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SIM_ADJUST -- A computer code that adjusts simulated equivalents for observations or predictions

This report documents the SIM_ADJUST computer code. SIM_ADJUST surmounts an obstacle that is sometimes encountered when using universal model analysis computer codes such as UCODE_2005 (Poeter and others, 2005), PEST (Doherty, 2004), and OSTRICH (Matott, 2005; Fredrick and others (2007). These codes often read simulated equivalents from a list in a file produced by a process model such as MODFLOW that represents a system of interest. At times values needed by the universal code are missing or assigned default values because the process model could not produce a useful solution. SIM_ADJUST can be used to (1) read a file that lists expected observation or prediction names and possible alternatives for the simulated values; (2) read a file produced by a process model that contains space or tab delimited columns, including a column of simulated values and a column of related observation or prediction names; (3) identify observations or predictions that have been omitted or assigned a default value by the process model; and (4) produce an adjusted file that contains a column of simulated values and a column of associated observation or prediction names. The user may provide alternatives that are constant values or that are alternative simulated values. The user may also provide a sequence of alternatives. For example, the heads from a series of cells may be specified to ensure that a meaningful value is available to compare with an observation located in a cell that may become dry. SIM_ADJUST is constructed using modules from the JUPITER API, and is intended for use on any computer operating system. SIM_ADJUST consists of algorithms programmed in Fortran90, which efficiently performs numerical calculations.

Ground Water Modeling Investigation Report↗

Developing Vs30 site-condition maps by combining observations with geologic and topographic constraints

Despite obvious limitations as a proxy for site amplification, the use of time-averaged shear-wave velocity over the top 30 m (V S30 ) remains widely practiced, most notably through its use as an explanatory variable in ground motion prediction equations (and thus hazard maps and ShakeMaps, among other applications). As such, we are developing an improved strategy for producing V S30 maps given the common observational constraints. Using the abundant V S30 measurements in Taiwan, we compare alternative mapping methods that combine topographic slope, surface geology, and spatial correlation structure. The different V S30 mapping algorithms are distinguished by the way that slope and geology are combined to define a spatial model of V S30 . We consider the globally applicable slope-only model as a baseline to which we compare two methods of combining both slope and geology. For both hybrid approaches, we model spatial correlation structure of the residuals using the kriging-with-a-trend technique, which brings the map into closer agreement with the observations. Cross validation indicates that we can reduce the uncertainty of the V S30 map by up to 16% relative to the slope-only approach.

Conference Paper↗

U.S. Geological Survey development of a Landsat-based Fire Disturbance ECV

The United States Geological Survey (USGS) is the steward of the Landsat archive which includes satellite imagery dating back to 1972. The United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change have specified requirements to systematically observe atmosphere, ocean, and land characteristics, or Essential Climate Variables (ECVs). The Global Climate Observing System has developed formal specifications for ECVs that are technically and economically feasible for systematic ECV observation. Fire Disturbance is one of the 14 Terrestrial ECVs, and is defined as “burned area” supplemented by “active fires” and fire radiated power” (FRP) measurements. Landsat’s temporal resolution and sensor characteristics make it suitable for mapping burned area, but not suitable for monitoring active fires or FRP. In this paper, we describe the development of a database for calibration, verification, and validation of a Landsat-based burned area ECV, along with the algorithms to be tested against that database.

Conference Paper↗

Comparison of smoothing methods for the development of a smoothed seismicity model for Alaska and the implications for seismic hazard

In anticipation of the update of the Alaska seismic hazard maps (ASHMs) by the U. S. Geological Survey, we report progress on the comparison of smoothed seismicity models developed using fixed and adaptive smoothing algorithms, and investigate the sensitivity of seismic hazard to the models. While fault-based sources, such as those for great earthquakes in the Alaska-Aleutian subduction zone and for the ~10 shallow crustal faults within Alaska, dominate the seismic hazard estimates for locations near to the sources, smoothed seismicity rates make important contributions to seismic hazard away from fault-based sources and where knowledge of recurrence and magnitude is not sufficient for use in hazard studies. Recent developments in adaptive smoothing methods and statistical tests for evaluating and comparing rate models prompt us to investigate the appropriateness of adaptive smoothing for the ASHMs. We develop smoothed seismicity models for Alaska using fixed and adaptive smoothing methods and compare the resulting models by calculating and evaluating the joint likelihood test. We use the earthquake catalog, and associated completeness levels, developed for the 2007 ASHM to produce fixed-bandwidth-smoothed models with smoothing distances varying from 10 to 100 km and adaptively smoothed models. Adaptive smoothing follows the method of Helmstetter et al. and defines a unique smoothing distance for each earthquake epicenter from the distance to the nth nearest neighbor. The consequence of the adaptive smoothing methods is to reduce smoothing distances, causing locally increased seismicity rates, where seismicity rates are high and to increase smoothing distances where seismicity is sparse. We follow guidance from previous studies to optimize the neighbor number (n-value) by comparing model likelihood values, which estimate the likelihood that the observed earthquake epicenters from the recent catalog are derived from the smoothed rate models. We compare likelihood values from all rate models to rank the smoothing methods. We find that adaptively smoothed seismicity models yield better likelihood values than the fixed smoothing models. Holding all other (source and ground motion) models constant, we calculate seismic hazard curves for all points across Alaska on a 0.1 degree grid, using the adaptively smoothed and fixed smoothed seismicity models separately. Because adaptively smoothed models concentrate seismicity near the earthquake epicenters where seismicity rates are high, the corresponding hazard values are higher, locally, but reduced with distance from observed seismicity, relative to the hazard from fixed-bandwidth models. We suggest that adaptively smoothed seismicity models be considered for implementation in the update to the ASHMs because of their improved likelihood estimates relative to fixed smoothing methods; however, concomitant increases in seismic hazard will cause significant changes in regions of high seismicity, such as near the subduction zone, northeast of Kotzebue, and along the NNE trending zone of seismicity in the Alaskan interior.

Alaska↗

Status and trends monitoring of the mainstem Columbia River: sample frame development and review of programs relevant to the development of an integrated approach to monitoring

Implementing an Integrated Status and Trends Monitoring program (ISTM) for the mainstem Columbia River will help identify trends in important natural resources and help us understand the long-term collective effects of management actions. In this report, we present progress towards the completion of a stepwise process that will facilitate the development of an ISTM for the mainstem Columbia River. We discuss planning and regulatory documents that can be used to identify monitoring goals and objectives and present existing monitoring and research activities that should be considered as the development of a Columbia River ISTM proceeds. We also report progress towards the development of sample frames for the Columbia and Snake Rivers and their floodplains. The sample frames were formulated using Digital Elevation Models (DEM’s) of the river channel and upland areas and a Generalized Random-Tessellation Stratified (GRTS) algorithm for an area based resource to generate “master sample(s).” Working with the Pacific Northwest Aquatic Monitoring Partnership (PNAMP) we facilitated the transfer of the sample frames to the PNAMP “Monitoring Sample Designer” tool. We then discuss aspects of response and survey designs as they pertain to the formulation of a mainstem Columbia River ISTM. As efforts to formulate an ISTM for the mainstem Columbia River proceed, practitioners should utilize the extensive literature describing the planning and implementation of fish and wildlife mitigation and recovery efforts in the Columbia River Basin. While we make progress towards establishing an ISTM framework, considerable work needs to be done to formulate an ISTM program for the mainstem Columbia River. Long-term monitoring programs have been established for other large rivers systems; scientists that have experience planning, implementing, and maintaining large river monitoring efforts such as those in the Colorado, Illinois, and Mississippi Rivers should be consulted and involved as efforts proceed.

Idaho;Oregon;Washington↗

Geopressure gradient maps of Southern Louisiana, state, and vicinity

This series of five maps characterizes the subsurface pressure system of southern Louisiana, including the associated State and Federal waters. These maps were generated using the U.S. Geological Survey’s (USGS) comprehensive geopressure-gradient model (Burke et al., 2012b, 2013) that delineates the regional pressure system spanning the onshore and offshore Gulf of Mexico basin, USA. Previously, the model was used to generate ten regional-scale maps (Burke et al., 2012a): five contour maps characterized the depth to the surface defined by the first occurrence of regional isopressure gradients ranging from 0.60 psi/ft to 1.00 psi/ft, in 0.10-psi/ft increments; and five supporting maps displayed the spatial density of the data used to construct the regional contour maps. Explanation of generalized geopressure gradients and pressure-regime nomenclature is given here. The five contour maps in this series characterize the depth to the surface defined by the first occurrence of isopressure gradients ranging from 0.60 psi/ft to 1.00 psi/ft, in 0.10-psi/ft increments. The geographical extent of this geopressure-gradient model is delineated on the maps, which encompass one of the most densely drilled regions of southern Louisiana and adjacent areas. The boundary of the model represents the area of greatest well density to maintain accurate contouring to the edge of the model. The pressure data were obtained from the IHS database (IHS Energy Group, 2011) and geologic folios (Dodge and Posey, 1981; Bebout and Gutiérrez, 1982; 1983; Eversull, 1984; Foote et al., 1990), which were compiled and digitally archived (Burke et al., 2011). Data quality analysis, linear-pressure interpolation calculations, and contouring algorithms defining the geopressure-gradient model are described by Burke et al. (2012b, 2013). The isopressure-gradient trends depicted on these maps are not intended for detailed interpretation at specific locations.

Louisiana↗

Thresholds for conservation and management: structured decision making as a conceptual framework

A conceptual framework is provided for considering the threshold concept in natural resource management and conservation. We define three kinds of thresholds relevant to management and conservation. Ecological thresholds are values of system state variables at which small changes bring about substantial or specified changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process.We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

Book↗

Geospatial optimization of siting large-scale solar projects

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting some large-scale solar projects, such as concentrating solar power (CSP), is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility- scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent with each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.

Arizona;California;Colorado;Idaho;Montana;Nevada;N↗

Inventory and mapping of flood inundation using interactive digital image analysis techniques

LANDSAT digital data and color infra-red photographs were used in a multiphase sampling scheme to estimate the area of agricultural land affected by a flood. The LANDSAT data were classified with a maximum likelihood algorithm. Stratification of the LANDSAT data, prior to classification, greatly reduced misclassification errors. The classification results were used to prepare a map overlay showing the areal extent of flooding. These data also provided statistics required to estimate sample size in a two phase sampling scheme, and provided quick, accurate estimates of areas flooded for the first phase. The measurements made in the second phase, based on ground data and photo-interpretation, were used with two phase sampling statistics to estimate the area of agricultural land affected by flooding These results show that LANDSAT digital data can be used to prepare map overlays showing the extent of flooding on agricultural land and, with two phase sampling procedures, can provide acreage estimates with sampling errors of about 5 percent. This procedure provides a technique for rapidly assessing the areal extent of flood conditions on agricultural land and would provide a basis for designing a sampling framework to estimate the impact of flooding on crop production.

Canadian Journal of Remote Sensing↗

Data integration using color space transforms

The demand for increased spatial resolution without sacrificing spectral discrimination can be fulfilled by integration of data from different sensor systems and satellite programs. Data of high spatial resolution are frequently available in panchromatic (black-and-white) form rather than multispectral. Techniques gave been developed to combine the higher resolution panchromatic data with a multispectral data set of lower spatial resolution. The standard method of integration modulates the intensity of the mutispectral with the panchromatic data. A less subjective approach uses an algorithm that describes color in terms of intensity (I), hue (H), and saturation (S). Combinations of high resolution panchromatic data (SPOT panchromatic) and lower resolution multispectral data [Landsat thematic mapper (TM), SPOT XS] have been developed. The SPOT data were acquired on April 3, 1986, and the Landsat TM data were acquired on April 5, 1986. The data sets were registered to each other and the multi-spectral data sets were contrast enhanced. The enhanced multispectral data sets were then transformed from red/green/blue (RGB) color space into IHS space. In each case (TM/SPOT panchromatic and SPOT XS/SPOT panchromatic), the SPOT panchromatic data were remapped on a cumulative histogram percentage basis to match the multispectral "I" data. These remapped SPOT panchromatic data were substituted for the original multispectral "I" and the hybrid IHS data transformed back into RGB space for display. While this technique is experimental and still being refined, the results, to date, indicate that the IHS method will be valuable for generating improved images that effectively present both high resolution spatial digital data and multispectral data.

Pecora XI Symposium↗

Landsat-faciliated vegetation classification of the Kenai National Wildlife Refuge and adjacent areas, Alaska

A Landsat-based vegetation map was prepared for Kenai National Wildlife Refuge and adjacent lands, 2 million and 2.5 million acres respectively. The refuge lies within the middle boreal sub zone of south central Alaska. Seven major classes and sixteen subclasses were recognized: forest (closed needleleaf, needleleaf woodland, mixed); deciduous scrub (lowland and montane, subalpine); dwarf scrub (dwarf shrub tundra, lichen tundra, dwarf shrub and lichen tundra, dwarf shrub peatland, string bog/wetlands); herbaceous (graminoid meadows and marshes); scarcely vegetated areas ; water (clear, moderately turbid, highly turbid); and glaciers. The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo interpretation, and digital Landsat data. Major steps in the Landsat analysis involved: preprocessing (geometric connection), spectral class labeling of sample areas, derivation of statistical parameters for spectral classes, preliminary classification of the entree study area using a maximum-likelihood algorithm, and final classification through ancillary information such as digital elevation data. The vegetation map (scale 1:250,000) was a pioneering effort since there were no intermediate-sclae maps of the area. Representative of distinctive regional patterns, the map was suitable for use in comprehensive conservation planning and wildlife management.

Alaska↗

Monitoring the earth: too many players?

A number of organizations are currently engaged in, or proposing to embark on, worldwide measurement/monitoring programs. Program objectives vary in type and complexity, including a form of technical library (the Global Environment Monitoring System of the United Nations Environment Program), and an ambitious experiment to validate algorithms to derive land surface climatological parameters (International Satellite Land Surface Climatology Project). Modeling and understanding the Earth as an integrated system is an immense undertaking and will require at least as many measurements as are currently acquired. Improved coordination is required among the diverse national and international measurement/monitoring programs to ensure that sensors, launch dates, orbits, and supporting research are complementary to the maximum extent possible. Development of a long-term program of Earth system monitoring/modeling, such as the International Global Change Program proposed by the International Council of Scientific Unions, could provide the necessary focus and structure for effective international coordination and cooperation.

Pecora 10 Symposium↗

Processing techniques for global land 1-km AVHRR data

The U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in cooperation with several international science organizations has developed techniques for processing daily Advanced Very High Resolution Radiometer (AVHRR) 1-km data of the entire global land surface. These techniques include orbital stitching, geometric rectification, radiometric calibration, and atmospheric correction. An orbital stitching algorithm was developed to combine consecutive observations acquired along an orbit by ground receiving stations into contiguous half-orbital segments. The geometric rectification process uses an AVHRR satellite model that contains modules for forward mapping, forward terrain correction, and inverse mapping with terrain correction. The correction is accomplished by using the hydrologic features coastlines and lakes from the Digital Chart of the World. These features are rasterized into the satellite projection and are matched to the AVHRR imagery using binary edge correlation techniques. The resulting coefficients are related to six attitude correction parameters: roll, roll rate, pitch, pitch rate, yaw, and altitude. The image can then be precision corrected to a variety of map projections and user-selected image frames. Because the AVHRR lacks onboard calibration for the optical wavelengths, a series of time-variant calibration coefficients derived from vicarious calibration methods and are used to model the degradation profile of the instruments. Reducing atmospheric effects on AVHRR data is important. A method has been develop that will remove the effects of molecular scattering and absorption from clear sky observations, using climatological measurements of ozone. Other methods to remove the effects of water vapor and aerosols are being investigated.

Pecora 12 Symposium↗

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Pecora 12 Symposium↗

A workshop model simulating fate and effect of drilling muds and cuttings on benthic communities

Oil and gas exploration and production at marine sites has generated concern over potential environmental impacts resulting from the discharge of spent drilling muds and cuttings. This concern has led to a broad array of publicly and privately sponsored research. This report described a cooperative modeling effort designed to focus information resulting from this research through construction of explicit equations that simulate the potential impacts of discharge drilling fluids (muds) and cuttings on marine communities. The model is the result of collaboration among more than 30 scientists. The principal cooperating organizations were the E.S. Environmental Protection Agency, the U.S. Minerals Management Service, the Offshore Operators Committee, and the Alaska Oil and Gas Association. The overall simulation model can be conceptualized as three connected submodels: Discharge and Plume Fate, Sediment Redistribution, and Benthic Community Effects. On each day of simulation, these submodels are executed in sequence, with flows of information between submodels. The Benthic Community Effects submodel can be further divided into sections that calculate mortality due to burial, mortality due to toxicity, mortality due to resuspension disturbance, and growth of the community. The model represents a series of seven discrete 1-m 2 plots at specified distances along a transect in one direction away from a discharge point. It consists of coupled difference equations for which parameter values can easily be set to evaluate different conditions or to examine the sensitivity of output to various assumptions. Sets of parameter values were developed to represent four general cases or scenarios: (1) a shallow (5 m), cold environment with ice cover during a substantial fraction of the year, such as might be encountered in the Beaufort Sea, Alaska; (2) a shallow (20 m), temperate environment, such as might be encountered in the Gulf of Mexico; (3) a deeper (80 m), temperate environment, such as might be encountered in the Gulf of Mexico; and (4) a very deep (1,000 m) environment, such as might be encountered on the Atlantic slope. The focus of the modeling effort was on the connection of a reasonable representation of physical fate to the biological responses of populations, rather than on highly detailed representations of individual processes. For example, the calculations of physical fate are not as detailed as those in the recently published model of Brandsma et al. (1983). The value of the model described herein is in the broad scope of processes that are explicitly represented and linked together. The model cannot be considered to produce reliable predictions of the quantitative impacts of discharged drilling fluids and cuttings on biological populations at a particular site. Limitations of the model in predicting integrated fate and effects can be traced to three general areas: level of refinement of the algorithms used in the model; lack of understanding of the processes determining fate and effects; and parameter and data values. Despite the limitations, several qualitative conclusions concerning both potential impacts and the importance of various remaining data gaps can be drawn from the modeling effort. These include: (1) Simple, unequivocal conclusions about fate and effects across geographical regions and drilling operations are difficult, if not misleading, due to the large amount of variability in characteristics of discharged materials (e.g., oil content and toxicity), discharge conditions (e.g., duration of drilling operations), physical environments (e.g., water depth, current direction, and sediment disturbance regimes), and biological communities (e.g., intrinsic growth rates). Different combinations of these characteristics can result in substantial differences in simulated environmental fate and biological effects. For examples, simulated recovery in some high-energy environments occurs within months after the cessation of discharge operations, even at heavily impacted sites, whereas simulated recover in some low-energy environments takes years at heavily impacted sites. <2) Considerable difficulties remain in the reliable extrapolation of results from laboratory toxicity experiments to predictions of population effects in the field. (3) The volume of material discharged and duration of operations in the production drilling operations simulated by the model are sufficient to produce substantial simulated biological impacts at some plots, both in terms of differences from a control plot during the period of discharge operations, and in terms of the recovery period following the perturbations. Evaluation of the significance of potential effects involves the following factors: • Definition of a specific spatial and temporal reference frame (e.g., What is the natural variation? Is 1 year to be considered a "long" or "short" time? Is 50 m to be considered a "large" or "trivial" distance? • Consideration of rare or unique resources and particularly sensitive biotic assemblages. • Consideration of the potential for long term, cumulative effects. Some of these aspects are clearly beyond the scope of this modeling efforts (e.g., the model does not simulate the long term fate of resuspended material). The model does, however, contain an internal "reference frame" by comparison to simulated behavior at a control plot. The model, in general, simulates substantial "natural" variation at the reference or control plots, both over time, due to sediment disturbance events in medium to high energy environments, and over space, due to geographically varying conditions, such as water depth and current regime.

Report↗

Vegetation mapping of Nowitna National Wildlife Refuge, Alaska using Landsat MSS digital data

A Landsat-derived vegetation map was prepared for Nowitna National Wildlife Refuge. The refuge lies within the middle boreal subzone of north central Alaska. Seven major vegetation classes and sixteen subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, alluvial, subalpine); dwarf scrub (prostrate dwarf shrub tundra, dwarf shrub-graminoid tussock peatland); herbaceous (graminoid bog, marsh and meadow); scarcely vegetated areas (scarcely vegetated scree and floodplain); water (clear, turbid); and other areas (mountain shadow). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photointerpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is a 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Alaska↗

Intermediate-scale vegetation mapping of Innoko National Wildlife Refuge, Alaska using Landsat MSS digital data

A Landsat-derived vegetation map was prepared for lnnoko National Wildlife Refuge. The refuge lies within the northern boreal subzone of northwestern central Alaska. Six major vegetation classes and 21 subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, upland burn regeneration, subalpine); dwarf scrub (prostrate dwarf shrub tundra, erect dwarf shrub heath, dwarf shrub-graminoid peatland, dwarf shrub-graminoid tussock peatland, dwarf shrub raised bog with scattered trees, dwarf shrub-graminoid marsh); herbaceous (graminoid bog, graminoid marsh, graminoid tussock-dwarf shrub peatland); scarcely vegetated areas (scarcely vegetated scree and floodplain); and water (clear, sedimented). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo-interpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Alaska↗

Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport

Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial variability in transport was also detected in the longitudinal profiles audibly and using signal processing algorithms. These experiments demonstrate the ability of hydrophone technology to capture the temporal and spatial variability of sediment transport, which may be missed when samples are collected using conventional methods.

California, Colorado↗