MOAT – Micro-Organisms and Turbulence: Towards a Numerical Laboratory for Water Quality Prediction

  • Ansprechpartner:

    Stefanie West
    Harald Horn
    Jueying Qian

  • Förderung:

    Baden-Württemberg Stiftung

  • Partner:

    Prof. Dr. Markus Uhlmann , Institute for Hydromechanics, KIT
    Dr. Herlina Herlina , Institute for Hydromechanics, KIT

  • Starttermin:


  • Endtermin:



The quality of surface water typically depends upon a complex interplay between physical, chemical and biological factors which are far from being completely understood today. Nevertheless, ensuring an acceptable water quality is a crucial requirement in many environmentally-relevant processes. As a consequence, there still exist large uncertainties related to quality predictions based on state-of-the-art mathematical models of surface water bodies. One of the major shortcomings of the common approaches is their strong simplification with respect to turbulent transport phenomena (often treated with a statistical model and empirically-fitted coefficients) as well as to the multi-phase nature of the surface water system. The present project aims at pushing the modeling boundary further by performing – for the first time ever – massively-parallel computer simulations of a mathematical model which resolves all scales of: hydrodynamic turbulence, the concentration field of a dissolved gas phase, the micro-scale flow around suspended rigid particles. Our computer model is applied to the fate and transport of fecal indicator bacteria (such as E. coli) after a sewage overflow event into a streaming water body (such as a river or a canal), where the bacteria are initially present both in freely-suspended form as well as attached to the surfaces of the particles. Our large-scale simulations with increasing complexity will reveal the relative importance of the various transport and conversion sub-processes.

These results will provide important insight into the mechanisms through which the spatio-temporal heterogeneities of the complex flow affect the self-purification capability of a contaminated water body, which will in turn pave the way for a general improvement of water quality assessment methods.