Advertisement

Remote sensing-based water quality assessment for urban rivers: a study in linyi development area

  • Sheng Miao
  • Chao LiuEmail author
  • Binjie Qian
  • Qun Miao
Water Environmental Pollution and State of the Art Treatment Technologies
First Online:
  • 76 Downloads

Abstract

Nowadays, urban rivers play an important role in city development and make great contributions to urban ecology. Most urban rivers are the drinking water sources and water quality is extremely critical. The current assessment method in national standard of China has multiple limitations; therefore, this paper introduces an advanced assessment, that is, Canadian Water Quality Index (CWQI). This method can help to provide comprehensive and objective water quality assessment for the urban rivers. Moreover, CWQI can prevent waste of the water resource, since current assessment is pessimistic and tent to underestimate water samples to a lower grade. Linyi development area is selected as study region and CWQI method is applied to assess two major urban rivers within the area. The water monitoring data from 2014 to 2017 is acquired in 24 parameters. Since the CWQI calculation is still based on traditional water quality measurement in parameters, there will be a huge cost when increasing research scale and accuracy. In this paper, remote sensing technique is employed to develop models of CWQI scores from satellite data. By utilizing 23 selected monitoring instances and matching satellite data, linear regression analysis shows that red band data has highest correlation with CWQI in both two urban rivers in the study region. In addition, two testing datasets with five instances for each river are used to validate the RS-based CWQI models and the results show that testing datasets can be fitted well. With the models, CWQI distribution diagrams are generated and assist both spatial and temporal analysis. Experimental results show that the proposed approach can indicate actual water quality pattern which is validated by field visit. The proposed approach in this paper has satisfying effectiveness and robustness.

Keywords

Remote sensing Water quality index Urban rivers Spatial temporal analysis 
This is a preview of subscription content, log in to check access.

Notes

References

  1. Al-Janabi ZZ, Al-Obaidy AHMJ, Al-Kubaisi AR (2015) Applied of ccme water quality index for protection of aquatic life in the tigris river within baghdad city. J of Al-Nahrain Uni 18(2):99–107CrossRefGoogle Scholar
  2. Al-yassiry TM, Salman JM (2014) Ecological assessment of sewage in hilla city/iraq by canadian water quality index (cwqi). International Journal of Advanced Life Science 7(2):197–203Google Scholar
  3. Bordalo AA, Teixeira R, Wiebe WJ (2006) A water quality index applied to an international shared river basin: the case of the douro river. Environ Manag 38(6):910–920CrossRefGoogle Scholar
  4. Brown RM, McClelland NI, Deininger RA, O’Connor MF (1972) A water quality index—crashing the psychological barrier. In: Indicators of environmental quality, Springer, pp 173–182Google Scholar
  5. Carpenter D, Carpenter S (1983) Modeling inland water quality using landsat data. Remote Sens Environ 13(4):345–352CrossRefGoogle Scholar
  6. Comrey AL, Lee HB (2013) A first course in factor analysis. Psychology PressGoogle Scholar
  7. Davies JM (2006) Application and tests of the canadian water quality index for assessing changes in water quality in lakes and rivers of central north america. Lake Reservoir Manage 22(4):308– 320CrossRefGoogle Scholar
  8. Dede OT, Sezer M (2017) The application of canadian water quality index (cwqi) model for the assessment of water quality of aksu creek. J Fac Eng Archit Gazi Univ 32(3):909–917Google Scholar
  9. Farzadkia M, Djahed B, Shahsavani E, Poureshg Y (2015) Spatio-temporal evaluation of yamchi dam basin water quality using canadian water quality index. Environ Monit Assess 187(4):168CrossRefGoogle Scholar
  10. Fruchter B (1954) Introduction to factor analysisGoogle Scholar
  11. GB3838-2002 (2002) Environmental quality standards for surface waterGoogle Scholar
  12. Gu Q (2014) A study on drinking water quality variation in zhejiang province. Zhejiang University, PhD thesisGoogle Scholar
  13. Horton RK (1965) An index number system for rating water quality. J Water Pollut Control Fed 37(3):300–306Google Scholar
  14. Hurley T, Sadiq R, Mazumder A (2012) Adaptation and evaluation of the canadian council of ministers of the environment water quality index (ccme wqi) for use as an effective tool to characterize drinking source water quality. Water Res 46(11):3544–3552CrossRefGoogle Scholar
  15. Liu C, Cao XJ, Wang C, Sun JJ, Gu YT (2012) Study on the water quality and quantity scheduling scheme in xinxue river constructed wetland of China under the constraint condition of class iii of surface water quality. In: Advanced materials research, trans tech publ, vol 374 pp 923–927Google Scholar
  16. Liu L, Wu L (2016) Review on surface water quality index assessment method in foreign countries. Water Resour Prot 32(1):86–90Google Scholar
  17. Luansheng Shi CX (2006) The surface water qualitiy assessment in guangdong province. Guangdong Water Resources and Hydropower 6:58–61Google Scholar
  18. Miao Q, Liu C, Tan X, Liu Z, Gao Y (2009a) Eutrophication assessment of nansi lake, China through remote sensing technology. In: 2009. FCC’09 international conference on future computer and communication, IEEE, pp 28-31Google Scholar
  19. Miao Q, Tan X, Liu Z, Gao Y (2009b) Improved fuzzy mathematics method to evaluate water quality of qingdao dagu river, china. In: 2009. FSKD’09. Sixth international conference on fuzzy systems and knowledge discovery, vol 7. IEEE, pp 39-42Google Scholar
  20. Miao Q, Sun JJ, Xue S, Bian L, Wang XP (2012) Research of the model boundary problem of xinxue river constructed wetland. In: Applied mechanics and materials, trans tech publ, vol 178, pp 1050–1054Google Scholar
  21. Nemerow NL (1974) Scientific stream pollution analysis. McGraw-HillGoogle Scholar
  22. Rickwood C, Carr G (2009) Development and sensitivity analysis of a global drinking water quality index. Environ Monit Assess 156(1-4):73CrossRefGoogle Scholar
  23. Rocchini R, Swain L (1995) The british columbia water quality index. Water Quality Branch, EP Department, BC, Ministry of Environment, Land and Park, Victoria, BC, Canada 13Google Scholar
  24. Roy DP, Wulder M, Loveland TR, Woodcock C, Allen R, Anderson M, Helder D, Irons J, Johnson D, Kennedy R et al (2014) Landsat-8: science and product vision for terrestrial global change research. Remote Sens Environ 145:154–172CrossRefGoogle Scholar
  25. Saffran K (2001) Canadian water quality guidelines for the protection of aquatic life, ccme water quality index 1, 0. user’s manual. excerpt from publication no. 1299. Tech. rep., ISBN 1-896997-34-1Google Scholar
  26. Survey UG (2015) Landsat processing detailsGoogle Scholar
  27. Thiemann S, Kaufmann H (2002) Lake water quality monitoring using hyperspectral airborne data—a semiempirical multisensor and multitemporal approach for the mecklenburg lake district, germany. Remote Sens Environ 81(2-3):228–237CrossRefGoogle Scholar
  28. Williamson A, Grabau W (1974) Sediment concentration mapping in tidal estuaries. NASA Special Publication 351:1347Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Qingdao UniversityQingdaoChina
  2. 2.Qingdao University of TechnologyQingdaoChina

Personalised recommendations

Cite article

Buy options