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Minnesota Water Science Center |
U.S. Geological Survey Scientific Investigations Report 2007–5129
By Thomas A. Winterstein and David L. Lorenz
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Regression models were developed for the 25th percentile of June and September flows (first quartile of flow) for 47 streamflow-gaging stations (gaging stations) in the Upper Mississippi, Ohio, and Great Lakes drainage basins. The gaging stations that were selected for this analysis are on unregulated rivers, have at least 40 years of record, and have a nearby weather station with at least 70 years of precipitation record. Regression models were developed for each gaging station relating annual 25th percentile of June and September flows to selected precipitation variables. The explanatory variables are monthly precipitation (April–June, July–September) for each year of record, precipitation for the previous year, and average precipitation for the preceding 5-, 10-, 15-, 20-, 25-, and 30-year periods.
Short-term precipitation (April–June or July–September monthly precipitation) variables are the most common significant variables in the regression equations for the 25th percentile of June and September streamflows. May and June monthly precipitation are the most common significant variables among the regression models of the 25th percentile of June flows. August and September monthly precipitation are the most common significant variables in the regression models of the 25th percentile of September streamflow. July precipitation also is a significant explanatory variable in regression models of September streamflow.
The 25th-percentile flows in this study also are related to intermediate- and long-term precipitation variables. The intermediate-term precipitation variable (previous-year’s precipitation) has a more distinct spatial pattern than the long-term precipitation variable (multiyear running averages of annual precipitation) and is more likely to be significant in the western part than in the eastern part of the study area.
ContentsAbstract Introduction Preparation of Data for Analysis Selection of Gaging Stations Missing Data Determining the Regression Models Relation Between Precipitation and 25th-Percentile Flows Suggestions for Future Studies Summary References Cited |
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1. Study area and location of streamflow-gaging stations and weather stations. | |
2. Streamflow-gaging stations where previous year’s precipitation was a significant variable in the regression models for 25th percentile of (A) June and (B) September flows and a running average of precipitation was a significant variable in the regression models for 25th percentile of (C) June and (D) September flows. |
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3. Streamflow-gaging stations where April precipitation was a significant variable in the regression model for 25th percentile
of June flow. |
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4. Coefficient of variation for the period of record at weather stations used in this study. |
5. Graph showing daily streamflow at gaging station 03069500, Cheat River near Parsons, West Virginia,
and monthly precipitation at weather station 466867, Parsons 1NE, West Virginia, April–June, 1998. |
1. Streamflow-gaging stations and corresponding weather stations used in the study. | |
2. Weather stations used in the study. | |
3. Streamflow-gaging stations with missing record between 1960 and 2003. | |
4. Weather stations with missing record from 1930 through 2003. | |
5. Years for which annual precipitation values were estimated. | |
6. Multiple linear regression models for the 25th percentile of June streamflows. | |
7. Multiple linear regression models for the 25th percentile of September streamflows. |
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Suggested Citation:
Winterstein, T.A., and Lorenz, D.L., 2007, Relation between precipitation and the 25th percentile of June and September flows in streams in the
Great Lakes, Ohio, and Upper Mississippi River Basins: U.S. Geological Survey Scientific Investigations Report 2007-5129, 22 p.
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U.S. Department of the Interior, U.S. Geological Survey Persistent URL: https://pubs.water.usgs.gov/sir20075129 Page Contact Information: USGS Publishing Network Last modified:: Thursday, 01-Dec-2016 19:48:15 EST |