Preprints
https://doi.org/10.5194/hess-2021-55
https://doi.org/10.5194/hess-2021-55

  29 Mar 2021

29 Mar 2021

Review status: this preprint is currently under review for the journal HESS.

Drivers of drought-induced shifts in the water balance through a Budyko approach

Tessa Maurer1,2, Francesco Avanzi3, Steven D. Glaser2, and Roger C. Bales2,4 Tessa Maurer et al.
  • 1Blue Forest Conservation, Sacramento, CA, USA
  • 2Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720, USA
  • 3CIMA Research Foundation, via Armando Magliotto 2, 17100, Savona, Italy
  • 4Sierra Nevada Research Institute, University of California, Merced, CA, USA

Abstract. An inconsistent statistical relationship between precipitation and runoff has been observed between drought and non-drought periods, with less runoff usually observed during droughts than would be predicted using non-drought relationships. Most studies have examined these shifts using multi-linear regression models, which can identify correlations but are less appropriate for analyzing underlying hydrologic mechanisms. In this analysis, we show how the Budyko framework can be leveraged to quantify the impact of shifts in water allocation during drought using 30 years of data for 14 basins in California. We distinguish ″regime″ shifts, which result from changes in the aridity index along the same Budyko curve, from ″partitioning shifts″, which imply a change in the Budyko parameter ω and thus to the relationship among water-balance components that governs partitioning of available water. Regime shifts are primarily due to measurable climatic changes, making them predictable based on drought conditions. Partitioning shifts are related to nonlinear and indirect catchment feedbacks to drought conditions and are thus harder to predict a priori. We show that regime shifts dominate changes in absolute runoff during droughts, but that gains or losses due to partitioning shifts are still significant. We further discuss how basin characteristics and feedbacks correlate and may influence these shifts, finding that low aridity, high baseflow, a shift from snow to rain, and resilience of high-elevation runoff correlate to an increase in runoff as a fraction of precipitation during droughts. This new application of the Budyko framework can help identify mechanisms influencing catchment response to drought, with implications for water management in arid and drought-prone regions.

Tessa Maurer et al.

Status: open (until 24 May 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-55', Anonymous Referee #1, 07 Apr 2021 reply
    • AC1: 'Reply on RC1', Tessa Maurer, 16 Apr 2021 reply
  • RC2: 'Comment on hess-2021-55', Anonymous Referee #2, 08 Apr 2021 reply
    • AC2: 'Reply on RC2', Tessa Maurer, 16 Apr 2021 reply
  • RC3: 'Comment on hess-2021-55', Ryan Teuling, 05 May 2021 reply

Tessa Maurer et al.

Tessa Maurer et al.

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Short summary
Predicting how much water will end up in rivers is more difficult during droughts because the relationship between precipitation and streamflow can change in unexpected ways. We differentiate between changes that are predictable based on the weather patterns and those that harder to predict because they depend on the land and vegetation of a particular region. This work helps clarify why models are less accurate during droughts and helps predict how much water will be available for human use.