Monitoring and statistical modelling of sedimentation in gully pots

Abstract

Gully pots are essential assets designed to relief the downstream system by trapping solids and attached pollutants suspended in runoff. This study applied a methodology to develop a quantitative gully pot sedimentation and blockage model. To this end, sediment bed level time series from 300 gully pots, spanning 15 months, were collected. A generalised linear mixed modelling (GLMM) approach was applied to model and quantify the accumulation of solids in gully pots and to identify relevant physical and catchment properties that influence the complex trapping processes. Results show that the retaining efficiency decreases as sediment bed levels increase. Two typical silting evolutions were identified. Approximately 5% of all gully pots experienced progressive silting, eventually resulting in a blockage. The other gully pots show stabilising sediment bed levels. The depth of the sand trap, elapsed time since cleaning and the road type were identified to be the main properties discriminating progressive accumulation from stabilising sediment bed levels. Furthermore, sediment bed levels exhibit no residual spatial correlation, indicating that the vulnerability to a blockage is reduced as adjacent gully pots provide a form of redundancy. The findings may aid to improve maintenance strategies in order to safeguard the performance of gully pots.