Geology topics

Hannah Lee Podzorski

Publications and source records attributed to Hannah Lee Podzorski.

6 recordsLinked to original sources

USGS2026

Spatially consistent but temporally divergent changes in nitrate and phosphorus loads and yields in Illinois watersheds, 1997–2022

Illinois contributes substantial nutrient loads to the Gulf of America, warranting watershed-scale assessment. This study estimated nitrate-nitrogen (nitrate-N) and total phosphorus (TP) loads and yields for 49 Illinois 8-digit hydrologic unit code (HUC8) watersheds draining to the Mississippi River Basin from 1997–2022, comparing recent (2018–2022) to baseline (1997–2011) conditions. Estimates included point and nonpoint source contributions, dissolved phosphorus, and water yields. During the recent period, nonpoint sources dominated nutrient export (82% nitrate-N, 78% TP), though point sources drove high yields in the Chicago area. Spatially, nonpoint source nutrient hotspots persisted with nitrate-N yields highest in east-central and northern Illinois and TP yields higher in southern and western Illinois. Temporally, statewide nitrate-N loads decreased 9%, while TP loads increased 27%. Nitrate-N yields increased in 22 HUC8s and decreased in 20, while TP yields increased in 32 HUC8s and decreased in 9. For both nutrients, baseline yields were negatively correlated with yield changes, indicating high-yielding watersheds tended toward larger decreases or smaller increases. Water yields increased 19% on average but were weakly correlated with nutrient yield changes ( r = 0.23 and 0.20 for nitrate-N and TP). These results reveal spatially persistent yet temporally divergent nutrient export across Illinois, with contrasting nitrate-N and TP trajectories for nonpoint sources.

Illinois↗

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

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

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↗

USGS2025

Diverging trends in nitrate and phosphorus loads and yields across Illinois watersheds, 1997–2022

Illinois is a major contributor of nutrients to the northern Gulf of Mexico. As such, the State of Illinois initiated efforts to curb nutrient runoff over the last several decades. To evaluate progress towards these reductions, water-quality data were used to estimate incremental loads and yields of nitrate plus nitrite (NO3) and total phosphorus (TP) from 1997–2022 for 49 Illinois watersheds, defined using eight-digit hydrologic unit codes (HUC8), draining to the Mississippi River Basin. To estimate changes in NO3 and TP loads, recent loads from the period 2018 through 2022 were compared to baseline loads from 1997 through 2011. Nonpoint and point source loads, dissolved phosphorus (DP) loads, and water yields were also estimated. The sum of the incremental NO3 loads from the 49 HUC8s decreased 9% despite a 19% increase in water yield. Much of this decline occurred in HUC8s that had NO3 yields greater than 17 pounds per acre per year (lbs/acre/yr) during a 1997–2011 baseline period. The sum of all incremental HUC8 TP loads increased 25% despite a 27% reduction in point source discharge. Loads and yields were substantially larger for both NO3 and TP in the Chicago area. Outside the Chicago area, central and northern Illinois had higher NO3 yields than southern Illinois and a reverse pattern for TP where higher yields occur in southern Illinois. Nonpoint sources made up an estimated 82% and 78% of the NO3 and TP yields, respectively, across the HUC8s. In general, point source yields have mostly decreased over time, while nonpoint source yields varied depending on location and reflect the changes in the total yield.

Illinois↗