Search NASA⌕ Search

SEARCH · Search NASA

Results for “flood model”

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.

At least 361 records · Page 20

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

The Simulation EnviRonment for Geomorphology, Hydrodynamics, and Ecohydrology in Integrated form (SERGHEI) is a multi-dimensional, multi-domain, and multi-physics model framework for environmental and landscape simulation, designed with an outlook towards Earth system modelling. At the core of SERGHEI's innovation is its performance-portable high-performance parallel-computing (HPC) implementation, built from scratch on the Kokkos portability layer, allowing SERGHEI to be deployed, in a performance-portable fashion, in graphics processing unit (GPU)-based heterogeneous systems. In this work, we explore combinations of MPI and Kokkos using OpenMP and CUDA backends. In this contribution, we introduce the SERGHEI model framework and present with detail its first operational module for solving shallow-water equations (SERGHEI-SWE) and its HPC implementation. This module is designed to be applicable to hydrological and environmental problems including flooding and runoff generation, with an outlook towards Earth system modelling. Its applicability is demonstrated by testing several well-known benchmarks and large-scale problems, for which SERGHEI-SWE achieves excellent results for the different types of shallow-water problems. Finally, SERGHEI-SWE scalability and performance portability is demonstrated and evaluated on several TOP500 HPC systems, with very good scaling in the range of over 20 000 CPUs and up to 256 state-of-the art GPUs.

58 GEOSCIENCES↗

Decoding Resilience by Modeling Outage and Restoration Processes in Distribution Grids: A Pittsburgh Case Study

Climate-induced extreme weather events, such as floods and heatwaves, pose significant challenges to the resilience of urban power distribution grids. This paper examines the outage and restoration dynamics of Pittsburgh's power grid during the flood event in April 2024 and three heatwaves in June, July, and August 2024. We introduce a comprehensive modeling framework that integrates outage and restoration processes, enabling the quantification of resilience metrics, including total customer-hours of power outage, maximum residual values, and restoration durations across various ZIP codes. Our analysis highlights spatial disparities in outage impacts and restoration efficiencies, with ZIP Code 15222 experiencing the highest cumulative disruptions, while ZIP Code 15217 shows lower susceptibility. By linking statistical trends with weather events, this study underscores the critical need for targeted infrastructure upgrades and advanced restoration strategies. Furthermore, the proposed framework offers valuable insights for planning and managing resilient power systems in the face of increasing climate stress.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real Time Monitoring of Flooding from Microwave Satellite Observations

We have developed a new method for making high-resolution flood extent maps (e.g., at the 30-100 m scale of digital elevation models) in real-time from low-resolution (20-70 km) passive microwave observations. The method builds a "flood-potential" database from elevations and historic flood imagery and uses it to create a flood-extent map consistent with the observed open water fraction. Microwave radiometric measurements are useful for flood monitoring because they sense surface water in clear-or-cloudy conditions and can provide more timely data (e.g., compared to radars) from relatively wide swath widths and an increasing number of available platforms (DMSP, ADEOS-II, Terra, NPOESS, GPM). The chief disadvantages for flood mapping are the radiometers' low resolution and the need for local calibration of the relationship between radiances and open-water fraction. We present our method for transforming microwave sensor-scale open water fraction estimates into high-resolution flood extent maps and describe 30-day flood map sequences generated during a retrospective study of the 1993 Great Midwest Flood. We discuss the method's potential improvement through as yet unimplemented algorithm enhancements and expected advancements in microwave radiometry (e.g., improved resolution and atmospheric correction).

Galantowicz, John F.↗

Understanding the Spatial Organization of Simultaneous Heavy Precipitation Events Over the Conterminous United States

We introduce the idea of simultaneous heavy precipitation events (SHPEs) to understand whether extreme precipitation has a spatial organization manifested as specified tracks or contiguous fields with inherent scaling relationships. For this purpose, we created a database of SHPEs using ground-based precipitation observations recorded by the daily Global Historical Climatology Network across the conterminous United States during 1900–2014. SHPEs are examined for their seasonality, spatial manifestation, orientation, and areal extent. We quantified the spatial distribution of the centroids and principal axes of SHPEs and their quasi-elliptical manifestations, azimuthal orientations, and areal extents on the ground. Four seasons, December-January-February (DJF), March-April-May (MAM),June-July-August (JJA), and September-October-November (SON) are considered to examine the spatial patterns and associated large-scale atmospheric circulations. Results indicate that there are 54, 58, 103, and204 SHPEs in DJF, MAM, JJA, and SON seasons, and their longest stretches range on average between 650and 1,600, between 850 and 1,500, between 950 and 1,550, and between 750 and 1,450 km, respectively. SHPEs in the DJF, MAM, and JJA seasons occur mostly over the Pacific coast and central and midwestern United States, respectively. The atmospheric circulation patterns and mechanisms of precipitable water vapor and moisture transport in the atmosphere are also discussed in relation to these SHPEs. Power laws explain SHPEs' underlying area scaling behavior in all the four seasons, with stronger evidence in DJF and MAM. A seasonal spatial risk model is developed to predict the likelihood of SHPEs. Quantifying the characteristics of SHPEs and modeling their footprints can improve the projections of flood risk and understanding of damages to interconnected infrastructure systems.

54 ENVIRONMENTAL SCIENCES↗

Study of the zinc-silver oxide battery system

Theoretical and experimental models for the evaluation of current distribution in flooded, porous electrodes are discussed. An approximation for the local current distribution function was derived for conditions of a linear overpotential, a uniform concentration, and a very conductive matrix. By considering the porous electrode to be an analog of chemical catalyst structures, a dimensionless performance parameter was derived from the approximated current distribution function. In this manner the electrode behavior was characterized in terms of an electrochemical Thiele parameter and an effectiveness factor. It was shown that the electrochemical engineering approach makes possible the organizations of theoretical descriptions and of practical experience in the form of dimensionless parameters, such as the electrochemical Thiele parameters, and hence provides useful information for the design of new electrochemical systems.

Nanis, L.↗

Applications of remote sensing to watershed management

Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.

Rango, A.↗

The role of space borne imaging radars in environmental monitoring: Some shuttle imaging radar results in Asia

The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. How synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather is discussed. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agricultural land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems are discussed.

Imhoff, Marc L.↗

The role of space borne imaging radars in environmental monitoring: Some shuttle imaging radar results in Asia

The synoptic view afforded by orbiting Earth sensors can be extremely valuable for resource evaluation, environmental monitoring and development planning. For many regions of the world, however, cloud cover has prevented the acquisition of remotely sensed data during the most environmentally stressful periods of the year. This paper discusses how synthetic aperture imaging radar can be used to provide valuable data about the condition of the Earth's surface during periods of bad weather. Examples are given of applications using data from the Shuttle Imaging Radars (SIR) A and B for agriculture land use and crop condition assessment, monsoon flood boundary and flood damage assessment, water resource monitoring and terrain modeling, coastal forest mapping and vegetation penetration, and coastal development monitoring. Recent SIR-B results in Bangladesh are emphasized, radar system basics are reviewed and future SAR systems discussed.

Imhoff, M.↗

Environmental Assessments in the Riparian Corridor of the Colorado River Delta

We will develop remote sensing methods to conduct environmental assessments in the riparian corridor of the Colorado River delta, shared by the United States and Mexico. This important regional ecosystem is dependent upon US water flows, yet the most important wildlife habitats are in Mexico. The delta region is poorly known and difficult to monitor on the ground. We will use ground-validated, aerial and satellite methods to develop accurate vegetation and habitat maps and predictive hydrological and vegetation models of this ecosystem in response to US flood releases. The work products will advance our understanding of water resource issues in dryland climates and provide a specific application tool for a critical binational natural resource area.

Source record↗

Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Sets

The North American Land Data Assimilation System (NLDAS) is a collaborative project between NASA GSFC, NOAA, Princeton University, and the University of Washington. NLDAS has created surface meteorological forcing data sets using the best-available observations and reanalyses. The forcing data sets are used to drive four separate land-surface models (LSMs), Mosaic, Noah, VIC, and SAC, to produce data sets of soil moisture, snow, runoff, and surface fluxes. NLDAS hourly data, accessible from the NASA GES DISC Hydrology Data Holdings Portal, http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, are widely used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies of extreme events. More information is available at http://ldas.gsfc.nasa.gov/. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data sets have been recently released by NASA GES DISC.

Vollmer, Bruce E.↗

Climate-induced changes in forest disturbance and vegetation

New and published climate-model results are discussed which indicate that global warming favors increased rates of forest disturbance as a result of weather more likely to cause forest fires, convective wind storms, coastal flooding, and hurricanes. New sensitivity tests carried out with a vegetation model indicate that climate-induced increases in disturbance could, in turn, significantly alter the total biomass and compositional response of forests to future warming. An increase in disturbance frequency is also likely to increase the rate at which natural vegetation responses to future climate change. The results reinforce the hypothesis that forests could be significantly altered by the first part of the next century. The modeling also confirms the potential utility of selected time series of fossil pollen data for investigating the poorly understood natural patterns of century-scale climate variability.

Overpeck, Jonathan T.↗

Improvement and extension of a radar forest backscattering model

Radar modeling of mangal forest stands, in the Sundarbans area of Southern Bangladesh, was developed. The modeling employs radar system parameters with forest data on tree height, spacing, biomass, species combinations, and water (including slightly conductive water), content both in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, six model components are proposed, which are required to explain the contributions of various forest species combinations in the attenuation and scattering of mangal vegetated nonflooded or flooded surfaces. Statistical data of simulated images were compared with those of SIR-B images both to refine the modeling procedures and to appropriately characterize the model output. The possibility of delineation of flooded or nonflooded boundaries is discussed.

Simonett, David S.↗

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Tao, W. K.↗

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗

Ice-covered volcanic water flows on Ganymede

The most geologically reasonable model for the origin of grooved terrain on Ganymede involves flooding of a planetary graben system by water or water-ice magmas that rose to the surface along normal faults in the rift zones. To investigate this process further, the thermal evolution of a water flow on Ganymede's surface was examined. The model is a variation of earlier work on ice-covered water flows. It is based on the simplifying assumptions that laminar flow and a concomitant solid ice cover are achieved relatively soon after eruption; and that the amount of energy lost to the substratum is negligible.

Allison, M. L.↗

Electromagnetic reflection from multi-layered snow models

The remote sensing of snow-pack characteristics with surface installations or an airborne system could have important applications in water-resource management and flood prediction. To derive some insight into such applications, the electromagnetic response of multilayered snow models is analyzed in this paper. Normally incident plane waves at frequencies ranging from 1 MHz to 10 GHz are assumed, and amplitude reflection coefficients are calculated for models having various snow-layer combinations, including ice layers. Layers are defined by thickness, permittivity, and conductivity; the electrical parameters are constant or prescribed functions of frequency. To illustrate the effect of various layering combinations, results are given in the form of curves of amplitude reflection coefficients versus frequency for a variety of models. Under simplifying assumptions, the snow thickness and effective dielectric constant can be estimated from the variations of reflection coefficient as a function of frequency.

Linlor, W. I.↗

Radar modeling of tropical mangal forest stands

Radar modeling of mangal forest stands in the Sundarbans area of southern Bangladesh is discussed. The modeling uses radar system parameters with forest data on tree height, spacing, biomass, species combinations, and water content (including slightly conductive water) in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, six model components are proposed; the models are required to explain the contributions of various combinations of forest species in the attenuation and scattering of mangal-vegetated nonflooded or flooded surfaces. Statistical data of simulated images have been compared with those of SIR-B images both to refine the modeling procedures and to characterize the model output appropriately. The possibility of delineation of flooded or nonflooded boundaries is discussed.

Wang, Yong↗

A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet

We consider the scientifically challenging and policy-relevant task of understanding the past and projecting the future dynamics of the Antarctic ice sheet. The Antarctic ice sheet has shown a highly nonlinear threshold response to past climate forcings. Triggering such a threshold response through anthropogenic greenhouse gas emissions would drive drastic and potentially fast sea level rise with important implications for coastal flood risks. Previous studies have combined information from ice sheet models and observations to calibrate model parameters. These studies have broken important new ground but have either adopted simple ice sheet models or have limited the number of parameters to allow for the use of more complex models. These limitations are largely due to the computational challenges posed by calibration as models become more computationally intensive or when the number of parameters increases. Here, we propose a method to alleviate this problem: a fast sequential Monte Carlo method that takes advantage of the massive parallelization afforded by modern high-performance computing systems. We use simulated examples to demonstrate how our sample-based approach provides accurate approximations to the posterior distributions of the calibrated parameters. The drastic reduction in computational times enables us to provide new insights into important scientific questions, for example, the impact of Pliocene era data and prior parameter information on sea level projections. These studies would be computationally prohibitive with other computational approaches for calibration such as Markov chain Monte Carlo or emulation-based methods. We also find considerable differences in the distributions of sea level projections when we account for a larger number of uncertain parameters. For example, based on the same ice sheet model and data set, the 99th percentile of the Antarctic ice sheet contribution to sea level rise in 2300 increases from 6.5 m to 13.1 m when we increase the number of calibrated parameters from three to 11. With previous calibration methods, it would be challenging to go beyond five parameters. Here, this work provides an important next step toward improving the uncertainty quantification of complex, computationally intensive and decision-relevant models.

54 ENVIRONMENTAL SCIENCES↗