Linking 1D coastal ocean modelling to environmental management: an ensemble approach

Abstract

The use of a one-dimensional interdisciplinary numerical model of the coastal ocean as a tool contributing to the formulation of ecosystem-based management (EBM) is explored. The focus is on the definition of an experimental design based on ensemble simulations, integrating variability linked to scenarios (characterised by changes in the system forcing) and to the concurrent variation of selected, and poorly constrained, model parameters. The modelling system used was previously specifically designed for the use in "data-rich" areas, so that horizontal dynamics can be resolved by a diagnostic approach and external inputs can be parameterised by nudging schemes properly calibrated. Ensembles determined by changes in the simulated environmental (physical and biogeochemical) dynamics, under joint forcing and parameterisation variations, highlight the uncertainties associated to the application of specific scenarios that are relevant to EBM, providing an assessment of the reliability of the predicted changes. The work has been carried out by implementing the coupled modelling Dipartimento di Fisica e Astronomia, Alma Mater Studiorum Università di Bologna, Viale Berti Pichat 6/2, Bologna, Italy system BFM-POM1D in an area of Gulf of Trieste (northern Adriatic Sea), considered homogeneous from the point of view of hydrological properties, and forcing it by changing climatic (warming) and anthropogenic (reduction of the land-based nutrient input) pressure. Model parameters affected by considerable uncertainties (due to the lack of relevant observations) were varied jointly with the scenarios of change. The resulting large set of ensemble simulations provided a general estimation of the model uncertainties related to the joint variation of pressures and model parameters. The information of the model result variability aimed at conveying efficiently and comprehensibly the information on the uncertainties/reliability of the model results to non-technical EBM planners and stakeholders, in order to have the model-based information effectively contributing to EBM.

Synergising decision making and interventions across human health and environment: concepts for designing a model for infectious diseases

“…One final advantage of a hybrid modelling approach is that it easily facilities different levels of user engagement for different components. For example, a hydrological model may be purely data driven and developed by expert modellers using a complex systems approach and then included as a component in an ensemble model (Mussap et al, 2017). For other components, the use of local knowledge might be critical for integrating the social-cultural factors, and therefore require a participatory approach with local residents working together with data modellers (Scoones et al, 2017).…”

Editorial—the 8th International Workshop on Modeling the Ocean (IWMO 2016) in Bologna, Italy, June 7–10, 2016

“…Surface wave modeling (Clementi et al 2017;Cieślikiewicz et al 2017;Gic-Grusza and Dudkowska 2017; Guo and Sheng 2017;Sun et al 2017); (4.) Biogeochemicalphysical coupled models (Mussap et al 2017, Luo et al 2017. Below are short summaries (alphabetically ordered) of the 18 studies included in this special topical collection.…”

“…The model was able to capture two bloom periods in 1998 that were detected by remote sensing. Mussap et al (2017) used a one-dimensional version of POM coupled with biogeochemical flux model (BFM-POM1D) to study the impact of climate change warming and anthropogenic changes such as river nutrient loading in the Gulf of Trieste (northern Adriatic Sea). Ensemble simulations provided uncertainties for different parameters and different scenarios.…”