Evaluation of Evaporation from Water Reservoirs in Local Conditions at Czech Republic
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020711%3A_____%2F21%3A10154670" target="_blank" >RIV/00020711:_____/21:10154670 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/60460709:41330/21:86991
Výsledek na webu
<a href="https://www.mdpi.com/2306-5338/8/4/153/htm" target="_blank" >https://www.mdpi.com/2306-5338/8/4/153/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/hydrology8040153" target="_blank" >10.3390/hydrology8040153</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Evaluation of Evaporation from Water Reservoirs in Local Conditions at Czech Republic
Popis výsledku v původním jazyce
Evaporation is an important factor in the overall hydrological balance. It is usually derived as the difference between runoff, precipitation and the change in water storage in a catchment. The magnitude of actual evaporation is determined by the quantity of available water and heavily influenced by climatic and meteorological factors. Currently, there are statistical methods such as linear regression, random forest regression or machine learning methods to calculate evaporation. However, in order to derive these relationships, it is necessary to have observations of evaporation from evaporation stations. In the present study, the statistical methods of linear regression and random forest regression were used to calculate evaporation, with part of the models being designed manually and the other part using stepwise regression. Observed data from 24 evaporation stations and ERA5-Land climate reanalysis data were used to create the regression models. The proposed regression formulas were tested on 33 water reservoirs. The results show that manual regression is a more appropriate method for calculating evaporation than stepwise regression, with the caveat that it is more time consuming. The difference between linear and random forest regression is the variance of the data; random forest regression is better able to fit the observed data. On the other hand, the interpretation of the result for linear regression is simpler. The study introduced that the use of reanalyzed data, ERA5-Land products using the random forest regression method is suitable for the calculation of evaporation from water reservoirs in the conditions of the Czech Republic.
Název v anglickém jazyce
Evaluation of Evaporation from Water Reservoirs in Local Conditions at Czech Republic
Popis výsledku anglicky
Evaporation is an important factor in the overall hydrological balance. It is usually derived as the difference between runoff, precipitation and the change in water storage in a catchment. The magnitude of actual evaporation is determined by the quantity of available water and heavily influenced by climatic and meteorological factors. Currently, there are statistical methods such as linear regression, random forest regression or machine learning methods to calculate evaporation. However, in order to derive these relationships, it is necessary to have observations of evaporation from evaporation stations. In the present study, the statistical methods of linear regression and random forest regression were used to calculate evaporation, with part of the models being designed manually and the other part using stepwise regression. Observed data from 24 evaporation stations and ERA5-Land climate reanalysis data were used to create the regression models. The proposed regression formulas were tested on 33 water reservoirs. The results show that manual regression is a more appropriate method for calculating evaporation than stepwise regression, with the caveat that it is more time consuming. The difference between linear and random forest regression is the variance of the data; random forest regression is better able to fit the observed data. On the other hand, the interpretation of the result for linear regression is simpler. The study introduced that the use of reanalyzed data, ERA5-Land products using the random forest regression method is suitable for the calculation of evaporation from water reservoirs in the conditions of the Czech Republic.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Hydrology
ISSN
2306-5338
e-ISSN
—
Svazek periodika
8
Číslo periodika v rámci svazku
4
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
17
Strana od-do
"nestránkovano"
Kód UT WoS článku
000737239300001
EID výsledku v databázi Scopus
—