Dirk De Pauw

Modelling the production and degradation of soluble microbial products (SMP) in membrane bioreactors (MBR)

MBR biochemical conditions have an effect on membrane fouling and SMP have been attributed to be the main MBR foulant. Thus, predicting the SMP concentration is essential for understanding and controlling MBR fouling. However, existing SMP models are mostly too complex and over-parameterized, resulting in inadequate or absent parameter estimation and validation. This study extends the existing activated sludge model No. 2d (ASM2d) to ASM2dSMP with introduction of only 4 additional SMP-related parameters. Dynamic batch experimental results were used for SMP parameter estimation leading to reasonable parameter confidence intervals. Finally, the ASM2dSMP model was used to predict the impact of operational parameters on SMP concentration. It would found that solid retention time (SRT) is the key parameter controlling the SMP concentration. A lower SRT increased the utilization associated products (UAP) concentration, but decreased the biomass associated products (BAP) concentration and vice versa. A SRT resulting in minimum total SMP concentration can be predicted, and is found to be a relatively low value in the MBR. If MBRs operate under dynamic conditions and biological nutrient removal is required, a moderate SRT condition should be applied.

Stem‐mediated hydraulic redistribution in large roots on opposing sides of a Douglas‐fir tree following localized irrigation

*Increasing evidence about hydraulic redistribution and its ecological consequences is emerging. Hydraulic redistribution results from an interplay between competing plant and soil water potential gradients. In this work, stem-mediated hydraulic redistribution was studied in a 53-year-old Douglas-fir tree during a period of drought. *Sap flux density measurements using the heat field deformation method were performed at four locations: in two large opposing roots and on two sides of the tree stem. Hydraulic redistribution was induced by localized irrigation on one of the measured roots, creating heterogeneous soil water conditions. *Stem-mediated hydraulic redistribution was detected during night-time conditions when water was redistributed from the wet side of the tree to the nonirrigated dry side. In addition to stem-mediated hydraulic redistribution, bidirectional flow in the dry root was observed, indicating radial sectoring in the xylem. *It was observed that, through stem-mediated hydraulic redistribution, Douglas-fir was unable to increase its transpiration despite the fact that sufficient water was available to one part of the root system. This resulted from the strong water potential gradient created by the dry soil in contact with the nonirrigated part of the root system. A mechanism of stem-mediated hydraulic redistribution is proposed and its possible implications are discussed.

Practical aspects of sensitivity function approximation for dynamic models.

Sensitivity analysis can be used to quantify the magnitude of the dependency of model predictions on certain modelling assumptions, e.g. parameter values, initial conditions or inputs. The finite difference method, a local sensitivity analysis technique, is discussed in detail and situated among other methods. A lot of attention is paid to the practical issues concerning the implementation of this technique, more specifically the effect of nonlinearities of the model and numerical problems. The influence of the perturbation factor on the sensitivity calculations is investigated and different criteria are proposed to assess the quality of the sensitivity functions. A threshold value with good probability of detecting faulty sensitivity function calculations was found for one of these criteria, implying that the method can be automated.

Dynamic in-stream fate modeling of xenobiotic organic compounds: A case study of linear alkylbenzene sulfonates in the Lambro River, Italy

Using a conceptual hydraulic model, a one-dimensional dynamic river water quality model has been developed to assess the short-term fate of linear alkylbenzene sulfonates (LAS) in the river compartments water and benthic sediment. The model assumes local equilibrium sorption and that both dissolved and sorbed chemical are available for biodegradation. To investigate the interaction of nutrient dynamics and organic contaminant fate, the model is coupled with a basic water quality model. On the basis of the Lambro River (Italy) as a case study, the result shows that the model predictions agree well with the measured data set. The model output sensitivity to model parameters has been tested, and the results depict that the model is highly sensitive to the biodegrading parameters. Also, a comparison of a steady state with a dynamic simulation and the effect of nutrient dynamics on the LAS fate in the Lambro River as a scenario analysis are presented. The results indicate the usefulness of the proposed model for the short-term simulation of organic contaminant fate in unsteady environmental conditions.

A Kernel-Based Method to Determine Optimal Sampling Times for the Simultaneous Estimation of the Parameters of Rival Mathematical Models

When several models are proposed for one and the same process, experimental design techniques are available to design optimal discriminatory experiments. However, because the experimental design techniques are model‐based, it is important that the required model predictions are not too uncertain. This uncertainty is determined by the quality of the already available data, since low‐quality data will result in poorly estimated parameters, which on their turn result in uncertain model predictions. Therefore, model discrimination may become more efficient and effective if this uncertainty is reduced first. This can be achieved by performing dedicated experiments, designed to increase the accuracy of the parameter estimates. However, performing such an additional experiment for each rival model may undermine the overall goal of optimal experimental design, which is to minimize the experimental effort. In this article, a kernel‐based method is presented to determine optimal sampling times to simultaneously estimate the parameters of rival models in a single experiment. The method is applied in a case study where nine rival models are defined to describe the kinetics of an enzymatic reaction (glucokinase). The results clearly show that the presented method performs well, and that a compromise experiment is found which is sufficiently informative to improve the overall accuracy of the parameters of all rival models, thus allowing subsequent design of an optimal discriminatory experiment.

TreeWatch.net: A Water and Carbon Monitoring and Modeling Network to Assess Instant Tree Hydraulics and Carbon Status

TreeWatch.net is an initiative that has been developed to watch trees grow and function in real-time. It is a water- and carbon-monitoring and modeling network, in which high-quality measurements of sap flow and stem diameter variation are collected on individual trees. Automated data processing using a cloud service enables instant visualization of water movement and radial stem growth. This can be used to demonstrate the sensitivity of trees to changing weather conditions, such as drought, heat waves, or heavy rain showers. But TreeWatch.net’s true innovation lies in its use of these high-precision harmonized data to also parameterize process-based tree models in real-time, which makes displaying the much-needed mechanisms underlying tree responses to climate change possible. Continuous simulation of turgor to describe growth processes and long-term time series of hydraulic resistance to assess drought-vulnerability in real-time are only a few of the opportunities our approach offers. TreeWatch.net has been developed with the view to be complementary to existing forest monitoring networks and with the aim to contribute to existing dynamic global vegetation models. It provides high-quality data and real-time simulations in order to advance research on the impact of climate change on the biological response of trees and forests. Besides its application in natural forests to answer climate-change related scientific and political questions, we also envision a broader societal application of TreeWatch.net by selecting trees in nature reserves, public areas, cities, university areas, schoolyards, and parks to teach youngsters and create public awareness on the effects of changing weather conditions on trees and forests in this era of climate change.

Developing a framework for continuous use of models in daily management and operation of WWTPs: a life cycle approach.

We developed and evaluated a framework for the continuous use of dynamic models in daily management and operation of WWTPs. The overall aim is to generate knowledge and build in-house capacity for the reliable use of dynamic models in practice (within a regional water authority in The Netherlands). To this end, we have adopted a life cycle approach, where the plant model follows the different stages that make up the typical lifespan of a plant. Since this approach creates a framework in which models are continuously reused, it is more efficient in terms of resources and investment than the traditional approach where one always makes a new model for the plant whenever it is needed. The methodology was evaluated successfully at a 50,000 PE domestic EBPR plant (Haaren, The Netherlands). It is shown that the continuous use and update of models in a cyclic manner creates a learning cycle, which results in experience and knowledge generation about the plants modelling that accumulates and translates into improvements into the modelling quality and efficiency. Moreover, a model is now always on-the-shelf for process optimization.