comparison of m5 model tree and artificial neural network for estimating potential evapotranspiration in semi-arid climates

Authors

nozar ghahreman

mahsa sameti

abstract

evaporation is a fundamental parameter in the hydrological cycle. this study examines the performance of m5model tree and artificial neural network (ann) models in estimating potential evapotranspiration calculated bypenman- monteith and hargreaves- samani equations. daily weather data from two meteorological stations in asemi-arid climate of iran, namely kerman and zahedan, were collected during 1995-2004 and included the mean,maximum and minimum air temperatures, dewpoint, relative humidity, sunshine hours, and wind speed. resultsfor both stations showed that the performance of the m5 model tree was more accurate (r=0.982 and 0.98 forpenman-monteith equation and r=0.983 and 0.98 for hargreaves-samani equation in kerman and zahedan,respectively) than the ann model (r=0.975 and 0.978 for penman-monteith equation and r=0.967 and 0.974 forhargreaves-samani equation in kerman and zahedan, respectively), but the models’ differences wereinsignificant at a confidence level of 95%. it also performed better at the zahedan station using the penman-monteith equation. the most significant variables affecting the potential evapotranspiration in the case of thepenman–monteith equation were found to be mean air temperature, sunshine hours, wind speed, and relativehumidity. similarly, for the hargreaves-samani equation, the maximum and minimum temperatures, sunshinehours, and wind speed were determined to be the most significant variables. further studies in other climates arerecommended for further analysis.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Comparison of M5 Model Tree and Artificial Neural Network for Estimating Potential Evapotranspiration in Semi-arid Climates

Evaporation is a fundamental parameter in the hydrological cycle. This study examines the performance of M5model tree and artificial neural network (ANN) models in estimating potential evapotranspiration calculated byPenman- Monteith and Hargreaves- Samani equations. Daily weather data from two meteorological stations in asemi-arid climate of Iran, namely Kerman and Zahedan, were collected duri...

full text

comparison of regression tree, artificial neural network and hargrives-samani in estimation of reference evapotranspiration in semi region

the purpose of this study was to evaluate three models of artificial neural networks (ann), regression trees (m5) and hargrives-samani (hg) in estimation of reference evapotranspiration. for this purpose was used climate information of sistan va baloochestan, kerman, yazd and khorasan jonoobi from 1998 to 2008. in addition to effect of wind (u) on evapotranspiration (et0), estimation of et0 was...

full text

Groundwater level fluctuation forecasting Using Artificial Neural Network in Arid and Semi-Arid Environment

In arid and semi-arid environments, groundwater plays a significant role in the ecosystem. In the last decades, groundwater levels have decreased due to the increasing demand for water, weak irrigation management and soil damage. For the effective management of groundwater, it is important to model and predict fluctuations in groundwater levels. In this study, groundwater table in Kashan plain ...

full text

Comparison of Artificial Neural Network and Physically Based Models for Estimating of Reference Evapotranspiration in Greenhouse

Evapotranspiration (ET) is one of the major components of hydrologic cycle. Accurate estimation of this parameter is essential for studies such as water balance, irrigation system design and management, and water resources management. Generally we used climate data for calculating evapotranspiration from indirect methods. This study investigates the utility of artificial neural networks (ANNs) ...

full text

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

My Resources

Save resource for easier access later


Journal title:
desert

Publisher: international desert research center (idrc), university of tehran

ISSN 2008-0875

volume 19

issue 1 2014

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023