A framework for good biofilm reactor modeling practice (GBRMP) Bruce E. Rittmann, Joshua P. Boltz, Doris Brockmann, Glen T. Daigger, Eberhard Morgenroth, Kim Helleshøj Sørensen, Imre Takács, Mark van Loosdrecht and Peter A. Vanrolleghem ABSTRACT A researcher or practitioner can employ a biofilm model to gain insight into what controls the performance of a biofilm process and for optimizing its performance. While a wide range of biofilm- modeling platforms is available, a good strategy is to choose the simplest model that includes sufficient components and processes to address the modeling goal. In most cases, a one- dimensional biofilm model provides the best balance, and good choices can range from hand- calculation analytical solutions, simple spreadsheets, and numerical-method platforms. What is missing today is clear guidance on how to apply a biofilm model to obtain accurate and meaningful results. Here, we present a five-step framework for good biofilm reactor modeling practice (GBRMP). The first four steps are (1) obtain information on the biofilm reactor system, (2) characterize the influent, (3) choose the plant and biofilm model, and (4) define the conversion processes. Each step demands that the model user understands the important components and processes in the system, one of the main benefits of doing biofilm modeling. The fifth step is to calibrate and validate the model: System-specific model parameters are adjusted within reasonable ranges so that model outputs match actual system performance. Calibration is not a simple ‘by the numbers’ process, and it requires that the modeler follows a logical hierarchy of steps. Calibration requires that the adjusted parameters remain within realistic ranges and that the calibration process be carried out in an iterative manner. Once each of steps 1 through 5 is completed satisfactorily, the calibrated model can be used for its intended purpose, such as optimizing performance, trouble-shooting poor performance, or gaining deeper understanding of what controls process performance. Bruce E. Rittmann Biodesign Swette Center for Environmental Biotechnology, Arizona State University, P.O. Box 875701, Tempe, AZ 85287-5701, USA Joshua P. Boltz Volkert, Inc., 3809 Moffett Road, Mobile, AL 36618, USA Doris Brockmann INRA Transfert, LBE, Univ. Montpellier, INRA, Narbonne, France Glen T. Daigger Dept. of Civil and Environmental Engineering, University of Michigan, 1351 Beal Ave., Ann Arbor, MI 48109, USA Eberhard Morgenroth (corresponding author) ETH Zürich, Institute of Environmental Engineering, 8093 Zürich, Switzerland and Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland E-mail: Eberhard.Morgenroth@eawag.ch Kim Helleshøj Sørensen Wabag Water Technology Ltd, Bürglistrasse 31, 8401 Winterthur, Switzerland Imre Takács Dynamita, 7 Eoupe, 26110 Nyon, France Mark van Loosdrecht Dept. of Biochemical Engineering, Delft University of Technology, The Netherlands Peter A. Vanrolleghem Département de génie civil et de génie des eaux, modelEAU, Université Laval, 1065 Av. de la Médecine, Québec, QC G1 V 0A6, Canada Key words | biofilm, framework, good practice, modeling, reactor 1149 © IWA Publishing 2018 Water Science & Technology | 77.5 | 2018 doi: 10.2166/wst.2018.021 Downloaded from http://iwaponline.com/wst/article-pdf/77/5/1149/664424/wst077051149.pdf by guest on 08 June 2022