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Results for “Environmental Software”

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At least 19 recordsLinked to original sources
USGS2006

Helping Students make the transition from novice learner of ground-water concepts to expert using the Plume Busters software

Environmental and earth science students are novice learners and lack the experience needed to rise to the level of expert. To address this problem we have developed the prototype Plume Busters?? software as a capstone educational experience, in which students take on the role of an environmental consultant. Following a pipeline spill, the environmental consultant is hired by the pipeline owner to locate the resulting plume created by spill and remediate the contaminated aquifer at minimum monetary and time cost. The contamination must be removed from the aquifer before it reaches the river and eventually a downstream public water supply. The software consists of an interactive Java application and accompanying HTML linked pages. The application simulates movement of a plume from a pipeline break throug h a shallow alluvial aquifer towards the river. The accompanying web pages establish the simulated contamination scenario and provide students with background material on ground-water flow and transport principles. To make the role-play more realistic, the student must consider cost and time when making decisions about siting observation wells and wells for the pump-and-treat remediation system.

Journal of Geoscience Education↗
USGS2012

Identifying the decision to be supported: a review of papers from environmental modelling and software

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Leipzig↗
USGS2008

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models ( Smith and Heath, 2001 and Allen et al., 2004 ). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

Ecological Modelling↗
USGS2023

Improving ecological data science with workflow management software

Pressing environmental research questions demand the integration of increasingly diverse and large-scale ecological datasets as well as complex analytical methods, which require specialized tools and resources. Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor- and time-intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies. Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with the targets r package to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers. Although WMS requires familiarity with function-oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales.

Methods in Ecology and Evolution↗
USGS2015

Approaches in highly parameterized inversion—PEST++ Version 3, a Parameter ESTimation and uncertainty analysis software suite optimized for large environmental models

The PEST++ Version 1 object-oriented parameter estimation code is here extended to Version 3 to incorporate additional algorithms and tools to further improve support for large and complex environmental modeling problems. PEST++ Version 3 includes the Gauss-Marquardt-Levenberg (GML) algorithm for nonlinear parameter estimation, Tikhonov regularization, integrated linear-based uncertainty quantification, options of integrated TCP/IP based parallel run management or external independent run management by use of a Version 2 update of the GENIE Version 1 software code, and utilities for global sensitivity analyses. The Version 3 code design is consistent with PEST++ Version 1 and continues to be designed to lower the barriers of entry for users as well as developers while providing efficient and optimized algorithms capable of accommodating large, highly parameterized inverse problems. As such, this effort continues the original focus of (1) implementing the most popular and powerful features of the PEST software suite in a fashion that is easy for novice or experienced modelers to use and (2) developing a software framework that is easy to extend. The PEST++ Version 3 software suite can be compiled for Microsoft Windows®4 and Linux®5 operating systems; the source code is available in a Microsoft Visual Studio®6 2013 solution; Linux Makefiles are also provided. PEST++ Version 3 continues to build a foundation for an open-source framework capable of producing robust and efficient parameter estimation tools for large environmental models.

Techniques and Methods↗
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↗
USGS1991

QuickMAP

QuickMAP, a prototype desktop mapping system (DMS), uses easy to learn, simple to use windows, menus, and dialogues to provide support in natural resources decision-making.

Environmental Software↗
USGS1994

Wilderness monitoring and data management

In the last decade, increased public interest in natural areas has resulted in increased monitoring activity by federal wilderness managers to assess the status of wilderness values. Wilderness values are those large-scale entities of wilderness which comprise, in sum, wilderness character. Data collected through wilderness monitoring must support the maintenance of wilderness values. Wilderness monitoring must include the development of clear data management strategies and provisions for hypothesis testing. Unfortunately, some monitoring programs do not support the status assessment of wilderness values. Often wilderness monitoring programs have neglected even the most rudimentary principles of data management. This paper presents a model for wilderness monitoring, guidelines for data management, and an overview of a PC-compatible wilderness monitoring data base, the Monitoring Information Data Analysis System (MIDAS).

Environmental Software↗
USGS2022

Climate matching with the climatchR R package

Climate matching allows comparisons of climatic conditions between different locations to understand location and species range climatic suitability. The approach may be used as part of horizon scanning exercises such as those conducted for invasive species. We implemented the CLIMATCH algorithm into an R package, climatchR . The package allows automated and scripted climate matching exercises across all steps from downloading data to summarizing species climate matches. We also show how climatchR may be used with high-throughput computing to process many species. For example, we were able to calculate climate scores for over 8,000 species in less than 3 days using this package. This automation allows high-throughput processing of species data, a new development for improving the efficiency and speed of climate matching and horizon scanning.

Environmental Software & Modeling↗
USGS2023

Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees

Anthropogenic hydrologic alteration threatens the health of riverine ecosystems. Machine learning algorithms that employ the use of model trees to predict hydrologic alteration are underrepresented in related literature. This study assesses hydrologic alteration in the Pearl and Pascagoula River basins using modeled daily streamflow . Hydrologic alteration was determined by hypothesis testing and the computation of the net change across 60 years. Cubist models were developed for both basins to predict hydrologic alteration and to identify important basin characteristics. Results from net change and the hypothesis test indicated the basins were essentially identical with respect to the amount of hydrologic alteration. Cubist models for the basins successfully made accurate predictions of hydrologic alteration and demonstrated that the importance of basin geomorphology and land cover on alteration differed in both basins. The results of the study demonstrate the feasibility of model trees in assessing hydrologic alteration.

Mississippi↗
USGS2018

Geologic map of the Nepenthes Planum Region, Mars

This map product contains a map sheet at 1:1,506,000 scale that shows the geology of the Nepenthes Planum region of Mars, which is located between the cratered highlands that dominate the southern hemisphere and the less-cratered sedimentary plains that dominate the northern hemisphere. The map region contains cone- and mound-shaped landforms as well as lobate materials that are morphologically similar to terrestrial igneous or mud vents and flows. This map is part of an informal series of small-scale (large-area) maps aimed at refining current understanding of the geologic units and structures that make up the highland-to-lowland transition zone. The map base consists of a controlled Thermal Emission Imaging System (THEMIS) daytime infrared image mosaic (100 meters per pixel resolution) supplemented by a Mars Orbiter Laser Altimeter (MOLA) digital elevation model (463 meters per pixel resolution). The map includes a Description of Map Units and a Correlation of Map Units that describes and correlates units identified across the entire map region. The geologic map was assembled using ArcGIS software by Environmental Systems Research Institute ( http://www.esri.com ). The ArcGIS project, geodatabase, base map, and all map components are included online as supplemental data.

Scientific Investigations Map↗
USGS2010

Bringing modeling to the masses: A web based system to predict potential species distributions

Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.

Future Internet↗
USGS2012

Approaches in highly parameterized inversion: TSPROC, a general time-series processor to assist in model calibration and result summarization

The TSPROC ( T ime S eries PROC essor) computer software uses a simple scripting language to process and analyze time series. It was developed primarily to assist in the calibration of environmental models. The software is designed to perform calculations on time-series data commonly associated with surface-water models, including calculation of flow volumes, transformation by means of basic arithmetic operations, and generation of seasonal and annual statistics and hydrologic indices. TSPROC can also be used to generate some of the key input files required to perform parameter optimization by means of the PEST ( P arameter EST imation) computer software. Through the use of TSPROC, the objective function for use in the model-calibration process can be focused on specific components of a hydrograph.

Techniques and Methods↗
USGS2020

Approaches to highly parameterized inversion: PEST++ Version 5, a software suite for parameter estimation, uncertainty analysis, management optimization and sensitivity analysis

PEST++ Version 5 extends and enhances the functionality of the PEST++ Version 3 software suite, providing environmental modeling practitioners access to updated Version 3 tools as well as new tools to support decision making with environmental models. Version 5 of PEST++ includes tools for global sensitivity analysis (PESTPP-SEN); least-squares parameter estimation with integrated first-order, second-moment parameter and forecast uncertainty estimation (PESTPP-GLM); an iterative, localized ensemble smoother (PESTPP-IES); and a tool for management optimization under uncertainty (PESTPP-OPT). Additionally, all PEST++ Version 5 tools have a built-in fault-tolerant, multithreaded parallel run manager and are model independent, using the same protocol as the widely used PEST software suite. PEST++ Version 5 is consistent with PEST++ Version 3 conventions and design philosophy. The software’s emphasis continues to target efficient and optimized algorithms that have proven beneficial in decision-support settings and can accommodate large, highly parameterized problems. Expanded and new capabilities are now available to express uncertainty using Monte Carlo and analytical uncertainty approaches and allow evaluation of thousands to millions of parameters. New management optimization capabilities in Version 5 also allow environmental models to be used to answer management questions using multiple societal constraints in a risk-based framework. The PEST++ Version 5 software suite can be compiled for Microsoft Windows® and Unix-based operating systems such as Apple and Linux®; the source code is available with a Microsoft Visual Studio® 2019 solution; and CMake support for all three operating system is also provided. PEST++ Version 5 continues to build a foundation for an open-source framework capable of producing model-independent, robust, and efficient decision-support tools for large environmental models. The functionality of each of the PEST++ tools are demonstrated on a simple example problem. Implications of decisions used when using the PEST++ suite tools are also discussed.

Techniques and Methods↗
USGS2005

Acute toxicity value extrapolation with fish and aquatic invertebrates

Assessment of risk posed by an environmental contaminant to an aquatic community requires estimation of both its magnitude of occurrence ( exposure ) and its ability to cause harm ( effects ). Our ability to estimate effects is often hindered by limited toxicological information. As a result, resource managers and environmental regulators are often faced with the need to extrapolate across taxonomic groups in order to protect the more sensitive members of the aquatic community. The goals of this effort were to 1) compile and organize an extensive body of acute toxicity data, 2) characterize the distribution of toxicant sensitivity across taxa and species, and 3) evaluate the utility of toxicity extrapolation methods based upon sensitivity relations among species and chemicals. Although the analysis encompassed a wide range of toxicants and species, pesticides and freshwater fish and invertebrates were emphasized as a reflection of available data. Although it is obviously desirable to have high-quality acute toxicity values for as many species as possible, the results of this effort allow for better use of available information for predicting the sensitivity of untested species to environmental contaminants. A software program entitled “Ecological Risk Analysis” (ERA) was developed that predicts toxicity values for sensitive members of the aquatic community using species sensitivity distributions. Of several methods evaluated, the ERA program used with minimum data sets comprising acute toxicity values for rainbow trout, bluegill, daphnia, and mysids provided the most satisfactory predictions with the least amount of data. However, if predictions must be made using data for a single species, the most satisfactory results were obtained with extrapolation factors developed for rainbow trout (0.412), bluegill (0.331), or scud (0.041). Although many specific exceptions occur, our results also support the conventional wisdom that invertebrates are generally more sensitive to contaminants than fish are.

Archives of Environmental Contamination and Toxico↗
USGS2003

Use of retrospective data to assess ecotoxicological monitoring needs for terrestrial vertebrates residing in Atlantic coast estuaries

The “Contaminant Exposure and Effects–Terrestrial Vertebrates” (CEE-TV) database contains 4,336 records of ecotoxicological information for free-ranging amphibians, reptiles, birds, and mammals residing in Atlantic and Florida Gulf coast estuaries and their drainages. To identify spatial data gaps, those CEE-TV records for which the specific study location were known ( n =2,740) were combined with watershed and wildlife management unit boundaries using Geographic Information Systems software. The US Environmental Protection Agency's Index of Watershed Indicators (IWI), which classifies watersheds based on water quality and their vulnerability to pollution, was used to prioritize these data gaps. Of 136 watersheds in the study area, 15 that are classified by the IWI as having water quality problems or high vulnerability to pollution lacked terrestrial vertebrate ecotoxicological monitoring or research in the past decade. Older studies within some of these watersheds documented high levels of contaminants in wildlife tissues. Of 90 National Wildlife Refuge units, 42 without current data fall within watersheds of concern. Of 40 National Park units larger than 1 km 2 , 17 without current data fall within watersheds of concern. Issues encountered in this analysis highlighted the need for spatially and temporally replicated field monitoring programs that utilize random sampling. Without data from such studies, it will be difficult to perform unbiased assessments of regional trends in contaminant exposure and effects in terrestrial vertebrates.

Ecotoxicology↗
USGS2017

Bedrock and structural geologic maps of eastern Candor Sulci, western Ceti Mensa, and southeastern Ceti Mensa, Candor Chasma, Valles Marineris region of Mars

This map product contains a set of three 1:18,000-scale maps showing the geology and structure of study areas in the western Candor Chasma region of Valles Marineris, Mars. These maps are part of an informal series of large-scale maps and map-based topical studies aimed at refining current understanding of the geologic history of western Candor Chasma. The map bases consist of digital elevation models and orthorectified images derived from High Resolution Imaging Science Experiment (HiRISE) data. These maps are accompanied by geologic cross sections, colorized elevation maps, and cutouts of HiRISE images showing key superposition relations. Also included in this product is a Correlation of Map Units that integrates units across all three map areas, as well as an integrated Description of Map Units and an integrated Explanation of Map Symbols. The maps were assembled using ArcGIS software produced by Environmental Systems Research Institute (http://www.esri.com). The ArcGIS projects and databases associated with each map are included online as supplemental data.

Scientific Investigations Map↗