Highly varying hydro-climatological conditions, multi-party decision-making contexts, and the dynamic interconnection between water and other critical infrastructures create a wealth of challenges and opportunities for water resources planning and management. For example, reservoir operators must account for a number of time-varying drivers, such as the downstream users’ demands, short- and long-term water availability, electricity prices, and the share of power supplied by wind and solar technologies. In this context, adaptive and robust management solutions are paramount to the reliability and resilience of water resources systems. To this purpose, emerging work is focusing on the development of models and algorithms that adapt short-term decisions to newly available information, often issued in the form of weather or streamflow forecasts, or extracted from observational data collected via pervasive sensor networks, remote sensing, cyberinfrastructure, or crowdsourcing.
In this session, we solicit novel contributions related to improved multi-sectoral forecasts (e.g., water availability and demand, energy and crop prices), novel data analytics and machine learning tools for processing observational data, and real-time control solutions taking advantage of this new information. Examples include: 1) approaches for incorporating additional information within control problems; 2) methods for characterizing the effect of forecast uncertainty on the decision-making process; 3) integration of information with users’ preferences, behavioral uncertainty, and institutional setting; 4) studies on the scalability and robustness of optimal control algorithms. We welcome real-world examples on the successful application of these methods into decision-making practice.

Convener: Matteo Giuliani | Co-conveners: Stefano Galelli, Julianne Quinn, Amaury Tilmant
| Tue, 09 Apr, 08:30–10:15
Room 2.31
| Attendance Tue, 09 Apr, 10:45–12:30
Hall A

Attendance time: Tuesday, 9 April 2019, 10:45–12:30 | Hall A

Chairperson: Stefano Galelli, Matteo Giuliani
A.198 |
Md. Humayain Kabir, Md. Manzoorul Kibria, and Mohammad Mosharraf Hossain
A.200 |
Amaury Tilmant, Hajar Ashouri, Emixi Valdez, Jasson Pina, and Francois Anctil
A.201 |
Barbara Cencur Curk, Goran Vizintin, Saso Celarc, and Petra Souvent
A.202 |
Giorgio Falcini, Elena Muratore, Federico Giudici, Andrea Castelletti, Davide Airoldi, Elisabetta Garofalo, Matteo Giuliani, and Holger Maier
A.203 |
Jazmin Zatarain Salazar, Federica Bertoni, Matteo Giuliani, and Andrea Castelletti
A.204 |
Sara Cazzaniga, Federica Bertoni, Matteo Giuliani, and Andrea Castelletti
A.205 |
Julianne Quinn, Patrick Reed, Matteo Giuliani, Andrea Castelletti, Jared Oyler, and Robert Nicholas
A.206 |
Christoph Libisch-Lehner, Harald Kling, Bernhard Wipplinger, Martin Fuchs, and Hans-Peter Nachtnebel
A.207 |
Forecast-informed reservoir operating rules based on Bayesian approach using climate index
Guang Yang and Paul Block
A.208 |
Paul Block, Shu Wu, Benjamin Zaitchik, Shraddhanand Shukla, Annalise Blum, Sarah Alexander, and Ying Zhang
A.210 |
A prediction model for water demand in watershed by combining the stepwise cluster analysis with neural networks
Zhang Yi