Water Inventory Data Collection Form
Part of a series of 34 energy efficiency checklists, data collection forms, and how-to guides, the Water Inventory Data Collection Form facilitates data entry.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
SEARCH · Search NASA
Results for “water inventory data”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Ground water use inventory in Minnesota using LANDSAT data
An irrigation ground water use inventory in Sherburne County, Minnesota, was attempted by indirectly locating irrigation wells by determining the location of irrigated lands. Digital classification of LANDSAT MSS imagery was employed using the IDIMS at Goddard Space Flight Center. Single-date classification proved moderately successful after accurate ground truth data were obtained. A combination of supervised and unsupervised classification was used. Multitemporal analysis using August 10 and May 21, 1978 imagery was also attempted. This unsupervised classification proved most successful in identifying crops and irrigated fields.
Beissel, D. R.↗
The ten-ecosystem study investigation plan
With the continental United States divided into ten forest and grassland ecosystems, the Ten Ecosystem Study (TES) is designed to investigate the feasibility and applicability of state-of-the-art automatic data processing remote sensing technology to inventory forest, grassland, and water resources by using Land Satellite data. The study will serve as a prelude to a possible future nationwide remote sensing application to inventory forest and rangeland renewable resources. This plan describes project design and phases, the ten ecosystem, data utilization and output, personnel organization, resource requirements, and schedules and milestones.
Kan, E. P.↗
Uncertainty analysis on reactivity and discharged inventory for a pressurized water reactor fuel assembly due to {sup 235,238}U nuclear data uncertainties
This paper discusses the uncertainty analysis on reactivity and inventory for a typical PWR fuel element as a result of uncertainties in {sup 235,238}U nuclear data. A typical Westinghouse 3-loop fuel assembly fuelled with UO{sub 2} fuel with 4.8% enrichment has been selected. The Total Monte-Carlo method has been applied using the deterministic transport code DRAGON. This code allows the generation of the few-groups nuclear data libraries by directly using data contained in the nuclear data evaluation files. The nuclear data used in this study is from the JEFF3.1 evaluation, and the nuclear data files for {sup 238}U and {sup 235}U (randomized for the generation of the various DRAGON libraries) are taken from the nuclear data library TENDL. The total uncertainty (obtained by randomizing all {sup 238}U and {sup 235}U nuclear data in the ENDF files) on the reactor parameters has been split into different components (different nuclear reaction channels). Results show that the TMC method in combination with a deterministic transport code constitutes a powerful tool for performing uncertainty and sensitivity analysis of reactor physics parameters. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary
Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.
Castruccio, P. A.↗
The development of a land use inventory for regional planning using satellite imagery
Water quality planning in Ohio, Kentucky, and Indiana is reviewed in terms of use of land use data and satellite imagery. A land use inventory applicable to water quality planning and developed through computer processing of LANDSAT-1 imagery is described.
Hessling, A. H.↗
The use of Landsat digital data to detect and monitor vegetation water deficiencies
In the Large Area Crop Inventory Experiment a technique was devised using a vector transformation of Landsat digital data to indicate when vegetation is undergoing moisture stress. A relation was established between the remote-sensing-based criterion (the Green Index Number) and a ground-based criterion (Crop Moisture Index).
Thompson, D. R.↗
Practical applications of Landsat data
Some practical applications of Landsat MSS and TM data are discussed, including renewable resource inventory and monitoring; water resources inventory and assessment; and urban land use analysis. Consideration is also given to the geological applications of Landsat MSS and TM data. These applications include: mapping major geological units; rock-type recognition; mapping volcanic surface deposits; and mapping linears. The TM and MSS spectral bands corresponding to the data applications are listed in a table.
Conner, P. K.↗
Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data
The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.
Thompson, D. R.↗
Critical land resources inventory using ERTS data
The State of Wisconsin has embarked on a Critical Resources Information Program aimed at defining, establishing the units of measurement, inventorying, and monitoring natural and cultural spatial resource elements which are of statewide or regional significance. This paper presents the results of using ERTS data to inventory certain significant natural resources, such as agricultural land, forests, surface water and wetlands. Computer-generated spatial and statistical comparisons of resource data derived from conventional sources, RB-57 photographs, and ERTS images of Wisconsin suggest that certain resources can be inventoried and monitored on a statewide basis using ERTS images. Preliminary results of data extraction using ERTS digital tapes are also presented. The interpretation of certain natural and cultural resource information from ERTS images is anticipated to be an operational part of Wisconsin's Critical Resources Information Program.
Kiefer, R. W.↗
Comparative life cycle assessment of remote potable water supply for the Department of Defense
The Department of Defense (DOD) and other agencies, including relief organizations, require potable water for remote missions around the globe. As part of recent initiative by the U.S. Federal government through Executive Order 14057, the DOD has been instructed to investigate the sustainability of operations and practices within the context of climate change. One such practice that needs to be addressed is the procurement of potable water, an essential requirement of any remote mission or location. Currently, there are three primary means of procuring potable water at remote locations: bottled water, on-site purification, or tie-in to existing, local infrastructure. The first two operations are often considered the most secure options, but have sustainability concerns. The purpose of this study is to compare the environmental impacts of bottled water procurement versus on-site treatment via a mobile Reverse Osmosis Water Purification Unit (ROWPU), which uses multiple levels of filtration to make potable water from a local source. A cradle-to-gate assessment was developed for both systems to compare different options for potable water supply. An in person inventory was paired with data taken from the Ecoinvent 3.8 database to directly compare the two systems. The two systems are compared on a 5-year timeline to analyze the environmental impact of repeated bottled water transport versus diesel generator-fueled on-site treatment. Across all impact categories, the results indicate that high energy costs of the reverse osmosis process have significantly less impact on the environment than the repetitive transport and procurement of bottled water. The results of the study have important implications for advancing sustainable operations for remote communities or temporary settlements.
54 ENVIRONMENTAL SCIENCES↗
An integrated study of earth resources in the State of California using remote sensing techniques
Remote sensing activities for the management of California's water project are reported. Integrated efforts are based largely on airborne remote sensing data processing to inventory the various kinds of earth resources observed. Work centered on defining parameters pertinent to determine water yield and discernible through remote sensing techniques; (2) determining accuracy in measuring and mapping parameters using remote sensing data flown to various specifications; and (3) relating water yield predictions to actual water yields. Remote sensing imagery of the Perris valley shows that land developers established a number of locations to promote present agricultural land for non-agricultural land use.
Colwell, R. N.↗
A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data
The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements. These databases, often referred to as inventories, can be used for a wide variety of environmental reporting and modeling purposes to characterize conditions in the United States. Yet, users are often challenged to find, retrieve, and interpret these data due to the unique schemes employed for data management, which could result in erroneous estimations or double-counting of emissions. To address these challenges, a system called Standardized Emission and Waste Inventories (StEWI) has been created. The system consists of four python modules that provide rapid access to USEPA inventory data in standard formats and permit filtering and combination of these inventory data. When accessed through StEWI, reported emissions of carbon dioxide to air and ammonia to water are reduced approximately two- and four-fold, respectively, to avoid duplicate reporting. StEWI will greatly facilitate the use of USEPA inventory data in chemical release and exposure modeling and life cycle assessment tools, among other things. To date, StEWI has been used to build the recent USEEIO model and the baseline electricity life cycle inventory database for the Federal LCA Commons.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data
Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.
random forest↗
Water Footprint of European Rooftop Photovoltaic Electricity based on Regionalised Life Cycle Inventories
The water use of photovoltaic (PV) electricity has been investigated in very few studies so far, which may be due to the low water demand of PV systems during operation. In this study, the water consumption and water withdrawal of electricity generated by PV systems were assessed by considering all life cycle stages and by taking account of country-level regional differences in water availability. The life cycle inventories of the manufacture of monocrystalline silicon (mono-Si) and cadmium telluride (CdTe) PV modules are based on data collected between 2010 and 2013 and take account of the shares of different countries in total global production. The water use in the life cycle inventories of European rooftop PV systems and conventional electricity generation technologies was regionalised to the country or region (such as continents, political or geographic entities of several countries) level and complemented by the share of water lost by evaporation. The AWARE (Available WAter REmaining) method was used to assess the water stress impact caused by water consumption and water withdrawal of electricity generation by European rooftop PV systems as well as by reservoir hydroelectric power plants and large-scale hard coal and nuclear power plants in Europe. The functional unit of this analysis is 1 kWh of alternating current (AC) electricity (at busbar). The life cycle inventories were linked to KBOB (Coordination Group for Construction and Property Services) life cycle inventory data DQRv2:2016, which are based on ecoinvent data v2.2 and contain updated life cycle inventory data in relevant economic sectors. This study was financed by the Swiss Federal Office of Energy (SFOE) and carried out in the framework of the Task 12 of the Photovoltaic Power Systems Programme (PVPS) of the International Energy Agency (IEA).
14 SOLAR ENERGY↗
Nuclide Inventory Benchmark for BWR Spent Nuclear Fuel: Challenges in Evaluation of Modeling Data Assumptions and Uncertainties
This work discusses challenges and approaches to uncertainty analyses associated with the development of a nuclide inventory benchmark for fuel irradiated in a boiling water reactor. The benchmark under consideration is being developed based on experimental data from the SFCOMPO international database. The focus herein is on how to address missing data in fuel design and operating conditions that are important for adequately simulating the time-dependent changes in fuel during irradiation in the reactor. The effects of modeling assumptions and uncertainties in modeling parameters on the calculated nuclide inventory were analyzed and quantified through computational models developed using capabilities in the SCALE code system. Particular attention was given to the impact of the power history and water coolant density on the calculated nuclide inventory, as well as to the effect of geometry modeling considerations not usually addressed in a nuclide inventory benchmark. These considerations include gap closure, channel bow, and channel corner radius, which do not usually apply to regular reactor operation but are relevant for assessing impacts of potential anomalous operating scenarios.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Utilization of EREP data in geological evaluation, regional planning, forest management, and water management in North Carolina
The author has identified the following significant results. The S190A, S190B, and S192 photographs and imagery were studied, using standard air-photo interpretation techniques supplemented by color additive viewing and density slicing. The EREP data were found to have potential usefulness for natural resource inventory work, water quality monitoring, and land use mapping for specific problems at scales up to 1:30,000. Distinctions between forest types in North Carolina are limited to conifers, mixed conifer-hardwoods, and hardwoods. Geologic interpretation was limited to detection of lineaments; lithologic differentiation and soil group mapping have proved infeasible in North Carolina except for differentiation of wetland soils in the coastal plain. Imagery from the S192 multispectral scanner has proved to be capable of useful discriminations for vegetation and crop analysis.
Welby, C. W.↗
COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Tree Inventory
This is the tree inventory (diameter, species, and live/dead status) data from the Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment is part of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field Measurements and Experiments; see https://compass.pnnl.gov/FME/COMPASSFME) project. It addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in eastern Maryland, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments.This dataset includes:- An overall dataset README file.- The tree inventory data in both "wide" and "long" forms. These contain the same information but are structured differently, with the former more useful for human viewers and the latter more amenable for programmatic analyses.- A key to the species/genus codes used, which follow the U.S. Department of Agriculture's PLANTS schema (https://plants.usda.gov/).- A copy of the R code used to generate the wide- and long-form data files.All files are comma-separated value (CSV) and no special software is required to read them.
54 ENVIRONMENTAL SCIENCES↗