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Reseach Article

Fuzzy based Decision Support Model for Irrigation System Management

by Amthal K. Mousa, Muayad S. Croock, Mohammed N. Abdullah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 9
Year of Publication: 2014
Authors: Amthal K. Mousa, Muayad S. Croock, Mohammed N. Abdullah
10.5120/18230-9177

Amthal K. Mousa, Muayad S. Croock, Mohammed N. Abdullah . Fuzzy based Decision Support Model for Irrigation System Management. International Journal of Computer Applications. 104, 9 ( October 2014), 14-20. DOI=10.5120/18230-9177

@article{ 10.5120/18230-9177,
author = { Amthal K. Mousa, Muayad S. Croock, Mohammed N. Abdullah },
title = { Fuzzy based Decision Support Model for Irrigation System Management },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 9 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 14-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number9/18230-9177/ },
doi = { 10.5120/18230-9177 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:35:42.661139+05:30
%A Amthal K. Mousa
%A Muayad S. Croock
%A Mohammed N. Abdullah
%T Fuzzy based Decision Support Model for Irrigation System Management
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 9
%P 14-20
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an efficient irrigation system is proposed based on computing evapotranspiration (ET) and the required irrigation quantity using fuzzy inference methodology. The aim of this system is to schedule irrigation according to the particular requirements of a crop and to the change in various climatological parameters and other factors. This is to avoid over- or under-watering which significantly affects the crop quality and yields using the proposed algorithm. Moreover, our algorithm reduces the power switching, hence it conserves energy. The results demonstrate that the fuzzy model is a quick and accurate tool for calculating evapotranspiration as well as the required net irrigation. Besides, no water stress occurs because our model prohibits depletion in soil moisture from reaching 100% which represents permanent wilting point. Since, irrigation always starts when depletion ratio reaches 50% of total available soil moisture. Additionally, we introduce a general algorithm as a part of the proposed system to calculate the irrigation time, which well suits both micro-irrigation methods: sprinkler and drip irrigation.

References
  1. Allen, R. G. , Pereira, L. S. , Raes, D. , Smith, M. , 1998. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO, Rome, p. 300 (Irrigation and Drainage Paper, 56).
  2. S. Muhammad Umair, R. Usman, 2010. Automation of Irrigation System Using ANN based Controller, International Journal of Electrical & Computer Sciences IJECS-IJENS Vol:10 No:02
  3. Xinrong Zhang?Bo Chang, 2012. Design of Water-saving Irrigation Monitoring System Based on CC2430 and Fuzzy-PID. Journal of Control Engineering and Technology (JCET), Vol. 2 Iss. 3, P. 124-129
  4. Xiaohong Peng, Guodong Liu, 2012. Intelligent Water-saving Irrigation System Based on Fuzzy Control and Wireless Sensor Network. Fourth International Conference on Digital Home
  5. Peng Xiaohong, Mo Zhi, Xiao Laisheng, Liu Guodong, 2009. A Water-saving Irrigation System Based on Fuzzy Control Technology and Wireless Sensor Network, IEEE
  6. Zheng Yao and Guohuan Lou, XiuLi Zeng and Qingxin Zhao, 2010. Research and Development Precision irrigation control system in agricultural, International Conference on Computer and Communication Technologies in Agriculture Engineering IEEE
  7. Xinrong Zhang?Bo Chang, 2012. Design of Water-saving Irrigation Monitoring System Based on CC2430 and Fuzzy-PID, Journal of Control Engineering and Technology (JCET) Vol. 2 Iss. 3 P. 124-129
  8. Nourani, V. ; Mogaddam, A. A. ; Nadiri, A. O. , (2008a). An ANNbased model for spatiotempral groundwater level forecasting. Hydrol. Process, 22 (26), 5054-5066 (13 pages).
  9. T. Rajaee; S. A. Mirbagheri; V. Nourani; A. Alikhani, 2010. Prediction of daily suspended sediment load using wavelet and neurofuzzy combined model. Int. J. Environ. Sci. Tech, 7 (1), 93-110 (7 pages).
  10. Ketema Tilahun Zeleke and Leonard John Wade. Evapotranspiration Estimation Using Soil Water Balance, Weather and Crop Data. www. intechopen. com.
  11. Fuzzy Logic Toolbox™, User's Guide, 2014, www. mathworks. com.
  12. Shaohua Wan, 2012. Research on the Model for Crop Water Requirements in Wireless Sensor Networks. International Conference on Management of e-Commerce and e-Government, IEEE.
  13. Iraqi Agribusiness Program, Irrigation Guidelines. 2012, www. inma-iraq. com.
Index Terms

Computer Science
Information Sciences

Keywords

Deficit irrigation evapotranspiration FIS fuzzy Matlab.