Performance assessment of evapotranspiration estimated from different data sources over agricultural landscape in Northern India

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F20%3A82187" target="_blank" >RIV/60460709:41330/20:82187 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007%2Fs00704-019-03076-4" target="_blank" >https://link.springer.com/article/10.1007%2Fs00704-019-03076-4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00704-019-03076-4" target="_blank" >10.1007/s00704-019-03076-4</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Performance assessment of evapotranspiration estimated from different data sources over agricultural landscape in Northern India

Popis výsledku v původním jazyce

Accurate estimation of evapotranspiration is generally constrained due to lack of required hydrometeorological datasets. This study addresses the performance analysis of reference evapotranspiration (ETo) estimated from NASA/POWER, National Center for Environmental Prediction (NCEP) global reanalysis data before and after dynamical downscaling through the Weather Research and Forecasting (WRF) model. The state-of-the-art Hamons and Penman-Monteiths methods were utilized for the ETo estimation in the Northern India. The performance indices such as bias, root mean square error (RMSE), and correlation (r) were calculated, which showed the values 0,242, 0,422, and 0,959 for NCEP data (without downscaling) and 0,230, 0,402, and 0,969 for the downscaled data respectively. The results indicated that after WRF downscaling, there was some marginal improvement found in the ETo as compared to the without downscaling datasets. However, a better performance was found in the case of NASA/POWER datasets with bias,

Název v anglickém jazyce

Performance assessment of evapotranspiration estimated from different data sources over agricultural landscape in Northern India

Popis výsledku anglicky

Accurate estimation of evapotranspiration is generally constrained due to lack of required hydrometeorological datasets. This study addresses the performance analysis of reference evapotranspiration (ETo) estimated from NASA/POWER, National Center for Environmental Prediction (NCEP) global reanalysis data before and after dynamical downscaling through the Weather Research and Forecasting (WRF) model. The state-of-the-art Hamons and Penman-Monteiths methods were utilized for the ETo estimation in the Northern India. The performance indices such as bias, root mean square error (RMSE), and correlation (r) were calculated, which showed the values 0,242, 0,422, and 0,959 for NCEP data (without downscaling) and 0,230, 0,402, and 0,969 for the downscaled data respectively. The results indicated that after WRF downscaling, there was some marginal improvement found in the ETo as compared to the without downscaling datasets. However, a better performance was found in the case of NASA/POWER datasets with bias,

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

2020

Kód důvěrnosti údajů

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

Název periodika

Theoretical and Applied Climatology

ISSN

0177-798X

e-ISSN

1434-4483

Svazek periodika

140

Číslo periodika v rámci svazku

1-2

Stát vydavatele periodika

AT - Rakouská republika

Počet stran výsledku

12

Strana od-do

145-156

Kód UT WoS článku

000521505600011

EID výsledku v databázi Scopus

2-s2.0-85077520211