K Afed Ullah - School of Environment, Harbin Institute of Technology, Harbin, China- Department of Civil Engineering, University of Engineering and Technology Peshawar, Peshawar,Pakistan
J Jiang - School of Environment, Harbin Institute of Technology, Harbin, China- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
P Wang - School of Environment, Harbin Institute of Technology, Harbin, China

Surface waters are the most important economic resource for humans which provide waterfor agricultural, industrial and anthropogenic activities. Surface water quality plays vital role in protectingaquatic ecosystems. Unplanned urbanization, intense agricultural activities and deforestation are positivelyassociated with carbon, nitrogen and phosphorous related water quality parameters. Multiple buffersgive robust land use land cover and water quality model and highlight the impacts of land use land covercharacteristics on water quality parameters at various scales which will guide watershed managers forparticular application of best management practices to enhance stream health. Traditionally, water qualitydata collections are based on discrete sampling and were analyzed through statistical techniques which weredesigned for spatially isolated measurements. Traditional multivariate statistical approaches uncover hiddeninformation in water quality data but they are unable to expose spatial relationship. The complexity ofinformation 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 usingvarious statistical approaches. Every statistical method has unique purpose, application and solves differentproblems. This review article pinpoints that how statistical approaches in combination with spatial scale canbe applied to develop statistically significant land use land cover- water quality relationship for better waterquality evaluation.

Agricultural activities; Land use land cover (LULC); Statistical approach; Urbanization; Water quality