Acid sulphate soil risk mapping - ways to reduce acidity in water bodies

Background and goals

There is a broad societal debate on Artificial Intelligence (AI), with both supporters and opponents. Some see AI as very dangerous, while others claim it will save the world. Regardless of these extremes, AI is a multidisciplinary and interdisciplinary field that is integrated into our daily lives. Today, data is already being collected, analysed and used for intelligent services in many sectors, such as retail, healthcare or environmental technologies. Given the great potential of AI to solve complex problems, its development and use will become increasingly important in the future. Today, one of the biggest environmental problems in Finland is acid sulphate soils. Such soils cause serious ecological damage. In order to reduce the problem, it is important to locate areas where these types of soils occur.

Objectives and benefits

The aim is to develop a model to create acid sulphate soil risk maps for the pilot areas

by modelling old and new research data. The risk mapping model will allow the maps to be

to be created for the entire coastal zone. Risk assessment based on soil samples will be combined with

hydrogeochemical data, looking at the actual loading of different types of sulphate soils in different regions of the world.

different hydrological conditions and estimate the load. Hydrogeochemical

studies will use SWAT modelling, analysis of existing data and

complementary studies. The data will be analysed using machine learning and real-time computation methods, and

produce a prototype mobile application.

Results

The results of the project will be communicated interactively

to stakeholders. The outputs of the project will include an acid sulphate soil risk map for the pilot areas and

a prototype of a mobile application as a tool for authorities, water management planners,

contractors, consultants and experts.

Societal impact

The societal impact of the project is the new knowledge on acid sulphate soils and the analytical risk map of specific areas.