A soil-water balance model (SWB) was developed to estimate potential recharge and surface runoff for portions of the Cannon River drainage basin, southeast Minnesota, for the period 1995 through 2010. The model was used in the creation of Cannon River streamflow distribution maps, as part of the associated report, U.S. Geological Survey Scientific Investigations Map 2017-3390 (http://dx.doi.org/10.3133/SIM20173390). This SWB model was calibrated using three independent hydrograph separation models: PART, Hysep-fixed, and Hysep-sliding method. The basic framework for this model was the statewide Minnesota SWB potential recharge model, described, calibrated, and documented as part of U.S. Geological Survey Scientific Investigations Report 2015-5038 (http://dx.doi.org/10.3133/sir20155038). Daymet (version 2) daily surface weather data necessary for running this SWB model, including "prcp", "tmax", and "tmin", can be downloaded from this SWB model archive. Alternatively, the Daymet v2 are available upon request through the following link: https://doi.org/10.3334/ORNLDAAC/1219.
|Title||Soil-Water-Balance model data sets for the Cannon River drainage basin, southeast Minnesota, 1995-2010|
|Authors||Erik A Smith|
|Product Type||Data Release|
|Record Source||USGS Digital Object Identifier Catalog|
|USGS Organization||Upper Midwest Water Science Center|
Streamflow distribution maps for the Cannon River drainage basin, southeast Minnesota, and the St. Louis River drainage basin, northeast Minnesota
Erik Smith, Ph.D.
Streamflow distribution maps for the Cannon River drainage basin, southeast Minnesota, and the St. Louis River drainage basin, northeast MinnesotaStreamflow distribution maps for the Cannon River and St. Louis River drainage basins were developed by the U.S. Geological Survey, in cooperation with the Legislative-Citizen Commission on Minnesota Resources, to illustrate relative and cumulative streamflow distributions. The Cannon River was selected to provide baseline data to assess the effects of potential surficial sand mining, and the St.
Erik Smith, Ph.D.