Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications

Numerous models had been developed to predict the annual evapotranspiration (ET) in vegetated lands across various spatial scales. Fu's (Scientia Atmospherica Sinica, 5, 23–31) and Zhang's (Water Resources Research, 37, 701–708) ET simulation models have emerged as highly effective and have been widely used. However, both formulas have the non-quantitative parameters (m in Fu's model and w in Zhang's model). Based on the collected 1789 samples from global long-term hydrological studies, this study discovered significant relations between m (or w) and vegetation coverage or greenness in collected catchments. Then, we used these relations to qualify the parameters in both Zhang's and Fu's models. Results show that the ET estimation accuracies of Fu's (or Zhang's) model are significantly improved by about 13.49 mm (or 6.74 mm) for grassland and cropland, 38.52 mm (or 29.84 mm) for forest and shrub land (coverage<40%), 19.74 mm (or 16.17 mm) for mixed land (coverage<40%), respectively. However, Zhang's model shows higher errors compared with Fu's model, especially in regions with high m (or w) values, such as those with dense vegetations or P/E₀ (annual precipitation to annual potential ET) smaller than 1.0. Additionally, this study also reveals that for regions with vegetation cover less than 40%, the annual ET is not only determined by vegetation types, but also relates to the sizes of vegetation-covered areas. Conversely, for regions with vegetation cover more than 40%, the annual ET is mainly determined by the vegetation density rather than vegetation types or vegetation coverage. Thus, linking m (or w) parameters with vegetation greenness allows leveraging remote sensing for forest management in data-scarce areas, safeguarding regional water resources. This study pioneers integrating vegetation-related indices with basin parameters, advocating for their crucial role in more effective hydrological modelling.     

Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models

Evapotranspiration (ET) is an important parameter in hydrologic processes and modelling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ET_c) accurately is critical for improving irrigation system and basin water management. The use of remote sensing-based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near-infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modelling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north–south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analysed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices.     

Simulating daily, monthly and annual water balances in a land surface model using alternative root water uptake schemes

Hydrological simulations at multi-temporal time scales by a widely used land surface model (LSM) are investigated under contrasting vegetation and meteorological conditions. Our investigation focuses particularly on the effects of two different representations of root water uptake and root profile on simulated evapotranspiration (ET) and soil moisture by the Integrated BIosphere Simulator (IBIS). For this purpose, multi-year eddy covariance measurements, collected at four flux-tower sites across North America, were used to gauge IBIS simulations with: (a) its standard version (IBIS2.1), in which static root water uptake (RWU) and root profile schemes are incorporated; and (b) a modified version in which dynamic RWU and root profile schemes replaces the static schemes used in the standard version. Overall, our results suggest that the modified version of the model performs more realistically than the standard version, particularly when high atmospheric demand for evaporation is combined with high atmospheric vapour pressure deficit and low soil water availability. The overall correlation between simulated and measured monthly ET rates at the simulated sites reached 0.87 and 0.91 for the standard and the modified versions, respectively. Our results also show that the incorporation of the dynamic RWU in IBIS yields improved simulations of ET under very dry conditions, when soil moisture falls down to very low levels. This suggests that adequate representations of vegetation responses to drought are needed in LSMs as many state of the art climate models projections of future climate indicate more frequent and/or more intense drought events occurring in some regions of the globe. Our analysis also highlighted the urgent need for adequate methodologies to correct field measurements that exhibit energy imbalances in order to provide rigorous assessments of land surface model simulations of heat and mass exchanges between the land surface and the atmosphere.     

Distributed modelling of future changes in hydrological processes of Spencer Creek watershed

The hydrologic impact of climate change has been largely assessed using mostly conceptual hydrologic models. This study investigates the use of distributed hydrologic model for the assessment of the climate change impact for the Spencer Creek watershed in Southern Ontario (Canada). A coupled MIKE SHE/MIKE 11 hydrologic model is developed to represent the complex hydrologic conditions in the Spencer Creek watershed, and later to simulate climate change impact using Canadian global climate model (CGCM 3·1) simulations. Owing to the coarse resolution of GCM data (daily GCM outputs), statistical downscaling techniques are used to generate higher resolution data (daily precipitation and temperature series). The modelling results show that the coupled model captured the snow storage well and also provided good simulation of evapotranspiration (ET) and groundwater recharge. The simulated streamflows are consistent with the observed flows at different sites within the catchment. Using a conservative climate change scenario, the downscaled GCM scenarios predicted an approximately 14–17% increase in the annual mean precipitation and 2–3 °C increase in annual mean maximum and minimum temperatures for the 2050s (i.e., 2046–2065). When the downscaled GCM scenarios were used in the coupled model, the model predicted a 1–5% annual decrease in snow storage for 2050s, approximately 1–10% increase in annual ET, and a 0·5–6% decrease in the annual groundwater recharge. These results are consistent with the downscaled temperature results. For future streamflows, the coupled model indicated an approximately 10–25% increase in annual streamflows for all sites, which is consistent with the predicted changes in precipitation. Overall, it is shown that distributed hydrologic modelling can provide useful information not only about future changes in streamflow but also changes in other key hydrologic processes such as snow storage, ET, and groundwater recharge, which can be particularly important depending on the climatic region of concern. The study results indicate that the coupled MIKE SHE/MIKE 11 hydrologic model could be a particularly useful tool for understanding the integrated effect of climate change in complex catchment scale hydrology. Copyright © 2010 John Wiley & Sons, Ltd.     

Use of remote sensing for evapotranspiration monitoring over land surfaces

Abstract

Monitoring evapotranspiration (ET) at large scales is important for assessing climate and anthropogenic effects on natural and agricultural ecosystems. This paper describes techniques used in evaluating ET with remote sensing, which is the only technology that can efficiently and economically provide regional and global coverage. Some of the empirical/statistical techniques have been used operationally with satellite data for computing daily ET at regional scales. The more complex numerical simulation models require detailed input parameters that may limit their application to regions containing a large database of soils and vegetation properties. Current efforts are being directed towards simplifying the parameter requirements of these models. Essentially all energy balance models rely on an estimate of the available energy (net radiation less soil heat flux). Net radiation is not easily determined from space, although progress is being made. Simplified approaches for estimating soil heat flux appear promising for operational applications. In addition, most ET models utilize remote sensing data in the shortwave and thermal wavelengths to measure key boundary conditions. Differences between the radiometric surface temperature and aerodynamic temperature can be significant and progress in incorporating this effect is evident. Atmospheric effects on optical data are significant, and optical sensors cannot see through clouds. This has led some to use microwave observations as a surrogate for optical data to provide estimates of surface moisture and surface temperature; preliminary results are encouraging. The approaches that appear most promising use surface temperature and vegetation indices or a time rate of change in surface temperature coupled to an atmospheric boundary layer model. For many of these models, differences with ET observations can be as low as 20% from hourly to daily time scales, approaching the level of uncertainty in the measurement of ET and contradicting some recent pessimistic conclusions concerning the utility of remotely sensed radiometric surface temperature for determining the surface energy balance.     

On the role of soil moisture in daytime evolution of temperatures

This paper explores the relationship between temperature, evaporation and soil moisture using a planetary boundary layer (PBL) model. It focuses on illustrating and quantifying the effect of soil moisture on the evolution of daytime temperatures. A simple convective PBL model coupled with the Penman–Monteith (PM) equation is used to estimate evapotranspiration. Following calibration and sensitivity analysis, the model was used to simulate the relative impact of dry and wet soil moisture conditions on daytime temperatures by changing the surface resistance parameter in the PM equation. It was found that the maximum temperature that can be reached during a day is constrained by the amount of soil moisture and the available net radiation, confirming previously published results. Higher temperatures can be reached with greater net radiation and dry soil moisture conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Climate sensitivity of water use by riparian woodlands at landscape scales

Semi-arid riparian woodlands face threats from increasing extractive water demand and climate change in dryland landscapes worldwide. Improved landscape-scale understanding of riparian woodland water use (evapotranspiration, ET) and its sensitivity to climate variables is needed to strategically manage water resources, as well as to create successful ecosystem conservation and restoration plans for potential climate futures. In this work, we assess the spatial and temporal variability of Cottonwood (Populus fremontii)-Willow (Salix gooddingii) riparian gallery woodland ET and its relationships to vegetation structure and climate variables for 80 km of the San Pedro River corridor in southeastern Arizona, USA, between 2014 and 2019. We use a novel combination of publicly available remote sensing, climate and hydrological datasets: cloud-based Landsat thermal remote sensing data products for ET (Google Earth Engine EEFlux), Landsat multispectral imagery and field data-based calibrations to vegetation structure (leaf-area index, LAI), and open-source climate and hydrological data. We show that at landscape scales, daily ET rates (6–10 mm day⁻¹) and growing season ET totals (400–1,400 mm) matched rates of published field data, and modelled reach-scale average LAI (0.80–1.70) matched lower ranges of published field data. Over 6 years, the spatial variability of total growing season ET (CV = 0.18) exceeded that of temporal variability (CV = 0.10), indicating the importance of reach-scale vegetation and hydrological conditions for controlling ET dynamics. Responses of ET to climate differed between perennial and intermittent-flow stream reaches. At perennial-flow reaches, ET correlated significantly with temperature, whilst at intermittent-flow sites ET correlated significantly with rainfall and stream discharge. Amongst reaches studied in detail, we found positive but differing logarithmic relationships between LAI and ET. By documenting patterns of high spatial variability of ET at basin scales, these results underscore the importance of accurately accounting for differences in woodland vegetation structure and hydrological conditions for assessing water-use requirements. Results also suggest that the climate sensitivity of ET may be used as a remote indicator of subsurface water resources relative to vegetation demand, and an indicator for informing conservation management priorities.     

Research on the method for retrieving soil moisture using thermal inertia model

1 Introduction Thermal inertia is a bulk property that shows the re- sistance of a material to an input or output of heat. This plays a very important role in certain geological and hydrological studies, and climate modeling. In the 1970s, a simple thermal inertia model was proposed by Watson et al.[1―3]. Pratt (1979)[4] improved the thermal inertia model based on application tests where more factors were considered such as solar ra- diance, thermal conductivity effect, average humidity of g…     

北京大学陆面过程模式PKULM(Peking University Land Model)介绍及检验

陆面过程模式是气候模式和天气模式的核心组成部分之一.在土壤—植被—大气耦合模式(Soil-PlantAtmosphere Model,SPAM)的基础上,发展了新一代北京大学陆面过程模式PKULM(Peking University Land Model).本文首先介绍了PKULM的辐射传输、湍流输送、光合作用、土壤水热输送等过程的参数化方案;采用隐式迭代计算框架,发展并应用了一个快速的线性方程组求解算法,提高了模式计算稳定性;提出并使用了二分搜索算法计算气孔阻抗,避免了CLM(Community Land Model)等使用的迭代方法在干旱区不稳定的情况,提高了模式的适用性;采用水势为基础的土壤水分扩散方程,使模式能够模拟土壤饱和区的水分输送过程,为进一步与水文过程模式耦合奠定了基础;还发展了一个地表积水与径流过程的机理模型,提高了模式对地表水分平衡过程的模拟能力;最后,使用"中国西北干旱区陆—气相互作用观测试验"平凉站的资料对模式进行了检验并与NOAH(National Center for Environmental Prediction,Oregon State University,Air Force,and Hydrology Lab model)陆面过程模式的模拟结果进行了比较,结果表明PKULM能够较好地模拟西北半干旱区农田下垫面地气交换过程.     

Transpiration and evaporation of grassland using land surface modelling

Partitioning transpiration (T) from evapotranspiration (ET) is a key process for understanding the interaction between land surfaces and the atmosphere. This paper reports daily partitioning results for a grassland over a 10-year period, obtained using the Community Land Model 3.5 (CLM3.5) land surface model. Hourly forcing data were collected from a long-term observation system located in the northeast of Japan ( http://doi.org/10.24575/0001.198108 ). To test the model behavior, total ET was validated using eddy correlation measurements combined with the energy balance method. The results were compared with previous research using an isotope approach for partitioning. The results demonstrate that our model can capture the dynamics of ET and its components at this location. Evaporation (E), originating from the ground and canopy, varied inter-annually, and from 2006 to 2015, average annual E was approximately 285 mm/year from the ground and 45 mm/year from the canopy. Average, T, was approximately 302 mm/year, accounting for approximately 48% of the total ET. Inter-annual results demonstrate that the water flux transported by vegetation ranges from 17 to 83% during the April–October period. A sensitivity test conducted with forcing data indicates air temperature, incident solar radiation, and longwave radiation exhibited a notable effect on all ET components. Relative humidity exhibited the only negative feedback to both evaporation and transpiration, contrary to the other forcing parameters. Our study reemphasized the effectiveness of CLM3.5 in partitioning T from ET and in understanding the complex interaction between land surfaces and the atmosphere.     

Further evaluation of the Sim-ReSET model for ET estimation driven by only satellite inputs

Abstract

A simple remote sensing evapotranspiration (ET) model (Sim-ReSET) has been proposed but only tested using field measurements at a site with a semi-arid climate. Its performance for mapping ET using only satellite data remained unknown. In this study, the Sim-ReSET model was further evaluated for ET estimation driven by only MODIS data products. The estimated ET rates were compared with ground-based observational data from a variety of ecosystems and climates across China. The results show that MODIS-based ET estimates are consistent with both the ET measurements from eddy covariance flux towers and those from the Penman-Monteith method combined with micrometeorological data. Evaporation fraction (EF) is indicative of land surface moisture. The derivative EF maps demonstrate that the proposed ET data set obtained from the Sim-ReSET model and MODIS data is capable of capturing the spatio-temporal pattern of land surface moisture for different land covers with different climates.

Editor Z.W. Kundzewicz

Citation Sun, Z.G., Wang, Q.X., Matsushita, B., Fukushima, T., Ouyang, Z., Watanabe, M., and Gebremichael, M., 2013. Further evaluation of the Sim-ReSET model for ET estimation driven by only satellite inputs. Hydrological Sciences Journal, 58 (5), 994–1012.     

Evapotranspiration in the Mekong and Yellow river basins / Evapotranspiration dans les bassins du Mekong et du Fleuve Jaune

Abstract

Estimates of potential evapotranspiration (PET) and reference evapotranspiration (RET) were compared over the Mekong and Yellow river basins, representing humid and semi-arid Asian monsoon regions. Multiple regression relationships between monthly RET, PET, LAI (leaf area index) and climatic variables were explored for different vegetation types. Over the Mekong River basin, the spatial average of RET is only 1.7% lower than PET; however, RET is 140% higher than PET over parts of the Tibetan Plateau, due to the short and sparse grassland, and 30% lower than PET in parts of the lower basin due to the tall and well-developed forests. Over the Yellow River basin, RET is estimated to be higher than PET, on average about 50% higher across the whole basin, due to the generally sparse vegetation. A close linear relationship between annual RET and PET allows the establishment of a regional regression to predict monthly PET from monthly RET, climatic variables and/or vegetation LAI. However, the large prediction errors indicate that the Shuttleworth-Wallace (S-W) model, although it is more complex, should be recommended due to its more robust physical basis and because it successfully accounts for the effect of changing land surface conditions on PET. The limited available field data suggest that the S-W estimate may be more realistic. It was also found that vegetation conditions in summer are primarily controlled by the regional antecedent precipitation in the cold and dry seasons over the Loess Plateau in the middle reaches of the Yellow River.     

A new approach for measuring surface hydrological connectivity

The development of surface hydrological connectivity is a key determinant of flood magnitude in drylands. Thresholds in runoff response may be reached when isolated runoff-generating areas connect with each other to form continuous links to river channels, enabling these areas to contribute to flood hydrographs. Such threshold behaviour explains observed nonlinearities and scale dependencies of dryland rainfall–runoff relationships and complicates attempts at flood prediction. However, field methods for measuring the propensity of a surface to transmit water downslope are lacking, and conventional techniques of infiltration measurement are often inappropriate for use on non-agricultural drylands. Here, we argue for a reconceptualization of the dryland surface runoff process, suggesting that the downslope transfer of water should be considered alongside surface infiltration; that is, there is a need for the “aggregated” measurement of infiltration and overland flow hydraulics. Surface application of a set volume of water at a standardized rate generates runoff that travels downslope; the distance it travels downslope is determined by infiltration along the flow, integration of flow paths, and flow resistance. We demonstrate the potential of such a combined measurement system coupled with structure-from-motion photogrammetry to identify surface controls on runoff generation and transfer on dryland hillslopes, with vegetation, slope, surface stone cover, and surface roughness all having a significant effect. The measurement system has been used on slopes up to 37° compared with the flat surface typically required for infiltration methods. On average, the field workflow takes ~10–15 min, considerably quicker than rainfall simulation. A wider variety of surfaces can be sampled with relative ease, as the method is not restricted to stone and vegetation-free land. We argue that this aggregated measurement represents surface connectivity and dryland runoff response better than standard hydrological approaches and can be applied on a much greater variety of dryland surfaces.     

Modelling plant canopy effects on annual variability of evapotranspiration and heat fluxes for a semi‐arid grassland on the southern periphery of the Eurasian cryosphere in Mongolia

The ability to predict vegetation cover effects on thermal/water regimes can enhance our understanding of canopy controls on evapotranspiration. The Simultaneous Heat and Water (SHAW) model is a detailed process model of heat and water movement in a snow–residue–soil system. This paper describes provisions added to the SHAW model for vegetation cover and simulation of heat and water transfer through the soil–plant–air continuum. The model was applied to four full years (May 2003–April 2007) of data collected on sparse grassland at Nalaikh in north‐eastern Mongolia. Simulated soil temperature and radiation components agreed reasonably well with measured values. The absolute differences between simulated and measured soil temperatures were larger at both the surface layer and deeper layer, but relatively smaller in the layer from 0·8 to 2·4 m. Radiation components were mimicked by the SHAW model with model efficiency (ME) reaching 0·93–0·72. Latent and sensible heat fluxes were simulated well with MEs of 0·93 and 0·87, respectively. The vegetation control on evapotranspiration was investigated by sensitivity experiments of model performance with changing leaf area index (LAI) values but constant of other variables. The results suggest that annual evapotranspiration ranged from 16 to ? 22% in response to extremes of doubled and zero LAI. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of NLDAS‐2 evapotranspiration against tower flux site observations

The North American Land Data Assimilation System project phase 2 (NLDAS‐2) has run four land surface models for a 30‐year (1979–2008) retrospective period. Land surface evapotranspiration (ET) is one of the most important model outputs from NLDAS‐2 for investigating land–atmosphere interaction or to monitor agricultural drought. Here, we evaluate hourly ET using in situ observations over the Southern Great Plains (Atmospheric Radiation Measurement/Cloud and Radiation Testbed network) for 1 January 1997–30 September 1999 and daily ET u‐sing in situ observations at the AmeriFlux network over the conterminous USA for an 8‐year period (2000–2007). The NLDAS‐2 models compare well against observations, with the National Centers for Environmental Prediction's Noah land surface model performing best, followed, in order, by the Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic models. Daily evaluation across the AmeriFlux network shows that for all models, performance depends on season and vegetation type; they do better in spring and fall than in winter or summer and better for deciduous broadleaf forest and grasslands than for croplands or evergreen needleleaf forest. Copyright © 2014 John Wiley & Sons, Ltd.     

A simple temperature method for the estimation of evapotranspiration

Accurate estimation of evapotranspiration (ET) is essential in water resources management and hydrological practices. Estimation of ET in areas, where adequate meteorological data are not available, is one of the challenges faced by water resource managers. Hence, a simplified approach, which is less data intensive, is crucial. The FAO‐56 Penman–Monteith (FAO‐56 PM) is a sole global standard method, but it requires numerous weather data for the estimation of reference ET. A new simple temperature method is developed, which uses only maximum temperature data to estimate ET. Ten class I weather stations data were collected from the National Meteorological Agency of Ethiopia. This method was compared with the global standard PM method, the observed Piche evaporimeter data, and the well‐known Hargreaves (HAR) temperature method. The coefficient of determination (R²) of the new method was as high as 0.74, 0.75, and 0.91, when compared with that of PM reference evapotranspiration (ET_o), Piche evaporimeter data, and HAR methods, respectively. The annual average R² over the ten stations when compared with PM, Piche, and HAR methods were 0.65, 0.67, and 0.84, respectively. The Nash–Sutcliff efficiency of the new method compared with that of PM was as high as 0.67. The method was able to estimate daily ET with an average root mean square error and an average absolute mean error of 0.59 and 0.47 mm, respectively, from the PM ET_o method. The method was also tested in dry and wet seasons and found to perform well in both seasons. The average R² of the new method with the HAR method was 0.82 and 0.84 in dry and wet seasons, respectively. During validation, the average R² and Nash–Sutcliff values when compared with Piche evaporation were 0.67 and 0.51, respectively. The method could be used for the estimation of daily ET_o where there are insufficient data. Copyright © 2013 John Wiley & Sons, Ltd.     

Modelling hydrological processes influenced by soil,rock and vegetation in a small karst basin of southwest China

Hydrological processes in karst basins are controlled by permeable multimedia, consisting of soil pores, epikarst fractures, and underground conduits. Distributed modelling of hydrological dynamics in such heterogeneous hydrogeological conditions is a challenging task. Basing on the multilayer structure of the distributed hydrology‐soil‐vegetation model (DHSVM), a distributed hydrological model for a karst basin was developed by integrating mathematical routings of porous Darcy flow, fissure flow and underground channel flow. Specifically, infiltration and saturated flow movement within epikarst fractures are expressed by the ‘cubic law’ equation which is associated with fractural width, direction, and spacing. A small karst basin located in Guizhou province of southwest China was selected for this hydrological simulation. The model parameters were determined on the basis of field measurement and calibrated against the observed soil moisture contents, vegetation interception, surface runoff, and underground flow discharges from the basin outlet. The results show that due to high permeability of the epikarst zone, a significant amount of surface runoff is only generated after heavy rainfall events during the wet season. Rock exposure and the epikarst zone significantly increase flood discharge and decrease evapotranspiration (ET) loss; the peak flood discharge is directly proportional to the size of the aperture. Distribution of soil moisture content (SMC) primarily depends on topographic variations just after a heavy rainfall, while SMC and actual ET are dominated by land cover after a period of consecutive non‐rainfall days. The new model was able to capture the sharp increase and decrease of the underground streamflow hydrograph, and as such can be used to investigate hydrological effects in such rock features and land covers. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulation of crop growth and energy and carbon dioxide fluxes at different time steps from hourly to daily

Understanding the exchange processes of energy and carbon dioxide (CO₂) in the soil–vegetation–atmosphere system is important for assessing the role of the terrestrial ecosystem in the global water and carbon cycle and in climate change. We present a soil–vegetation–atmosphere integrated model (ChinaAgrosys) for simulating energy, water and CO₂ fluxes, crop growth and development, with ample supply of nutrients and in the absence of pests, diseases and weed damage. Furthermore, we test the hypotheses of whether there is any significant difference between simulations over different time steps. CO₂, water and heat fluxes were estimated by the improving parameterization method of the coupled photosynthesis–stomatal conductance–transpiration model. Soil water evaporation and plant transpiration were calculated using a multilayer water and heat‐transfer model. Field experiments were conducted in the Yucheng Integrated Agricultural Experimental Station on the North China Plain. Daily weather and crop growth variables were observed during 1998–2001, and hourly weather variables and water and heat fluxes were measured using the eddy covariance method during 2002–2003. The results showed that the model could effectively simulate diurnal and seasonal changes of net radiation, sensible and latent heat flux, soil heat flux and CO₂ fluxes. The processes of evapotranspiration, soil temperature and leaf area index agree well with the measured values. Midday depression of canopy photosynthesis could be simulated by assessing the diurnal change in canopy water potential. Moreover, the comparisons of simulated daily evapotranspiration and net ecosystem exchange (NEE) under different time steps indicated that time steps used by a model affect the simulated results. There is no significant difference between simulated evapotranspiration using the model under different time steps. However, simulated NEE produces large differences in the response to different time steps. Therefore, the accurate calculation of average absorbed photosynthetic active radiation is important for the scaling of the model from hourly steps to daily steps in simulating energy and CO₂ flux exchanges between winter wheat and the atmosphere. Copyright © 2007 John Wiley & Sons, Ltd.     

Multi‐model ensemble prediction of terrestrial evapotranspiration across north China using Bayesian model averaging

Using high‐quality dataset from 12 flux towers in north China, the performance of four evapotranspiration (ET) models and the multi‐model ensemble approaches including the simple averaging (SA) and Bayesian model average (BMA) were systematically evaluated in this study. The four models were the single‐layer Penman–Monteith (P–M) model, the two‐layer Shuttleworthe–Wallace (S–W) model, the advection–aridity (A–A) model, and a modified Priestley–Taylor (PT‐JPL). Based on the mean value of Taylor skill (S) and the regression slope between measured and simulated ET values across all sites, the order of overall performance of the individual models from the best to the worst were: S–W (0.88, 0.87), PT‐JPL (0.80, 1.17), P–M (0.63, 1.73) and A–A (0.60, 1.68) [statistics stated as (Taylor skill, regression slope)]. Here, all models used the same values of parameters, LAI and fractional vegetation cover as well as the forcing meteorological data. Thus, the differences in model performance were mainly attributed to errors in model structure. To the ensemble approach, the BMA method has the advantage of generating more skillful and reliable predictions than the SA scheme. However, successful implementation of BMA requires accurate estimates of its parameters, and some degradation in performance were observed when the BMA parameters generated from the training period were used for the validation period. Thus, it is necessary to explore the seasonal variations of the BMA parameters according the different growth stages. Finally, the optimal conditional density function of half‐hourly ET approximated well by the double‐exponential distribution. Copyright © 2016 John Wiley & Sons, Ltd.     

Impact of flooded rice paddy on remotely sensed evapotranspiration in the Krishna River basin,India

Evapotranspiration (ET) is one of the major water exchange processes between the earth's surface and the atmosphere. ET is a combined process of evaporation from open water bodies, bare soil and plant surfaces, and transpiration from vegetation. Remote sensing-based ET models have been developed to estimate spatially distributed ET over large regions, however, many of them reportedly underestimate ET over semi-arid regions (Jamshidi et al., Journal of Hydrometeorology, 2019, 20, 947–964). In this work, we show that underestimation of ET can occur due to the open water evaporation from flooded rice paddies ignored in the existing ET models. To address the gap in ET estimation, we have developed a novel approach that accounts for the missing ET component over flooded rice paddies. Our method improved ET estimates by a modified Penman-Monteith algorithm that considered the fraction of open water evaporation from flooded rice paddies. Daily ET was calculated using ground based meteorological data and the MODIS satellite data over the Krishna River Basin. Seasonal and annual ET values over the Krishna Basin were compared with two different ET algorithms. ET estimates from these two models were also compared for different crop combinations. Results were validated with flux tower-based measurements from other studies. We have identified a 17 mm/year difference in average annual ET over the Krishna River Basin with this new ET algorithm. This is very critical in basin scale water balance analysis and water productivity studies.