Streamflow 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. Louis River was selected to determine the effects of ongoing Mesabi Iron Range mining. Each drainage basin (Cannon, St. Louis) was subdivided into nested drainage basins: the Cannon River was subdivided into 152 nested drainage basins, and the St. Louis River was subdivided into 353 nested drainage basins. For each smaller drainage basin, the estimated volumes of groundwater discharge (as base flow) and surface runoff flowing into all surface-water features were displayed under the following conditions: (1) extreme low-flow conditions, comparable to an exceedance-probability quantile of 0.95; (2) low-flow conditions, comparable to an exceedance-probability quantile of 0.90; (3) a median condition, comparable to an exceedance-probability quantile of 0.50; and (4) a high-flow condition, comparable to an exceedance-probability quantile of 0.02.
Streamflow distribution maps were developed using flow-duration curve exceedance-probability quantiles in conjunction with Soil-Water-Balance model outputs; both the flow-duration curve and Soil-Water-Balance models were built upon previously published U.S. Geological Survey reports. The selected streamflow distribution maps provide a proactive water management tool for State cooperators by illustrating flow rates during a range of hydraulic conditions. Furthermore, after the nested drainage basins are highlighted in terms of surface-water flows, the streamflows can be evaluated in the context of meeting specific ecological flows under different flow regimes and potentially assist with decisions regarding groundwater and surface-water appropriations. Presented streamflow distribution maps are foundational work intended to support the development of additional streamflow distribution maps that include statistical constraints on the selected flow conditions.
Citation Information
| Publication Year | 2017 |
|---|---|
| Title | Streamflow distribution maps for the Cannon River drainage basin, southeast Minnesota, and the St. Louis River drainage basin, northeast Minnesota |
| DOI | 10.3133/sim3390 |
| Authors | Erik A. Smith, Christopher A. Sanocki, David L. Lorenz, Katrin E. Jacobsen |
| Publication Type | Report |
| Publication Subtype | USGS Numbered Series |
| Series Title | Scientific Investigations Map |
| Series Number | 3390 |
| Index ID | sim3390 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Minnesota Water Science Center |
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Soil-Water-Balance model data sets for the St. Louis River drainage basin, northeast Minnesota, 1995-2010
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Erik Smith, Ph.D.
Hydrologist
Water-Use Data and Research Program Coordinator
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Soil-Water-Balance model data sets for the St. Louis River drainage basin, northeast Minnesota, 1995-2010
A soil-water balance model (SWB) was developed to estimate potential recharge and surface runoff for portions of the St. Louis River drainage basin, northeast Minnesota, for the period 1995 through 2010. The model was used in the creation of St. Louis River streamflow distribution maps, as part of the associated report, U.S. Geological Survey Scientific Investigations Map 2017-3390 (http://dx.doi.Soil-Water-Balance model data sets for the Cannon River drainage basin, southeast Minnesota, 1995-2010
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 - Connect
Erik Smith, Ph.D.
HydrologistWater-Use Data and Research Program CoordinatorEmailPhone