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At least 271 records · Page 15Linked to original sources
USGS2013

The National assessment of shoreline change—A GIS compilation of vector shorelines and associated shoreline change data for the Pacific Northwest coast

Sandy ocean beaches are a popular recreational destination and are often surrounded by communities that consist of valuable real estate. Development along sandy coastal areas is increasing despite the fact that coastal infrastructure may be repeatedly subjected to flooding and erosion. As a result, the demand for accurate information regarding past and present shoreline changes is increasing. Investigators with the U.S. Geological Survey's National Assessment of Shoreline Change Project have compiled a comprehensive database of digital vector shorelines and rates of shoreline change for the Pacific Northwest coast including the states of Washington and Oregon. No widely accepted standard for analyzing shoreline change currently exists. Current measurement and methods for calculating rates of change vary from study to study, precluding the combination of study results into statewide or regional assessments. The impetus behind the national assessment was to develop a standardized method that is consistent from coast to coast for measuring changes in shoreline position. The goal was to facilitate the process of periodically and systematically updating the measurements in an internally consistent manner. A detailed report on shoreline change for the Pacific Northwest coast that contains a discussion of the data presented here is available and cited in the Geospatial Data section of this report.

Oregon, Washington↗
USGS2009

Web-Based Geospatial Tools to Address Hazard Mitigation, Natural Resource Management, and Other Societal Issues

Federal, State, and local government agencies in the United States face a broad range of issues on a daily basis. Among these are natural hazard mitigation, homeland security, emergency response, economic and community development, water supply, and health and safety services. The U.S. Geological Survey (USGS) helps decision makers address these issues by providing natural hazard assessments, information on energy, mineral, water and biological resources, maps, and other geospatial information. Increasingly, decision makers at all levels are challenged not by the lack of information, but by the absence of effective tools to synthesize the large volume of data available, and to utilize the data to frame policy options in a straightforward and understandable manner. While geographic information system (GIS) technology has been widely applied to this end, systems with the necessary analytical power have been usable only by trained operators. The USGS is addressing the need for more accessible, manageable data tools by developing a suite of Web-based geospatial applications that will incorporate USGS and cooperating partner data into the decision making process for a variety of critical issues. Examples of Web-based geospatial tools being used to address societal issues follow.

Fact Sheet↗
USGS2017

Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States

This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.

Biological Invasions↗
USGS2011

Dose-Response Calculator for ArcGIS

The Dose-Response Calculator for ArcGIS is a tool that extends the Environmental Systems Research Institute (ESRI) ArcGIS 10 Desktop application to aid with the visualization of relationships between two raster GIS datasets. A dose-response curve is a line graph commonly used in medical research to examine the effects of different dosage rates of a drug or chemical (for example, carcinogen) on an outcome of interest (for example, cell mutations) (Russell and others, 1982). Dose-response curves have recently been used in ecological studies to examine the influence of an explanatory dose variable (for example, percentage of habitat cover, distance to disturbance) on a predicted response (for example, survival, probability of occurrence, abundance) (Aldridge and others, 2008). These dose curves have been created by calculating the predicted response value from a statistical model at different levels of the explanatory dose variable while holding values of other explanatory variables constant. Curves (plots) developed using the Dose-Response Calculator overcome the need to hold variables constant by using values extracted from the predicted response surface of a spatially explicit statistical model fit in a GIS, which include the variation of all explanatory variables, to visualize the univariate response to the dose variable. Application of the Dose-Response Calculator can be extended beyond the assessment of statistical model predictions and may be used to visualize the relationship between any two raster GIS datasets (see example in tool instructions). This tool generates tabular data for use in further exploration of dose-response relationships and a graph of the dose-response curve.

Data Series↗
USGS2007

Predicting the potential distribution of invasive exotic species using GIS and information-theoretic approaches: A case of ragweed (Ambrosia artemisiifolia L.) distribution in China

Invasive exotic species pose a growing threat to the economy, public health, and ecological integrity of nations worldwide. Explaining and predicting the spatial distribution of invasive exotic species is of great importance to prevention and early warning efforts. We are investigating the potential distribution of invasive exotic species, the environmental factors that influence these distributions, and the ability to predict them using statistical and information-theoretic approaches. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, for most species, absence data are not available. Presented with the challenge of developing a model based on presence-only information, we developed an improved logistic regression approach using Information Theory and Frequency Statistics to produce a relative suitability map. This paper generated a variety of distributions of ragweed (Ambrosia artemisiifolia L.) from logistic regression models applied to herbarium specimen location data and a suite of GIS layers including climatic, topographic, and land cover information. Our logistic regression model was based on Akaike's Information Criterion (AIC) from a suite of ecologically reasonable predictor variables. Based on the results we provided a new Frequency Statistical method to compartmentalize habitat-suitability in the native range. Finally, we used the model and the compartmentalized criterion developed in native ranges to "project" a potential distribution onto the exotic ranges to build habitat-suitability maps. ?? Science in China Press 2007.

Chinese Science Bulletin↗
USGS2003

NOGA Online: a USGS resource for energy GIS data and services

The PowerPoint presentation in this report was given at the BLM Resource Management Tools Conference in Phoenix, Arizona, April, 2003. Some diagrams that appeared in the original presentation have been updated in this report. It informs that the U.S. Geological Survey (USGS) Central Energy Resources Team (CERT) in Denver, Colorado, is providing National Oil and Gas Assessment (NOGA) results online at http://energy.cr.usgs.gov/oilgas/noga/. Available at this site are recently completed assessments of the potential for undiscovered oil and natural gas resources of five priority provinces (Montana Thrust Belt, Powder River Basin, San Juan Basin, Southwestern Wyoming, Uinta-Piceance) to meet the requirements of the Energy Policy and Conservation Act of 2000 (EPCA 2000). High demand for current assessment results and for the entirely digital, 1995 NOGA results for other provinces, prompted CERT to develop an internet map application using ArcIMS to deliver geologic data to the public. CERT continues to work on assessing oil and natural gas resources of priority basins in the United States; assessment results and GIS layers are made available at this site on an ongoing basis.

Open-File Report↗
USGS2003

Hydrogeologic factors that influence ground water movement in the desert southwest United States

A project to study ground-water and surface-water interactions in the desert southwestern United States was initiated in 2001 by the Tucson, Arizona office of the Water Resources Division, U.S. Geological Survey (USGS). One of the goals of the Southwest Ground-water Resources Project was to develop a regional synthesis that includes the use of available digital geologic data, which is growing rapidly due to the increasing use of Geographic Information Systems (GIS). Included in this report are the digital maps and databases of geologic information that should have a direct impact on the studies of ground-water flow and surface-water interaction. Ground-water flow is governed by many geologic factors or elements including rock and soil permeability, stratigraphy and structural features. These elements directly influence ground-water flow, which is key to understanding the possible inter-connectivity of aquifer systems in desert basins of the southwestern United States. We derive these elements from the evaluation of regional geology and localized studies of hydrogeologic basins. These elements can then be applied to other unstudied areas throughout the desert southwest. This report presents a regional perspective of the geologic elements controlling ground-water systems in the desert southwest that may eventually lead to greater focus on smaller sub-regions and ultimately, to individual ground-water basins.

Arizona, California, Colorado, Idaho, Nevada, New ↗
USGS1997

A Graphical-User Interface for the U. S. Geological Survey's SUTRA Code using Argus ONE (for simulation of variable-density saturated-unsaturated ground-water flow with solute or energy transport)

This report describes a Graphical-User Interface (GUI) for SUTRA, the U.S. Geological Survey (USGS) model for saturated-unsaturated variable-fluid-density ground-water flow with solute or energy transport,which combines a USGS-developed code that interfaces SUTRA with Argus ONE, a commercial software product developed by Argus Interware. This product, known as Argus Open Numerical Environments (Argus ONE TM ), is a programmable system with geographic-information-system-like (GIS-like) functionality that includes automated gridding and meshing capabilities for linking geospatial information with finite-difference and finite-element numerical model discretizations. The GUI for SUTRA is based on a public-domain Plug-In Extension (PIE) to Argus ONE that automates the use of ArgusONE to: automatically create the appropriate geospatial information coverages (information layers) for SUTRA, provide menus and dialogs for inputting geospatial information and simulation control parameters for SUTRA, and allow visualization of SUTRA simulation results. Following simulation control data and geospatial data input bythe user through the GUI, ArgusONE creates text files in a format required for normal input to SUTRA,and SUTRA can be executed within the Argus ONE environment. Then, hydraulic head, pressure, solute concentration, temperature, saturation and velocity results from the SUTRA simulation may be visualized. Although the GUI for SUTRA discussed in this report provides all of the graphical pre- and post-processor functions required for running SUTRA, it is also possible for advanced users to apply programmable features within Argus ONE to modify the GUI to meet the unique demands of particular ground-water modeling projects.

Open-File Report↗
USGS2014

An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri

Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed. Distinct basin characteristics were evaluated and selected for use on the basis of their theoretical relation to flow, results from previous studies, and the ability to reliably measure the basin characteristic using digital datasets and geographic information system (GIS) technology. The key basin characteristics determined or computed for each of the 39 basins upstream from the streamflow-gaging stations were drainage area, percent impervious area, main-channel slope based on the 10- and 85-percent length method, percentage of the basin area in storage (lakes, ponds, reservoirs, wetlands), the composite Natural Resources Conservation Service curve number estimated from a combination of the soil type data and land-use characteristics, and the streamflow variability index developed for the recently completed study of low-flow regression in Missouri. Characteristics of spatial and temporal rainfall distribution came from the next generation weather radar (NEXRAD) network. Procedures were developed for this study to convert the variable radar sweep rate into a 5-minute total rainfall hyetograph using data from the radar bin at the centroid of a given basin. Additional characteristics determined for each storm on the basin included the 5-day and 14-day antecedent rainfall, estimated from the mean of daily rainfall values from various rain gages in the area. The database of observed rainfall and runoff events for the 39 basins upstream from the streamflow-gaging stations was analyzed to compute the optimal storm-specific initial abstraction and constant loss values, as well as the time to peak, peak streamflow, and shape factor values of the GUH. The optimal storm-specific values were used to develop a regional regression equation for initial abstraction; conversely, the constant loss was estimated not by regression but from either a generalized or specific regional mean value. The optimal storm-specific values of GUH time to peak, GUH peak streamflow, and GUH shape factor were used to develop regression equations for the GUH. The regression equations for the GUH initially were tested alone, and then were combined with the appropriate regional regression equation for initial abstraction and both the generalized regional and specific regional mean constant loss values. For the GUH regression equations, the interquartile range was substantially smaller than the range spanned by the minimum and maximum values, which indicates most of the errors have much smaller variation, and the minimum and maximum values may be extreme outliers. The central tendency of the regressed errors for peak streamflow and runoff hydrograph volume were both approximately zero, which implies a generally unbiased estimation of these values. The mean and median of the regressed errors for time to peak streamflow were both small but greater than zero, which implies the GUH regression equations create a hydrograph that has a peak that is later in time than observed. Specifically, the regressed times indicate an offset of about 10 minutes, on average, from observed. The mean and median of the regressed errors for widths of the runoff hydrograph at 50 and 75 percent were less than zero, which implies the GUH tends to slightly underestimate these widths compared to the observed. The appropriate regional initial abstraction regression equation was combined with both the generalized and the specific regional mean constant loss values and the GUH regression equations. Both the generalized regional mean constant loss and specific regional mean constant loss forms of the basin-loss model worked equally well to model the observed runoff hydrograph based on the error analysis, and neither model seems to make a consistently better approximation. Both initial abstraction and constant loss models combined with the GUH regression equations were further validated using several storms available after the start of the project in early 2011 with similar but consistently higher error results. If these methods are used in an urban area in Missouri other than those examined in this study, advice to the user is given to consider using the generalized regional mean values. If these methods are used in an urban area that is a subbasin of one of the basins in this study, advice to the user is given to consider using the specific regional mean values. The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.

Missouri↗
USGS2011

Quantifying home range habitat requirements for bobcats (Lynx rufus) in Vermont, USA

We demonstrate how home range and habitat use analysis can inform landscape-scale conservation planning for the bobcat, Lynx rufus , in Vermont USA. From 2005 to 2008, we outfitted fourteen bobcats with GPS collars that collected spatially explicit locations from individuals every 4 h for 3–4 months. Kernel home range techniques were used to estimate home range size and boundaries, and to quantify the utilization distribution (UD), which is a spatially explicit, topographic mapping of how different areas within the home range are used. We then used GIS methods to quantify both biotic (e.g. habitat types, stream density) and abiotic (e.g. slope) resources within each bobcat’s home range. Across bobcats, upper 20th UD percentiles (core areas) had 18% less agriculture, 42% less development, 26% more bobcat habitat (shrub, deciduous, coniferous forest, and wetland cover types), and 33% lower road density than lower UD percentiles (UD valleys). For each bobcat, we used Akaike’s Information Criterion (AIC) to evaluate and compare 24 alternative Resource Utilization Functions (hypotheses) that could explain the topology of the individual’s UD. A model-averaged population-level Resource Utilization Function suggested positive responses to shrub, deciduous, coniferous forest, and wetland cover types within 1 km of a location, and negative responses to roads and mixed forest cover types within 1 km of a location. Applying this model-averaged function to each pixel in the study area revealed habitat suitability for bobcats across the entire study area, with suitability scores ranging between −1.69 and 1.44, where higher values were assumed to represent higher quality habitat. The southern Champlain Valley, which contained ample wetland and shrub habitat, was a concentrated area of highly suitable habitat, while areas at higher elevation areas were less suitable. Female bobcat home ranges, on average, had an average habitat suitability score of near 0, indicating that home ranges consisted of both beneficial and detrimental habitat types. We discuss the application of habitat suitability mapping and home range requirements for bobcat conservation and landscape scale management.

Vermont↗
USGS2014

An expanded model: flood-inundation maps for the Leaf River at Hattiesburg, Mississippi, 2013

Digital flood-inundation maps for a 6.8-mile reach of the Leaf River at Hattiesburg, Mississippi (Miss.), were created by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Leaf River at Hattiesburg, Miss. (station no. 02473000). Current conditions for estimating near-real-time areas of inundation by use of USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/ . In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations at the Leaf River at Hattiesburg, Miss. streamgage (02473000) and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from light detection and ranging (lidar) data having a 0.6-foot vertical and 9.84-foot horizontal resolution) in order to delineate the area flooded at each water level. Development of the estimated flood inundation maps as described in this report update previously published inundation estimates by including reaches of the Bouie and Leaf Rivers above their confluence. The availability of these maps along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS 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.

Mississippi↗
USGS2017

Modeling global Hammond landform regions from 250-m elevation data

In 1964, E.H. Hammond proposed criteria for classifying and mapping physiographic regions of the United States. Hammond produced a map entitled “Classes of Land Surface Form in the Forty-Eight States, USA”, which is regarded as a pioneering and rigorous treatment of regional physiography. Several researchers automated Hammond?s model in GIS. However, these were local or regional in application, and resulted in inadequate characterization of tablelands. We used a global 250 m DEM to produce a new characterization of global Hammond landform regions. The improved algorithm we developed for the regional landform modeling: (1) incorporated a profile parameter for the delineation of tablelands; (2) accommodated negative elevation data values; (3) allowed neighborhood analysis window (NAW) size to vary between parameters; (4) more accurately bounded plains regions; and (5) mapped landform regions as opposed to discrete landform features. The new global Hammond landform regions product builds on an existing global Hammond landform features product developed by the U.S. Geological Survey, which, while globally comprehensive, did not include tablelands, used a fixed NAW size, and essentially classified pixels rather than regions. Our algorithm also permits the disaggregation of “mixed” Hammond types (e.g. plains with high mountains) into their component parts.

Transactions in GIS↗
USGS2011

Characterization of salinity and selenium loading and land-use change in Montrose Arroyo, western Colorado, from 1992 to 2010

Salinity and selenium are naturally occurring and perva-sive in the lower Gunnison River Basin of Colorado, includ-ing the watershed of Montrose Arroyo. Although some of the salinity and selenium loading in the Montrose Arroyo study area is from natural sources, additional loading has resulted from the introduction of intensive irrigation in the water-shed. With increasing land-use change and the conversion from irrigated agricultural to urban land, land managers and stakeholders need information about the long-term effects of land-use change on salinity and selenium loading. In response to the need to advance salinity and selenium science, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, Colorado River Basin Salinity Control Forum, and Colorado River Water Conservation District, developed a study to characterize salinity and selenium loading and how salinity and selenium sources may relate to land-use change in Montrose Arroyo. This report characterizes changes in salinity and selenium loading to Montrose Arroyo from March 1992 to February 2010 and the magnitude of land-use change between unirrigated desert, irrigated agricultural, and urban land-use/land-cover types, and discusses how the respective loads may relate to land-use change. Montrose Arroyo is an approximately 8-square-mile watershed in Montrose County in western Colorado. Salinity and selenium were studied in Montrose Arroyo in a 2001 study as part of a salinity- and selenium-control lateral project. The robust nature of the historical dataset indicated that Montrose Arroyo was a prime watershed for a follow-up study. Two sites from the 2001 study were used to monitor salinity and selenium loads in Montrose Arroyo in the follow-up study. Over the period of 2 water years and respective irrigation seasons (2008-2010), 27 water-quality samples were collected and streamflow measurements were made at the historical sites MA2 and MA4. Salinity and selenium concen-trations, loads, and streamflow were compared between the pre-lateral-project and post-growth periods and between the post-lateral-project and post-growth periods. No significant differences in streamflow, salinity (concen-tration and load), or selenium (concentration and load) were found at MA4 between the pre-lateral project and post-growth periods or between the post-lateral-project and post-growth periods. The statistical analysis indicated no significant dif-ferences in streamflow or salinity (both concentration and load) between the pre-lateral-project and post-growth periods or between the post-lateral-project and post-growth periods at MA2; however, selenium concentrations and loads were significantly greater between the pre-lateral-project and post-growth periods and between the post-lateral-project and post-growth periods at MA2. Land-use change between MA4 and MA2 may have contributed to the determined differences in selenium values, but the specific mechanisms causing the increases between periods are unknown. The size of the urbanized area in Montrose Arroyo was quantified for 1993, 2002, and 2009 by using a geographic information system (GIS) with imagery from the specified years. The greatest change in land use from 1993 to 2009 was the increase of urban land due to conversion from irrigated agricultural land. The conversion of previously unirrigated desert to urban land or irrigated agriculture could become more common if urbanization and development expands into the eastern part of the watershed because a majority of the un-urbanized land in eastern Montrose Arroyo is unirrigated desert. By applying GIS to the City of Montrose 2008 com-prehensive growth plan, it was estimated that approximately 786 acres of previously irrigated agricultural land will be converted to urban land and 689 acres of unirrigated desert will be converted to urban land under the plan scenario. New development on previously unirrigated land in shale areas would likely increase the potential for mobilization of sele-nium and salinity from new sources to Montrose Arroyo and the Lower Gunnison River Basin.

Scientific Investigations Report↗
USGS2005

The New Hampshire watershed tool: a geographic information system tool to estimate streamflow statistics and ground-water-recharge rates

Estimates of low-flow statistics, flow durations, and ground-water-recharge rates are needed to assist water-resource managers in assessing surface-water resources and ground-water availability. Often these estimates are required at ungaged sites where no observed streamflow data are available for analysis. Regression equations for estimating low-flow statistics and flow durations, and for estimating ground-water-recharge rates at ungaged sites have been developed for New Hampshire. However, use of these equations requires numerous input parameters, such as basin and climatic characteristics. This report describes a customized geographic information system (GIS) application, the New Hampshire Watershed Tool, that automates the measurement of the characteristics used for input to the regression equations and calculates the corresponding flow statistics and ground-water-recharge rates.

Open-File Report↗
USGS2011

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

Scientific Investigations Report↗
USGS2015

Flood-inundation maps for the Tippecanoe River at Winamac, Indiana

Digital flood-inundation maps for a 6.2 mile reach of the Tippecanoe River at Winamac, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 03331753, Tippecanoe River at Winamac, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/in/nwis/uv?site_no=03331753 . In addition, information has been provided by the USGS to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http://water.weather.gov/ahps/ ). The NWS AHPS forecasts flood hydrographs at many sites that are often collocated with USGS streamgages, including the Tippecanoe River at Winamac, Ind. NWS AHPS forecast peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation and forecasts of flood hydrographs at this site. For this study, flood profiles were computed for the Tippecanoe River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at the Tippecanoe River streamgage, in combination with the current (2014) Federal Emergency Management Agency flood-insurance study for Pulaski County. The calibrated hydraulic model was then used to determine nine water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The 1-percent annual exceedance probability (AEP) flood stage (flood with recurrence intervals within 100 years) has not been determined yet for this streamgage location. The rating has not been developed for the 1-percent AEP because the streamgage dates to only 2001. The simulated water-surface profiles were then used with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [lidar]) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage 03331753, Tippecanoe River at Winamac, Ind., and forecast stream stages from the NWS AHPS, provides 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.

Indiana↗
USGS2000

A decision support system for prioritizing forested wetland restoration in the Yazoo Backwater Area, Mississippi

A working prototype decision support system (DSS) was developed for the Yazoo Backwater Area, Mississippi, to help planners and managers prioritize, plan, conduct, and optimize forested wetland restoration activities. The DSS comprises geographic information system (GIS) spatial data themes, application programs that provide a cumulative analysis of the relative ability of sites to function as wetlands, and output data that are specific to a given restoration analysis scenario. The DSS input includes GIS data themes such as geomorphology, soils, land use, elevation, farmed wetlands, flood frequency, topographic depressions, streams, public lands, roads, and permanent water bodies, which can be used as spatial templates to define areal hydrologic settings. These GIS data themes can then be ranked and combined to estimate the relative suitability of a potential wetland restoration site, thereby, determining relative wetland equivalence on the landscape. The GIS applications used in this DSS perform the following three functions: assess the ecology (the Eco-Assessor); reclassify land-use in areas selected for restoration (the Tree-Translator); and generate output data to compare restoration scenarios (the Parameter-Generator). Areas selected for reforestation are translated (in the GIS) into ?forested? land use, and the tree species that are ?planted? on the landscape (in the DSS) either compose an ecologically optimal or an economically optimal community of tree species. Output from the DSS can be compared and analyzed by using economic, statistical, graphical, and tabular methods. Output data for seven selected scenarios were generated for the Yazoo Backwater Area and are presented as examples to illustrate the flexibility of the DSS to identify areas that meet restoration objectives.

Water-Resources Investigations Report↗
USGS2014

High spatial resolution WorldView-2 imagery for mapping NDVI and its relationship to temporal urban landscape evapotranspiration factors

Evapotranspiration estimation has benefitted from recent advances in remote sensing and GIS techniques particularly in agricultural applications rather than urban environments. This paper explores the relationship between urban vegetation evapotranspiration (ET) and vegetation indices derived from newly-developed high spatial resolution WorldView-2 imagery. The study site was Veale Gardens in Adelaide, Australia. Image processing was applied on five images captured from February 2012 to February 2013 using ERDAS Imagine. From 64 possible two band combinations of WorldView-2, the most reliable one (with the maximum median differences) was selected. Normalized Difference Vegetation Index (NDVI) values were derived for each category of landscape cover, namely trees, shrubs, turf grasses, impervious pavements, and water bodies. Urban landscape evapotranspiration rates for Veale Gardens were estimated through field monitoring using observational-based landscape coefficients. The relationships between remotely sensed NDVIs for the entire Veale Gardens and for individual NDVIs of different vegetation covers were compared with field measured urban landscape evapotranspiration rates. The water stress conditions experienced in January 2013 decreased the correlation between ET and NDVI with the highest relationship of ET-Landscape NDVI (Landscape Normalized Difference Vegetation Index) for shrubs (r 2 = 0.66) and trees (r 2 = 0.63). However, when the January data was excluded, there was a significant correlation between ET and NDVI. The highest correlation for ET-Landscape NDVI was found for the entire Veale Gardens regardless of vegetation type (r 2 = 0.95, p > 0.05) and the lowest one was for turf (r 2 = 0.88, p > 0.05). In support of the feasibility of ET estimation by WV2 over a longer period, an algorithm recently developed that estimates evapotranspiration rates based on the Enhanced Vegetation Index (EVI) from MODIS was employed. The results revealed a significant positive relationship between ETMODIS and ETWV2 (r 2 = 0.9857, p > 0.05). This indicates that the relationship between NDVI using high resolution WorldView-2 imagery and ground-based validation approaches could provide an effective predictive tool for determining ET rates from unstressed mixed urban landscape plantings.

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