hydroMOPSO
My Caption
hydroMOPSO R package.
Description
hydroMOPSO is an R package designed to support robust multi-objective optimisation of complex environmental and engineering models. It implements a state-of-the-art Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm, tailored to address the practical challenges commonly encountered in hydrological modelling, such as non-linearity, non-smooth response surfaces, computationally intensive simulations, and competing performance criteria.
hydroMOPSO is built to integrate seamlessly with real-world modelling workflows. It can optimise models written in R as well as external simulation models executed from the system console—such as distributed hydrological or water quality models—by communicating through standard input and output files. This architecture allows users to perform advanced optimisation without modifying model source code, preserving model integrity while enabling systematic calibration across multiple parameters, variables, and time periods.
Designed with flexibility and computational efficiency in mind, hydroMOPSO supports parallel execution on multi-core machines and computing clusters, making it suitable for large-scale calibration and decision-support applications. Its configurable optimisation settings and multi-objective capabilities enable users to explore trade-offs among performance metrics and identify parameter sets that balance competing modelling goals.
hydroMOPSO is widely applicable to hydrology and other environmental sciences, providing a technically rigorous and operationally practical framework for global optimisation. It is particularly well suited for researchers and practitioners who require transparent, reproducible, and scalable tools to calibrate complex models and support evidence-based analysis.
I am an Associate Professor in the Department of Civil Engineering at the University of La Frontera. I hold a PhD in Environmental Engineering from the University of Trento (Italy) and completed postdoctoral training at the European Commission’s Joint Research Centre. I have more than 20 years of experience in water resources research and have previously served as an Associate Researcher at the Center for Climate and Resilience Research (CR)2 and as a member of the Earth Sciences Assessment Group of the Chilean National Research and Development Agency (ANID).
My research lies at the interface of hydrology, data science, and environmental sciences, with a particular focus on the use of gridded datasets and open-source tools to investigate droughts, extreme events, and water-related impacts of global change.
I work across spatial and temporal scales to improve the understanding of catchment-scale hydrological processes and to translate this knowledge into operational modelling, forecasting, and early-warning systems that support robust environmental decision-making.
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