There is a growing interest in quantifying regional scale actual evapotranspiration (ET) for water accounting and for water productivity assessments at river basin scale.200

The irrigated Indus Basin in Pakistan has insufficient water resources to supply all its stakeholders. Information on evaporative depletion across the Basin is an important requirement if the water resources are to be managed efficiently. This paper presents the Surface Energy Balance Algorithm for Land (SEBAL) method used to compute actual evapotranspiration for large areas based on public domain National Oceanic and Atmospheric Administration (NOAA) satellite data. Computational procedures for retrieving actual evapotranspiration from satellites have been developed over the last 20 years. The current work is among the first applications used to estimate actual evapotranspiration on an annual scale across a vast river basin system with a minimum of ground data. Only sunshine duration and wind speed are required as input data for the remote sensing flux algorithm. The results were validated in the Indus Basin by comparing results from a field‐scale transient moisture flow model, in situ Bowen ratio measurements, and residual water balance analyses for an area of 3 million ha. The accuracy of assessing time‐integrated actual annual evapotranspiration varied from 0% to 10% on a field scale to 5% at the regional level. Spatiotemporal information on actual evapotranspiration helps to evaluate water distribution and water use between large irrigation project areas. Wide variations in evaporative depletion between project areas and crop types were found. Satellite‐based measurements can provide such information and avoid the need to rely on field databases.

Field-based soil moisture measurements are cumbersome. Remote sensing techniques based on active or passive microwave data have limitations. This paper presents and validates a new method based on land surface energy balances using remotely sensed optical data (including thermal infrared), which allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. Root zone depth can be variable when crops are emerging. The pixel-wise “evaporative fraction” (ratio of latent heat flux to net available energy) is related to volumetric soil moisture through a standard regression curve that is independent of soil and vegetation type. Validation with measured root zone soil moisture in cropped soils in Mexico and Pakistan has a root mean square error of 0.05cm3 cm-3; the error is less than 0.07cm3 cm-3 in 90% of cases. Consequently, soil moisture data should be presented in class intervals of 0.05cm3 cm-3. The utility of this method is demonstrated at the field ...