Open WL Archief (OWA)

With an aim of enhancing the applicability of conceptual river water quality simulators, a Conceptual Integrated Tool for Water quality Assessment (CIToWA) has been developed in the framework of this PhD research, hereby addressing the limitations described earlier. The tool is developed to: 1) present a robust solutions scheme 2) enable simulation of size-selective sediment-bound pollutant transport, and 3) enable simulation of complex stream networks using a conceptual approach. It is aims to maintain the computational speed of conceptual models but increases the versatility.

In CIToWA, the river system is divided in reaches, conceptual elements that divide the channel longitudinally in to different parts. The discharges and the velocities in these reaches must be provided by external simulation tools. The reaches are further considered to act as Continuously Stirred Tanks Reactors (CSTR), whereby complete mixing is assumed within each reach. The water quality tool integrates several components, developed for specific purposes. The first component is the simulator of dissolved oxygen, biochemical oxygen demand, the nitrogen compounds, the phosphorus compounds, and the algae.

A quasi-analytical solver is developed to simulate robust solutions of water quality problems, based on the CSTR principles and on ordinary first order reaction equations. The performance of the quasi-analytical solver is evaluated by simulating different experiments and testing the robustness of its solution under extreme conditions. The results are also compared with the performance of SWAT (Soil and Water Assessment Tool) – a commonly used water quality simulator - and with high and low order numerical solvers that are commonly used in other conceptual water quality simulators. The comparison shows that the quasi-analytical solver simulates robust solutions -even for large computation time steps- in all the experiments and performs better than all the solvers used in the comparison. This increases the reliability of the solutions as well as the speed of computation of CIToWA.

A method is also developed to simulate complex stream networks and systems characterized by bi-directional interactions. The method uses the direction of the flow to enable pollutant transport in a reverse direction (from downstream to upstream), if needed.

A second component of CIToWA deals with the sediment and sediment-bound pollutants. The sediment transport module considers the sediment in suspension and the sediment on the river bed, taking settlement and resuspension into account. Hereby, the Particle Size Distributions of the sediment (PSD) are taken into account by considering probability density functions. The temporal and spatial evolution of the mean and standard deviation of the PSD –caused by settlement, resuspension, and emissions– are determined by using statistical functions of mixture distributions. The concepts of this novel sediment transport simulator are validated by simulating extensive sediment mobility data of laboratory and field experiments from literature, as well as by a case study on the River Zenne (see below). CIToWA simulates the sediment-bound pollutant transport using a Langmuir adsorption model. The adsorption simulator integrates the quasi-analytical solver with the fine fraction of the sediment – the mass of the sediment to which pollutants adsorb. The latter module was also tested on a case study on the River Zenne.

An application of CIToWA in the complex river – canal system of the River Zenne (Belgium) illustrates its applicability for real cases. The system is characterized by bifurcations, such as overflows from the river to the canal and some of the reaches experience two-directional flows. The flow in the canal is characterized by high and frequent discontinuities as the flow is controlled by the sluice activities.

A comparison of the simulation results of CIToWA with those of a previous detailed water quality model of the River Zenne shows that CIToWA performs as well or better than the detailed model. The better performance of CIToWA is attributable to the fact that it runs fast (23 seconds to run the model with an hourly time step over the period 2007-2010) and hence automatic parameter optimization can be carried out – one of the key objectives of the research. The latter was indeed not the case for the detailed model, as the latter required 10 days of computation time to run the model for the pre-cited period.