A novel method to convert daytime evapotranspiration into daily evapotranspiration based on variable canopy resistance

Liu, Guoshui; Hafeez, Mohsin; Liu, Yü; Xu, Di; Vote, Camilla

doi:10.1016/j.jhydrol.2011.10.042

Cited by 19 publications

(15 citation statements)

References 29 publications

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“…The maximum of half-hourly G s varied from 4.5 mm s −1 at the initial stage to 36.6 mm s −1 at the mid-season stage, and changed almost synchronously with R n (Fig. 2a), indicating that radiation was the main factor influencing G s in the course of daytime, which is consistent with previous studies (Irmak and Mutiibwa, 2010;Liu et al, 2011;Steduto and Hsiao, 1998). As air temperature (T a ) and vapor pressure deficit (VPD) increased in the afternoon (Fig.…”

Section: Prediction Of Evapotranspirationsupporting

confidence: 90%

“…Although Shuttleworth and Wallace (1985) described a well-known model with a separate treatment of soil and vegetation evaporation for sparse canopy, its practical application requires specifying five aerodynamic and surface conductances that are difficult to determine (Kool et al, 2014). In addition, some studies have developed empirical or semiempirical models of G s , such as the K-P model (Katerji and Rana, 2006;Rana et al, 2012), and Todorovic model (Liu et al, 2011;Todorovic, 1999). However, an analytical dynamic form for G s combining the soil evaporation and crop transpiration has not been established yet for canopy from partial to full cover based on a dynamic fraction of canopy cover.…”

Section: Introductionmentioning

confidence: 99%

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A dynamic surface conductance to predict crop water use from partial to full canopy cover

Ding

Kang

Zhang

et al. 2015

Agricultural Water Management

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Section: Prediction Of Evapotranspirationsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

A dynamic surface conductance to predict crop water use from partial to full canopy cover

Ding

Kang

Zhang

et al. 2015

Agricultural Water Management

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“…Colaizzi and Liu suggest Equation (1) that a model performs well when the MAE is less than 50% of the measured standard deviation, Equation (2) that there are few outliers when the RMSE is not greater than 50% of the MAE, and Equation (3) that the higher the value of d, the better the model performance [30,31]. …”

Section: Methodsmentioning

confidence: 99%

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin

Liu

Zhu

et al. 2016

Sensors

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Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index—FY-2D cloud type sunshine factor—is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration.

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“…The constant reference evaporative fraction (EFr, the ratio of actual to reference grass (alfalfa) ET) method, which was proposed by Trezza [] to use a fixed surface resistance of 50 (30) s/m during the daytime and 200 s/m during the nighttime for reference grass (alfalfa) ET estimates and assumes that EFr is relatively constant during the day, is one of the most widely applied schemes for upscaling instantaneous remote sensing estimates of ET. The effectiveness of the constant EFr method in upscaling instantaneous ET data has been investigated and demonstrated by numerous studies that used primarily local (in situ) metrological observations [ Colaizzi et al ., ; Chávez et al ., ; Allen et al ., ; Liu et al ., ; Tang et al ., ]. Biases may be found when this method is tested by using only remote sensing data [ Cammalleri et al ., ].…”

Section: Introductionmentioning

confidence: 99%

Temporal upscaling of instantaneous evapotranspiration on clear‐sky days using the constant reference evaporative fraction method with fixed or variable surface resistances at two cropland sites

Tang

Sun

et al. 2017

JGR Atmospheres

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Surface evapotranspiration (ET) is an important component of water and energy in land and atmospheric systems. This paper investigated whether using variable surface resistances in the reference ET estimates from the full‐form Penman‐Monteith (PM) equation could improve the upscaled daily ET estimates in the constant reference evaporative fraction (EFr, the ratio of actual to reference grass/alfalfa ET) method on clear‐sky days using ground‐based measurements. Half‐hourly near‐surface meteorological variables and eddy covariance (EC) system‐measured latent heat flux data on clear‐sky days were collected at two sites with different climatic conditions, namely, the subhumid Yucheng station in northern China and the arid Yingke site in northwestern China and were used as the model input and ground‐truth, respectively. The results showed that using the Food and Agriculture Organization (FAO)‐PM equation, the American Society of Civil Engineers‐PM equation, and the full‐form PM equation to estimate the reference ET in the constant EFr method produced progressively smaller upscaled daily ET at a given time from midmorning to midafternoon. Using all three PM equations produced the best results at noon at both sites regardless of whether the energy imbalance of the EC measurements was closed. When the EC measurements were not corrected for energy imbalance, using variable surface resistance in the full‐form PM equation could improve the ET upscaling in the midafternoon, but worse results may occur in the midmorning to noon. Site‐to‐site and time‐to‐time variations were found in the performances of a given PM equation (with fixed or variable surface resistances) before and after the energy imbalance was closed.

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A novel method to convert daytime evapotranspiration into daily evapotranspiration based on variable canopy resistance

Cited by 19 publications

References 29 publications

A dynamic surface conductance to predict crop water use from partial to full canopy cover

A dynamic surface conductance to predict crop water use from partial to full canopy cover

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin

Temporal upscaling of instantaneous evapotranspiration on clear‐sky days using the constant reference evaporative fraction method with fixed or variable surface resistances at two cropland sites

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