Skip to main content
SpringerLink
Log in

A survey of smart water quality monitoring system

  • Review Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

The smart water quality monitoring, regarded as the future water quality monitoring technology, catalyzes progress in the capabilities of data collection, communication, data analysis, and early warning. In this article, we survey the literature till 2014 on the enabling technologies for the Smart Water Quality Monitoring System. We explore three major subsystems, namely the data collection subsystem, the data transmission subsystem, and the data management subsystem from the view of data acquiring, data transmission, and data analysis. Specifically, for the data collection subsystem, we explore selection of water quality parameters, existing technology of online water quality monitoring, identification of the locations of sampling stations, and determination of the sampling frequencies. For the data transmission system, we explore data transmission network architecture and data communication management. For the data management subsystem, we explore water quality analysis and prediction, water quality evaluation, and water quality data storage. We also propose possible challenges and future directions for each subsystem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • ADES (2008) ADES groundwater national portal.http://www.ades.eaufrance.fr. Cited jun 2014

  • Adomavicius G, Tuzhilin A (2001) Expert-driven validation of rule-based user models in personalization applications. Data Mining and Knowledge Discovery 5(1–2):33–58

  • Aitken DJ, Gooding CP (2010) U.S. Patent No. 7,852,855. U.S. Patent and Trademark Office, Washington

    Google Scholar 

  • Allen M, Preis A, Iqbal M, Whittle AJ (2012) Case study: a smart water grid in Singapore. Water Pract Technol 7(4)

  • Banna MH, Imran S, Francisque A, Najjaran H, Sadiq R, Rodriguez M, Hoorfar M (2013) Online drinking water quality monitoring: review on available and emerging technologies. Critical Reviews in Environmental Science and Technology, (just-accepted)

  • Beckers CV, Chamberlain SG, Grimsrud GP (1972) Quantitative methods for preliminary design of water quality surveillance systems. Socioeconomic Environmental Studies Series Report No. EPA-R5-72-001. US EPA, Washington

    Google Scholar 

  • Box GE, Pierce DA (1970) Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. J Am Stat Assoc 65(332):1509–1526

    Article  Google Scholar 

  • Bughin J, Chui M, Manyika J (2010) Clouds, big data, and smart assets: ten tech-enabled business trends to watch. McKinsey Q 56(1):75–86

    Google Scholar 

  • Canter LW (1985) River water quality monitoring. Lewis Publishers, Inc., Chelsea

    Google Scholar 

  • Chen Q, Zhang Y, Hallikainen M (2007) Water quality monitoring using remote sensing in support of the EU water framework directive (WFD): a case study in the gulf of Finland. Environ Monit Assess 124(1–3):157–166

    Article  CAS  Google Scholar 

  • Chen Y, Shu J, Zhang S, Liu L, Sun L (2009) Data fusion in wireless sensor networks. In Electronic Commerce and Security, 2009. ISECS'09. Second International Symposium on (Vol. 2, pp. 504-509). IEEE

  • Cheng S (2003) Heavy metal pollution in China: origin, pattern and control. Environ Sci Pollut Res 10(3):192–198

    Article  CAS  Google Scholar 

  • Chilundo M, Kelderman P (2008) Design of a water quality monitoring network for the Limpopo river basin in Mozambique. Phys Chem Earth Parts A/B/C 33(8):655–665

    Article  Google Scholar 

  • Chinese Center for Disease Control and Prevention (2014) http://www.chinacdc.cn/jkzt/hjws/hjws/201103/t20110314_28158.htm. Acessed Dec 2014

  • Clemson University (2013) http://www.clemson.edu/public/impacts/13spring/stories/intelligent_river.html. Acessed Dec 2014

  • Deininger RA, Males RM (2001) Design of early warning and predictive source-water monitoring systems. american water works association

  • Deng JL (2002) The foundation of grey theory. Huazhong University of Science and Technology Press, Wuhan, pp 22–26, 1

    Google Scholar 

  • Department of Environment and Conservation (2011) Real-time water quality monitoring program. http://www.env.gov.nl.ca/env/waterres/rti/rtwq/index.html. Accessed Dec, 2014

  • Drake CH (1985) On-line water quality monitoring. In 5. International Environment and Safety Conference, London(UK), 16-19 Sep 1985 (Vol. 1985)

  • Duan Q, Ajami NK, Gao X, Sorooshian S (2007) Multi-model ensemble hydrologic prediction using Bayesian model averaging. Adv Water Resour 30(5):1371–1386.1

    Article  Google Scholar 

  • Dubois E, Fasson J, Donny C, Chaput E (2010) Enhancing TCP based communications in mobile satellite scenarios: TCP peps issues and solutions. In advanced satellite multimedia systems conference (asma) and the 11th signal processing for space communications workshop (spsc), 2010 5th (pp. 476-483). IEEE

  • Dzemydienė D, Maskeliūnas S, Jacobsen K (2008) Sustainable management of water resources based on web services and distributed data warehouses. Technol Econ Dev Econ 14(1):38–50

    Article  Google Scholar 

  • Edwards AMC, Thornes JB (1973) Annual cycle in river water quality: a time series approach. Water resources research, 9(5), 1286-1295

  • EPA (2014) United States Environmental Protection Agency http://water.epa.gov/type/watersheds/monitoring/monintr.cfm. Accessed Jun 2014

  • HECWFS/Huron to Erie Connecting Waterways Forecasting System (2007) http://glos.us/data-tools/huron-erie-connecting-waterways-forecasting-system. Acessed Jun 2014 200

  • Fang X, Misra S, Xue G, Yang D (2012) Smart grid-the new and improved power grid: a survey. Commun Surv Tutorials, IEEE 14(4):944–980

    Article  Google Scholar 

  • Feldman R (2014) Blue I Water Technologies http://www.siww.com.sg/media/smart-water-quality-monitoring-system-smart-water-networks-will-be-introduced-blue-i-water. Accessed Jun 2014

  • Fitzpatrick C (2010). Aquas Smart Water Solutions bring range to the UK

  • Fraternali P, Castelletti A, Soncini-Sessa R, Vaca Ruiz C, Rizzoli AE (2012) Putting humans in the loop: social computing for water resources management. Environ Model Softw 37:68–77

    Article  Google Scholar 

  • Frey M, Sullivan L (2004) Practical Application of Online Monitoring. Awwa Research Foundation

  • Gao J, Xiao Y, Liu J, Liang W, Chen CL (2012) A survey of communication/networking in smart grids. Futur Gener Comput Syst 28(2):391–404

    Article  Google Scholar 

  • Glasgow HB, Burkholder JM, Reed RE, Lewitus AJ, Kleinman JE (2004) Real-time remote monitoring of water quality: a review of current applications, and advancements in sensor, telemetry, and computing technologies. J Exp Mar Biol Ecol 300(1):409–448

    Article  Google Scholar 

  • GLATOS/Great Lakes Acoustic Telemetry Observation System (2009)

  • GLOS (2010) http://glos.us/. Acessed Jun 2014

  • Gómez JAD, Alonso CA, García AA (2011) Remote sensing as a tool for monitoring water quality parameters for Mediterranean Lakes of European Union water framework directive (WFD) and as a system of surveillance of cyanobacterial harmful algae blooms (SCyanoHABs). Environ Monit Assess 181(1–4):317–334

    Article  Google Scholar 

  • BC Government (2006) A compendium of working water quality guidelines for British Columbia. http://www.env.gov.bc.ca/wat/wq/BCguidelines/working.html#ref. Accessed Jun 2014

  • Gray NF (2008) Drinking water quality. Cambridge University Press

  • Gu L, Jia D, Vicaire P, Yan T, Luo L, Tirumala A, Krogh BH (2005) Lightweight detection and classification for wireless sensor networks in realistic environments. In Proceedings of the 3rd international conference on Embedded networked sensor systems (pp. 205-217). ACM

  • Gungor VC, Lambert FC (2006) A survey on communication networks for electric system automation. Comput Netw 50(7):877–897

    Article  Google Scholar 

  • Harmancioglu NB, Fistikoglu O, Ozkul SD, Singh VP, Alpaslan MN (1999) Water quality monitoring network design. Kluwer Academic Publishers, Dordrecht

    Book  Google Scholar 

  • Hasan R, Raghav A, Mahmood S, Hasan MA (2011) Artificial Intelligence in River Quality Assessment. In Information Management, Innovation Management and Industrial Engineering (ICIII), 2011 International Conference on (Vol. 1, pp. 491-495). IEEE

  • Hayes B (2008) Cloud computing. Commun ACM 51(7):9–11

    Article  Google Scholar 

  • He D, Zhang LX (2012) The water quality monitoring system based on WSN. In Consumer electronics, communications and networks (CECNet), 2012 2nd International Conference on (pp. 3661-3664). IEEE

  • Health Canada (2009) Guidelines for Canadian drinking water quality: Chlorine. http://www.hc-sc.gc.ca/ewh-semt/alt_formats/hecs-sesc/pdf/pubs/water-eau/chlorine-chlore/tech_doc_chlor-eng.pdf. Accessed Jun 2014

  • Health Canada (2013) http://hc-sc.gc.ca/ewh-semt/consult/_2011/ecoli/draft-ebauche-eng.php#a44 nerrs, (2014) http://www.nerrs.noaa.gov/Doc/SiteProfile/ACEBasin/html/modules/watqual/wmeutro.htm. Accessed Jun 2014

  • Hering D, Borja A, Carstensen J, Carvalho L, Elliott M, Feld CK, de Bund WV (2010) The european water framework directive at the age of 10: a critical review of the achievements with recommendations for the future. Sci Total Environ 408(19):4007–4019

    Article  CAS  Google Scholar 

  • Horton RE (1945) Erosional development of streams. Geol Soc Am Bull 56:281–283

    Article  Google Scholar 

  • Hu Y, Li VO (2001) Satellite-based internet: a tutorial. IEEE Commun Mag 39(3):154–162

    Article  Google Scholar 

  • Huang GH, Chang NB (2003) The perspectives of environmental informatics and systems analysis. J Environ Inform 1(1):1–7

    Article  Google Scholar 

  • IBM (2013) http://www-03.ibm.com/press/us/en/pressrelease/41387.wss. Accessed Jun 2014

  • Ioos (2008) http://www.ioos.noaa.gov/. Accessed Jun 2014

  • IOOS (2008) http://www.ioos.noaa.gov/. Accessed Jun 2014

  • IOOS (2013) http://www.ioos.noaa.gov/about/governance/ioos_report_congress2013.pdf. Acessed Jun 2014

  • Jiao ZP, Li W, Liu CF, Tian Y (2011) The database design of estuary environmental impact assessment system based on 3S. Procedia Environ Sci 10:2213–2217

    Article  CAS  Google Scholar 

  • Jin C, De-lin L, Fen-xiang M (2009) An improved ID3 decision tree algorithm. In computer science & education, 2009. ICCSE'09. 4th International conference on (pp. 127-130). IEEE.1

  • Jiong L, Zhigang C, Junaid KM (2009) TP-satellite: a new transport protocol for satellite IP networks. Aerosp ElectronSyst, IEEE Trans 45(2):502–515

    Article  Google Scholar 

  • Juan H, Xingqiao L, Liqiang C (2012) Design of a wireless water environment monitoring system based on ZigBee in aquaculture. Fish Modernization 39(1):34–39

    Google Scholar 

  • Karamouz M, Nokhandan AK, Kerachian R, Maksimovic Č (2009) Design of on-line river water quality monitoring systems using the entropy theory: a case study. Environ Monit Assess 155(1–4):63–81

    Article  CAS  Google Scholar 

  • Kennish MJ, Fertig B, Lathrop RG (2012) Assessment of nutrient loading and eutrophication in Barnegat Bay-Little Egg Harbor, New Jersey in support of nutrient management planning. Rutgers University

  • Krishna AK, Satyanarayanan M, Govil PK (2009) Assessment of heavy metal pollution in water using multivariate statistical techniques in an industrial area: a case study from Patancheru, Medak District, Andhra Pradesh, India. J Hazard Mater 167(1):366–373

    Article  CAS  Google Scholar 

  • Laanen ML (2007) Yellow matters: improving the remote sensing of coloured dissolved organic matter in inland freshwaters

  • Le Dinh T, Hu W, Sikka P, Corke P, Overs L, Brosnan S (2007) Design and deployment of a remote robust sensor network: experiences from an outdoor water quality monitoring network. In local computer networks, 2007. LCN 2007. 32nd IEEE Conference on (pp. 799-806). IEEE

  • Leone A, Chen D (2007) Implementation of an object oriented data model in an information system for water catchment management: java JDO and Db4o object database. Environ Model Softw 22(12):1805–1810

    Article  Google Scholar 

  • Liu J, Liu J, Reich J, Cheung P, Zhao F (2003) Distributed group management for track initiation and maintenance in target localization applications. In Information Processing in Sensor Networks (pp. 113-128). Springer Berlin Heidelberg

  • Loftis J, Ward R (1980) Cost-effective selection of sampling frequencies for regulatory water quality monitoring. Environ Int 3:297–302

    Article  Google Scholar 

  • Manache G, Melching CS (2008) Identification of reliable regression-and correlation-based sensitivity measures for importance ranking of water-quality model parameters. Environ Model Softw 23(5):549–562

    Article  Google Scholar 

  • Marce R, Rodríguez‐Arias MA, García JC, Armengol JOAN (2010) El Niño southern oscillation and climate trends impact reservoir water quality. Glob Chang Biol 16(10):2857–2865

    Article  Google Scholar 

  • Meng T, Wu C, Shang B, Gao C, Zhang Y (2011) Design of point to multi-point wireless communication system based on ZigBee. In wireless communications, networking and mobile computing (WiCOM), 2011 7th International Conference on (pp. 1-4). IEEE

  • Mutchek M (2013) Moving Towards Sustainable and Resilient Smart Water Grids: Networked Sensing and Control Devices in the Urban Water System. Arizona State University

  • Naddeo V, Zarra T, Belgirno V (2007) Optimization of sampling frequency for river water quality assessment according to Italian implementation of EU water framework directive. Environ Sci Policy 10:243–249

    Article  Google Scholar 

  • Naddeo V, Scannapieco D, Zarra T, Belgiorno V (2013) River water quality assessment: implementation of non-parametric test for sampling frequency optimization. Land Use Policy 30:197–205

    Article  Google Scholar 

  • Najah A, El-Shafie A, Karim OA, Jaafar O, El-Shafie AH (2011) An application of different artificial intelligences techniques for water quality prediction. Int J Phys Sci 6(22):5298–5308

    Google Scholar 

  • Nasirudin MA, Za'bah UN, Sidek O (2011) Fresh water real-time monitoring system based on wireless sensor network and GSM. In Open Systems (ICOS), 2011 I.E. Conference on (pp. 354-357). IEEE

  • NAWQA/National Water-Quality Assessment Program (2013) http://pubs.usgs.gov/of/2013/1160/pdf/OF13-1160.pdf. Acessed Jun 2014

  • Neamtu M, Ciumasu IM, Costica N, Costica M, Bobu M, Nicoara MN, De Alencastro LF (2009) Chemical, biological, and ecotoxicological assessment of pesticides and persistent organic pollutants in the Bahlui River, Romania. Environ Sci Pollut Res 16(1):76–85

    Article  Google Scholar 

  • Nemerow NL (1974) Scientific stream pollution analysis. McGraw-Hill.

  • NOAA (2009) http://www.nodc.noaa.gov/. Accessed Jun 2014

  • Papoutsa C, Hadjimitsis DG, Themistocleous K, PerdikouP, Retalis A, Toulios L (2010) Smart monitoring of water quality in Asprokremmos Dam in Paphos, Cyprus using satellite remote sensing and wireless sensor platform. In Proc. SPIE (Vol. 7831, p. 78310Q)

  • Payment P, Waite M, Dufour A (2003) Introducing parameters for the assessment of drinking water quality. Assessing microbial safety of drinking water, 47

  • Ramadan RA (2012) Towards Smart Egypt—The Role of Large Scale WSNs. In Advanced Machine Learning Technologies and Applications (pp. 203-212). Springer Berlin Heidelberg

  • Ritchie JC, Zimba PV, Everitt JH (2003) Remote sensing techniques to assess water quality. Photogramm Eng Remote Sens 69(6):695–704

    Article  Google Scholar 

  • Sanders T, Ward R, Loftis J, Steele T, Adrian D, Yevjevich V (1983) Design of networks for monitoring water quality. Water Resources Publications, Colorado

    Google Scholar 

  • Sharp WE (1971) A topologically optimum water-sampling plan for rivers or streams. Water Resour Res 7:1641–1646

    Article  Google Scholar 

  • Shin PS, Song YR, Choi YJ, Park YS (2009) Seoul (Korea) Online water quality monitoring of drinking water. In world environmental and water resources congress 2009@ sGreat Rivers (pp. 103-111) ASCE

  • Storey MV, van der Gaag B, Burns BP (2011) Advances in on-line drinking water quality monitoring and early warning systems. Water Res 45(2):741–747

    Article  CAS  Google Scholar 

  • Strobl RO, Robillard PD (2008) Network design for water quality monitoring of surface freshwaters: a review. J Environ Manag 87(4):639–648

    Article  Google Scholar 

  • Telci IT, Nam K, Guan J, Aral MM (2009) Optimal water quality monitoring network design for river systems. J Environ Manag 90(10):2987–2998

    Article  Google Scholar 

  • The Office of Waterworks Seoul (2014) http://arisu.seoul.go.kr. Accessed Dec, 2014

  • Thompson K, Kadiyala R (2014) Protecting water quality and public health using a smart grid. Procedia Eng 70:1649–1658

    Article  Google Scholar 

  • Trescott A, Park MH (2013) Remote sensing models using Landsat satellite data to monitor algal blooms in Lake Champlain. Water Sci Technol 67(5):1113–1120

    Article  CAS  Google Scholar 

  • U.S. Environmental Protection Agency Science and Ecosystem Support Division (2013) http://www.epa.gov/region4/sesd/fbqstp/Wastewater-Sampling.pdf. Acessed Dec 2014

  • UN/ECE (2000) Guidelines on Monitoring and Assessment of Transboundary Rivers. Task Force on Monitoring and Assessment, RIZA

  • US Geological Survey (USGS) (2000) Ground water atlas of the Unites States. United States Geological Survey, Reston, VA.http://pubs.usgs.gov/ha/ha730/index.html. Cited Jun 2014

  • USEPA (2005) Water Sentinel online water quality monitoring as an indicator of drinking water contamination, EPA 817-D-05-002. U.S. Environmental Protection Agency, Water Security Division, Washington

    Google Scholar 

  • USEPA (2009b) National primary drinking water regulations. http://water.epa.gov/drink/contaminants/upload/mcl-2.pdf. Accessed Jun 2014

  • USGS (2010) http://nhd.usgs.gov/. Accessed Jun 2014

  • USGS (2011) http://water.usgs.gov/nawqa/. Accessed Jun 2014

  • USGS (2014) http://waterdata.usgs.gov/nwis/qw. Acessed Jun 2014

  • Wang Z, Wang Q, Hao X (2009) The design of the remote water quality monitoring system based on WSN. In wireless communications, networking and mobile computing, 2009. WiCom'09. 5th international conference on (pp. 1-4). IEEE

  • Ward RC (1973) Data acquisition systems in water quality management. Socioeconomic Environmental Series Studies Report No. EPA-R5-73-014. US EPA, Washington

    Google Scholar 

  • WHO (2003) pH in Drinking-water: Background document for development of WHO Guidelines for Drinking-water Quality. http://www.who.int/water_sanitation_health/dwq/chemicals/en/ph.pdf. Accessed Jun 2014

  • World Meteorological Organization (1994) Guide to Hydrological Practice. WMO-No. 168, WMO, Geneva

  • Xie Z, Lou I, Ung WK, Mok KM (2012) Freshwater algal bloom prediction by support vector machine in Macau storage reservoirs. Mathematical problems in engineering, 2012

  • Xu L, Jiang T, Xie J, Zheng S (2010) Red tide algae classification using SVM-SNP and semi-supervised FCM. In education technology and computer (ICETC), 2010 2nd International Conference on(Vol. 1, pp. V1-389). IEEE

  • Yoon S, Ye W, Heidemann J, Littlefield B, Shahabi C (2011) SWATS: wireless sensor networks for steamflood and waterflood pipeline monitoring. Netw, IEEE 25(1):50–56

    Article  Google Scholar 

  • Zhao X, Qi Q, Zhao G, Zheng J (2012) Establishment and applications of fuzzy comprehensive evaluation model for city drinking water source quality assessment. Keji Daobao/ Science & Technology Review 30(11):53–56

    CAS  Google Scholar 

  • Zhu X, Li D, He D, Wang J, Ma D, Li F (2010) A remote wireless system for water quality online monitoring in intensive fish culture. Comput Electron Agric 71:S3–S9

    Article  Google Scholar 

Download references

Acknowledgments

This work has been supported by National Natural Science Foundation of China under Grant (No. 61272060), National Science and Technology Major Project (No. 2014ZX07104-006), the Hundred Talents Program of CAS (No. Y21Z110A10).

Author information

Authors and Affiliations

  1. Institute of Electronic Information & Technology, Chongqing Institutes of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

    Jianhua Dong, Guoyin Wang, Huyong Yan & Xuerui Zhang

  2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

    Ji Xu

Authors
  1. Jianhua Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guoyin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huyong Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ji Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xuerui Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xuerui Zhang.

Additional information

Responsible editor: Philippe Garrigues

Appendix

Appendix

Table 2 A summary of major projects/programs/trials
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dong, J., Wang, G., Yan, H. et al. A survey of smart water quality monitoring system. Environ Sci Pollut Res 22, 4893–4906 (2015). https://doi.org/10.1007/s11356-014-4026-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-014-4026-x

Keywords

Search

Navigation