干旱区生态环境知识资源中心

This paper develops an algorithm for computing spatially-distributed monthly potential evaporation (PE) over a mountainous region, the Lhasa River basin in China. To develop the algorithm, first, correlation analysis of different meteorological variables was conducted. It was observed that PE is significantly correlated with vapour pressure and temperature differences between the land surface and the atmosphere. Second, the Dalton model, which was developed based on the mass transfer mechanism, was modified by including the influence of the related meteorological variables. Third, the influence of elevation on monthly temperature, vapour pressure and wind velocity was analysed, and functions for extending these meteorological variables to any given altitude were developed. Fourth, the inverse distance weighting method was applied to integrate the extended meteorological variables from five stations adjacent to and within the Lhasa River basin. Finally, using the modified Dalton model and the integrated meteorological variables, we computed the spatially-distributed monthly PE. This study indicated that spatially-distributed PE can be obtained using data from sparse meteorological stations, even if only one station is available; the results show that in the Lhasa River basin PE decreases when elevation increases. The new algorithm, including the modified model and the method for spatially extending meteorological variables can provide the basic inputs for distributed hydrological models.