Regionalization of runoff models derived by genetic programming

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F17%3A73285" target="_blank" >RIV/60460709:41330/17:73285 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.jhydrol.2017.02.018" target="_blank" >http://dx.doi.org/10.1016/j.jhydrol.2017.02.018</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jhydrol.2017.02.018" target="_blank" >10.1016/j.jhydrol.2017.02.018</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Regionalization of runoff models derived by genetic programming

Popis výsledku v původním jazyce

The aim of this study is to assess the potential of hydrological models derived by genetic programming (GP) to estimate runoff at ungauged catchments by regionalization. A set of 176 catchments from the MOPEX (Model Parameter Estimation Experiment) project was used for our analysis. Runoff models for each catchment were derived by genetic programming (hereafter GP models). A comparison of efficiency was made between GP models and three conceptual models (SAC-SMA, BTOPMC, GR4J). The efficiency of the GP models was in general comparable with that of the SAC-SMA and BTOPMC models but slightly lower (up to 10% for calibration and 15% in validation) than for the GR4J model. The relationship between the efficiency of the GP models and catchment descriptors (CDs) was investigated. From 13 available CDs the aridity index and mean catchment elevation explained most of the variation in the efficiency of the GP models. The runoff for each catchment was then estimated considering GP models from single or multip

Název v anglickém jazyce

Regionalization of runoff models derived by genetic programming

Popis výsledku anglicky

The aim of this study is to assess the potential of hydrological models derived by genetic programming (GP) to estimate runoff at ungauged catchments by regionalization. A set of 176 catchments from the MOPEX (Model Parameter Estimation Experiment) project was used for our analysis. Runoff models for each catchment were derived by genetic programming (hereafter GP models). A comparison of efficiency was made between GP models and three conceptual models (SAC-SMA, BTOPMC, GR4J). The efficiency of the GP models was in general comparable with that of the SAC-SMA and BTOPMC models but slightly lower (up to 10% for calibration and 15% in validation) than for the GR4J model. The relationship between the efficiency of the GP models and catchment descriptors (CDs) was investigated. From 13 available CDs the aridity index and mean catchment elevation explained most of the variation in the efficiency of the GP models. The runoff for each catchment was then estimated considering GP models from single or multip

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10501 - Hydrology

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Hydrology

ISSN

0022-1694

e-ISSN

—

Svazek periodika

2017

Číslo periodika v rámci svazku

547

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

544-556

Kód UT WoS článku

000398871100040

EID výsledku v databázi Scopus

2-s2.0-85013840588