Developing a multi-proxy varve chronology at Steel Lake, MN, USA to examine quantitative correlation to local hydroclimate and improve predictive modeling

Project overview

The Upper Mississippi River basin is experiencing changes in precipitation, extreme weather, and flooding. Current statistical models of climate are restricted by short data sets that limit the ability to determine the likelihood of the largest flooding events, droughts, and other climatic hazards. To improve these models, we will use seasonally layered lake sediments calibrated by local weather and stream gage data to reconstruct the past 1000 years of climate and river flow in this region. The sediments deposited in the lake reflect the climatic events within their watershed with identifiable seasonal signals, allowing for seasonal reconstructions. For each dated layer, elemental data will be correlated to local instrumental datasets to determine relationships and reconstruct climate history beyond the relatively short instrumental time frame. This longer and high-resolution record will be used to improve forecasting models and ultimately impact water allocation and infrastructural design decisions in a changing climate.