Construction and Evaluation of Submerged Vanes for Stream Control, HR-274, 1988

The objective of this study was to determine the practicality and effectiveness of using submerged vanes ("Iowa Vanes") to control bank erosion in a bend of East Nishnabotna River, Iowa. The vane system was constructed during the summer of 1985. It functions by eliminating, or reducing, the centrifugally induced helical motion of the flow in the bend, which is the root cause of bank undermining. The system was monitored over a 2-year period, from September 1985 to October 1987. Two surveys were conducted in the spring of 1986 in which data were taken of depths and velocities throughout the bend and of water-surface slope. The movement of the bank was determined from aerial photos and from repeated measurements of the vane-to-bank distance. The bankfull scour depths and velocities along the bank have been reduced significantly; and the movement of the bank has been stopped or considerably reduced. The improvements were obtained without changing the energy slope of the channel. Areas of design improvements were identified.

Survey of Users of the USGS Stream-Gaging Network in Iowa, 1996, HR-383, 1996

A survey was sent to over 200 Federal, State, and local agencies that might use streamflow data collected by the U. S. Geological Survey in Iowa. A total of 181 forms were returned and 112 agencies indicated that they use streamflow data. The responses show that streamflow data from the Iowa USGS stream-gaging network, which in 1996 is composed of 117 stations, are used by many agencies for many purposes and that many stations provide streamflow data that fulfill a variety of joint purposes. The median number of respondents per station that use data from the station was 6 and the median number of data-use categories indicated per station was 9. The survey results can be used by agencies that fund the Iowa USGS stream-gaging network to help them decide which stations to continue to support if it becomes necessary to reduce the size of the stream-gaging network.

Stream Stabilization in Western Iowa: Structure Evaluation and Design Manual, HR-385, 1998

Stream degradation is the action of deepening the stream bed and widening the banks due to the increasing velocity of water flow. Degradation is pervasive in channeled streams found within the deep to moderately deep loess regions of the central United States. Of all the streams, however, the most severe and widespread entrenchment occurs in western Iowa streams that are tributaries to the Missouri River. In September 1995 the Iowa Department of Transportation awarded a grant to Golden Hills Resource Conservation and Development, Inc. The purpose of the grant, HR-385 "Stream Stabilization in Western Iowa: Structure Evaluation and Design Manual", was to provide an assessment of the effectiveness and costs of various stabilization structures in controlling erosion on channeled streams. A review of literature, a survey of professionals, field observations and an analysis of the data recorded on fifty-two selected structures led to the conclusions presented in the project's publication, Design Manual, Streambed Degradation and Streambank Widening in Western Iowa. Technical standards and specifications for the design and construction of stream channel stabilization structures are included in the manual. Additional information on non-structural measures, monitoring and evaluation of structures, various permit requirements and further resources are also included. Findings of the research project and use and applications of the Design Manual were presented at two workshops in the Loess Hills region. Participants in these workshops included county engineers, private contractors, state and federal agency personnel, elected officials and others. The Design Manual continues to be available through Golden Hills Resource Conservation and Development.

Data Acquisition and Computer Plotting of Delamtect Data, HR-269, 1985

The overall system is designed to permit automatic collection of delamination field data for bridge decks. In addition to measuring and recording the data in the field, the system provides for transferring the recorded data to a personal computer for processing and plotting. This permits rapid turnaround from data collection to a finished plot of the results in a fraction of the time previously required for manual analysis of the analog data captured on a strip chart recorder. In normal operation the Delamtect provides an analog voltage for each of two channels which is proportional to the extent of any delamination. These voltages are recorded on a strip chart for later visual analysis. An event marker voltage, produced by a momentary push button on the handle, is also provided by the Delamtect and recorded on a third channel of the analog recorder.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Stream Stabilization in Western Iowa, HR-352, 1994

Stream channel erosion in the deep loess soils region of western Iowa causes severe damage along hundreds of miles of streams in twenty-two counties. The goal of this project was to develop information, systems, and procedures for use in making resource allocation decisions related to the protection of transportation facilities and farmland from damages caused by stream channel erosion. Section one of this report provides an introduction. Section two presents an assessment of stream channel conditions from aerial and field reconnaissance conducted in 1993 and 1994 and a classification of the streams based on a six stage model of stream channel evolution. A Geographic Information System is discussed that has been developed to store and analyze data on the stream conditions and affected infrastructure and assist in the planning of stabilization measures. Section three presents an evaluation of two methods for predicting the extent of channel degradation. Section four presents an estimate of costs associated with damages from stream channel erosion since the time of channelization until 1992. Damage to highway bridges represent the highest costs associated with channel erosion, followed by railroad bridges and right-of-way; loss of agricultural land represents the third highest cost. An estimate of costs associated with future channel erosion on western Iowa streams is also presented in section four. Section four also presents a procedure to estimate the benefits and costs of implementing stream stabilization measures. The final section of this report, section five, presents information on the development of the organizational structure and administrative procedures which are being used to plan, coordinate, and implement stream stabilization projects and programs in western Iowa.

Recent advances in remote sensing image processing

Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.

A Fast Gradient Approximation for Nonlinear Blind Signal Processing

When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. 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 eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Stream Water Quality Summary, 2000-2013

Summary of stream water quality data collected from 2000 through 2013.

Stream Water Quality Summary, 2014

Summary of stream water quality data collected in 2014.

Stream Water Quality Summary, 2000-2014

Summary of stream water quality data collected from 2000 through 2014.

Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, 2003

US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

05046-017 Dry Run Creek Watershed Final Report

Dry Run Creek Watershed was designated an impaired waterbody by DNR in 2002, following an assessment of the biota in the stream by DNR Biologist, Tom Wilton. Subsequent studies by IOWATER Snapshot effort in 2003, found e-coli bacteria concentrations and high nitrate readings in excess of the State of Iowa limits for recreational streams. The Dry Run Creek Watershed Improvement Project is comprised of five major components. Three components will feature demonstrations of structural best management practices (BMPs) to protect water quality in Dry Run Creek. The fourth is an educational workshop to "kick-off" the initiative and background the stakeholders of the watershed in new stormwater management strategies for water quality protection. The fifth is a monitoring program that will provide data on the effectiveness of the practices to be demonstrated. Measurable outcomes from these projects include monitoring to document the effectiveness of infiltration­ based BMPs to reduce pollutant loading in urban stormwater runoff and reducing the volume of stormwater discharged directly into Dry Run Creek via storm sewer flows. Understanding of and social acceptance of new stormwater strategies and practices will also be monitored by surveys of watershed stakeholders and compared to findings of a survey done before the start of the project.