Small Scale Drainage Network Problem Detection Moving beyond the Concept of ARF. A Preliminary Study

Historically, assessments of drainage networks rely on applying design rainfall to existing catchments over a set return period. Nevertheless, for large catchments, it is unrealistic to believe that long-return-period rainfalls would impact the entire region. As a result, in the past, design rainfall was decreased based on the total area of the catchment using specific Areal Reduction Factors (ARF). This methodology presents difficulties because rainfall is localised; it may rain on one side of the street but not on the other. Achieving a statistically significant length of rainfall records and a sufficient density of rainfall gauges is challenging, which complicates the calculation of design rainfall depths. Further complications arise with uncertainties in projecting a design rainfall depth in a changing climate. Modern calculation methods are making obsolete the traditional approach of simply applying a design rainfall on a whole catchment. This paper presents an alternative approach to designing and then testing the performance of a system. This is done by applying the rainfall centre to various sub-catchments of the network, identifying the worst-case scenario, which, by definition, corresponds to the critical situation for the given return period. The proposed procedure is applied to an ideal catchment, specifically created for the purpose of evaluation (an ideal catchment, being theoretically “perfect”), which facilitates a better understanding of the problems, because a real catchment with its own critical issues can mask the underlying problems.