Geology topics

Mackenzie K. Marti

Publications and source records attributed to Mackenzie K. Marti.

13 recordsLinked to original sources

USGS2026

Floods of June 20–July 6, 2024, in the Big Sioux River, Rock River, Little Sioux River, Ocheyedan River, and Floyd River Basins, northwestern Iowa

Major flooding occurred on June 20–July 6, 2024, in northwestern Iowa affecting the Big Sioux, Rock, Little Sioux, Ocheyedan, and Floyd River Basins. Heavy rain fell in northwestern Iowa, southwestern Minnesota, and southeastern South Dakota on June 20–22, 2024. Parts of northwestern Iowa recorded 2–6 inches of rainfall and localized amounts exceeding 12 inches. A maximum peak-of-record streamflow of 175,000 cubic feet per second at the U.S. Geological Survey streamgage Big Sioux River at Akron, Iowa (06485500), was recorded on June 22, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at four locations along the Big Sioux River between U.S. Interstate 29 at Sioux City, Iowa, upstream to Iowa Highway 10 north of Hawarden, Iowa, a distance of 75.7 river miles. A maximum peak-of-record streamflow of 157,000 cubic feet per second at the U.S. Geological Survey streamgage Rock River near Rock Valley, Iowa (06483500), was recorded on June 22, 2024, and had an annual exceedance probability of less than 0.2 percent. High-water marks were measured at eight locations along the Rock River between County Road B30 east of Hudson, South Dakota, upstream to Iowa Highway 9 at Rock Rapids, Iowa, a distance of 39.3 river miles. A maximum peak-of-record streamflow of 63,000 cubic feet per second at the U.S. Geological Survey streamgage Little Sioux River at Correctionville, Iowa (06606600), was recorded on June 24, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at 11 locations along the Little Sioux River between Iowa Highway 31 west of Correctionville, Iowa, upstream to U.S. Highway 18 north of Spencer, Iowa, a distance of 134.8 river miles. A maximum streamflow of 24,500 cubic feet per second at the U.S. Geological Survey streamgage Ocheyedan River near Spencer, Iowa (06605000), was recorded on June 22, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at three locations along the Ocheyedan River between County Road M38 west of Spencer, Iowa, upstream to U.S. Highway 18 west of Everly, Iowa, a distance of 12.8 river miles. A maximum streamflow of 41,000 cubic feet per second at the U.S. Geological Survey streamgage Floyd River at Alton, Iowa (06600100), was recorded on June 22, 2024, and had an annual exceedance probability range of 1–1.99 percent. High-water marks were measured at six locations along the Floyd River between Iowa Highway 3 at Le Mars, Iowa, upstream to Iowa Highway 10 at Alton, Iowa, a distance of 27.5 river miles. The high-water marks were used to develop flood profiles for the Big Sioux, Rock, Little Sioux, Ocheyedan, and Floyd Rivers.

Iowa, Minnesota, South Dakota↗

USGS2026

Floods of June 2024 in northwestern Iowa

Following a heavy, multiday rainfall event that took place between June 20 and June 22, 2024, widespread flooding occurred in parts of northwestern Iowa. Ten U.S. Geological Survey (USGS) streamgages with periods of record ranging from 56 to 99 years in length experienced new peaks of record, three of which were more than double the previous peak-of-record: 06483500 (Rock River near Rock Valley, Iowa), 06605850 (Little Sioux River at Linn Grove, Iowa), and 06606600 (Little Sioux River at Correctionville, Iowa). A Presidential declaration of a major disaster for the State of Iowa was approved on June 24, 2024, and the cost of the flooding is estimated at over $310 million. The severity of this flooding prompted the USGS, in cooperation with the Iowa Department of Transportation, to summarize the meteorological and hydrological conditions preceding the flooding, compile estimates of the magnitude of peak flows resulting from the flooding, and update estimates of peak-flow frequency for selected USGS streamgages. Of the 33 streamgages analyzed, a peak streamflow occurred that corresponded to an annual exceedance probability of less than 4 percent at 13 streamgages, an annual exceedance probability of less than 1 percent at 6 streamgages, and an annual exceedance probability of less than 0.2 percent at 1 streamgage.

Iowa↗

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

Regional analysis of the dependence of peak-flow quantiles on climate with application to adjustment to climate trends

Standard flood-frequency analysis methods rely on an assumption of stationarity, but because of growing understanding of climatic persistence and concern regarding the effects of climate change, the need for methods to detect and model nonstationary flood frequency has become widely recognized. In this study, a regional statistical method for estimating the effects of climate variations on annual maximum (peak) flows that allows for the effect to vary by quantile is presented and applied. The method uses a panel–quantile regression framework based on a location-scale model with two fixed effects per basin. The model was fitted to 330 selected gauged basins in the midwestern United States, filtered to remove basins affected by reservoir regulation and urbanization. Precipitation and discharge simulated using a water-balance model at daily and annual time scales were tested as climate variables. Annual maximum daily discharge was found to be the best predictor of peak flows, and the quantile regression coefficients were found to depend monotonically on annual exceedance probability. Application of the models to gauged basins is demonstrated by estimating the peak-flow distributions at the end of the study period (2018) and, using the panel model, to the study basins as-if-ungauged by using leave-one-out cross validation, estimating the fixed effects using static basin characteristics, and parameterizing the water-balance model discharge using median parameters. The errors of the quantiles predicted as-if-ungauged approximately doubled compared to the errors of the fitted panel model.

Hydrology↗

USGS2025

The joint effect of changes in urbanization and climate on trends in floods: A comparison of panel and single-station quantile regression approaches

Estimates of annual maximum (peak) flow quantiles are needed for basins undergoing changes in both urbanization and climate. Most previous work on the effect of urbanization on peak flows has considered urbanization alone and only the spatial variation in flood quantiles or its mean temporal effect, and most work on the effect of nonstationarity in climate has focused on single-station analyses, which give uncertain results for extreme quantiles. To address these gaps, three approaches to the statistical estimation of the joint effects of changes in impervious cover and climate on the estimation of peak-flow quantiles were compared: single-station quantile regression; a fixed effect panel-quantile regression (pQR) method using a location (mean) shift to homogenize the panel; and a location-scale panel regression model (pQRmom), which accounts for both scale (variance) and location effects. The different approaches were applied to a dataset consisting of instantaneous annual peak flows from 127 minimally nested basins in the midwestern United States with at least 4 % change in imperviousness. The annual maximum daily discharge from a water-balance model was selected as the primary climate predictor; in addition, to provide a comparison of climate predictors, precipitation was also considered. The coefficients from single-station regressions were usually sufficiently certain to determine the effects of climate variation but usually too uncertain to estimate the effects of urbanization. The panel-quantile regression approaches give much more certain results, but their estimates of quantile dependence differ: although both indicate urbanization effects decreasing with decreasing annual exceedance probability (AEP), the pQRmom urbanization coefficients are insignificantly different from zero for AEPs less than 0.10, whereas the pQR coefficients remain positive and are significant except for AEP = 0.01, the smallest AEP value considered. Although the location-scale structure of the pQRmom approach has less flexible quantile dependence than the pQR approach, the pQRmom approach has somewhat lower overall error, and it is found that by subsetting the dataset to homogenize the scale effects, the pQR and pQRmom results become similar, indicating the insignificant urbanization coefficients for small AEPs of the pQRmom results are likely correct for the study dataset.

Arkansas, Illinois, Indiana, Iowa, Michigan, Minne↗

USGS2024

Peak streamflow trends in Illinois and their relation to changes in climate, water years 1921–2020

This report characterizes changes in peak streamflow in Illinois and the relation of these changes to climatic variability, and provides a foundation for future studies that can address nonstationarity in peak-flow frequency analysis in Illinois. Records of annual peak and daily streamflow at streamgages and gridded monthly climatic data (observed and modeled) were examined across four trend periods (100 years, water years 1921–2020; 75 years, 1946–2020; 50 years, 1971–2020; 30 years 1991–2020) for trends, change points, and other statistical properties indicative of changing conditions. Median peak streamflows generally exhibit upward trends across the State for the 100- and 75-year trend periods and in northern and southern Illinois for the 50- and 30-year trend periods. The medians of the trend magnitudes (normalized by median peak streamflow) range from a 23-percent increase during the 30-year trend period to a 41-percent increase during the 100-year trend period. Streamgages with trends in peak streamflow often also have change points, or abrupt changes, in streamflow magnitude. More than two-thirds of streamgages at the 100- and 75-year trend periods exhibit a trend and change point in median peak streamflow in the same direction. Temporally, clusters of change points are observed in the late 1960s through early 1980s for the 100- and 75-year trend periods and around 2006 for the 50- and 30-year trend periods. Trends in the 90-percent quantile of peak streamflow, which correspond to the 10-percent exceedance probability often used for the design of drainage structures, increased about the same amount as the 50-percent quantile peak streamflows, except at the 100-year trend period, where the 50-percent quantile peak flow increased more for almost all streamgages. The frequency of high flows has also increased in Illinois, with increases in peaks-over-threshold observed across much of the State for the 100- and 75-year trend periods and in northern and southern Illinois for the 50- and 30-year trend periods. Upward trends in observed temperature and observed annual precipitation dominate in all trend periods, with clusters of likely upward trends observed in northern and southern Illinois at the 50- and 30-year trend periods. As expected in response to increasing temperature, the modeled proportion of precipitation falling as snow has largely decreased in the study basins across the State, and modeled potential evapotranspiration has increased. Upward trends in modeled annual runoff, which in this report incorporates only the effects of climatic variation, are observed in the same geographic areas where there are increases in observed annual precipitation. The widespread upward trends in the magnitude of median peak streamflows and the frequency with which high flows occur across the State at the 100- and 75-year trend periods and in northern and southern Illinois at the 50- and 30-year trend periods appear to be driven largely by increases in precipitation based on spatial patterns of these changes and statistical relations between streamflow and climate metrics. Other effects not considered in this report, like urbanization, may be important drivers for certain streamgages in the State. The prevalence of nonstationarity in peak streamflow in Illinois has important implications for peak-flow frequency analysis. Average annual precipitation and the occurrence of extreme precipitation events are expected to increase across the State. If precipitation continues to increase as expected, peak-flow frequency estimates based on older records may no longer represent the hydrologic regime of today, and methods for nonstationary peak-flow frequency analysis may be needed.

Illinois↗

USGS2024

Peak streamflow trends in Missouri and their relation to changes in climate, water years 1921–2020

This report characterizes changes in peak streamflow in Missouri and the relation of these changes to climatic variability, and provides a foundation for future studies that can address nonstationarity in peak-streamflow frequency analysis in Missouri. Records of annual peak and daily streamflow at streamgages and gridded monthly climatic data (observed and modeled) were examined across four trend periods (100 years, water years 1921–2020; 75 years, 1946–2020; 50 years, 1971–2020; and 30 years, 1991–2020) for trends, change points (abrupt changes in the streamflow time series), and other statistical properties indicative of changing conditions. Peak streamflow magnitudes generally exhibit upward trends across the State for the 100-, 75-, and 50-year trend periods and only in southern Missouri for the 30-year trend period. The medians of the trend magnitudes (normalized by median peak streamflow) range from a 10-percent increase during the 30-year trend period to a 40-percent increase during the 100-year trend period. Changes in the 90-percent quantile of peak streamflow, which correspond to the 10-percent exceedance probability often used for the design of drainage structures, are not as substantial or widespread, showing consistent increases mainly in the southern part of the State in the 50- and 30-year trend periods. Streamgages with trends in peak streamflow often also have change points, or abrupt changes, in streamflow magnitude. Change points in peak streamflows generally follow that of the peak streamflow trends, with upward change points throughout most of the State at the 100- and 75-year trend periods and in southern Missouri at the 30-year trend period. Temporally, clusters upward of change points are observed in the 1970s through 1980s for the 100-, 75-, and 50-year trend periods and around 2006 and 2007 for the 50- and 30-year trend periods. A peaks-over-threshold analysis, which evaluates changes in the frequency of peak streamflows over a certain threshold, indicates that high flows have increased in frequency at 50 to 64 percent of streamgages in the 100- and 75-year trend periods. Most streamgages in the 50- and 30-year trend periods exhibit no change. Although the frequency of high flows has increased at some streamgages and trend periods in Missouri, these increases are not as widespread as the increases in the magnitude of peak streamflow. Upward trends in observed temperature and observed annual precipitation dominate in all trend periods, with no downward trends in precipitation and only two somewhat likely downward trends in temperature for the 100-year trend period. Increases in annual precipitation mostly are limited to southern Missouri for the 30-year trend period. The proportion of precipitation falling as snow has largely decreased in the study basins across the State, which is expected in response to increasing temperature. Upward trends in modeled annual runoff, which in this study incorporates only the effects of climatic variation, are observed in the same geographic areas where there are increases in observed annual precipitation. When peak streamflow and climatic trends are considered together, widespread upward trends in peak streamflows for the 100-, 75-, and 50-year trend periods and for the 30-year trend period mainly in southern Missouri (encompassing both trends and abrupt change) appear to be driven largely by increases in precipitation based on spatial patterns and statistical relations. The prevalence of nonstationarity in peak streamflow in Missouri has important implications for peak-flow frequency analysis. Winter and spring precipitation and the occurrence of extreme precipitation events are expected to increase across the State. If precipitation continues to increase as expected, peak-flow frequency estimates based on older records may no longer represent the hydrologic regime of today, and methods for nonstationary peak-flow frequency analysis may be needed.

Missouri↗

USGS2024

Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States. This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States. Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

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

USGS2023

Method for identification of reservoir regulation within U.S. Geological Survey streamgage basins in the Central United States using a decadal dam impact metric

Researchers routinely study streamflow data to understand the effects of natural climate variability and anthropogenic climate change, and to develop methods for estimating streamflow at ungaged locations. These studies require streamflow data that are not modified or largely altered by other anthropogenic activities, such as reservoirs or diversions. This report discusses a method for identifying basins with reservoir regulation using a decadal impact metric that characterizes the degree of regulation of a given river reach. The method is applied to U.S. Geological Survey streamgage basins from eight States in the Central United States. Using this metric, 140 streamgages with known regulation effects (annual peak streamflow values qualified with a code 6) were evaluated for their impact metric values in decades with annual peak streamflow values qualified with code 6. Based on the distribution of median impact metric values at these regulated basins, a threshold value of 0.1 was identified as the value that when exceeded was the most characteristic of the regulated streamgage basins in the study area. Streamgage basins from nine States with peak streamflow values that were not qualified with code 6 were evaluated for impact metric values equal to or greater than the established threshold. About 13 percent of streamgages (136 of 1,017) had an impact metric equal to or greater than the identified regulated threshold at some point in their periods of record. The method discussed in this report, which has limitations owing to characteristics of the data underlying the dam impact metric, provides a regionally consistent approach to identifying regulated U.S. Geological Survey streamgage basins.

Iowa, Illinois, Michigan, Missouri, Montana, North↗

USGS2023

Estimating peak-flow quantiles for selected annual exceedance probabilities in Illinois

This report presents the methods, results, and applications of an updated flood-frequency study for the State of Illinois. This study, which uses data through September 2017, updates two previous studies that used data through 1999 and 2009, respectively. Flood-frequency estimates are used for a variety of land-use planning and infrastructure design purposes, including for the hydraulic design of bridges. The flood frequencies presented are the stream discharges (or quantiles) that are exceeded each year with a given probability, called the annual exceedance probability (AEP). Estimates are provided for eight AEPs: 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002. The basic data used are the annual maximum discharges (peak flows) at streamgages in and near Illinois and the measurable physical properties (basin characteristics) of the basins upstream from those streamgages. The logarithms of the peak flow records at qualifying streamgages were fit to the Pearson Type 3 distribution using federally recommended methods, providing one of the two primary products of the study, which is the set of peak-flow quantiles at the streamgages and their uncertainties. The other primary product is sets of equations, determined by least-squares regression, that relate the peak-flow quantiles and the basin characteristics. There is one set of equations for each of Illinois’ seven hydrologic regions, and, for each region, one equation for each AEP. These regional equations allow the estimation of peak-flow quantiles at ungaged locations throughout the state and their uncertainties. A set of illustrative example applications is provided, and tables of all results at all study streamgages and regions are provided in associated data releases. The study results are also being made available in a web application, StreamStats.

Illinios↗

USGS2023

Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records

Flood-frequency analysis is essential in numerous water-resource management applications, including critical structure design and flood-plain mapping. A basic assumption within Bulletin 17C [1], the standardized guidelines for conducting flood-frequency analysis, is that basins without major hydrologic alterations, such as regulation or urbanization, exhibit stationary statistical properties of the distribution of annual peak streamflow. That is, the mean, variance, and skew are constant over time and the peak-flow record is a representative sample of the population of future floods [1]. In recent decades, better understanding of long-term climatic persistence and concerns about climate and land-use change have caused the assumption of stationarity in peak-flow records to be reexamined [2, 3, 4, 5]. Under nonstationary conditions, the long-term distributional properties (mean, variance, and/or skew) of peak-flow series change one or more times, either gradually or abruptly. Nonstationarities may be attributed to one source, but are often a result of a mixture of drivers, making detection and attribution of nonstationarities challenging [6, 7, 8]. Failure to incorporate observed trends and abrupt changes into flood-frequency analysis may result in a poor representation of the true flood risk. Bulletin 17C currently offers no guidance on how to account for nonstationarities when estimating floods and acknowledges the benefit additional flood frequency studies that incorporate changing climate or basin characteristics into the analysis would provide[1].

Midwest↗

USGS2022

Estimated daily mean streamflow in Iowa using the Flow-Duration Curve Transfer Method StreamStats application

The U.S. Geological Survey (USGS) operates many streamgages throughout the country that provide historical and real-time daily streamflow information. Accurate estimates of daily streamflow and the percentage of time that a certain volume of streamflow occurs or is exceeded in a stream is crucial information for structure design and other activities conducted by federal, state, and local officials. However, many important locations are ungaged and therefore lack the in-depth data provided at streamgages. The USGS provides hydrologic information like streamflow statistics and drainage basin characteristics in the web-based tool StreamStats (https://streamstats.usgs.gov/ss/). A newly released StreamStats functionality developed by the StreamStats development team working closely with USGS scientists in the Central Midwest Water Science Center incorporates flow-duration statistics already available at USGS streamgages to calculate daily mean streamflow estimates for rural, ungaged locations in Iowa [1].

Iowa↗

USGS2014

Estimation of regional flow-duration curves for Indiana and Illinois

Flow-duration curves (FDCs) of daily streamflow are useful for many applications in water resources planning and management but must be estimated at ungaged sites. One common technique for estimating FDCs at ungaged sites in a given region is to use equations obtained by linear regression of FDC quantiles against multiple basin characteristics that can be computed by means of a geographic information system (GIS) computer program. In this study, such regional regression equations for estimating FDC quantiles were computed at the 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 98, 99, 99.5, 99.8, and 99.9-percent exceedance probabilities for rural, unregulated streams in Indiana and Illinois with temporally stationary records, using data through September 30, 2007. The approach used accounts for censored values below 0.01 cubic feet per second, which are observed at exceedance probabilities as low as 70 percent (that is, occurring at least 30 percent of the time). The basin characteristics used are suitable for computation by the USGS Web-based application, StreamStats, and are available for all U.S. Environmental Protection Agency (EPA) Region V states and the larger Great Lakes area, with some specific local exceptions. Indiana and Illinois were each divided into three regions, and a different set of equations for estimating FDC quantiles was computed for each region. The error of estimation of the FDC quantiles, measured as the mean square residual in log space converted to a percentage of the quantile, varies somewhat among regions and varies strongly with exceedance probability, with a minimum error of 10 to 20 percent at an exceedance probability of 5 or 10 percent, but rises to 17 to 38 percent at the high-flow end of the FDCs (the 0.1-percent quantile) and 100 to 745 percent at the low-flow end. For comparison, errors of estimation also were computed for FDC quantiles estimated by linear regression on drainage area alone and by using the drainage-area ratio (DAR) method. Three criteria, the nearest basin centroid and two others termed “strict” and “broad”, were used to select index stations for the DAR method. The “strict” and “broad” criteria put conditions on the basin centroid distance and the range of their drainage-area ratios, and the errors were averaged for all index station pairs satisfying each criterion. The use of the simpler DAR method usually resulted in higher errors of estimation compared to the linear regression equations with multiple basin characteristics, except occasionally in the case of the DAR method with the strict index station selection criterion, a criterion that is rarely possible to satisfy in practice. An example application of the estimated equations to one gaged and a few ungaged locations in a watershed in the study area is included to illustrate the steps required. These steps are the computation of the basin characteristics and, using those characteristics together with the estimated equations, the computation of the FDC quantiles and their uncertainties.

Illinois, Indiana↗