Geology topics

Research about Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, Wisconsin

Source-linked reports with geographic coverage including Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, Wisconsin.

4 recordsLinked to original sources

USGS2025

Hydroclimatic and land-use factors affecting peak streamflow in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis provides the basis for flood risk estimates used by water-resource managers in land-use planning, and it informs the design of essential infrastructure such as bridges and culverts. Federal guidelines for flood-frequency analysis do not offer guidance on addressing changing climate and land-use conditions when estimating floods. However, failing to consider climatic and land-use changes that cause abrupt or gradual changes in flood regimes can result in a poor representation of the true flood risk. In response to concerns about changing flood regimes, the U.S. Geological Survey, in cooperation with nine State agencies (Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation) began a study to examine variability and change in hydrology and climate and the effects of urbanization and tile drainage on flooding. The analyses of patterns and changes in hydrology and climate were reported in a multichapter Scientific Investigations Report, the findings of which are summarized in this U.S. Geological Survey Circular. Additional analyses documenting changes in seasonality of flooding and the effects of urbanization and tile drainage were completed and published as separate studies and are also summarized in this Circular. These studies provide extensive exploratory analysis of peak streamflow, daily streamflow, and climate data, setting the stage for advancements in flood-frequency analysis.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗

USGS2025

Nonstationary flood frequency analysis using regression in the north-central United States

Traditional flood frequency methods assume that the statistical properties of peak streamflow do not change with time and may not be appropriate for many areas in the north-central United States. This study examines a nonstationary flood frequency analysis method that uses ordinary least squares linear regression to estimate flood magnitudes at U.S. Geological Survey streamgages that exhibit trends and change points in a nine-State region including Montana, North Dakota, South Dakota, Minnesota, Illinois, Iowa, Wisconsin, Missouri, and Michigan. Additionally, an extension of this method is introduced, which enables nonstationary flood frequency based on a statistical relation with a stochastic climate predictor. Estimates of the 1-percent annual exceedance probability flood using regression equations to adjust for conditions in 2020 were computed at U.S. Geological Survey streamgages across the study area. Regression equations used either a time index or a climate variable as the explanatory variable for changes in peak streamflow. Of 153 candidate streamgages, the assumptions of time-adjusted analyses were met at 137 streamgages. Climate-adjusted flood frequency analyses were applicable at 98 streamgages based on annual precipitation, annual temperature, or annual snowfall. Time- and climate-adjusted methods produced similar estimates of the 1-percent annual exceedance probability flood magnitude at streamgages where both methods were applicable. Nonstationary estimates of the 1-percent annual exceedance probability flood were primarily greater than stationary estimates in eastern North and South Dakota, Minnesota, Iowa, Illinois, and parts of Missouri and less than stationary estimates in Montana, western North and South Dakota, and Wisconsin. The largest differences between stationary and nonstationary flood estimates were in North and South Dakota and Minnesota.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗

USGS2025

A framework for understanding the effects of subsurface agricultural drainage on downstream flows

Understanding controls on streamflow volume and magnitude is important to water resource management applications, such as critical water and transportation structure design and floodplain mapping. Changes in land use and agricultural practices, such as subsurface agricultural drainage, may be contributing to changes in streamflow characteristics. Subsurface agricultural drainage, also known as tile drainage, is the practice of installing drains in the subsurface of agricultural fields to improve productivity. Because of the complex interactions between subsurface drainage systems, precipitation, local soil conditions, and land management practices, it is difficult to determine how subsurface agricultural drainage affects downstream flow. Previously developed subsurface agricultural drainage conceptual models under dry, saturated, and winter conditions are summarized, and current literature on the effects of subsurface agricultural drainage on downstream flows, focusing on peak flow, non-event flow, and total flow to develop frameworks for discussing these systems is compiled. The effects that subsurface drainage has on hydrologic systems are expected to vary by site and are seasonally based on system design, soil type, moisture conditions, precipitation characteristics, and land conditions. Subsurface drainage can affect the magnitude of peak flow by converting surface runoff from a storm event to subsurface runoff. By increasing hydrologic connectivity of a catchment, subsurface drainage can increase non-event flow or the flow between two storm events, typically dependent on lateral flow through the subsurface and groundwater. Theoretically, by diverting water from groundwater recharge or by reducing water available for evapotranspiration, subsurface drainage may increase the total volume of flow. Precipitation changes may increase infiltration, excess overland flow, and flood risk regardless of the presence or absence of subsurface drainage.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗

USGS2025

Changes in streamflow seasonality associated with hydroclimatic variability in the north-central United States among three discrete temporal periods, 1946–2020

Study region North-central United States Study focus This study uses circular statistics to characterize the seasonal properties of annual maximum (AMS) and peaks-over-threshold (POT) streamflow time series for 841 and 623 selected U.S. Geological Survey (USGS) streamgages, respectively, without regulation or substantial diversion among common 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, through September 30, 2020). A subset of AMS time series with detected change points (abrupt changes) in the median and (or) scale are analyzed on either side of the change point to evaluate changes in their circular statistics. New hydrologic insights for the region In the 50-year trend period, five regions share common mean flood timing in the AMS and POT partial duration series. Changes from asymmetric distributions to reflective symmetric distributions are detected particularly among the 50- and 30-year trend periods in the northernmost States of Minnesota, North Dakota, and Wisconsin. For the subset of streamgages with abrupt change points in the AMS, regional patterns of changes in seasonality are detected between the period of records before and after the change point. These findings can inform decisions related to the AMS used for flood frequency and potential mixed population analyses and flood control operations that may be affected by changes in when seasonal events occur, how long seasonal events last, and the long-term variability in the intensity and frequency of seasonal events.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗