Constrained two layer models for estimating evapotranspiration
David L B Jupp
CSIRO Division of Water Resources Canberra,
ACT, 2601, Australia
Abstract
Thermal region remote sensing allows you to map and monitor the distribution of surface temperature. Together with meteorological data, this information is of great value in water resources applications and in environmental remote sensing institutions where the hydrological cycle is a key element. This paper discusses some questions related to the need for complexity in model used to interpret remotely sensed data. In particular, it shows how a class of constrained Two-layer models provide useful improvements on the One-layer, or Penman-Monteith, models while still retaining simplicity and ease of use with the generally limited data available through remote sensing
Introduction
The use of remotely sensed thermal infrared radiation has been increasingly applied to the study of the distribution and flow of water in the earth surface layer. In principle, the application is immediate, since the presence of water in the soil and/or the root zone of plants and trees combined with solar radiation results in evaportranspiration ( ET in the following) and a net cooling of the surface relative to similar areas with less available water as well as retention of heat during the night relative to the drier areas However, in practice, the dynamic exchanges taking place between the atmosphere and surface layer and the nature of the surface layer (trees or grass for example) result in observed temperature distributions which are complex and it is difficult to develop direct relationships between remotely sensed surface temperature and available moisture in the surface layers of the soil.
In this situation, the remotely sensed data must either be used empirically as collateral data in the study of the spatial heterogeneity and distribution of moisture - for which it is ideally suited - or combined with models of the processes involved in mass and energy exchanges in the earth surface layer. The models being used with remotely sensed data have a wide variety in complexity and detail. All are based on the principle of the energy balance:
Rn = lE + H + G---------------------------(1)
Where:
R
n is net radiation in units of Wm
-2;
lE is latent heat flux ( with
l as Latent heat of vaporization);
H is sensible heat flux; and
G is flux of heat into the soil or other storages.
The available models disaggregate the energy balance among the components of the surface layer and relate it in various ways to the water balance and the dynamics of the energy and water fluxes in the soil, vegetation and atmosphere. Through the latent heat, or evaportranspiration, term of the energy balance, remote sensing or surface temperature can provide information on the moisture content of the upper soil layers and the resistance of the surface layer to loss of moisture. This paper discusses a range of such models which are simple enough to be supported by the limited data available from remote sensing as well as being adequate to estimate the ET and other fluxes. In particular, it examines some issues raised in the practical demonstration of the methods in Jupp and Kalma ( 1989) and Kalma and Jupp
