Abstract
The complementary relationship for estimating evapotranspiration (ET) is a simple approach requiring only commonly available meteorological data; however, most complementary relationship models decrease in predictive power with increasing aridity. In this study, a previously developed Granger and Gray (GG) model by using Budyko framework is further improved to estimate ET under a variety of climatic conditions. This updated GG model, GG-NDVI, includes Normalized Difference Vegetation Index (NDVI), precipitation, and potential evapotranspiration based on the Budyko framework. The Budyko framework is consistent with the complementary relationship and performs well under dry conditions. We validated the GG-NDVI model under operational conditions with the commonly used remote sensing-based Operational Simplified Surface Energy Balance (SSEBop) model at 60 Eddy Covariance AmeriFlux sites located in the USA. Results showed that the Root Mean Square Error (RMSE) for GG-NDVI ranged between 15 and 20 mm/month, which is lower than for SSEBop every year. Although the magnitude of agreement seems to vary from site to site and from season to season, the occurrences of RMSE less than 20 mm/month with the proposed model are more frequent than with SSEBop in both dry and wet sites. Another finding is that the assumption of symmetric complementary relationship is a deficiency in GG-NDVI that may introduce an inherent limitation under certain conditions. We proposed a nonlinear correction function that was incorporated into GG-NDVI to overcome this limitation. As a result, the proposed model produced much lower RMSE values, along with lower RMSE across more sites, as compared to SSEBop.
Highlights
According to the U.S Geological Survey (USGS) Famine Early Warning Systems Network [1], the rate and amount of evapotranspiration (ET) plays a considerable role in the monitoring of water loss from agricultural lands
Phase 1 is the validation stage in which comparisons are made between the SSEBop model and measured ET to assess the accuracy of the remote sensing method to estimate ET
In Phase 2, a comparison of estimated ET from Granger and Gray (GG)-Normalized Difference Vegetation Index (NDVI) with observed data will be performed to identify the weaknesses of the GG-NDVI model, especially relative to the complementary relationship, and appropriate corrections will be proposed
Summary
According to the U.S Geological Survey (USGS) Famine Early Warning Systems Network [1], the rate and amount of evapotranspiration (ET) plays a considerable role in the monitoring of water loss from agricultural lands. As noted by Senay et al [2], ET may be used to show the current vegetation condition compared to the historical records. This comparison has the potential to help identify vegetation stress in time and space. McMahon [3] classified the ground-based ET methods into six classes on the basis of application: 1) potential evapotranspiration (ETP); 2) reference evapotranspiration; 3) actual evapotranspiration; 4) open water evaporation; 5) lake/ storage evaporation; and 6) pan evaporation. We have focused on actual ET in this study because it can be representative of actual conditions, whereas reference evapotranspiration would require a vegetation resistance parameter and deep lakes would require water temperature data. We use the term “evapotranspiration (ET)” in this paper to include actual evapotranspiration except in places where the term “reference (crop) evapotranspiration” is used by other authors
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