Local and global factors controlling water-energy balances within the Budyko framework
Article first published online: 11 DEC 2013
©2013 The Authors. Geophysical Research Letters published by Wiley on behalf of the American Geophysical Union.
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Geophysical Research Letters
Volume 40, Issue 23, pages 6123–6129, 16 December 2013
How to Cite
2013), Local and global factors controlling water-energy balances within the Budyko framework, Geophys. Res. Lett., 40, 6123–6129, doi:10.1002/2013GL058324., , , , and (
- Issue published online: 30 DEC 2013
- Article first published online: 11 DEC 2013
- Accepted manuscript online: 28 NOV 2013 10:32PM EST
- Manuscript Accepted: 19 NOV 2013
- Manuscript Revised: 13 NOV 2013
- Manuscript Received: 14 OCT 2013
- 100 talents program. Grant Numbers: Y323025111, Y251101111
- Western Development Project. Grant Number: KZCX2-XB3-10
- the Key Project of the National Twelfth Five-Year Research Program of China. Grant Number: 2010BAE00739
- water-energy partition;
 Quantifying partitioning of precipitation into evapotranspiration (ET) and runoff is the key to assessing water availability globally. Here we develop a universal model to predict water-energy partitioning (ϖ parameter for the Fu's equation, one form of the Budyko framework) which spans small to large scale basins globally. A neural network (NN) model was developed using a data set of 224 small U.S. basins (100–10,000 km2) and 32 large, global basins (~230,000–600,000 km2) independently and combined based on both local (slope, normalized difference vegetation index) and global (geolocation) factors. The Budyko framework with NN estimated ϖ reproduced observed mean annual ET well for the combined 256 basins. The predicted mean annual ET for ~36,600 global basins is in good agreement (R2 = 0.72) with an independent global satellite-based ET product, inversely validating the NN model. The NN model enhances the capability of the Budyko framework for assessing water availability at global scales using readily available data.