Document Type : REVIEW PAPER

Authors

1 School of Environment, Harbin Institute of Technology, Harbin, China

2 Department of Civil Engineering, University of Engineering and Technology Peshawar, Peshawar, Pakistan

3 School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Abstract

Surface waters are the most important economic resource for humans which provide water for agricultural, industrial and anthropogenic activities. Surface water quality plays vital role in protecting aquatic ecosystems. Unplanned urbanization, intense agricultural activities and deforestation are positively associated with carbon, nitrogen and phosphorous related water quality parameters. Multiple buffers give robust land use land cover and water quality model and highlight the impacts of land use land cover characteristics on water quality parameters at various scales which will guide watershed managers for particular application of best management practices to enhance stream health. Traditionally, water quality data collections are based on discrete sampling and were analyzed through statistical techniques which were designed for spatially isolated measurements. Traditional multivariate statistical approaches uncover hidden information in water quality data but they are unable to expose spatial relationship. The complexity of information in water quality data needs new statistical approaches which uncover spatiotemporal variability. This review briefly discusses influences of land use land cover characteristics on surface water quality, effects of spatial scale on land use land cover- water quality relationship, and water quality modeling using various statistical approaches. Every statistical method has unique purpose, application and solves different problems. This review article pinpoints that how statistical approaches in combination with spatial scale can be applied to develop statistically significant land use land cover- water quality relationship for better water quality evaluation.

Graphical Abstract

Land use impacts on surface water quality by statistical approaches

Highlights

  • Statistical techniques were easy and needed comparatively less data record as compared to water quality models
  • BHLR and GWR had the ability to analyze spatial variation between water quality and land use
  • Storm runoff drained more pollutants from land as compared to dry season
  • All land use did not contribute equal amount of pollutant to the nearby water body.

Keywords

Letters to Editor

GJESM Journal welcomes letters to the editor for the post-publication discussions and corrections which allows debate post publication on its site, through the Letters to Editor. Letters pertaining to manuscript published in GJESM should be sent to the editorial office of GJESM within three months of either online publication or before printed publication, except for critiques of original research. Following points are to be considering before sending the letters (comments) to the editor.

[1] Letters that include statements of statistics, facts, research, or theories should include appropriate references, although more than three are discouraged.
[2] Letters that are personal attacks on an author rather than thoughtful criticism of the author’s ideas will not be considered for publication.
[3] Letters can be no more than 300 words in length.
[4] Letter writers should include a statement at the beginning of the letter stating that it is being submitted either for publication or not.
[5] Anonymous letters will not be considered.
[6] Letter writers must include their city and state of residence or work.
[7] Letters will be edited for clarity and length.

CAPTCHA Image