SEARCH · Engineering Papers

Results for “Water Management”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

NASA NTRS2013

The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

Suppose you are a city planner, regional water manager, or wildlife conservation specialist who is asked to include the potential impacts of climate variability and change in your risk management and planning efforts. What climate information would you use? The choice is often regional or local climate projections downscaled from global climate models (GCMs; also known as general circulation models) to include detail at spatial and temporal scales that align with those of the decision problem. A few years ago this information was hard to come by. Now there is Web-based access to a proliferation of high-resolution climate projections derived with differing downscaling methods.

downscaled projections↗

NASA NTRS2004

Alssat Development Status and Its Applications in Trade Studies

The development of the Advanced Life Support (ALS) Sizing Analysis Tool (ALSSAT) using Microsoft® Excel was initiated by the Crew and Thermal Systems Division (CTSD) of Johnson Space Center (JSC) in 1997 to support the ALS and Exploration Offices in Environmental Control and Life Support System (ECLSS) design and studies. It aids the user in performing detailed sizing of the ECLSS based on suggested default values or user inputs for different combinations of the ALS regenerative system technologies (Ref. 1, 2). This analysis tool will assist the user in performing ECLSS preliminary design and trade studies as well as system optimization efficiently and economically. Since ALSSAT's latest publication in ICES 2001 (Ref. 1) describing the development of ALSSAT with its Air Revitalization Subsystem (ARS), Water Management Subsystem (WMS), and Biomass Subsystem (Biomass) mass balance sheets, ALSSAT has been expanded to include mass balance and sizing models for the remaining three ALS subsystems, namely, the Solid Waste Management Subsystem (SWMS), the Food Management Subsystem (FMS), and the Thermal Control Subsystem (TCS). The external interfaces, including the Extravehicular Activities (EVA) and Human Accommodations (HA), were implemented into ALSSAT in 2002. The overall mass balance sheet, which integrates the six ALS subsystems and the external interfaces applicable to the ECLSS, was also developed. In 2003, ALSSAT was upgraded to include the consideration of redundancy and contingency options in the ECLSS, as well as more ALS regenerative technology selections. ALSSAT has been used for the Metric Calculation for FY02 and FY03 (Ref. 3). Several trade studies were conducted in 2003. The analytical results will be presented in this paper.

Yeh, H. Y. (Jannivine)↗

NASA NTRS2015

Using Dynamically Downscaled Climate Model Outputs to Inform Projections of Extreme Precipitation Events

Many of the storms that generate damaging floods are caused by locally intense, sub-daily precipitation, yet the spatial and temporal resolution of the most widely available climate model outputs are both too coarse to simulate these events. Thus there is often a disconnect between the nature of the events that cause damaging floods and the models used to project how climate change might influence their magnitude. This could be a particular problem when developing scenarios to inform future storm water management options under future climate scenarios. In this study we sought to close this gap, using sub-daily outputs from the Weather Research and Forecasting model (WRF) from each of the nine climate regions in the United States. Specifically, we asked 1) whether WRF outputs projected consistent patterns of change for sub-daily and daily precipitation extremes; and 2) whether this dynamically downscaled model projected different magnitudes of change for 3-hourly vs 24-hourly extreme events. We extracted annual maximum values for 3-hour through 24-hour precipitation totals from an 11-year time series of hindcast (1995-2005) and mid-century (2045-2055) climate, and calculated the direction and magnitude of change for 3-hour and 24-hour extreme events over this timeframe. The model results project that the magnitude of both 3-hour and 24-hour events will increase over most regions of the United States, but there was no clear or consistent difference in the relative magnitudes of change for sub-daily vs daily events.

Climate models↗

NASA NTRS2015

Artesian Well Abandonment at Launch Complex 39A

The artesian well tasked for abandonment was located on the LOX side (northwest area) of the launch complex. The exact date of well installation is unknown. The well was no longer in use at the time of the abandonment request, but was previously utilized under St. Johns River Water Management District (SJRWMD) consumptive use permit (No. 50054) for the Floridian Aquifer. The exact construction details of the LOX artesian well were also unknown; however, a similar-type artesian well was previously located on the LH2 side of the site, which was abandoned in 2012. Based on discussions with the NASA RPM and review of the LH2 artesian well abandonment completion report, the LH2 artesian well was reported to be an 8-inch diameter, 330-foot deep well. The NASA RPM communicated that the LOX artesian well was likely to be an 8-inch diameter, 380-foot deep well. This information was used for scoping, and was subsequently confirmed to be substantially accurate. No additional information could be found for the LOX artesian well using the NASA Remediation Information System (RIS).

Morgan, Lindsay↗

NASA NTRS2017

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Hydrological models↗

NASA NTRS2017

Transforming Science Data for GIS: How to Find and Use NASA Earth Observation Data Without Being a Rocket Scientist

NASAs Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. The challenge is that Earth Observation data is complicated. There is plenty of data available, however, the science teams have had a top-down approach: define what it is you are trying to study -select a set of satellite(s) and sensor(s), and drill down for the data.Our alternative is to take a bottom-up approach using eight environmental fields of interest as defined by the Group on Earth Observations (GEO) called Societal Benefit Areas (SBAs): Disaster Resilience (DR) Public Health Surveillance (PHS) Energy and Mineral Resource Management (EMRM) Water Resources Management (WRM) Infrastructure and Transport Management (ITM) Sustainable Urban Development (SUD) Food Security and Sustainable Agriculture (FSSA) Biodiversity and Ecosystems Sustainability (BES).

DAAC↗

NASA NTRS2017

NASA Advanced Explorations Systems: 2017 Advancements in Life Support Systems

The NASA Advanced Exploration Systems (AES) Life Support Systems (LSS) project strives to develop reliable, energy-efficient, and low-mass spacecraft systems to provide environmental control and life support systems (ECLSS) critical to enabling long duration human missions beyond low Earth orbit (LEO). Highly reliable, closed-loop life support systems are among the capabilities required for the longer duration human space exploration missions planned in the mid-2020s and beyond. The LSS Project is focused on four are-as-architecture and systems engineering for life support systems, environmental monitoring, air revitalization, and wastewater processing and water management. Starting with the International Space Station (ISS) LSS systems as a point of departure where applicable, the three-fold mission of the LSS Project is to address discrete LSS technology gaps, to improve the reliability of LSS systems, and to advance LSS systems toward integrated testing aboard the ISS. This paper is a follow on to the AES LSS development status reported in 2016 and provides additional details on the progress made since that paper was published with specific attention to the status of the Aerosol Sampler ISS Flight Experiment, the Spacecraft Atmosphere Monitor (SAM) Flight Experiment, the Brine Processor Assembly (BPA) Flight Experiment, the CO2 removal technology development tasks, and the work investigating the impacts of dormancy on LSS systems.

Schneider, Walter F.↗

NASA NTRS2018

Prioritizing Aquatic Science and Applications Needs in the Chesapeake Bay for a Space-Borne Hyperspectral Mission

The Chesapeake Bay is the largest estuary in North America, benefiting a growing population through its ecosystem services, fishing, recreations, and transportation routes. Studies indicate the health of the Bay as seen some improvement in recent years, yet threats to its health persist (e.g. warming, pollution nutrient run-off). Increasing human activities in coastal regions requires constant vigilance by agencies managing water quality, to ensure the safety of the population. Since April 2018, an interagency working group has been meeting monthly and a daylong workshop was convened with science and applications stakeholders around the overall theme of monitoring water quality from space. Current ocean color images indicate bloom locations used to guide in situ sampling efforts, despite limited spatial, spectral and temporal resolution. High resolution hyperspectral remote sensing provides a potential opportunity to measure additional indicators of ecological health and water quality. Assessing the needs of the aquatic user community around the Chesapeake Bay will inform science and applications recommendations during the current architecture study for a Surface Biology and Geology (SBG) Mission, as well as future scoping studies of other coastal and inland water bodies.

Schollaert Uz, Stephanie↗

NASA NTRS2019

Chapter 14: 100 Years of Progress in Hydrology

The focus of this chapter is progress in hydrology for the last 100 years. During this period, we have seen a marked transition from practical engineering hydrology to fundamental developments in hydrologic science, including contributions to Earth system science. The first three sections in this chapter review advances in theory, observations, and hydrologic prediction. Building on this foundation, the growth of global hydrology, land-atmosphere interactions and coupling, ecohydrology, and water management are discussed, as well as a brief summary of emerging challenges and future directions. Although the review attempts to be comprehensive, the chapter offers greater coverage on surface hydrology and hydrometeorology for readers of this American Meteorological Society (AMS) Monograph.

Peters-Lidard, Christa D.↗

NASA NTRS2019

Omni-gravity Hydroponics for Space Exploration

As part of the NASA Plant Water Management technology demonstration experiments, a capillary fluidics hydroponic system that can function in a variety of gravity environments has been developed and tested for crop production in space. A passive liquid delivery method is employed that drastically reduces the number of contaminable moving parts providing a high reliability solution requiring minimal resources for operation. The terrestrial, lunar, and Martian environments are managed in a ‘gravity-dominated mode,’ while the low-gravity transit and orbit environments are managed in a ‘capillary fluidics mode,’ where the role of gravity is replaced by the equally passive effects of surface tension, conduit shape, and wettability. The unique considerations for priming, germination, aeration, nutrient supply, root accommodation, layout, crew interaction, etc. are highlighted. Design guides for system function are provided along with high Technology Readiness Level demonstrations of the system during terrestrial and drop tower tests. Long duration tests are planned on short schedule aboard the International Space Station in 2019.

gravity↗

NASA NTRS2019

Using NASA Earth Observation Data in ArcGIS

The NASA Goddard Earth Sciences Data and Information Services Center archives tens of thousands of Earth Observation (EO) parameters for land, atmosphere, and ocean. To facilitate GIS users to easily find, visualize, obtain, and analyze these EO data through, we developed an ArcGIS infrastructure with the Server, image services, Portal, and AOL. We will show how this capability supports broad GIS applications. Use cases including water management and air quality analyses will be demonstrated.

Wei, Jennifer↗

NASA NTRS2019

Assimilation of Sentinel 1 and SMAP – Based Satellite Soil Moisture Retrievals into SWAT Hydrological Model: the Impact of Satellite Revisit Time and Product Spatial Resolution on Flood Simulations in Small Basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR obtained via S1 over ASCAT was small likely due to very challenging areas for S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the soil moisture pre-storm conditions.

Small basins↗

NASA NTRSDate not supplied

Estimating Everglades Peat Reserves and Losses on a Landscape-Scale

The Florida Everglades formed from sawgrass and other aquatic plant remains that have accumulated over thousands of years and is a patterned peatland. The region was initially drained for agricultural and urban development in the late 1800s by the lowering of Lake Okeechobee water levels through canal drainage. Over the course of the past century, the Everglades has further been altered by the construction of canals and levees to provide control of Lake Okeechobee and Everglades water levels. The drainage has caused the loss of much of the peat of the Everglades by peat fires and microbial oxidation, much of it occurring between the 1880s and the 1950s. Plans for Everglades restoration are designed to provide additional water to flow through the remaining Everglades. Additional water into the Everglades would prevent further peat loss by reducing oxidation and encouraging the accretion of peat that has been lost. This potentially could result in the sequestration of significant quantities of atmospheric carbon. We used historic records to determine how much peat was there originally and how much has been lost. Over the past century and a half, approximately 50% of the original Everglades has been lost to agricultural and urban development. In addition, much of the peat in the remaining Everglades Protection Area has been lost. We used Geographic Information Systems technologies to determine the volume and mass of peat, the mass of carbon for each of the predrainage landscapes as well as the current Everglades regions. To do this, historical and current surveys within the Everglades were used to create elevation maps. With these maps, along with a bedrock contour map of south Florida, and soils data from the USEPA, we estimated Everglades peat characteristics. These calculations provide rough, quantitative estimates of the historical Everglades, its current condition, and the changes in the peat soil that have taken place since the 19th century. Given the uncertainties in the hindcasting of some of these data sets, this analysis provides rough estimates for the peat volumes and related constituents. Our calculations indicate that the current Everglades roughly contains less than 24% of theoriginal peat volume, 17% of its mass and 19% of its carbon. The work described was fully supported by the South Florida Water Management District, West Palm Beach, FL

Thomas Walter Dreschel↗

NASA NTRS2020

Tree Rings and Observations Suggest No Stable Cycles In Sierra Nevada Cool‐Season Precipitation

California's water resources rely heavily on cool‐season (November–March) precipitation in the Sierra Nevada. Interannual variability is highly volatile and seasonal forecasting has little to no skill, making water management particularly challenging. Over 1902–2020, Sierra Nevada cool‐season precipitation totals exhibited significant 2.2‐ and 13–15‐year cycles, accounting for approximately 40% of total variability and perhaps signifying potential as seasonal forecasting tools. However, the underlying climate dynamics are not well understood and it is unclear whether these cycles are stable over the long‐term. We use tree rings to reconstruct Sierra Nevada cool‐season precipitation back to 1400. The reconstruction is skillful, accounting for 55–74% of observed variability and capturing the 20th‐century 2.2‐ and 13–15‐year cycles. Prior to 1900, the reconstruction indicates no other century‐long periods of significant spectral power in the 2.2‐ or 13–15‐year bands. The reconstruction does indicate significant cyclicity over other extended periods of several decades or longer, however, with dominant periodicities in the ranges of 2.1–2.7 and 3.5–8 years. The late 1700s through 1800s exhibited the highest‐amplitude cycles in the reconstruction, with periodicities of 2.4 and 5.7–7.4 years. The reconstruction should serve to caution against extrapolating the observed 2.2‐ and 13–15‐year cycles to guide future expectations. On the other hand, observations and the reconstruction suggest that interannual variability of Sierra Nevada cool‐season precipitation is not a purely white noise process and research should aim to diagnose the dynamical drivers of extended periods of cyclicity in this critical natural resource.

Paleoclimate↗

NASA NTRS2018

UAS-Based P-Band Signals of Opportunity for Remote Sensing of Snow and Root Zone Soil Moisture

We have developed the P-band Signals of Opportunity (SoOp) sensor based on the Unmanned Aircraft System (UAS) to remotely sense Snow Water Equivalent (SWE) and Root Zone Soil Moisture (RZSM). The P-band UAS SoOp sensor for Hydrology (UASHydro) would operate on the S2 aircraft developed by Black Swift Technologies for sensing of SWE and RZSM with a spatial resolution of about 10m. Root-zone soil moisture and snow water storage in land are critical parameters of the water cycle. The long-term goal of our development would be to use small UAS to perform regional high resolution observation of two key hydrological measurements to improve the estimation of terrestrial water storage for water management, crop production and forecasts of natural hazard. The UASHydro concept utilizes passive receivers to detect the reflection of strong existing P-band radio signals at the 360-380 MHz band from geostationary Mobile Use Objective System (MUOS) communication satellites launched by the US Navy. The SWE remote sensing measurement principle using the P-band SoOp is based on the propagation delay (or phase change) of radio signals through the snowpack. The time delay of the reflected signal due to the snowpack with respect to snow-free conditions is directly proportional to the snowpack SWE, while the soil moisture can be retrieved from the reflectivity at the P-band frequencies for MUOS. We have been conducting ground-based campaigns to test the instrumentation and data processing methods at the Fraser Experimental Forest in Colorado since February 2016. The field campaign data has provided support to the measurement concept. To install the SoOp technologies on the UAS, a lightweight antenna has been built and interfaces with the S2 built by Black Swift Technologies have been completed. A set of flights have been planned starting April 2018 through the end of 2018 in Colorado.

Elston, Jack↗

NASA NTRS2019

Assimilation of Sentinel 1 and SMAP–based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (HSAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via the Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR-SWI obtained via S1 over ASCAT was small, likely due to very challenging areas for the S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the pre-storm soil moisture conditions.

Shima Azimi↗

NASA NTRS2020

Windows of Opportunity for Skillful Forecasts Subseasonal to Seasonal and Beyond

There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.

Annarita Mariotti↗

NASA NTRS2022

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗