Ingrid Keupers

Development and testing of a fast conceptual river water quality model

Modern, model based river quality management strongly relies on river water quality models to simulate the temporal and spatial evolution of pollutant concentrations in the water body. Such models are typically constructed by extending detailed hydrodynamic models with a component describing the advection-diffusion and water quality transformation processes in a detailed, physically based way. This approach is too computational time demanding, especially when simulating long time periods that are needed for statistical analysis of the results or when model sensitivity analysis, calibration and validation require a large number of model runs. To overcome this problem, a structure identification method to set up a conceptual river water quality model has been developed. Instead of calculating the water quality concentrations at each water level and discharge node, the river branch is divided into conceptual reservoirs based on user information such as location of interest and boundary inputs. These reservoirs are modelled as Plug Flow Reactor (PFR) and Continuously Stirred Tank Reactor (CSTR) to describe advection and diffusion processes. The same water quality transformation processes as in the detailed models are considered but with adjusted residence times based on the hydrodynamic simulation results and calibrated to the detailed water quality simulation results. The developed approach allows for a much faster calculation time (factor 105) without significant loss of accuracy, making it feasible to perform time demanding scenario runs.

Impact of urban WWTP and CSO fluxes on river peak flow extremes under current and future climate conditions

The impact of urban water fluxes on the river system outflow of the Grote Nete catchment (Belgium) was studied. First the impact of the Waste Water Treatment Plant (WWTP) and the Combined Sewer Overflow (CSO) outflows on the river system for the current climatic conditions was determined by simulating the urban fluxes as point sources in a detailed, hydrodynamic river model. Comparison was made of the simulation results on peak flow extremes with and without the urban point sources. In a second step, the impact of climate change scenarios on the urban fluxes and the consequent impacts on the river flow extremes were studied. It is shown that the change in the 10-year return period hourly peak flow discharge due to climate change (-14% to +45%) was in the same order of magnitude as the change due to the urban fluxes (+5%) in current climate conditions. Different climate change scenarios do not change the impact of the urban fluxes much except for the climate scenario that involves a strong increase in rainfall extremes in summer. This scenario leads to a strong increase of the impact of the urban fluxes on the river system.

Conceptual river water quality model with flexible model structure

Abstract Physically-based river water quality models are valuable tools for river basin management and planning. However, their long computational times pose many difficulties for applications that involve a large number of model iterations. This paper addresses this problem by developing a faster, surrogate conceptual model based on the detailed reference models. The hydrodynamic information and water quality process equations from different detailed models are considered as ensembles in the developed model. The model conceptualizes rivers using cascades of reservoirs and lumps the advection-diffusion and physico-biochemical processes. We tested the model by comparing its performance for the Molse Neet river, Belgium, with two popular reference models, namely, MIKE 11 and InfoWorks RS. Results show that the conceptual model performs equally well as the reference models, but with simulation time 104 times faster. The successful testing of this model opens a development avenue towards problem solving in the context of water quality control and management.

Modelling the time variance of the river bed roughness coefficient for improved simulation of water levels

ABSTRACT Aquatic macrophytes create seasonally variable changes in river bed roughness. These changes in roughness influence the hydrodynamic behaviour of the river, for example, elevated water levels for the same discharge. In most hydrodynamic river models, the roughness is assumed constant in time, which may lead to high errors in the river water level results. When the river water level results are applied to water quality studies, biased estimates may be obtained of river flow velocities, dilution and other water quality processes. This article investigates how models implemented in two common hydrodynamic modelling software packages (MIKE11 and InfoWorks RS) can be adopted to take into account the time-varying river bed roughness due to plant growth. Albeit the use of a different approach by the two models, it is shown that both can account for that influence. After application to the Grote Nete river catchment in Belgium, far more accurate river water level results are obtained. Overall, the increase in accuracy of the water level simulations outweighs the increase in model complexity required to enable simulation of the vegetation changes. The model results can also be used to correct discharge estimates based on the measured water levels as shown for this case study.