Frequently asked Questions about Beach Monitoring, 2003

Part of Iowa's Water Ambient monitoring Program, produced by the Iowa Department of Natural Resources.

Frequently asked Questions about Beach Monitoring for Environmental Prefessionals, 2003

This fact sheet answers questions such as, is it safe to swim in the water and who is monitoring the beaches in Iowa

Iowa Beach Monitoring, 2002

This fact sheet answers questions such as, is it safe to swim in the water and who is monitoring the beaches in Iowa

Iowa Beach Monitoring, 2002

This fact sheet answers questions such as, is it safe to swim in the water and who is monitoring the beaches in Iowa

Iowa Beach Monitoring, 2004

This fact sheet answers questions such as, is it safe to swim in the water and who is monitoring the beaches in Iowa

Iowa's Beach Monitoring Program, 2005

This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.

Iowa Beach Monitoring, 2003

This fact sheet answers questions such as, is it safe to swim in the water and who is monitoring the beaches in Iowa

The Iowa Beach Study Experience, 2007

This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.

Iowa Beach Monitoring Program, 2007

This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.

Iowa's Beach Monitoring Program 2007, 2008

This monthly report from the Iowa Department of Natural Resources is about the water quality management of Iowa's rivers, streams and lakes.

08006-003 East Okoboji Beach Final Report

East Okoboji Beach was platted on April 20, 1961 and includes over 90.4 acres with 489 lots. The East Okoboji Beach project includes a complete storm water discharge system, which includes low impact development and reconstruction of the roadways in East Okoboji Beach. The East Okoboji Beach Project is an enormous project that is the first Dickinson County project to retrofit LID practices, lake-friendly storm-water drainage systems and roadway reconstruction throughout an existing sub- division. This cooperative project between DNR, Dickinson County, and EOB landowners includes engineering retention ponds, rain gardens, bio-swales and other LID practices to reduce nutrient and sediment pollutants flowing directly into East Okoboji. The nature of the problem stems back to that original plat where small lots were platted and developed without planning for storm water discharge. There was no consideration of the effects of filling in and developing over the many wetland areas existing in EOB. The scope of the problem covers the entire 90.4 acres in East Okoboji Beach, the DNR owned land and the farmed land to the east. The nature of the problem stems from storm water runoff flowing throughout the watershed and into East Okoboji Beach where it flows down self-made paths and then into East Lake Okoboji. That storm water runoff dumps nutrient and sediment pollutions directly into East Lake Okoboji. The expected result of this project is a new roadway and drainage system constructed with engineering that is intended to protect East Lake Okoboji and the land and homes in East Okoboji Beach. The benefit will be the improvement in the waters and the reduction of the siltation in the East Lake Okoboji.

Iowa's Beach Monitoring Program, 2008

Summary of bacteria monitoring of Iowa's beaches.

Iowa's Beach Monitoring Program, 2009

Summary of bacteria monitoring of Iowa's beaches.

Volume of Traffic on the Primary Road System, 2002

The Office of Transportation Data, in cooperation with the Federal Highway Administration, prepares this biennial traffic report. This report is used by federal, state, and local governmental agencies in determining highway needs, construction priorities, route location and environmental impact studies, and the application of appropriate design standards. The general public uses this information in determining the amount of traffic that passes a given area as they make their development plans and propose land use changes. The above reflects only a few of the many technical uses for this data.

Quantifying Uncertainty in Real Time Performance Measurement for Highway Winter Maintenance Operations – Phase 2, RB03-013, 2014

Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive maintenance operations. In order to assess the performance of these maintenance operations, it would be beneficial to develop a model for expected speed reduction based on weather variables and normal maintenance schedules. Such a model would allow the Iowa DOT to identify situations in which speed reductions were much greater than or less than would be expected for a given set of storm conditions, and make modifications to improve efficiency and effectiveness. The objective of this work was to predict speed changes relative to baseline speed under normal conditions, based on nominal maintenance schedules and winter weather covariates (snow type, temperature, and wind speed), as measured by roadside weather stations. This allows for an assessment of the impact of winter weather covariates on traffic speed changes, and estimation of the effect of regular maintenance passes. The researchers chose events from Adair County, Iowa and fit a linear model incorporating the covariates mentioned previously. A Bayesian analysis was conducted to estimate the values of the parameters of this model. Specifically, the analysis produces a distribution for the parameter value that represents the impact of maintenance on traffic speeds. The effect of maintenance is not a constant, but rather a value that the researchers have some uncertainty about and this distribution represents what they know about the effects of maintenance. Similarly, examinations of the distributions for the effects of winter weather covariates are possible. Plots of observed and expected traffic speed changes allow a visual assessment of the model fit. Future work involves expanding this model to incorporate many events at multiple locations. This would allow for assessment of the impact of winter weather maintenance across various situations, and eventually identify locations and times in which maintenance could be improved.