Evaluation of six empirical evapotranspiration equations - case study: Campos dos Goytacazes/RJ

Fernandes, Lázaro Costa; Paiva, Célia Maria; Filho, Otto Corrêa Rotunno

doi:10.1590/s0102-77862012000300002

Cited by 34 publications

(17 citation statements)

References 4 publications

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“…The performance of Jensen-Haise equation at Tessalit is in agreement with [55] who reported large discrepancies when using this equation under extremely arid condition like the Saharan arid climate at Tessalit. Similar to the results of this study, the Jensen-Haise equation presented also the highest RMSE of 1.63 mm/day with a relative error over 40% in the State of Rio de Janeiro, Southeast of Brazil [56]. However, [57] reported that the Jensen-Haise equation was the best among 23 ETo methods evaluated under the extremely arid climate conditions in the central Saudi Arabia.…”

Section: Evaluation Of the Selected Eto Equationssupporting

confidence: 84%

Evaluation of Eleven Reference Evapotranspiration Models in Semiarid Conditions

Djaman¹,

Koudahe²,

Akinbile³

et al. 2017

JWARP

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The objectives of this study were to evaluate the performance of the FAO Penman Monteith reference evapotranspiration model under limited data and some mine temperature methods of reference evapotranspiration (ETo) under the semiarid and arid conditions in Mali. The results showed that under limited data conditions, the FAO-PM equation achieved accurate estimation of daily ETo when solar radiation, relative humidity, and wind speed are lacking individually with root mean squared errors (RMSE) averaging 0.52, 0.56 and 0.62 mm/day, respectively. Much more accurate ETo was estimated under relative humidity and wind speed missing data conditions with RMSE varying from 0.20 to 0.58 mm/day and average RE, MBE and MAE of 6.7%, −0.25 mm/day and 0.30 mm/day. The Jensen-Haise equation systematically overestimated ETo while the Hansen, Christiansen, and Irmak, and the two Tabari's equations underestimated ETo at all weather stations. The Abtew equation showed the best performance among the selected ETo equations.

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Section: Evaluation Of the Selected Eto Equationssupporting

confidence: 84%

Evaluation of Eleven Reference Evapotranspiration Models in Semiarid Conditions

Djaman¹,

Koudahe²,

Akinbile³

et al. 2017

JWARP

View full text Add to dashboard Cite

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“…Furthermore, Kalma et al (2008), conducted a review of 30 remote sensing ET modelling results relative to ground based measurements and contended that the ground based measurement methods were not incontrovertibly more reliable than the remote sensing ET modelling methods. Moreover, most of the ground based measurement methods are usually cost intensive thereby constraining measurements over large areas and thus making spatial extrapolation difficult (Moran and Jackson, 1991;Verstraeten et al, 2008;Melesse et al, 2009;Fernandes et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

Abiodun

Guan

Post

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000–2005) and 7-year validation period (2007–2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

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“…It is indicator of the deviation in estimation [1] of ET. The corresponding relative RMSE (rRMSE) is the ratio of RMSE divided by the mean value of ET-PM, which when multiplied by 100% gives the relative error [11]. These values are given in parenthesis next to RMSE values in Tables 4 and 6.…”

Section: Mathematical Methods Of Evaluating the Statistical Parametermentioning

confidence: 99%

“…The use of FAO56-PM equation is the recommended method to estimate potential evapotranspiration of a given location. The equation is physically based [1] and therefore provides consistent ET in many regions and climates without any need to estimate additional parameters [6,11]. But it requires many meteorological variables such as input of temperature, wind speed, relative humidity and radiation that limit its widespread use [19].…”

Section: Introductionmentioning

confidence: 99%

“…In most developing countries, it may not always be possible to find data that spans this much duration for a large number of locations of interest. If data are available for all the variables of PM equation even for limited duration, the ET calculated from the PM equation can be used as a reference for comparison or for calibration purposes [3,11].…”

Section: Introductionmentioning

confidence: 99%

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Three methods of estimating the power of maximum temperature in TM–ET estimation equation

Mengistu

Amente

2019

SN Appl. Sci.

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The use of FAO56-PM is still the preferred method for the estimation of evapotranspiration (ET) regardless of locations. But in places where data that satisfy all the meteorological variables of PM equation are non-existent or missing, the use of either temperature or radiation-based methods is the alternative option, since both radiation and temperature are the main drivers of ET. From the latter two, temperature-based ET estimation methods are still the simplest ones to use. However, there are challenges since some of the parameters used in the temperature-based equations are location dependent. Such location dependence is due to variability in terms of latitude, altitude and other geo-location parameters. Therefore, local calibration of temperature-based methods is necessary to get better estimates of ET. In this study, one temperature-based ET estimation method known as Temesgen-Melesse's (TM) method was assessed in relation to the PM equation using data of ten Class I meteorological stations in Ethiopia. In the study, three different techniques were tested to find location-dependent maximum temperature power ('n') used in TM equation (i.e., to calibrate the method). The first two techniques involve calibration using PM data. In the first case, monthly averaged data that span from 1 to 5 years were used (as five data sets of 12, 24, 36, 48 and 60 months). In the second case, daily values that span from 10 to 30 days were used in three groups of 10-, 20-, and 30-day data sets. In the third technique, an attempt was made to estimate 'n' from the location latitude, altitude and average of the monthly averaged maximum temperature (T̄m x ). The results obtained from each technique are given as follows. Calibration from the monthly averaged data gave good 'n' values for all the stations with R 2 values ranging from 0.80 to 0.92. There were no differences in the number of data points (12,24, 36, 48 and 60 months) used, which means data points of 12 months are sufficient for the calibration. Calibration using the daily data gave satisfactory 'n' results for all the stations tested, though the statistical parameters and performance tests did not give results that are comparable to the monthly averaged values. The results were nearly the same for 10-, 20-, or 20-day data points, which means any one of them can be used for calibration purposes. Estimation of 'n' from latitude, altitude and T̄m x gave results that are comparable to the ones with 'n' calibrated. The percent differences between the 'n' calibrated using data of 131 months and the 'n' values obtained from monthly data and daily data calibrations are less than 0.16% and 0.5%, respectively. The calculated 'n' showed a percent difference of less than 1.1%. Using calculated 'n' is better than performing calibration using daily data. It can also be considered as option when at least 1-year PM data are not available for calibration.

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Evaluation of six empirical evapotranspiration equations - case study: Campos dos Goytacazes/RJ

Cited by 34 publications

References 4 publications

Evaluation of Eleven Reference Evapotranspiration Models in Semiarid Conditions

Evaluation of Eleven Reference Evapotranspiration Models in Semiarid Conditions

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

Three methods of estimating the power of maximum temperature in TM–ET estimation equation

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