Search NASA⌕ Search

SEARCH · Search NASA

Results for “Simulated flooding”

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.

445 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Levelized Cost of CO 2 Captured Using Five Physical Solvents in Pre-combustion Applications

Aspen Plus v8.8 was used to perform techno-economic analysis (TEA) of a CO 2 capture process from a typical fuel gas stream in a 543-MW pre-combustion power plant using five different physical solvents (Selexol, PEGPDMS-1, NMP, [aPy][Tf 2 N] and [hmim][Tf 2 N]). The process included a countercurrent packed-bed absorber operating under high-pressure over a wide range of temperatures and three pressure-swing flash drums for solvent regeneration. Furthermore, two packings, Mellapak 250Y and IMTP50, were used and the Levelized costs of CO 2 captured (LCOC) were calculated. The simulation results indicated that using Mellapak 250Y exhibited lower LCOC values than those when using IMTP50 for the five solvents under all conditions used as it offered better mass transfer. The CO 2 capture process carried out at low temperatures showed lower LCOC values than those at higher temperatures due to the increased CO 2 solubility in the solvents at lower temperatures, requiring smaller absorber diameter and lower solvent circulation rates, which offset the cooling requirements. Comparing the lowest LCOC values for the five solvents, the hydrophobic PEGPDMS-1 solvent was the most promising one compared to the other four solvents, due to its lowest capital and operating costs and noncorrosive, which enabled using less expensive materials for the process equipment.

42 ENGINEERING↗
NASA NTRS2011

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Njoku, Eni↗
NASA NTRS2018

The Land Surface Data Toolkit (LDT v7.2) - A Data Fusion Environment for Land Data Assimilation Systems

The effective applications of land surface models (LSMs) and hydrologic models pose a varied set of data input and processing needs, ranging from ensuring consistency checks to more derived data processing and analytics. This article describes the development of the Land surface Data Toolkit (LDT), which is an integrated framework designed specifically for processing input data to execute LSMs and hydrological models. LDT not only serves as a preprocessor to the NASA Land Information System (LIS), which is an integrated framework designed for multi-model LSM simulations and data assimilation (DA) integrations, but also as a land-surface-based observation and DA input processor. It offers a variety of user options and inputs to processing datasets for use within LIS and stand-alone models. The LDT design facilitates the use of common data formats and conventions. LDT is also capable of processing LSM initial conditions and meteorological boundary conditions and ensuring data quality for inputs to LSMs and DA routines. The machine learning layer in LDT facilitates the use of modern data science algorithms for developing data-driven predictive models. Through the use of an object-oriented framework design, LDT provides extensible features for the continued development of support for different types of observational datasets and data analytics algorithms to aid land surface modeling and data assimilation.

droughts and floods↗
DOE OSTI2025

Surface heat flux and its association with the MJO in the tropical western Pacific using ARM observations

The Madden-Julian oscillation (MJO) is a major atmospheric phenomenon in the tropics that moves eastward every 20 to 100 days. It brings heavy rain and strong winds, influencing extreme weather events far beyond the tropics – including flooding, hurricanes, tornadoes and heavy snow in the United States. Therefore, an improved understanding of the MJO is critical for enhancing weather forecasts and supporting better decision-making for communities, emergency managers, and the private sector. Past studies, based on short-term observations or long-term model data, have emphasized the dominant role of atmospheric humidity in driving the MJO. Our research, using long-term observations (2000-2014) from three U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) sites in the tropical western Pacific (Manus, Nauru, and Darwin) confirms those past findings. However, we also show that atmospheric temperature, especially in the mid and upper troposphere, also plays a key role in the MJO’s evolution from its quiet (suppressed) to convective (active) phase. These findings provide valuable insights into how the MJO evolves and may help evaluate and improve weather and climate models. Our study also examined how the exchange of heat between the Earth's surface and the atmosphere, called surface heat flux, interacts with the MJO. This flux includes components such as latent heat (related to evaporation), sensible heat (related to temperature difference between surface and atmosphere), and radiation. We found that modulation in MJO convection is well connected to surface heat flux over the tropical western Pacific. One surface heat flux component often overlooked is the sensible heat flux due to precipitation (Q P ). Since falling raindrops are typically cooler than the land or ocean surface, they can cool the surface and affect local weather. To test the impact of Q P on convection during MJO, we incorporated it into a weather model, and ran simulations for two periods: April 2009 (when the MJO was active) and June 2006 (when it was not). Including Q P reduced errors in simulating the daily peak of rainfall—by 83% during the strong MJO and 23% during the inactive phase. It also improved the timing of peak daily rainfall and reduced the overall precipitation error by about 10%. These improvements were especially noticeable during periods of heavy rainfall. Our results suggest that even small heat exchanges from rainfall can play a significant role in shaping local weather. Accounting for these effects, particularly in regions like the tropical islands, can lead to more accurate simulations of the MJO-associated precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Investigating Hydroclimatic Impacts of the 168–158 BCE Volcanic Quartet and Their Relevance to the Nile River Basin and Egyptian History

The Ptolemaic era (305–30 BCE) is an important period of Ancient Egyptian history known for its material and scientific advances, but also intermittent political and social unrest in the form of (sometimes widespread) revolts against the Ptolemaic elites. While the role of environmental pressures has long been overlooked in this period of Egyptian history, ice-core-based volcanic histories have identified the period as experiencing multiple notable eruptions, and a repeated temporal association between explosive volcanism and revolt has recently been noted. Here we analyze the global and regional (Nile River basin) hydroclimatic response to a unique historical sequence of four large and closely timed volcanic eruptions (first a tropical one, followed by three extratropical northern hemispheric events) between 168 and 158 BCE, a particularly troubled period in Ptolemaic history for which we now provide a more detailed hydroclimatic context. The NASA (National Aeronautics and Space Administration) GISS (Goddard Institute for Space Studies) ModelE2.1 Earth system model simulates a strong radiative response with a radiative forcing (top of atmosphere) of −7.5 W m−2 (following the first eruption) and −2.5 W m−2 (after each of the three remaining eruptions) at a global scale. Associated with this, we observe a global surface cooling of the order of 1.5 ∘C following the first (tropical) eruption, with the following three extratropical eruptions extending the cooling period for more than 15 years. Consequently, this series of eruptions is observed to constrain the northward migration of the inter-tropical convergence zone (ITCZ) during the Northern Hemisphere summer monsoon season, and major monsoon zones (African, South Asian, and East Asian) were seen to experience a suppression of rainfall of >1 mm d−1 during the monsoon (JJAS) season averaged for 2 years after each eruption. A substantial suppression of the Indian and North African summer monsoon (over the Nile River headwater region) was seen to strongly affect the modeled river flow in the catchment and discharge at river mouth. River mass flow over the basin was observed to decrease by 29 % and 38 % relative to an unperturbed (non-volcanic) annual mean flow in the first and second year, respectively, after the first (i.e., tropical) eruption. A moderate decrease ranging between 5 % and 18 % was observed after the third and fourth (extratropical) eruptions. These results indicate, in sum, that the first eruption likely produced a strong hydroclimate response, with the following extratropical eruptions prolonging this. These results also support the recently hypothesized association between ice-core-based signals of explosive volcanism and hydroclimatic variability during the Ptolemaic era, including the suppression of the agriculturally critical Nile summer flooding.

hydroclimate impacts↗
DOE OSTI2025

Assessing the Role of Hydrodynamics in Enhancing Height-Above-the-Nearest-Drainage Derived Synthetic Rating Curves: A Comparative Study in the Wu River Basin, Taiwan

The conventional approach to generating synthetic rating curves (SRC) using the Height-Above-the-Nearest-Drainage (HAND) method typically relies on the assumption of uniform flow, such as Manning's equation, to establish stage-discharge ratings. The zero-physics application of the uniform flow equation is insufficient for capturing detailed hydraulic features (e.g., backwater effect) and neglects the hydraulic effects from adjacent channels. This lack of hydrodynamic computation can impact the accuracy and effectiveness of riverine flood risk estimation and management. To reduce this foreseeable error, we introduce the HAND-hd workflow, which integrates sophisticated hydrodynamic computations in the production of HAND-based SRC with hydrodynamic features (SRC hd ). The results indicate that SRC hd demonstrates consistent agreement with both gauge observations and benchmark solutions. Additionally, the comparative analysis suggests that SRC hd provides notable improvements in stage-discharge ratings over conventional HAND-based SRCs, particularly in channels with mild bed gradients, where it reduces water stage prediction errors and percent biases. In steeper channel segments, SRC hd maintains comparable accuracy to conventional methods. The comprehensive evaluation in this study emphasizes the potential discrepancies and inaccuracies associated with the adoption of the uniform flow assumption in the conventional HAND-SRCs and addresses the necessity of including hydrodynamic physics in the application of HAND-based SRC (e.g., inundation map) in channels with mild gradients.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Improved Calibration of Modeled Discharge and Storage Change in the Atchafalaya Floodplain Using SAR Interferometry

This study focuses on the feasibility of using SAR interferometry to support 2D hydrodynamic model calibration and provide water storage change in the floodplain. Two-dimensional (2D) flood inundation modeling has been widely studied using storage cell approaches with the availability of high resolution, remotely sensed floodplain topography. The development of coupled 1D/2D flood modeling has shown improved calculation of 2D floodplain inundation as well as channel water elevation. Most floodplain model results have been validated using remote sensing methods for inundation extent. However, few studies show the quantitative validation of spatial variations in floodplain water elevations in the 2D modeling since most of the gauges are located along main river channels and traditional single track satellite altimetry over the floodplain are limited. Synthetic Aperture Radar (SAR) interferometry recently has been proven to be useful for measuring centimeter-scale water elevation changes over the floodplain. In the current study, we apply the LISFLOOD hydrodynamic model to the central Atchafalaya River Basin, Louisiana, during a 62 day period from 1 April to 1 June 2008 using two different calibration schemes for Manning's n. First, the model is calibrated in terms of water elevations from a single in situ gauge that represents a more traditional approach. Due to the gauge location in the channel, the calibration shows more sensitivity to channel roughness relative to floodplain roughness. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. Since SAR interferometry receives strongly scatters in floodplain due to double bounce effect as compared to specular scattering of open water, the calibration shows more dependency to floodplain roughness. An iterative approach is used to determine the best-fit Manning's n for the two different calibration approaches. Results suggest similar floodplain roughness but slightly different channel roughness. However, application of SAR interferometry provides a unique view of the floodplain flow gradients, not possible with a single gauge calibration. These gradients, allow improved computation of water storage change over the 46-day simulation period. Overall, the results suggest that the use of 2D SAR water elevation changes in the Atchafalaya basin offers improved understanding and modeling of floodplain hydrodynamics.

Jung, Hahn Chul↗
NASA NTRS2017

Extreme Storms

Key Findings: 1. Human activities have contributed substantially to observed ocean-atmosphere variability in the Atlantic Ocean (medium confidence), and these changes have contributed to the observed upward trend in North Atlantic hurricane activity since the 1970s (medium confidence). 2. Both theory and numerical modeling simulations generally indicate an increase in tropical cyclone (TC) intensity in a warmer world, and the models generally show an increase in the number of very intense TCs. For Atlantic and eastern North Pacific hurricanes and western North Pacific typhoons, increases are projected in precipitation rates (high confidence) and intensity (medium confidence). The frequency of the most intense of these storms is projected to increase in the Atlantic and western North Pacific (low confidence) and in the eastern North Pacific (medium confidence). 3. Tornado activity in the United States has become more variable, particularly over the 2000s, with a decrease in the number of days per year with tornadoes and an increase in the number of tornadoes on these days (medium confidence). Confidence in past trends for hail and severe thunderstorm winds, however, is low. Climate models consistently project environmental changes that would putatively support an increase in the frequency and intensity of severe thunderstorms (a category that combines tornadoes, hail, and winds), especially over regions that are currently prone to these hazards, but confidence in the details of this projected increase is low. 4. There has been a trend toward earlier snowmelt and a decrease in snowstorm frequency on the southern margins of climatologically snowy areas (medium confidence). Winter storm tracks have shifted northward since 1950 over the Northern Hemisphere (medium confidence). Projections of winter storm frequency and intensity over the United States vary from increasing to decreasing depending on region, but model agreement is poor and confidence is low. Potential linkages between the frequency and intensity of severe winter storms in the United States and accelerated warming in the Arctic have been postulated, but they are complex, and, to some extent, contested, and confidence in the connection is currently low. 5. The frequency and severity of landfalling "atmospheric rivers" on the U.S. West Coast (narrow streams of moisture that account for 30 percent to 40 percent of the typical snowpack and annual precipitation in the region and are associated with severe flooding events) will increase as a result of increasing evaporation and resulting higher atmospheric water vapor that occurs with increasing temperature. (Medium confidence)

Kossin, J. P.↗
NASA NTRS2014

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Case. Jonathan↗
NASA NTRS2014

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the planetary boundary layer (PBL) of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface, particularly within weakly-sheared environments such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in land surface and numerical weather prediction (NWP) models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-impact weather over eastern Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) NWP model in real time to support its daily forecasting operations, making use of the NOAA/National Weather Service (NWS) Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the KMS-WRF runs on a regional grid over eastern Africa. Two organizations at the NASA Marshall Space Flight Center in Huntsville, AL, SERVIR and the Shortterm Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMS for enhancing its regional modeling capabilities through new datasets and tools. To accomplish this goal, SPoRT and SERVIR is providing enhanced, experimental land surface initialization datasets and model verification capabilities to KMS as part of this collaboration. To produce a land-surface initialization more consistent with the resolution of the KMS-WRF runs, the NASA Land Information System (LIS) is run at a comparable resolution to provide real-time, daily soil initialization data in place of data interpolated from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model soil moisture and temperature fields. Additionally, realtime green vegetation fraction (GVF) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite will be incorporated into the KMS-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service (NESDIS). Finally, model verification capabilities will be transitioned to KMS using the Model Evaluation Tools (MET; Brown et al. 2009) package in conjunction with a dynamic scripting package developed by SPoRT (Zavodsky et al. 2014), to help quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. Furthermore, the transition of these MET tools will enable KMS to monitor model forecast accuracy in near real time. This paper presents preliminary efforts to improve land surface model initialization over eastern Africa in support of operations at KMS. The remainder of this extended abstract is organized as follows: The collaborating organizations involved in the project are described in Section 2; background information on LIS and the configuration for eastern Africa is presented in Section 3; the WRF configuration used in this modeling experiment is described in Section 4; sample experimental WRF output with and without LIS initialization data are given in Section 5; a summary is given in Section 6 followed by acknowledgements and references.

Case, Johnathan L.↗
NASA NTRS2004

Winds, Water Budgets and Stable Isotopes in Tropical Cyclones using TRMM and QUICKSCAT

Water vapor is the most abundant greenhouse gas in the atmosphere. Changes in its concentration and distribution are controlled by the hydrologic cycle. Because of its capacity to absorb and emit long wave radiation, release latent heat during condensation in storms and reflect short wave radiation when clouds form it has a major impact on Global climate change. The stable isotope ratios of water are H20 H2l6O and H0 H2l6O. These ratios change whenever water undergoes a phase change. They also change in both rain and water vapor whenever an air parcel is exposed to rain. In addition the relative changes in the two ratios differ as a &nction of the relative humidity. In short, the stable isotope ratios in water vapor in the atmosphere contain an integrated history of the processes affecting the concentration and distribution of water vapor in the atmosphere. Therefore the measurement and interpretation of changes in these stable isotope ratios are a powerful tool matched by no other method in tracing the transport history of water in the atmosphere. Our initial studies under this grant focused on the changes of the stable isotope ratios of precipitation and water vapor in tropical cyclones. The changes in time and space were found to be very large and to trace the transport of water in the storms reflecting changes in basic structural features. Because the stable isotope ratios of rains from tropical cyclones are so low flooding associated with land falling tropical cyclones introduces a negative isotopic spike into the coastal surface waters. In addition the stable isotope ratios of water vapor in the vicinity of tropical cyclones is anomalously low. This suggests that carbonate shelled organisms such as ostracoda living in coastal waters have the potential to record the isotopic spike and thereby provide a long term record of tropical storm activity in sediment cores containing fossil shells. Likewise, tree rings in coastal environments offer a similar potential. We have analyzed the oxygen isotopic composition of ostrcoda shells formed in the floodwaters of Tropical Storm Allison (2001) and discovered the negative isotopic 1 16 spike. Because we had learned that storm activity has a major impact on the stable isotope ratios of water vapor in the tropics and sub-tropics we decided to analyze the isotopic compositions of water vapor in different locations in the tropics. We did this in Puerto Escondido, Mexico in July 1998, near Kwajalein Island in the Pacific in 1999 as part of a TRMM summer field program and in 2001 in Key West, Florida as part of the CAMEX 4 summer field program. Our isotopic studies along with our earlier tropical cyclone studies showed that the low isotopic ratios in water vapor induced by exposure to rains the storms persisted for 48 hours often far away from the original storm site. We also noted that positive isotopic spikes were introduced into atmospheric water vapor if winds were high and extensive sea spray was present. These findings have a significant impact on the interpretation of the stable isotope studies of tropical ice cores found in the high mountain regions of the tropics. The assumption made in interpreting the ice core record is that the source water vapor evaporated from the sea surface is in near isotopic equilibrium with the seawater and undergoes a decrease during its transport that reflects the change in temperature from the sea surface to the site of the ice core. Because an additional isotopic depletion occurs at the sea surface source area that depends on the intensity, duration and size of the tropical rain system the isotopic variations found in the ice cores must take into account changes in past storm activity in the tropics. These systems must be an important source of water vapor to the ice cores because they charge the troposphere with water vapor to a far greater vertical height than evaporation in quiescent regions. Finally, an interest in increased heat transfer in thnterior of tropical cyclones resulting from greater amounts of sea spray is a topic of considerable interest to the research community. Increases in sea spray may be related to rapid changes in the intensity of hurricanes, a feature of hurricanes that currently is very poorly forecast. Project CBLAST of the Hurricane Research Division of NOAA is an active program that uses P3 research aircraft to evaluate this problem. An instrument has been designed and built at the University of Houston that will be placed on the P3 research aircraft during the 2004 hurricane season. It continuously measures the salt content of rain in hurricanes. Changes in the salt content of the rains should reflect the abundance of sea spray at the sea surface. In this way maps of sea spray intensity in hurricanes may be forthcoming. This should help computer modelers who simulate hurricanes to better understand the potential of changes in sea spray to change the intensity of hurricanes. The cost of designing, building and installing this instrument was borne largely by funding from this NASA grant. A list of presentations at national meetings and publications that were as the result of funding from this NASA grant are found in the report.

Lawrence, James R.↗
DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗
DOE OSTI2025

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗