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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Online Access: | http://www.mdpi.com/1099-4300/16/3/1287 |
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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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1725536281164775424 |