ORIGINAL_ARTICLE
An integrated mixed-integer linear programming (MILP) model for urban water supply chain optimization
Integrated water resources management is a systematic process for sustainable development, allocation and monitoring of water resources that is used for social, economic and environmental purposes. In this study, a multi-period mixed-integer linear programming (MILP) model for urban water supply network management is proposed. The proposed model considers all echelons of water supply chain from supply centers to wastewater treatment centers. Also, the model optimizes the decisions such as selecting the suitable water supply centers and capacity level optimization. To verify and validate the proposed model a real case study is conducted in Urmia. The model is solved by the General Algebraic Modeling System (GAMS) software and its results have been analyzed. According to the results, the optimal water supply centers, optimal water flow, optimal water inventory, and optimal capacity levels of wastewater treatment centers in different periods are determined. Also, in case of transferring the remaining additional treated water to Urmia lake, its level is increased by about 0.007 cm.
https://arww.razi.ac.ir/article_1602_f23a30b26b53a684c89bb6a99a4e2258.pdf
2020-12-01
102
110
10.22126/arww.2021.5146.1163
Urban water
Water resource management
Water network optimization
Integrated urban water management
Liner programing
Sahar
Hanifeh Dokht
s.hanife63@urmia.ac.ir
1
Department of Industrial Engineering, Faculty of Engineering, Urmia University, Urmia, West Azerbaijan, Iran.
AUTHOR
Maghsud
Solimanpur
m.soliemanpor1@chmail.com
2
Department of Industrial Engineering, Faculty of Engineering, Urmia University, Urmia, West Azerbaijan, Iran.
AUTHOR
Reza
Babazadeh
r.babazadeh@urmia.ac.ir
3
Department of Industrial Engineering, Faculty of Engineering, Urmia University, Urmia, West Azerbaijan, Iran.
LEAD_AUTHOR
Abayan A., Kapelan Z., Savic D., Walters G., Least-cost design of water distribution networks under demand uncertainty, Journal of Water Resources Planning and Management 131 (2005) 375-382.
1
Bach p., Rauch W., Mikkelsen P., Mccarthy Deletic A., A critical review of integrated urban water modeling – Urban drainage and beyond, Environmental Modelling & Software 54 (2014) 88-107.
2
Chung G., Lansey K., Bayraksan G., Reliable water supply system design under uncertainty, Environmental Modelling & Software 24 (2009) 449–462.
3
Darbandsari P., Kerachian R., Malakpour-Estalaki S., An Agent-based behavioral simulation model for residential water demand management: The case-study of Tehran, Iran, Simulation Modelling Practice and Theory 78 (2017) 51–72.
4
Fattahi P., and Fayyaz S., A compromise programming model to integrated urban water management, Water Resourses Management 24 (2010) 1211–1227.
5
Guo P., Huang G.H., Zhu H., Wang X.L., A two-stage programming approach for water resources management under randomness and fuzziness, Environmental Modelling & Software 25 (2010) 1573-1581..
6
Han Y.C., Huang G.H., Li C.H., An Interval-parameter multi-stage stochastic chance-constrained mixed integer-programming model for inter-basin water resources management systems under Uncertainty, Journal of computer and society (2008).
7
Lan F., Lin W., Lansey K., Scenario-based robust optimization of a water supply system under risk of facility failure, Environmental Modelling & Software 67 (2015) 160-172.
8
Lari A.R.and Pishvae M.S., Mathematical optimization model for location-allocation decision in urban water supply chain, Journal of Mathematics and Technology 6 (2015) 181-189.
9
Li Y.P., Huang G.H., Nie S.L., An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty, Advances in Water Resources (2005) 776–789.
10
Naderi M., and Pishvaee M., A stochastic programming approach to integrated water supply and wastewater collection network design problem, Computers and Chemical Engineering 104 (2017) 107–127.
11
Qin X.S., and Xu X.S., Analyzing urban water supply through an acceptability-index-based interval approach, Advances in Water Resources 34 (2011) 873–886.
12
Safavi H., Golmohammadi M., Sandoval-Solis S., Scenario analysis for integrated water resources planning and management under uncertainty in the Zayandehrud River Basin, Journal of Hydrology 539 (2016) 1-48.
13
Wang S., and Huang G.H., An integrated approach for water resources decision making under interactive and compound uncertainties, Omega 44 (2014) 32–40.
14
Zarghami M., Abrishamchi A., Ardakanian R., Multi-criteria decision making for integrated urban water management, Water Resourses Management 22 (2008) 1017–1029.
15
Zhou Yang., Huang Guo H., Yang Boting., Water resources management under multi-parameter interactions: A factorial multi-stage stochastic programming approach, Omega 41 (2013) 559–573.
16
ORIGINAL_ARTICLE
Evaluation of the SINTACS-LU model capability in the analysis of aquifer vulnerability potential in semi-arid regions
Detection of aquifer vulnerable areas can highlight preventive actions for groundwater contamination. Different models have been presented for the evaluation of vulnerability that one of the most regular and well-known models of the overlapping index as the SINTACS-LU (Soggiacence, actual infiltration, non saturated zone, typology of overburden, hydrogeological characteristics of the aquifer, hydraulic conductivity, topographic Slope) model was considered in this research. In fact, this model has been extended based on the impact of land use parameters in the vulnerability evaluation. Purpose of this study is the qualitative evaluation of Birjand plain aquifer vulnerability using the SINTACS-LU model. For this, the Birjand plain aquifer in the statistical periods of 2013-2018 has been evaluated. According to the results of this assessment, the SINTACS-LU vulnerability zoning map reveals that 15 percent of the studied region has the vulnerability of medium to high, 75 percent of the area has a high vulnerability, and 10 percent has the too high vulnerability. In order to the verification of the SINTACS-LU model, the relationship between the vulnerability index and the obtained nitrate concentration values from 21 groundwater samples were assessed. The correlation coefficient between the SINTACS-LU vulnerability index and the nitrate concentration was 75 percent, which indicates the appropriate correlation of this model with the nitrate concentration as the indicator of the groundwater contamination.
https://arww.razi.ac.ir/article_1409_4dae11d6d083314d6abb21747b9bbceb.pdf
2020-12-01
111
119
10.22126/arww.2020.4785.1151
contamination
Ground water
Land Use
Nitrate
SINTACS-LU
Mobin
Eftekhari
mobineftekhari@yahoo.com
1
Water and Hydraulic Structures, Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
LEAD_AUTHOR
Mohammad
Akbari
moakbari@birjand.ac.ir
2
Department of Civil Engineering, Faculty of Engineering, University of Birjand, Birjand,Iran.
AUTHOR
Ahmadi Far R., Mousavi M., Rahimzadegan M., Groundwater pollution risk zoning using GIS (Case study: Sarab Plain), Journal of Soil and Water Conservation Studies 24 (2017) 1-20 (In Persian).
1
Antonakos A.K., and lambrakis N.J., Development and testing of three hybrid methods for the assessment of aquifer vulnerability to nitrates, based on the Drastic model, an example from NE Korinthia, Greece Journal of Hydrology 333 (2007) 288-304.
2
Asghari Moghaddam A., Adigozalpour A., Mohammady A., Vulnerability assessment of oshnavieh plain aquifer by SINTACS and DRASTIC models, Journal of Natural Environmental Hazards 7 (2018) 99-120.
3
Baihaqi M.F., Kusratmoko E., Rustanto A., Comparison of drastic-Lu and Sintacs-Lu models in mapping shallow groundwater vulnerability against pollution in Ci Deres watershed, Sumatra Journal of Disaster, Geography and Geography Education 3 (2019) 137-141.
4
Brahim F.B., Kanfir H., Bouri S., Groundwater vulnerability and risk mapping of the northern sfax aquifer, Tunisia, Arabian Journal for Science and Engineering 37 (2012) 1405-1421.
5
Civita M., Vulnerability maps of aquifers subjected to pollution: theory and practice, Pitagora Editrice, Bologna (1994) 325.
6
Eftekhari M., Madadi K., and Akbari M., Monitoring the fluctuations of the birjand plain aquifer using the GRACE satellite images and the GIS spatial analyses, Watershed Management Researches Journal 32 (2019) 51-65 (In Persian).
7
Ewusi A., Ahenkorah I., Kuma J., Groundwater vulnerability assessment of the tarkwa mining area using SINTACS approach and GIS, Ghana Mining Journal 17 (2017) 18-30.
8
Fadaei Nobandeghani A., The evaluation of the inherent vulnerability potential of Shiraz plain aquifer using Drastic and Composite DRASTIC (CD) and Nitrate Vulnerability (NV) models in the GIS, Master''s Thesis Shiraz University of Medical Sciences (2014) (In Persian).
9
Fatemi A., Long-term assessment of water quality and soil degradation risk via hydrochemical indices of Gharasoo River, Iran, Journal of Applied Research in Water and Wastewater 2 (2015) 131-136.
10
Hassanpour M., and Khozeymehnezhad H., Placement of nutrient wells for artificial nutrition and improvement of aquifer quality in Birjand plain using treated wastewater, Iranian Journal of Research in Environmental Health 4 (2018) 215-226 (In Persian).
11
Huan H., Wang J., Teng Y., Assessment and validation of groundwater vulnerability to nitrate based on a modified DRASTIC model: A case study in Jilin City of northeast China, Science of the Total Environment 440 (2012) 14-23.
12
Keshavarz A., Khashaei A., Najafi M.H., Locating of suitable area of pumping drinking water using FAHP method (Case study: Birjand aquifer, Journal of Water and Wastewater 25 (2015) 91 (In Persian).
13
Kim Y. J., and Hamm S.Y., Assessment of the potential for groundwater contamination using the DRASTIC/EGIS technique, Cheongju area, South Korea, Hydrogeology Journal 17 (1999) 227-235.
14
Lodwick W.A., Monson W., Svoboda L., Attribute error and sensitivity analysis of map operations in geographical informations systems: suitability analysis, International Journal of Geographical Information System 4 (1990) 413-428.
15
Mahmoodzadeh E., Rezaeian S., Ahmadi A., Sensitivity analysis of groundwater vulnerability in the Meymeh plain of Isfahan using the DRASTIC method, The 1st International Conference on Environmental Crisis and its Solutions, Kish Island, Iran, (2013) (In Persian).
16
Mastrocicco M., Gianluigi B., Kazakis N., Colombani N., Voudouris K., and Tedesco D., A modified SINTACS method for groundwater vulnerability and pollution risk assessment in highly anthropized regions based on NO3 and SO4 concentrations, Science of the Total Environment 609 (2017) 1512-1523.
17
Pisciotta A., Cusimano G., Favara R., Groundwater nitrate risk assessment using intrinsic vulnerability methods: A comparative study of environmental impact by intensive farming in the Mediterranean region of Sicily, Italy, Journal of Geochemical Exploration 156 (2015) 89-100.
18
Primastuti D.W., and Kusratmoko E., Spatial pattern of shallow groundwater vulnerability to contamination using SINTACS model in Taman rahayu, Bekasi Regency, AIP Conference Proceedings, (2018).
19
Qadir R., Hamamin D., Saeed S., Groundwater vulnerability map of Sulaymaniyah sub-basin using SINTACS model, Sulaymaniyah Governorate, Kurdistan Region, Iraq, Journal of Zankoy Sulaimani 20 (2016) 277-292.
20
Rahimzadeh kivi M., Hamzeh S., Kardan Moghadam H., Identification of vulnerability potential of groundwater quality in Birjand plain using DRASTIC model and its calibration using AHP, Physical Geography Research 47 (2015) 481-498 (In Persian).
21
Remesan R., and Panda R.K., Groundwater vulnerability assessment, risk mapping, and nitrate evaluationin a small agricultural watershed: using the DRASTIC model and GIS, Journal of Environmental Quality Management 17 (2008) 53-75.
22
Roholamin Kasmaei A., Nezhad Naderi M., Bahrami, Z., Water pollution management in wells of zawar village for investigation of effects of nitrogen fertilizers in nitrate entry into groundwater, Journal of Applied Research in Water and Wastewater 4 (2017) 354-357.
23
Rufino F., Busico G., Cuoco E., Darrah T.H., Tedesco D., Evaluating the suitability of urban groundwater resources for drinking water and irrigation purposes: an integrated approach in the Agro-Aversano area of Southern Italy, Environmental Monitoring and Assessment 191 (2019) 768.
24
Shiekhvanloo M., Assessment of groundwater vulnerability potential of Birjand plain, Dissertation for M.Sc. Degree in Hydrogeology, University of Sistan and Baluchestan, (2007) (In Persian).
25
Tesoriero A.J., Inkpen E.L., Voss F.D., Assessing ground-water vulnerability using logistic regression, Proceedings for the Source Water Assessment and Protection 98 Conference, Dallas, TX (1998) 157– 65.
26
Utami N.D., Sudarmadji M.Eng.S., Setyawan Purnama I.S., Utilization of SINTACS method for assessing water vulnerability to pollution in OPAK HILIR watershed, BANTUL REGENCY, Master Thesis of Geography, Gadjah Mada University, Indonesia; (2019).
27
Wang J., He J., Chen H., Assessment of groundwater contamination risk using hazard quantification, a modified DRASTIC model and groundwater value, Beijing plain, China, Science of the Total Environment 432 (2012) 216-226.
28
WHO, Guidelines for Drinking Water Quality, Geneva, (1996).
29
Yang Y.S., and Wang L., Catchment-scale vulnerability assessment of groundwater pollution from diffuse sources using the DRASTIC method: A case study, Hydrological Sciences Journal–Journal des Sciences Hydrologiques 55 (2010) 1206-1216.
30
ORIGINAL_ARTICLE
Simulation of hydraulic jump length on sloping coarse floors adopting extreme learning machine
In this paper, the hydraulic jump length on a slope rough floor is simulated through the extreme learning machine (ELM). Then, the parameters affecting the hydraulic jump on the slope rough bed are detected. After that, five different ELM model are developed so as to determine the influenced factor. Next, the results obtained from different ELM models are analyzed. The comparison of the results with the experimental data proves the acceptable accuracy of the mentioned numerical models. Regarding the results from the numerical method, the superior ELM model estimates the hydraulic jump length in terms of the flow Froude number, the ratio of bed roughness, the ratio of sequent depths and bed slope. The values of the root mean square error (RMSE), mean absolute percent error (MAPE), scatter index (SI) and correlation coefficient (R) for the superior model are respectively obtained 0.657, 3.507, 0.052 and 0.985. Based on the simulation, the flow Froude number at upstream is introduced as the most effective parameter in predicting the jump length on the sloping rough floor.
https://arww.razi.ac.ir/article_1349_eff46572cbab57c22442ce84af7ad63d.pdf
2020-12-01
120
126
10.22126/arww.2020.4427.1138
Extreme Learning Machine
Hydraulic Jump Length
Rough floor
Sensitivity analysis
Sloping flume
Amir Hosein
Azimi
amir.azimi@gmail.com
1
Department of Water Engineering, faculty of Agriculture, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
AUTHOR
Saeid
Shabanlou
saeid.shabanlou@gmail.com
2
Department of Water Engineering, faculty of Agriculture, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
LEAD_AUTHOR
Behrouz
Yaghoubi
behrouz.yaghoubi.h@gmail.com
3
Department of Water Engineering, faculty of Agriculture, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
AUTHOR
Abbaspour A., Farsadizadeh D., Ghorbani M.A. Estimation of hydraulic jump on corrugated bed using artificial neural networks and genetic programming, Water Science and Engineering 6 (2013) 189–198.
1
Akhbari A., Zaji A.H., Azimi H., Vafaeifard M., Predicting the discharge coefficient of triangular plan form weirs using radian basis function and M5’methods, Journal of Applied Research in Water and Wastewater 4 (2017) 281-289.
2
Azimi H., Bonakdari H., Ebtehaj I., Gene expression programming-based approach for predicting the roller length of a hydraulic jump on a rough bed, ISH Journal of Hydraulic Engineering (2019) 1-11.
3
Azimi H., Bonakdari H., Ebtehaj I., Gharabaghi B., Khoshbin F., Evolutionary design of generalized group method of data handling-type neural network for estimating the hydraulic jump roller length, Acta Mechanica 229 (2018a) 1197-1214.
4
Azimi H., Bonakdari H., Ebtehaj I., Michelson D.G., A combined adaptive neuro-fuzzy inference system–firefly algorithm model for predicting the roller length of a hydraulic jump on a rough channel bed, Neural Computing and Applications 29 (2018) 249-258.
5
Azimi H., Heydari M., Shabanlou S., Numerical simulation of the effects of downstream obstacles on malpasset dam break pattern, Journal of Applied Research in Water and Wastewater 5 (2018a) 441-446.
6
Bhasin V., Bedi P., Singh N., Aggarwal C., FS-EHS: Harmony search based feature selection algorithm for steganalysis using ELM, in innovations in bio-inspired computing and applications, Advances in Intelligent Systems and Computing 424 (2016) 393-402.
7
Carollo F., Ferro V., Pampalone V., Hydraulic Jumps on Rough Beds, Journal Hydraulic Engineering 133 (2007) 989-999.
8
Ead S.A., Effect of bed corrugations on the characteristics of a hydraulic jump, Final Research Report 14/427, King Saud University, College of Engineering, Research Center (2007).
9
Ead S., and Rajaratnam N., Hydraulic jumps on corrugated beds, Journal Hydraulic Engineering 128 (2002) 656-663.
10
Ebtehaj I., and Bonakdari H., A Comparative study of extreme learning machines and support vector machines in prediction of sediment transport in open channels, International Journal of Engineering Transactions B: Applications 29 (2016) 1523-1530.
11
Hager W.H., Bremen R., Kawagoshi N., Classical hydraulic jump: length of roller, Journal of Hydraulic Research 28 (1990) 591-608.
12
Hager W.H., and Wanoschek R., Hydraulic jump in triangular channel, Journal of Hydraulic Research 25 (1987) 549-564.
13
He Y. L., Geng Z.Q., Zhu Q.X., A data-attribute-space-oriented double parallel (DASODP) structure for enhancing extreme learning machine: Applications to regression datasets, Engineering Applications of Artificial Intelligence 41 (2015) 65-74.
14
Huang G-B., Zhu Q-Y., Siew C-K., Extreme learning machine: a new learning scheme of feedforward neural networks, Proceedings of the International Joint Conference on Neural Networks 2 (2004) 985–990.
15
Huang G-B., Zhu Q-Y., Siew C-K., Extreme learning machine: theory and applications, Neurocomputing 70 (2006) 489–501.
16
Izadjoo F., Shafai-Bejestan M., Corrugated bed hydraulic jump stilling basin, Journal of Applied Science 7 (2007) 1164-1169.
17
Kumar M., and Lodhi A.S., Hydraulic jump over sloping rough floors, ISH Journal of Hydraulic Engineering 22 (2016) 127-134.
18
Mohamed Ali H.S., Effect of roughened bed stilling basin on length of rectangular hydraulic jump, Journal of Hydraulic Engineering 117 (1991) 83-93.
19
Omid M.H., Omid M., Esmaeeli V.M., Modelling hydraulic jumps with artificial neural networks, Proceedings of the Institution of Civil Engineers-Water Management 158 (2005) 65–70.
20
Pandey P., and Govind R., Analysis of randomized performance of bias parameters and activation function of extreme learning machine, International Journal of Computer Applications 135 (2016) 23-28.
21
Shen Y., Xu J., Li H., Xiao L., ELM-based spectral-spatial classification of hyperspectral images using bilateral filtering information on spectral band-subsets, In Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (2016) 497-500.
22
ORIGINAL_ARTICLE
Assessment of modern approach of water governance in the development of water exploitation systems in Sistan region
Water is the basis of life, the foundation of nature, and the pillar of social, economic, and cultural development of societies. So, the supply of safe and consumable water has always been a concern. On the other hand, a major challenge of modern societies is the lack of precipitation and frequent droughts. Thus, the present paper assesses the principles of water governance in the Sistan region with respect to the development of water exploitation systems with an environmental approach and presents an integrated multi-attribute decision-making model with a water governance approach in the Sistan region. The simple additive weighting (SAW) method that is used here is one of the multiple attribute decision making (MADM) methods. The indicators of water governance principles were derived from the opinions of 30 water experts, faculty members, and water users in the Sistan region by the SAW method, and weights were assigned to them to form MADM matrices. According to the results, six indicators were derived as the indicators determining the principles of water governance. ‘Traditional users’ was selected as the strongest system and ‘irrigation and drainage networks exploitation companies’ as the weakest system. Also, according to the results of water experts, the first rank was assigned to ‘irrigation and drainage networks exploitation companies’ (A2) with the final crisp score of 6.818 followed by ‘water user cooperatives’ (A4) with the final crisp score of 6.515 in the second rank and ‘private firms’ (A6) with the final crisp score of 6.308 in the third rank.
https://arww.razi.ac.ir/article_1607_f360ecb9fd672ee70bf491fa44728f03.pdf
2020-12-01
127
136
10.22126/arww.2021.4205.1125
Water Governance
Economic Assessment
Water resources
Exploitation System Development
Drought
Farzaneh
Shahbakhsh
farzad.shahbakhsh1396@gmail.com
1
Department of Agricultural Economics, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran.
AUTHOR
Mahdi
Safdari
mahdisafdariut@gmail.com
2
Department of Agricultural Economics, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran.
LEAD_AUTHOR
Ali
Sardar Shahraki
a.shahraki65@gmail.com
3
Department of Agricultural Economics, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran.
AUTHOR
Abdelgawad G., Arslan A., Gaihbe A., Kadouri F., the effects of saline irrigation water management and salt tolerant tomato varieties on sustainable production of tomato in Syria (1999– 2002), Agricultural Water Management 78 (2005) 39– 53.
1
Afroozeh F., Mousavi S., Torkamani, J., analysis of water swings and optimizing water consumption in the agricultural sector of Sistan region: Application of fuzzy approach, Journal of Agricultural Economics Research 3 (2011) 37-59.
2
Afsari A., Haji Naseri S., Fazeli, M., Feirahi, D., A sociological examination of water governance in Lake Urmia crisis: Grounded theory model, Journal of Strategic Studies of Public Policy 7 (2018) 53-72.
3
Ahmadi M., Beheshtian R., Moghadasi M., Kazemi M.A., Review of water governance, Proceedings of 1st International Conference of Water Management, Demand and Use Efficiency (2018).
4
Ahmadi S., and Badisar S., The right to water in international human rights system, Environmental Law 1 (2017) 38-50.
5
Almohammad S., Malek Mohammadi B., Yavari A., Yazdanpanah M. policymaking of sustainable governance and management of terrain resources in the watershed of Lake Urmia, Rahbord, 23 (2014) 151-179.
6
Alizadeh S., and Mohammadi H., dynamic system modeling by temporal and spatial distribution pattern of drought in Iran, Geography 13 (2015) 141-160.
7
Allan T., the Middle East water question: Hydropolitics and the global economy, London and New York; (2001).
8
Asgharipour M., multi-criteria decision-making. Tehran, Iran: Tehran University Press; (2002).
9
Daliri F., SeyedSaraji H., Kholghi M., water shed system plaining and management using optimization model (case study: Gharmabdasht watershed), Journal of Range and Watershed Management 62 (2009) 274-256.
10
Gaedi S., Afrasiab P., Liaghat A., the effect of conjunctive use of fresh and saline water in the Sistan region, Iranian Journal of Soil and Water Research 46 (2015) 455-463.
11
Hajimoradi A., Azadeghan M., Najafi Ghodoosi A., Nikravan M., Alam Rajabi H., Panahi N., detailed report of the first meeting on water resources policy making with a focus on productivity and sustainable governance of water resources, Tehran, Iran: Amirkabir University Press; (2014).
12
Hashemi S., an institutional and structural framework to implement integrated water resource management in Iran. Proceedings of the 18th Conference of Research Achievements, Iranian Water Resources Management Corporation (2012).
13
Jamali S., The legal rules governing water governance and its gaps in legal system of Iran (Thesis); (2017).
14
Kahrizi S., A study on good governance in water management improvement (Thesis), Tehran, Iran: Tehran Markazi Branch of Islamic Azad University; (2014).
15
Kariminazar M., Moghaddamnia A., Mosaedi A., Investigation of climatic factors affecting occurrence of drought (Case study: Zabol Region), Journal of Water and Soil Conservation, 17 (2011) 145-158.
16
Labajos R., and Alier M., Political ecology of water conflicts, WIREs Water, 2 (2015) 537-558.
17
Mahmoodzadeh S., Shahrabi J., Pariazar M., Zaeri M.S., Project selection by using fuzzy AHP and TOPSIS technique, International Journal of Human and Social Sciences 1 (2007) 135 – 141.
18
Nosrati K., and Kazemi Y., Daily monitoring of drought and water resources in different climates of Iran, Journal of Range and Watershed Management 64 (2010) 79-94.
19
Pahl-Wostl C., Water governance in the face of global change from understanding to transformation, First Ed., Springer International Publishing: Switzerland; (2015).
20
Piri H., Rahdari V., Maleki S., study and compare performance of four meteorological drought index in the risk management droughts in Sistan and Baluchestan province, Journal of Irrigation and Water Engineering 3 (2013) 96-114.
21
Razeie T., Danesh P., Safzian B., The temporal and spatial pattern of meteorological droughts in Sistan and Baluchestan province, Scientific Journal of Agriculture 30 (2007) 85-99.
22
Saeedi I., and Darabi H., Campus Landscape design based on resilience approach and water shortage (Case study: Campus of Malayer University), Journal of Environmental Studies 40 (2015) 1051-1066.
23
Safaee A., and Malek Mohammadi B., game theoretic insights for sustainable common poll water resources governance (Case study: Lake Urmia water conflict), Journal of Environmental Studies 40 (2014) 121-138.
24
Salari F., Ghorbani M., Malekian A., Social monitoring in local stakeholders network to water resources local governance (Case study: Razin Watershed, Kermanshah city), Journal of Range and Watershed Management 68 (2015) 287-305.
25
Sardar Shahraki A., The determination of socio-economic effects of pomegranate production in Sistan Region, Iranian Economic Review 23 (2019) 491-508.
26
Sardar Shahraki A., Shahraki J., Hashemi Monfared S.A., Ranking and level of development according to the agricultural indices, case study: Sistan region, International Journal of Agricultural Management and Development (IJAMAD) 6 (2016) 93-100.
27
Sardar Shahraki A., Shahraki J., Hashemi Monfared S.A., An application of WEAP model in water resources management considering the environmental scenarios and economic assessment Case study: Hirmand Catchment, Modern Applied Science 10 (2018) 49-56.
28
Sardar Shahraki A., Shahraki J., Hashemi Monfared S.A., An integrated fuzzy multi-criteria decision-making method combined with the weap model for prioritizing agricultural development; Case study: Hirmand Catchment, ECOPERSIA 6 (2018) 205-214.
29
Sardar Shahraki A., Shahraki J., Hashemi Monfared S.A., Application of fuzzy technique for order-preference by similarity to ideal solution (ftopsis) to prioritize water resource development economic scenarios in Pishin catchment, International Journal of Business and Development Studies 10 (2018) 77-94.
30
Sardar Shahraki A., Optimum allocation of water resources in Hirmand Watershed: The use of game theory and assessment of management scenarios (Dissertation), Zahedan, Iran: Sistan and Baluchestan University Press; (2016).
31
Sardar Shahraki A., AliAhmadi N., Safdari M., A new approach to evaluate the economic efficiency and productivity of agriculture sector: the application of window data envelopment analysis (WDEA), Environmental Energy and Economic Research (EEER) 2 (2018) 145-160.
32
Sardar Shahraki A., and Karim M.H., The economic efficiency trend of date orchards in Saravan county, Iranian Economic Review, 22 (2018) 1093-1112.
33
Silva A.C.S., Galvão C.O., Silva G.N.S., Droughts and governance impacts on water scarcity: an analysis in the Brazilian semi-arid, Copernicus Publications on behalf of the International Association of Hydrological Sciences 369 (2015) 129–134.
34
Sternlieb F., and Laituri M., Spatialising agricultural water governance data in polycentric regimes, Water Alternatives 8 (2015) 36-56.
35
Tanguay G., Measuring the sustainability of cities: An analysis of the use of local indicators, Ecological Indicators 10 (2010) 407–418.
36
Yaqob Y., Al-Sa`Ed R., Sorial G., Sudian M., Simulation of transboundary wastewater resource management scenarios in the Wadi Zomer watershed, using a WEAP model, International Journal of Basic and Applied Sciences 4 (2015) 27-35.
37
Yousefi A., Amini A., Fathi O., Sustainable water governance: The main challenge of water crisis management in the Zayanderud river, Proceedings of the 1st National Conference of Water Crisis; (2013).
38
ORIGINAL_ARTICLE
Simulation of bridge pier scour depth base on geometric characteristics and field data using support vector machine algorithm
In this paper, two groups of datasets including Froehlich (1988) and USGS were implemented to simulate scour depth for bridge piers of three shapes (circular, sharp-nose and rectangular) using support vector machine (SVM) algorithm. The results of the SVM were compared with gene expression programming (GEP) and the non-linear regression model. Independent parameters extracted using dimensional analysis were Froud number (Fr), the ratio of pier length to pier width (L/b), the ratio of sediment particle diameters (d50/d84), the ratio of sediment mean size to pier width (d50/b) and attack angle of water flow (α). Different combinations of independent variables were used to achieve optimum performance of the simulator. The results showed that among three simulators, the SVM algorithm had the best performance to predict local scour depth. The sensitivity analysis revealed that among independent parameters, the descending order of effectivity was Fr, sediment size, L/b, and α.
https://arww.razi.ac.ir/article_1610_95b74ffec6370e4ecaa0bd7ede3ec66a.pdf
2020-12-01
137
143
10.22126/arww.2021.5747.1189
Intelligent model
Sensitivity analysis
scour depth
field data
Mahdi
Majedi-Asl
mehdi.majedi@gmail.com
1
Department of Civil Engineering, Faculty of Engineering, University of Maragheh, East Azerbaijan, Iran.
LEAD_AUTHOR
Rasoul
Daneshfaraz
daneshfaraz@yahoo.com
2
Department of Civil Engineering, Faculty of Engineering, University of Maragheh, East Azerbaijan, Iran.
AUTHOR
Mehdi
Fuladipanah
fuladipanah@gmail.com
3
Department of Civil Engineering, Ramhormoz Branch, Islamic Azad University, Ramhormoz, Iran.
AUTHOR
John
Abraham
jpabraham@stthomas.edu
4
Department of Mechanical Engineering, Faculty of Engineering, University of St. Thomas, St Paul, MN, USA.
AUTHOR
Mohammad
Bagherzadeh
bagherzadeh.mbz96@gmail.com
5
Department of Civil Engineering, Faculty of Engineering, University of Maragheh, East Azerbaijan, Iran.
AUTHOR
Akib S., Mohammadhassani M., Jahangirzadeh A., Application of ANFIS and LR in prediction of scour depth in bridges, Computers & Fluids 91 (2014) 77-86.
1
Azamathulla H.M., Haque A.A.M., Orediction of scour depth at culvert outlets using gene-expression programming, International Innovative Computing Information Control 8 (2012) 5045-5054.
2
Bateni S.M., Borgheib S.M., Jeng D.S., Neural network and neuro-fuzzy assessments for scour depth around bridge piers, Engineering Applications of Artificial Intelligence 20 (2007a) 401-414.
3
Bateni S.M., Jeng D.S., Melville B.W., Bayesian neural networks for prediction of equilibrium and time-dependent scour depth around bridge piers, Advances in Engineering Software 38 (2007b) 102-111.
4
Chou J.S., and Pham A.D., Nature-inspired metaheuristic optimization in least squares support vector regression for obtaining bridge scour information, Information Sciences 399 (2017) 64-80.
5
Daneshfaraz R., Chabokpour J., Desineh M., Ghaderi A., The experimental study of the effects of river mining holes on the bridge piers, Iranian Journal of Soil and Water Research 50 (2019) 1619-1633.
6
Eghbali P., Daneshfaraz R., Saghebian S.M., Simulation of temporal development of scour hole around a wing-wall abutment using gene expression programming, Water and Soil Science 23 (2013) 177-188.
7
Froehlich D.C., Analysis of onsite measurements of scour at piers, Hydraulic Engineering: Proceedings of the National Conference on Hydraulic Engineering (1988) 534-539.
8
Geol A., Predicting Bridge Pier Scour Depth with SVM. International Scholarly and Scientific Research & Innovation 9(2) (2015) 1619-1624.
9
Ghaderi A., and Abbasi S., CFD simulation of local scouring around airfoil-shaped bridge piers with and without collar, Sādhanā 44 (10) (2019) 216.
10
Ghaderi A., Daneshfaraz R., Dasineh M., Evaluation and prediction of the scour depth of bridge foundations with HEC-RAS numerical model and empirical equations (Case study: bridge of Simineh Rood Miandoab, Iran), Engineering Journal 23 (2019) 279-295.
11
Ghaemi N., Etemad-Shahidi A., Ataie-Ashtiani B., Estimation of current-induced pile groups scour using a rule-based method, Journal of Hydro Informatics 15 (2013) 516-528.
12
Heidarpour M., Afzalimehr H., Izadinia E., Reduction of local scour around bridge pier groups using collars, International Journal of Sediment Research 25 (2010) 411–422.
13
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14
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15
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16
Laursen E.M., Scour at bridge crossings, Transition ASCE 127 (1962) 166-180.
17
MajediAsl M., Daneshfaraz R., Valizadeh S., Experimental investigation of the river materials mining effect on the scouring around armed pier groups, Iranian Journal of Soil and Water Research 50 (2019a) 1363-1380.
18
Meliville B.W., and Sutherland A.J., Design method for local scour at bridge piers, Journal of Hydraulic Engineering 114 (1988) 1210-1226.
19
Mihoub R., Chabour N., Guermoui M., Modeling soil temperature based on Gaussian process regression in a semi-arid-climate; Case study: Ghardaia, Algeria, Geo-mechanics and Geophysics for Geo-Energy and Geo-Resources 2 (2016) 397–403.
20
Moradinejad A., Saneie M., Ghaderi A., Shahri S.M.Z., Experimental study of flow pattern and sediment behavior near the intake structures using the spur dike and skimming wall, Applied Water Science 9 (2019) 195.
21
Najafzadeh M., Rezaie-Balf M., Rashidi E., Prediction of maximum scour depth around piers with debris accumulation using EPR, MT and GEP model, Journal of Hydroinformation 18 (2016) 867-884.
22
Norouzi R., Daneshfaraz R., Ghaderi A., Investigation of discharge coefficient of trapezoidal labyrinth weirs using artificial neural networks and support vector machines, Applied Water Science 9 (2019) 148.
23
Pandey M., Sharma P.K., Ahmad Z., Singh U.K., Experimental investigation of clear-water temporal scour variation around bridge pier in gravel, Environmental Fluid Mechanics 18 (2018) 871–890.
24
Roushangar K., Alami M.T., Shiri J., MajediAsl M., Determining discharge coefficient of labyrinth and arced labyrinth weirs using support vector machine, Hydrology Research 49 (2017a) 924-938.
25
Roushangar K., Alami M.T., MajediAsl M., Shiri J., Modeling discharge coefficient of normal and inverted orientation labyrinth weirs using machine learning techniques, ISH Journal of Hydraulic Engineering 23 (2017b) 331-340.
26
Sharafi H., Ebtehaj I., Bonakdari H., HosseinZaji A., Design of a support vector machine with different kernel functions to predict scour depth around bridge piers, Natural Hazard 84 (2016) 2145-2162.
27
Shen H.W., Schneider V.R., Karaki S.S., Local scour around bridge piers, Journal of Hydraulic Division ASCE 95 (1969) 1919-1940.
28
Sreedhara B.M., Rao M., Mandal S., Application of an evolutionary technique (PSO–SVM) and ANFIS in clear-water scour depth prediction around bridge piers, Neural Computing and Applications 31 (2019) 7335-7349.
29
Thendiyath R., Prakash V., Role of Regression Models in Bridge Pier Scour Prediction. International Journal of Applied Metaheuristic Computing 11(2) (2020) 156-170.
30
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34
ORIGINAL_ARTICLE
Assessment of the quality and quantity of groundwater in Bahadoran plain using neural network methods, geostatistical and multivariate statistical analysis
Growing water demand in various sectors including agriculture, industry, drinkingwater and eventually increasing production and risk of pollution have imposedmounting pressure on water resources. The relative stability of renewable waterresources makes it necessary to pay special attention to the conservation andoptimal use of these resources, especially in desert areas such as Iran, and thisrequires careful and principle planning for the optimal use of existing waterresources. In this research, a descriptive-analytical method was adopted. The datawere collected from fifteen wells during an 8-year period (2010-2017). TheKolmogorov-Smirnov method was recruited to assess the normality of datadistribution. Also, since the classical data (water quality data) did not take intoaccount the spatial distribution of groundwater quality parameters, we used thegeostatistics for this purpose. The results suggested that the dominant groundwatertype in the Bahadoran region was sodium chloride (NaCl), which is highly volatile.This volatility can be attributed to cationic and anionic exchanges as well as thedissolution of salt and gypsum in the neogene formation of the region. On the otherhand, overexploitation and increasing drainage of agricultural, residential and evenindustrial wastewaters in the plain water resources have drastically influenced thegroundwater quality. In the second period of the studied period (2012-2013), thelevel of maximum classes of most parameters has increased compared to the firstperiod, and these changes have increased with a greater slope in the third period.According to the studies, the most important formations in terms of reservoir rock,feed source of alluvial plains and groundwater quality are lower cretaceouscalcareous sediments of Bahadoran.
https://arww.razi.ac.ir/article_1611_fa2be71f44a3d25ad5cb28d2095fc595.pdf
2020-12-01
144
151
10.22126/arww.2021.4367.1134
Groundwater
Bahadoran plain
Geostatistics
Water quality
Hydrochemical software
Yazd province
Mohammad Sadegh
Talebi
talebi@meybod.ac.ir
1
Department of Geography, Faculty of Humanities, Meybod University, Meybod, Iran.
LEAD_AUTHOR
Mehran
Fatemi
yazdfatemi@meybod.ac.ir
2
Department of Geography, Faculty of Humanities, Meybod University, Meybod, Iran.
AUTHOR
Adib A., and Zamani R., Study of Spatial Changes in Groundwater Quality Indicators in Dezful Plain Using Geostatistics, Journal of Water Resources Engineering 8 (2015) 1 – 12.
1
Alipour A., Rahimi J., Azarnivand A., Groundwater quality assessment for drinking and agricultural uses - prerequisite for landscaping planning in arid and semi-arid regions of Iran, Journal of Rangeland and Watershed Management (Natural Resources of Iran) 70 (2017) 423- 434.
2
Ebrahimi A., Guidelines for designing, monitoring and controlling the quality of groundwater resources in Iran, Publication Iran Water Resources Management Organization (2001) 95.
3
Hajiannezhad M., and Rahsepar A.R., Investigating the effect of wastewater and wastewater treatment wastewater on water quality parameters of Zayandehrud river, Journal of Health Research 6 (27) (2009) 14-27.
4
Hassani Pak A., Geostatistics, Publication University of Tehran, 5th Ed., (2017) 314.
5
Kholfi A., Glossary of geology and related sciences and technology, Jihad Daneshgahi Publication of Shahid Bahonar University of Kerman, (2009) 258.
6
Salajeghe A., Land use change and its effects on river water quality (case study: Karkheh watershed area), Journal of Environmental Studies 37 (2010) 81-86.
7
Sedaghat M., Land and water resources (groundwater), 6th Ed., Payame Noor University; (2015) 125.
8
Safari S., Basics and application of physical-hydraulic models, 3th Ed., Shahid Chamran University, Ahvaz, Iran; (2016) 205.
9
Report of the detailed plan of watershed management studies of Bahadoran basin. (2009). Zersa Consulting Engineers, Tehran, 215 pages.
10
Mozafarizadeh F., Investigating the effect of geological formations on underground water resources quality in Gitvand plain, Master's thesis, Shahid Chamran University of Ahvaz (2006).
11
Talebi M.S., Sadral-Dini M.A., Dehghani Firoozabadi N., Arid and semi-arid regions, Meybod Azad University (2016) 202.
12
Malakutian G., Simulation of the behavior of aquifers in Shuro plain, Master's thesis, Faculty of Geology, University of Zahedan; (2004) 135.
13
Nakhaei Nejadfard S., Zehtabian G., Malekian A., Khosravi H., Study of temporal and spatial changes in the quality and quantity of groundwater in Sarayan plain in South Khorasan, Iranian Journal of Range and Desert Research (2017) 268-279.
14
Nazarizadeh F., Ershadian B., Zandvakili K., Investigating the groundwater in Balarood plain, The First Regional Conference on the Exploitation of Water Resources in Karoun and Zayanderoud Basin, Shahrekurd (2006) 128 - 135.
15
Nowshadi M., Bidokhtar N., Yousefi M., Analysis and measurement of groundwater quality in the Nurabad Mamesani plain, National Conference on Environmental Health, Shahid Beheshti University, Tehran (2009).
16
Robinson H., Metternicht water quality and presence of pesticides in a tropical coastal wetland in southern Mexico, Marine pollution Bulletin 8 2006( 1130 -1141.
17
Ryan K., and Douglas C., Spatial and temporal patterns of slinity and temperature at an intertidal groundwater seep, Journal of Estuarine Coastal and Shelf Science (2006).
18
Dhar R.K., Zheng Y., Stute M., Vangeen A., Temporal variability of groundwater chemistry in shallow and deep aquifers of Araihazar, Bangladesh, Journal of Contaminat Hydrology (2008).
19
ORIGINAL_ARTICLE
Investigation of effect of optimal time interval on the linear Muskingum method using particle swarm optimization algorithm
In engineering works, calculation of the peak zone of the flood is very important. Therefore, in the present study, a method was presented to increase the accuracy of the flood routing of the peak zone of the inflow hydrograph. The recorded data in the Ahwaz and Farsiat hydrometric stations were used, both of which are related to the Karun river, Iran. In contrast to previous studies, in addition to calculating the coefficients of linear Muskingum method (X, K), the time interval (Δt) parameter was also optimized in the present study using the PSO algorithm. The results showed that if only the X and K coefficients were calculated, the mean relative error (MRE) of the peak zone for the first, second and third floods were equal to 8.34, 2.24, and 1.99 %, respectively. However, by using the optimized Δt value, the corresponding error decreased to 5.14, 0.44, and 1.08 %.
https://arww.razi.ac.ir/article_1613_a364444f91e1b773db25e321ebdce5b4.pdf
2020-12-01
152
156
10.22126/arww.2021.4426.1137
Flood routing
Linear Muskingum method
Optimization of Δt parameter
PSO algorithm
Hadi
Norouzi
hadinorouzi72@gmail.com
1
Department of Civil Engineering, Faculty of Engineering, University of Zanjan, Zanjan, Iran.
LEAD_AUTHOR
Jalal
Bazargan
jbazargan@znu.ac.ir
2
Department of Civil Engineering, Faculty of Engineering, University of Zanjan, Zanjan, Iran.
AUTHOR
Abozari N., Hassanvand M., Salimi A.H., Heddam S., Mohammadi H.O.,
1
Noori A., Comparison performance of artificial neural network based
2
method in estimation of electric conductivity in wet and dry periods:
3
Case study of Gamasiab river, Iran, Journal of Applied Research in
4
Water and Wastewater 6 (2019) 88-94.
5
Afshar A., Kazemi H., Saadatpour M., Particle swarm optimization for
6
automatic calibration of large scale water quality model (CE-QUALW2):
7
Application to Karkheh reservoir, Iran, Water Resources
8
Management 25 (2011) 2613-2632.
9
Bazargan J., and Norouzi H., Investigation the effect of using variable
10
values for the parameters of the linear muskingum method using the
11
particle swarm algorithm (PSO), Water Resources Management 32
12
(2018) 4763-4777.
13
Chau K., A split-step PSO algorithm in prediction of water quality
14
pollution, In International Symposium on Neural Networks, Springer,
15
Berlin, Heidelberg (2005) 1034-1039.
16
ORIGINAL_ARTICLE
Sustainable environmental management and solid waste control in the Ekbatan wastewater treatment plant (EWTP), Tehran, Iran
Sustainable development highly depends on how we manage various parts of the industry, and it plays a significant role in the sewage purge system to pay attention to the clutch reducer elements. Complementary procedures and technologies are needed to resolve water governance concerns, urging a rapid alteration of the economics, engineering, and administration agendas to determine our generation's water challenges. Ekbatan Wastewater Treatment Plant (EWTP) confronts several problems that necessitate comprehensive and strategic planning and management. An analysis of strength-weakness-opportunity-threat (SWOT) and quantitative strategic planning matrix (QSPM) methods were used to investigate strategic factors. For scoring the proposed strategies, a group of experts who are familiar with environmental management was selected. Environmental factors were recognized and investigated. According to experts' opinions, important and unimportant factors were identified and prioritized. The most effective strategy to further strengthen the current situation is "expanding the treatment plant activities such as internal infrastructure and urban utilities to manage more waste."
https://arww.razi.ac.ir/article_1640_f06c23937a79d5fb064a9b9350979310.pdf
2020-12-01
157
162
10.22126/arww.2021.5879.1194
Strategic management
Sustainable development
SWOT
QSPM
Waste management
Mohammad
Zahed
zahed.moe@gmail.com
1
Department of Cell and Molecular Biology, Kharazmi University, Tehran, Iran.
LEAD_AUTHOR
Aeen
Eftekhari
aeen.eftekhari@gmail.com
2
Department of Civil, Environmental, and Geomatic Engineering (BAUG), Swiss Federal Institute of Technology (ETHZ), Stefano‐Franscini‐Platz 5, 8093 Zürich, Switzerland.
AUTHOR
Hassan
Hoveidi
hoveidi@ut.ac.ir
3
Department of Environmental Management, College of Engineering, University of Tehran, Tehran, Iran.
AUTHOR
Faranak
Hejabi
faran.hj@yahoo.com
4
Department of Cell and Molecular Biology, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran.
AUTHOR
Afshar F., Abbaspour M., Lahijanian A., Providing a practical model of the waste management master plan with emphasis on public participation "using the SWOT method and the QSPM matrix and the FAHP method", Advances in Environmental Technology 5 (2019) 77-96.
1
Alkan Y., A research at sustainable urban scale: example of Çanakkale, Environmental Monitoring and Assessment 192 (2020) 1-12.
2
Ammar E., Maury H., Morin L., Sghir A., Environmental, economic, and ethical assessment of the treated wastewater and sewage sludge valorization in agriculture, Interaction and Fate of Pharmaceuticals in Soil-Crop Systems (2020).
3
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4
Bui T.D., Tsai F.M., Tseng M.L., Ali M.H., Identifying sustainable solid waste management barriers in practice using the fuzzy Delphi method, Resources, Conservation and Recycling 154 (2020) 1-14.
5
Cherubini F., Bargigli S., Ulgiati S., Life cycle assessment (LCA) of waste management strategies: Landfilling, sorting plant and incineration, Energy 34 (2009) 2116–2123.
6
Dashti A.F., Aziz H.A., Adlan M.N., Ibrahim A.H., Calcined limestone horizontal roughing filter for treatment of palm oil mill effluent polishing pond, International Journal of Environmental Science and Technology 16 (2019) 6419-6430.
7
Dashti A.F., Aziz H.A., Ibrahim A.H., Zahed M.A., Suspended solid removal of palm oil mill effluent using horizontal roughing filter and calcinated limestone, Water, Air, & Soil Pollution 231 (2020) 1-15.
8
El Houari A., Ranchou-Peyruse M., Ranchou-Peyruse A., Bennisse R., Bouterfas R., Goni Urriza M.S., Guyoneaud R., Microbial communities and sulfate-reducing microorganisms’ abundance and diversity in municipal anaerobic sewage sludge digesters from a wastewater treatment plant (Marrakech, Morocco), Processes 8 (2020) 1284.
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Jagaba A.H., Shuaibu A., Umaru I., Musa S., Lawal I.M., Abubakar S., Stabilization of soft soil by incinerated sewage sludge ash from municipal wastewater treatment plant for engineering construction, Sustainable Structure and Materials 2 (2019) 32-44.
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17
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18
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19
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20
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Metcalf E.I., Wastewater engineering-treatment and reuse, USA; Mic Graw-Hill, (2014).
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Moumen Z., El Idrissi N.E.A., Tvaronavičienė M., Lahrach A., Water security and sustainable development, Insights into Regional Development 1 (2019) 301-317
24
Ngoc U.N., and Schnitzer H., Sustainable solutions for solid waste management in Southeast Asian countries, Waste Management 29 (2009) 1982–1995.
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Ortigara A.R.C., Kay M., Uhlenbrook S., A review of the SDG 6 synthesis report 2018 from an education, training, and research perspective, Water 10 (2018) 1353.
26
Pandey C.L., Managing urban water security: challenges and prospects in Nepal, Environment, Development and Sustainability (2020) 1-17.
27
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28
Shahbod N., Bayat M., Mansouri N., Nouri J., Ghodousi J., Application of Delphi method and fuzzy analytic hierarchy process in modeling environmental performance assessment in urban medical centers, Environmental Energy and Economic Research 4 (2020) 43-56.
29
Solsona S.P., Montemurro N., Chiron S., Barceló D., (Eds.) Interaction and fate of pharmaceuticals in soil-crop systems: The impact of reclaimed wastewater, Springer Nature 103 (2021).
30
Vila Seoane M.F., Alibaba's discourse for the digital silk road: the electronic World Trade Platform and 'inclusive globalization, Chinese Journal of Communication 13 (2020) 68-83.
31
Wei L., Zhu F., Li Q., Xue C., Xia X., Yu H., Bai S., Development, current state and future trends of sludge management in China: Based on exploratory data and CO2-equivalent emissions analysis, Environment International 144 (2020) 1-12.
32
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33
Zeinolabedini M., and Najafzadeh M., Comparative study of different wavelet-based neural network models to predict sewage sludge quantity in wastewater treatment plant, Environmental Monitoring and Assessment 191 (2019) 163.
34
Zhang Z., and Chen Y., Effects of microplastics on wastewater and sewage sludge treatment and their removal: a review, Chemical Engineering Journal 382 (2020) 122955.
35
Zhao J., Hou T., Zhang Z., Shimizu K., Lei Z., Lee D.J., Anaerobic co-digestion of hydrolysate from anaerobically digested sludge with raw waste activated sludge: Feasibility assessment of a new sewage sludge management strategy in the context of a local wastewater treatment plant, Bioresource Technology 314 (2020) 1-8.
36
Zhu L., Song Q., Sheng N., Zhou X., Exploring the determinants of consumers' WTB and WTP for electric motorcycles using CVM method in Macau, Energy Policy 127 (2019) 64-72.
37
ORIGINAL_ARTICLE
Study of biofilm creating bacteria in drinking water of Ahvaz city in Iran
In order to investigate the biofilm creating bacteria in drinking water of Ahvaz, Iran, 4 different types of frequently used kitchen dishes (made up of plastic, glass, zinc, and teflon) were used for storage of drinking water under the same conditions at room temperature (25 °C) in triplicate order. After the formation of the slime layer, microbiological tests were performed. Results showed that after 3 days, the biofilm layer was created. The biofilm creating bacteria of studied water belonged to both the gram-negative and gram-positive groups and were identified as follows: Staphylococcus aureus, Eschershia coli, Salmonella typhimorium, Entrobacter aerogenes, and Shigella sp. Results showed that the plastic dishes had the highest rate of bacterial growth and E. coli with 65 % of the growth was the most abundant bacteria of the investigated biofilm. It could be concluded that even in purified drinking water there were bacteria with the ability to create biofilm which needs more attention to purification processes and water storage in consideration with the quality of the dishes.
https://arww.razi.ac.ir/article_1571_9d3bcf25e875168c5905d57ae3f8617a.pdf
2020-12-01
163
166
10.22126/arww.2020.4435.1140
Bacteria
Biofilm
Drinking water
Zahra
Salehi Reyhani
zsalehireyhani4@gmail.com
1
Department of Biology, Dezful Branch, Islamic Azad University, Dezful, Iran.
AUTHOR
Zahra
Khoshnood
zkhoshnood@gmail.com
2
Department of Biology, Dezful Branch, Islamic Azad University, Dezful, Iran.
LEAD_AUTHOR
Anand S., Singh D., Avadhanula M., Marka S., Development and control of bacterial biofilms on dairy processing membranes, Comparative Review of Food Science and Food Safety 13 (2014) 18-33.
1
Boe-Hansen R., Martiny A.C., Arvin E., Albrechtsen H.J., Monitoring biofilm formation and activity in drinking water distribution networks under oligotrophic conditions, Water Science and Technology 47 (2003) 91-97.
2
Bomo A.M., Storey M.V., Ashbolt N.J., Detection, integration and persistence of aeromonads in water distribution pipe biofilms, Journal of Water and Health 2 (2004) 83-96.
3
Characklis W.G., McFeters G.A., Marshall K.C., Physiological ecology in biofilm systems, First Ed., John Wiley & Sons, New York; (1990).
4
Costerton, J., Geesey G., Cheng K., How bacteria stick, Scientific American 238 (1987) 86-5.
5
Flemming H., Biofouling in water system- cases, Causes and countermea sures, Applied Microbiology and Biotechnology 59 (2002) 629-40.
6
Juhna T., Birzniece D., Larsson S., Zulenkovs D., Shapiro A., Azevedo N.F., Menard-Szczebara F., Castagnet S., Feliers C., Keevil C.W., Detection of Escherichia coli in biofilms from pipe samples and coupons in drinking water distribution networks, Applied Environmental Microbiology 73 (2007) 7456-7464.
7
Mirhendi S.H., and Nikaeen M., Wastewater microbiology, First Ed.,Tehran University of Medical Sciences, Iran; (2004) (In Persian).
8
Percival S., Knapp J.S., Edyrean R., Wales D., Biofilms, mains water and stainless steel, Water Research 32 (1998) 2187-201.
9
Rivardo F., Turner R., Allegrone G., Ceri H., Martinotti M., Antiadhesion activity of two biosurfactants produced by Bacillus spp. prevents biofilm formation of human bacterial pathogens, Journal of Applied Microbiology and Biotechnology83 (2009) 541-553.
10
September S., Els F., Venter S., Brozel V., Prevalence of bacterial pathogens in biofilms of drinking water distribution systems, Journal of water Health 5 (2007) 219-227.
11
Szymanska J., Biofilm and dental unit water lines, Annual Agriculture and Environment Medicine 10 (2003) 151-57.
12
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13
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14
ORIGINAL_ARTICLE
The effect of Typha Latifolia L. on heavy metals phytoremediation at the urban and industrial wastewater entrance to the Meighan wetland, Iran
A mixture of urban and industrial wastewater is discharged into the Meighan wetland, Arak, Iran. The heavy metals containing wastewater leads to environmental hazards whereby phytoremediation can be used for removing pollutants from contaminated water. An essential native plant that is abundant in the Meighan wetland is Typha Latifolia L. The effect of T. Latifolia L. was investigated on the removal of heavy metals (aluminum, zinc, copper, and nickel) at the inlet of Arak wastewater treatment plant into Meighan wetland. The soil (0-30 cm in depth) and plants (aerial and root biomass) were sampled in September 2019. In the laboratory, heavy metal accumulation in samples was measured via atomic absorption method. The results of analysis of variance (ANOVA) revealed that the concentrations of all four metals were significantly different across the soil, root, and aerial biomass. The results of mean comparison by Duncan's test indicated that the highest concentration of aluminum was in the soil, while the lowest in aerial parts. Copper was maximum in the root, and the minimum was found in the aerial parts. Also, the concentration of zinc was the highest in the root, and the lowest in the soil. And, nickel was maximum in the soil while being minimum in the root. Data showed that the concentrations of aluminum in the soil, root, and aerial biomass of T. Latifolia L. were multiple times higher than permissible limit. The concentration of nickel in the soil was slightly higher than the acceptable limit, but the concentrations of other heavy metals in the soil, in aerial biomass, and in the root of T. Latifolia L. were within the acceptable range. The results indicated T.Latifolia L. is a suitable plant for the phytoremediation and water treatment in the Meighan wetland.
https://arww.razi.ac.ir/article_1641_f453aa8f0b70b461e0d013823ee0bbbd.pdf
2020-12-01
167
171
10.22126/arww.2021.5831.1193
Phytoremediation
Heavy removal
Typha Latifolia L
Meighan wetland
Water treatment
Masumeh
Heidarzadeh
m_heidarzadeh1987@yahoo.com
1
Department of Range and Watershed Management, Arak Branch, Islamic Azad University, Arak, Iran.
AUTHOR
Nourollah
Abdi
n-abdi@iau-arak.ac.ir
2
Department of Range and Watershed Management, Arak Branch, Islamic Azad University, Arak, Iran.
LEAD_AUTHOR
Javad
Varvani Farahani
j-varvani@iau-arak.ac.ir
3
Department of Range and Watershed Management, Arak Branch, Islamic Azad University, Arak, Iran.
AUTHOR
Abbas
Ahmadi
abahmadi@gmail.com
4
Department of Range and Watershed Management, Arak Branch, Islamic Azad University, Arak, Iran.
AUTHOR
Hamid
Toranjzar
h-toranjzar@iau-arak.ac.ir
5
Department of Range and Watershed Management, Arak Branch, Islamic Azad University, Arak, Iran.
AUTHOR
Davodpour R., The feasibility study of using honeybee as a bioindicator species for monitoring transfer of heavy metals in the soil-plant-food chain (case study: major foci of beekeeping and honey production in Markazi province), PhD Thesis of Environmental Contamination, Islamic Azad University, Hamedan branch; (2018).
1
Ebadati F., Esmaeili Sari A., Riahi Bakhtiari A.R., The level and trend of changes in heavy metals as well as aquatic plant organs plus sediments of Miankaleh wetland, Environmental Science 31 (2005) 53-57.
2
Firouzshahian N., Payandeh K., Sabzalipour S., Monitoring Cd, Ni, and Vd elements in Phragmites australis and Typha Latifolia L. aquatic plants in Hourolazim wetland in Khuzestan province, Development Biology Journal (2019) 47-60.
3
Ghasemi A., Accumulation of heavy metals in superficial sediments and in Typha Latifolia L. aquatic plant in Anzali international wetland, MSc., Thesis of environmental science, at faculty of environment at Isfahan industrial University; (2013).
4
Ghanadpour J., and Zndmoqadam A., Accumulation of heavy metals lead, zinc, nickel and cadmiumin (Typhalatifolia) and river sediments Arvand and Bahmanshir in winter season, Journal Wetlands 5 (2010) 29-36 (In Persian).
5
Haji Hosseini M., Varvani J., Abdi N., Comparing the concentration of heavy metals (Al, Pb, Zn, Ni) in surface sediments of Meighan wetland, 2st National Congress Of Environmental Protection and Planning, Hamedan, Iran (2013).
6
Jafari Haghighi M., Soil-sampling analysis methods as well as important physiochemical analyses with emphasis on theoretical and applied principles, First Edition, Nedaye Zoha Publications, Iran; (2003).
7
Karimi H., The encyclopedia of Iran’s Herbage, First Edition, Agricultural science publications, Iran; (2009).
8
Norouzi Nodeh R., Investigating two species Alyssum longistylum L. and Aegilops columnaris Zhuk as phyto-remediating plants for Arak wastewater, MSc. Thesis, Arak University; (2009).
9
Salehi A., Phytoremediation: A remediation technology of heavy metal contaminated soils, Human & Environment 17 (2019) 27-42.
10
Vahid Dastjerdi M., Shanbezadeh S., Zahab Saniei A., Rouzegar R., Investigating and comparing the accumulation of heavy metals in the water, soil, and plants of Gavkhuni international wetland in 2002-2006, Health System Research 6 (2010) 829-836.
11
ORIGINAL_ARTICLE
Adsorption of cationic dye from aqueous solution using SBA-15 nano particles synthesized by stem sweep ash as the source of silica
Today, many efforts have been made to use agricultural waste as a cheap and abundant resource for providing suitable adsorbents to remove pollutants such as industrial dyes. The aim of this study was to remove dye from water under different conditions using SBA-15 nano particles as adsorbents their silica was prepared from stem sweep ash (SSA). Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD) and N2 adsorption experiments were applied to evaluate the structural characteristics of obtained adsorbent. In addition, to remove Azure B dye by SBA-15, the optimal values were obtained as the parameters of contact time = 30 min, pH = 8, temperature = 65 °C, adsorbent amount = 0.01 g, stirring rate = 90 rpm and initial dye concentration = 100 mg/L. The kinetic and thermodynamic experiments were conducted on the adsorption process as well. The results of the experiments demonstrated that the total surface area and total pore volume of the adsorbent were 780 m2/g and 0.8483 cm3/g, respectively. Moreover, the surface adsorption process of Azure B followed the Langmuir's isothermal model, and kinetic data followed the surface adsorption of pseudo-second-order kinetic model. Besides, the values of ΔH° and ΔS° were 5409.32 j/mol and 37.28 j/mol K, respectively, and the maximum adsorption capacity of adsorbent was 166.66 mg/g.
https://arww.razi.ac.ir/article_1644_ffec8657707bc6ebf73335e8bd2eb8f5.pdf
2020-12-01
172
179
10.22126/arww.2021.5648.1186
Stem sweep ash
Azure B
Nano particles
SBA-15
Elham
Chiani
chiani_e@yahoo.com
1
Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
AUTHOR
Seyed Naser
Azizi
seyednaserazizi@yahoo.com
2
Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
LEAD_AUTHOR
Shahram
Ghasemi
sghasemi@umz.ac.ir
3
Department of Nano, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
AUTHOR
Salma
Ehsani Tilami
salmaehsani@yahoo.com
4
Department of Basic Science, Farhangian University, Tehran, Iran.
AUTHOR
Abo-Farha S.A., Comparative study of oxidation of some azo dyes by different advanced oxidation processes: Fenton like photo-fenton and photo-fenton-like, The Journal of American Science 6 (2010) 128-42.
1
Alipanahpour D.E., Ghaedi M., AsfaramA., Mehrabi F., Sadeghfar F., efficient adsorption of Azure B on to CNTs/Zn: ZnO @ Ni2P-NCs from aqueous solution in the presence of ultrasound wave based on multivariate optimization, Journal Of Industrial and Engineering Chemistry 74 (2019) 55–62.
2
Asif J.K., Jinxi S., Khalid A., Fozia R., Mesoporous silica MCM-41, SBA-15 and derived Bridged polysilsesquioxane SBA-PMDA 1 for the selective removal of textile reactive dyes from wastewater, Journal of Molecular Liquids 298 (2019) 1-10.
3
Azizi S.N., Ghasemi S., Kavian S., Synthesis and characterization of NaX nanozeolite using stem sweep as silica source and application of Ag-modified nanozeolite in electrocatalytic reduction of H2O2, Biosensors and Bioelectronics 62 (2014) 1-7.
4
Azizi S.A., Ghasemi S., Chiani E., Nickel/mesoporous silica (SBA-15) modified electrode: An effective porous material for electrooxidation of methanol, Electrochimica Acta 88 (2013) 463–472.
5
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6
Daneshvar N., Salari D., Khataee A.R., Photocatalytic degradation of azo dye acid red 14 in water: investigation of the effect of operational parameters, Journal of Photochemistry and Photobiology A: Chemistry A 157 (2003) 111-116.
7
Duraisamy R., Kiruthigam P., Hirpaye B., Berekute A., Adsorption of azure B dye on rice husk activated carbon: equilibrium, kinetic and thermodynamic studies, International Journal of Water Research 5 (2015) 18-28.
8
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9
Gök Ö., Özcan A.S., Özcan A., Adsorption behavior of a textile dye of Reactive Blue 19 from aqueous solutions onto modified bentonite, Applied Surface Science 256 (2010) 5439-5443.
10
Gu X., He M., Shi Y., Li Z., La-containing SBA-15/H2O2 systems for the microwave assisted oxidation of alignin model phenolic monomer, Maderas-Cienciay Tecnologia 12 (2010) 181-188.
11
Huang C.H., Chang K.P., Ou H.D., Chiang Y.C, Wang C.F., Adsorption of cationic dyes onto mesoporous silica, Microporous Mesoporous Mater 141 (2011) 102–109.
12
Kalapathy U., Proctor A., Shultz J., A simple method for production of pure silica from rice hull ash, Bioresource Technology 73 (2000) 257-262.
13
Kikuchi R., Application of coal ash to environmental improvement transformation into zeolite, potassium fertilizer and FGD absorbent, Resources Conservation and Recycling 27 (1999) 333-346.
14
Kumaran G.M., Garg S., Soni K., Kumar M., Sharma L.D., Rao K.S.R., Dhar G.M., Effect of Al-SBA-15 support on catalytic functionalities of hydrotreating catalysts, II effect of variation of molybdenum and promoter contents on catalytic functionalities, Industrial & Engineering Chemistry Research 46 (2007) 4747-475.
15
Kyzas G.Z., Lazaridis N.K., Mitropoulos A.C., Removal of dyes from aqueous solutions with untreated coffee residues as potential low-cost adsorbents: equilibrium, reuse and thermodynamic approach, Chemical Engineering Journal 189 (2012) 148-59.
16
Li X., Zhang J., Liu B., Liu J., Wang C., Chen G., Hydrodeoxygenation of lignin-derived phenols to produce hydrocarbons over Ni/Al-SBA-15 prepared with different impregnants, Fuel 243 (2019) 314-321
17
Lotito M., De Sanctis M., Di Iaconi C., Bergna G., Textile wastewater treatment: aerobic granular sludge vs activated sludge systems, Water Research 54 (2014) 337-346.
18
Mouni L., Belkhiri L., Bollinger G.C., Bouzaza A., Assadi A., Tirri T., Dahmoune F., Madani K., Remini H., Removal of methylene blue from aqueous solutions by adsorption on Kaolin: kinetic and equilibrium studies, Applied Clay Science 153 (2018) 38- 45.
19
Muhammad A., Shafeeq A., Butt M.A., Rizvi Z.H., Chughtai M.A., Rehman S., Decolorization and removal of COD and BOD from raw and biotreated textile dye bath effluent through advanced oxidation processes (AOPS), Brazilian Journal of Chemical Engineering 25 (2008) 453-459.
20
Nesic A.R., Kokunesoski M.J., Volkov-Husovic T.D., Sava J.V., New method for quantification of dye sorption using SBA mesoporous silica as a target sorbent, Environmental Monitoring and Assessment 188 (2016) 160-172.
21
Qiang T., Song Y., Zhao J., Li J., Controlled incorporation homogeneous Ti-doped SBA-15 for improving methylene blue adsorption capacity, Journal of Alloys and Compounds 770 (2019) 792-802.
22
Speybroeck M.V., Barillaro V., Thi T.D., Mellaerts R., Martens J., Humbeeck J.V., Vermant J., Annaert P., Mooter G.V., Augustijns P., Ordered mesoporous silica materials SBA-15: A broad spectrum formulation platform for poorly soluble drugs, Journal of Pharmaceutical Sciences 98 (2008) 2648-2658.
23
Tsai C.H., Chang W.C., Saikia D., Wu C.E., Kao H.M., Functionalization of cubic mesoporous silica SBA-16 with carboxylic acid via one-pot synthesis route for effective removal of cationic dyes, Journal of Hazardous Materials 309 (2016) 236-248.
24
Thuadaij N., and Nuntiya A., Preparation of nanosilica powder from rice husk ash by precipitation method, Chiang Mai Journal of Science 35 (2008) 206-211.
25
Ulrich K., Galvosas P., Karger J., Grinber F., Vernimmen J., Meynen V., Cool P., Self-Assembly and diffusion of block copolymer templates in SBA-15 nanochannels, Journal of Physical Chemistry B 114 (2010) 4223-4229.
26
Xiangping Li., Han Y., Jianguang, Zhang., Juping, L., Guanyi, C., Effect of organic template removal approaches on physiochemical characterization of Ni/Al-SBA-15 and eugenol hydrodeoxygenation, Journal of Solid State Chemistry 282 (2019) 121063
27
Xiao L.P., Li J.Y, Jin H.X, Xu R.R., Removal of organic templates from mesoporous SBA-15 at room temperature using UV/dilute H2O2, Microporous and Mesoporous Materials 96 (2006) 413-418.
28
Yanling D., Bin L., Shuying Z., Jingxiang Z., Xiaoguang W., Qinghai C., Removal of methylene blue from coloured effluents by adsorption onto SBA‐15, Nanomaterials 86 (2010) 616-619.
29
Zhu G.Q., Wang F.G., Xu K.J., Ga Q.C., Li Y.Y., Structure and properties of carboxymethyl chitosan film modified by poly(l-lactic acid), Asian Journal of Chemistry 26 (2014) 33-35.
30
ORIGINAL_ARTICLE
The trapping of colloid particles in porous media: Mechanisms and applications, review
This review paper will serve to explain how a particle is trapped on a porous media, and describe the mobility of those particles when passing through a media. It also presents the different parameters that play an important role on the trapping mechanism and the role of biofilm formation. The deposition and trapping mechanism of particles in porous media is governed by the action of different mechanisms such as interception, sieving, diffusion, gravitational and Van Der Waals forces, Brownian diffusion, and inertia. The particle retention through the porous media leads to the formation of a biofilm and the clogging of the media. The understanding of particle retention, clogging, and biofilm formation is interesting because it plays a major role in soil recovery process such as bioremediation, biosorption and filtration (on sand and activated carbon) used for degradation of particles (colloids and microorganisms) and harmful contaminants (heavy metals, drugs) by microorganisms.
https://arww.razi.ac.ir/article_1645_9dfb8e711f7df8f6e35346275912c703.pdf
2020-12-01
180
188
10.22126/arww.2020.1645
Retention
Biolloids
Biofilm
Clogging
Bioremediation
Bouchenak Khelladi
Racha Medjda
1
Department of Hydraulics, Faculty of Technology, University of Tlemcen, Tlemcen-Algeria, France.
LEAD_AUTHOR
Chiboub Fellah
Abdelghani
2
Department of Hydraulics, Faculty of Technology, University of Tlemcen, Tlemcen-Algeria, France.
AUTHOR
Pontié
Maxime
3
Department of Chemistry, Group Analysis and Processes, Faculty of Sciences, University of Angers, Angers, France.
AUTHOR
Guellil Fatima
Zohra
4
Department of Chemistry, Faculty of Chemistry, University of Tlemcen, Tlemcen- Algeria, France.
AUTHOR
Al-Mulla Emad Abbas J., Jabbar F.H., AL-Hamadani Rawaa Fahim C., Porous media for removal of organic and inorganic contaminants, Nano Biomedicine and Engineering 10 (2018) 104-116.
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2
Bai Hongjuan, Lassabatere Laurent, and Lamy E., Colloid transport in aggregated porous media with intra- and inter-aggregate porosities, Industrial & Engineering Chemistry Research (2018).
3
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8
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