Browse > Article
http://dx.doi.org/10.11614/KSL.2019.52.2.094

Spatial Variation in Land Use and Topographic Effects on Water Quality at the Geum River Watershed  

Park, Se-Rin (Department of Forestry and Landscape Architecture, Konkuk University)
Choi, Kwan-Mo (Department of Forestry and Landscape Architecture, Konkuk University)
Lee, Sang-Woo (Department of Forestry and Landscape Architecture, Konkuk University)
Publication Information
Abstract
In this study, we investigated the spatial variation in land use and topographic effects on water quality at the Geum river watershed in South Korea, using the ordinary least squares(OLS) and geographically weighted regression (GWR) models. Understanding the complex interactions between land use, slope, elevation, and water quality is essential for water pollution control and watershed management. We monitored four water quality indicators -total phosphorus, total nitrogen, biochemical oxygen demand, and dissolved oxygen levels - across three land use types (urban, agricultural, and forested) and two topographic features (elevation and mean slope). Results from GWR modeling revealed that land use and topography did not affect water quality consistently through space, but instead exhibited substantial spatial non-stationarity. The GWR model performed better than the OLS model as it produced a higher adjusted $R^2$ value. Spatial variation in interactions among variables could be visualized by mapping $R^2$ values from the GWR model at fine spatial resolution. Using the GWR model, we were able to identify local pollution sources, determine habitat status, and recommend appropriate land-use planning policies for watershed management.
Keywords
GWR; LULC; OLS; topography; water quality;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Abbaspour, K.C., J. Yang, I. Maximov, R. Siber, K. Bogner, J. Mieleitner and R. Srinivasan. 2007. Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology 333: 413-430.   DOI
2 Ahearn, D.S., R.W. Sheibley, R.A. Dahlgren, M. Anderson, J. Johnson and K.W. Tate. 2005. Land use and land cover influence on water quality in the last free-flowing river draining the western Sierra Nevada, California. Journal of Hydrology 313: 234-247.   DOI
3 An, K.J., S.W. Lee, S.J. Hwang, S.R. Park and S.A. Hwang. 2016. Exploring the non-stationary effects of forests and developed land within watersheds on biological indicators of streams using geographically-weighted regression. Water 8: 120.   DOI
4 Brunsdon, C., A.S. Fotheringham and M.E. Charlton. 1998. Geographically Weighted Regression - Modelling spatial nonstationarity. Journal of the Royal Statistical Society 47: 431-443.   DOI
5 Bu, H., W. Meng, Y. Zhang and J. Wan. 2014. Relationships between land use patterns and water quality in the Taizi River basin, China. Ecological Indicators 41: 187-197.   DOI
6 Clement, F., J. Ruiz, M.A. Rodriguez, D. Blais and S. Campeau. 2017. Landscape diversity and forest edge density regulate stream water quality in agricultural catchments. Ecological Indicators 72: 627-639.   DOI
7 Calder, I.R., J. Amezaga, B. Aylward, J. Bosch, L. Fuller, K. Gallop, A. Gosain, R. Hope, G. Jewitt, M. Miranda, I. Porras and V. Wilson. 2004. Forests and water - closing the gap between public and science perceptions. Water Science and Technology 49: 39-53.
8 Chang, H. 2008. Spatial analysis of water quality trends in the Han River basin, South Korea. Water Research 42: 3285-3304.   DOI
9 Clapcott, J.E., K.J. Collier, R.G. Death, E.O. Goodwin, J.S. Harding, D. Kelly and R.G. Young. 2012. Quantifying relationships between land use gradients and structural and functional indicators of stream ecological integrity. Freshwater Biology 57: 74-90.
10 Fotheringham, A.S., C. Brunsdon and M.E. Charlton. 2002. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, Wiley.
11 Gyawali, S., K. Techato, C. Yuangyai and C. Musikavong. 2013. Assessment of relationship between land uses of riparian zone and water quality of river for sustainable development of river basin, A case study of U-Tapao river basin. Thailand. Environmental Sciences 17: 291-297.
12 KMA (Korea Meteorological Administration). http://www.weather. go.kr/weather/climate/average_south.jsp.
13 Hwang, S.A., S.J. Hwang, S.R. Park and S.W. Lee. 2016. Examining the relationships between watershed urban land use and stream water quality using linear and generalized additive models. Water 8: 155.   DOI
14 Khatri, N. and S. Tyagi. 2015. Influences of natural and anthropogenic factors on surface and groundwater quality in rural and urban areas. Frontiers in Life Science 8: 23-39.   DOI
15 Kim, H.J. and S.W. Lee. 2011. Determinants of 5 major crimes in Seoul metropolitan area: Application of Mixed GWR model. Seoul Studies 12: 137-155.
16 Kim, J.W. and J.S. Um. 2013. Exploring NDVI gradient varying across landform and solar intensity using GWR: a case study of Mt. Geumgang in North Korea. Journal of the Korean Society for Geospatial Information System 21: 73-81.   DOI
17 Kim, K.Y. 2011. Identification of centers using GWR and spatial clustering methods: A case study on Daegu metropolitan city. Journal of the Korean Urban Geographical Society 14: 73-86.
18 Lee, S.W., S.J. Hwang, S.B. Lee, H.S. Hwang and H.C. Sung. 2009. Landscape-ecological approach to the relationships of land use patterns in watersheds to water quality characteristics. Landscape and Urban Planning 92: 80-89.   DOI
19 Li, C., F. Li, Z. Wu and J. Cheng. 2017. Exploring spatially varying and scale-dependent relationships between soil contamination and landscape patterns using geographically weighted regression. Applied Geography 82: 101-114.   DOI
20 Lee, S.W. 2013. Testing non-stationary relationship between the proportion of green areas in watersheds and water quality using geographically weighted regression model. Journal of the Korean Institute of Landscape Architecture 41: 43-51.   DOI
21 NIER (National Institute of Environmental Research). 2017. National Water Quality Assessment (2016). Available from http://webbook.me.go.kr/DLi-File/NIER/09/023/5642050.pdf.
22 Paliwal, R., P. Sharma and A. Kansal. 2007. Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS. Journal of Environmental Management 83: 131-144.   DOI
23 Park, S.R., H.J. Lee, S.W. Lee, S.J. Hwang, M.S. Byeon, G.J. Joo, K.S. Jeong, D.S. Kong and M.C. Kim. 2011. Relationships between land use and multi-dimensional characteristics of streams and rivers at two different scales. International Journal of Limnology 47: 107-116.   DOI
24 Tong, S.T.Y. and W. Chen. 2002. Modeling the relationship between land use and surface water quality. Journal of Environmental Management 66: 377-393.   DOI
25 Pratt, B. and H. Chang. 2012. Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales. Journal of Hazardous Materials 209-210: 48-58.   DOI
26 Richards, K., M. Sharp, N. Arnold, A. Gurnell, M. Clark, M. Tranter and W. Lawson. 1996. An integrated approach to modelling hydrology and water quality in glacierized catchments. Hydrological Processes 10: 479-508.   DOI
27 Shen, Z., X. Hou, W. Li, G. Aini, L. Chen and Y. Gong. 2015. Impact of landscape pattern at multiple spatial scales on water quality: A case study in a typical urbanized watershed in China. Ecological Indicators 48: 417-427.   DOI
28 Singh, S. and A. Mishra. 2014. Spatiotemporal analysis of the ef fects of forest covers on stream water quality in Western Ghats of peninsular India. Journal of Hydrology 519: 214-224.   DOI
29 Sliva, L. and D.D. Willams. 2001. Buffer zone versus whole catchment approaches to studying land use impact on river water quality. Water Research 35: 3462-3472.   DOI
30 Tu, J. and Z.G. Xia. 2008. Examining spatially varying relationships between land use and water quality using geographically weighted regression. Science of the Total Environment 407: 358-378.   DOI
31 Tu, J. 2011. Spatially varying relationships between land use and water quality across an urbanization gradient explored by geographically weighted regression. Applied Geography 31: 376-392.   DOI
32 Wang, Q., J. Ni and J. Tenhunen. 2005. Application of a geographically weighted regression analysis to estimate net primary production of Chinese forest ecosystems. Global Ecology and Biogeography 14: 379-393.   DOI
33 Wang, X. 2001. Integrating water quality management and land use planning in a watershed context. Journal of Environmental Management 61: 25-36.   DOI
34 Woli, K.R., T. Nagumo, K. Kuramochi and R. Hatano. 2004. Evaluating river water quality through land use analysis and N budget approaches in livestock farming areas. Science of Total Environment 329: 61-74.   DOI
35 Xiao, J. and W. Ji. 2007. Relating landscape characteristics to non-point source pollution in mine waste-located watersheds using geospatial techniques. Journal of Environmental Management 88: 529-551.
36 Yang, X.J. 2012. An assessment of landscape characteristics affecting estuarine nitrogen loading in an urban watershed. Journal of Environmental Management 94: 50-60.   DOI