Impact of uncertainties in meteorological forcing data and land surface parameters on global estimates of terrestrial water balance components
✍ Scribed by O. N. Nasonova; Ye. M. Gusev; Ye. E. Kovalev
- Publisher
- John Wiley and Sons
- Year
- 2011
- Tongue
- English
- Weight
- 616 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0885-6087
- DOI
- 10.1002/hyp.7651
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✦ Synopsis
Abstract
The quality of near‐surface meteorology and land surface parameters strongly influences the simulation of terrestrial water balance components by land surface models. In this article, the sensitivity of global estimates of terrestrial water balance components to uncertainties in meteorological forcing data and land surface parameters is investigated using the SWAP land surface model and different global datasets. The latter were prepared within the framework of the International Satellite Land‐Surface Climatology Project (ISLSCP) Initiative II and the Second Global Soil Wetness Project (GSWP‐2). Sixteen variants of estimations of mean annual water balance components on the global scale were obtained. The discrepancies among the variants were found to be large: global annual run‐off varied by 1·9 times; its surface and sub‐surface components by 2·2 and 1·8 times, respectively; run‐off ratio by 1·5 times and the other hydrological quantities by 1·2–1·3 times. Uncertainties in precipitation datasets translate to uncertainties in run‐off and evapotranspiration depending on the ratio of real evapotranspiration to its potential value E/E~0~. In the areas with high E/E~0~, differences in P across precipitation datasets mainly translated to differences in R. In the areas with the lowest values of E/E~0~, run‐off is nearly insensitive to changes in P, while uncertainty in P mostly translates to uncertainty in E. Uncertainties in E and R due to different radiation datasets are the same in absolute units. Impact of uncertainties in soil parameters on estimations of water balance components can be comparable with the impact of uncertainties in forcing data. Copyright © 2010 John Wiley & Sons, Ltd.