Article

Application of the Fuzzy Logic Model for Prediction of the Monthly Evaporation Rate

Author(s):

Keval Jariwala, GEC Surat; S. I. Waikhom ,GEC Surat; V. G. Yadav ,GEC Surat

Keywords

Fuzzy, Fuzzy Model, Evaporation, Arid Climate

Abstract

Evaporation is the most influencing parameter of the hydrologic cycle and it is a key component playing an important role for development and the management of various water resource projects in arid/semi-arid climatic regions. Fuzzy logic is being used widely as the decision-making tool. In various past studies, Fuzzy Logic has been used to predict the values of various hydrological parameters with much less error. Present study intended to determine the application of Fuzzy Logic to predict the monthly evaporation. A Fuzzy model was developed from the observed data of average monthly maximum temperature, wind speed, relative humidity, and water temperature from Jan-2017 to Jan-2018. The predicted values of evaporation, by Fuzzy model, are compared with the actual field observations to evaluate its performance.

Reference

    [1] Goyal Manish Kumar, Birendra Bharti, Quilty John, Adamowski Jan, Pandey Ashish (2014) Modeling of daily pan evaporation in sub-tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS, Elsevier, Expert Systems with Applications 41 (2014) 5267–5276, http://dx.doi.org/10.1016/j.eswa.2014.02.047 [2] Keskin Erol M, Özlem Terzi and Dilek Taylan, (2004) Fuzzy logic model approaches to daily pan evaporation estimation in western Turkey, Taylor and Francis, Hydrological Sciences Journal, 49:6, -1010, DOI: 10.1623/hysj.49.6.1001.55718 [3] Kulkarni, A. D. and Anaokar, G. S. (2016) Prediction of Evaporation Loss in Reservoir with Fuzzy Logic Approach, European Journal of Advances in Engineering and Technology, 2016, 3(12):39-42, ISSN: 2394 - 658X [4] Patel Jayantilal N and Balve Pranita N. (2016) Evapotranspiration Estimation with Fuzzy Logic, International Journal of Advances in Mechanical and Civil EngineeringVolume-3, Issue-4, Aug.-2016, ISSN: 2394-2827. [5] Moghaddamnia A, M. Ghafari Gousheh, J. Piri, S. Amin, D. Han, (2008) Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques, Elsevier, Advances in Water Resources 32 (2009)88–97, doi: 10.1016/j.advwatres.2008.10.005 Book [6] S. Vedula and P.P. Mujumdar (2007) Water Resource System Modelling techniques and analysis

Other Details

Paper ID: GRDCF012069
Published in: Conference : Emerging Research and Innovations in Civil Engineering
Page(s): 349 - 353

Article Preview

Download   Google Scholar