Development of a multi attribute decision making model for selection of automatic measurement systems in irrigation networks

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Water Structure Engineering, Faculty of Agriculture, Tarbiat Modares University, Iran

2 Associate Professor, Water Structure Engineering Department, Faculty of Agriculture, Tarbiat Modares University, Iran

3 Associate Professor, Industrial Engineering Department, Tarbiat Modares University, Iran

Abstract

Application of automatic systems, including discharge measurement technology is one of the effective methods for improving delivery management, water use efficiency, flexibility, and performance of irrigation networks. Several aspects such as hydraulic, technical, physical, environmental, economic, social, and managerial, have significant impact on these systems selection. Due to diversity of the alternatives and numerous affecting factors, suitable selection of automatic discharge measurement technology is a complex task, which makes it necessary to apply multi attributes models. In this paper, TOPSIS method is used for selection of automatic discharge measurement systems. At the first step, different alternatives for automatic discharge measurement and effective attributes on selection of these systems are identified, introduced and categorized. Afterward decision matrix, as the model input, is produced by scoring attributes for all alternatives. The decision making model that used TOPSIS ranking method and Entropy weighting method, is developed in MATLAB software and is run for L1 canal of Qazvin irrigation network. The results show that the discharge- depth and velocity-area automatic systems have higher ranking. In addition pressure and floating water level sensor are better than bubbler and ultrasonic options.

Keywords

References

1-   آذر ع (1380) بسط و توسعۀ روش آنتروپی شانون برای پردازش داده­ها در تحلیل محتوی. علوم انسانی دانشگاه الزهرا (س). سال یازدهم. شمارۀ 37 و 38، بهار و تابستان.
2-     اصغرپور م ج. (1390) تصمیم‌گیری چندمعیاره. چاپ نهم. انتشارات دانشگاه تهران. تهران. 399 صفحه.
3-   خلخالی م.، منعم م ج.، ابراهیمی ک. (1387) تدوین مدل پشتیبانی تصمیم برای ارزیابی و بهبود عملکرد شبکه‌های آبیاری و زهکشی. مجلۀ تحقیقات مهندسی کشاورزی، 9 (1): 125-140.
4-   عنابستانی ع ا.، خسروبیگی ر.، تقیلو ع ا.، شمس­الدینی ر (1390) سطح­بندی پایداری توسعۀ روستایی با استفاده از فن تصمیم­گیری چندمعیارۀ برنامه­ریزی توافقی CP (مطالعۀ موردی: روستاهای شهرستان کمیجان)، مجلۀ جغرافیای انسانی، 3 (2): 108-126.
5-   صادقی ف (1391) توسعۀ مدل ارزیابی سامانه‌های کنترل خودکار در شبکه‌های آبیاری. گروه سازه­های آبی دانشگاه تربیت مدرس. تهران. پایان­نامۀ کارشناسی ارشد.
6-   منعم م ج.، هاشمی شاهدانی م (1390) خوشه‌بندی مکانی شبکه‌های آبیاری با استفاده از روش کلاسیک K-mean، مجلۀ تحقیقات منابع آب ایران، 7(1): 38-46.
7-   منعم م ج.، قدوسی ح (1383) ارزیابی و بهبود عملکرد هشت شبکۀ آبیاری کشور با انجام تحلیل حساسیت در مدل­های تحلیل پوششی داده‌ها (DEA). مجلۀ علوم کشاورزی و منابع طبیعی دانشگاه علوم کشاورزی و منابع طبیعی گرگان. 11 (1): 69-77 .
8-   منعم م ج.، علیرضائی م ر.، صالحی طالشی ا (1381) ارزیابى عملکرد بهره‌بردارى از شبکه‌هاى آبیارى به روش تحلیل پوششى داده‌ها DEA. مجلۀ علوم و فنون کشاورزی و منابع طبیعی دانشگاه صنعتی اصفهان. 6(4): 11-25.
9-   مؤمنی م.، جعفرنژاد ا.، صادقی ش (1390) جایابی بهینۀ مراکز توزیع در فرایند بازاریابی با استفاده از روش‌های ریاضی. مجلۀ مدیریت صنعتی. 3(6): 129-148.
10- هاشمی شاهدانی، س. م. 1387. خوشه­بندی مکانی و زمانی شبکه­های آبیاری با استفاده از روش کلاسیک و فازی(مطالعۀ موردی شبکۀ آبیاری قزوین)، پایان­نامۀ ارشد گروه سازه­های آبی دانشگاه تربیت مدرس.
11-   Alinezhad A, Makui A, Kiani Mavi R and Zohrehbandian M (2011). An MCDM-DEA approach for technology selection. IndustrialEngineeringInternational. 7 (12): 32-38.
12-   Berger P A (2006) Generating Agricultural Landscapes for Alternative Futures Analysis: A Multiple Attribute Decision-Making Model. Transactions in GIS. 10(1): 103–120
13-   Bos M G (1989) Discharge Measurement Structures. 3th Revised Edition. International Institute for Land Reclamation and Improvement.  Netherlands. 401 pages.
14-   Chen S J and Hwang C L (1992) Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag New York, Inc. Secaucus, NJ, USA. ISBN: 0387549986.
15-   Freeman B J (2008) Modernization Criteria Assessment for Water Resources Planning; Klamath Irrigation Project, U.S. Institut für Wasserbau der Universitt Stuttgart. ISBN 3-933761-70-0.
16-   Gomez Limon J A, Berbel J and Arriaza M (2007) MCDM Farm System Analysis for Public Management of Irrigated Agriculture. Handbook Of Operations Research In Natural Resources International Series In Operations Research amp; Mana. Volume 99, pp 93-114.
17-   Kohansal M R and Rafiei Darani H (2009) Choosing and Ranking Irrigation Methods and the Study of Effective Factors of adoption in Khorasan Razavi Province in Iran. Bulgarian Journal of Agricultural Science, 15 (1), 67-76.
18-   Latinopoulos D (2009) Multicriteria Decision Making for Efficient Water and Land Resources Allocation in Irrigated Agriculture. Environment, Development and Sustainability. 11(2): 329-343.
19-   Mozaffari  M  M, Alvandi M and Memarzade M (2012) A Novel MCDM Method for Technology Selection. European Journal of Scientific Research. 71(4): pp. 600-618.
20-   Raju K S and Duckstein L (2004) Integrated Application of Cluster and Multicriterion Analysis for Ranking Water Resources Planning Strategies: a Case Study in Spain. Hydro Informatics. 6: 295-307.
21-   Rezaei P, Rezaie K, Nazari-Shirkouhi S and Jamalizadeh Tajabadi M R (2013) Application of Fuzzy Multi-Criteria Decision Making Analysis for Evaluating and Selecting the Best Location for Construction of Underground Dam. Acta Polytechnica Hungarica. 10 (7): 187-205.
22-   Saraiva J P and Pinheiro A C (2007) A Multi-Criteria Approach for Irrigation Water Management. Agricultural Economics Review. 8(1):64-77.
23-   Shajari M, Bakhshoodeh M and Soltani G R (2008) Suitability of Multiple- Criteria Decision Making Simulations to Study Irrigation Water Demand: A Case Study in the Doroudzan River Basin, Iran. American- Eurasian Journal. Agricultural and Environmental Science. 2 (1): 25-35.
24-   Shen Y  Ch, Lin G T R and Tzeng G H (2011) Combined DEMATEL techniques with novel MCDM for the organic light emitting diode technology selection. Expert Systems with Applications. 38: 1468–1481.
25-   Shirokova Y, Sokolov V and Manthrithilake H (2009) Integrated Water Resources Management: Putting Good Theory into Real Practice: Central Asian Experience. First edition. Scientific and Information Center of the Interstate Commission for Water Coordination (SIC ICWC) and GWP CACENA, Tashkent.381 pages.
26-   International Organization for Standardization (ISO) (1997) Measurement of liquid flow in open channels-General guidelines for selection of method, Technical Report, ISO/TR8363.
27-   Vacino J B, Baldovin M J and Gutierrez C (2005) Multicriteria and Multiperiod Programming for Scenario Analysis in Guadalquivir River Irrigated Farming. XI th Congress of the EAAE (European Association of Agricultural Economists).The Future of Rural Europe in the Global Agri- Food System, Copenhagen, Denmark.
28-   Water Measurement Manual. 3rd edition (1997) Revised reprint (2001)
29-   Yelmaz B and Yurdusev M A (2011) Use of Data Envelopment Analysis as a Multi Criteria Decision Tool – A Case of Irrigation Management. Mathematical and Computational Applications. 16(3): 669-679.
Water and Irrigation Management
Volume 4, Issue 2 - Serial Number 2
October 2015
Pages 177-190

Files

Share

How to cite

Statistics