EFFICIENT METHODS OF AUTOMATIC CALIBRATION FOR RAINFALL-RUNOFF MODELLING IN THE FLOREON+ SYSTEM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10237288" target="_blank" >RIV/61989100:27240/17:10237288 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/17:10237288
Result on the web
<a href="http://nnw.cz/obsahy17.html#27.022" target="_blank" >http://nnw.cz/obsahy17.html#27.022</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2017.27.022" target="_blank" >10.14311/NNW.2017.27.022</a>
Alternative languages
Result language
angličtina
Original language name
EFFICIENT METHODS OF AUTOMATIC CALIBRATION FOR RAINFALL-RUNOFF MODELLING IN THE FLOREON+ SYSTEM
Original language description
Calibration of rainfall-runoff model parameters is an inseparable part of hydrological simulations. To achieve more accurate results of these simulations, it is necessary to implement an efficient calibration method that provides sufficient refinement of the model parameters in a reasonable time frame. In order to perform the calibration repeatedly for large amount of data and provide results of calibrated model simulations for the flood warning process in a short time, the method also has to be automated. In this paper, several local and global optimization methods are tested for their efficiency. The main goal is to identify the most accurate method for the calibration process that provides accurate results in an operational time frame (typically less than 1 hour) to be used in the flood prediction Floreon(+) system. All calibrations were performed on the measured data during the rainfall events in 2010 in the Moravian-Silesian region (Czech Republic) using our in-house rainfall-runoff model.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LM2011033" target="_blank" >LM2011033: The support of the participation in the PRACE initiative and the access of the academic community and the industry of the Czech Republic to HPC resources at the European level</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
—
Volume of the periodical
27
Issue of the periodical within the volume
4
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
23
Pages from-to
391-413
UT code for WoS article
000410411900005
EID of the result in the Scopus database
2-s2.0-85028693698