A5088803594- Water resources management and optimization
- Water-Energy-Food Nexus Studies
- Hydrology and Watershed Management Studies
- Flood Risk Assessment and Management
- Water Systems and Optimization
- Reservoir Engineering and Simulation Methods
- Hydrological Forecasting Using AI
- Hydrology and Sediment Transport Processes
- Hydrology and Drought Analysis
- Transboundary Water Resource Management
- Smart Grid Energy Management
- Advanced Control Systems Optimization
- Soil erosion and sediment transport
- Climate change impacts on agriculture
- Electric Power System Optimization
- Hydropower, Displacement, Environmental Impact
- Climate variability and models
- Meteorological Phenomena and Simulations
- Energy and Environment Impacts
- Climate Change Policy and Economics
- Cryospheric studies and observations
- Tropical and Extratropical Cyclones Research
- Fish Ecology and Management Studies
- Integrated Energy Systems Optimization
- Auction Theory and Applications
Politecnico di Milano
2016-2025
University of Brescia
2024
Charles River Laboratories (Netherlands)
2024
Bioengineering Technology and Systems (Italy)
2022-2023
ETH Zurich
2015-2022
RFF-CMCC European Institute on Economics and the Environment
2021-2022
CMCC Foundation - Euro-Mediterranean Center on Climate Change
2022
Hasso Plattner Institute
2021
John Wiley & Sons (United States)
2016-2020
École Polytechnique Fédérale de Lausanne
2018
This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by need for stronger harmonisation research efforts. The procedure involved public consultation through online media, followed two workshops which large number potential science questions were collated, prioritised, and synthesised. In spite diversity participants (230 scientists total), process revealed much about priorities state our science: preference continuity...
Optimal management policies for water reservoir operation are generally designed via stochastic dynamic programming (SDP). Yet, the adoption of SDP in complex real-world problems is challenged by three curses dimensionality, modeling, and multiple objectives. These considerably limit SDP's practical application. Alternatively, this study focuses on use evolutionary multiobjective direct policy search (EMODPS), a simulation-based optimization approach that combines search, nonlinear...
Abstract We present a forecast‐based adaptive management framework for water supply reservoirs and evaluate the contribution of long‐term inflow forecasts to reservoir operations. Our is developed snow‐dominated river basins that demonstrate large gaps in forecast skill between seasonal inter‐annual time horizons. quantify bound components optimal, operation. The uses an Ensemble Streamflow Prediction (ESP) approach generate retrospective, one‐year‐long streamflow based on Variable...
Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed its quantification. Recent studies shown that the application of different robustness can result rankings alternatives, but there has little discussion what potential causes this might be. To shed some light on issue, we present a unifying framework calculation metrics, which assists with understanding how work, when they should be used, why sometimes disagree. The...
Artificial Neural Networks (ANNs), sometimes also called models for deep learning, are used extensively the prediction of a range environmental variables. While potential ANNs is unquestioned, they surrounded by an air mystery and intrigue, leading to lack understanding their inner workings. This has led perpetuation number myths, resulting in misconception that applying primarily involves "throwing" large amount data at "black-box" software packages. this convenient way side-step principles...
Although being one of the most popular and extensively studied approaches to design water reservoir operations, Stochastic Dynamic Programming is plagued by a dual curse that makes it unsuitable cope with large systems: computational requirement grows exponentially number state variables considered (curse dimensionality) an explicit model must be available describe every system transition associated rewards/costs modeling). A variety simplifications approximations have been devised in past,...
Abstract This study contributes a decision analytic framework to overcome policy inertia and myopia in complex river basin management contexts. The combines reservoir identification, many‐objective optimization under uncertainty, visual analytics characterize current operations discover key trade‐offs between alternative policies for balancing competing demands system uncertainties. approach is demonstrated on the Conowingo Dam, located within Lower Susquehanna River, USA. River an...
Abstract Managing water resources systems requires coordinated operation of system infrastructure to mitigate the impacts hydrologic extremes while balancing conflicting multisectoral demands. Traditionally, recommended management strategies are derived by optimizing operations under a single problem framing that is assumed accurately represent objectives, tacitly ignoring myriad effects could arise from simplifications and mathematical assumptions made when formulating problem. This study...
Strategic planning in the Mekong Basin could improve trade-offs between hydropower and sediment supply to Delta.
Input variable selection is an important issue associated with the development of several hydrological applications. Determining optimal input vector from a large set candidates to characterize preselected output might result in more accurate, parsimonious, and, possibly, physically interpretable model natural process. In context, modeled system often exhibits nonlinear dynamics and multiple interrelated variables. Moreover, number candidate inputs can be very redundant, especially when...