Local and global factors controlling water-energy balances within the Budyko framework

Authors

  • Xianli Xu,

    Corresponding author
    1. Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
    2. Huanjiang Observation and Research Station for Karst Ecosystem, Chinese Academy of Sciences, Huanjiang, China
    • Corresponding author: X. Xu, Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan 410125, China. (xuxianliww@gmail.com)

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  • Wen Liu,

    1. College of Resources and Environmental Sciences, Hunan Normal University, Changsha, China
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  • Bridget R. Scanlon,

    1. Bureau of Economic Geology, Jackson School of Geosciences, University of Texas at Austin, Austin, Texas, USA
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  • Lu Zhang,

    1. Water for a Healthy Country Flagship, CSIRO Land and Water, Canberra, ACT, Australia
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  • Ming Pan

    1. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
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Abstract

[1] 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.

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