Minnesota's Legacy

All Projects

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Recipient
RESPEC
2013 Fiscal Year Funding Amount
$70,000
Fund Source

This project will complete spatial and temporal revisions , recalibration and validation of 7 watershed HSPF models. These fully functioning calibrated validated executable models will simulate hydrology, sediment (sand, silt, and clay), temperature, phosphorus, nitrogen, dissolved oxygen, biochemical oxygen demand, and algae at the 12-digit HUC subbasin scale (or finer).

Blue Earth
Brown
Carver
Cottonwood
Dakota
Faribault
Freeborn
Jackson
Le Sueur
Lincoln
Lyon
Martin
McLeod
Murray
Nicollet
Pipestone
Ramsey
Redwood
Renville
Rice
Scott
Sibley
Steele
Waseca
Watonwan
Yellow Medicine
Recipient
Tetra Tech
2015 Fiscal Year Funding Amount
$125,000
Fund Source

The goal of this project is to construct, calibrate, and validate a Hydrological Simulation Program FORTRAN (HSPF) model for Minnesota portions of the Des Moines River watershed.

Cottonwood
Jackson
Lyon
Martin
Murray
Nobles
Pipestone
Recipient
RESPEC
2011 Fiscal Year Funding Amount
$214,963
Fund Source

This project will complete spatial and temporal revisions of 6 Hydrologic Simulation Program FORTRAN (HSPF) models, the recalibration and validation of 7 watershed HSPF models, and the revision of the drainage network and point source representation of the Pomme de Terre HSPF model.

Big Stone
Blue Earth
Brown
Carver
Cottonwood
Dakota
Douglas
Faribault
Freeborn
Grant
Hennepin
Jackson
Le Sueur
Lincoln
Lyon
Mahnomen
Martin
McLeod
Murray
Nicollet
Norman
Otter Tail
Pipestone
Polk
Ramsey
Redwood
Renville
Rice
Scott
Sibley
Steele
Stevens
Swift
Waseca
Watonwan
Yellow Medicine
Recipient
Tetra Tech
2017 Fiscal Year Funding Amount
$3,969
Fund Source

This project is for constructing, calibrating, and validating a Hydrologic Simulation Program FORTRAN (HSPF) watershed models for the Minnesota portions of the Des Moines Headwaters, Lower Des Moines, and East Fork Des Moines watersheds. The model can be used to provide information to support conventional parameter Total Maximum Daily Load (TMDL) reports. This model generates predicted output timeseries data for hydrology, sediment, nutrients, and dissolved oxygen that are consistent with observed data.

Cottonwood
Jackson
Lyon
Martin
Murray
Pipestone