water resources Optimal design of sewage networks for Al-Jaffryah Quarter and Al-Kut Trade Center using genetic algorithms and spectral analysis of the river to know the effect of network waste.

Authors

  • marwa kareem civil engineering department/wasit university
  • Mohammed S. Shamkhi Civil Engineering Department, University of Technology, Baghdad, Iraq

DOI:

https://doi.org/10.31185/ejuow.Vol10.Iss2.307

Keywords:

Optimal design, image classification, supervised classification, ArcGIS

Abstract

The essential objective of this study is the development of an appropriate model to obtain the low cost optimization design of the sewage network. The complexity and the huge number of discrete and non-linear constraints in problems of sewage system design make their treatment important. For this aim, an adaptive model of the Genetic Algorithm (GA) of efficient and effective optimization design with a consistent layout is proposed. The MATLAB code was used to optimize the sewage network for the Al Jafriya neighborhood and Al Kut commercial center. Spectral analysis of the Tigris River was also carried out for the area of the estuaries of the studied network to find out the extent of pollution due to the network being a joint network (rain and sewage). According to the obtained results, the developed model achieved the optimum  solution with the minimum cost and least generations number. It can be also noticed that the estuaries of the studied storm system have a significant influence on the quality of the river water. Thus, this research proposes the implementation and management of an isolated sewage system that is routed to wastewater treatment plants.

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References

Kanu, I., & Achi, O. K. (2011). Industrial effluents and their impact on water quality of receiving rivers in Nigeria. Journal of applied technology in environmental sanitation, 1(1), 75-86.‏

Słyś, D. A. N. I. E. L., & Stec, A. G. N. I. E. S. Z. K. A. (2012). Hydrodynamic modelling of the combined sewage system for the city of Przemyśl. Environment Protection Engineering, 38(4), 99-112.‏

Hassan, W.H., 2019. Application of a genetic algorithm for the optimization of a location and inclination angle of a cut-off wall for anisotropic foundations under hydraulic structures. Geotechnical and Geological Engineering, 37(2), pp.883-895.

Hassan, W.H., 2017. Application of a genetic algorithm for the optimization of a cutoff wall under hydraulic structures. Journal of Applied Water Engineering and Research, 5(1), pp.22-30.

Sivanandam, S. N., & Deepa, S. N. (2008). Genetic algorithms. In Introduction to genetic algorithms (pp. 15-37). Springer, Berlin, Heidelberg.

Hassan, W.H. and Hashim, F.S., 2020. The effect of climate change on the maximum temperature in Southwest Iraq using HadCM3 and CanESM2 modelling. SN Applied Sciences, 2(9), pp.1-11.

Merritt, L.B. and Bogan, R.H., 1973. Computer-based optimal design of sewer systems. Journal of the Environmental Engineering Division, 99(1), pp.35-53.

Froise, S. and Burges, S.J., 1978. Least-cost design of urban-drainage networks. Journal of the Water Resources Planning and Management Division, 104(1), pp.75-92.

Li, G., & Matthew, R. G. (1990). New approach for optimization of urban drainage systems. Journal of Environmental Engineering, 116(5), 927-944.

Pan, T.C. and Kao, J.J., 2009. GA-QP model to optimize sewer system design. Journal of Environmental Engineering, 135(1), pp.17-24.

Rawat J, and Kumar M 2015 Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India The Egyptian Journal of Remote Sensing and Space Science 18(1) 77-84

Hegazy I R, and Kaloop M R 2015 Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt International Journal of Sustainable Built Environment 4(1) 117-124

Long, W., & Srihann, S. (2004, September). Land cover classification of SSC image: unsupervised and supervised classification using ERDAS Imagine. In IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium (Vol. 4, pp. 2707-2712). IEEE.

Al-Kubaisi, Q. Y., Al-khafaji, A., & AL-saadi, Q. M. (2010). Enviromental pollution study of Tigris river within Baghdad city using remote sensing techniques. Iraqi journal of desert studies, 2(2).

Allawai, M. F., & Ahmed, B. A. (2019). Using GIS and Remote Sensing Techniques to Study Water Quality Changes and Spectral Analysis of Tigris River within Mosul City, North of Iraq. Iraqi Journal of Science, 2300-2307.

Holland John, H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.

Atiyah, R. H., & Hassan, W. H. (2021, August). Optimum design of sewer networks with pump station using Genetic Algorithms. In Journal of Physics: Conference Series (Vol. 1973, No. 1, p. 012187). IOP Publishing.‏

Hossen, H., & Negm, A. (2016, April). Performance of water bodies extraction techniques “embedded in ERDAS”: Case Study Manzala Lake, Northeast of Nile Delta, Egypt. In Nineteenth International Water Technology Conference, IWTC19 Sharm ElSheikh (pp. 21-23).

Carrizosa Priego, E. J., & Romero Morales, M. D. (2013). Supervised classification and mathematical optimization. Computers & Operations Research, 40 (1), 150-165.

Jog, S., & Dixit, M. (2016, June). Supervised classification of satellite images. In 2016 Conference on Advances in Signal Processing (CASP) (pp. 93-98). IEEE.

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Published

2022-07-07

How to Cite

kareem, marwa, & Shamkhi, M. S. (2022). water resources Optimal design of sewage networks for Al-Jaffryah Quarter and Al-Kut Trade Center using genetic algorithms and spectral analysis of the river to know the effect of network waste. Wasit Journal of Engineering Sciences, 10(2), 119–130. https://doi.org/10.31185/ejuow.Vol10.Iss2.307