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At least 649 records · Page 36Linked to original sources
USGS2023

Ground motion and seismic hazard in the central and eastern United States

This report describes work carried out under the U.S. Nuclear Regulatory Commission (NRC) Interagency Agreement to the U.S. Geological Survey (USGS) “Research to Support NRC’s Seismic Hazard Analyses” for Task 3, “Seismic Hazard and Ground Motion Models.” The focus of this work has been on evaluation of the Next Generation Attenuation (NGA)-East groundmotion models (GMMs) with available ground-motion data and evaluation of alternative methods for characterizing epistemic uncertainty for probabilistic seismic hazard analysis (PSHA). When the Interagency Agreement commenced, the USGS’s National Seismic Hazard Model (NSHM) was being updated, and a significant part of the update for the 2018 NSHM included the introduction of new GMMs for the central and eastern United States (CEUS) (Petersen et al., 2020). In addition to the implementation of the then-recently developed NGA-East GMMs (Goulet et al., 2018), the ground-motion characterization for the CEUS in the 2018 NSHM also included a logic-tree branch with weights applied to the updated “adjusted seed” models that were developed as part of the NGA-East process and in updates by the GMM developers. The Statement of Work for Task 3 of the NRC Interagency Agreement to the USGS included the following parts: (1) Describe technically acceptable approaches in combining GMMs for use in PSHA calculations; (2) Evaluate the effect of using different sets of GMMs (NGA-East SSHAC versus NGA-East USGS) on PSHA calculations; (3) Describe the results of the GMM testing against recorded data, and provide a recommendation on the GMMs application for use in the PSHA; (4) Evaluate the impacts of recently updated individual GMMs on the published NGAEast models; and (5) Submit a final Technical Letter Report documenting results of this task. We present results from this work in two sections: (Chapter 1) Updated Central and Eastern United States Ground Motions and Ground-Motion Analyses; and (Chapter 2) Approaches to Combining Ground-Motion Models for Probabilistic Seismic Hazard Analysis in the Central and Eastern United States.

central and eastern United States↗
USGS1999

SutraPlot, a graphical post-processor for SUTRA, a model for ground-water flow with solute or energy transport

This report documents a graphical display post-processor (SutraPlot) for the U.S. Geological Survey Saturated-Unsaturated flow and solute or energy TRAnsport simulation model SUTRA, Version 2D3D.1. This version of SutraPlot is an upgrade to SutraPlot for the 2D-only SUTRA model (Souza, 1987). It has been modified to add 3D functionality, a graphical user interface (GUI), and enhanced graphic output options. Graphical options for 2D SUTRA (2-dimension) simulations include: drawing the 2D finite-element mesh, mesh boundary, and velocity vectors; plots of contours for pressure, saturation, concentration, and temperature within the model region; 2D finite-element based gridding and interpolation; and 2D gridded data export files. Graphical options for 3D SUTRA (3-dimension) simulations include: drawing the 3D finite-element mesh; plots of contours for pressure, saturation, concentration, and temperature in 2D sections of the 3D model region; 3D finite-element based gridding and interpolation; drawing selected regions of velocity vectors (projected on principal coordinate planes); and 3D gridded data export files. Installation instructions and a description of all graphic options are presented. A sample SUTRA problem is described and three step-by-step SutraPlot applications are provided. In addition, the methodology and numerical algorithms for the 2D and 3D finite-element based gridding and interpolation, developed for SutraPlot, are described. 1

Open-File Report↗
USGS2022

Evaluating the sensitivity of multi-dimensional model predictions of salmon habitat to the source of remotely sensed river bathymetry

Multi-dimensional numerical models are fundamental tools for investigating biophysical processes in aquatic ecosystems. Remote sensing techniques increase the feasibility of applying such models at riverscape scales, but tests of model performance on large rivers have been limited. We evaluated the potential to develop two-dimensional (2D) and three-dimensional (3D) hydrodynamic models for a 1.6-km reach of a large gravel-bed river using three sources of remotely sensed river bathymetry. We estimated depth from hyperspectral image data acquired from conventional and uncrewed aircraft and multispectral satellite imagery. Our results indicated that modeled water depth errors were similar between 2D and 3D models, with depth residuals that were comparable to the uncertainty associated with the bathymetry used as input. We found good agreement between measured and modeled depth-averaged velocities generated by 2D and 3D models, while 3D models provided superior predictions of near-bed velocities. We found that optimal model performance occurred for lower flow resistance values than previously reported in the literature, possibly as a consequence of the high-resolution bathymetry used as model input. Model predictions of winter-run Chinook salmon ( Oncorhynchus tshawytscha ) spawning and rearing habitat were not sensitive to the source of bathymetric information, but bioenergetic predictions related to adult holding costs were influenced by the input bathymetry. Our results suggest that hyperspectral imagery acquired from piloted and/or uncrewed aircraft can be used to map the bathymetry of clear-flowing, relatively shallow large rivers with sufficient accuracy to support multi-dimensional flow model development; models developed from multispectral satellite imagery had more limited predictive capability.

California↗
USGS2020

Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data

Stream water temperature ( T s ) is a variable of critical importance for aquatic ecosystem health. T s is strongly affected by groundwater-surface water interactions which can be learned from streamflow records, but previously such information was challenging to effectively absorb with process-based models due to parameter equifinality. Based on the long short-term memory (LSTM) deep learning architecture, we developed a basin-centric lumped daily mean T s model, which was trained over 118 data-rich basins with no major dams in the conterminous United States, and showed strong results. At a national scale, we obtained a median root-mean-square error of 0.69°C, Nash–Sutcliffe model efficiency coefficient of 0.985, and correlation of 0.994, which are marked improvements over previous values reported in literature. The addition of streamflow observations as a model input strongly elevated the performance of this model. In the absence of measured streamflow, we showed that a two-stage model could be used, where simulated streamflow from a pre-trained LSTM model ( Q sim ) still benefited the T s model even though no new information was brought directly into the inputs of the T s model. The model indirectly used information learned from streamflow observations provided during the training of Q sim , potentially to improve internal representation of physically meaningful variables. Our results indicate that strong relationships exist between basin-averaged forcing variables, catchment attributes, and T s that can be simulated by a single model trained by data on the continental scale.

Environmental Research Letters↗
USGS2023

Range-wide trends in tiger conservation landscapes, 2001 - 2020

Of all the ways human beings have modified the planet over the last 10,000 years, habitat loss is the most important for other species. To address this most critical threat to biodiversity, governments, non-governmental actors, and the public need to know, in near real-time, where and when habitat loss is occurring. Here we present an integrated habitat modelling system at the range-wide scale for the tiger ( Panthera tigris ) to measure and monitor changes in tiger habitat at range-wide, national, biome, and landscape scales, as often as the underlying inputs change. We find that after nearly 150 years of decline, effective potential habitat for the tiger seems to have stabilized at around 16% of its indigenous extent (1.817 million km 2 ). As of the 1st of January 2020, there were 63 Tiger Conservation Landscapes in the world, covering 911,920 km 2 shared across ten of the 30 modern countries which once harbored tiger populations. Over the last 20 years, the total area of Tiger Conservation Landscapes (TCLs) declined from 1.025 million km 2 in 2001, a range-wide loss of 11%, with the greatest losses in Southeast Asia and southern China. Meanwhile, we documented expansions of modelled TCL area in India, Nepal, Bhutan, northern China, and southeastern Russia. We find significant potential for restoring tigers to existing habitats, identified here in 226 Restoration Landscapes. If these habitats had sufficient prey and were tigers able to find them, the occupied land base for tigers might increase by 50%. Our analytical system, incorporating Earth observations, in situ biological data, and a conservation-oriented modelling framework, provides the information the countries need to protect tigers and enhance habitat, including dynamic, spatially explicit maps and results, updated as often as the underlying data change. Our work builds on nearly 30 years of tiger conservation research and provides an accessible way for countries to measure progress and report outcomes. This work serves as a model for objective, range-wide, habitat monitoring as countries work to achieve the goals laid out in the Sustainable Development Goals, the 30×30 Agenda, and the Kunming-Montreal Global Biodiversity Framework.

Frontiers in Conservation Science↗
USGS1971

Suggested criteria for hydrologic design of storm-drainage facilities in the San Francisco Bay Region, California

This report presents basic criteria, in the form of tables and graphs, for each of the four methods of hydrologic design most commonly used in the San Francisco Bay region--flood-frequency analysis, Rational Method, unit-hydrograph method, and runoff simulation by means of hydrologic basin modeling. The term "hydrologic design" as used in this report refers to the computation of either design values of peak discharge or design hydrographs of storm runoff. The hydraulics of open-channel and pipeline flow and the actual design of appurtenances for conveying the runoff are not discussed in this paper. Use of the suggested criteria results in fairly close agreement between peak discharges computed by the flood-frequency and unit-hydrograph methods. Those peak discharges are not directly comparable with discharges computed by the Rational Method, in part because the results obtained by the Rational Method are affected by the values assigned to parameters for overland and channel flow. Those parameters are additional to the ones used in the flood-frequency and unit-hydrograph methods. A demonstration of runoff simulation by use of a hydrologic basin model is beyond the scope of this paper--such demonstrations are found in the appropriate references cited. However, this report does present an original technique for transposing storm rainfall in the region, storm transposition being commonly required to obtain the precipitation input used with hydrologic basin models.

California↗
USGS2014

Sediment-hosted gold deposits of the world: Database and grade and tonnage models

All sediment-hosted gold deposits (as a single population) share one characteristic—they all have disseminated micron-sized invisible gold in sedimentary rocks. Sediment-hosted gold deposits are recognized in the Great Basin province of the western United States and in China along with a few recognized deposits in Indonesia, Iran, and Malaysia. Three new grade and tonnage models for sediment-hosted gold deposits are presented in this paper: (1) a general sediment-hosted gold type model, (2) a Carlin subtype model, and (3) a Chinese subtype model. These models are based on grade and tonnage data from a database compilation of 118 sediment-hosted gold deposits including a total of 123 global deposits. The new general grade and tonnage model for sediment-hosted gold deposits (n=118) has a median tonnage of 5.7 million metric tonnes (Mt) and a gold grade of 2.9 grams per tonne (g/t). This new grade and tonnage model is remarkable in that the estimated parameters of the resulting grade and tonnage distributions are comparable to the previous model of Mosier and others (1992). A notable change is in the reporting of silver in more than 10 percent of deposits; moreover, the previous model had not considered deposits in China. From this general grade and tonnage model, two significantly different subtypes of sediment-hosted gold deposits are differentiated: Carlin and Chinese. The Carlin subtype includes 88 deposits in the western United States, Indonesia, Iran, and Malaysia, with median tonnage and grade of 7.1 Mt and 2.0 g/t Au, respectively. The silver grade is 0.78 g/t Ag for the 10th percentile of deposits. The Chinese subtype represents 30 deposits in China, with a median tonnage of 3.9 Mt and medium grade of 4.6 g/t Au. Important differences are recognized in the mineralogy and alteration of the two sediment-hosted gold subtypes such as: increased sulfide minerals in the Chinese subtype and decalcification alteration dominant in the Carlin type. We therefore recommend using the appropriate grade and tonnage model presented in this study for mineral resource assessments depending on the geologic and mineralogical data available for a region. Tonnage and contained gold within the general sediment-hosted gold model are analyzed based on major geologic features such as tectonic setting and magmatic (dikes, sills, and stocks) or amagmatic environment. The results show a significant difference in tonnage and contained gold, with higher median values in deposits spatially associated with igneous rocks, regardless of structural style of the deposit. These results suggest that magmatic environments control mineralization intensity—an important consideration in the regional assessment of prospective areas for sediment-hosted gold deposits.

Open-File Report↗
USGS2017

Co-producing simulation models to inform resource management: a case study from southwest South Dakota

Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.

South Dakota↗
USGS1983

Slides showing quantitative models for mineral-resource assessment of the Rolla 1 degree x 2 degrees Quadrangle, Missouri

Th.is report consists of nineteen 35-mm color slides sh.owing digital synthesis and quantitative modeling of five geologic recognition criteria for assessment of Mississippi Valley-type resource potential in the Rolla 1° x 2° quadrangle, Missouri. The digital synthesis and quantitative modeling (Pratt and others, 1982) was done to supplement an earlier manual synthesis and evaluation (Pratt, 1981). The five criteria synthesized in this study, and the sources of data used, are that most known deposits are: In dolomite of the Bonneterre Formation, near the limestone-dolomite interface, which is defined as ls:dol = 1:16 (Thacker and Anderson, 1979; Kisvarsanyi, 1982); Near areas where insoluble residues of "barren" Bonneterre Formation contain anomalously high amounts of base metals (Erickson and others, 1978); Near areas of faults and fractures in the Bonneterre Formation or in underlying rocks (Pratt, 1982); In "brown rock" (finely crystalline brown dolomite) near the interface with "white rock" (coarsely recrystallized, white or very light gray, vuggy, illite-bearing dolomite) (Kisvarsanyi, 1982); Near or within favorably situated digitate reef-complex facies (Kisvarsanyi , 1982).

Open-File Report↗
USGS1983

Platte River Forum for the Future: workshop model documentation

The Platte River Forum for the Future (PRFF) is an effort by the Nebraska Natural Resources Commission (NNRC) to bring together representatives of interests and agencies concerned with management of the Platte River and, assisted by various computer technologies, to reach some degree of agreement on the “best uses” of the remaining waters of the Platte. Simulation modeling is being used in this effort as a focal point for developing a common understanding of the behavior of the Platte River system, synthesizing existing information, identifying additional needed information, and analyzing the potential consequences of various management alternatives. The NNRC initiated the project in August 1982 by convening a workshop for interested parties in Grand Island, Nebraska. This workshop was devoted to construction of a preliminary simulation model describing the Platte River system. A group of facilitators/modelers from the U.S. Fish and Wildlife Service (FWS) assisted participants in translating their understanding of the Platte River into the framework of the model. In October 1982, FWS personnel began a process of training several people from Nebraska in the use of the model. At that time, minor revisions and corrections were made in the model and various development scenarios were prepared for discussion with participants at a second workshop, which was held in early November 1982. The purpose of this report is to document the status of the PRFF simulation model as of the end of the November 1982 meeting. We emphasize that the intent is not to describe a final product. Except for minor revisions and correction of obvious errors, the model described herein is that which existed at the end of the August workshop. The model contains the foundation for a comprehensive aid to decisionmakers, but at this time it is preliminary in nature, needing refinement and verification before it can be truly useful in analyzing management alternatives. The purpose of this report is to provide a solid foundation for that important future work. The report is divided into three basic parts. The first is a brief overview of the various components of the model and how they fit together. It is intended for those who are not particularly interested in the details of model formulation. The second is a detailed discussion of the logic, assumptions, equations, and data used in constructing the model. This detailed description is also referenced to specific sections of the third part, which is a set of appendices containing listings of the computer code as it presently exists.

Nebraska↗
USGS2018

Potential impacts of projected climate change on vegetation-management strategies in Hawai‘i Volcanoes National Park

Climate change is expected to alter the seasonal and annual patterns of rainfall and temperature in the Hawaiian Islands. Land managers and other responsible agencies will need to know how plant-species habitats will change over the next century in order to manage these resources effectively. This issue is a major concern for resource managers at Hawai‘i Volcanoes National Park (HAVO), where currently managed Special Ecological Areas (SEAs) for important plant species and communities may no longer provide suitable habitats in the future as the climate changes. Expanding invasive-species distributions also may pose a threat to areas where native plants currently predominate. The objective of this project was to combine recent climate-modeling efforts for the state of Hawai‘i with existing models of plant-species distribution in order to forecast suitable habitat ranges under future climate conditions derived from the Coupled Model Intercomparison Project, phase 3 (CMIP3) global circulation model that was dynamically downscaled for the Hawaiian Islands by using the Hawai‘i Regional Climate Model (HRCM). The HRCM uses the A1B emission scenario (a median future climate projection) from the Special Report on Emissions Scenarios (SRES). On the basis of this model, maps showing projected plant-species ranges were generated for four years as snapshots in time (2000, 2040, 2070, 2090) and for three different trajectories of climate change (gradual, linear, rapid) between the present and future. We mapped probabilistic surfaces of suitable habitat for 39 plant species (both native and alien [nonnative]) identified as being of interest to HAVO resource managers. We displayed these surfaces in terms of change relative to present conditions, whether the range of a given plant species was expected to contract, expand, or remain the same in the future. Within HAVO, approximately two-thirds (18 of 29) of the modeled native plant species were projected to contract in range, whereas one-third (11 of 29) were projected to increase. Most of the HAVO SEAs were projected to lose most of the native plant species modeled. Within HAVO, all alien plant species except Lantana camara were projected to contract in range within the park; this trend was observed in most SEAs, including those at low, middle, and high elevations. Congruence was good in the “current” (2000) distribution of plant-species richness and SEA configurations; however, the congruence between species-richness hotspots and SEAs diminished by the projected “end-of-century” (2090) distribution. Over time, the projected species-richness hotspots increasingly occurred outside of the currently configured SEA boundaries.

Hawai'i↗
USGS2020

Minnesota landowners’ trust in their department of natural resources, salient values similarity and wildlife value orientations

Due to extensive land conversion over the last century, much of the native prairie pothole ecosystem has been converted to agricultural or other human uses. The prairie pothole ecosystem is found in the northern plains of Iowa, Minnesota, South Dakota, North Dakota, and Montana. Because most of the land in this region is privately owned and used for agricultural production, most impacts to wildlife habitat are the result of decisions by individual landowners. Landowner trust in natural resource management agencies is important for agencies to effectively accomplish their mission. We measured the nature (competence and fairness) and level of trust that western Minnesota landowners have in the Minnesota Department of Natural Resources (MnDNR) and landowners’ wildlife value orientations (WVO). Landowners rated MnDNR slightly higher in competence than fairness; however, these two dimensions were strongly correlated. We developed a MnDNR trust scale (six items) and a three-cluster model dividing landowners along the MnDNR trust scale, which we named Negative (28%), Neutral (43%), and Positive (29%). We provide evidence supporting the salient values similarity (SVS) model that states people have trust in agencies holding similar values; landowners reporting greater importance for wildlife consideration when making land-use decisions also reported greater trust in the MnDNR. In addition, mutualist landowners had the highest trust in the MnDNR and utilitarian landowners the lowest level of trust, which is opposite of the trust relationship reported for the general public with state wildlife agencies. Based on the SVS model, our results suggest that mutualist landowners perceive greater congruence with MnDNR goals related to wildlife habitat compared to utilitarian landowners.

Minnesota↗
USGS1999

Hydrology of the coastal lowlands aquifer system in parts of Alabama, Florida, Louisiana, and Mississippi

Existing data on water levels, water use, water quality, and aquifer properties were used to construct a multilayer digital model to simulate flow in the aquifer system. The report describes the geohydrologic framework of the aquifer system, and the development, calibration, and sensitivity analysis of the ground-water-flow model, but it is primarily focused on the results of the simulations that show the natural flow of ground water throughout the regional aquifer system and the changes from the natural flow caused by development of ground-water supplies.

Alabama, Florida, Louisiana, Mississippi↗
USGS2012

GEM Basic Building Taxonomy (Version 1.0)

This report documents the development of Global Earthquake Model (GEM) Basic Building Taxonomy and it also provides version 1.0 of this Taxonomy for its immediate application within GEM Physical Risk projects. Criteria for development of the GEM Building Taxonomy required that the Taxonomy be relevant to seismic performance of different construction types; be comprehensive yet simple; be collapsible; be adhering to principles that are familiar to the range of users; and ultimately be extensible to non-buildings and other hazards. The taxonomy is organized as a series of expandable tables, which contain information pertaining to various building attributes. Each attribute describes a specific characteristic that could potentially affect the seismic performance of a building. This report describes the structure and the content of the Basic Building Taxonomy, which consists of eight basic attributes, in detail. These attributes were selected after a series of interactions/discussions with all the GEM Physical Risk Global Component project teams. In addition, we also tried to gather feedback from a number of participants outside the GEM Risk Consortium group. The Basic Taxonomy attributes discussed in this report are: material; lateral load-resisting system; roof; floor; building height; date of construction; structural irregularity, and occupancy. A future Detailed Building Taxonomy will provide more details related to certain aforementioned attributes in the Basic Building Taxonomy. As well, it will also include additional attributes that are necessary for assessing building vulnerability using analytical procedures. The report also illustrates the practical use of the proposed GEM Basic Building Taxonomy by discussing example case studies, wherein the building-specific characteristics are mapped directly using GEM Taxonomic attributes and a simple taxonomic string is constructed for that building. The building taxonomy data model is highly flexible and it can be easily incorporated within the relational database architecture. Due to its ability to represent building typologies using a shorthand form, it is also possible to use this taxonomy for non-database applications. Key terms in the taxonomy are explained in an online glossary, which provides both text and graphic descriptions for the attributes and their details.

Report↗
USGS2003

A Framework for Long-term Ecological Monitoring in Olympic National Park: Prototype for the Coniferous Forest Biome

This report is the result of a five-year collaboration between scientists of the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, Olympic Field Station, and the natural resources staff of Olympic National Park to develop a comprehensive strategy for monitoring natural resources of Olympic National Park. Olympic National Park is the National Park Serviceʼs prototype monitoring park, representing parks in the coniferous forest biome. Under the umbrella of the National Park Serviceʼs prototype parks program, U.S. Geological Survey and Olympic National Park staffs are obligated to: develop strategies and designs for monitoring the long-term health and integrity of national park ecosystems with a significant coniferous forest component. design exportable monitoring protocols that can be used by other parks within the coniferous forest biome (i.e., parks having similar environments), and create a demonstration area and ʻcenter of excellenceʼ for assisting other parks in developing ecological monitoring programs. Olympic National Park is part of the North Coast and Cascades Network, a network of seven Pacific Northwestern park units created recently by the National Park Serviceʼs Inventory and Monitoring Program to extend the monitoring of ʻvital signsʼ of park health to all National Park Service units. It is our intent and hope that the monitoring strategies and conceptual models described here will meet the overall purpose of the prototype parks monitoring program in proving useful not only to Olympic National Park, but also to parks within the North Coast and Cascades Network and elsewhere. Part I contains the conceptual design and sampling framework for the prototype long-term monitoring program in Olympic National Park. In this section, we explore key elements of monitoring design that help to ensure the spatial, ecological, and temporal integration of monitoring program elements and discuss approaches used to design an ecosystem-based monitoring program. Basic monitoring components include ecosystem drivers, (e.g., climate, atmospheric inputs, human pressures), indicators of ecosystem integrity (e.g., biogeochemical indicators), known threats (e.g., impacts of introduced mountain goats), and focal or ʻkeyʼ species (e.g., rare or listed species, Roosevelt elk). Monitoring system drivers and key indicators of ecosystem integrity provide the long-term baseline needed to judge what constitutes ʻunnaturalʼ variation in park resources and provide the earliest possible warning of unacceptable change. Monitoring effects of known threats and the status of focal species will provide information useful to park managers for dealing with current park issues. In Part I we describe the process of identifying potential indicators of ecological condition and present conceptual models of park ecosystems. In addition we report results from several workshops held in conjunction with Olympic National Park aimed at identifying potential indicators of change in the parkʼs ecosystem. First, we describe the responses of Olympic National Park staff to the generic question, “What is the most important resource to monitor in Olympic National Park and why?” followed by the responses from resource and land managers from areas adjoining the park. We also catalogue the responses of various expert groups that we asked to help identify the most appropriate system drivers and indicators of change in the Olympic National Park ecosystems. Results of the workshops provided the justification for selecting basic indicators of ecosystem integrity, effects of current threats to park resources, and focal resources of parks to detect both the currently evident and unforeseeable changes in park resources. We conclude Part I by exploring several generic statistical issues relevant to monitoring natural resources in Olympic National Park. Specifically we discuss trade-offs associated with sampling extensively versus sampling intensively in smaller geographic regions and describe a conceptual framework to guide development of a generic sampling frame for monitoring. We recommend partitioning Olympic National Park into three zones of decreasing accessibility to maximize monitoring efficiency. We present examples of how the generic sampling frame could be used to help ensure spatial integration of individual monitoring projects. Part II of the report is a record of the potential monitoring questions and indicators identified to date in our workshops. The presentation is organized according to the major system drivers, components, and processes identified in the intermediate-level working model of the Olympic National Park ecosystem. For each component of the park system, we develop the need and justification for monitoring, articulate park management issues, and describe key resources and ecosystem functions. We also present a pictorial conceptual model of each ecological subsystem, identify monitoring questions, and list potential indicators for each monitoring question. We conclude each section by identifying linkages of indicators to other ecological subsystems in our general ecosystem model, spatial and temporal contexts for monitoring (where and how often to monitor), and research and development needs. Part II represents the most current detailed listing of potential indicators—the material for subsequent discussions of monitoring priorities and selection of indicators for protocol development. Collectively, the sections of this report contain a comprehensive list of the important monitoring questions and potential indicators as well as recommendations for designing an integrated monitoring program. In Part I, Chapter 6 we provide recommendations on how to proceed with the important next steps in the design process: establishing priorities among the many possible monitoring questions and indicators, and beginning to research and design effective long-term monitoring protocols.

Information and Technology Report↗
USGS2009

New light on a dark subject: On the use of fluorescence data to deduce redox states of natural organic matter (NOM)

This paper reports the use of excitation-emission matrix fluorescence spectroscopy (EEMS), parallel factor statistical analysis (PARAFAC), and oxidation-reduction experiments to examine the effect of redox conditions on PARAFAC model results for aqueous samples rich in natural organic matter. Fifty-four aqueous samples from 11 different geographic locations and two plant extracts were analyzed untreated and after chemical treatments or irradiation were used in attempts to change the redox status of the natural organic matter. The EEMS spectra were generated and modeled using a PARAFAC package developed by Cory and McKnight (2005). The PARAFAC model output was examined for consistency with previously reported relations and with changes expected to occur upon experimental oxidation and reduction of aqueous samples. Results indicate the implied fraction of total sample fluorescence attributed to quinone-like moieties was consistent (0.64 to 0.78) and greater than that observed by Cory and McKnight (2005). The fraction of the quinone-like moieties that was reduced (the reducing index, RI) showed relatively little variation (0.46 to 0.71) despite attempts to alter the redox status of the natural organic matter. The RI changed little after reducing samples using zinc metal, oxidizing at high pH with air, or irradiating with a Xenon lamp. Our results, however, are consistent with the correlations between the fluorescence indices (FI) of samples and the ratio of PARAFAC fitting parameters suggested by Cory and McKnight (2005), though we used samples with a much narrower range of FI values.

Aquatic Sciences↗
USGS2021

Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument

Worldwide, billions of people rely on fresh groundwater reserves for their domestic, agricultural and industrial water use. Extreme droughts and excessive groundwater pumping put pressure on water authorities in maintaining sustainable water usage. High-resolution integrated models are valuable assets in supporting them. The Netherlands Hydrological Instrument (NHI) provides the Dutch water authorities with open source modeling software and data. However, NHI integrated groundwater models often require long run times and large memory usage, therefore strongly limiting their application. As a solution, we present a distributed memory parallelization, focusing on the National Hydrological Model. Depending on the level of integration, we show that significant speedups can be obtained up to two orders of magnitude. As far as we know, this is the first reported integrated groundwater parallelization of an operational hydrological model used for national-scale integrated water management and policy making. The parallel model code and data are freely available.

Environmental Software & Modelling↗