Geology topics

James L. Kiesler

Publications and source records attributed to James L. Kiesler.

4 recordsLinked to original sources

USGS2011

Observed and forecast flood-inundation mapping application-A pilot study of an eleven-mile reach of the White River, Indianapolis, Indiana

Near-real-time and forecast flood-inundation mapping products resulted from a pilot study for an 11-mile reach of the White River in Indianapolis. The study was done by the U.S. Geological Survey (USGS), Indiana Silver Jackets hazard mitigation taskforce members, the National Weather Service (NWS), the Polis Center, and Indiana University, in cooperation with the City of Indianapolis, the Indianapolis Museum of Art, the Indiana Department of Homeland Security, and the Indiana Department of Natural Resources, Division of Water. The pilot project showed that it is technically feasible to create a flood-inundation map library by means of a two-dimensional hydraulic model, use a map from the library to quickly complete a moderately detailed local flood-loss estimate, and automatically run the hydraulic model during a flood event to provide the maps and flood-damage information through a Web graphical user interface. A library of static digital flood-inundation maps was created by means of a calibrated two-dimensional hydraulic model. Estimated water-surface elevations were developed for a range of river stages referenced to a USGS streamgage and NWS flood forecast point colocated within the study reach. These maps were made available through the Internet in several formats, including geographic information system, Keyhole Markup Language, and Portable Document Format. A flood-loss estimate was completed for part of the study reach by using one of the flood-inundation maps from the static library. The Federal Emergency Management Agency natural disaster-loss estimation program HAZUS-MH, in conjunction with local building information, was used to complete a level 2 analysis of flood-loss estimation. A Service-Oriented Architecture-based dynamic flood-inundation application was developed and was designed to start automatically during a flood, obtain near real-time and forecast data (from the colocated USGS streamgage and NWS flood forecast point within the study reach), run the two-dimensional hydraulic model, and produce flood-inundation maps. The application used local building data and depth-damage curves to estimate flood losses based on the maps, and it served inundation maps and flood-loss estimates through a Web-based graphical user interface.

Indiana↗

USGS2008

User's Guide to the Water-Analysis Screening Tool (WAST): A Tool for Assessing Available Water Resources in Relation to Aquatic-Resource Uses

A water-analysis screening tool (WAST) was developed by the U.S. Geological Survey, in partnership with the Pennsylvania Department of Environmental Protection, to provide an initial screening of areas in the state where potential problems may exist related to the availability of water resources to meet current and future water-use demands. The tool compares water-use information to an initial screening criteria of the 7-day, 10-year low-flow statistic (7Q10) resulting in a screening indicator for influences of net withdrawals (withdrawals minus discharges) on aquatic-resource uses. This report is intended to serve as a guide for using the screening tool. The WAST can display general basin characteristics, water-use information, and screening-indicator information for over 10,000 watersheds in the state. The tool includes 12 primary functions that allow the user to display watershed information, edit water-use and water-supply information, observe effects downstream from edited water-use information, reset edited values to baseline, load new water-use information, save and retrieve scenarios, and save output as a Microsoft Excel spreadsheet.

Open-File Report↗

USGS2005

Atrazine concentrations in stream water and streambed sediment pore water in the St. Joseph and Galien River basins, Michigan and Indiana, May 2001-September 2003

The U.S. Geological Survey (USGS) sampled multiple stream sites across the St. Joseph and Galien River Basins to detect and quantify the herbicide atrazine using a field enzyme-linked immunosorbent assay (ELISA) triazine test. In May 2001, July 2001, April 2002, August 2002, August 2003 and September 2003, composite samples were collected across streams at USGS streamflow-gaging stations. Concentrations and instantaneous loading for atrazine sampled in stream water throughout the St. Joseph River and Galien River Basins in Michigan and Indiana ranged from nondetection (< 0.05 part per billion (ppb)) with an associated load less than 0.001 kilogram per day (kg/d) to 6 ppb and a maximum load of 10 kg/d. Atrazine concentrations were highest in May 2001 just after the planting season. The lowest concentration was found in April 2002 just before planting. Atrazine concentrations in streambed-sediment pore water were not spatially connected with atrazine concentrations in stream-water samples. This study showed that atrazine concentrations were elevated from May to July in the St. Joseph and Galien River Basins. At many sites, concentrations exceeded the level that has been shown to feminize frog populations (0.2 ppb). There were 8 sites where concentrations exceeded 0.2 ppb atrazine in May 2001 and July 2001.

Indiana, Michigan↗

USGS2002

Documentation and analysis of a geographic information system application for combining data layers, using nonpoint-source pollution as an example

A geographical information system application has been developed that allows scientists to combine multiple data layers into a single data layer. This application provides an effective tool for identifying areas where the potential effect of the combination of data layers may be greater than any single data layer. Such a tool is useful in studying an activity that cannot be measured directly. Scientists wanting to identify areas where an activity may have the greatest effect can identify factors that directly or indirectly reflect the effect of the activity being studied. When combined, these factors would identify areas where the potential for the activity to have an effect are greatest. The data layers used to develop the single data layer determine the activity addressed by the application?the application was developed to identify areas where the potential for nonpoint-source pollution to affect areas of Indiana is greater relative to other areas in Indiana. To evaluate the potential in other states or areas, data layers for those states or areas would be used. To address a different activity, even activities not related to water resources, data layers that directly or indirectly reflect the effects of the activity being studied would be used in the application. The application was developed using Environmental System Research Institute's ArcView geographical information system and the ArcView extension, Spatial Analyst. To use the application, the user selects data layers related to the activity being studied, describes the variability of a data element between geographic areas on each data layer, assigns a relative importance factor to each data layer, and focuses the output by identifying a watershed of interest. The application then assigns a rank value to the features within each data layer on the basis of the spatial variation of the data layer. The data layers are converted to grids. The values of the grid cells are the product of the rank values and the importance factors. The cells for each data layer are combined to form a single grid. The combination is summarized to describe the spatial variation for the watershed of interest. The combined data layer does not show the actual potential effect of the selected factors but rather the relative difference in the potential effect among areas when all data layers are considered. An analysis of the application indicates that the selected data layers to be combined should be at the greatest spatial resolution possible; however, all data layers do not have to be at the same spatial resolution. The spatial variation of the data layers should be adequately defined. The size of each grid cell should be small enough to maintain the spatial definition of smaller features within the data layers. The most accurate results are shown to occur when the values for the grid cells representing the individual data layers are summed and the mean of the summed grid-cell values is used to describe the watershed of interest.

Indiana↗