Abstract: 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. (C) 2010 Elsevier Ltd. All rights reserved.

Abstract: In this study a numerical groundwater reactive transport model of a shallow groundwater aquifer contaminated with volatile organic compounds is developed. In addition to advective-dispersive transport, the model includes contaminant release from source areas, natural attenuation, abiotic degradation by a permeable reactive barrier at the site, and dilution by infiltrating rain. Aquifer heterogeneity is parameterized using pilot points for hydraulic conductivity, specific yield and groundwater recharge. A methodology is developed and applied to estimate the large number of parameters from the limited data at the field site (groundwater levels, groundwater concentrations of multiple chemical species, point-scale measurements of soil hydraulic conductivity, and lab-scale derived information on chemical and biochemical reactions). The proposed methodology relies on pilot point parameterization of hydraulic parameters and groundwater recharge, a regularization procedure to reconcile the large number of spatially distributed model parameters with the limited field data, a step-wise approach for integrating the different data sets into the model, and high performance computing. The methodology was proven to be effective in reproducing multiple contaminant plumes and in reducing the prior parameter uncertainty of hydraulic conductivity and groundwater recharge. Our results further indicate that contaminant transport predictions are strongly affected by the choice of the groundwater recharge model and flow parameters should be identified using both head and concentration measurements. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: Stimulated anaerobic dechlorination is generally considered a valuable step for the remediation of aquifers polluted with chlorinated ethenes (CEs). Correct simulation and prediction of this process in situ, however, require good knowledge of the associated biological reactions. The aim of this study was to evaluate the dechlorination reaction in an aquifer contaminated with trichloroethene (TCE) and its daughter products, discharging into the Zenne River. Different carbon sources were used in batch cultures and these were related to the dechlorination reaction, together with the monitored biomarkers. Appropriate kinetic formulations were assessed. Reductive dechlorination of TCE took place only when external carbon sources were added to microcosms, and occurred concomitant with a pronounced increase in the Dehalococcoides mccartyi cell count as determined by 16S rRNA gene-targeted qPCR. This indicates that native dechlorinating bacteria are present in the aquifer of the Zenne site and that the oligotrophic nature of the aquifer prevents a complete degradation to ethene. The type of carbon source, the cell number of D. mccartyi or the reductive dehalogenase genes, however, did not unequivocally explain the observed differences in degradation rates or the extent of dechlorination. Neither first-order, Michaelis-Menten nor Monod kinetics could perfectly simulate the dechlorination reactions in TCE spiked microcosms. A sensitivity analysis indicated that the inclusion of donor limitation would not significantly enhance the simulations without a clear process understanding. Results point to the role of the supporting microbial community but it remains to be verified how the complexity of the microbial (inter)actions should be represented in a model framework. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.