EGU2020-10125
https://doi.org/10.5194/egusphere-egu2020-10125
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

A brisk local uncertainty estimator for hydrologic simulations and predictions (Blue Cat)

Demetris Koutsoyiannis1 and Alberto Montanari2
Demetris Koutsoyiannis and Alberto Montanari
  • 1National Technical University of Athens, Athens, Greece
  • 2University of Bologna, Department DICAM, Bologna, Italy (alberto.montanari@unibo.it)

We propose a brisk method for uncertainty estimation in hydrology which maximizes the probabilistic efficiency of the estimated confidence bands over the whole range of the predicted variables. It is an innovative approach framed within the blueprint we proposed in 2012 for stochastic physically-based modelling of hydrological systems. We present the theoretical foundation which proves that global uncertainty can be estimated with an integrated approach by tallying the empirical joint distribution of predictions and predictands in the calibration phase. We also theoretically prove the capability of the method to correct the bias and to fit heteroscedastic uncertainty for any probability distribution of the modelled variable. The method allows the incorporation of physical understanding of the modelled process along with its sources of uncertainty. We present an application to a toy case to prove the capability of the method to correct the bias and the entire distribution function of the predicting model. We also present a case study of a real world catchment. We prepare open source software to allow reproducibility of the results and replicability to other catchments. We term the new approach with the acronym BLUE CAT: Brisk Local Uncertainty Estimation by Conditioning And Tallying.

How to cite: Koutsoyiannis, D. and Montanari, A.: A brisk local uncertainty estimator for hydrologic simulations and predictions (Blue Cat), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10125, https://doi.org/10.5194/egusphere-egu2020-10125, 2020

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