Estimation of reference evapotranspiration using multivariate fractional polynomial, Bayesian regression, and robust regression models in three arid environments

By M. Khoshravesh, Mohammad Ali Gholami Sefidkouhi, Mohammad Valipour. Applied Water Science, 2017

80 citations recorded by the source corpus.

The proper evaluation of evapotranspiration is essential in food security investigation, farm management, pollution detection, irrigation scheduling, nutrient flows, carbon balance as well as hydrologic modeling, especially in arid environments. To achieve sustainable development and to ensure water supply, especially in arid environments, irrigation experts need tools to estimate reference evapotranspiration on a large scale. In this study, the monthly reference evapotranspiration was estimated by three different regression models including the multivariate fractional polynomial (MFP), robust regression, and Bayesian regression in Ardestan, Esfahan, and Kashan. The results were compared with Food and Agriculture Organization (FAO)-Penman–Monteith (FAO-PM) to select the best model. The results show that at a monthly scale, all models provided a closer agreement with the calculated values for FAO-PM (R2 > 0.95 and RMSE < 12.07 mm month−1). However, the MFP model gives better estimates than the other two models for estimating reference evapotranspiration at all stations.

Subfields: Global and Planetary Change, Soil Science

View Paper: https://www.semanticscholar.org/paper/f06b17cf5c53bf0820214b3442cb063767335c0d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Guillermo Marcillo
2. Fernando E. Miguez
3. Mohammad Valipour
4. Christian Thiel
5. Gillian Harrison

In Soil Science

1. Guillermo Marcillo
2. Fernando E. Miguez
3. M. Khoshravesh
4. Mohammad Ali Gholami Sefidkouhi

Citations in the corpus

• Corn yield response to winter cover crops: An updated meta-analysis (2017, methodology): “Weighted models, robust to compensate for the unequal variance effect (Khoshravesh et al. 2015), were fitted for N fertilization and WCC termination.”
• How Much Meteorological Information Is Necessary to Achieve Reliable Accuracy for Rainfall Estimations (2016, background): “However, these models are very useful for forecasting changes in hydrological processes considering agricultural water management, evapotranspiration, and water crisis issues [2–17].”