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Regional-Specific Numerical Models of Evapotranspiration Using Gene-Expression Programming Interface in Sahel

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  • Seydou Traore
  • Aytac Guven

Abstract

An accurate and simple Reference Evapotranspiration (ETo) numerical model eases to use for supporting irrigation planning and its effective management is highly desired in Sahelian regions. This paper investigates the performance ability of the Gene-expression Programming (GEP) for modeling ETo using decadal climatic data from a Sahelian country; Burkina Faso. For the study; important data are collected from six synoptic meteorological stations located in different regions; Gaoua, Pô, Boromo, Ouahigouya, Bogandé and Dori. The climatic data combinations are used as inputs to develop the GEP models at regional-specific data basis for estimating ETo. GEP performances are evaluated with the root mean square error (RMSE), and coefficient of correlation (R) between estimated and targeted Penman-Monteith FAO56 set as the true reference values. Obviously; from the statistical viewpoint; GEP computing technique has showed a good ability for providing numerical models on a regional data basis. The performances of GEP based on temperatures data are quite good able to substitute empirical equations at regional level to some extent. It is found that the models with wind velocity yield high accuracies by causing radical improve of the performances with R 2 (0.925-0.961) and RMSE (0.131-0.272 mm day -1 ); while relative humidity may cause only (R 2 = 0.801-0.933 and RMSE = 0.370-0.578 mm day -1 ). Statistically; GEP is an effectual modeling tool for computing successfully evapotranspiration in Sahel. Copyright Springer Science+Business Media Dordrecht 2012

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  • Seydou Traore & Aytac Guven, 2012. "Regional-Specific Numerical Models of Evapotranspiration Using Gene-Expression Programming Interface in Sahel," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(15), pages 4367-4380, December.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:15:p:4367-4380
    DOI: 10.1007/s11269-012-0149-3
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    References listed on IDEAS

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    1. Lopez-Urrea, R. & Olalla, F. Martin de Santa & Fabeiro, C. & Moratalla, A., 2006. "An evaluation of two hourly reference evapotranspiration equations for semiarid conditions," Agricultural Water Management, Elsevier, vol. 86(3), pages 277-282, December.
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    4. Hazi Azamathulla & Aminuddin Ghani & Cheng Leow & Chun Chang & Nor Zakaria, 2011. "Gene-Expression Programming for the Development of a Stage-Discharge Curve of the Pahang River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(11), pages 2901-2916, September.
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    3. K. Durga Rao & Vala Rao & Vinay Dadhwal, 2014. "Improvement to the Thornthwaite Method to Study the Runoff at a Basin Scale Using Temporal Remote Sensing Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1567-1578, April.
    4. Jinping Zhang & Yong Zhao & Zhihong Ding, 2014. "Research on the Relationships Between Rainfall and Meteorological Yield in Irrigation District," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1689-1702, April.
    5. Sajjad Abdollahi & Jalil Raeisi & Mohammadreza Khalilianpour & Farshad Ahmadi & Ozgur Kisi, 2017. "Daily Mean Streamflow Prediction in Perennial and Non-Perennial Rivers Using Four Data Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4855-4874, December.
    6. Kima, Aimé Sévérin & Traore, Seydou & Wang, Yu-Min & Chung, Wen-Guey, 2014. "Multi-genes programing and local scale regression for analyzing rice yield response to climate factors using observed and downscaled data in Sahel," Agricultural Water Management, Elsevier, vol. 146(C), pages 149-162.
    7. Hatice Citakoglu & Murat Cobaner & Tefaruk Haktanir & Ozgur Kisi, 2014. "Estimation of Monthly Mean Reference Evapotranspiration in Turkey," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 99-113, January.
    8. Ali Sabziparvar & Roya Mousavi & Safar Marofi & Niaz Ebrahimipak & Majid Heidari, 2013. "An Improved Estimation of the Angstrom–Prescott Radiation Coefficients for the FAO56 Penman–Monteith Evapotranspiration Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2839-2854, June.
    9. H. Azamathulla & Robert Jarrett, 2013. "Use of Gene-Expression Programming to Estimate Manning’s Roughness Coefficient for High Gradient Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 715-729, February.
    10. Traore, Seydou & Zhang, Lei & Guven, Aytac & Fipps, Guy, 2020. "Rice yield response forecasting tool (YIELDCAST) for supporting climate change adaptation decision in Sahel," Agricultural Water Management, Elsevier, vol. 239(C).
    11. Tabasum Rasool & A. Q. Dar & M. A. Wani, 2021. "Development of a Predictive Equation for Modelling the Infiltration Process Using Gene Expression Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1871-1888, April.

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