An Investigation of User Costs and Benefits of Winter Road Closures, June 2005

This project explores the user costs and benefits of winter road closures. Severe winter weather makes travel unsafe and dramatically increases crash rates. When conditions become unsafe due to winter weather, road closures should allow users to avoid crash costs and eliminate costs associated with rescuing stranded motorists. Therefore, the benefits of road closures are the avoided safety costs. The costs of road closures are the delays that are imposed on motorists and motor carriers who would have made the trip had the road not been closed. This project investigated the costs and benefits of road closures and found that evaluating the benefits and costs is not as simple as it appears. To better understand the costs and benefits of road closures, the project investigates the literature, conducts interviews with shippers and motor carriers, and conducts case studies of road closures to determine what actually occurred on roadways during closures. The project also estimates a statistical model that relates weather severity to crash rates. Although, the statistical model is intended to illustrate the possibility to quantitatively relate measurable and predictable weather conditions to the safety performance of a roadway. In the future, weather conditions such as snow fall intensity, visibility, etc., can be used to make objective measures of the safety performance of a roadway rather than relying on subjective evaluations of field staff. The review of the literature and the interviews clearly illustrate that not all delays (increased travel time) are valued the same. Expected delays (routine delays) are valued at the generalized costs (value of the driver’s time, fuel, insurance, wear and tear on the vehicle, etc.), but unexpected delays are valued much higher because they result in interruption of synchronous activities at the trip’s destination. To reduce the costs of delays resulting from road closures, public agencies should communicate as early as possible the likelihood of a road closure.

Effects of Pavement Surface Texture on Noise and Frictional Characteristics HR-281, February 1987

An experimental modification of the transverse groove surface texture of a section of an urban interstate highway was performed by the Iowa Department of Transportation. Transverse groove texturing i s a design feature required by the Federal Highway Administration t o reduce skidding under wet pavement conditions. Adjacent residents claimed the texturing was the cause of especially annoying tonal characteristics within the traffic noise. A research proposal to modify the existing texture pattern by surface grinding and to study the noise and friction effects was approved for funding by the Iowa Highway Research Board. Results i n the form of a comparison between traffic noise before modification and traffic noise immediately after and 15 months after modification indicate that the change in surface texture has lowered overall traffic noise levels by reducing a high frequency component of the traffic noise spectrum. Fraffic testing data show reduced capacity of the roadway to inhibit wet pavement skidding as a result of the surface modification.

Techniques for Estimating Flood-Frequency Discharges for Streams in Iowa, HR-395A, 2001

A statewide study was conducted to develop regression equations for estimating flood-frequency discharges for ungaged stream sites in Iowa. Thirty-eight selected basin characteristics were quantified and flood-frequency analyses were computed for 291 streamflow-gaging stations in Iowa and adjacent States. A generalized-skew-coefficient analysis was conducted to determine whether generalized skew coefficients could be improved for Iowa. Station skew coefficients were computed for 239 gaging stations in Iowa and adjacent States, and an isoline map of generalized-skew-coefficient values was developed for Iowa using variogram modeling and kriging methods. The skew map provided the lowest mean square error for the generalized-skew- coefficient analysis and was used to revise generalized skew coefficients for flood-frequency analyses for gaging stations in Iowa. Regional regression analysis, using generalized least-squares regression and data from 241 gaging stations, was used to develop equations for three hydrologic regions defined for the State. The regression equations can be used to estimate flood discharges that have recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years for ungaged stream sites in Iowa. One-variable equations were developed for each of the three regions and multi-variable equations were developed for two of the regions. Two sets of equations are presented for two of the regions because one-variable equations are considered easy for users to apply and the predictive accuracies of multi-variable equations are greater. Standard error of prediction for the one-variable equations ranges from about 34 to 45 percent and for the multi-variable equations range from about 31 to 42 percent. A region-of-influence regression method was also investigated for estimating flood-frequency discharges for ungaged stream sites in Iowa. A comparison of regional and region-of-influence regression methods, based on ease of application and root mean square errors, determined the regional regression method to be the better estimation method for Iowa. Techniques for estimating flood-frequency discharges for streams in Iowa are presented for determining ( 1) regional regression estimates for ungaged sites on ungaged streams; (2) weighted estimates for gaged sites; and (3) weighted estimates for ungaged sites on gaged streams. The technique for determining regional regression estimates for ungaged sites on ungaged streams requires determining which of four possible examples applies to the location of the stream site and its basin. Illustrations for determining which example applies to an ungaged stream site and for applying both the one-variable and multi-variable regression equations are provided for the estimation techniques.

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.