Geology topics

S. Mike Linhart

Publications and source records attributed to S. Mike Linhart.

9 recordsLinked to original sources

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.

Iowa↗

USGS2015

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

Iowa, Minnesota↗

USGS2013

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

Iowa↗

USGS2012

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft 3 /s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft 3 /s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft 3 /s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft 3 /s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft 3 /s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft 3 /s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

Illinois;Iowa;Minnesota;Missouri;Nebraska;Wisconsi↗

USGS2006

Bathymetric contour maps for lakes surveyed in Iowa in 2003

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources (IDNR), conducted bathymetric surveys on four lakes in Iowa during 2003 (Don Williams Lake, Easter Lake, Lake Macbride, and Lake Meyer). The purpose of the surveys is to provide the IDNR with information for the development of total maximum daily load (TMDL) limits, in particular, for estimating sediment load and deposition rates. The bathymetric surveys can provide a baseline for future work on sediment loads and deposition rates for these lakes. All lakes surveyed in 2003 are man-made lakes with fixed spillways. Bathymetric data were collected using boat-mounted, differential global positioning system (GPS) equipment, echo depth-sounding equipment, and computer software. Data were processed with commercial hydrographic software and exported into a geographic information system (GIS) for mapping and calculation of area and volume. Lake volume estimates ranged from 590,501,000 cubic feet (13,600 acre-feet) at Lake Macbride to 17,831,000 cubic feet (410 acre-feet) at Lake Meyer. Surface area estimates ranged from 38,118,000 square feet (875 acres) at Lake Macbride to 1,373,000 square feet (32 acres) at Lake Meyer.

Iowa↗

USGS2006

Bathymetric contour maps of lakes surveyed in Iowa in 2004

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted bathymetric surveys on six lakes in Iowa during 2004 (Lake Darling, Littlefield Lake, Lake Minnewashta, Nine Eagles Lake, Prairie Rose Lake, and Upper Gar Lake). The surveys were conducted to provide the Iowa Department of Natural Resources with information for the development of total maximum daily load limits, particularly for estimating sediment load and deposition rates. The bathymetric surveys can provide a baseline for future work on sediment loads and deposition rates for these lakes. Two of the lakes surveyed in 2004, Lake Minnewashta and Upper Gar Lake, are natural lakes. The other four lakes are manmade lakes with fixed spillways. Bathymetric data were collected using a boat-mounted, differential global positioning system, echo depth-sounding equipment, and computer software. Data were processed with commercial hydrographic software and exported into a geographic information system for mapping and calculating area and volume. Lake volume estimates ranged from 83,924,000 cubic feet (1,930 acre-feet) at Lake Darling to 5,967,000 cubic feet (140 acre-feet) at Upper Gar Lake. Surface area estimates ranged from 10,660,000 square feet (240 acres) at Lake Darling to 1,557,000 square feet (36 acres) at Upper Gar Lake.

Iowa↗

USGS2001

Effects of remedial grouting on the ground-water flow system at Red Rock Dam near Pella, Iowa

Previous studies have shown direct evidence of under-seepage at Red Rock Dam on the Des Moines River near Pella, Iowa. Underseepage is thought to occur primarily on the northeast side of the dam in the lower bedrock of the St. Louis Limestone, which consists of discontinuous basal evaporite beds and an overlying cavity zone. Because of concerns about the integrity of the dam, the U.S. Army Corps of Engineers initiated a remedial grouting program in September 1991. To assess the effectiveness of the remedial grouting program and to evaluate methods for future assessments, a study was conducted by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers. Potentiometric surface maps of the overburden and bedrock indicate that the direction of ground-water flow on the northeast side of the dam has changed little from pre-grout to post-grout periods. A comparison of water levels, between a pre-grout date and a post-grout date, shows that water levels decreased but that the decrease may be more attributable to changes in dam operations than to remedial grouting. Waterlevel data for the same two dates indicate that a more gradual potentiometric surface exists on the northeast side of the dam than on the southwest side of the dam, which suggests that the hydraulic connection between Lake Red Rock and downgradient bedrock wells still is greater on the northeast side of the dam than on the southwest side. Hydrographs for some wells on the northeast side of the dam indicated a departure from pre-grout trends at approximately the same time grouting was initiated. To varying degrees, hydrographs for the same wells then appear to return to a trend similar to pre-grout years, possibly as a result of new flow paths developing over time after remedial grouting. Spearman correlation coefficients computed for water levels in wells, pool, and tailwater indicate that some areas on the northeast side of the dam appear to be less under the influence of changing pool elevations after grouting than before grouting. This suggests that the hydraulic connection between the Red Rock pool and some downgradient areas has decreased. Analysis of water samples collected from selected wells on the northeast side of the dam shows significant increases in sulfate concentrations beginning about the same time remedial grouting was done upgradient from the wells, possibly indicating that flow paths were cut off to these wells, thereby reducing the amount of mixing with fresh reservoir water. Observable changes in chloride concentrations or trends as a result of remedial grouting were not apparent. Analysis results for hydrogen and oxygen stable isotope samples collected since 1995 indicate large seasonal fluctuations of isotope ratios in the tailwater (assumed representative of the reservoir). Similar but more subdued fluctuations were observed at some wells, but other wells appeared to have little seasonal change. Stable sulfur isotope results indicate the presence of distinct water types between Lake Red Rock and in ground water from downgradient bedrock wells. Sulfur isotope values from samples from a bedrock well located upgradient from the grout curtain indicate a mixture of pool and ground water, whereas samples from downgradient overburden wells have values similar to the pool. Samples from the bedrock wells downgradient from the grout curtain have sulfur isotope values similar to a value obtained from analysis of a gypsum and anhydrite core sample. Hydrographs, statistical analysis of waterlevel data, and water-chemistry data suggest that underseepage on the northeast side of the dam has been reduced but not completely eliminated. Some areas appear to have been affected to a greater degree and for a longer period of time than other areas. Future monitoring of water levels, water chemistry, and stable isotopes can aid in the evaluation of the long-term effectiveness of remedial grouting.

Iowa↗

USGS2001

Ammonia in ground water from the Mississippi River alluvium, Fort Madison, Iowa

The U.S. Geological Survey, in cooperation with the City of Fort Madison, conducted a study of the potential sources and possible processes that might produce ammonia in ground water from the Mississippi River alluvium near Fort Madison, Iowa. High ammonia concentrations of 3.0 to 6.4 milligrams per liter were detected in water produced from municipal well Fort Madison #4 from 1992 through 1996. Total organic carbon concentrations of about 5 milligrams per liter were also reported during the same time period. Water-level measurements from two municipal wells and one well at Iowa State Penitentiary were used to determine that the general direction of ground-water flow during the two days of sampling was from northeast to southwest toward wells Fort Madison #4 and Fort Madison #5. Continuous pumping of other nearby wells probably influenced the direction of ground-water flow on these days. Because of a till confining unit separating the Mississippi River and the alluvial aquifer, it is uncertain to what extent induced recharge occurs to the alluvial aquifer from the river. Water samples were collected from three municipal wells, two industrial wells, one watersupply well at the Iowa State Penitentiary, one domestic well, two creeks, and the Mississippi River. Tritium analytical results indicate that the time of recharge was after 1953 for water from the municipal wells (where tritium samples were collected). The ammonia concentration, 5.1 milligrams per liter, was considerably higher in ground water collected from well Fort Madison #4 compared to samples collected from other wells. The dissolved organic carbon concentration was also highest in ground water collected from well Fort Madison #4 (5.5 milligrams per liter) although samples from other wells were also relatively high, 2.6 to 5.3 milligrams per liter. The most likely process producing the high ammonia concentration in ground water in the vicinity of well Fort Madison #4 is decomposition of organic matter (ammonification). Nitrogen isotope values, when compared to nitrogen isotope values found in ground water in the vicinity of some of the other wells, indicate the possibility that a higher percentage of the ammonia found in ground water in the vicinity of well Fort Madison #4 may be from human and(or) other animal wastes. Higher concentrations of dissolved phosphorus, orthophosphate, and a higher chloride-to-sodium mole ratio found in ground water sampled from well Fort Madison #4 could be indicative of a sewage or septic source. Potential sources include existing or abandoned septic systems, leaking sanitary sewer lines, commercial or residential waste-disposal sites, and agricultural runoff upgradient from well Fort Madison #4, or possibly, bed sediments of the Mississippi River.

Iowa↗

USGS2000

Effects of land use and hydrogeology on the water quality of alluvial aquifers in eastern Iowa and southern Minnesota, 1997

Ground-water samples were collected from monitoring wells at 31 agricultural and 30 urban sites in the Eastern Iowa Basins study unit during June–August 1997 to evaluate the effects of land use and hydrogeology on the water quality of alluvial aquifers. Ground-water samples were analyzed for common ions, nutrients, dissolved organic carbon, tritium, radon-222, pesticides and pesticide metabolites, volatile organic compounds, and environmental isotopes. Calcium, magnesium, and bicarbonate were the dominant ions in most samples and were likely derived from solution of carbonate minerals (calcite and dolomite) present in alluvial detrital deposits. Chloride and nitrate were dominant anions in samples from several wells. Sodium and chloride concentrations were significantly higher in samples from urban areas, where roads are more numerous and road salts may be more frequently applied, than in agricultural areas. Nitrate was detected in 94 percent of samples from agricultural areas and 77 percent of samples from urban areas. Nitrate concentrations were significantly higher in agricultural areas than in urban areas and exceeded the U.S. Environmental Protection Agency maximum ontaminant level for drinking water (10 milligrams per liter as N) in 39 percent of samples from agricultural areas. Nitrate concentrations in samples from urban areas did not exceed the maximum contaminant level. Greater use of fertilizers in agricultural areas most likely contributes to higher nitrate concentrations in samples from those areas. Tritium-based ages indicate ground water was most likely recharged after the 1950’s at all but one sampling site. Agricultural and urban land-use areas have remained relatively stable in the study area since the 1950’s; therefore, the effects of current land use should be reflected in ground water sampled during this study. Radon-222 was detected in all samples and exceeded the U.S. Environmental Protection Agency’s previously proposed maximum contaminant level for drinking water (300 picocuries per liter) in 71 percent of samples. Pesticides were detected in 84 percent of samples from agricultural areas and 70 percent from urban areas. Atrazine and metolachlor were the most frequently detected pesticides in samples from agricultural areas; atrazine and prometon were the most frequently detected pesticides in samples from urban areas. None of the pesticide oncentrations exceeded U.S. Environmental Protection Agency maximum contaminant levels or lifetime health advisories for drinking water. Pesticide metabolites were detected in 94 percent of samples from agricultural areas and 53 percent from urban areas. Metolachlor ethane sulfonic acid and deethylatrazine were the most frequently detected metabolites in samples from agricultural areas; metolachlor ethane sulfonic acid and alachlor ethane sulfonic acid were the most frequently detected metabolites in samples from urban areas. Total metabolite concentrations were significantly higher in samples from agricultural areas than in samples from urban areas. Total pesticide concentrations (parent compounds) tended to be higher in samples from agricultural areas; however, this difference was not statistically significant. Metabolites constituted the major portion of the total residue concentration in the alluvial aquifer. Volatile organic compounds were detected in 40 percent of samples from urban areas and 10 percent from agricultural areas. Methyl tertbutyl ether was the most commonly detected volatile organic compound and was present in 23 percent of samples from urban areas. Elevated concentrations (greater than 30 micrograms per liter) of methyl tert-butyl ether and BTEX compounds (benzene, toluene, ethylbenzene, and xylene) in two samples from urban areas suggest the possible presence of point-source gasoline leaks or spills. Factors other than land use may contribute to observed differences in water quality between and within agricultural and urban areas. Nitrate, atrazine, deethylatrazine, and deisopropylatrazine concentrations were significantly higher in shallow wells with sample intervals nearer the water table and in wells with thinner cumulative clay thickness above the sample intervals. These relations suggest that longer flow paths allow for greater residence time and increase opportunities for sorption, degradation, and dispersion, which may contribute to decreases in nutrient and pesticide concentrations with depth. Nitrogen speciation was influenced by redox conditions. Nitrate concentrations were significantly higher in ground water with dissolved-oxygen concentrations in excess of 0.5 milligram per liter. Ammonia concentrations were higher in ground water with dissolved-oxygen concentrations of 0.5 milligram per liter or less; however, this relation was not statistically significant. The amount of available organic matter may limit denitrification rates. Elevated nitrate concentrations (greater than 2.0 mg/L) were significantly related to lower dissolved organic carbon concentrations in water samples from both agricultural and urban areas. A similar relation between nitrate concentrations (in water) and organic carbon concentrations (in aquifer material) also was observed but was not statistically significant.

Iowa, Minnesota↗