Hydrozip: how hydrological knowledge can be used to improve compression of hydrological data
type: Item
instance of: scholarly article
title: Hydrozip: how hydrological knowledge can be used to improve compression of hydrological data
zbMATH Open document ID: 1302.86030
author: Steven V. Weijs
author: Nick van de Giesen
author: Marc B. Parlange
published in: Entropy
publication date: 2014-09-19T00:00:00Z
review text: Summary: From algorithmic information theory, which connects the information content of a data set to the shortest computer program that can produce it, it is known that there are strong analogies between compression, knowledge, inference and prediction. The more we know about a data generating process, the better we can predict and compress the data. A model that is inferred from data should ideally be a compact description of those data. In theory, this means that hydrological knowledge could be incorporated into compression algorithms to more efficiently compress hydrological data and to outperform general purpose compression algorithms. In this study, we develop such a hydrological data compressor, named HydroZIP, and test in practice whether it can outperform general purpose compression algorithms on hydrological data from 431 river basins from the Model Parameter Estimation Experiment (MOPEX) data set. HydroZIP compresses using temporal dependencies and parametric distributions. Resulting file sizes are interpreted as measures of information content, complexity and model adequacy. These results are discussed to illustrate points related to learning from data, overfitting and model complexity.
Mathematics Subject Classification ID: 86A32
Mathematics Subject Classification ID: 94A15
Mathematics Subject Classification ID: 62B10
Mathematics Subject Classification ID: 94A40
Mathematics Subject Classification ID: 86-08
zbMATH DE Number: 6346113
zbMATH Keywords: data compression
zbMATH Keywords: algorithmic information theory
zbMATH Keywords: hydrology
zbMATH Keywords: inference
zbMATH Keywords: streamflow
zbMATH Keywords: MOPEX
Wikidata QID: Q61938856
describes a project that uses: HydroZIP
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/e15041289
OpenAlex ID: W2131279443
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DOI: 10.3390/E15041289
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description: scientific article; zbMATH DE number 6346113