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Estimating evapotranspiration is an important component in the monitoring of agricultural and environmental systems. This chapter will focus on the developing evapotranspiration method using general meteorological data and Normalized Difference Vegetation Index (NDVI). The proposed model in this chapter will be refined by using both the complementary relationship and the Budyko framework. The relative evaporation parameter in the complementary relationship will be derived by using precipitation, potential evapotranspiration, and NDVI based on that the Budyko framework can support the complementary relationship. It is also important to determine whether the proposed model can compete and deliver accuracy similar to remote sending method in the aspect of application. The results in the first phase showed the proposed model could be a powerful methodology to estimate ET among the ground-based method. In the second phase, a nonlinear correction function was proposed to better describe the complementary relationship. We will also demonstrate that the use of ET is a better approach for drought estimations than considering reference ET. More importantly, the advantage of the proposed model is that it can comprehensively consider both effects of precipitation and vegetation information. Taken together, this chapter has extended our knowledge of ET to support water resource management.

Many operational drought indices focus on precipitation and temperature when depicting hydro-climatic anomalies and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between wet environmental evaporation which is the ET rate of a surface with unlimited moisture and actual ET is leveraged in a new drought index based on complementary relationship. The proposed drought index, the Evapotranspiration Water deficit Drought Index (EWDI), is to compare the ET rate of a saturated surface with current water demand. To calculate EWDI, monthly actual ET estimated from an improved GG model using precipitation, Normalized Difference Vegetation Index, and meteorological data. We presented that EWDI produces results that are consistent with the United States Drought Monitor which is widely used for drought monitoring. Also, we found that EWDI can serve as an indicator of rapidly evolving fast droughts developing over a few weeks and is able to capture drought conditions better when we use an accurate ET method.

Land surface actual evapotranspiration (ET) is an important process in terrestrial water balance and reliable estimates of ET are necessary to improve water resources management. In this regard, there is a growing body of literature that recognizes the importance of an accurate ET model. Among them, the complementary relationship between ET and potential ET (ETP) has been the subject of many studies because it uses only meteorological data as inputs. However, there is an increasing concern that some complementary relationship models perform poorly under dry conditions. To overcome this limitation, this dissertation was designed to extend the latest complementary relationship model, Modified GG, using both meteorological data and vegetation information, NDVI, which is readily available from remote sensing data. The proposed model, Adjusted GG-NDVI, was validated by comparing to other ET models and measured ET data. With Adjusted GG-NDVI, this dissertation addressed the applicability of using ET as a proxy for drought monitoring. As a result, the drought patterns from the proposed drought index, EWDI, were consistent with commonly used USDM in the United States. More importantly, this study described drought conditions by comprehensively considering both precipitation and vegetation conditions. Taken together, these findings have significant implications for the understanding of how ET can assist in water resources management.