Our computational intensive research is supported by two proprietary servers (Intel Xeon E5-2660 2.20 GHz with 32 processing cores and 96 GB Ram), along with access to the pan-European supercomputing infrastructure offered by PRACE (Partnership for Advanced Computing in Europe).


CASCADE - CAtchment Sediment Connectivity And Delivery

Matlab toolbox for sediment transport and connectivity in large rivers. This algorithm is described in Tangi, Schmitt, Bizzi and Castelletti (2019).

FRIDA – FRamework for Index-based Drought Analysis

Matlab toolbox supporting a fully-automated design of basin-customized drought indexes based on the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS) applied to the case study of the Jucar river basin (Spain), a drought prone, highly regulated Mediterranean water system, where an advanced drought management plan relying on the formulation of an ad-hoc State Index is used for triggering drought restraining measures.

M3O: Multi-Objective Optimal Operations of multipuropose water reservoir systems

Matlab toolbox for designing the optimal daily operations of multipurpose water reservoir systems through several state-of-the-art methods. Version 1.0 of the toolbox includes Deterministic and Stochastic Dynamic Programming, Implicit Stochastic Optimization, Sampling Stochastic Dynamic Programming, Fitted Q-Iteration, Evolutionary Multi-Objective Direct Policy Search, Model Predictive Control.

HBV rainfall-runoff model

C++ model implementation, Java interface for calibration with MOEA Framework, model tutorial. This model was used in Giuliani and Castelletti (2016).

Iterative Input Selection algorithm

MatLab implementation of the IIS algorithm relying on Extremely Randomized Trees, woking both in regression and classification mode. The same algorithm with a C-library implementing the Extremely Randomized Trees is available HERE. This algorithm is described in Galelli and Castelletti (2013).

Sparse Principal Component Analysis

Matlab toolbox comprising 8 formulations of SPCA using Alternating Maximization. This toolbox was used in Galelli et al. (2015).