Magnus Johansson works within the field of integrating natural disaster risk reduction with climate change adaptation. His main interest is within lessons learning (tools, methods and data capture) after past events.
He is responsible for master courses in societal risk management and further education on climate adaptation and risk reduction for professionals working in private or public sector. Together with colleagues at Karlstad university he has developed a new teaching concept where stakeholder cooperation, social learning and local perspectives are in focus.
Dr. Magnus Johansson is a senior lecturer in risk management and a researcher at the Centre for Climate and Safety (CCS) at Karlstad University. He and his colleagues conducts multi-disciplinary research and education within the area of disaster risk management and climate change adaptation. The centre has a focus on floods and its consequences for humans, ecosystems and the society. The Centre runs a network of stakeholders, both public and private organizations, and is also one of three partners in the national research school at the Swedish Centre for Natural Disaster Science (CNDS) together with Uppsala University and Swedish National Defence College. Magnus Johansson supervise PhD students and is active as a teacher on courses within the research school.
He has also been employed as an analyst and project leader within the area of natural hazards at the MSB (Swedish Civil Contingencies Agency) Lessons Learning Section during 2006-2016. He was responsible for the government commission to build the Swedish Natural Hazards Information System (ndb.msb.se), which was done in cooperation with Joint Research Centre (JRC) in Ispra, Italy, and stakeholders in Sweden (Swedish Geotechnical Institute, SMHI, Swedish Geological Survey, Road Administrative Board, The Swedish Board of Housing, Building and Planning, Swedish Police, insurance businesses, some selected municipalities and county administrative boards).
His research is currently focused on lessons learning and data capture from past extreme hydrometeorological accidents and risk assessments.