2011Plant Soil and EnvironmentOpen access

Evaluation of evapotranspiration models for estimating daily reference evapotranspiration in arid and semiarid environments

Osama Mohawesh

Open full text 44 citations

Abstract

Daily outputs from eight evapotranspiration models were tested against reference evapotranspiration (ETo) data computed by FAO56PM to assess the accuracy of each model in estimating ETo. Models were compared at eight stations across Jordan. Results show that Hargreaves modified models were the best in light of mean biased error (MBE), root mean square error (RMSE) and mean absolute error (MAE). The MBE, RMSE, and MAE values ranged from -1.47 to 0.81, 3.87 to 1.14 and 0.87 to 3.15 mm/day for HarM1, and from -1.45 to 0.89, 1.08 to 3.91, and 0.85 to 3.16 mm/day for HarM2, respectively, which would make it the best models in light of the MBE, RMSE and MAE ranging from -6.18 to 2.79, 6.90 to 1.08 and 4.74 to 0.85 mm/day for all models and stations. Comparisons were also made using three composite regions: countrywide, semiarid, and arid regions. In conclusion, local calibration is needed for the whole models or the linear regression can be used to calculate the ETo.

Open-access reader

About this research paper

What this paper is about

Daily outputs from eight evapotranspiration models were tested against reference evapotranspiration (ETo) data computed by FAO56PM to assess the accuracy of each model in estimating ETo. Models were compared at eight stations across Jordan. Results show that Hargreaves modified models were the best in light of mean biased error (MBE), root mean square error (RMSE) and mean absolute error (MAE). The MBE, RMSE, and MAE values ranged from -1.47 to 0.81, 3.87 to 1.14 and 0.87 to 3.15 mm/day for HarM1, and from -1.45 to 0.89, 1.08 to 3.91, and 0.85 to 3.16 mm/day for HarM2, respectively, which would make it the best models in light of the MBE, RMSE and MAE ranging from -6.18 to 2.79, 6.90 to 1.08 and 4.74 to 0.85 mm/day for all models and stations. Comparisons were also made using three composite regions: countrywide, semiarid, and arid regions. In conclusion, local calibration is needed for the whole models or the linear regression can be used to calculate the ETo.

Why it matters

OpenAlex reports 44 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Daily outputs from eight evapotranspiration models were tested against reference evapotranspiration (ETo) data computed by FAO56PM to assess the accuracy of each model in estimating ETo. Models were compared at eight stations across Jordan. Results show that Hargreaves modified models were the best in light of mean biased error (MBE), root mean square error (RMSE) and mean absolute error (MAE). The MBE, RMSE, and MAE values ranged from -1.47 to 0.81, 3.87 to 1.14 and 0.87 to 3.15 mm/day for HarM1, and from -1.45 to 0.89, 1.08 to 3.91, and 0.85 to 3.16 mm/day for HarM2, respectively, which would make it the best models in light of the MBE, RMSE and MAE ranging from -6.18 to 2.79, 6.90 to 1.08 and 4.74 to 0.85 mm/day for all models and stations. Comparisons were also made using three composite regions: countrywide, semiarid, and arid regions. In conclusion, local calibration is needed for the whole models or the linear regression can be used to calculate the ETo.

Key concepts: Evapotranspiration, Mean squared error, Arid, Mean absolute error, Calibration, Mathematics, Linear regression, Environmental science

Related papers

Back to paper searchBrowse research topicsOriginal source
Evaluation of evapotranspiration models for estimating daily reference evapotranspiration in arid and semiarid environments — Research Paper | ScholarLens