Estimation of Potential Evapotranspiration across Sri Lanka Using a Distributed Dual-Source Evapotranspiration Model under Data Scarcity

Abstract

Evapotranspiration estimations are not common in developing countries though most of them have water scarcities for agricultural purposes. erefore, it is essential to estimate the rates of evapotranspiration based on the available climatic parameters. Proper estimations of evapotranspiration are unavailable to Sri Lanka, even though the country has a signi cant agricultural contribution to its economy. erefore, the Shuttleworth–Wallace (S-W) model, a process-based two-source potential evapotranspiration (PET) model, is implemented to simulate the spatiotemporal distribution of PET, evaporation from soil (ETs), and transpiration from vegetation canopy (ETc) across the total landmass of Sri Lanka. e country was divided into a grid with 6km × 6km cells. e meteorological data, including rainfall, temperature, relative humidity, wind speed, net solar radiation, and pan evaporation, for 14 meteorological stations were used in this analysis. ey were interpolated using Inverse Distance Weighting (IDW), Universal kriging, and iessen polygon methods as appropriate so that the generated thematic layers were fairly closer to reality. Normalized Dierence Vegetation Index (NDVI) and soil moisture data were retrieved from publicly available online domains, while the threshold values of vegetation parameters were taken from the literature. Notwithstanding many approximations and uncertainties associated with the input data, the implemented model displayed an adequate ability to capture the spatiotemporal distribution of PET and its components. A comparison between predicted PET and recorded pan evaporations resulted in a root mean square error (RMSE) of 0.75 mm/day. e model showed high sensitivity to Leaf Area Index (LAI). e model revealed that both spatial and temporal distribution of PETis highly correlated with the incoming solar radiation uxes and aected by the rainfall seasons and cultivation patterns. e model predicted PET values accounted for 80–90% and 40–60% loss of annual mean rainfall, respectively, in the drier and wetter parts of the country. e model predicted a 0.65 ratio of annual transpiration to annual evapotranspiration.