Predicting the efficiency of deposit removal during filter backwash

Abstract

The long-term performance of granular media filters used in drinking water treatment is ultimately limited by the efficiency of the backwash process. This paper demonstrates that it is possible to develop quantitative predictions of backwash efficiency based on filter operating conditions. An experimental investigation into the effect of backwash rate, type of coagulant, degree of clogging and accumulation of residual deposits (not removed by backwash) on the efficiency of fluidised bed filter backwash in laboratory scale filters is described. A natural raw water was used and small variations in the raw water characteristics (manifested as variations in raw water turbidity, temperature, pH, rate of head loss development and turbidity removal efficiency) within each set of experiments appeared to affect the efficiency of backwash in addition to the parameters varied deliberately. Stepwise linear regression and statistical analysis of model significance were used to determine which of several possible filtration and backwash parameters were the best predictors of backwash performance. Backwash rate, filter run time, rate of head loss development and mass of residual deposits accumulated during previous runs were found to be the best predictors of backwash efficiency for any given filter cycle. Floc deposits appeared to become more difficult to remove the longer they remained in the filter, while rate of head loss development appeared to provide some indication of the strength of cohesive deposits for filter runs of similar length. The efficiency of detachment of freshly deposited floc appeared to increase as the mass of residual deposits and mud balls in the filter increased. The numerical correlations developed in this study are site specific but the methodology can be adapted to any filter operation and backwash regime.