Global Analysis of the Role of Terrestrial Water Storage in the Evapotranspiration Estimated from the Budyko Framework at Annual to Monthly Time Scales

• Published in: Journal of hydrometeorology 2019-10, Vol.20 (10), p.2003-2021
• Main Authors: Wu, Chuanhao, Yeh, Pat J.-F., Wu, Haichun, Hu, Bill X., Huang, Guoru
• Format: Article
• Language: English
• Subjects: Analytical errors; Annual; Arid climates; Arid regions; Catchment area; Climate; Climate effects; Climate variability; Error analysis; Errors; Evapotranspiration; Evapotranspiration estimates; Frameworks; Humid climates; Monthly; Parameter estimation; Potential evapotranspiration; Precipitation; Runoff; Seasons; Time; Topography; Variability; Vegetation; Water balance; Water budget; Water resources; Water shortages; Water storage; Water supply
• ISSN: 1525-755X; 1525-7541
• DOI: 10.1175/JHM-D-19-0065.1

Recent studies have extended the applicability of the Budyko framework from the long-term mean to annual or shorter time scales. However, the effects of water storage change ΔS on the overall water balance estimated from the Budyko models (BM) at annual-to-monthly time scales were less investigated, particularly at the continental or global scales, due to the lack of large-scale ΔS data. Here, based on a 25-yr (1984–2008) global gridded terrestrial water budget dataset and by using an analytical error-decomposition framework, we analyzed the effects of ΔS in evapotranspiration (ET) predicted from BM at both grid and basin scales under diverse climates for the annual, wet-seasonal, dry-seasonal, and monthly time scales. Results indicated that the BM underperforms in the short dry (wet) seasons of predominantly humid (dry) basins, with lower accuracy under more humid climates (at annual, dry-seasonal, and monthly scales) and under more arid climates (at wet-seasonal scale). When the effects of ΔS are incorporated into BM, improvements can be found mostly at annual and dry-seasonal scales, but not notable at wet-seasonal and monthly scales. The magnitudes of ΔS are positively correlated with the errors in BM-predicted ET for most global regions at annual and monthly scales, especially under arid climates. Under arid climates, the variability of ET prediction errors is controlled mainly by the ΔS variability at annual and monthly time scales. In contrast, under humid climates the effect of ΔS on ET prediction errors is generally limited, particularly at the wet-seasonal scale due to the more dominant influences of other climatic factors (precipitation and potential ET) and catchment responses (runoff).