Geology topics

M. Willis

Publications and source records attributed to M. Willis.

3 recordsLinked to original sources

USGS2012

On the use of wave parameterizations and a storm impact scaling model in National Weather Service Coastal Flood and decision support operations

National Weather Service (NWS) Weather Forecast Offices (WFO) are responsible for issuing coastal flood watches, warnings, advisories, and local statements to alert decision makers and the general public when rising water levels may lead to coastal impacts such as inundation, erosion, and wave battery. Both extratropical and tropical cyclones can generate the prerequisite rise in water level to set the stage for a coastal impact event. Forecasters use a variety of tools including computer model guidance and local studies to help predict the potential severity of coastal flooding. However, a key missing component has been the incorporation of the effects of waves in the prediction of total water level and the associated coastal impacts. Several recent studies have demonstrated the importance of incorporating wave action into the NWS coastal flood program. To follow up on these studies, this paper looks at the potential of applying recently developed empirical parameterizations of wave setup, swash, and runup to the NWS forecast process. Additionally, the wave parameterizations are incorporated into a storm impact scaling model that compares extreme water levels to beach elevation data to determine the mode of coastal change at predetermined “hotspots” of interest. Specifically, the storm impact model compares the approximate storm-induced still water level, which includes contributions from tides, storm surge, and wave setup, to dune crest elevation to determine inundation potential. The model also compares the combined effects of tides, storm surge, and the 2 % exceedance level for vertical wave runup (including both wave setup and swash) to dune toe and crest elevations to determine if erosion and/or ocean overwash may occur. The wave parameterizations and storm impact model are applied to two cases in 2009 that led to significant coastal impacts and unique forecast challenges in North Carolina: the extratropical “Nor'Ida” event during 11-14 November and the large swell event from distant Hurricane Bill on 22 August. The coastal impacts associated with Nor'Ida were due to the combined effects of surge, tide, and wave processes and led to an estimated 5.8 million dollars in damage. While the impacts from Hurricane Bill were not as severe as Nor'Ida, they were mainly associated with wave processes. Thus, this event exemplifies the importance of incorporating waves into the total water level and coastal impact prediction process. These examples set the stage for potential future applications including adaption to the more complex topography along the New England coast.

Conference Paper↗

USGS2011

Analysis of passive surface-wave noise in surface microseismic data and its implications

Tight gas reservoirs are projected to be a major portion of future energy resources. Because of their low permeability, hydraulic fracturing of these reservoirs is required to improve the permeability and reservoir productivity. Passive seismic monitoring is one of the few tools that can be used to characterize the changes in the reservoir due to hydraulic fracturing. Although the majority of the studies monitoring hydraulic fracturing exploit down hole microseismic data, surface microseismic monitoring is receiving increased attention because it is potentially much less expensive to acquire. Due to a broader receiver aperture and spatial coverage, surface microseismic data may be more advantageous than down hole microseismic data. The effectiveness of this monitoring technique, however, is strongly dependent on the signal-to-noise ratio of the data. Cultural and ambient noise can mask parts of the waveform that carry information about the subsurface, thereby decreasing the effectiveness of surface microseismic analysis in identifying and locating the microseismic events. Hence, time and spatially varying suppression of the surface-wave noise ground roll is a critical step in surface microseismic monitoring. Here, we study a surface passive dataset that was acquired over a Barnett Shale Formation reservoir during two weeks of hydraulic fracturing, in order to characterize and suppress the surface noise in this data. We apply techniques to identify the characteristics of the passive ground roll. Exploiting those characteristics, we can apply effective noise suppression techniques to the passive data. ?? 2011 Society of Exploration Geophysicists.

SEG Technical Program Expanded Abstracts↗

USGS2006

The ionospheric impact on GPS performance in southern polar region

The primary objective of this paper is to present the results of the study of the effects of varying ionospheric conditions on the GPS signal tracking in the southern polar region. In the first stage of this study, the data collected by the OSU/USGS team in October-November 2003 within the TAMDEF (Transantarctic Mountains Deformation) network were used together with some IGS Antarctic stations to study the effect of severe ionospheric storms on GPS hardware. Note that TAMDEF is a joint USGS/OSU project with the primary objective of measuring crustal motion in the Transantarctic Mountains of Southern Victoria Land using GPS techniques. This study included ten Antarctic stations equipped with different dual-frequency GPS hardware, and the data were evaluated for two 24-hour periods of severe ionospheric storm (2003/10/29) and moderate ionospheric conditions (minor storm of 2003/11/11). The results of this study were presented at the LAG Assembly in Cairns, Australia (Grejner-Brzezinska et al., 2005). Additional tests, in a more controlled environment, were carried out at the US Antarctic station, McMurdo, between January 10 and February 6, 2006, under varying ionospheric conditions, where several different types of receivers were connected to the same antenna located on the rooftop of the Crary Laboratory (the primary test site). In this scenario, each antenna was subject to identical ionospheric effects during each day of the test, and no spatial decorrelation effects were present, as seen in the previous study, due to the spatial separation of the receivers tested. It should be noted, however, that no moderate or severe ionospheric storms occurred during the experiment, so, unfortunately, this type of conditions was not tested here. The test was repeated with different receivers connected to different antenna types; a total of four 5-day sessions were carried out. The following receiver types were used at the primary site: Trimble 5700, Ashtech Z-Surveyor, JNS Euro-80 and Novatel DL-4, with the following antennas: Trimble Zephyr Geodetic, Ashtech D/M and Ashtech E/M chokering. In addition, data collected by the MCM4 IGS station, MCMD UNAVCO station, and CRAR USGS station, all located within 300 m from the primary test site, were used in the analyses. These stations were equipped with the following receiver/antenna combinations: ADA SNR-12/AOAD/MJT chokering (MCM4), Trimble NETRS/AOAD/MJT chokering (MCMD), and TPS ODYSEY_E/JPSREGANT_DD_E (CRAR). The UNAVCO TEQC software was used to carry out the analyses. Depending on the data sampling rate and the mask angle, the expected numbers of observations per receiver/satellite were compared to the actual number of measurements collected during the ionospheric events, with a special emphasis on L2 data. A total number of cycle slips and losses of lock were computed and compared among the hardware types. The results presented here indicate that there is no significant effects on the GPS receivers during minor ionospheric storms (Kp<5). However, the results reported in ibid, indicate significant differences in the hardware performance under severe ionospheric storms. Thus, careful hardware selection is needed to assure data quality/continuity when observations may be affected by severe ionospheric disturbances, while under calm to minor ionospheric activity level there is no significant difference in performance among the hardware tested here.

Conference Paper↗