Abstract
Pearson's correlation was used to determine relations between infiltration and affecting factors using flow monitoring data measured in 24 areas with different characteristics. Factors showed relatively high correlations than others were indexed to determine infiltration rates of the study area. Among 8 factors(service area, sewer length, sewer diameter, multiplier of sewer length and diameter, number of manholes, population, number of properties, number of households) tested, the multiplier of sewer length and diameter, the number of population and the number of household in each service area indicated higher correlation coefficient(>0.8) than others. The goodness of fitness of linear regressions between infiltration and the factors followed the order: sewer length and diameter(0.68)> population(0.65)> number of household(0.60). Infiltration rates calculated by the multiplier of sewer length and diameter, the number of population and the number of household in each service area were 0.046~1.0396 $m^{3}/d{\cdot}mm-km$, 0.0917~1.7355 $m^{3}/capita{\cdot}d$, 0.196~4.529 $m^{3}/household {\cdot}d$ respectively. After sewerage rehabilitation work of the area, the infiltration rates calculated by above factors with high correlations are expected to be used for comparing effectiveness of the work once they are estimated under the same flow measuring conditions.
