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Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data

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Abstract

This paper reviews methods for estimating evaporation from landscapes, regions and larger geographic extents, with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Particular attention is given to the validation of such approaches against ground based flux measurements. An assessment of some 30 published validations shows an average root mean squared error value of about 50 W m−2 and relative errors of 15–30%. The comparison also shows that more complex physical and analytical methods are not necessarily more accurate than empirical and statistical approaches. While some of the methods were developed for specific land covers (e.g. irrigation areas only) we also review methods developed for other disciplines, such as hydrology and meteorology, where continuous estimates in space and in time are needed, thereby focusing on physical and analytical methods as empirical methods are usually limited by in situ training data. This review also provides a discussion of temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evaporation. Improved temporal scaling procedures are required to extrapolate instantaneous estimates to daily and longer time periods and gap-filling procedures are needed when temporal scaling is affected by intermittent satellite coverage. It is also noted that analysis of multi-resolution data from different satellite/sensor systems (i.e. data fusion) will assist in the development of spatial scaling and aggregation approaches, and that several biological processes need to be better characterized in many current land surface models.

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Notes

  1. The term evaporation as used in this paper refers to what is often referred to as evapotranspiration, which includes all processes of vaporization. It is denoted as E. The equivalent latent heat flux is denoted by λE where λ is the latent heat of vaporization (J kg−1). Over land surfaces the evaporation term comprises transpiration from vegetation, evaporation of water intercepted by the canopy of plants and trees, evaporation from the soil surface and evaporation from small water surfaces.

  2. The Normalised Diffference Vegetation Index (NDVI) is defined as [ρ NIR − ρ RED]/[ρ NIR + ρ RED] where ρ NIR and ρ RED represent the spectral reflectances in the near-infrared and red parts of the spectrum.

  3. The radiative temperature (Trad) measured by an infrared radiometer from a spaceborne platform is assumed to approximate the hemispherical radiometric temperature as defined by Norman and Becker (1995).

  4. The term one-source is used to describe models which implicitly treat the energy exchanges between soil, vegetation and the atmosphere. Such models have also been called single-layer models (see Kustas 1990).

  5. The aerodynamic surface temperature (Taero) according to Norman and Becker (1995) is that temperature, which, when combined with the air temperature and a resistance calculated from the log-profile theory, provides an estimate of the sensible heat flux.

  6. Two-source models are one-dimensional models which estimate the sensible and latent heat fluxes from the soil and the vegetation separately (see Kustas and Norman 1999). Two-source models have also been called two-layer models (see Kustas 1990).

  7. RMSE = Root Mean Square Error = square root of the mean of the squares of the differences between estimate and observation; r = correlation coefficient and r2 = coefficient of determination; and Relative Error = estimation error = (RMSE/mean value ) ×100%.

Abbreviations

B:

Coefficient in Eq. 3 (−)

CBN :

Bulk turbulent transfer coefficient (−)

Cp :

Specific heat of air at constant pressure (J kg−1 K−1)

D:

Zero plane displacement height (m)

E, Ea :

Actual evaporation rate (mm day−1)

En :

Normalised actual evaporation (mm day−1)

Ep :

Potential evaporation rate (mm day−1)

EPT :

Priestley–Taylor evaporation rate (mm day−1)

Ew :

Equilibrium evaporation rate (mm day−1)

ea :

Actual vapour pressure of the air (Pa)

ea*:

Saturated vapour pressure of the air (Pa)

es*:

Saturated vapour pressure at Ts (Pa)

eu*:

Saturated vapour pressure at Tu (Pa)

fc :

Fractional vegetation cover (−)

G:

Soil heat flux (W m−2)

Gs :

Surface conductance (m s−1)

gb :

Bulk leaf boundary layer conductance (m s−1)

H:

Sensible heat flux (W m−2)

Hc :

Sensible heat flux to/from canopy (W m−2)

Hs :

Sensible heat flux to/from soil (W m−2)

K↓:

Downwelling shortwave radiation flux (W m−2)

K↑:

Upwelling shortwave radiation flux (W m−2)

k:

Von Karman’s constant (0.4)

kB−1 :

Dimensionless ratio used to calculate rex

L:

Monin-Obukhov length (m)

L↓:

Downwelling longwave radiation flux (W m−2)

L↑:

Upwelling longwave radiation flux (W m−2)

n:

Exponent in Eq. 3

ra :

Aerodynamic resistance (s m−1)

rc :

Canopy resistance (s m−1)

rcp :

Canopy resistance at potential transpiration (s m−1)

rex :

Excess (supplementary, extra) resistance (s m−1)

Rn :

Net (allwave) radiation flux (W m−2)

(Rn)d :

Daily total of net radiation (W m−2)

rr :

Radiometric-convective resistance (s m−1)

rs :

Surface (stomatal, soil) resistance (s m−1)

T∞ :

Surface temperature of very dry pixel (K; °C)

Ta :

Air temperature at screen height (K; °C)

Taero :

Aerodynamic surface temperature (K; °C)

Tc :

Canopy temperature (K; °C)

Td :

Dew point temperature (K; °C)

TH :

Surface temperature of pixel with λE = 0 (K; °C)

TλE :

Surface temperature of pixel with H = 0 (K; °C)

Tk :

Kinetic temperature (K; °C)

To :

Surface temperature of very wet pixel (K; °C)

T0 :

Temperature of mean air stream in canopy (K; °C)

Trad :

Radiative surface temperature (K; °C)

Ts :

Radiative surface (soil + vegetation) temperature (K; °C)

Tsoil :

Soil surface temperature (K; °C)

Tu :

Unknown surface temperature in Eqs. 25 and 26 (K; °C)

Tv :

Foliage (vegetation) temperature (K; °C)

u:

Wind velocity (m s−1)

u*:

Friction velocity (m s−1)

zoh :

Roughness length for sensible heat transfer (m)

zom :

Roughness length for momentum transfer (m)

α:

Broadband albedo; hemispherical reflectance

αPT :

Priestley–Taylor parameter

β:

Stress factor in Jiang and Islam (2003)

γ:

Psychrometric constant (Pa K−1)

Δ:

Slope of saturated vapour pressure curve at current air temperature (Pa K−1)

ε:

Emissivity

θ:

View angle

Λ:

Evaporative fraction (λE/(Rn−G))

Λr :

Relative evaporation (Ea/Ep)

λ:

Latent heat of vaporization (J kg−1)

ψh :

Stability correction for sensible heat transfer

ψm :

Stability correction for momentum transfer

ϕ:

Parameter in Eqs. 14 and 15

ρ:

Air density (kg m−3)

ρ :

Upwelling spectral reflectance (−)

Ω:

Decoupling coefficient of Jarvis and McNaughton (1986)

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Acknowledgements

The authors wish to thank Wim Bastiaanssen, Gilles Boulet, Huub Savenije and two anonymous referees for their useful comments on earlier drafts of this paper.

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Authors and Affiliations

  1. School of Engineering, University of Newcastle, Callaghan, NSW, 2308, Australia

    Jetse D. Kalma

  2. CSIRO Land and Water and eWater CRC, GPO Box 1666, Canberra, ACT, 2601, Australia

    Tim R. McVicar

  3. School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Matthew F. McCabe

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  1. Jetse D. Kalma
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  2. Tim R. McVicar
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  3. Matthew F. McCabe
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Correspondence to Jetse D. Kalma.

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Kalma, J.D., McVicar, T.R. & McCabe, M.F. Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data. Surv Geophys 29, 421–469 (2008). https://doi.org/10.1007/s10712-008-9037-z

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