Entropy: From Thermodynamics to Hydrology

Some known results from statistical thermophysics as well as from hydrology are revisited from a different perspective trying: (a) to unify the notion of entropy in thermodynamic and statistical/stochastic approaches of complex hydrological systems and (b) to show the power of entropy and the princi...

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Main Author: Demetris Koutsoyiannis
Format: Article
Language:English
Published: MDPI AG 2014-02-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/16/3/1287
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spelling doaj-3c3f10c588ee4d5b96adc3389b9e61322020-11-24T23:31:42ZengMDPI AGEntropy1099-43002014-02-011631287131410.3390/e16031287e16031287Entropy: From Thermodynamics to HydrologyDemetris Koutsoyiannis0Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, 157 80 Zographou, GreeceSome known results from statistical thermophysics as well as from hydrology are revisited from a different perspective trying: (a) to unify the notion of entropy in thermodynamic and statistical/stochastic approaches of complex hydrological systems and (b) to show the power of entropy and the principle of maximum entropy in inference, both deductive and inductive. The capability for deductive reasoning is illustrated by deriving the law of phase change transition of water (Clausius-Clapeyron) from scratch by maximizing entropy in a formal probabilistic frame. However, such deductive reasoning cannot work in more complex hydrological systems with diverse elements, yet the entropy maximization framework can help in inductive inference, necessarily based on data. Several examples of this type are provided in an attempt to link statistical thermophysics with hydrology with a unifying view of entropy.http://www.mdpi.com/1099-4300/16/3/1287entropyprinciple of maximum entropystatistical thermophysicshydrologystochastics
collection DOAJ
language English
format Article
sources DOAJ
author Demetris Koutsoyiannis
spellingShingle Demetris Koutsoyiannis
Entropy: From Thermodynamics to Hydrology
Entropy
entropy
principle of maximum entropy
statistical thermophysics
hydrology
stochastics
author_facet Demetris Koutsoyiannis
author_sort Demetris Koutsoyiannis
title Entropy: From Thermodynamics to Hydrology
title_short Entropy: From Thermodynamics to Hydrology
title_full Entropy: From Thermodynamics to Hydrology
title_fullStr Entropy: From Thermodynamics to Hydrology
title_full_unstemmed Entropy: From Thermodynamics to Hydrology
title_sort entropy: from thermodynamics to hydrology
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2014-02-01
description Some known results from statistical thermophysics as well as from hydrology are revisited from a different perspective trying: (a) to unify the notion of entropy in thermodynamic and statistical/stochastic approaches of complex hydrological systems and (b) to show the power of entropy and the principle of maximum entropy in inference, both deductive and inductive. The capability for deductive reasoning is illustrated by deriving the law of phase change transition of water (Clausius-Clapeyron) from scratch by maximizing entropy in a formal probabilistic frame. However, such deductive reasoning cannot work in more complex hydrological systems with diverse elements, yet the entropy maximization framework can help in inductive inference, necessarily based on data. Several examples of this type are provided in an attempt to link statistical thermophysics with hydrology with a unifying view of entropy.
topic entropy
principle of maximum entropy
statistical thermophysics
hydrology
stochastics
url http://www.mdpi.com/1099-4300/16/3/1287
work_keys_str_mv AT demetriskoutsoyiannis entropyfromthermodynamicstohydrology
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