Preprints
https://doi.org/10.5194/egusphere-2023-2875
https://doi.org/10.5194/egusphere-2023-2875
02 Jan 2024
 | 02 Jan 2024

Leveraging a time-series event separation method to untangle time-varying hydrologic controls influence on wildfire disturbed streamflow

Haley A. Canham, Belize A. Lane, Colin B. Phillips, and Brendan P. Murphy

Abstract. Watershed disturbances can have broad, long-lasting impacts that result in a range of streamflow response. Increasing disturbance regimes, particularly from wildfire, is a growing concern for watershed management. The influence of watershed disturbances on rainfall-runoff patterns has proved challenging to isolate from undisturbed streamflow variability due to the role of hydrologic controls that vary through time, including water year type, seasonality, and antecedent precipitation. To better assess the influence of watershed disturbance on rainfall-runoff event patterns we developed the Rainfall-Runoff Event Detection and Identification (RREDI) toolkit. The RREDI toolkit is a novel time-series event separation method that automates the pairing and attribution of precipitation and streamflow events, leveraging and building on existing event separation methods. A rainfall-runoff event dataset of 5042 events was generated by the RREDI toolkit from a collection of nine western US study watersheds spanning a range of streamflow regimes, watershed properties, and burn characteristics. Through analyzing the rainfall-runoff event dataset, we found that water year type and season were significant controls on rainfall-runoff metrics. The significance of antecedent precipitation was variable between watersheds, indicating a more complex relationship for this control. The watershed-specific permutations of significant controls resulted in unique significant condition group trends in the rainfall storm depth and peak runoff relationship in two contrasting watersheds. In general, for each of the significant condition groups post-fire peak runoff was higher than undisturbed peak runoff except during winter in snow-dominated watersheds. Consideration of the time-varying hydrologic controls, particularly water year type and season, were identified as important when untangling the influence of wildfire on the rainfall-runoff patterns. The RREDI toolkit can be further applied to investigate the influence of other watershed disturbances and controls to increase understanding of rainfall-runoff patterns across the landscape.

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Haley A. Canham, Belize A. Lane, Colin B. Phillips, and Brendan P. Murphy

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-2875', Yanchen Zheng, 09 Mar 2024
    • AC3: 'Reply on CC1', Haley Canham, 12 Jun 2024
  • RC1: 'Comment on egusphere-2023-2875', Yanchen Zheng, 11 Mar 2024
    • AC1: 'Reply on RC1', Haley Canham, 12 Jun 2024
  • RC2: 'Comment on egusphere-2023-2875', Anonymous Referee #2, 10 May 2024
    • AC2: 'Reply on RC2', Haley Canham, 12 Jun 2024
Haley A. Canham, Belize A. Lane, Colin B. Phillips, and Brendan P. Murphy

Model code and software

Rainfall-Runoff Event Detection and Identification (RREDI) toolkit Haley A. Canham and Belize A. Lane https://www.hydroshare.org/resource/797fe26dfefb4d658b8f8bc898b320de/

Haley A. Canham, Belize A. Lane, Colin B. Phillips, and Brendan P. Murphy

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Short summary
The influence of watershed disturbances has proved challenging to isolate from natural streamflow variability. This study presents the RREDI toolkit, a novel time-series event separation method, and evaluates the influence of time-varying hydrologic controls relative to wildfire effects on event runoff response. Across watersheds and runoff metrics, water year type and season influenced rainfall-runoff response, and accounting for these controls enabled clearer detection of post-fire effects.