Preprints
https://doi.org/10.5194/egusphere-2025-6241
https://doi.org/10.5194/egusphere-2025-6241
05 Feb 2026
 | 05 Feb 2026
Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

Characterising runoff processes for Australia: Insights from a parsimonious rainfall-runoff event identification method

Mohammad Masoud Mohammadpour Khoie, Danlu Guo, and Conrad Wasko

Abstract. Rainfall-runoff events are widely used in hydrological applications, from flood estimation and flood forecasting, to understanding catchment responses in a climate/anthropogenic affected world. The majority of methods used to identify rainfall-runoff events are statistical in nature, relying on subjective, user-defined ‘rules’ (i.e., parameters) that define a rainfall-runoff event. Since no ground-truth information is available to confirm the exact beginning and end of rainfall-runoff events, there is noticeable inconsistency (i.e. uncertainty) within the results. In this study, we propose the Robust Variance-based Event Identification Method (RVEIM), a new parsimonious rainfall-runoff event identification method which uses fewer parameters and better mimics the natural runoff generation process; decreasing the uncertainty in rainfall-runoff event identification. RVEIM detects runoff events by focusing on changes of streamflow variance and pairs to the corresponding rainfall event(s) simultaneously. RVEIM was compared to a benchmarking event identification method in 8 representative catchments in Australia. A sensitivity analysis was performed using a comprehensive set of plausible event identification parameter values for both methods. Results revealed that the variation of rainfall-runoff events characteristics – including annual number, length of runoff events, and the mean volume of runoff events – showed limited uncertainty from the RVEIM (standard deviation within ±15 % of the mean across 8 representative Australian catchments). This demonstrates robustness of RVEIM, while the benchmarking method exhibited considerably greater uncertainty in the event characteristics, with coefficients of variation exceeding 23 % and more than an order of magnitude difference across catchments. Using RVEIM, we present the first comprehensive summary of rainfall-runoff event characteristics across 467 Australian catchments. The distribution of event-scale runoff coefficients for individual catchments shows a strong climate gradient. Such systematic shifts in the distribution of runoff coefficient across climate regions indicate that climate variables play an important role in catchment response and point to potential contrasts in dominating runoff generation mechanisms across climate zones.

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Mohammad Masoud Mohammadpour Khoie, Danlu Guo, and Conrad Wasko

Status: open (until 19 Mar 2026)

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Mohammad Masoud Mohammadpour Khoie, Danlu Guo, and Conrad Wasko
Mohammad Masoud Mohammadpour Khoie, Danlu Guo, and Conrad Wasko

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Short summary
We developed a new method to identify rainfall-runoff events which is less uncertain and more reliable. The Robust Variance-based Event Identification Method (RVEIM) uses fewer parameters and better represents natural runoff processes. RVEIM  is easily transferable across various climates and enhances hydrologic modeling, flood forecasting, and disaster resilience.
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