Global scale massive feature extraction from monthly hydroclimatic time series Statistical characterizations, spatial patterns and hydrological similarity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F21%3A86949" target="_blank" >RIV/60460709:41330/21:86949 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/abs/pii/S0048969720381432?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0048969720381432?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.scitotenv.2020.144612" target="_blank" >10.1016/j.scitotenv.2020.144612</a>
Alternative languages
Result language
angličtina
Original language name
Global scale massive feature extraction from monthly hydroclimatic time series Statistical characterizations, spatial patterns and hydrological similarity
Original language description
Hydroclimatic time series analysis focuses on a few feature types which describe a small portion of the entire information content of the observations. Aiming to exploit a larger part of the available information and, thus, to deliver more reliable results here we approach hydroclimatic time series analysis differently, by performing massive feature extraction. In this respect, we develop a big data framework for hydroclimatic variable behaviour characterization. This framework relies on approximately 60 diverse features and is completely automatic (in the sense that it does not depend on the hydroclimatic process at hand). We apply the new framework to characterize mean monthly temperature, total monthly precipitation and mean monthly river flow. The applications are conducted at the global scale by exploiting 40 year long time series originating from over 13 000 stations. We extract interpretable knowledge on seasonality, trends, autocorrelation, long range dependence and entropy, and on feature ty
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10501 - Hydrology
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Science of the Total Environment
ISSN
0048-9697
e-ISSN
1879-1026
Volume of the periodical
767
Issue of the periodical within the volume
144612
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
68
Pages from-to
1-68
UT code for WoS article
000617681100051
EID of the result in the Scopus database
2-s2.0-85099361084