Effective visualization for the spatiotemporal trend analysis of the water quality in the Nakdong River of Korea

Abstract Spatial and temporal trend analyses were performed to obtain more meaningful water quality information in table and three-dimensional graph forms. Using the statistical approaches of the Seasonal Mann–Kendall (SMK) and LOcally WEighted Scatter plot Smoother (LOWESS) methods, the trends of three water quality parameters, including Biochemical Oxygen Demand (BOD), Total Nitrogen (TN), and Total Phosphorus (TP) measured along the Nakdong River of Korea between 1992 and 2002 were analyzed. The trends of the slopes were calculated using the SMK method for two consecutive stations and years. These values are provided in the trend tables which indicate the extreme upward and downward trends. Also, three-dimensional graphs of the water quality in the Nakdong River were generated with respect to the distance from upstream of the river and time of month. From this study, it was concluded that these tables and three-dimensional maps could be used as a useful tool to provide the spatiotemporal trend information such as the hot spots/moments of improvement and deterioration in the water quality of the Nakdong River, with the present web-based information system.

[1]  H. B. Mann Nonparametric Tests Against Trend , 1945 .

[2]  Jurgen D. Garbrecht,et al.  VISUALIZATION OF TRENDS AND FLUCTUATIONS IN CLIMATIC RECORDS , 1994 .

[3]  Norman Jones,et al.  Managing temporal data in a comprehensive modeling environment , 2000 .

[4]  Seok Soon Park,et al.  A water quality modeling study of the Nakdong River, Korea , 2002 .

[5]  G. Joo,et al.  Vertical distribution of Microcystis population in the regulated Nakdong River, Korea , 2000, Limnology.

[6]  Frank Molkenthin,et al.  A virtual GIS-based hydrodynamic model system for Tamshui River , 2001 .

[7]  D. Hirst,et al.  Trends in stream water quality in Environmental Change Network upland catchments: the first 5 years. , 2001, The Science of the total environment.

[8]  Donald H. Burn,et al.  Hydrologic effects of climatic change in west-central Canada , 1994 .

[9]  Seok Soon Park,et al.  Design of a water quality monitoring network in a large river system using the genetic algorithm , 2006 .

[10]  Guebuem Kim,et al.  Factors controlling excess radium in the Nakdong River estuary, Korea: submarine groundwater discharge versus desorption from riverine particles , 2002 .

[11]  D. Tomasko,et al.  Water quality issues in the Nakdong River Basin in the Republic of Korea , 1999 .

[12]  Stuart G. Walesh Dad is out, POP is in , 1999 .

[13]  W. Cleveland Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .

[14]  Friedrich Recknagel,et al.  Prediction and elucidation of phytoplankton dynamics in the Nakdong River (Korea) by means of a recurrent artificial neural network , 2001 .

[15]  E. Bedrick,et al.  HYDROLOGICAL AND GEOCHEMICAL TRENDS AND PATTERNS IN THE UPPER RIO GRANDE, 1975 TO 1999 1 , 2004 .

[16]  R. Hirsch,et al.  Techniques of trend analysis for monthly water quality data , 1982 .

[17]  VIRGINIA USA WATER QUALITY, 1978 TO 1995: REGIONAL INTERPRETATION 1 , 2002 .

[18]  B. Silverman,et al.  Some Aspects of the Spline Smoothing Approach to Non‐Parametric Regression Curve Fitting , 1985 .

[19]  Dennis P. Lettenmaier,et al.  Trends in stream quality in the continental United States, 1978–1987 , 1991 .

[20]  John Cobourn INTEGRATED WATERSHED MANAGEMENT ON THE TRUCKEE RWER IN NEVADA1 , 1999 .

[21]  Heejun Chang,et al.  Multi-scale analysis of oxygen demand trends in an urbanizing Oregon watershed, USA. , 2008, Journal of environmental management.

[22]  W. Cleveland,et al.  Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting , 1988 .

[23]  William W. Walker WATER QUALITY TRENDS AT INFLOWS TO EVERGLADES NATIONAL PARK1 , 1991 .

[24]  Ping Zhang,et al.  An image construction method for visualizing managerial data , 1998, Decis. Support Syst..

[25]  Heejun Chang,et al.  Spatial analysis of water quality trends in the Han River basin, South Korea. , 2008, Water research.

[26]  William H. McDowell,et al.  Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems , 2003, Ecosystems.

[27]  Joseph N. Boyer,et al.  Maximizing Information from a Water Quality Monitoring Network through Visualization Techniques , 2000 .

[28]  D. Ahlfeld,et al.  ESTIMATING THE PROBABILITY OF EXCEEDING GROUNDWATER QUALITY STANDARDS1 , 1994 .

[29]  Heejun Chang Spatial and Temporal Variations of Water Quality in the Han River and Its Tributaries, Seoul, Korea, 1993–2002 , 2005 .

[30]  D. Helsel,et al.  Statistical methods in water resources , 2020, Techniques and Methods.

[31]  Donald H. Burn,et al.  Climate change effects on the hydrologic regime within the Churchill-Nelson River Basin , 1997 .

[32]  David B Baker,et al.  Trends in water quality in LEASEQ rivers and streams (northwestern Ohio), 1975-1995. Lake Erie Agricultural Systems for Environmental Quality. , 2002, Journal of environmental quality.

[33]  William G. Jacoby Loess: a nonparametric, graphical tool for depicting relationships between variables , 2000 .

[34]  Linfield Brown,et al.  Statistics for Environmental Engineers , 2002 .