RELATIONS BETWEEN EVAPORATION COEFFICIENTS AND VEGETATION INDEXES STUDIED BY MODEL SIMULATIONS

Calculations using a heat balance and a radiative transfer model have been done to study relations among evaporation coefficients and vegeta tion indices. The evaporation coefficients are the crop coefficient (d efined as the ratio of total evaporation and reference crop evaporatio n) and the transpiration coefficient (defined as the ratio of unstress ed transpiration and reference crop evaporation), while the vegetation indices considered in this study are the normalized difference, soil adjusted vegetation index, and transformed soil adjusted vegetation in dex. The reference crop evaporation has been calculated using the Prie stley-Taylor equation. The observed variations of crop (wheat) height, leaf area index, and weather conditions for 30 days at Phoenix (Arizo na), together with the reflectances of different types of soil in wet and dry states, are used in the simulation. The total evaporation calc ulated from the model compared well with lysimeter observations. Varia tions in soil evaporation can introduce considerable scatter in the re lation between the crop coefficient and leaf area index, while this sc atter is much less for the relation between transpiration coefficient and leaf area index. The simulation results for 30 days of crop and we ather data and reflectances of 19 soil types in wet and dry conditions gave significant linear correlations between the transpiration coeffi cient and the vegetation indices, the explained variance (r2) being hi ghest for the soil adjusted vegetation index (r2 = 0.88) and lowest fo r the normalized difference (r2 = 0.81). A clump vegetation model is u sed to address the effect of spatial heterogeneity on the relationship between the transpiration coefficient and soil adjusted vegetation in dex. These simulated relationships between transpiration coefficient a nd vegetation indices for wheat are discussed in the context of the re lationships derived from observations for several crops and grasses. T he present analysis provides a theoretical basis for estimating, trans piration from remotely sensed data.