively, which are better than those of LE of the reanalysis datasets. The estimated long-term summer LE presents a decreasing (an increasing) trend of −7.4 (1.8) W m−2 decade−1 during 1980–1991 (1992–2018). The LE variation is closely associated with the local soil moisture influenced by precipitation, glacier, and near-surface water conditions at the Ali site. The summer soil moisture also presents a decreasing (an increasing) trend of −0.082 (0.022) decade−1 during 1980–1991 (1992–2018). The normalized difference vegetation index generally shows the consistent trend with LE at the Ali site.

Using the maximum entropy production approach to integrate energy budget modelling in a hydrological model

Abstract. Total terrestrial evaporation, also referred to as evapotranspiration, is a key process for understanding the hydrological impacts of climate change given that warmer surface temperatures translate into an increase in the atmospheric evaporative demand. To simulate this flux, many hydrological models rely on the concept of potential evaporation (PET), although large differences have been observed in the response of PET models to climate change. The maximum entropy production (MEP) model of land surface fluxes offers an alternative approach for simulating terrestrial evaporation in a simple way while fulfilling the physical constraint of energy budget closure and providing a distinct estimation of evaporation and transpiration. The objective of this work is to use the MEP model to integrate energy budget modelling within a hydrological model. We coupled the MEP model with HydroGeoSphere (HGS), an integrated surface and subsurface hydrologic model. As a proof of concept, we performed one-dimensional soil column simulations at three sites of the AmeriFlux network. The coupled model (HGS-MEP) produced realistic simulations of soil water content (root-mean-square error – RMSE – between 0.03 and 0.05 m3 m−3; NSE – Nash–Sutcliffe efficiency – between 0.30 and 0.92) and terrestrial evaporation (RMSE between 0.31 and 0.71 mm d−1; NSE between 0.65 and 0.88) under semi-arid, Mediterranean and temperate climates. At the daily timescale, HGS-MEP outperformed the stand-alone HGS model where total terrestrial evaporation is derived from potential evaporation, which we computed using the Penman–Monteith equation, although both models had comparable performance at the half-hourly timescale. This research demonstrated the potential of the MEP model to improve the simulation of total terrestrial evaporation in hydrological models, including for hydrological projections under climate change.

Surface Energy Budgets of Arctic Tundra During Growing Season

AbstractThis study analyzed summer observations of diurnal and seasonal surface energy budgets across several monitoring sites within the Arctic tundra underlain by permafrost. In these areas, latent and sensible heat fluxes have comparable magnitudes, and ground heat flux enters the subsurface during short summer intervals of the growing period, leading to seasonal thaw. The maximum entropy production (MEP) model was tested as an input and parameter parsimonious model of surface heat fluxes for the simulation of energy budgets of these permafrost‐underlain environments. Using net radiation, surface temperature, and a single parameter characterizing the thermal inertia of the heat exchanging surface, the MEP model estimates latent, sensible, and ground heat fluxes that agree closely with observations at five sites for which detailed flux data are available. The MEP potential evapotranspiration model reproduces estimates of the Penman‐Monteith potential evapotranspiration model that requires at least five input meteorological variables (net radiation, ground heat flux, air temperature, air humidity, and wind speed) and empirical parameters of surface resistance. The potential and challenges of MEP model application in sparsely monitored areas of the Arctic are discussed, highlighting the need for accurate measurements and constraints of ground heat flux.

Estimation of Surface Heat Fluxes Over the Central Tibetan Plateau using the Maximum Entropy Production Model

AbstractSurface heat fluxes over the central Tibetan Plateau have been estimated using the maximum entropy production (MEP) model with the surface energy balance and the observation data from the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX‐III). The MEP surface heat fluxes are highly correlated with those of the TIPEX‐III observations. The agreement between the MEP and TIPEX‐III heat fluxes is higher when the observed surface energy balance closure is better. The errors of the MEP heat fluxes are smaller compared to those of the fluxes derived from the bulk transfer method, the Land Data Assimilation Systems, and the Simple Biosphere Model version 2 reported in the previous studies. The values of MEP sensible and latent heat fluxes tend to be less than those of the previous bulk heat fluxes. Thus, the MEP model can reasonably estimate surface heat fluxes over the central Tibetan Plateau.

Comparing the Performance of the Maximum Entropy Production Model With a Land Surface Scheme in Simulating Surface Energy Fluxes

AbstractHydrological projections under future climate change have been shown to be sensitive to the formulation of evapotranspiration. Many hydrological models still rely on empirical formulations of this flux, and hence do not take into account the surface energy budget. On the other hand, land surface schemes, which are used within the climate models to describe land hydrology and associated surface heat fluxes (SHF), rely on the energy conservation. Due to land surface schemes complexity, they are not suitable for integration in traditional hydrological models. A newly developed and relatively simple Maximum Entropy Production model, which operates under the constraint of energy conservation and allows for an appropriate partitioning of available energy into SHF, appears to be a good alternative for integration in hydrological models. However, the MEP's performances still need to be evaluated under various environmental conditions. This study aims to evaluate the SHF simulated by MEP using observations over a multiyear period from several carefully chosen snow‐free sites located in low‐latitude regions. Moreover, simulated fluxes were compared to those derived from the Canadian Land Surface Scheme (CLASS), which was run at the same sites. The analysis of simulated and observed fluxes associated with different water stress conditions suggests that the abilities of MEP and CLASS in estimating sensible and latent heat fluxes are comparable. It was also found that the MEP and CLASS fluxes are in a good agreement with observations. However, the simulated nocturnal fluxes show that both models are in less agreement with the observations.

Using Maximum Entropy Production to Describe Microbial Biogeochemistry Over Time and Space in a Meromictic Pond

Determining how microbial communities organize and function at the ecosystem level is essential to understanding and predicting how they will respond to environmental change. Mathematical models can be used to describe these communities, but properly representing all the biological interactions in extremely diverse natural microbial ecosystems in a mathematical model is challenging. We examine a complementary approach based on the maximum entropy production (MEP) principle, which proposes that systems with many degrees of freedom will likely organize to maximize the rate of free energy dissipation. In this study, we develop an MEP model to describe biogeochemistry observed in Siders Pond, a phosphate limited meromictic system located in Falmouth, MA that exhibits steep chemical gradients due to density-driven stratification that supports anaerobic photosynthesis as well as microbial communities that catalyze redox cycles involving O, N, S, Fe and Mn. The MEP model uses a metabolic network to represent microbial redox reactions, where biomass allocation and reaction rates are determined by solving an optimization problem that maximizes entropy production over time, and a 1D vertical profile constrained by an advection-dispersion-reaction model. We introduce a new approach for modeling phototrophy and explicitly represent oxygenic photoautotrophs, photoheterotrophs and anoxygenic photoautotrophs. The metabolic network also includes reactions for aerobic organoheterotrophic bacteria, sulfate reducing bacteria, sulfide oxidizing bacteria and aerobic and anaerobic grazers. Model results were compared to observations of biogeochemical constituents collected over a 24 hour period at 8 depths at a single 15 m deep station in Siders Pond. Maximizing entropy production over long (3 day) intervals produced results more similar to field observations than short (0.25 day) interval optimizations, which support the importance of temporal strategies for maximizing entropy production over time. Furthermore, we found that entropy production must be maximized locally instead of globally where energy potentials are degraded quickly by abiotic processes, such as light absorption by water. This combination of field observations and modeling results indicate that natural microbial systems can be modeled by using the maximum entropy production principle applied over time and space using many fewer parameters than conventional models.

Application of the Maximum Entropy Production Model of Evapotranspiration over Partially Vegetated Water-Limited Land Surfaces

Abstract The maximum entropy production (MEP) model based on nonequilibrium thermodynamics and the theory of Bayesian probabilities was recently developed to model land surface fluxes, including soil evaporation and vegetation transpiration. This model requires few input data and ensures the closure of the surface energy balance. This study aims to test the capability of such a model to realistically simulate evapotranspiration (ET) over a wide range of climates and vegetation covers. A weighting coefficient is introduced to calculate total ET from soil evaporation and vegetation transpiration over partially vegetated land surfaces, resulting in the MEP-ET model. Using this coefficient, the model outputs are compared with in situ observations of ET at eight FLUXNET sites across the continental United States. Results confirm the close agreement between the MEP-ET predicted daily ET and the corresponding observations at sites characterized by moderately limited water availability. Poor ET results were obtained under high water stress conditions. A regulation parameter was therefore introduced in the MEP-ET model to properly take into account the effects of soil water stress on stomata, yielding the generalized MEP-ET model. This parameter considerably reduced model biases under water stress conditions for various heterogeneous land surface sites. The generalized MEP-ET model outperforms several popular ET models, including Penman–Monteith (PM), modified Priestley–Taylor–Jet Propulsion Laboratory (PT-JPL), and air-relative-humidity-based two-source model (ARTS) at all test sites.

Hindcasting the Madden-Julian Oscillation With a New Parameterization of Surface Heat Fluxes.

The recently developed maximum entropy production (MEP) model, an alternative parameterization of surface heat fluxes, is incorporated into the Weather Research and Forecasting (WRF) model. A pair of WRF cloud‐resolving experiments (5 km grids) using the bulk transfer model (WRF default) and the MEP model of surface heat fluxes are performed to hindcast the October Madden‐Julian oscillation (MJO) event observed during the 2011 Dynamics of the MJO (DYNAMO) field campaign. The simulated surface latent and sensible heat fluxes in the MEP and bulk transfer model runs are in general consistent with in situ observations from two research vessels. Compared to the bulk transfer model, the convection envelope is strengthened in the MEP run and shows a more coherent propagation over the Maritime Continent. The simulated precipitable water in the MEP run is in closer agreement with the observations. Precipitation in the MEP run is enhanced during the active phase of the MJO with significantly reduced regional dry and wet biases. Large‐scale ocean evaporation is stronger in the MEP run leading to stronger boundary layer moistening to the east of the convection center, which facilitates the eastward propagation of the MJO.

Testing the maximum entropy production approach for estimating evapotranspiration from closed canopy shrubland in a low‐energy humid environment

AbstractQuantifying and partitioning evapotranspiration (ET) into evaporation and transpiration is challenging but important for interpreting vegetation effects on the water balance. We applied a model based on the theory of maximum entropy production to estimate ET for shrubs for the first time in a low‐energy humid headwater catchment in the Scottish Highlands. In total, 53% of rainfall over the growing season was returned to the atmosphere through ET (59 ± 2% as transpiration), with 22% of rainfall ascribed to interception loss and understory ET. The remainder of rainfall percolated below the rooting zone. The maximum entropy production model showed good capability for total ET estimation, in addition to providing a first approximation for distinguishing evaporation and transpiration in such ecosystems. This study shows that this simple and low‐cost approach has potential for local to regional ET estimation with availability of high‐resolution hydroclimatic data. Limitations of the approach are also discussed.

Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration–Clouds and the Earth’s Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

A coupled force‐restore model of surface temperature and soil moisture using the maximum entropy production model of heat fluxes

AbstractA coupled force‐restore model of surface soil temperature and moisture (FRMEP) is formulated by incorporating the maximum entropy production model of surface heat fluxes and including the gravitational drainage term. The FRMEP model driven by surface net radiation and precipitation are independent of near‐surface atmospheric variables with reduced sensitivity to the uncertainties of model input and parameters compared to the classical force‐restore models (FRM). The FRMEP model was evaluated using observations from two field experiments with contrasting soil moisture conditions. The modeling errors of the FRMEP predicted surface temperature and soil moisture are lower than those of the classical FRMs forced by observed or bulk formula based surface heat fluxes (bias 1 ~ 2°C versus ~4°C, 0.02 m3 m−3 versus 0.05 m3 m−3). The diurnal variations of surface temperature, soil moisture, and surface heat fluxes are well captured by the FRMEP model measured by the high correlations between the model predictions and observations (r ≥ 0.84). Our analysis suggests that the drainage term cannot be neglected under wet soil condition. A 1 year simulation indicates that the FRMEP model captures the seasonal variation of surface temperature and soil moisture with bias less than 2°C and 0.01 m3 m−3 and correlation coefficients of 0.93 and 0.9 with observations, respectively.