Environmental
Intelligence
for Global Change
We are a research group based at the Department of Electronics, Information, and Bioengineering, Politecnico di Milano. Our research mission is advancing environmental decision-analytics for supporting human decisions in complex engineering systems including multiple actors and exposed to evolving multisectoral demands and global change. Our research fuses environmental, climate, and hydrologic disciplines with machine learning, optimal control, and evolutionary computation. This multidisciplinary mix yields innovative, flexible, and robust solutions facilitating participatory decision making processes by addressing the multifaceted complexity of environmental systems, including their nested interdependencies across stakeholders, processes, and policies at different spatial scales; as well as potential changes in human-nature interactions and feedbacks under changing climate extremes and societal demands.
How can global sustainability boundaries be translated into practical approaches for managing water resources at the river basin scale? A new review article, “Review and reframing of the operationalisation of the water planetary boundary for
Water resources optimization conventionally maximizes system-wide efficiency, treating distributional equity as secondary. Here we present a framework that directly incorporates equity into optimization using Atkinson’s inequality measure. This approach makes distributional value judgements transparent through
We are pleased to share a new publication in Water Resources Research developed in collaboration with colleagues from Duke University and the University of California Davis. The paper explores a fundamental question in water resources
