State-of-the-science modeling tool in Minnesota - graph

Model predictions of the impact of reduced phosphorus loads will support management decisions. In this illustrative example, model predictions are compared to the water quality standard.

State-of-the-science modeling tool in Minnesota

 

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Success Story

Modeling Tool Supports High-Profile TMDL Study in Lake Pepin Watershed

A highly valued recreational area, Lake Pepin is a natural impoundment of the Upper Mississippi River on the border of Minnesota and Wisconsin. The Lake Pepin watershed is large, covering more than half of Minnesota. Lake Pepin is included in Minnesota’s Section 303(d) list of impaired waters, and a Total Maximum Daily Load (TMDL) is being developed. LimnoTech has been contracted by the Minnesota Pollution Control Agency to develop a modeling tool to support a combined TMDL for turbidity and nutrient enrichment.

Problem

The Lake Pepin TMDL is the most significant and high-profile TMDL in the state, impacting growing communities with wastewater discharge and agricultural needs. With significant economic impact on agriculture and development within the watershed, the TMDL will undergo close scrutiny.

Approach

LimnoTech has worked closely with the Science Advisory Panel to develop a highly credible modeling tool to support the TMDL study. The model addresses complex technical issues, including the size of the system and interrelated nature of the impairments (reducing turbidity leading to more algal growth). The modeling framework is based on three-dimensional hydrodynamics and advanced algal dynamics, representing state-of-the-science in large ecosystem modeling. LimnoTech has also worked with the Stakeholder Advisory Committee to ensure that the model addresses local concerns. The resulting tool is based on the best available science and is supported by both technical experts and local stakeholders.

Result

The model is being used to inform decisions for TMDL allocations, which will have major economic impact on local communities and agricultural producers. The model will provide an accurate understanding of what is needed to meet water quality objectives, and the most efficient means of attaining these objectives.