Topographic instructions of the United States Geological Survey. Map compilation from aerial photographs
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Mapping cropland waterway buffers for switchgrass development in the eastern Great Plains, USA
Switchgrass ( Panicum virgatum L.), a highly productive perennial grass, has been recommended as one potential source for cellulosic biofuel feedstocks. Previous studies indicate that planting perennial grasses (e.g., switchgrass) in high‐topographic‐relief cropland waterway buffers can improve local environmental conditions and sustainability. The main advantages of this land management practice include (i) reducing soil erosion and improving water quality because switchgrass requires less tillage, fertilizers, and pesticides; and (ii) improving regional ecosystem services (e.g., improving water infiltration, minimizing drought and flood impacts on production, and serving as carbon sinks). In this study, we mapped high‐topographic‐relief cropland waterway buffers with high switchgrass productivity potential that may be suitable for switchgrass development in the eastern Great Plains (EGP). The US Geological Survey (USGS) Compound Topographic Index map, National Land Cover Database 2011, USGS irrigation map, and a switchgrass biomass productivity map derived from a previous study were used to identify the switchgrass potential areas. Results show that about 16 342 km 2 ( c . 1.3% of the total study area) of cropland waterway buffers in the EGP are potentially suitable for switchgrass development. The total annual estimated switchgrass biomass production for these suitable areas is approximately 15 million metric tons. Results from this study provide useful information on EGP areas with good cellulosic switchgrass biomass production potential and synergistic substantial potential for improvement of ecosystem services.
Great Plains↗
Geological and Geographical Atlas of Colorado and portions of adjacent territory
Sheets I-IV are triangulations, drainage, land classification, and geologic maps of Colorado west of longitude 102°, on the scale of 12 miles to the inch. Sheets V-XVI are topographic (contour) and geologic maps of Colorado and adjacent States, between meridians 104° 30' and 109° 30' and parallels 36° 45' and 40° 30', on the scale of 4 miles to the inch. Sheets XVII and XVIII contain three geologic sections across the State, west of the longitude 104° 30'. Sheets XIX and XX are panoramic views of the Pikes Peak group, Sawatch Range, central portion of West Elk Mountains, Twin Lakes, southwestern border of the Mesa Verde, San Juan Mountains, and La Plata Mountains.
Colorado↗
Geological and Geographical Atlas of Colorado and portions of adjacent territory
Sheets I-IV are triangulations, drainage, land classification, and geologic maps of Colorado west of longitude 102°, on the scale of 12 miles to the inch. Sheets V-XVI are topographic (contour) and geologic maps of Colorado and adjacent States, between meridians 104° 30' and 109° 30' and parallels 36° 45' and 40° 30', on the scale of 4 miles to the inch. Sheets XVII and XVIII contain three geologic sections across the State, west of the longitude 104° 30'. Sheets XIX and XX are panoramic views of the Pikes Peak group, Sawatch Range, central portion of West Elk Mountains, Twin Lakes, southwestern border of the Mesa Verde, San Juan Mountains, and La Plata Mountains.
Colorado↗
Where’s the rock: Using convolutional neural networks to improve land cover classification
While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock ( rock ) from soil cover ( other ). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDA’s 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95 F 1 "> F 1 score. Comparatively, the classical OBIA approach gives only a 0.84 F 1 "> F 1 score. This is an improvement over existing land cover maps, which underestimate rock by almost 90%. The resulting CNN approach is likely scalable but dependent on high-quality imagery and high-performance algorithms using representative training sets informed by expert mapping. As image quality and quantity continue to increase globally, machine learning models that incorporate high-quality training data informed by geologic, topographic, or other topical maps may be applied to more effectively identify exposed rock in large image collections.
California↗
Surficial geologic map of the Noatak National Preserve, Alaska
The surficial geologic map of the Noatak National Preserve (NNP) is a compilation that incorporates portions of four published USGS maps (Hamilton, 1980, 1981, 1984a,b), a USGS Open-File Report (Hamilton, 2003), and unpublished field mapping. It covers an area of about 28,700 km 2 , and includes parts of eight 1:250,000-scale quadrangles. The mapped area generally terminates at NNP boundaries, which generally follow the sharp divides that separate the Noatak drainage system from north-flowing drainages of the Alaskan North Slope and south-flowing tributaries to the Kobuk River. The mapping extends short distances beyond those boundaries where passes across divides were traversed by glaciers issuing from the Noatak drainage or by overflow waters from glacial lakes. Along the western edge of the map, where the NNP boundary is unrelated to topographic features, I have extended the mapping to the nearest natural boundary, the active channel of the Noatak River, and have mapped beyond that limit only in places where surficial deposits are essential for understanding regional geology.
Alaska↗
Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i
Sustained-yield hunting of introduced ungulates in the Hawaiian Islands often conflicts with the conservation of native species, but there is little reliable data to guide effective management. European mouflon sheep ( Ovis musimon ; mouflon) and axis deer ( Axis axis ; deer) were introduced on the island of Lāna‘i to provide additional hunting opportunities. Managers will require better information regarding the ecological associations of introduced ungulate species, relative to the habitats occupied, to resolve longstanding conflicts between native species conservation and sustained-yield hunting on islands. To address this information need, we modeled sheep and deer ecological associations, habitat-use, and suitability using data obtained from an intensive aerial survey completed in 2013 and temporally matching environmental data. In habitat suitability models evaluated by Receiver Operating Characteristic (ROC) metrics, predictor importance in a generalized linear model (GLM) of deer decreased in the following order: afternoon cloud cover, topographic slope, mean annual precipitation (MAP), elevation, normalized difference vegetation index (NDVI), and bare soil index. In a random GLM model of mouflon, predictor importance decreased in the following order: afternoon cloud cover, deer habitat suitability, NDVI, bare soil index, topographic slope, elevation, and MAP. Mouflon were restricted to lower elevation arid slopes, whereas deer were more broadly distributed throughout upland environments of the island. The presence of deer was also an important predictor for mouflon distribution, although mouflon was not an important predictor of deer, suggesting asymmetrical competition. Removal of the more abundant deer population may lead to an increase in abundance and distribution of mouflon without containment. This work represents the first habitat suitability analysis for all nonnative ungulates on any entire Hawaiian island. Our results are applicable to other islands where conflicts may arise with introduced ungulates, sustained-yield hunting, and native species conservation.
Hawaii↗
Shallow ground water in the Boulder-Fort Collins-Greeley area, Front Range urban corridor, Colorado, 1975-77
Shallow ground water may limit the location of construction and excavation projects in parts of the Front Range Urban Corridor. A shallow water table occurs from 0 to 50 feet below the land surface principally in the alluvial deposits along the streams and rivers in the Boulder-Fort Collins-Greeley area. This shallow water table underlies approximately 400 square miles and is maintained by natural recharge within the South Platte River basin and by the infiltration of irrigation water that is diverted into the basin from streams and reservoirs in the Colorado and the Laramie River basins. Return flow from irrigation, which is mostly ground water, helps maintain the flow of the South Platte River and its tributaries. The report includes a map from which depth to water table and the direction of ground-water movement can be determined. The map, compiled on a topographic base, shows the areal extent of the saturated materials and the altitude and configuration of the ground-water surface. The water-table contour map was prepared using data from approximately 400 wells. Monitoring of shallow ground-water within the study area shows depths to water have changed only slightly over the last 20 years, except for some seasonal and drought-related fluctuations. Gradients, computed from ground-water measurements, range from 27.7 feet per mile in Lone Tree-Spring Creek valley to 10.3 feet per mile in the South Platte River valley. The shallow ground-water underflow from the major tributaries in the basin is about 29,000 acre-feet per year, and underflow calculated at a cross section near Kersey is about 12,000 acre-feet per year.
Colorado↗
Terrestrial Ecosystems - Topographic Moisture Potential of the Conterminous United States
As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated topographic moisture potential classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe. A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Substrate moisture regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and therefore topographic moisture potential is one of the key input layers in this biophysical stratification. The method used to produce these topographic moisture potential classes was based on the derivation of ground moisture potential using a combination of computed topographic characteristics (CTI, slope, and aspect) and mapped National Wetland Inventory (NWI) boundaries. This method does not use climate or soil attributes to calculate relative topographic moisture potential since these characteristics are incorporated into the ecosystem model though other input layers. All of the topographic data used for this assessment were derived from the USGS 30-meter National Elevation Dataset (NED ) including the National Compound Topographic Index (CTI). The CTI index is a topographically derived measure of slope for a raster cell and the contributing area from upstream raster cells, and thus expresses potential for water flow to a point. In other words CTI data are 'a quantification of the position of a site in the local landscape', where the lowest values indicate ridges and the highest values indicate stream channels, lakes and ponds. These CTI values were compared to independent estimates of water accumulation by obtaining geospatial data from a number of sample locations representing two types of NWI boundaries: freshwater emergent wetlands and freshwater forested/shrub wetlands. Where these shorelines (the interface between the NWI wetlands and adjacent land) occurred, the CTI values were extracted and a histogram of their statistical distributions was calculated. Based on an evaluation of these histograms, CTI thresholds were developed to separate periodically saturated or flooded land, mesic uplands (moderately moist), and uplands. After the range of CTI values for these three different substrate moisture regimes was determined, the CTI values were grouped into three initial topographic moisture potential classes. As a final step in the generation of this national data layer, the uplands classification was subdivided into either very dry uplands or dry uplands. Very dry uplands were defined as uplands with relatively steep, south-facing slopes, and identification of this class was based on the slope and aspect datasets derived from the NED. The remaining uplands that did not meet these additional criteria were simply re-classified as dry uplands. The final National Topographic Moisture Potential dataset for the conterminous United States contains four classes: periodically saturated or flooded land (CTI = 18.5), mesic uplands (12 =< CTI < 18.5), dry uplands (CTI < 12), and very dry uplands (CTI < 12, Slope > 24 degrees and 91 degrees =< Aspect =< 314 degrees). This map shows a smoothed and generalized image of the four topographic moisture potential classes. Additional information about this map and any of the data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.
Scientific Investigations Map↗
Topographic change detection at select archeological sites in Grand Canyon National Park, Arizona, 2007-2010
Human occupation in Grand Canyon, Arizona, dates from at least 11,000 years before present to the modern era. For most of this period, the only evidence of human occupation in this iconic landscape is provided by archeological sites. Because of the dynamic nature of this environment, many archeological sites are subject to relatively rapid topographic change. Quantifying the extent, magnitude, and cause of such change is important for monitoring and managing these archeological sites. Such quantification is necessary to help inform the continuing debate on whether and how controlled releases from Glen Canyon Dam, located immediately upstream of Grand Canyon National Park, are affecting site erosion rates, artifact transport, and archeological resource preservation along the Colorado River in Grand Canyon. Although long-term topographic change resulting from a variety of natural processes is inherent in the Grand Canyon region, continued erosion of archeological sites threatens both the archeological resources and our future ability to study evidence of past cultural habitation. Thus, this subject is of considerable interest to National Park Service managers and other stakeholders in the Glen Canyon Dam Adaptive Management Program. Understanding the causes and effects of archeological site erosion requires a knowledge of several factors, including the location, timing, and magnitude of the changes occurring in relation to archeological resources, the rates of change, and the relative contribution of potential causes. These potential causes include sediment depletion associated with managed flows from Glen Canyon Dam, site-specific weather and overland flow patterns, visitor impacts, and long-term regional climate change. To obtain this information, highly accurate, spatially specific data are needed from sites undergoing change. Using terrestrial lidar techniques, and building upon three previous surveys of archeological sites performed in 2006 and 2007, we collected two new datasets in April and September 2010 and processed and improved upon existing methods to generate high-accuracy (3 to 5 cm vertical change threshold) topographic change-detection maps for 10 survey areas encompassing 9 archeological sites along the Colorado River corridor. We also used terrestrial lidar techniques to investigate several other metrics for studying archeological site stability, including monitoring cultural structures and artifacts and remotely measuring cryptobiotic soil crust areas. Our topographic change results indicate that 9 of 10 survey areas showed signs of either erosion, deposition, or both during the 2007–2010 time interval and that these changes can be linked to a variety of geomorphic processes, primarily overland flow gullying and aeolian sand transport. In several cases, large (>50 cm) vertical change occurred, and in one case, more than 100 m 3 of sediment was eroded. Further, for all sites monitored throughout the river corridor during this time period, the overall signal was related to erosion rather than deposition. These results highlight the potential for rapid archeological site change in Grand Canyon. Whereas the topographic change results presented herein provide the highest level of change detection yet performed on entire archeological sites in Grand Canyon, additional work in combining these results with site-specific weather, hydrology, and geomorphology data is needed to provide a more thorough understanding of the causes of the documented topographic changes. Linking lidar-derived measurements of topographic changes with these other data sources should provide land managers with a scientific basis for making management decisions regarding archeological resources in Grand Canyon National Park and assist in answering open questions regarding the influence that sediment-depleted flows from Glen Canyon Dam have on archeological site stability.
Arizona↗
Comparative lahar hazard mapping at Volcan Citlaltépetl, Mexico using SRTM, ASTER and DTED-1 digital topographic data
In this study, we evaluated and compared the utility of spaceborne SRTM and ASTER DEMs with baseline DTED-1 “bald-earth” topography for mapping lahar inundation hazards from volcan Citlaltépetl, Mexico, a volcano which has had a history of producing debris flows of various extents. In particular, we tested the utility of these topographic datasets for resolving ancient valley-filling deposits exposed around the flanks of the volcano, for determining their magnitude using paleohydrologic methods and for forecasting their inundation limits in the future. We also use the three datasets as inputs to a GIS stream inundation flow model, LAHARZ, and compare the results. In general all three datasets, with spatial resolution of 90 m or better, were capable of resolving debris flow and lahar deposits at least 3 × 10 6 m 3 in volume or larger. Canopy- and slope-related height errors in the ASTER and SRTM DEMs limit their utility for measuring valley-filling cross-sectional area and deriving flow magnitude for the smallest deposits using a cross-sectional area to volume scaling equation. Height errors in the ASTER and SRTM DEMs also causes problems in resolving stream valley hydrography which controls lahar flow paths and stream valley morphology which controls lahar filling capacity. However, both of the two spaceborne DEM datasets are better than DTED-1 at resolving fine details in stream hydrography and erosional morphologies of volcaniclastics preserved in the valleys around the more humid, eastern flanks of the volcanic range. The results of LAHARZ flow inundation modeling using all three DEMs as inputs are remarkably similar and co-validate one another. For example, at Citlaltépetl all lahar simulations show that the city of Orizaba is the most vulnerable to flows similar in magnitude to, or larger than, one that occurred in 1920. Many of the other cities and towns illustrated are built higher up on terrace deposits of older debris flows, and are safe from all but the largest flows, which occur less frequently. Finally, ASTERs 60 km swath width and 8% duty cycle presents a challenge for mapping lahar inundation hazards at E–W oriented stream valleys in low-latitude areas with persistent cloud cover. However, its continued operations enhances its utility as a means for updating the continuous but one-time coverage of SRTM, and for filling voids in the SRTM dataset such as those that occur along steep-sided valleys prone to hazards from future lahars.
Journal of Volcanology and Geothermal Research↗
Improved mapping of National Atmospheric Deposition Program wet-deposition in complex terrain using PRISM-gridded data sets
High-elevation regions in the United States lack detailed atmospheric wet-deposition data. The National Atmospheric Deposition Program/National Trends Network (NADP/NTN) measures and reports precipitation amounts and chemical constituent concentration and deposition data for the United States on annual isopleth maps using inverse distance weighted (IDW) interpolation methods. This interpolation for unsampled areas does not account for topographic influences. Therefore, NADP/NTN isopleth maps lack detail and potentially underestimate wet deposition in high-elevation regions. The NADP/NTN wet-deposition maps may be improved using precipitation grids generated by other networks. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) produces digital grids of precipitation estimates from many precipitation-monitoring networks and incorporates influences of topographical and geographical features. Because NADP/NTN ion concentrations do not vary with elevation as much as precipitation depths, PRISM is used with unadjusted NADP/NTN data in this paper to calculate ion wet deposition in complex terrain to yield more accurate and detailed isopleth deposition maps in complex terrain. PRISM precipitation estimates generally exceed NADP/NTN precipitation estimates for coastal and mountainous regions in the western United States. NADP/NTN precipitation estimates generally exceed PRISM precipitation estimates for leeward mountainous regions in Washington, Oregon, and Nevada, where abrupt changes in precipitation depths induced by topography are not depicted by IDW interpolation. PRISM-based deposition estimates for nitrate can exceed NADP/NTN estimates by more than 100% for mountainous regions in the western United States.
Environmental Monitoring and Assessment↗
Airborne laser mapping of Assateague National Seashore Beach
Results are presented from topographic surveys of the Assateague Island National Seashore using an airborne scanning laser altimeter and kinematic Global Positioning System (GPS) technology. The instrument used was the Airborne Topographic Mapper (ATM), developed by the NASA Arctic Ice Mapping (AIM) group from the Goddard Space Flight Center's Wallops Flight Facility. In November, 1995, and again in May, 1996, these topographic surveys were flown as a functionality check prior to conducting missions to measure the elevation of extensive sections of the Greenland Ice Sheet as part of NASA's Global Climate Change program. Differences between overlapping portions of both surveys are compared for quality control. An independent assessment of the accuracy of the ATM survey is provided by comparison to surface surveys which were conducted using standard techniques. The goal of these projects is to make these measurements to an accuracy of ± 10 cm. Differences between the fall 1995 and 1996 surveys provides an assessment of net changes in the beach morphology over an annual cycle.
Maryl↗
Spatial geologic data model for the Gunnison, Grand Mesa, Uncompahgre National Forests mineral resource assessment area, southwestern Colorado and digital data for the Leadville, Montrose, Durango, and Colorado parts of the Grand Junction, Moab, and Cortez 1° x 2° geologic maps
The digital geologic and geographic information system (GIS) data presented here were prepared to aid in Grand Mesa, Uncompahgre, Gunnison National Forest (GMUG) mineral resource assessment Project studies by the U.S. Geological Survey Mineral Resource Program. The goals of the GMUG Project is to provide mineral resource data and an assessment for undiscovered mineral resources in U.S. Forest Service (USFS) and Bureau of Land Management (BLM) lands in southwestern Colorado. The Project area covers a large region in southwestern Colorado that is bounded by latitudes 37o 45’ to 39o 30’ north and longitudes 106o to 109o west. The study area is covered by all or parts of six 1o x2o topographic and quadrangle geologic maps, which include geologic maps for the Leadville (Tweto and others, 1978), Montrose (Tweto and others, 1976), Durango (Steven and others, 1974), Grand Junction (Cashion, 1973), Moab (Williams, 1976), and Cortez (Haynes and others, 1972) quadrangles. These geologic maps were used inasmuch as a complete remapping and compilation effort for this study area was beyond the scope of the Project.
Colorado↗
Mapping forested wetland inundation in the Delmarva Peninsula, USA: Use of deep learning model
The Delmarva Peninsula in the eastern United States is dominated by thousands of small, forested depressional wetlands that are highly sensitive to climate change and climate variability but provide critical ecosystem services. Due to the relatively small size of these depressional wetlands and occurrence under forest canopy cover, it is very challenging to map their inundation status based on existing remote sensing data and traditional classification approaches. In this study, we applied a state-of-the-art deep semantic segmentation network to map forested wetland inundation in the Delmarva region by integrating leaf-off Worldview-3 (WV3) multispectral data with fine resolution light detection and ranging (lidar) intensity and topographic data, including digital elevation model (DEM) and topographic wetness index (TWI). Wetland inundation maps generated from lidar intensity were used for model calibration and validation. The wetland inundation map results were also validated by field polygons and compared to the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) geospatial dataset and a random forest output from a previous study. Our results demonstrate that our deep learning model can accurately determine inundation status with an overall accuracy of 95% against field data and high overlap with lidar mapped inundation. The integration of topographic metrics in deep learning model can improve classification accuracy in depressional wetlands. This study highlights the great potential of deep learning models to map wetland inundation through use of high resolution optical and lidar remote sensing datasets.
Maryland↗
Landslide overview map of the conterminous United States
The accompanying landslide overview map of the conterminous United States is one of a series of National Environmental Overview Maps that summarize geologic, hydrogeologic, and topographic data essential to the assessment of national environmental problems. The map delineates areas where large numbers of landslides exist and areas which are susceptible to landsliding. It was prepared by evaluating the geologic map of the United States and classifying the geologic units according to high, medium, or low landslide incidence (number) and high, medium, or low susceptibility to landsliding. Rock types, structures, topography, precipitation, landslide type, and landslide incidence are mentioned for each physical subdivision of the United States. The differences in slope stability between the Colorado Plateau, the Appalachian Highlands, the Coast Ranges of California, and the Southern Rocky Mountains are compared in detail, to illustrate the influence of various natural factors on the types of landsliding that occur in regions having different physical conditions. These four mountainous regions are among the most landslide-prone areas in the United States. The Colorado Plateau is a deformed platform where interbedded sedimentary rocks of varied lithologic properties have been gently warped and deeply eroded. The rocks are extensively fractured. Regional fracture systems, joints associated with individual geologic structures, and joints parallel to topographic surfaces, such as cliff faces, greatly influence slope stability. Detached blocks at the edges of mesas, as well as columns, arched recesses, and many natural arches on the Colorado Plateau, were formed wholly or in part by mass movement. In the Appalachian Highlands, earth flows, debris flows, and debris avalanches predominate in weathered bedrock and colluvium. Damaging debris avalanches result when persistent steady rainfall is followed by a sudden heavy downpour. Landsliding in unweathered bedrock is controlled locally by joint systems similar to those on the Colorado Plateau. In some places, outward gravitational movement of valley walls due to stress release has formed anticlines and caused thrusting in the center of valleys. In the Coast Ranges of California, slopes are steep, and rocks are varied and extensively deformed. One of the most slide-prone terrains of the Coast Ranges is the tectonic melange of the Franciscan assemblage, on which huge masses of debris are moving slowly downslope. In southern California, debris flows generated by soil slips are particularly damaging. Similar flows are common in poorly consolidated Tertiary rocks of the central part of the State. Like the debris avalanches of the Appalachian Highlands, the flows form during intense rainfall after previous steady rain. The Southern Rocky Mountains are complex in rock type and climate, so that the landslides there are also complex. Slides range from rock-falls at one extreme to slumps and debris flows at the other. They include ?sackungen,? which are distinguished by ridgetop grabens associated with uphill-facing scarps on ridge sides, both features of gravitational origin. Extensive regional joint patterns have not been recognized, and shallow soil slips are only a minor hazard.
conterminous United States↗
Limited evidence of late Quaternary tectonic surface deformation in the eastern Tennessee seismic zone, USA
The ~300-km-long eastern Tennessee seismic zone (ETSZ), USA, is the second-most seismically active region east of the Rocky Mountains. Seismicity generally occurs below the Paleozoic fold-and-thrust belt within the Mesoproterozoic basement, at depths of 5–26 km, and earthquake magnitudes during the instrumental record have been moment magnitude ( M w )≤4.8. Evidence of surface deformation may not exist or be difficult to detect because of the vegetated and soil-mantled landscape, landslides, locally steep topography, anthropogenic landscape modification, or long, irregular recurrence intervals between surface-rupturing earthquakes. Despite the deep seismicity, analog models indicate that accumulation of strike-slip or oblique-slip displacement at depth could be expected to propagate upward through the Paleozoic section, producing a detectable surficial signal of distributed faulting. To identify potential surface deformation, we interrogated the landscape at different spatial scales. We evaluated morphotectonic and channel metrics, such as channel sinuosity and catchment-scale hypsometry. Additionally, we mapped possible fault-related topographic features on 1-m lidar. Finally, we integrated our observations with available bedrock and Quaternary surficial mapping and subsurface geophysical data. At a regional scale, most morphotectonic and channel metrics have a strong lithologic control. Within smaller regions of similar lithology, we observe changes in landscape metrics like channel sinuosity and catchment-scale hypsometry that spatially correlate with new lineaments identified in this study and previously mapped east–west Cenozoic faults. These faults have apparent left-lateral offsets, are optimally oriented to slip in the current stress field, and match kinematics from recent focal mechanisms, but do not clearly preserve evidence of late Pleistocene or Holocene tectonic surface deformation. Most newly mapped lineaments might be explained by either tectonic or non-tectonic origins, such as fluvial or karst processes. We also re-evaluated a previously described paleoseismic site and interpret that the exposure does not record evidence of late Pleistocene faulting but instead is explained by fluvial stratigraphy.
Tennessee↗
Analysis of floods, including the tropical storm Irene inundation, of the Ottauquechee River in Woodstock, Bridgewater, and Killington and of Reservoir Brook in Bridgewater and Plymouth, Vermont
Digital flood-inundation maps were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, New York District for a 25-mile reach of the Ottauquechee River and a 2-mile reach of Reservoir Brook in Vermont. The reach of the Ottauquechee River that was studied extends from River Road Bridge in Killington, Vt., to the Taftsville Dam in the village of Taftsville, in the town of Woodstock, Vt., and the reach of Reservoir Brook extends from a location downstream from the Woodward Reservoir in Plymouth, Vt., to its confluence with the Ottauquechee River in Bridgewater, Vt. The inundation maps depict estimates of the areal extent of flooding corresponding to the 1-percent annual exceedance probability (AEP) flood (also referred to as the 100-year flood) and the peak of the tropical storm Irene flood of August 28, 2011, which was greater than the 0.2-percent AEP flood (also referred to as the 500-year flood), as referenced to the USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). In addition to the two digital flood inundation maps, flood profiles were created that depict the study reach flood elevation of tropical storm Irene of August 2011 and the 10-, 2-, 1-, and 0.2-percent AEP floods, also known as the 10-, 50-, 100-, and 500-year floods, respectively. The 10-, 2-, 1-, and 0.2-percent AEP flood discharges were determined using annual peak flow data from the USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). Flood profiles were computed for the Ottauquechee River and Reservoir Brook by means of a one-dimensional step-backwater model. The model was calibrated using documented high-water marks of the peak of the tropical storm Irene flood of August 2011 as well as stage discharge data as determined for USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). The simulated water-surface profiles were combined with a digital elevation model within a geographic information system to delineate the areas flooded during tropical storm Irene and for the 1-percent AEP water-surface profile. The digital elevation model data were derived from light detection and ranging (lidar) data obtained for a 3,281-foot (1,000-meter) corridor along the Ottauquechee River study reach and were augmented with 33-foot (10- meter) contour interval data in the modeled flood-inundation areas outside the lidar corridor. The 33-foot (10-meter) contour interval USGS 15-minute quadrangle topographic digital raster graphics map used to augment lidar data was produced at a scale of 1:24,000. The digital flood inundation maps and flood profiles along with information regarding current stage from USGS streamgages on the Internet provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.
Vermont↗