Véronique Vandenberghe

Coupling a hydrological water quality model and an economic optimization model to set up a cost-effective emission reduction scenario for nitrogen

A modelling approach is presented that determines the most cost-effective set of reduction measures to reach an in-stream concentration target. The framework is based on the coupling of two models: the hydrological water quality model SWAT and an economic optimization model (Environmental Costing Model, ECM). SWAT is used to determine the relationship between the modelled in-stream concentration at the river basin outlet and the associated emission reduction. The ECM is used to set up marginal abatement cost curves for nutrients and oxygen demanding substances. Results for nitrogen are presented for the Grote Nete river basin in Belgium for the year 2006. Results show that the good status for total nitrogen can be reached in the study area. The most cost-effective measures are more productive dairy cattle, implementing basic measures as defined in the WFD, winter cover crops, improved efficiency of WWTP, enhanced fodder efficiency for pigs, further treatment of industrial waste water and tuned fertilization.

Evaluation of uncertainty propagation into river water quality predictions to guide future monitoring campaigns

To evaluate the future state of river water in view of actual pollution loading or different management options, water quality models are a useful tool. However, the uncertainty on the model predictions is sometimes too high to draw proper conclusions. Because of the complexity of process based river water quality models, it is best to investigate this problem according to the origin of the uncertainty. If the uncertainty stems from input data or parameter uncertainty, more reliable results are obtained by performing specific measurement campaigns. The aim of the research reported in this paper is to guide these measurement campaigns based on an uncertainty analysis. The practical case study is the river Dender in Flanders, Belgium. First an overview of different techniques that give valuable information for the reduction of input and parameter uncertainty is given. A global sensitivity analysis shows the importance of the different uncertainty sources. Further an analysis of the uncertainty bands is performed to find differences in uncertainty between certain periods or locations. This shows that the link between periods with high uncertainty and specific circumstances (climatological, eco-regional, etc.) can help in gathering data for the calibration of submodels (e.g. diffuse pollution vs. point pollution).

Modelling Real-Time Control Options on Virtual Sewer Systems

The study presents a benchmarking methodology to assess the performance of sewer systems and to evaluate the performance of real-time control (RTC) strategies by model simulation. The methodology i...