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TREND DETECTION OF DRAINAGE WATER QUALITY IN EGYPT

IWRA World Water Congress 2003 Madrid Spain
IWRA WWC2003 - default topic
Author(s): Bahaa M. KHALIL Rasha M.S. El KHOLY & Shaden T. ABDEL GAWAD

Bahaa M. KHALIL Rasha M.S. El KHOLY & Shaden T. ABDEL GAWAD


Article:

Abstract

Water quality has been the principal limiting factor to water availability. The assessment of short and long-term water quality changes is a challenging problem. During the last two decades, there has been an increasing demand for monitoring water quality of many water bodies by regular measurements of various water quality parameters. The result has been the gradual accumulation of reliable water quality records and the examination of these data for trends (Hirsch et al., 1991). Without such information of the trend detection of the water bodies, effective water quality management remains impossible. The goal of this research is to identify water quality trends in Egyptian drains. The proposed analysis aims at determining how and to what degree several water quality parameters are changing, and characterizing the function and response of the drains to seasonal variability besides the correlation of load-discharge relationships and concentration-discharge relationship where the load-discharge relationships showed better correlation than that of concentrationdischarge relationships. Although several parameters are examined, particular emphasis is given herein to ascertaining trends in nutrients, organic matter and physical parameters. An examination of a vital drainage catchement in the eastern region of Egypt’s Nile Delta is conducted to describe the short-term trends. The data of five water quality variables (NO3, P, BOD, COD, TSS) and the discharge monitored on a monthly basis for the period August 1997-December 2002 were selected for this analysis. This study examines the time series of monthly values of water quality parameters and the discharge using statistical methods and the existence of trends and thus1presents the evaluation of the best-fitted trend models. Trends are detected using the regression analysis of the variables involved. Due to the wide variation over time in the statistical tests for nutrients, organic matter and physical parameters, the trend varied as for BOD, COD, TSS and NO3 concentrations it was downwards following the quadratic equation while the concentration of P showed no trend.

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