Bluecat is a new method that Demetris Koutsoyiannis and myself recently proposed to estimate uncertainty of hydrological predictions. Bluecat comes with an open source and user friendly software to support its application. The original idea was elaborated by Demetris during his stay in Bologna in 2019. Formalisation of the method and software preparation were as all of my working hours from February 2020 to May 2021 were absorbed by the management of the COVID19 emergency in the academia.
Bluecat is a Brisk Local Uncertainty Estimator for Deterministic Simulations and Predictions. In essence, Bluecat is a method to transform a deterministic prediction model into a stochastic prediction model, therefore turning from a point prediction to the probability distribution of the predictand. From the latter distribution, a mean (or median) prediction is obtained along with the confidence bands. Therefore Bluecat performs two tasks:
- It updates the deterministic prediction, therefore providing a new point prediction;
- It provides confidence limits for the prediction for an assigned confidence level.
Therefore, Bluecat is not only an uncertainty assessment method: it is rather a new prediction model with a stochastic structure, and eventually a physical basis that is rooted into the deterministic model. Bluecat can be applied in conjunction with any deterministic prediction model. To provide an example of application, we refer here to rainfall-runoff modeling .
Figure 1. Conceptual scheme of Bluecat (see the Bluecat paper for details).
Bluecat is rooted in the bluprint for process-based modeling of uncertain hydrological systems proposed by Montanari and Koutsoyiannis in 2012. Here, we aim to propose an extension whose distinguishing feature is its intuitive approach that is particularly suited for technical applications.
Bluecat is introduced in a submitted paper that is available online. Click here to download the Bluecat paper.
UPDATE: the paper has been accepted for open access publication on Water Resources Research, the final version is available here.
The following papers describe applications of Bluecat:
Koutsoyiannis, D., & Montanari, A. (2022). Climate Extrapolations in Hydrology: The Expanded Bluecat Methodology. Hydrology, 9(5), 86 (Open access).
- Rozos, E., Koutsoyiannis, D., & Montanari, A. (2022). KNN vs. Bluecat—Machine Learning vs. Classical Statistics. Hydrology, 9(6), 101 (Open access).
Figure 2. Bluecat (source: Hydrology (MDPI)).
We prepared a software package to apply Bluecat in the R environment. The software applies Bluecat in conjunction with the HyMod rainfall-runoff model (Boyle, 2000). Therefore, the software includes a routine to run HyMod and optimise its parameters. Extension to any other prediction model is straightforward. A package to support the user in applying Bluecat to a generic deterministic model is under preparation. The software comes with a detailed help function, along with data sets and detailed instructions to apply Bluecat to reproduce the case studies presented in the Bluecat paper. The software is open source and fully commented. We welcome extensions of the software and modifications. We are looking forward to working with interested researchers and users to extend the software capabilities and usability. Click here to access the software in GitHub.
Click here to download a Powerpoint presentation of Bluecat.
Click here to download a Powerpoint presentation of Bluecat in the Italian language.
My presentation of Bluecat at the EGU22 General Assembly.
Click here to watch a video presentation of Bluecat in YouTube which uses the above Powerpoint presentation as a supporting media (actually the video shows a previous version of the Powerpoint presentation. We apologise for some spelling errors in the video presentation, that were then corrected in the presentation file that is available for download above).
Presentation of Bluecat at the EGU22 General Assembly.
Boyle, D. (2000). Multicriteria calibration of hydrological models (Unpublished doc- toral dissertation). Univ of Arizona, Tucson. Koutsoyiannis, D., and Montanari, A. (2021). Bluecat: A Local Uncertainty Estimator for Deterministic Simulations and Predictions, submitted manuscript. Preprint available online at http://dx.doi.org/10.13140/RG.2.2.23863.65445 (the paper provides an extended list of references). The image of the blue cat is taken from the picture available at https://www.flickr.com/photos/cizauskas/36142084534/ of the Andy Warhol exhibition at the High Museum, Atlanta, Georgia, USA (CC BY-NC-ND 4.0)
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