A Statistical Approach for the Analysis and Forecasting of Water Quantity and Quality in King Talal Reservoir

Ahmad Bani Hani, Ahmad Jamrah, Sulieman Tarawneh


This study concentrated on presenting statistical methods for the use in studying and projecting quantity and quality variables in Zarka River, which is a main supplier of King Talal Reservoir (KTR). The quantity variable used was the flow, and the quality variables were (TSS, BOD5, COD, T-P, and T-N). The data collected for each variable covered a period of 156 months from the year 1988 till the end of the year 2000. The procedure used in analyzing the six variables includes auto, cross and vertical distance correlation at the point of direct discharge into KTR, which receives water from the mixing of Zarka River and the effluent of Samra wastewater treatment plant. Deterministic and stochastic forecasting of the six variables was used in finding the best model to be used in projection. The study results indicate that the exponential growth method yielded the least percentage of mean error for predicting TSS and T-P. The ARIMA model yielded the least percentage of mean error for BOD5 forecasting. None of the models satisfied the 10 percentage of mean error for BOD5 forecasting. Based on the percentage of mean error, the COD was best described by the quadratic method, the T-N was best predicted by the linear method, and the auto regression method succeeded most in predicting the flow.


water quality, King Talal Reservoir, deterministic forecasting, stochastic forecasting

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