Revista Chapingo Serie Ciencias Forestales y del Ambiente
ESTIMATING DAILY NET RADIATION FROM MULTIPLE LINEAR REGRESSION MODELS
ISSNe: 2007-4018   |   ISSN: 2007-3828
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Keywords

Meteorological variables
evapotranspiration
net radiation
subhumid-humid zone

How to Cite

Ocampo, D. ., & Rivas, R. (2013). ESTIMATING DAILY NET RADIATION FROM MULTIPLE LINEAR REGRESSION MODELS. Revista Chapingo Serie Ciencias Forestales Y Del Ambiente, 19(2), 263–271. https://doi.org/10.5154/r.rchscfa.2012.04.031

##article.highlights##

  • Net radiation is the principal variable affecting evapotranspiration
  • Multiple regression is appropriate method for estimating the net radiation
  • Applied regression models introduce the local effects of the analyzed zone

Abstract

Knowledge of daily net radiation (Rn) is basic to quantifying energy used in various processes occurring at the surface level such, as evapotranspiration. This study applies a Multiple Linear Regression Model (MRLM) for the estimation of Rn in a subhumid-humid zone of Argentina. In the model we used weather data of solar radiation, temperature and relative humidity, Rn (measured with a Kipp & Zonen net radiometer) and inverse relative distance earth-sun. As a result, eight estimation equations of Rn were obtained. The MRLM models were evaluated using the statistics Mean Bias Error (MBE) and Root Mean Square Error (RMSE). The results showed good adjustment and low error at daily scale, highlighting those equations involving solar radiation, temperature, relative humidity and inverse distance earth- sun, allowing calculation of Rn with errors less than 19 W∙m-2.

https://doi.org/10.5154/r.rchscfa.2012.04.031
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References

Alados, I., Foyo-Moreno, I., Olmo, F. J., & Alados-Arboledas, L. (2003). Relationship between net radiation and solar radiation for semi-arid shrub-land. Agricultural and Forest Meteorology, 116, 221–227. doi: https://doi.org/10.1016/S0168-1923(03)00038-8

Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and Drainage Paper 56. Rome, Italy: Food and Agriculture Organization of the United Nations. http://www.fao.org/docrep/X0490E/X0490E00.htm

Environmental and Water Resources Institute of the American Society of Civil Engineers (EWRI-ASCE). (2005). The ASCE standardized reference evapotranspiration equation. Report of the task committee on standardization of reference evapotranspiration. Virginia, USA: Autor. http://www.kimberly.uidaho.edu/water/asceewri/ascestzdetmain2005.pdf

Brutsaert, W. (2010). Evaporation into the atmosphere. Theory, history and applications (1a ed.). Dordrecht, Holland: Reidel Publishing Company.

Carmona, F., Rivas, R., Ocampo, D., Schirmbeck, J., & Holzman, M. (2011). Sensores para la medición y validación de variables hidrológicas. Revista Aqua-LAC, 3(1), 26–36. http://www.unesco.org.uy

Fritschen, L. J., & Fritschen, C. L. (2005). Bowen ratio energy balance method. In Hatfield, J. L., & Baker, J. M. (Eds.), Micrometeorology in agricultural systems (pp. 397–405). Madison, USA: American Society of Agronomie.

Irmak, S., Irmak, A., Jones, J. W., Howell, T. A., & Jacobs, J. M. (2003). Predicting daily net radiation using minimum climatological data. Journal of Irrigation and Drainage Engineering, 129(4), 256–269. doi: https://doi.org/10.1061/(ASCE)0733-9437(2003)

Jensen, M. E., Burman, R. D., & Allen. R. G. (1990). Evapotranpiration and irrigation water requeriments. Manual and reports on engineering practices N° 70. New York, USA: American Society of Civil Engineers.

Kjaersgaard, J. H., Cuenca, R. H., Martínez-Cob, A., Gavilán, P., Plauborg, F., Mollerup, M., & Hansen, S. (2009). Comparison of the performance of net radiation calculation models. Theoretical and Applied Climatology, 98(1-2), 57– 66. doi: https://doi.org/10.1007/s00704-008-009-8

Ocampo, D., & Rivas, R. (2011). Evaluación de métodos de estimación de la evapotranspiración a escala mensual y anual en Argentina: Aplicación en zonas húmedas y áridas. Cuadernos del Curiham, 17, 33–41.

Ortega-Farías, S., Antonioletti, R., & Olioso, A. (2000). Net radiation model evaluation at hourly time step for mediterranean conditions. Agronomie, 20, 157–164. doi: https://doi.org/10.1051/agro:2000116

Salinas, M. F., & Silva, C. Z. (2007). Modelos de regresión y correlación II. Regresión lineal múltiple. Ciencia & Trabajo, 23, 39–41. http://www.cienciaytrabajo.cl/pdfs/23/pagina%2039.pdf

Willmott, C. J. (1982). Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63(11), 1309–1369. http://climate.geog.udel.edu

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