Roberto Pastres

Managing the rearing of Tapes philippinarum in the lagoon of Venice: a decision support system.

The paper illustrates a multicriteria approach for the rational choice of the areas to be dedicated to extensive aquaculture in a coastal basin. Areas are selected by combining spatial information, such as healthiness and depth, with the results of a 3D model, which simulates the dynamics of the primary production and that of the species to be reared. The approach has been applied to the rearing of the bivalve Tapes philippinarum in the lagoon of Venice. The areas more suitable for rearing activities have been identified, and the relation between yield and seeding density is discussed.

Modelling macroalgae (Ulva rigida) in the Venice lagoon: Model structure identification and first parameters estimation

Abstract The paper describes the definition and a first parametrization of a dynamic model of macroalgae ( Ulva rigida ) population. Based on specific literature, a two-step kinetic scheme is selected for modelling growth and uptake of nitrogen and, therefore, the intratissual concentration of nitrogen has been considered as a state variable of the model. Accordingly, Ulva r. growth rate depends on the concentration of phosphorus in the external medium and on the intratissual nitrogen concentration, which influences, in turn, the uptake rates of reduced and oxidized nitrogen. The influences of temperature and light intensity on Ulva r. photosynthetic activity are also discussed. The dynamics of dissolved oxygen has also been modelled and a specific mortality rate, depending on dissoved oxygen, has been adopted. The model has proved to be qualitatively consistent with the available literature, while a first parametrization yields results in quantitative agreement with short term laboratory experiments, regarding samples collected in the lagoon of Venice. The model has been applied to data sets collected in the lagoon of Venice and is capable of reproducing the main features of the seasonal dynamic of Ulva r. These results prompted its inclusion in a comprehensive 3D transport-water quality model of the Venice lagoon ecosystem.

A comparison between the uncertainties in model parameters and in forcing functions: its application to a 3D water-quality model

This paper illustrates the application of both local and global sensitivity analysis techniques to an estimation of the uncertainty in the output of a 3D reaction-diffusion ecological model; the model describes the seasonal dynamics of dissolved Nitrogen and Phosphorous, and those of the phytoplanktonic and zooplanktonic communities in the lagoon of Venice. Two sources of uncertainty were taken into account and compared: (1) uncertainty concerning the parameters of the governing equation; (2) uncertainty concerning the forcing functions. The mean annual concentrations of Dissolved Inorganic Nitrogen (DIN) was regarded as the model output, as it represents the largest fraction of the Total Dissolved Nitrogen, TDN, for which the current Italian legislation sets a quality target in the lagoon of Venice. A local sensitivity analysis was initially used, so as to rank the parameters and provide an initial estimation of the uncertainty, which is a result of an imperfect knowledge of the dynamic of the system. This uncertainty was compared with that induced by an imperfect knowledge of the loads of Nitrogen, which represent the main forcing functions. On the basis of the results of the local analysis, the most important parameters and loads were then taken as the sources of uncertainty, in an attempt to assess their relative contributions. The global uncertainty and sensitivity analyses were carried out by means of a sampling-based Monte Carlo method. The results of the subsequent input-output regression analysis suggest that the variance in the model output could be partitioned among the sources of uncertainty, in accordance with a linear model. Based on this model, 79% of the variance in the mean annual concentration of DIN was accounted for by the uncertainty in the parameters which specify the dynamics of the phytoplankton and zooplankton, and only 5% by the uncertainties in the three main Nitrogen sources.

Addressing Sustainability of Clam Farming in the Venice Lagoon

The clam fishing and aquaculture system in the Venice Lagoon still appears insufficiently resilient to buffer external and internal perturbations, such as productivity fluctuations, unregulated fishing, and market related dynamics, despite the efforts of regional and local authorities to achieve the sustainable development. According to the System Approach Framework (SAF), based on previous studies and stakeholder interactions, we developed a model integrating ecological, social, and economic (ESE) aspects. We chose the aspects necessary to represent the essential dynamics of major ecological, social, and economic clam farming system components to project the consequences of implementing alternative management policies and to address the ecological and social carrying capacity. Results of the simulations suggest that a properly managed farming system can sustain an acceptable income and support the local community, while reducing negative environmental impacts, social conflicts, and consumer health risks and improving system resilience. The results highlight the importance of an interdisciplinary, participatory, and adaptive approach in planning the management of this important renewable resource.

Long term simulations of population dynamics of Ulva r. in the lagoon of Venice

Abstract The dynamic of macroalgae is implemented in a 3D transport-water-quality model of the central part of the lagoon of Venice. Ulva biomass density and nitrogen concentration in Ulva tissue have been added to the set of state variables previously considered, that is to phytoplankton and zooplankton densities, concentrations of nutrients in water, detritus and dissolved oxygen. The model shows that Ulva succeeds in the competition with the phytoplanktonic community in the shallower areas, where water temperature and irradiance levels reaching the bottom are sufficient to sustain growth. Long term evolutions of Ulva colonies, under different scenarios of forcing functions, show that adverse meteoclimatic conditions can be more effective in reducing Ulva biomass than a consistent decrease in the loads of Nitrogen.

The Extended Kalman Filter (EKF) as a tool for the assimilation of high frequency water quality data

The Extended Kalman Filter (EKF) was applied to the analysis of high frequency field measurements of dissolved oxygen (DO), water temperature, salinity, collected by multiparametric sensors in the lagoon of Venice. This paper focuses on the practical aspects of the implementation of the EKF as a data assimilation technique and does not deal with the problems associated with the identification of the model. In this regard, the EKF has proved to be a useful tool for the updating of the estimates of the parameters of a simple DO-chlorophyll model, which can be used for linking the high frequency data to meteorological forcings, such as solar radiation and wind, and to other low frequency measurements of water quality parameters, such as the concentrations of Chlorophyll a and nutrients. The model can subsequently be used as a tool for checking the consistency of all this data, and may also be employed for controlling the quality of the data collected by the multiparametric sensors.

Global Uncertainty and Sensitivity Analysis of a Food-web Bioaccumulation Model

A global uncertainty and sensitivity analysis (UA/SA) of a state-of-the-art, food-web bioaccumulation model was carried out. We used an efficient screening analysis technique to identify the subset of the most relevant input factors among the whole set of 227 model parameters. A quantitative UA/SA was then applied to this subset to rank the relevance of the parameters and to partition the variance of the model output among them by means of a nonlinear regression of the outcomes of 1,000 Monte Carlo simulations. The concentrations of four representative persistent organic pollutants (POPs) in two representative species of the coastal marine food web of the Lagoon of Venice (Italy) were taken as model outputs. The screening analysis showed that the ranking was remarkably different in relation to the species and chemical being considered. The subsequent Monte Carlo-based quantitative analysis pointed out that the relationships among some of the parameters and the model outputs were nonlinear. The nonlinear regression showed that the fraction of output variance accounted for by each parameter was strongly dependent on the range of the octanol-water partition coefficient (K(OW)) values being considered. For the less hydrophobic chemicals, the main sources of model uncertainty were the parameters related to the respiratory bioaccumulation, whereas for the more hydrophobic ones, K(OW) and the other parameters related to the dietary uptake explained the largest fractions of the variance of the chemical concentrations in the organisms. The analysis highlighted that efforts are still needed for reducing uncertainty of model parameters to get reliable results from the application of food web bioaccumulation models.

Local sensitivity analysis of a distributed parameters water quality model

Abstract A local sensitivity analysis is presented of a 1D water-quality reaction-diffusion model. The model describes the seasonal evolution of one of the deepest channels of the lagoon of Venice, that is affected by nutrient loads from the industrial area and heat emission from a power plant. Its state variables are: water temperature, concentrations of reduced and oxidized nitrogen, Reactive Phosphorous (RP), phytoplankton, and zooplankton densities, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD). Attention has been focused on the identifiability and the ranking of the parameters related to primary production in different mixing conditions.

Thermal exchanges at air-water interfacies and reproduction of temperature vertical profiles in water columns

Abstract For a 3-D eutrophication-diffusion macromodel of the central part of the Venice Lagoon, air-water heat fluxes are computed interpolating, through Fourier series expansion, meteoclimatic variables averaged over a thirty years survey. Also reproduced with the same interpolation methods, is the daily fluctuation of incident light as well as the annual variation of the photoperiod. With an interative procedure temperature values, to be assigned at each grids point and corresponding to each hour of a reference year, are computed also accounting for the thermal inertia of water columns of varying depths. By statistical examination of temperature vertical profiles, depth varying diffusivities are also estimated, which enables, without assumption of an instantaneous mixing, the reproduction of heat diffusion from the surface to the bottom water cells. Procedures, preliminary refined and verified for a one-dimensional vertical system input, are next implemented on a three-dimensional submodel of reduced size provided of “open boundaries”: this last submodel, under a continuous input of energy and of matter is seen to attain a steady states as well as to be capable of simulating regime conditions. A further validation is performed, on a submodel of 43 × 47 × 20 cells, encompassing a limited portion of the macromodel and presenting the actual lagoon bathymetry. Macromodels seasonalisation so achieved, enables for a more correct simulation of the periodical behaviour of light and of temperature, forcing functions governing the eutrophication phenomena.

Using parallel computers in environmental modelling: a working example

Abstract An application of the utilization of parallel supercomputers for a 3D eutrophication-diffusion macromodel of the Venice lagoon is presented. Problems encountered in program restructuration, in the choice and in the introduction of parallel algorithms for solving the diffusion equation are discussed, together with the approach used to exploit multitasking performances. Results obtained show that, through appropriate coding, execution times for a full year simulation of the model, involving the diffusion and the trophic interactions of eight state variables, with a time step of one hour, have been decreased by about an order of magnitude.