**1. Introduction**

Land surface evapotranspiration (ET) is an essential part of agricultural water management, and there are many classical methods including the Penman [1]. In the recent years, the Food and Agriculture Organization (FAO) version of Penman-Monteith Equation [2] is widely used to estimate ET. However, this method is limited for hydrologic purpose. For example, meteorological data need to be measured at 2-m elevation, and the FAO method is mainly used to estimate crop ET from agricultural lands using crop coefficients which are derived from unlimited water conditions and specific times of the growing cycle. As an alternative, the complementary relationship (CR) developed by Bouchet [3] can be used to estimate ET using general meteorological data. This approach proposed the first complementary function of potential evapotranspiration (ETP) and wet environment evapotranspiration (ETW) for a

wide range of available energy to estimate ET. Bouchet [3] postulated that the decrease in ET is matched by an equivalent increase in ETP as a surface dries. Later, Granger and Gray [4] model named as the GG model is one of the widely known models using the CR because it requires only meteorological data. Recently, Ref. [5] modified the GG model with meteorological data from 34 global eddy covariance sites. While the results were very good as compared other published ET methods, they mentioned that further refinements can improve performance under dry conditions. A probable reason is that the original GG model was empirically derived from wet biased environments in Canada. Taking this limitation into account, the model development was designed to extend the latest CR model using both meteorological data and NDVI. We then will validate the proposed model with other ET methods including a remote sensing model. Finally, we will address the possibility of using ET as a proxy for drought monitoring through a new drought index.
