Results for “work management” — Page 14

NASA NTRS1984

The human role in space. Volume 3: Generalizations on human roles in space

The human role in space was studied. The role and the degree of direct involvement of humans that will be required in future space missions, was investigated. Valid criteria for allocating functional activities between humans and machines were established. The technology requirements, ecnomics, and benefits of the human presence in space were examined. Factors which affect crew productivity include: internal architecture; crew support; crew activities; LVA systems; IVA/EVA interfaces; and remote systems management. The accomplished work is reported and the data and analyses from which the study results are derived are included. The results provide information and guidelines to enable NASA program managers and decision makers to establish, early in the design process, the most cost effective design approach for future space programs, through the optimal application of unique human skills and capabilities in space.

Source record↗

NASA NTRS2018

Managing Variability: A Cognitive Ethnography of the Work of Airline Dispatchers

Airline dispatchers' workflow is often described in broad terms like 'flight planning' and 'flight following'. Such high-level descriptions fail to recognize the number and complexity of tasks involved in these activities. An ethnographic study was conducted at three US airlines to understand the cognitive workload involved in flight planning. Fuel planning was identified as one of five key flight planning tasks. Fuel planning was conducted concurrently with other planning and monitoring tasks which often led to interruptions. Planning fuel was dynamic, with recalculations required whenever other factors varied (e.g., payload, route, alternates). This rework increased workload and opportunities for error while reducing efficiency. Four main factors contributed variability to fuel planning: contingency planning, load planning, pilots, and station operations. Strategies for managing variability included pattern identification, use of buffers, rounding up, and leveraging software tools. Software design often added to workload by forcing dispatchers to attend to low level tasks.

dispatcher↗

NASA NTRS2018

A Concept for Civil Space Traffic Management

As technology has improved, operators have sought to use cubesats, as well as smallsats more generally, to perform increasingly more ambitious and sophisticated functions. Despite this, practical concerns associated with cubesat infant mortality, conjunctions, limited maneuverability, and debris generation have been relatively muted because most cubesats have been launched to lower orbits that limit both their orbital lifetime and consequences should a collision occur. NASA ARC has developed a concept for a highly-automated and distributed space traffic management (STM) architecture, drawing on similar work done to provide traffic management for small unmanned aerial systems (UAS) operating at low altitudes. The system proposes a strategy to accommodate growing space traffic volume safely, as well as pave the way for a transition of civil STM authority to a civilian governmental entity. The architecture envisions an open-access software platform architecture of data and service suppliers, consumers, and regulators, connected via a set of application programming interfaces (APIs). The platform would build on, rather than replicate existing integration and coordination efforts within the space situational awareness ecosystem, using existing standards for data message formats from organizations like the Consultative Committee for Space Data Systems and wrapping, rather than replacing existing integrations. We will present an initial STM architecture in this presentation, with a few examples showing how stakeholders can interact structurally, but flexibly, within this architecture.

Space Situational Awareness↗

NASA NTRS2013

Development of a Universal Waste Management System

NASA is working with a number of commercial companies to develop the next low Earth orbit spacecraft. The hardware volume and weight constraints are similar to or greater than those of the Apollo era. This, coupled with the equally demanding cost challenge of the proposed commercial vehicles, causes much of the Environmental Control and Life Support System (ECLSS) designs to be reconsidered. The Waste Collection System (WCS) is within this group of ECLSS hardware. The development to support this new initiative is discussed within. A WCS concept - intended to be common for all the vehicle platforms currently on the drawing board - is being developed. The new concept, referred to as the Universal Waste Management System (UWMS), includes favorable features from previous designs while improving on other areas on previous Space Shuttle and the existing International Space Station (ISS) WCS hardware, as needed. The intent is to build a commode that requires less crew time, improved cleanliness, and a 75% reduction in volume and weight compared to the previous US ISS/Extended Duration Orbitor WCS developed in the 1990s. The UWMS is most similar to the ISS Development Test Objective (DTO) WCS design. It is understood that the most dramatic cost reduction opportunity occurs at the beginning of the design process. To realize this opportunity, the cost of each similar component between the UWMS and the DTO WCS was determined. The comparison outlined were the design changes that would result with the greatest impact. The changes resulted in simplifying the approach or eliminating components completely. This initial UWMS paper will describe the system layout approach and a few key features of major components. Future papers will describe the UWMS functionality, test results, and components as they are developed.

Stapleton, Thomas J.↗

DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for the Proposed Versatile Test Reactor, Oak Ridge, Tennessee

The US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre (~13,000-ha) Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park (NERP) and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education also represent potential effects of federal actions on the NERP, and impacts on, e.g., deer harvest, must be considered on the Oak Ridge Wildlife Management Area when other aspects of the human environment are affected. The United States currently has no fast neutron testing capability to support advanced nuclear research and development. The proposed Versatile Test Reactor (VTR) will take advantage of current investments by the US government and private industry in nuclear reactors to expedite the design and construction process, using proven technology to create a world-class scientific infrastructure. The VTR will take advantage of fast neutrons provided by this proven technology, along with a capability to rapidly insert, conduct, and remove state-of-the-art experiments. An advantage of the VTR is that it can support future innovations in experimental capabilities without modifying the facility. The VTR will support progress in a variety of science and technology areas, including testing and qualification of advanced reactor fuels; testing and qualification of innovative structural materials; testing of innovative components and instruments; validation of advanced modeling and simulation tools; and versatility for future technical missions. Through proven technology, the VTR can take advantage of existing reactor designs and operating experience to reduce the risk, cost, and time for design and construction. The top available resources of DOE laboratories, industry, and universities will be used to expedite reactor design and construction toward developing the scientific infrastructure that affords a strong testing capability that can be sustained over many years. This report summarizes current knowledge of natural and cultural resources primarily within the VTR construction area. At the time of this report, the proposed VTR site design includes a construction area of ~150.4 acres (~69.9 ha), which contains an ~51.3-acre (~20.8-ha) operations area, located within forested natural areas of the ORR. The primary goal of the work presented here was to evaluate potential effects on sensitive resources that might result from development and construction activities associated with VTR. In addition to on-the-ground surveys during spring and summer 2020 by the ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled from a 2011 forest inventory and supplemented with limited ground observations in 2020. The individuals who obtained and compiled the data presented here are familiar with and routinely assess sensitive resources on the ORR. Anyone who references this report must consider that the timing of surveys did not permit a complete delineation of the resources that will be affected. If the VTR project proceeds, additional surveys will be required to account for the seasonal patterns of various threatened and endangered species. Data deficiencies and potential resources that likely went undetected are indicated where possible. Accordingly, this report should facilitate more environmentally sound decisions during planning and 2 development of the VTR site, provide a foundation for further assessment of sensitive and cultural resources, and help project managers better address regulatory guidance and DOE policies on sustainable development in compliance with, for example, the US Endangered Species Act (ESA), Migratory Bird Treaty Act (MBTA), Tennessee Rare Plant Protection and Conservation Act of 1985, Tennessee Nongame and Endangered or Threatened Wildlife Species Conservation Act of 1974, several federal and state regulations regarding aquatic resource protection, and site-specific policies as outlined in various ORR management plans developed by ORNL and TWRA for DOE.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

Next Steps: Laying the Groundwork for Bundle Protocol v7

Delay/Disruption Tolerant Networking (DTN) is a networking model and protocol suite that extends the terrestrial internet to the challenging communication environments of space. These environments are typically subject to frequent disruptions, which can cause delays or errors. DTN protects data transmission by wrapping data into bundles (similar to Internet Protocol packets), storing them until a connection can be established between two nodes (similar to terrestrial routers or computers), and forwarding them to their destinations. Bundle Protocol (BP) is responsible for generating those bundles and creates the transport layer of DTN, much like how Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) create the transport layer of the Internet Protocol. BPv6 is the current, accepted version of the Bundle Protocol standard. However, recent missions and test implementations have revealed missing components and areas for improvement in the standard. Using lessons learned from NASA missions and gathering inspiration from the Internet Protocol, BPv7 is intended to be a more robust Bundle Protocol that improves upon its predecessor and increases the technology readiness level of the DTN architecture. The DTN Standard Interface Design team, a sub-team of the DTN Infusion Project at the Goddard Space Flight Center, worked to create a dictionary of terms for bundle components and functional decomposition of the protocol. These efforts aided in the standardization of BP interfaces, something missing from BPv6, and supported parallel network management and configuration work. This standardization will ultimately contribute to LunaNet (a lunar communications and navigation architecture that will bring networking, positioning, navigation, timing and science services to the Moon), the Solar System Internet (SSI), and expand crewed and uncrewed space exploration opportunities.

DTN↗

NASA NTRSDate not supplied

Next Steps: Laying the Groundwork for Bundle Protocol v7

Delay/Disruption Tolerant Networking (DTN) is a networking model and protocol suite that extends the terrestrial internet to the challenging communication environments of space. These environments are typically subject to frequent disruptions, which can cause delays or errors. DTN protects data transmission by wrapping data into bundles (similar to Internet Protocol packets), storing them until a connection can be established between two nodes (similar to terrestrial routers or computers), and forwarding them to their destinations. Bundle Protocol (BP) is responsible for generating those bundles and creates the transport layer of DTN, much like how Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) create the transport layer of the Internet Protocol. BPv6 is the current, accepted version of the Bundle Protocol standard. However, recent missions and test implementations have revealed missing components and areas for improvement in the standard. Using lessons learned from NASA missions and gathering inspiration from the Internet Protocol, BPv7 is intended to be a more robust Bundle Protocol that improves upon its predecessor and increases the technology readiness level of the DTN architecture. The DTN Standard Interface Design team, a sub-team of the DTN Infusion Project at the Goddard Space Flight Center, worked to create a dictionary of terms for bundle components and functional decomposition of the protocol. These efforts aided in the standardization of BP interfaces, something missing from BPv6, and supported parallel network management and configuration work. This standardization will ultimately contribute to LunaNet (a lunar communications and navigation architecture that will bring networking, positioning, navigation, timing and science services to the Moon), the Solar System Internet (SSI), and expand crewed and uncrewed space exploration opportunities.

dtn↗

DOE OSTI2025

AmeriFlux US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops). Site Description - US-VT1 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-VT1 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT2) incorporates cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗

DOE OSTI2025

AmeriFlux US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops). Site Description - US-VT2 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest that uses cover crops. US-VT2 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT1) does not incorporate cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗

DOE OSTI2026

AmeriFlux FLUXNET-1F US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops). This is the FLUXNET version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops) produced by applying the standard ONEFlux (1F) software. Site Description - US-VT1 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-VT1 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT2) incorporates cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗

DOE OSTI2026

AmeriFlux FLUXNET-1F US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops). This is the FLUXNET version of the carbon flux data for the site US-VT2 Vermillion Tributary Paired Cropland – Site 2 (Corn/Soy; Cover Crops) produced by applying the standard ONEFlux (1F) software. Site Description - US-VT2 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest that uses cover crops. US-VT2 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT1) does not incorporate cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.

Key, Kesondra [Indiana University - Bloomington]↗

NASA NTRS1985

Training managers for high productivity: Guidelines and a case history

Hughes Aircrafts 13-year productivity study clearly identifies management as the key link in the entire productivity chain. This fact led to the establishment of a long-term series of seminars on personal, managerial, organizational, and operational productivity for all levels and sectors of line and staff management. To inspire the work force to higher levels of productivity and creativity management, itself, must first be inspired. In turn they have to clearly understand the productive and creative processes, fashion an effective productivity improvement plan with sound strategy and implementation, create an optimal environmental chemistry, and provide the outstanding leadership necessary to propel their organizations to achieve full potential. The primary goals of the seminars are to (1) ignite that spark of inspiration, enabling productive action to follow, (2) provide participants a credible roadmap and effective tools for implementation, and (3) develop a dedicated commitment to leadership and productivity throughout the management team.

Ranftl, R. M.↗

NASA NTRS2019

Cloud Governance at Scale

Operating and maintaining a large multi-tenant ecosystem in the cloud requires scalable solutions to unique technical and process challenges. The Cloud Computing model grants significant permissions to development teams that traditionally were reserved for Data-Center Administrators and Supply-Chain Managers. Earthdata Cloud has worked to re-cast traditional data-center management into a sensible cloud-first model. This talk discusses some of our challenges, solutions, and way ahead.

financial controls↗

DOE OSTI2020

Natural Resources Assessment for the SNS Second Target Station, Oak Ridge, Tennessee

The US Department of Energy’s Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education on the National Environmental Research Park represent potential impacts of federal actions. Moreover, federal actions that affect the quantity and quality of hunting opportunities and deer reduction harvest on the Oak Ridge Wildlife Management Area must be considered whenever other aspects of the human environment (as defined by NEPA) are affected. The Spallation Neutron Source (SNS) is a premiere facility at ORNL that provides advanced capabilities in neutron scattering to promote new discoveries and research opportunities in material sciences, physics, chemistry, biological sciences, and others. A conceptual design for a Second Target Station (STS) has been in consideration for several years. The STS is intended to complement and enhance existing ORNL capabilities, notably research and exploration of complex materials. The proposed STS will involve development of existing natural areas on the ORR, which might contain sensitive resources that require mitigation or avoidance in accordance with existing policies and regulation. This report summarizes current knowledge of natural and cultural resources within the STS project area. At the time of this report, the proposed STS project consisted of an operations area comprising 55.4 acres (22.4 ha) and a total review area for potential construction comprising ~224 acres (90.6 ha). The review area is located primarily within forested natural areas of the ORR with minor development in the form of power-line rights-of-way and secondary/graveled roads (Figure 1). The primary goal was to evaluate potential effects on sensitive resources that might result from development of the STS. In addition to onthe-ground surveys during summer 2009 and fall 2019 to summer 2020 by ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled primarily from a 2013 forest inventory effort for Forest Management Compartment 17 and supplemented with limited ground observations in 2019. The individuals who obtained and compiled the data that are presented here are familiar with and routinely assess sensitive resources on the ORR.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a collection of objects stored within an RDate file, stateWaterRightsHarmonized.RData. Each object either describes how one should interact with the other objects, or contains the harmonized water rights data. Here is each object described in detail: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. The column headers for each data frame are: waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. basinNum - The alpha-numeric identifier of the WMA the record belongs to. priorityDate - The priority date associated with the right. allocatedFlow - The maximum flow of the allocation in cubic feet per second (ft3s-1). source - Whether the right is for surface water or groundwater. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. rightsByState_surface: A list of the cleaned surface water rights collected from each state. See rightsByState_ground for more details on how the data is formatted. fullRightsRecs: A list of the combined groundwater and surface water records for each state. Essentially, these lists are the merging of rightsByState_ground and rightsByState_surface by state. See rightsByState_ground for more details on how the data is formatted. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page.

Economics↗

DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to included within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state.

Economics↗

DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two-digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use(s) from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to include within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state. For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. This object holds the the data that is exported to created the xxGroundwaterHarmonizedRights.csv files. rightsByState_surface: A list of data frames with the cleaned surface water rights collected from each state. This object holds the the data that is exported to created the xxSurfaceWaterHarmonizedRights.csv files. fullRightsRecs: A list of the combined groundwater and surface water records for each state. This object holds the the data that is exported to created the xxFullHarmonizedRights.csv files. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page. The code related to the creation of this dataset can be viewed within HarDWR GitHub Repository/dataHarmonization.

Economics↗

NASA NTRS2016

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗