Sensitivity Analysis of a Cyanobacterial Growth and Movement Model under Two Different Flow Regimes

Abstract

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling cyanobacterial behaviour in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes, reservoirs and rivers. A new deterministicmathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including light, nutrients and temperature. A parameter sensitivity analysis using a oneat-a-time approach was carried out. There were two objectives of the sensitivity analysis presented in this paper: to identify the key parameters controlling the growth and movement patterns of cyanobacteria and to provide a means for model validation. The result of the analysis suggested that maximum growth rate and day length period were the most significant parameters in determining the population growth and colony depth, respectively.

Assessing the Sensitivity of SWMM to Variations in Hydrological and Hydraulic Parameters: A Case Study for the city of Istanbul

“…Sensitivity analysis can be described as the process of determining model output sensitivity to changes in its input parameters. In other words, sensitivity analysis of a mathematical model investigates how the uncertainty in the output of a model can be apportioned to different sources of uncertainty in the model input (Hamby, 1995), and involves analytical examination of input parameters to aid model validation and to provide guidance for future research and data requirements (Guven and Howard, 2011). According to Mulligan and Wainwright (2004), sensitivity analyses and subsequent derived information can be used for several purposes including:…”