Given the widespread ecological implications that would accompany any significant change in evaporative demand of the atmosphere, this study investigated spatial and temporal variation in several accepted expressions of potential evaporation (PE). The study focussed on forest regions of North America, with 1 km-resolution spatial coverage and a monthly time step, from 1951–2014. We considered P...

Prediction of potential evapotranspiration (PET) using an artificial neural network (ANN) with a different architecture is not uncommon. Most researchers select the optimal statistical indicators. However, there still gap to be filled in future applications various drought indices and assessment location, duration, average, maximum minimum. The objective was compare performance PET computed ANN...

abstract potential evapotranspiration is one of basic parameter in hydrologic cycle that should be estimate in irrigation design and scheduling, watershed hydrology studies. many applications in diverse disciplines require estimates of evapotranspiration (et) at hourly or smaller time steps. the primary objectives of this study were to compare the american society of civil engineers (asce) and ...

A simplified equation to estimate spatial reference evapotranspiration (ETo_Ts) from remote sensing-based surface temperature (Ts) and local standard meteorological data is suggested. It is based on a parameterization of the meteorological conditions of the first few meters of the atmosphere through two parameters (a and b) which come from a simpler form of the Penman–Monteith equation:

17 18 The responses of canopy conductance to variation in solar radiation, vapour pressure deficit and soil 19 moisture have been extensively modelled using a Jarvis-Stewart (JS) model. Modelled canopy 20 conductance has then often been used to predict transpiration using the Penman-Monteith (PM) 21 model. We previously suggested an alternative approach in which the JS model is modified to 22

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...