Here is a brief description of about current research activities
of the Planning and Management of Environmental Systems group.
Further information can be found on the personal web pages
of the people of the group.
Description of the research areas:
|| Air and water quality
|| The dynamics of air and water pollution is studied with deterministic and stochastic models
both for short term prediction of quality conditions
and to assess optimal long term plans for pollution reduction.
|| Integrated Water Resources Management
Parsimonious modelling for simulation and forecasting of water systems,
namely rainfall-runoff process and distribution networks.
Development and implementation of methods based on Optimal Control Theory
for the efficient management of multi-purpose reservoirs,
reservoir networks and distribution networks (namely
Stochastic Dynamic Programming, Neuro-Dynamic Programming,
Reinforcement Learning). Either off-line and on-line policy design
problems are adressed.
Analysis and development of methods based on Decision and Negotiation Theory
for eliciting preference structures and
supporting decision-making in multi-objective,
multi-DMs context and under uncertainty.
Design and implementation of Multi Objective Decision Support Systems
for integrated and participatory planning of water resources at the basin scale.
Sustainable exploitation of ecosystems, in particular of fish resources.
Alternative management policies are assessed under a multi-objective perspective
that integrates economic, social and environmental viewpoints
and accounts for environmental and demographic uncertainty.
Simple mechanistic models for plant-animal interactions.
Proposal and analysis of novel mathematical models
for identifying the key mechanisms that originate spatial patterns of trees in forests.
Model selection in population time series.
Development and testing of new methods based on Statistical Learning Theory
to distinguish between linear and nonlinear ecological models.
Special attention is devoted to devising robust methods for short time series.
Analysis of the extinction risk in fragmented landscapes.
Habitat loss is one of the main causes of species extinction.
We develop spatially implicit and explicit models
to discuss the effects of different conservation policies on the probability of species persistence.