Kjeld Schaarup-Jensen

Risk analysis using stochastic reliability methods applied to two cases of deterministic water quality models

Abstract For the computation of extreme event statistics with respect to pollutant loads and environmental effects, the uncertainty in model parameters of deterministic models and the inherent stochastic variability in input variables have to be taken into account. Two stochastic reliability methods—combinations of the First Order Reliability Method (FORM) with Directional Simulation with Importance Sampling (FORM/DIS) or with Latin Hypercube Sampling (FORM/LHS)—were used for risk analysis related to acute environmental effects. The range of probabilities of exceedence at which these combined methods are more efficient than crude Monte Carlo simulation (CMC) or Latin Hypercube Sampling (LHS) only, was investigated. Their efficiency in relation to the required number of model simulations to accurately estimate the small exceedence probabilities of extremes compared to that of Monte Carlo simulation was demonstrated with two case studies: (1) to estimate exceedence probabilities of limit pollutant concentrations in a lake after a loading event using a simple numerical model. At exceedence probabilities smaller than 0.1 both FORM/DIS and FORM/LHS gave more accurate results than crude Monte Carlo simulation, and this improvement increased rapidly with decreasing probabilities. (2) to estimate the frequencies of occurrence of extremely low dissolved oxygen (DO) concentrations in a stream receiving multiple COD loads from combined sewer overflows and storm water outlets using a D issolved O xygen S tream MO del (DOSMO). In this example the relationships between stochastic parameters and the model output are strongly non-linear and the number of loading events that determine the in-stream DO concentration is variable. Here, FORM/LHS was more efficient than than FORM/DIS in estimating very small probabilities. A general limit value for the probability of exceedence below which FORM/LHS or FORM/DIS were more efficient than Crude Monte Carlo simulation and Latin Hypercube Sampling could not be given, but they were lower for the complex stream DO model than for the simple lake model. Based on these very different case studies it is concluded that the methods can generally be applied to a large variety of numerical models within the field of environmental engineering.

A Danish sewer research and monitoring station

A research and monitoring station has been established as a part of the intercepting sewer from Frejlev, a small town of 2000 inhabitants 7 km Southwest of Aalborg, Denmark. The purpose is to perform continuous high quality time series of flow as well as waste water and runoff water characteristics. Based on these future time series, research will be carried out in order to establish knowledge on dry weather characteristics, and rainfall-runoff relationships including the variability of relevant storm water pollutants. Furthermore, the measurements can form the basis of a better understanding of transport and transformation of pollutants in combined sewers including suspended and bed load characteristics, sedimentation and resuspension.

On hydraulic and pollution effects of converting combined sewer catchments to separate sewer catchments

The overall objective of this paper is to contribute to the standing debate concerning the advantages of separate sewer systems compared to traditional combined sewer systems. By a case study this investigation reveals that transformation of part of a town from being serviced with combined sewer systems to become serviced with separate sewer systems decreases the volumes of storm water and pollutants diverted to the waste water treatment plant and discharged as combined sewer overflow. This happens at the expense of an increase in volumes of storm water and pollutant loads diverted to local receiving waters when detention ponds are not built-in the new separate sewer systems. It is concluded that consequences can be fatal for receiving waters, if no retention of pollutants is integrated into the system.

Probabilistic modelling of combined sewer overflow using the First Order Reliability Method

This paper presents a new and alternative method (in the context of urban drainage) for probabilistic hydrodynamical analysis of drainage systems in general and especially prediction of combined sewer overflow. Using a probabilistic shell it is possible to implement both input and parameter uncertainties on an application of the commercial urban drainage model MOUSE combined with the probabilistic First Order Reliability Method (FORM). Applying statistical characteristics on several years of rainfall, it is possible to derive a parameterization of the rainfall input and the failure probability and return period of combined sewer overflow to receiving waters can be found.