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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/hess-2017-441
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2017-441
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  25 Aug 2017

25 Aug 2017

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This discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

Modeling water balance using the Budyko framework over variable timescales under diverse climates

Chuanhao Wu1, Pat J.-F. Yeh2, Kai Xu1, Bill X. Hu1, Guoru Huang3,4, and Peng Wang1,5 Chuanhao Wu et al.
  • 1Institute of Groundwater and Earth Sciences, Jinan University, Guangzhou 510632, China
  • 2Department of Civil and Environmental Engineering, National University of Singapore, Singapore
  • 3School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
  • 4State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510640, China
  • 5Chongqing Key Laboratory of Karst Environment, Chongqing 400715, China

Abstract. Understanding the effects of climate and catchment characteristics on overall water balance at different temporal scales remains a challenging task due to the large spatial heterogeneity and temporal variability. Based on a long-term (1960–2008) land surface hydrologic dataset over China, this study presented a systematic examination of the applicability of the Budyko model (BM) under various climatic conditions at long-term mean annual, annual, seasonal and monthly temporal scales. The roles of water storage change (WSC, dS/dt) in water balance modeling and the dominant climate control factors on modeling errors of BM are investigated. The results indicate that BM performs well at mean annual scale and the performance in arid climates is better than humid climates. At other smaller timescales, BM is generally accurate in arid climates, but fails to capture dominant controls on water balance in humid climates due to the effects of WSC not included in BM. The accuracy of BM can be ranked from high to low as: dry seasonal, annual, monthly, and wet seasonal timescales. When WSC is incorporated into BM by replacing precipitation (P) with effective precipitation (i.e., P minus WSC), significant improvements are found in arid climates, but to a lesser extent in humid climates. The ratio of the standard deviation of WSC to that of evapotranspiration (E), which increases from arid to humid climates, is found to be the key indicator of the BM simulation errors due to the omission of the effect of WSC. The modeling errors of BM are positively correlated with the temporal variability of WSC and hence larger in humid climates, and also found to be proportional to the ratio of potential evapotranspiration (PET) to E. More sophisticated models than the BM which explicitly incorporate the effect of WSC are required to improve water balance modeling in humid climates particularly at all the annual, seasonal, and monthly timescales.

Chuanhao Wu et al.

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Chuanhao Wu et al.

Chuanhao Wu et al.

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