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At least 145 records · Page 8Linked to original sources

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Computers & Geosciences

NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings

Hyperparameter optimization approaches were applied to improve performance and accuracy of groundwater flow models. Freely available new software, NWTOPT, is described that uses Tree of Parzen Estimators (TPE) and Random Search algorithms to optimize MODFLOW-NWTs solver settings. We ran 3500 trials on a steady-state and transient model. To quantify the performance of candidate solver settings, we defined a loss function based on time elapsed and mass balance error of the MODFLOW-NWT forward run. Before optimization the steady- state model ran in ~12 min and the transient model ran in ~5 h with acceptable mass balance error (<1%). After optimization runtimes were reduced to ~2.7 min (steady state) and ~48 min (transient) with errors below 0.1%. In both cases TPE found hyperparameters that resulted in faster running and lower error models than those found by Random Search. The time to complete the optimization trials was also shorter with the TPE algorithm.

Environmental Modelling and Software

UTILIZATION OF GEOGRAPHIC INFORMATION SYSTEMS TECHNOLOGY IN THE ASSESSMENT OF REGIONAL GROUND-WATER QUALITY.

The U. S. Geological Survey (USGS) in cooperation with the U. S. Environmental Protection Agency Office of Pesticide Programs and several State agencies in Oregon has prepared a digital spatial database at 1:500,000 scale to be used as a basis for evaluating the potential for ground-water contamination by pesticides and other agricultural chemicals. Geographic information system (GIS) software was used to assemble, analyze, and manage spatial and tabular environmental data in support of this project. Physical processes were interpreted relative to published spatial data and an integrated database to support the appraisal of regional ground-water contamination was constructed. Ground-water sampling results were reviewed relative to the environmental factors present in several agricultural areas to develop an empirical knowledge base which could be used to assist in the selection of future sampling or study areas.

Conference Paper

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Techniques and Methods

Capture-recapture methodology

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

Book chapter

Effects of carbamazepine to visual function in early life stage fish

The frequent detection of pharmaceuticals and personal care products (PPCPs) in the environment raises concern for aquatic systems. Carbamazepine (CBZ), an antiepileptic drug, is among the most detected PPCP globally, with concentrations in surface water exceeding those that induce toxicity to aquatic organisms. Non-targeted transcriptomic profiling was conducted in zebrafish ( Danio rerio ) larvae exposed to 0, 1, 5, 10, or 50 μg/L CBZ from 2 h post fertilization (hpf) through hatching, and then sampled at 48, 72, or 144 hpf. Transcriptomic profiles were annotated and characterized with in silico bioinformatic software to assess top enriched pathways and identify targets of environmentally relevant concentrations of CBZ and anchor molecular effects to higher levels of biological organization. Based on this analysis, CBZ was predicted to impair visual perception and sensory system development. The number of eye saccades, determined with a visually mediated behavioral assay, optokinetic response, was significantly reduced in 144 hpf larvae exposed to concentrations as low as 1 μg/L CBZ. These results indicate that environmentally relevant concentrations of CBZ may target and impact processes involved in visual function in fish.

Environmental Research

HAZPAC: An interactive map of Pacific Rim natural hazards, population, and infrastructure

This is an online version of a CD-ROM publication. The text files that describe using this publication make reference to software provided on the disc. For this online version the software can be downloaded for free from Adobe Systems and Environmental Systems Research Institute, Inc. (ESRI). Welcome to HAZPAC! HAZPAC is an interactive map about natural hazard risk in the Pacific Rim region. It is intended to communicate to a broad audience the ideas of 'Crowding the Rim,' which is an international, public-private partnership that fosters collaborative solutions for regional risks. HAZPAC, which stands for 'HAZards of the PACific,' uses Geographic Information System (GIS) technology to help people visualize the socioeconomic connections and shared hazard vulnerabilities among Pacific Rim countries, as well as to explore the general nature of risk. Please refer to the 'INTRODUCTION TO HAZPAC' section of the readme file below to determine which HAZPAC project will be right for you. Once you have decided which HAZPAC project is suitable for you, please refer to the 'GETTING STARTED' sections in the readme file for some basic information that will help you begin using HAZPAC. Also, we highly recommend that you follow the Tutorial exercises in the project-specific HAZPAC User Guides. The User Guides are PDF (Portable Document Format) files that must be read with Adobe Acrobat Reader (a free copy of Acrobat Reader is available using the link near the bottom of this page).

Data Series

Revision and product generation software

The U.S. Geological Survey (USGS) developed revision and product generation (RevPG) software for updating digital line graph (DLG) data and producing maps from such data. This software is based on ARC/INFO, a geographic information system from Environmental Systems Resource Institute (ESRI). RevPG consists of ARC/INFO Arc Macro Language (AML) programs, C routines, and interface menus that permit operators to collect vector data using aerial images, to symbolize the data on-screen, and to produce plots and color-separated files for use in printing maps.

Fact Sheet

Bringing Bayesian models to life

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models.

Book

Prediction of lethal/effective concentration/dose in the presence of multiple auxiliary covariates and components of variance

Predictors of the percentile lethal/effective concentration/dose are commonly used measures of efficacy and toxicity. Typically such quantal-response predictors (e.g., the exposure required to kill 50% of some population) are estimated from simple bioassays wherein organisms are exposed to a gradient of several concentrations of a single agent. The toxicity of an agent may be influenced by auxiliary covariates, however, and more complicated experimental designs may introduce multiple variance components. Prediction methods lag examples of those cases. A conventional two-stage approach consists of multiple bivariate predictions of, say, medial lethal concentration followed by regression of those predictions on the auxiliary covariates. We propose a more effective and parsimonious class of generalized nonlinear mixed-effects models for prediction of lethal/effective dose/concentration from auxiliary covariates. We demonstrate examples using data from a study regarding the effects of pH and additions of variable quantities 2???,5???-dichloro-4???- nitrosalicylanilide (niclosamide) on the toxicity of 3-trifluoromethyl-4- nitrophenol to larval sea lamprey (Petromyzon marinus). The new models yielded unbiased predictions and root-mean-squared errors (RMSEs) of prediction for the exposure required to kill 50 and 99.9% of some population that were 29 to 82% smaller, respectively, than those from the conventional two-stage procedure. The model class is flexible and easily implemented using commonly available software. ?? 2007 SETAC.

Environmental Toxicology and Chemistry

Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

Nevada

U.S. Geological Survey spatial data access

The U.S. Geological Survey (USGS) has done a progress review on improving access to its spatial data holdings over the Web. The USGS EROS Data Center has created three major Web-based interfaces to deliver spatial data to the general public; they are Earth Explorer, the Seamless Data Distribution System (SDDS), and the USGS Web Mapping Portal. Lessons were learned in developing these systems, and various resources were needed for their implementation. The USGS serves as a fact-finding agency in the U.S. Government that collects, monitors, analyzes, and provides scientific information about natural resource conditions and issues. To carry out its mission, the USGS has created and managed spatial data since its inception. Originally relying on paper maps, the USGS now uses advanced technology to produce digital representations of the Earth’s features. The spatial products of the USGS include both source and derivative data. Derivative datasets include Digital Orthophoto Quadrangles (DOQ), Digital Elevation Models, Digital Line Graphs, land-cover Digital Raster Graphics, and the seamless National Elevation Dataset. These products, created with automated processes, use aerial photographs, satellite images, or other cartographic information such as scanned paper maps as source data. With Earth Explorer, users can search multiple inventories through metadata queries and can browse satellite and DOQ imagery. They can place orders and make payment through secure credit card transactions. Some USGS spatial data can be accessed with SDDS. The SDDS uses an ArcIMS map service interface to identify the user’s areas of interest and determine the output format; it allows the user to either download the actual spatial data directly for small areas or place orders for larger areas to be delivered on media. The USGS Web Mapping Portal provides views of national and international datasets through an ArcIMS map service interface. In addition, the map portal posts news about new map services available from the USGS, many simultaneously published on the Environmental Systems Research Institute Geography Network. These three information systems use new software tools and expanded hardware to meet the requirements of the users. The systems are designed to handle the required workload and are relatively easy to enhance and maintain. The software tools give users a high level of functionality and help the system conform to industry standards. The hardware and software architecture is designed to handle the large amounts of spatial data and Internet traffic required by the information systems. Last, customer support was needed to answer questions, monitor e-mail, and report customer problems.

Journal of Geospatial Engineering

OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features

The National Hydrography Dataset (NHD) is a foundational geospatial data source in the United States that enables extensive and diverse environmental research and supports decision-making in numerous contexts. However, the NHD requires regular validation and update given possible inconsistent initial collection and hydrographic changes. Furthermore, systems or tools that use NHD data must manage regular updates that occur within the high-resolution version of the NHD (NHD HR). This research contributes to filling this gap by establishing an open-source software tool named OpenCLC, which automatically identifies matching and mismatching line features between two sets of hydrographic flowlines. Aside from identifying differences among two version of NHD lines, results can be applied to improve the quality of NHD HR content. OpenCLC significantly outperforms the best available commercial off-the-shelf software in computational scalability, and it is made widely available as part of the CyberGIS Toolkit to benefit broad environmental and geospatial science communities.

SoftwareX

Social.Water - A crowdsourcing tool for environmental data acquisition

Remote telemetry has a long history of use for collection of environmental measurements. With the rise of mobile phones and SMS text-messaging capacity, many members of the general pubic carry communications equipment in their pockets at all times. Enabling the general public to provide environmental data through text messages has the potential both to provide additional data to scientific projects and also to raise awareness of the projects through participation. Hydrologic measurements – some of which can be made without training, involve a single measurement, and are often made in rural areas – are well-suited to text-message conveyance. Many other environmental measurements are similarly well-suited for this technology. Social.Water is a software package, written in Python, that collects, parses, and categorizes text messages sent to a dedicated phone number, updates a simple database, and posts both graphical results and the database on the Web. Social.Water was designed as the backend to the Crowdhydrology project and is written in an object-oriented design that makes customization and modification straightforward.

Computers & Geosciences

An Overview of the GIS Weasel

This fact sheet provides a high-level description of the GIS Weasel, a software system designed to aid users in preparing spatial information as input to lumped and distributed parameter environmental simulation models (ESMs). The GIS Weasel provides geographic information system (GIS) tools to help create maps of geographic features relevant to the application of a user?s ESM and to generate parameters from those maps. The operation of the GIS Weasel does not require a user to be a GIS expert, only that a user has an understanding of the spatial information requirements of the model. The GIS Weasel software system provides a GIS-based graphical user interface (GUI), C programming language executables, and general utility scripts. The software will run on any computing platform where ArcInfo Workstation (version 8.1 or later) and the GRID extension are accessible. The user controls the GIS Weasel by interacting with menus, maps, and tables.

Fact Sheet

Watershed boundaries and digital elevation model of Oklahoma derived from 1:100,000-scale digital topographic maps

This document provides a general description of the procedures used to develop the data sets included on this compact disc. This compact disc contains watershed boundaries for Oklahoma, a digital elevation model, and other data sets derived from the digital elevation model. The digital elevation model was produced using the ANUDEM software package, written by Michael Hutchinson and licensed from the Centre for Resource and Environmental Studies at The Australian National University. Elevation data (hypsography) and streams (hydrography) from digital versions of the U.S. Geological Survey 1:100,000-scale topographic maps were used by the ANUDEM package to produce a hydrologically conditioned digital elevation model with a 60-meter cell size. This digital elevation model is well suited for drainage-basin delineation using automated techniques. Additional data sets include flow-direction, flow-accumulation, and shaded-relief grids, all derived from the digital elevation model, and the hydrography data set used in producing the digital elevation model. The watershed boundaries derived from the digital elevation model have been edited to be consistent with contours and streams from the U.S. Geological Survey 1:100,000-scale topographic maps. The watershed data set includes boundaries for 11-digit Hydrologic Unit Codes (watersheds) within Oklahoma, and 8-digit Hydrologic Unit Codes (cataloging units) outside Oklahoma. Cataloging-unit boundaries based on 1:250,000-scale maps outside Oklahoma for the Arkansas, Red, and White River basins are included. The other data sets cover Oklahoma, and where available, portions of 1:100,000-scale quadrangles adjoining Oklahoma.

Oklahoma

Development of the Hydroecological Integrity Assessment Process for Determining Environmental Flows for New Jersey Streams

The natural flow regime paradigm and parallel stream ecological concepts and theories have established the benefits of maintaining or restoring the full range of natural hydrologic variation for physiochemical processes, biodiversity, and the evolutionary potential of aquatic and riparian communities. A synthesis of recent advances in hydroecological research coupled with stream classification has resulted in a new process to determine environmental flows and assess hydrologic alteration. This process has national and international applicability. It allows classification of streams into hydrologic stream classes and identification of a set of non-redundant and ecologically relevant hydrologic indices for 10 critical sub-components of flow. Three computer programs have been developed for implementing the Hydroecological Integrity Assessment Process (HIP): (1) the Hydrologic Indices Tool (HIT), which calculates 171 ecologically relevant hydrologic indices on the basis of daily-flow and peak-flow stream-gage data; (2) the New Jersey Hydrologic Assessment Tool (NJHAT), which can be used to establish a hydrologic baseline period, provide options for setting baseline environmental-flow standards, and compare past and proposed streamflow alterations; and (3) the New Jersey Stream Classification Tool (NJSCT), designed for placing unclassified streams into pre-defined stream classes. Biological and multivariate response models including principal-component, cluster, and discriminant-function analyses aided in the development of software and implementation of the HIP for New Jersey. A pilot effort is currently underway by the New Jersey Department of Environmental Protection in which the HIP is being used to evaluate the effects of past and proposed surface-water use, ground-water extraction, and land-use changes on stream ecosystems while determining the most effective way to integrate the process into ongoing regulatory programs. Ultimately, this scientifically defensible process will help to quantify the effects of anthropogenic changes and development on hydrologic variability and help planners and resource managers balance current and future water requirements with ecological needs.

Scientific Investigations Report

The influence of coarse-scale environmental features on current and predicted future distributions of narrow-range endemic crayfish populations

1.A major limitation to effective management of narrow-range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2.Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate-change scenarios. 3.The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 6587% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4.Current models created using two spatial resolutions (1 and 4.5km2) showed that fine-resolution data more accurately represented current distributions. For three of the four species, the 1-km2 resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1-km2 resolution models were more accurate than 4.5-km2 resolution models. 5.Future projected (4.5-km2 resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low-emission scenario, whereas two of four species would be severely restricted in range under moderatehigh emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species-distribution models. 6.These model predictions illustrate possible impacts of climate change on narrow-range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.

Freshwater Biology