Author(s): Karl-Erich Lindenschmidt; Eric Akomeah; Luis Morales-Marin; Elmira Hassanzadeh

Linked Author(s):

Keywords: Integrated catchment modelling; Identifiability; Uncertainty; Cold region; Ice processes

Abstract: There is mounting evidence that ice phenology influences the biogeochemistry of aquatic ecosystems. For under-ice eutrophic aquatic ecosystems in saline environments, it is critical to delineate key parameters and processes for long-term management of such systems. Such systems are saddled with anoxic and bloom risks, with under-ice nutrient cycling being a precursor for spring and summer blooms. In this study, a novel top-down modelling and posteriori identifiability analysis in a Monte-Carlo framework is employed to highlight key parameters and processes contributing to rising eutrophication in the Prairie region of the North American Great Plains, Qu’Appelle River Basin. Landscape nutrient export processes and main stem in-stream processes were hypothesized and linked in VENSIM system-dynamics model and in-stream Water quality Analysis Simulation Program (WASP) models. Model integration was achieved using a python wrapper. Sensitivity metrics were estimated from an ensemble of 10,000 simulation runs. The interaction and cross-correlation of landscape and instream processes were inferred from these metrics. Results from the study showed that winter warming is critical to eutrophication in the studied system and the need to explicitly incorporate overwintering nutrient mechanisms in new generation integrated water quality models.

DOI:

Year: 2020