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DOE OSTI2023

HarDWR - Cumulative Water Rights Curves

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. This product is the dataset used as input to the WBM model (Grogan et al., in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (submission pending). This database contains 1,744 individual .csv files, two for each Water Management Area (WMA; see here) in the 11-state region. File naming convention: WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either S for surface water rights, or G for groundwater rights. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the ### unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al., in review)

Economics↗

DOE OSTI2024

Data for Grogan et al. "Bringing Hydrologic Realism to Water Markets"

This data set provides model output and post-processing files required to reproduce the results, tables, and figures in the paper "Bringing Hydrologic Realism to Water Markets" by Grogan et al. (in review). Other input data used in this study includes: Lisk, M., Grogan, D., Zuidema, S., Caccese, R., Peklak, D., Zheng, J., Fisher-Vanden, K., Lammers, R., Olmstead, S., & Fowler, L. (2023). Harmonized Database of Western U.S. Water Rights (HarDWR) (Version v1) [Data set]. MSD-LIVE Data Repository. https://doi.org/10.57931/2205619 Two models were used in this study: (1) The University of New Hampshire Water Balance Model WBM, and (2) a Water Market Model. Market model code and model output post-processing code that make use of these data can be found here Model output files are: 1. WBM output files: scenario[x]_wbm_output.zip Where [x] is one of 1, 2, 2a, 3, and 3a Each zipped directory contains 7 gridded NetCDF files, each reporting the 10-year annual average value of a given variable, in units of average mm/day: File Name: wbm_indUseGross_yc.nc; Description: Water withdrawals by industry (part of the urban sector) File Name: wbm_domUseGross_yc.nc; Description: Water withdrawals by the domestic sector (part of the urban sector) File Name: wbm_irrigationGross_yc.nc; Description: Water withdrawals for agriculture File Name: wbm_irrigationExtra_yc.nc; Description: Water withdrawals from unsustainable groundwater for agriculture File Name: wbm_indUseEvap_yc.nc; Description: Consumptive water use by industry File Name: wbm_domUseEvap_yc.nc; Description: Consumptive water use by the domestic sector File Name: wbm_irrigationNet_yc.nc; Description: Consumptive water use by agriculture The file full_cell_area.nc gives the area of each grid cell in km2, which is used for converting water depth to water volume. 2. Water market model output & post processing output Folder: marketTrdSummaries/ Description: Files in this folder are used as input to code 1_WelfareCalculation_actual_trades.R. They summarize historical water right trade transactions in each state. File Name: welfare_gain_by_state_sector.csv; Description: Welfare gains by state and sector, as shown in Figure 3F. Used in code Figure3.R and produced (as a .xlsx file) by code 2_DemandCurves_simulated_trades.R File Name: welfare_data_actual.rdata; Description: welfare gains by WMA from actual historical trades, as shown in Figure 3A. This data is the output of code 1_WelfareCalculation_actual_trades.R File Name: welfare_summary_simulated.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 1. Produced by code 2_DemandCurves_simulated_trades.R, and used in code 4_WelfareCalculation.R. File Name: welfare_summary_cutoffs.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 2. Produced by code 3_DemandCurves_simulated_trades_cutoffs.R, and used in code 4_WelfareCalculation.R. File Name: welfare_summary_cutoffs_SGMS.xlsx; Description: Welfare gains by state as simulated by the market model in Scenario 2a. Produced by code 3_DemandCurves_simulated_trades_cutoffs.R, and used in code 4_WelfareCalculation.R. File Name: welfare_data_actual.rdata; Description: Spatial data, actual historical welfare gains by WMA as shown in Figure 3A. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated.rdata; Description: Spatial data, simulated Scenario 1 welfare gains by WMA as shown in Figure 3B. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated_cutoffs.rdata; Description: Spatial data, simulated Scenario 2 welfare gains by WMA. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. File Name: welfare_data_simulated_cutoffs_SGMA.rdata; Description: Spatial data, simulated Scenario 2a welfare gains by WMA. Produced by code 4_WelfareCalculation.R and used by code Figure3.R. Additional files are provided for efficient reproduction of tables and figures. These include: File Name: wma_thresold_dates_Scenario2(a).csv; Description: Wet vs. paper right threshold dates for each WMA. Shown in Figure 2A,B. Produced and used by code calculate_thresolds_Figure2.R File Name: WWRTradeBounds (directory); Description: Trade boundary shapefile required to reproduce Figure 3A-D. Used in code Figure3.R File Name: welfare_region_totals.csv; Description: Welfare gains for the entire study region, as shown in Figure 3E. Used in code Figure3.R File Name: Welfare_gain_by_state_sector.csv; Description: Welfare gains by state and sector, as shown in Figure 3F. Used in code Figure3.R and produced (as a .xlsx file) by code 2_DemandCurves_simulated_trades.R File Name: WECC_MERIT_5min_v3b_mask.nc; Description: Gridded file that identified which land grid cells are in the WBM model domain, used for processing in code Figure4.py File Name: Table_1.csv; Description: All data in Table 1, reproducible from WBM output files using code table_1.R

Economics↗

DOE OSTI2024

HarDWR - Cumulative Water Rights Curves

Economics↗

DOE OSTI2020

HarDWR - Cumulative Water Rights Curves

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on Harmonized Water Rights Records v2.0 sourced from WestDAAT - Added "Unspecified" was a water source category, and files associated with this category v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description This product an updated version of the database used as input to the WBM model (Grogan et al. in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (2024). This database contains 2,667 individual .csv files, three for each Water Management Area (WMA) in the 11-state region. File Naming WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either "S" for surface water rights, "G" for groundwater rights, or "U" for unspecified. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the [###] unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al. in review) 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 the study region. 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 second index in this object, the data for California will also be in the second index for each accompanying list. wmasRightsPersGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for groundwater. wmasRightsPersSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for surface water. wmasRightsPersUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for water from an unspecified source. wmasRightsTotsGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for groundwater. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for surface water. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for water from an unspecified source. This object is provided for convenience to check out original total values, if desired. wmaIDByState: A list of data frames which contain the by state allocation by WMA matrix. There is a matrix for each state in a different data frame within the object.

Economics↗

DOE OSTI2025

Tethys Water Demand Data

U.S. water demand varies sharply by sector and region as land use, population, weather patterns, and economic activity co-evolve. High-resolution water demand data is required to capture these dynamics, support integrated energy-water-land modeling, and local-to-regional water scarcity assessments. This dataset contains gridded (1/8 degree), monthly, multi-sector water demand dataset for the contiguous United States (CONUS) covering 1980-2100 across eight future scenarios of human-Earth system change. The dataset covers irrigation, thermoelectric, municipal (public-supply and domestic), livestock, manufacturing, and mining demands, separately for withdrawals and consumption, and includes per-cell renewable vs. non-renewable water source attributions. The dataset is validated against the latest USGS 2010-2020 water-use data for the three largest water demand sectors (Domestic, Electricity, and Irrigation), with correlations ranging from 0.73-0.95 at the HUC6 scale. The two datasets largely agree on an aggregate basis with per-sector bias falling within +/-7%, but they disagree on the spatial allocation of water with individual HUC6 basins having normalized RMSE from 68-171% and median absolute percent difference from 37-86%. This dataset advances prior global products by combining state-resolved sectoral demands from GCAM-USA, future power-plant siting from the CERF model, and scenario-consistent high-resolution climate and population forcing data across the eight scenarios.

GCAM-USA↗

DOE OSTI2022

Genome assembly PYCC 8100

The yeast Torulaspora delbrueckii is gaining importance for biotechnology due to its ability to increase wine sensorial complexity and for enhancing pre-frozen bread dough leavening. However, little is known about its population structure, and variation in gene content, or possible domestication routes have not been investigated. Here, we address these issues and update the circumscription of T. delbrueckii, which is composed of five major clades. Among the three European clades, a lineage associated with the wild arboreal niche is sister to the two other lineages that are linked with anthropic environments, one to wine fermentations and the other one to diverse sources including dairy products and bread dough (Mix- Anthropic clade). Using 62 genomes we identified 5629 genes in the pangenome of T. delbrueckii and 270 genes in the cloud genome. A pangenome tree analysis showed that wine strains have a genome composition were more similar to European wild arboreal strains than to those of the Mix Anthropic clade, in contradiction with the phylogenetic analysis. An association of gene content and ecology gave further support to the hypothesis that the Mix - Anthropic clade has the most specialized genome content and indicated that some of the exclusive genes were implicated in galactose and maltose utilization. More detailed analyses traced the acquisition of a cluster of GAL genes in strains associated with dairy products and the expansion and functional diversification of MAL genes in strains isolated from bread dough. Contrary to S. cerevisiae, domestication in T. delbrueckii is not primed by alcoholic fermentation and appears to be a recent event.

Sampaio, Jose P.↗

NASA NTRS1971

Environmental impact statement for Manned Spacecraft Center and White Sands Test Facility

This environment has not only attracted people and increased payrolls, but has also created a broader base for the local economy. The activity of the center was a catalyst to private enterprise and has led to sizeable residential and commercial developments. Adequate treatment of domestic and industrial waste water was maintained. A feasibility study is now being conducted to establish a plan for a coordinated, centerwide plan for advanced treatment of domestic and industrial waste water.

Source record↗

NASA NTRS1971

Effect of altered 'weight' upon animal tolerance to restraint.

The effect of altered weight upon animal tolerance to restraint was determined by simulating various accelerative forces with directed lead weights using restrained and nonrestrained domestic fowl (chickens). Weighting (increased weight) and conterweighting (reduced weight) produced a stressed condition - reduced relative lymphocyte counts, loss of body mass, and/or the development of a disorientation syndrome - in both restrained and nonrestrained (caged only) birds. The animal's tolerance to altered weight appeared to be a function of its body weight. Unrestrained birds were stressed by counterweighting (mean plus or minus standard error) 58.3 plus or minus 41% of their body weight, whereas restrained birds tolerated only 32.2 plus or minus 2.6% reduction in body weight. A training regimen for restrained birds was not effective in improving their tolerance to a reduced weight environment. It was concluded that domestic fowl living in a weightless (space) environment should be restrained minimally and supported by ventrally directed tension equivalent to approximately 50% of their body mass (their weight in a 1 G environment).

Burton, R. R.↗

NASA NTRS1973

Study of quiet turbofan STOL aircraft for short-haul transportation. Volume 6: Systems analysis

A systems analysis of the quiet turbofan aircraft for short-haul transportation was conducted. The purpose of the study was to integrate the representative data generated by aircraft, market, and economic analyses. Activities of the study were to develop the approach and to refine the methodologies for analytic tradeoff, and sensitivity studies of propulsive lift conceptual aircraft and their performance in simulated regional airlines. The operations of appropriate airlines in each of six geographic regions of the United States were simulated. The offshore domestic regions were evaluated to provide a complete domestic evaluation of the STOL concept applicability.

Source record↗

NASA NTRS1972

Current Problems and Issues in Air Freight Rates

Actions of the Civil Aeronautics Board in determining air freight rates are discussed. The tariff filings by domestic airlines for making basic changes in domestic fares and rates are reported. The roles of the carriers and the Civil Aeronautics Board in establishing freight rates are defined. Specific examples of areas of controversy in establishing freight rates are included. Methods for improving the air cargo and freight rate situation are proposed.

Stout, A. R.↗

NASA NTRS1974

Technology transfer - The NASA perspective

Domestic and international NASA technology utilization experiences are described together with prospects for applying technology to problems of local and state governments. Transfer mechanisms used by NASA to introduce new technology in both the private and public sectors of the domestic scene are discussed, and attention is given to experiences gained in a pilot program designed to establish a refined methodology for the transfer of aerospace-developed technology to developing nations. Technical assistance to local and state governments involves applications of NASA experiences to further the constructive involvement of industry.

Carlson, J. M.↗

NASA NTRS1976

Cost/benefit tradeoffs for reducing the energy consumption of the commercial air transportation system

The fuel saving potential and cost effectiveness of numerous operational and technical options proposed for reducing the fuel consumption of the U.S. commercial airline fleet was examined and compared. The impact of the most promising fuel conserving options on fuel consumption, passenger demand, operating costs and airline profits when implemented in the U.S. domestic and international airline fleets was determined. A forecast estimate was made of the potential fuel savings achievable in the U.S. scheduled air transportation system. Specifically, the means for reducing the jet fuel consumption of the U.S. scheduled airlines in domestic and international passenger operations were investigated. A design analysis was made of two turboprop aircraft as possible fuel conserving derivatives of the DC-9-30.

Kraus, E. F.↗

NASA NTRS1978

Photovoltaic village power application: Assessment of the near-term market

The village power application represents a potential market for photovoltaics. The price of energy for photovoltaic systems was compared to that of utility line extensions and diesel generators. The potential domestic demand was defined in both the government and commercial sectors. The foreign demand and sources of funding for village power systems in the developing countries were also discussed briefly. It was concluded that a near term domestic market of at least 12 MW min and a foreign market of about 10 GW exists.

Rosenblum, L.↗

NASA NTRS1978

Photovoltaic water pumping applications: Assessment of the near-term market

Water pumping applications represent a potential market for photovoltaics. The price of energy for photovoltaic systems was compared to that of utility line extensions and diesel generators. The potential domestic demand was defined in the government, commercial/institutional and public sectors. The foreign demand and sources of funding for water pumping systems in the developing countries were also discussed briefly. It was concluded that a near term domestic market of at least 240 megawatts and a foreign market of about 6 gigawatts exist.

Rosenblum, L.↗

NASA NTRS1978

Solar heating and cooling

To emphasize energy conservation and low cost energy, the systems of solar heating and cooling are analyzed and compared with fossil fuel systems. The application of solar heating and cooling systems for industrial and domestic use are discussed. Topics of discussion include: solar collectors; space heating; pools and spas; domestic hot water; industrial heat less than 200 F; space cooling; industrial steam; and initial systems cost. A question and answer period is generated which closes out the discussion.

Bartera, R. E.↗

NASA NTRS1978

Collation of monthly and semiannual reports covering instrumentation at the Decade 80 house in Tucson, Arizona

The Decade 80 solar house, located in Tucson, Arizona, was built to show the use of copper in home building and to demonstrate the use of solar energy to provide space heating and cooling and domestic hot water. The auxiliary energy sources are electrical resistance heating for the domestic hot water and a gas fired boiler for space heating and operation of the absorption air conditioning units. The Semi-Annual report gives an overview of the instrumentation effort with the back-up monthly reports reflecting more detail of the effort that went into the implementation of the data acquisition system.

Source record↗

NASA NTRS1978

An overview of the energy situation

Beginning with a historical review of the domestic pattern of energy usage, the current dependence of the United States upon dwindling petroleum resources is examined. The possible limit of petroleum usage is discussed, and recent oil production trends are presented. Coupling these with projected analyses of OPEC oil productive capability in the early 1980's indicates a serious worldwide as well as American energy problem in the next decade. The need for conservation and rapid development of application of alternative energy resources is discussed including quantitative projections of significant conservation efforts as well as estimates of domestic alternative energy resource capabilities.

Pitts, D. R.↗

NASA NTRS1978

Instrumentation at the Decade 80 solar house in Tucson, Arizona

Modifications, problems and solutions for the instrumentation system that occurred during the period from May through September, 1978, are described. The solar house was built to show the use of copper in home building and to demonstrate the use of solar energy to provide space heating and cooling and domestic hot water. The auxiliary energy sources are electrical resistance heating for the domestic hot water and a gas-fired boiler for space heating and operation of the adsorption air conditioning units.

Source record↗