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Summary: The paper looks at the pivotal role that the Monin–Obukhov length (L) can play within the sensible heat balance method for calculating evapotranspiration from remotely sensed multispectral data. It focuses on the possibility of using L as a cornerstone parameter for calculations of sensible heat flux from the pixel data. The paper shows that L can be separated from the other unknowns and can be found either by means of any general one-dimensional root finding method, or iteratively, starting with L ≃−∞. A simple algorithm is suggested to reduce the number of iterations. The paper goes on to show that all other output parameters can be calculated directly from the value of L that is established, and an analytical expression for the evaporative fraction found. A novel approach is proposed that allows a close approximation of the evaporative fraction to be derived directly without the need for time-consuming iterations within the main calculation step. Estimates of evapotranspiration from cotton in Southern Kazakhstan showed that the approximation performed well when compared with estimates of ET crop made using an iterative approach. An experimental approach for calculating E 24 is described for use in areas with minimal cloud cover. Comparison of SEBAL estimated Et c with calculated Et 0 for the short season cotton crop in Southern Kazakhstan indicated that for the actively transpiring cotton crop the crop factors were the same as those determined experimentally for low short season cotton in Kansas by Hunsaker [Hunsaker, D.J., 1999. Basal crop coefficients and water use for early maturity cotton. Trans. ASAE 42(4), 927–936]. [Copyright &y& Elsevier]

Increasing water scarcity in the downstream areas of several river basins demands improved water management and conservation in the upper reaches. Improved management is impossible without proper monitoring at various levels. In the Aral Sea Basin, monitoring is carried out, albeit largely by under-paid staff however, the water flows to farms and fields remain largely unmeasured due to poor infrastructure and lack of proper measurement facilities. Any conclusions drawn, and therefore the policies devised for water conservation, remain largely ineffective. Contrary to the prevalent human methods of monitoring, the potential for standard monitoring of large areas at field- or farm-level in terms of water depletion and yield, using the Surface Energy Balance Algorithm for Land (SEBAL), and eventually leading to water productivity calculations, is explored here using multi-source public and non-public remote sensing data combinations. The results show reasonable levels of accuracy and indicate areas needing improvements and further investigation and refinement. Farm-level maps of various water depletions and productivities provide a practical view of the performance for the meso-level. Finally, the link between the field, farm, district, and province is briefly addressed in order to provide a methodology using water depletion assessment at smaller level to upscale it to a sub-basin scale. [ABSTRACT FROM AUTHOR]