Evaluation of the Penman-Monteith and other 34 reference evapotranspiration equations under limited data in a semiarid dry climate

Djaman, Koffi; O’Neill, M. K.; Diop, Lamine; Bodian, Ansoumana; Allen, Suzanne; Koudahe, Komlan; Lombard, Kevin

doi:10.1007/s00704-018-2624-0

Cited by 59 publications

(36 citation statements)

References 57 publications

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“…On their side, Samaras et al (2014) evaluated 18 potential evapotranspiration equations under different Mediterranean climates in Greece. In United States, Lu et al (2005) compared six potential evapotranspiration methods under the southeastern United States climate while Djaman et al (2019) evaluated Penman–Monteith and 34 other reference evapotranspiration methods under semi-arid dry climate of New Mexico. In china, Yang et al (2016) evaluated eight evapotranspiration models under semi-arid and semi-humid areas.…”

Section: Introductionmentioning

confidence: 99%

“…The spatiotemporal availability and the representativeness of the required data is also a fundamental determinant of the choice of the estimate. Consequently, the use of simple empirical ones requiring fewer data is highly recommended, especially when there is a lack of data, as in the MENA region ( Djaman et al, 2015 , 2019 ; Er-Raki et al, 2010 ; Hadria et al, 2018 ; Mahmoud and Gan, 2019 ; Ning et al, 2018 ; Trajkovic and Kolakovic, 2009a ).…”

Section: Introductionmentioning

confidence: 99%

“…In general, there are three classes of estimates: (i) air temperature-based, (ii) radiation-based, and (iii) mass transfer based. After its local calibration, the first class provides good approximations of ET 0 and has the advantage of being widely studied ( Bicalho et al, 2016 ; Djaman et al, 2015 , 2019 ; Trajkovic, 2007 ). Often, these estimates are applied in areas where the climatic and agronomic conditions are very different from the humid or even Nordic settings in which they were developed and tested.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparative assessment of different reference evapotranspiration models towards a fit calibration for arid and semi-arid areas

Hadria¹,

Benabdelouhab²,

Lionboui³

et al. 2021

Journal of Arid Environments

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The enhancement of water efficiency requires controlling the high demand for irrigated agriculture which depends on improving the capabilities to accurately simulate the water cycle and its components. Among these, evapotranspiration is widely studied to estimate reference evapotranspiration (ET 0 ) but the performance and accuracy of the estimates vary. Moreover, these estimates require some hardly available or misrepresentative meteorological data which lead, mainly in arid and semi-arid areas, to errors and inaccuracies. Here, ET 0 of five empirical temperature-based estimates are compared to the standard FAO Penman–Monteith estimate (ET 0-PM ) under the representative and wide-ranging settings of 22 weather stations of Morocco. We found a significant positive correlation between ET 0-PM and solar radiation, average and maximum air temperatures. We have determined that the Dorji estimate shows relatively better precision and stability while it requires advanced calibration to accommodate arid and semi-arid conditions. After hundreds of calibration repetitions, we concluded a new estimate (ET 0-Hadria ) which demonstrates an overall improvement in the quality and precision of ET 0 assessment, mainly in flat areas. This estimate improved the precision and enhanced the precision in almost 68% of the stations. This simple calibrated estimate is an accurate, improved, and transferable tool achieved through a precise methodical process of selection and configuration.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparative assessment of different reference evapotranspiration models towards a fit calibration for arid and semi-arid areas

Hadria¹,

Benabdelouhab²,

Lionboui³

et al. 2021

Journal of Arid Environments

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“…Where: is observed data, is the predicted data by empirical model, is the mean of observed measured data, n is the total number of observed data points. Low values of MBE, MAE and MPE are indications of good model performance [DJAMAN et al 2018;MORIASI et al 2007;NDULUE et al 2018].…”

Section: Discussionmentioning

confidence: 99%

“…Solar radiation (Rs) is an important parameter in computing ETo together with other meteorological parameters like wind speed, temperature and relative humidity. Studies have shown strong correlation between solar radiation and ETo [DJAMAN et al 2018;KOSA 2011;KOUDAHE et al 2018;MARTEL et al 2018]. This shows that solar radiation is a dominant factor controlling the evapotranspiration process in these regions.…”

mentioning

confidence: 92%

Performance evaluation of solar radiation equations for estimating reference evapotranspiration (ETo) in a humid tropical environment

Ndulue¹,

Onyekwelu²,

Ogbu³

et al. 2019

Journal of Water and Land Development

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Solar radiation (Rs) is an essential input for estimating reference crop evapotranspiration, ETo. An accurate estimate of ETo is the first step involved in determining water demand of field crops. The objective of this study was to assess the accuracy of fifteen empirical solar radiations (Rs) models and determine its effects on ETo estimates for three sites in humid tropical environment (Abakaliki, Nsukka, and Awka). Meteorological data from the archives of NASA (from 1983 to 2005) was used to derive empirical constants (calibration) for the different models at each location while data from 2006 to 2015 was used for validation. The results showed an overall improvement when comparing measured Rs with Rs determined using original constants and Rs using the new constants. After calibration, the Swartman–Ogunlade (R2 = 0.97) and Chen 2 models (RMSE = 0.665 MJ∙m−2∙day−1) performed best while Chen 1 (R2 = 0.66) and Bristow–Campbell models (RMSE = 1.58 MJ∙m−2∙day−1) performed least in estimating Rs in Abakaliki. At the Nsukka station, Swartman–Ogunlade (R2 = 0.96) and Adeala models (RMSE = 0.785 MJ∙m−2∙day−1) performed best while Hargreaves–Samani (R2 = 0.64) and Chen 1 models (RMSE = 1.96 MJ∙m−2∙day−1) performed least in estimating Rs. Chen 2 (R2 = 0.98) and Swartman–Ogunlade models (RMSE = 0.43 MJ∙m−2∙day−1) performed best while Hargreaves–Samani (R2 = 0.68) and Chen 1 models (RMSE = 1.64 MJ∙m−2∙day−1) performed least in estimating Rs in Awka. For estimating ETo, Adeala (R2 =0.98) and Swartman–Ogunlade models (RMSE = 0.064 MJ∙m−2∙day−1) performed best at the Awka station and Swartman–Ogunlade (R2 = 0.98) and Chen 2 models (RMSE = 0.43 MJ∙m−2∙day−1) performed best at Abakaliki while Angstrom–Prescott–Page (R2 = 0.96) and El-Sebaii models (RMSE = 0.0908 mm∙day−1) performed best at the Nsukka station.

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Modelling forest biomass dynamics in relation to climate change in Romania using complex data and machine learning algorithms

Prăvălie

Niculiţă

Roșca

et al. 2023

Stoch Environ Res Risk Assess

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Evaluation of the Penman-Monteith and other 34 reference evapotranspiration equations under limited data in a semiarid dry climate

Cited by 59 publications

References 57 publications

Comparative assessment of different reference evapotranspiration models towards a fit calibration for arid and semi-arid areas

Comparative assessment of different reference evapotranspiration models towards a fit calibration for arid and semi-arid areas

Performance evaluation of solar radiation equations for estimating reference evapotranspiration (ETo) in a humid tropical environment

Modelling forest biomass dynamics in relation to climate change in Romania using complex data and machine learning algorithms

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