Scrutinizing parameter consistency and predictive uncertainty in rainfall-runoff models using Bayesian total error analysis

Dmitri Kavetski*, Mark Thyer, Benjamin Renard, George Kuczera, Stewart Franks, Sri Srikanthan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The lack of a robust framework for quantifying the uncertainty in the parameters and predictions of conceptual rainfall runoff (CRR) models remains a key challenge for hydrological science. The Bayesian total error analysis (BATEA) provides a systematic approach to hypothesize, infer and evaluate probability models describing input, output and model structural error. This paper compares the ability of BATEA and standard calibration approaches (standard least squares (SLS) and weighted least squares (WLS)) to address two key requirements of uncertainty assessment: (i) reliable quantification of predictive uncertainty and (ii) reliable estimation of parameter uncertainty. The case study was challenging due to the semi-arid climate, ephemeral responses and high rainfall gradients in the catchment. The post-calibration diagnostics suggest that BATEA provided a considerable improvement over SLS/WLS in terms of satisfying the assumed probability models. This was also confirmed using a novel quantile-based diagnostic for assessing whether the total predictive uncertainty is consistent with the observations. Parameter consistency and reliability was evaluated by comparing parameter estimates obtained for the same CRR model with same catchment runoff, but with different rainfall gauges and time periods. BATEA provided more consistent, albeit more uncertain, parameter estimates than SLS/WLS. The implication for CRR parameter regionalization is that the WLS/SLS-derived parameter estimates can be highly dependent on the choice of rainfall data and calibration period, which may obscure the relationship between CRR parameters and catchment attributes. In contrast, BATEA has the potential to remove this obstacle to regionalization.

Original languageEnglish
Title of host publicationWorld Environmental and Water Resources Congress 2008
Subtitle of host publicationAhupua'a - Proceedings of the World Environmental and Water Resources Congress 2008
Volume316
DOIs
Publication statusPublished - 1 Dec 2008
EventWorld Environmental and Water Resources Congress 2008: Ahupua'a - Honolulu, HI, United States
Duration: 12 May 200816 May 2008

Conference

ConferenceWorld Environmental and Water Resources Congress 2008: Ahupua'a
Country/TerritoryUnited States
CityHonolulu, HI
Period12/05/0816/05/08

Keywords

  • Bayesian analysis
  • Errors
  • Parameters
  • Rainfall
  • Runoff
  • Uncertainty principles

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