Climate Change and the Lake Constance Economy: Impacts, Risks and Adaptation

IEGR’s proposed study will examine the economic consequences of low water levels in the Lake Constance region, identify the extent to which these consequences can be attributed to human-induced climate change, and assess economically viable adaptation measures. It will cover lakeside communities in Germany, Austria and Switzerland, with a separate module addressing impacts beyond the region, including long-distance water supply.

The analysis will focus on shipping and ports, tourism and recreation, drinking water supply, fisheries and shoreline ecosystem services. It will investigate how the timing, duration and severity of low-water conditions affect operating costs, business activity, regional value added and societal welfare. Other pressures, such as rising water temperatures, invasive species and regional drought, will be assessed separately to avoid attributing their effects entirely to declining water levels.

The study will combine hydrological and climate modelling with economic data analysis and targeted surveys of businesses and infrastructure operators. Historical observations will help establish relationships between water levels and economic outcomes, while future scenarios will explore risks under different climate and adaptation pathways. Where suitable data are available, comparisons with modelled conditions without human-induced climate change will support attribution.

Economic assessment will distinguish between business losses, regional economic effects and wider welfare impacts, avoiding double counting. Adaptation options—including operational changes, modified harbour infrastructure and measures to strengthen water supply resilience—will be evaluated through their costs, avoided damages and remaining risks.

The proposed study is expected to take 12–18 months. Its outputs will include maps of exposed locations, sector-specific impact estimates, future risk scenarios and an assessment of adaptation options. Findings will clearly distinguish observed effects from projections and report uncertainty and data limitations.