Geology topics

Research about Iowa

Source-linked reports with geographic coverage including Iowa.

At least 91 records · Page 5Linked to original sources

USGS2018

Specific conductance as a tracer of preferential flow in a subsurface-drained field

Specific conductance (SC), soil volumetric water content (VWC), and discharge were monitored on a subsurface agricultural drain for a 2-yr period (2007–2008) to differentiate preferential flow paths from matrix flow paths. A major observation from the 2-yr period was the fast SC decrease after relatively small rainfall events, often <5 mm. A total of 25 paired rainfall–SC events were classified, with an average preferential flow onset time (from the event start) after 1.7 h and maximum preferential flow after 2.4 h. A specific conductance end-member mixing analysis (SC-EMMA) was used to determine the volume of water that infiltrated through preferential flow pathways. The SC-EMMA was used for 20 of the 25 paired rainfall–SC events; of the 20 classified events, the maximum preferential flow ranged from 11 to 75% of the total subsurface drain flow, with a mean maximum preferential flow of 31%. Overall, SC-EMMA illustrated that a significant portion of the subsurface drain discharge can be attributed to preferential flow, mainly through macropores or other largely open preferential flow pathways. The other primary mechanism, antecedent moisture conditions shifts, could only be shown for four of the 25 classified events. Specific conductance as a tracer of preferential flow was shown to be an effective tool for distinguishing preferential flow to subsurface drains. Even during relatively dry periods, the SC had a substantial decrease shortly after a rainfall event contrary to the conventional idea that macropore flow starts only after all the smaller pores are saturated and surface ponding begins to occur.

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USGS2018

A case study and a meta-analysis of seasonal variation in fish mercury concentrations

Mercury contamination in aquatic ecosystems is a concern due to health risks of consuming fish. Fish mercury concentrations are highly variable and influenced by a range of environmental factors. However, seasonal variation in mercury levels are typically overlooked when monitoring fish mercury concentrations, establishing consumption advisories, or creating accumulation models. Temporal variation in sampling could bias mercury concentration estimates of accumulation potential. Thus, the objectives of this study were to first evaluate seasonal variation of largemouth bass ( Micropterus salmoides ) axial muscle mercury concentration from two Iowa, USA impoundments. Second, we conducted a meta-analysis to evaluate if seasonal variation in mercury concentration is dependent upon mean mercury concentration, waterbody type, or fish trophic level or mean length. Largemouth bass were collected four times between May and October (24–36 fish per month) from Twelve Mile (2013) and Red Haw (2014) lakes. Largemouth bass axial muscle mercury concentrations were variable within and between lakes, ranging from undetectable ( < 0.05 mg/kg) to 0.54 mg/kg. Largemouth bass mercury concentrations were similar across months in Twelve Mile but varied temporally in Red Haw and were highest in July, intermediate in May and September, and lowest during October. Results of the meta-analysis suggest that seasonal variation in mercury concentrations is more likely to occur as mean mercury concentration of the population increases but is unrelated to waterbody type, trophic status, and fish size. Understanding seasonal variation in fish mercury concentrations will aid in the development of standardized sampling programs for long-term monitoring programs and fish consumption advisories.

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USGS2018

Flood-inundation and flood-mitigation modeling of the West Branch Wapsinonoc Creek Watershed in West Branch, Iowa

The U.S. Geological Survey (USGS) in cooperation with the city of West Branch and the Herbert Hoover National Historic Site of the National Park Service assessed flood-mitigation scenarios within the West Branch Wapsinonoc Creek watershed. The scenarios are intended to demonstrate several means of decreasing peak streamflows and improving the conveyance of overbank flows from the West Branch Wapsinonoc Creek and its tributary Hoover Creek where they flow through the city and the Herbert Hoover National Historic Site located within the city. Hydrologic and hydraulic models of the watershed were constructed to assess the flood-mitigation scenarios. To accomplish this, the models used the U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS) version 4.2 to simulate the amount of runoff and streamflow produced from single rain events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS) version 5.0 was then used to construct an unsteady-state model that may be used for routing streamflows, mapping areas that may be inundated during floods, and simulating the effects of different measures taken to decrease the effects of floods on people and infrastructure. Both models were calibrated to three historic rainfall events that produced peak streamflows ranging between the 2-year and 10-year flood-frequency recurrence intervals at the USGS streamgage (05464942) on Hoover Creek. The historic rainfall events were calibrated by using data from two USGS streamgages along with surveyed high-water marks from one of the events. The calibrated HEC–HMS model was then used to simulate streamflows from design rainfall events of 24-hour duration ranging from a 20-percent to a 1-percent annual exceedance probability. These simulated streamflows were incorporated into the HEC–RAS model. The unsteady-state HEC–RAS model was calibrated to represent existing conditions within the watershed. HEC–RAS model simulations with the existing conditions and streamflows from the design rainfall events were then done to serve as a baseline for evaluating flood-mitigation scenarios. After these simulations were completed, three different flood-mitigation scenarios were developed with HEC–RAS: a detention-storage scenario, a conveyance improvement scenario, and a combination of both. In the detention-storage scenario, four in-channel detention structures were placed upstream from the city of West Branch to attenuate peak streamflows. To investigate possible improvements to conveying floodwaters through the city of West Branch, a section of abandoned railroad embankment and an old truss bridge were removed in the model, because these structures were producing backwater areas during flooding events. The third scenario combines the detention and conveyance scenarios so their joint efficiency could be evaluated. The scenarios with the design rainfall events were run in the HEC–RAS model so their flood-mitigation effects could be analyzed across a wide range of flood magnitudes.

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USGS2018

Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa

Basin-characteristic measurements related to stream length, stream slope, stream density, and stream order have been identified as significant variables for estimation of flood, flow-duration, and low-flow discharges in Iowa. The placement of channel initiation points, however, has always been a matter of individual interpretation, leading to differences in stream definitions between analysts. This study investigated five different methods to define stream initiation using 3-meter light detection and ranging (lidar) digital elevation models (DEMs) data for 17 streamgages with drainage areas less than 50 square miles within the Des Moines Lobe landform region in north-central Iowa. Each DEM was hydrologically enforced and the five stream initiation methods were used to define channel initiation points and the downstream flow paths. The five different methods to define stream initiation were tested side-by-side for three watershed delineations: (1) the total drainage-area delineation, (2) an effective drainage-area delineation of basins based on a 2-percent annual exceedance probability (AEP) 12-hour rainfall, and (3) an effective drainage-area delineation based on a 20-percent AEP 12-hour rainfall. Generalized least squares regression analysis was used to develop a set of equations for sites in the Des Moines Lobe landform region for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs. A total of 17 streamgages were included in the development of the regression equations. In addition, geographic information system software was used to measure 58 selected basin-characteristics for each streamgage. Results of the regression analyses of the 15 lidar datasets indicate that the datasets that produce regional regression equations (RREs) with the best overall predictive accuracy are the National Hydrographic Dataset, Iowa Department of Natural Resources, and profile curvature of 0.5 stream initiation methods combined with the 20-percent AEP 12-hour rainfall watershed delineation method. These RREs have a mean average standard error of prediction (SEP) for 4-, 2-, and 1-percent AEP discharges of 53.9 percent and a mean SEP for all eight AEPs of 55.5 percent. Compared to the RREs developed in this study using the basin characteristics from the U.S. Geological Survey StreamStats application, the lidar basin characteristics provide better overall predictive accuracy.

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USGS2018

Flood of August 24–25, 2016, Upper Iowa River and Turkey River, northeastern Iowa

Major flooding occurred August 24–25, 2016, in the Upper Iowa River Basin and Turkey River Basin in northeastern Iowa following severe thunderstorm activity over the region. About 8 inches of rain were recorded for the 24-hour period ending at 4 p.m., August 24, at Decorah, Iowa, and about 6 inches of rain were recorded for the 24-hour period ending at 7 a.m., August 24, at Cresco, Iowa, about 14 miles northwest of Spillville, Iowa. A maximum peak-of-record discharge of 38,000 cubic feet per second in the Upper Iowa River at streamgage 05388250 Upper Iowa River near Dorchester, Iowa, occurred on August 24, 2016, with an annual exceedance-probability range of 0.2–1 percent. High-water marks were measured at six locations along the Upper Iowa River between State Highway 26 near the mouth at the Mississippi River and State Highway 76 about 3.5 miles south of Dorchester, Iowa, a distance of 15 river miles. Along the profiled reach of the Turkey River, a maximum peak-of-record discharge of 15,300 cubic feet per second at streamgage 05411600 Turkey River at Spillville, Iowa, occurred on August 24, 2016, with an annual exceedance-probability range of 1–2 percent. A maximum peak discharge of 35,700 cubic feet per second occurred on August 25, 2016, along the profiled reach of the Turkey River at streamgage 05411850 Turkey River near Eldorado, Iowa, with an annual exceedance-probability range of 0.2–1 percent. High-water marks were measured at 11 locations along the Turkey River between County Road B64 in Elgin and 220th Street, located about 4.5 miles northwest of Spillville, Iowa, a distance of 58 river miles. The high-water marks were used to develop flood profiles for the Upper Iowa River and Turkey River.

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USGS2017

Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations. A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa. The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System models of 12 river basins in western Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

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USGS2017

Intra‐annual variability of Silver Carp populations in the Des Moines River, USA

Since their introduction in the 1970s, Silver Carp Hypophthalmichthys molitrix have spread throughout the Mississippi River basin. Management of any species relies on an accurate understanding of population characteristics and dynamics. However, Silver Carp seasonal sampling variation is unknown. Sampling during periods of peak catch rates would facilitate Silver Carp assessment and management, improving monitoring and removal techniques. The objective of this study was to evaluate adult Silver Carp seasonal sampling variation with boat electroshocking and trammel nets. Silver Carp were collected monthly (April–October) during 2014 and 2015 from four locations in the Des Moines River, Iowa. Trammel nets rarely captured Silver Carp (mean ± SE = 4.9 ± 1.6 fish/net; 60% of fish were captured in 6.3% of net sets) and therefore were not included in analyses. Electroshocking catch rates (CPUEs) exhibited a bimodal distribution, with peak CPUEs generally occurring in May, June, and September and lower catch rates observed during July and August. Catch rates were positively related to river discharge at upstream sites but not at downstream sites. Silver Carp size structure was similar among months and sites except at Cliffland, where fish were smaller during August and October compared to earlier in the year. Finally, Silver Carp condition peaked during April and May and decreased throughout the year except at Keokuk, where peaks were observed during both May and August. Although spatiotemporal variability was substantial, these results suggest that sampling of Silver Carp via electroshocking in May–June and September–October generally produces higher catch rates compared to July–August sampling and generates a more representative size structure. Using site‐specific knowledge, monitoring and surveillance programs could more effectively sample during these periods of high vulnerability and densities in order to manage the spread and impacts of Silver Carp at statewide and regionwide scales.

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USGS2017

Highlighting the complexities of a groundwater pilot study during an avian influenza outbreak: Methods, lessons learned, and select contaminant results

The highly pathogenic avian influenza (H5N2) outbreak in the Midwestern United States (US) in 2015 was historic due to the number of birds and poultry operations impacted and the corresponding economic loss to the poultry industry and was the largest animal health emergency in US history. The U.S. Geological Survey (USGS), with the assistance of several state and federal agencies, aided the response to the outbreak by developing a study to determine the extent of virus transport in the environment. The study goals were to: develop the appropriate sampling methods and protocols for measuring avian influenza virus (AIV) in groundwater, provide the first baseline data on AIV and outbreak- and poultry-related contaminant occurrence and movement into groundwater, and document climatological factors that may have affected both survival and transport of AIV to groundwater during the months of the 2015 outbreak. While site selection was expedient, there were often delays in sample response times due to both relationship building between agencies, groups, and producers and logistical time constraints. This study's design and sampling process highlights the unpredictable nature of disease outbreaks and the corresponding difficulty in environmental sampling of such events. The lessons learned, including field protocols and approaches, can be used to improve future research on AIV in the environment.

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USGS2017

Response of anurans to wetland restoration on a midwestern agriculture landscape

Since the early 1990s, >5,000 ha of historic wetlands (and adjacent prairie) have been restored on the row-crop agricultural landscape of Winnebago County, Iowa, USA. From 2008–2011, we surveyed 22 of these sites for probabilities of occupancy and colonization by Boreal Chorus Frogs (BCF; Pseudacris maculata ), Northern Leopard Frogs (NLF; Lithobates pipiens ), and American Toads (AT; Anaxyrus americanus ). We used radio telemetry to measure patterns of movement and habitat use by 22 NLF and 54 AT and deployed biophysical models in available habitats to estimate their physiological costs. The BCF occupied 100% of restored wetlands; NLF and AT occupied 59–91% and 71–89%, respectively, varying according to annual weather conditions. The BCF colonized new sites within a year; NLF and AT required 3 and 2 yr, respectively. These differences were related to distances from the nearest established population and costs of intervening cover types, and were statistically related to the size and orientation of restored wetlands. The ranges of maximum straight-line distances moved by NLF and AT were 31–857 m and 42–2,932 m, respectively. Both NLF and AT selected wetlands and surrounding prairies, though NLF were nine times more likely to select wetland habitats than all others combined. About 24% of AT used row-crop fields extensively, but not until crops had grown sufficiently to reduce the physiological costs of these fields similar to that of prairies. Both BCF and AT navigated the dramatically altered row-crop landscape, but NLF depended more heavily on roadside ditches to find and colonize restored wetlands.

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USGS2017

Methods for estimating selected low-flow frequency statistics and harmonic mean flows for streams in Iowa

A statewide study was conducted to develop regression equations for estimating six selected low-flow frequency statistics and harmonic mean flows for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include: the annual 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years, the annual 30-day mean low flow for a recurrence interval of 5 years, and the seasonal (October 1 through December 31) 1- and 7-day mean low flows for a recurrence interval of 10 years. Estimation equations also were developed for the harmonic-mean-flow statistic. Estimates of these seven selected statistics are provided for 208 U.S. Geological Survey continuous-record streamgages using data through September 30, 2006. The study area comprises streamgages located within Iowa and 50 miles beyond the State's borders. Because trend analyses indicated statistically significant positive trends when considering the entire period of record for the majority of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. The median number of years of record used to compute each of these seven selected statistics was 35. Geographic information system software was used to measure 54 selected basin characteristics for each streamgage. Following the removal of two streamgages from the initial data set, data collected for 206 streamgages were compiled to investigate three approaches for regionalization of the seven selected statistics. Regionalization, a process using statistical regression analysis, provides a relation for efficiently transferring information from a group of streamgages in a region to ungaged sites in the region. The three regionalization approaches tested included statewide, regional, and region-of-influence regressions. For the regional regression, the study area was divided into three low-flow regions on the basis of hydrologic characteristics, landform regions, and soil regions. A comparison of root mean square errors and average standard errors of prediction for the statewide, regional, and region-of-influence regressions determined that the regional regression provided the best estimates of the seven selected statistics at ungaged sites in Iowa. Because a significant number of streams in Iowa reach zero flow as their minimum flow during low-flow years, four different types of regression analyses were used: left-censored, logistic, generalized-least-squares, and weighted-least-squares regression. A total of 192 streamgages were included in the development of 27 regression equations for the three low-flow regions. For the northeast and northwest regions, a censoring threshold was used to develop 12 left-censored regression equations to estimate the 6 low-flow frequency statistics for each region. For the southern region a total of 12 regression equations were developed; 6 logistic regression equations were developed to estimate the probability of zero flow for the 6 low-flow frequency statistics and 6 generalized least-squares regression equations were developed to estimate the 6 low-flow frequency statistics, if nonzero flow is estimated first by use of the logistic equations. A weighted-least-squares regression equation was developed for each region to estimate the harmonic-mean-flow statistic. Average standard errors of estimate for the left-censored equations for the northeast region range from 64.7 to 88.1 percent and for the northwest region range from 85.8 to 111.8 percent. Misclassification percentages for the logistic equations for the southern region range from 5.6 to 14.0 percent. Average standard errors of prediction for generalized least-squares equations for the southern region range from 71.7 to 98.9 percent and pseudo coefficients of determination for the generalized-least-squares equations range from 87.7 to 91.8 percent. Average standard errors of prediction for weighted-least-squares equations developed for estimating the harmonic-mean-flow statistic for each of the three regions range from 66.4 to 80.4 percent. The regression equations are applicable only to stream sites in Iowa with low flows not significantly affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. If the equations are used at ungaged sites on regulated streams, or on streams affected by water-supply and agricultural withdrawals, then the estimates will need to be adjusted by the amount of regulation or withdrawal to estimate the actual flow conditions if that is of interest. Caution is advised when applying the equations for basins with characteristics near the applicable limits of the equations and for basins located in karst topography. A test of two drainage-area ratio methods using 31 pairs of streamgages, for the annual 7-day mean low-flow statistic for a recurrence interval of 10 years, indicates a weighted drainage-area ratio method provides better estimates than regional regression equations for an ungaged site on a gaged stream in Iowa when the drainage-area ratio is between 0.5 and 1.4. These regression equations will be implemented within the U.S. Geological Survey StreamStats web-based geographic-information-system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the seven selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these seven selected statistics are provided for the streamgage.

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USGS2017

Amphibians, pesticides, and the amphibian chytrid fungus in restored wetlands in agricultural landscapes

Information on interactions between pesticide exposure and disease prevalence in amphibian populations is limited, especially from field data. Exposure to certain herbicides and insecticides has the potential to decrease the immune response in frogs, which can potentially lead to increased abundance of Batrachochytrium dendrobatidis (Bd) zoospores on individuals and in the wetlands. In contrast, exposure to certain fungicides can decrease Bd abundance on frog skin. We examined the relationships between the abundance of Bd on the skin of individual Boreal Chorus Frogs (Pseudacris maculata) and the concentrations of pesticides in the water and in frog tissue at six agriculturally dominated wetlands in Iowa, USA. We collected frogs from each wetland, swabbed them for Bd, and analyzed their tissues for a suite of fungicides, herbicides, and insecticides. We collected surface water from the wetlands and we analyzed it for the same suite of pesticides. We observed no relationship between Bd zoospores on the skin of individual frogs and the concentrations of total pesticides, total herbicides/insecticides and total fungicides in frog tissue. Similarly, we observed no relationship between Bd zoospore abundance in water and the concentration of total pesticides or total herbicides in water. However, we observed a negative relationship between Bd zoospore abundance in water and neonicotinoid concentrations in surface water. Negative results are seldom reported but can be important contributors to a more complete understanding of the complex and potentially synergistic relationships between disease and pesticides. Data from field studies on these relationships are particularly scarce. As our laboratory understanding of these relationships expands, the need for field based, or applied, studies grow.

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USGS2017

Long-term changes in Canade Goose nest success and nest densities at an Iowa wetland complex

Giant Canada geese ( Branta canadensis maxima ) were extirpated from Iowa by the early 1900s due to unregulated hunting, egg gathering, and wetland drainage in the nineteenth century (Bishop 1978). Ef- forts to reintroduce Canada geese in Iowa began in 1964 (Bishop and Howing 1972) and involved releasing flightless adults and goslings at nearly 30 sites across the state (Zenner and LaGrange 1998a). In 1972, 13 flightless pairs were released at Rice Lake Wildlife Management Area (WMA; Bishop 1978). By 1989, the breeding population of Canada geese at Rice Lake WMA had increased to 420 nesting adults (G. G. Zenner, Iowa Department of Natural Resources, unpublished data). Canada goose nest success and nest densities were documented from 1989–1991 on extant islands at Rice Lake WMA (Zenner and LaGrange 1998b).

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USGS2016

Canada goose nest survival at rural wetlands in north-central Iowa

The last comprehensive nest survival study of the breeding giant Canada goose ( Branta canadensis maxima ) population in Iowa, USA, was conducted >30 years ago during a period of population recovery, during which available nesting habitat consisted primarily of artificial nest structures. Currently, Iowa's resident goose population is stable and nests in a variety of habitats. We analyzed the effects of available habitat on nest survival and how nest survival rates compared with those of the expanding goose population studied previously to better understand how to maintain a sustainable Canada goose population in Iowa. We documented Canada goose nest survival at rural wetland sites in north-central Iowa. We monitored 121 nests in 2013 and 149 nests in 2014 at 5 Wildlife Management Areas (WMAs) with various nesting habitats, including islands, muskrat ( Ondatra zibethicus ) houses, and elevated nest structures. We estimated daily nest-survival rate using the nest survival model in Program MARK. Survival was influenced by year, site, stage, presence of a camera, nest age, and an interaction between nest age and stage. Nest success rates for the 28-day incubation period by site and year combination ranged from 0.10 to 0.84. Nest survival was greatest at sites with nest structures (β = 17.34). Nest survival was negatively affected by lowered water levels at Rice Lake WMA (2013 β = −0.77, nest age β = −0.07). Timing of water-level drawdowns for shallow lake restorations may influence nest survival rates.

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USGS2016

Methods for estimating selected spring and fall low-flow frequency statistics for ungaged stream sites in Iowa, based on data through June 2014

A statewide study was led to develop regression equations for estimating three selected spring and three selected fall low-flow frequency statistics for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include spring (April through June) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and fall (October through December) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years. Estimates of the three selected spring statistics are provided for 241 U.S. Geological Survey continuous-record streamgages, and estimates of the three selected fall statistics are provided for 238 of these streamgages, using data through June 2014. Because only 9 years of fall streamflow record were available, three streamgages included in the development of the spring regression equations were not included in the development of the fall regression equations. Because of regulation, diversion, or urbanization, 30 of the 241 streamgages were not included in the development of the regression equations. The study area includes Iowa and adjacent areas within 50 miles of the Iowa border. Because trend analyses indicated statistically significant positive trends when considering the period of record for most of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. Geographic information system software was used to measure 63 selected basin characteristics for each of the 211streamgages used to develop the regional regression equations. The study area was divided into three low-flow regions that were defined in a previous study for the development of regional regression equations. Because several streamgages included in the development of regional regression equations have estimates of zero flow calculated from observed streamflow for selected spring and fall low-flow frequency statistics, the final equations for the three low-flow regions were developed using two types of regression analyses—left-censored and generalized-least-squares regression analyses. A total of 211 streamgages were included in the development of nine spring regression equations—three equations for each of the three low-flow regions. A total of 208 streamgages were included in the development of nine fall regression equations—three equations for each of the three low-flow regions. A censoring threshold was used to develop 15 left-censored regression equations to estimate the three fall low-flow frequency statistics for each of the three low-flow regions and to estimate the three spring low-flow frequency statistics for the southern and northwest regions. For the northeast region, generalized-least-squares regression was used to develop three equations to estimate the three spring low-flow frequency statistics. For the northeast region, average standard errors of prediction range from 32.4 to 48.4 percent for the spring equations and average standard errors of estimate range from 56.4 to 73.8 percent for the fall equations. For the northwest region, average standard errors of estimate range from 58.9 to 62.1 percent for the spring equations and from 83.2 to 109.4 percent for the fall equations. For the southern region, average standard errors of estimate range from 43.2 to 64.0 percent for the spring equations and from 78.1 to 78.7 percent for the fall equations. The regression equations are applicable only to stream sites in Iowa with low flows not substantially affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. The regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system application. StreamStats allows users to click on any ungaged stream site and compute estimates of the six selected spring and fall low-flow statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged site are provided. StreamStats also allows users to click on any Iowa streamgage to obtain computed estimates for the six selected spring and fall low-flow statistics.

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USGS2016

Phosphorus in sediment in the Kent Park Lake watershed, Johnson County, Iowa, 2014–15

Phosphorus data were collected from the Kent Park Lake watershed in Johnson County, Iowa, in 2014 and 2015 to obtain information to assist in the management of the water quality in the lake. Phosphorus concentrations were measured for sediment from several ponds in the watershed and sediment deposited in the lake. The first set of samples was collected in 2014 to understand phosphorus in several potential sources to the lake and the spatial variability in lake sediments. Phosphorus concentrations ranged from 68 to 380 milligrams per kilogram in lake sediment and from 57 to 220 milligrams per kilogram in sedimentation and dredge spoil ponds. Additional samples were collected in 2015 to determine how phosphorus concentrations vary with depth in the lake sediment. Phosphorus concentrations generally decreased with increasing depth within the lake sediment. In 2015, total phosphorus concentrations in lake sediment ranged from 50 to 340 milligrams per kilogram.

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USGS2016

Statistical summaries of selected Iowa streamflow data through September 2013

Statistical summaries of streamflow data collected at 184 streamgages in Iowa are presented in this report. All streamgages included for analysis have at least 10 years of continuous record collected before or through September 2013. This report is an update to two previously published reports that presented statistical summaries of selected Iowa streamflow data through September 1988 and September 1996. The statistical summaries include (1) monthly and annual flow durations, (2) annual exceedance probabilities of instantaneous peak discharges (flood frequencies), (3) annual exceedance probabilities of high discharges, and (4) annual nonexceedance probabilities of low discharges and seasonal low discharges. Also presented for each streamgage are graphs of the annual mean discharges, mean annual mean discharges, 50-percent annual flow-duration discharges (median flows), harmonic mean flows, mean daily mean discharges, and flow-duration curves. Two sets of statistical summaries are presented for each streamgage, which include (1) long-term statistics for the entire period of streamflow record and (2) recent-term statistics for or during the 30-year period of record from 1984 to 2013. The recent-term statistics are only calculated for streamgages with streamflow records pre-dating the 1984 water year and with at least 10 years of record during 1984–2013. The streamflow statistics in this report are not adjusted for the effects of water use; although some of this water is used consumptively, most of it is returned to the streams.

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USGS2016

Detection of hepatitis E virus and other livestock-related pathogens in Iowa streams

Manure application is a source of pathogens to the environment. Through overland runoff and tile drainage, zoonotic pathogens can contaminate surface water and streambed sediment and could affect both wildlife and human health. This study examined the environmental occurrence of gene markers for livestock-related bacterial, protozoan, and viral pathogens and antibiotic resistance in surface waters within the South Fork Iowa River basin before and after periods of swine manure application on agricultural land. Increased concentrations of indicator bacteria after manure application exceeding Iowa's state bacteria water quality standards suggest that swine manure contributes to diminished water quality and may pose a risk to human health. Additionally, the occurrence of HEV and numerous bacterial pathogen genes for Escherichia coli , Enterococcus spp., Salmonella sp., and Staphylococcus aureus in both manure samples and in corresponding surface water following periods of manure application suggests a potential role for swine in the spreading of zoonotic pathogens to the surrounding environment. During this study, several zoonotic pathogens were detected including Shiga-toxin producing E. coli , Campylobacter jejuni , pathogenic enterococci, and S. aureus ; all of which can pose mild to serious health risks to swine, humans, and other wildlife. This research provides the foundational understanding required for future assessment of the risk to environmental health from livestock-related zoonotic pathogen exposures in this region. This information could also be important for maintaining swine herd biosecurity and protecting the health of wildlife near swine facilities.

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USGS2016

Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)

Nitrate-nitrogen is a common contaminant of drinking water in many agricultural areas of the United States of America (USA). Ingested nitrate from contaminated drinking water has been linked to an increased risk of several cancers, specific birth defects, and other diseases. In this research, we assessed the relationship between animal feeding operations (AFOs) and groundwater nitrate in private wells in Iowa. We characterized AFOs by swine and total animal units and type (open, confined, or mixed), and we evaluated the number and spatial intensities of AFOs in proximity to private wells. The types of AFO indicate the extent to which a facility is enclosed by a roof. Using linear regression models, we found significant positive associations between the total number of AFOs within 2 km of a well (p trend < 0.001), number of open AFOs within 5 km of a well (p trend < 0.001), and number of mixed AFOs within 30 km of a well (p trend < 0.001) and the log nitrate concentration. Additionally, we found significant increases in log nitrate in the top quartiles for AFO spatial intensity, open AFO spatial intensity, and mixed AFO spatial intensity compared to the bottom quartile (0.171 log(mg/L), 0.319 log(mg/L), and 0.541 log(mg/L), respectively; all p < 0.001). We also explored the spatial distribution of nitrate-nitrogen in drinking wells and found significant spatial clustering of high-nitrate wells (> 5 mg/L) compared with low-nitrate (≤ 5 mg/L) wells ( p = 0.001). A generalized additive model for high-nitrate status identified statistically significant areas of risk for high levels of nitrate. Adjustment for some AFO predictor variables explained a portion of the elevated nitrate risk. These results support a relationship between animal feeding operations and groundwater nitrate concentrations and differences in nitrate loss from confined AFOs vs. open or mixed types.

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