Comparative study of potential evapotranspiration and interception evaporation by land cover over Mekong basin

Abstract

AbstractPotential evapotranspiration is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P‐M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this article, the Shuttleworth–Wallace (S‐W) model is implemented to estimate the potential evapotranspiration from soil moisture (PET) and the potential evaporation from interception (PET0) directly in a form that recognizes vegetation diversity and temporal development without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme (IGBP) land cover classification. The spatial and temporal variation of the leaf area index (LAI) of vegetation is derived from the composite National Oceanic and Atmospheric Administration ‐ Advanced Very High Resolution Radiometer (NOAA‐AVHRR) normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit (CRU) database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S‐W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins.A comparison is made between the FAO‐56 method and the S‐W model when applied to the Mekong River basin for the period 1981–2000. The resulting estimates of RET and PET and their association with vegetation types and LAI are examined over the whole basin both annual and monthly and at five specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S‐W model not only reflects the change in climate but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET, and/or climatic variables, applying these relationships will likely result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of the vegetation. It is concluded that use of the implementation of the S‐W model described in this study results in a physically sound estimate of PET, which accounts for changing land surface conditions. Copyright © 2008 John Wiley & Sons, Ltd.