Journal of Water and Wastewater; Ab va Fazilab (in persian)

Journal of Water and Wastewater; Ab va Fazilab (in persian)

Using Artificial Neural Networks to Determine Significant Factors Affecting the Pricing of WPT Effluent for Industrial Uses in Isfahan

Document Type : Research Paper

Authors
Masoud Mirmohamadsaseghi 1
Babak Ebrahimi 2
Minoo Nazifi 3
Shahram Nakhaie 4
1 PhD of Geotechnical Engineering, Executive Manager, Isfahan Rerional Water Co
2 Manager of Planning and Economic analysis office, Isfahan Regional Water Co., Isfahan
3 Director, Budget and Water Planning office, Isfahan Regional Water Co.
4 Head, Division of Grounwater Resources, Isfahan Regional Water Co
10.22093/wwj.2017.39479
Abstract
The evidence indicates increasing trend of use of municipal wastewater treatment effluent as an alternative source of water both in developed and developing countries. Proper pricing of this unconventional water is one of the most effective economic tools to encourage optimum use of fresh water resources. In this study, artificial neural network is employed to identify and assess the factors affecting effluent tariffs supplied to local industries in Isfahan region. Given the wide variety of factors involved in the ultimate value of wastewater traement plant effluent, an assortment of relevant factors  has been considered in this study; the factors include the population served by the treatment plant, volume of effluent produced, maintenance, repair and replacement. costs of operating plants, topography, different water uses in the region, industrial wastewater collection fees, unit cost of pipe and fittings, and the volumes of water supplied from springs and aqueducts  in the region. Neural network modeling is used as a tool to determine the significance of each factor for pricing effluent. Based on the available data and the neural network models, the effects of different model architectures with different intermediate layers and numbers of nodes in each layer on the price of wastewater were investigated to develop aand adopt a final neural network model. Results indicate that the proposed neural network model enjoys a high potential and has been well capable of determining the weights of the parameter affecting in pricing effluent. Based on the the results of this study, the factors with the greatest role in effluent pricing are unit cost of pipe and fittings, industrial use of water, and the costs of plant maintentance, repair and replacement.
Keywords
Neural Networks
WTP Effluent Pricing
Reuse
Isfahan

Subjects

  1. Lassevits, J. F., and Berrua, D. (2001). “Study of phophorus-Propertion of Phosphorus from detergents in continental waters.” Geuplus Pers Comm, 350P.
  2. Edge, D. (1999). “Perspectives for nutrient removal from sewage and implications for sludge strategy.” Environ. Technol., 20, 759-763.
  3. Picton, P. (2002). Neural Networks: Principles and functional, translations doctor Mehdi Ghazanfari and Jamal Orkut, Publisher Iran University of Science and Technology, Tehran.
  4. Nowak, O., Franz, A., Svardal, K., and Müller, V. (1996). “Specific organic and nutrient loads in stabilised sludge from municipal treatment plants.” Water Sci. and Technol., 33, 243-250.
  5. Kashfi, H. (2012). “Private sector investment in wastewater treatment facilities for waste water allocation in the form of buyback contract.” 9th International Management Conference, Tehran, Iran.
  6. Abdolghafoorian, A., Tajrishy, M., and Abrishamchi, A. (2013). “Urban water management and wastewater runoff as new sources of water.” Water and Sanitation, 4, 29-42.
  7. Mohammadnegad, S., and Tajrishy, M. (1997). “Technical and economic evaluation of Tehran's wastwater treatment effluent for landscape irrigation.” Proceedings of the 2nd International Civil Engineering Conference, Sharif University of Technology, Iran.
  8. Salvitabar, A., Zarghami, A. M., and Abrishamchi, A. (2006). “System dynamics model in urban water management in Tehran.” Water and Sanitation, Vol. 17, No. 3 (59), 12-28.
  9. Asefi, H., and Zonoori, A. (2012). “The use of wastewater as renewable freshwater resources.” The First Regional Conference of Civil Engineering, Azad University of Khomeini Shahr, Isfahan, Iran. (In Persian)
  10. Najafi, M. and Bibalani, B. (2011). “Removable water requirement agricultural land resource allocation Tehran from urban waste water treatment plants, recycled water and wastewater.” Second place in the National Seminar on Water Resources Management, the first regional Conference on civil Engineering, Azad University of Khomeinishahr.
  11. Nowak, O. (2000). “Expenditure on the operation of municipal wastewater treatment plants for nutrient removal.” Water Sci. and Technol., 41, 281-289.
  12. Samadi, S., and Nazifi, M. (2014). “Analysis of factors affecting fluctuations in the price of gold using a Markov switching, Journal: Monetary Economics, Finance.” Scientific Research, 26, 121-146.
Journal of Water and Wastewater; Ab va Fazilab (in persian)
Volume 28, Issue 1 - Serial Number 107
March and April 2017
Pages 104-112