C. Bryan Young

Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting

Abstract Next-Generation Weather Radar (NEXRAD) multisensor precipitation estimates will be used for a host of applications that include operational streamflow forecasting at the National Weather Service River Forecast Centers (RFCs) and nonoperational purposes such as studies of weather, climate, and hydrology. Given these expanding applications, it is important to understand the quality and error characteristics of NEXRAD multisensor products. In this paper, the issues involved in evaluating these products are examined through an assessment of a 5.5-yr record of multisensor estimates from the Arkansas–Red Basin RFC. The objectives were to examine how known radar biases manifest themselves in the multisensor product and to quantify precipitation estimation errors. Analyses included comparisons of multisensor estimates based on different processing algorithms, comparisons with gauge observations from the Oklahoma Mesonet and the Agricultural Research Service Micronet, and the application of a validation f...

An evaluation of NEXRAD precipitation estimates in complex terrain

Next Generation Weather Radar (NEXRAD) precipitation estimates are used for hydrological, meteorological, and climatological studies at a wide range of spatial and temporal scales. The utility of radar-based precipitation estimates in such applications hinges on an understanding of the sources and magnitude of estimation error. This study examines precipitation estimation in the complex mountainous terrain of the northern Appalachian Mountains. Hourly digital precipitation (HDP) products for two WSR-88D radars in New York state are evaluated for a 2-year period. This analysis includes evaluation of range dependence and spatial distribution of estimates, radar intercomparisons for the overlap region, and radar-gage comparisons. The results indicate that there are unique challenges for radar-rainfall estimation in mountainous terrain. Beam blockage is a serious problem that is not corrected by existing NEXRAD algorithms. Underestimation and nondetection of precipitation are also significant concerns. Improved algorithms are needed for merging estimates from multiple radars with spatially variable biases.

Empirical Determination of Rational Method Runoff Coefficients

The rational method for determining peak flood discharges has been used for the design of hydraulic structures for decades. Despite the popularity of the method, little attention has been paid to improving guidance for selection of the runoff coefficient. This study determined rational runoff coefficients (the rational C ) for 72 gauged rural watersheds in Kansas ranging in size from 0.45 to 76.6  km2 using a frequency-based approach. The median rational C values for Kansas ranged from 0.17 for the 2-year recurrence interval in western Kansas up to 0.97 for the 100-year recurrence interval in eastern Kansas. This paper investigates the spatial variation in runoff coefficients and documents the dependence of the rational C on recurrence interval. The rational C values determined in this study do not exhibit dependence on drainage area, indicating that the method is acceptable for use on much larger basins than is typically assumed.

Calibration of Storm Drainage Design Inputs for a Small Urban Watershed

Storm-drainage design inputs such as lag times, times of concentration and rational runoff coefficients should be calibrated with local gaging data wherever possible. This paper documents the calibration of these inputs for the 170-acre Wilshire Woods watershed in the Kansas City metro area. The watershed is 33% impervious with curb-and-gutter streets, storm sewers, and a short segment of open channel. We determined the basin lag time by calibrating a simple watershed model with detailed rainfall and water-level data for 28 significant runoff events from the 13-year record. These calibrations yielded a lag time of 6 minutes and a corresponding time of concentration of 10 minutes. We performed a discharge-frequency analysis on the series of annual peak flows, and computed rational C values from the discharges and 10-minute rainfall intensities. We obtained rational C values of 0.42, 0.50, 0.52 and 0.54 for return periods of 2, 5, 10 and 25 years.

The Rosgen rosetta stone: translating rosgen terminology.

David Rosgens methods for river classification, analysis, and restoration design have been utilized to varying extents all over the United States. A growing body of geomorphic data is being collected by individuals trained in Rosgen methodologies. While this information can be extremely valuable for geomorphic analysis, it can be easily misapplied. Rosgen assigns unique definitions to common terms and uses special methods that differ from the definitions and methods used in traditional geomorphology, hydrology and hydraulics. Researchers and agencies using geomorphic data collected by Rosgen-trained surveyors need to understand what those differences are in order to correctly analyze and use the data. This paper explains terms and procedures involved in the reference-reach survey that may be misunderstood. This paper also suggests simple changes to the Rosgen reference-reach survey that will enhance the usability of the results for a broader range of research and practical applications.

Evaluating the Form of the Rational Equation

AbstractThe Rational method is widely used in the design of hydraulic structures, such as storm sewers and culverts. Many engineers consider the Rational equation a rule-of-thumb method and dismiss it in favor of regional flood-frequency equations. This paper presents a regional flood-frequency analysis of 72 gaged watersheds in Kansas, ranging in size from 0.44–76.7  km2. The analysis results in regression equations for the 2-year to 100-year peak discharges that are statistically indistinguishable from the Rational equation. The resulting Rational equations explain more of the variance in flood quantiles than the standard form of the USGS regional flood-frequency equations that are used in Kansas.

Structuring a Comprehensive Georeferenced Subgrade Database

Geotechnical properties are influenced by processes and conditions that vary in space and time, including erosion and deposition, stress history, depth to water, cementation, climate, and many other factors. Therefore the resulting properties of soil also vary in space. Inclusion of the spatial information associated with geotechnical data is essential for optimal use of such data. This paper describes how thousands of paper records of subgrade and pavement information were entered into a database adapted for storage of geotechnical information for the Kansas Department of Transportation. This information was georeferenced and imported into a geographic information system (GIS). This information is now available in an interactive system where it may be displayed, queried, or combined with other data for a wide range of analyses. A series of statistical analyses were conducted on the data. The resulting database has proven to be much more accessible than paper records and is capable of conveying a substantial amount of detailed information within the proper spatial context.