Water quality trend at the upper part of johor river in relation to rainfall and runoff pattern - Hamza, Hasmida (2009)
Due to the fact that rainfall and runoff have a vital relationship to water quality, these hydrological variables are among the most dominants controlling factor on the variation of water quality. Trend analysis on time series data has proved to be a useful tool for effective water resources planning, design, and management since trend detection of hydrological variables such as streamflow and precipitation provides useful information on the possibility of change tendency of the variables in the future. Both ARIMA modelling approach (parametric method) and Mann-Kendall test (non-parametric method) were applied to analyses the water quality and rainfall-runoff data for Johor River recorded for a long period (2004 to 2007). SPSS Statistical Packages Software was used in performing ARIMA time series modelling and Microsoft Excel function was used for Mann-Kendall (MK) test. This study aims to investigate the water quality trend over a long period particularly at the upper part of the Johor River in relation to rainfall and runoff pattern using both parametric and non-parametric method. This study focusing on four parameters of nutrient types of pollutant (NH4, turbidity, colour and SS) and four parameters of chemical types of pollutant (PH, Al, Mn, Fe). Nutrient and chemical types of pollutant is more significant as major land use surrounding Johor River is agricultural activities and eroded river corridor problem was observed. MK test shows that all of the parameters investigated are significant at 95% confidence limit. Increasing trend was observed for turbidity, colour and SS while decreasing trend in PH, Al, Mn and Fe. Probability (P) value obtained is zero and others gave value near to zero shows that all of the water quality parameters have quiet similar trend with rainfall and flow. The results from the fitted ARIMA models indicate that all of the water quality parameter investigated was generated by AutoRegressive Integrated Moving Average (ARIMA) processes ranges from ARIMA (1,1,1) to (2,1,2). Colour, Turbidity, SS, NH4 and Mn follow a similar trend with rainfall-runoff pattern while PH, Al and Fe have the opposite trend compare to rainfall-runoff pattern.