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NASA NTRSDate not supplied

Dissemination of Global Surface Water Mapping from SAR and Optical Data to Global Stakeholders

Under NASA Solicitation A.37 “Earth Science Applications: Disaster Risk Reduction and Response,” NASA’s Disasters Program is funding projects focused on flood forecasting, post-event flood mapping, flood depth estimation and pre-event flood severity using Earth observation (EO) datasets (SAR and optical imagery) and derived flood products. A new initiative in the Disasters Program is underway to disseminate the flood products from different sensors to global stakeholders via the Pacific Disaster Center’s DisasterAWARE®, the NASA Disasters Mapping Portal and potentially other mechanisms. This initiative will also generate an integrated flood product(s) using an ensemble approach that will combine outputs from hydrologic models and EO data for different stakeholders globally for decision-making and response efforts.

remote sensing↗
NASA NTRS2012

Overview of US AID-World Bank-NASA Collaboration to Address Water Management Issues in the MENA Region

The World Bank, USAID and NASA have recently established a joint project to study multiple issues pertaining to water related applications in the Middle East North Africa (MENA) region. The main concentration of the project is on utilization of remote sensing data and hydrological models to address crop irrigation and mapping, flood mapping and forecasting, evapotranspiration and drought problems prevalent in this large geographic area. Additional emphases are placed on understanding the climate impact on these areas as well. Per IPCC 2007 report, by the end of this century MENA region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. These observations generate multiple products such as soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gases, ice and snow measurements, and many more. All of the data products, models and research results are distributed-via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, droUght assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Finally, capacity building is a critical part of this project and NASA will assist in this effort as well.

Habib, Shahid↗
NASA NTRS2012

Customizing NASA's Earth Science Research Products for addressing MENA Water Challenges

As projected by IPCC 2007 report, by the end of this century the Middle East North Mrica (MENA) region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. In late 2011, the World Bank, USAID and NASA have joined hands to establishing integrated, modem, up to date NASA developed capabilities for various countries in the MENA region for addressing water resource issues and adapting to climate change impacts for improved decision making for societal benefits. The main focus of this undertaking is to address the most pressing societal issues which can be modeled and solved by utilizing NASA Earth Science remote sensing data products and hydrological models. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. NASA has over fifteen satellites and thirty instruments operating on these space borne platforms and generating over 2000 different science products on a daily basis. Some of these products are soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gasses, ice and snow measurements, and many more. All of the data products, models and research results are distributed via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, drought assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Training is an important component under this activity and adequate level of training will be offered to build basic capacity to work with NASA provided data products, models for their future use. This paper provides a comprehensive introduction to NASA's Earth Science mission for understanding the behavior of our home Planet, projecting its health for future generations and applying research results solving societal issues.

Habib, Shahid↗
DOE OSTI2020

Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information

Reliable near real-time precipitation estimates are essential for monitoring and managing of natural disasters such as floods. Quality of inputs and capability of the retrieval algorithm are two important aspects for developing satellite-based precipitation datasets. Most retrieval algorithms utilize infrared (IR) information as their input due to its fine spatiotemporal resolution and near-instantaneous availability. However, their sole reliance on IR information limits their capability to learn different mechanisms of precipitation during training, resulting in less accurate estimates. Moreover, recent advances in the field of machine learning offer attractive opportunities to improve the precipitation retrieval algorithms. This work investigates the effectiveness of adding geographical information (i.e. latitude and longitude) to IR information and the application of a U-Net-based convolutional neural network for improving the accuracy of retrieval algorithms. This research suggests that applying an appropriate CNN architecture on geographical and IR information provides an opportunity to improve the satellite-based precipitation products.

42 ENGINEERING↗
DOE OSTI2020

Projected changes in seasonal precipitation extremes over the United States in CMIP6 simulations

Quantifying how climate change may impact precipitation extremes is a priority for informing adaptation and policy planning. In this study, Coupled Model Intercomparison Project phase 6 global climate models are analyzed to identify robust signals of projected changes in summer and winter precipitation extremes over the United States (US). Under a projected fossil-fuel based economic (i.e. high greenhouse gas emissions) scenario, our results show consistent changes in the seasonal patterns for many precipitation extremes by the end of the 21st century. We find a robust projected increase in the intensity of winter precipitation across models, with less agreement during the summer. Similarly, a robust projected amplification of heavy precipitation over the northern US is evident in winter, while intermodel spread is prevalent in summer projections. Specifically, the heavy and very heavy winter precipitation days (R10mm and R20mm) exhibit larger increases compared to other aspects of precipitation. Additionally, changes in dry extremes (e.g. consecutive dry days) are found to differ significantly across various subregions and seasons. Overall, our results suggest that the US may suffer more natural disasters such as floods and droughts in the future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

A Geosynchronous Synthetic Aperture Provides for Disaster Management, Measurement of Soil Moisture, and Measurement of Earth-Surface Dynamics

A GEO-based Synthetic Aperture Radar (SAR) could provide daily coverage of basically all of North and South America with very good temporal coverage within the mapped area. This affords a key capability to disaster management, tectonic mapping and modeling, and vegetation mapping. The fine temporal sampling makes this system particularly useful for disaster management of flooding, hurricanes, and earthquakes. By using a fairly long wavelength, changing water boundaries caused by storms or flooding could be monitored in near real-time. This coverage would also provide revolutionary capabilities in the field of radar interferometry, including the capability to study the interferometric signature immediately before and after an earthquake, thus allowing unprecedented studies of Earth-surface dynamics. Preeruptive volcano dynamics could be studied as well as pre-seismic deformation, one of the most controversial and elusive aspects of earthquakes. Interferometric correlation would similarly allow near real-time mapping of surface changes caused by volcanic eruptions, mud slides, or fires. Finally, a GEO SAR provides an optimum configuration for soil moisture measurement that requires a high temporal sampling rate (1-2 days) with a moderate spatial resolution (1 km or better). From a technological point of view, the largest challenges involved in developing a geosynchronous SAR capability relate to the very large slant range distance from the radar to the mapped area. This leads to requirements for large power or alternatively very large antenna, the ability to steer the mapping area to the left and right of the satellite, and control of the elevation and azimuth angles. The weight of this system is estimated to be 2750 kg and it would require 20 kW of DC-power. Such a system would provide up to a 600 km ground swath in a strip-mapping mode and 4000 km dual-sided mapping in a scan-SAR mode.

Madsen, Soren↗
NASA NTRS1979

Briefcase Communicator

In the photo at bottom right, a U.S. Park Police officer is demonstrating a battery-powered communications system, sufficiently compact to be packed in a briefcase-size container, which can send and receive signals over great distances by means of satellite relay. Key to the system's efficacy is the high-powered transmitting and receiving equipment aboard such NASA satellites as the Applications Technology Satellite6 (ATS-6) and the joint U.S.-Canadian Communications Technology Satellite (CTS); this enables the briefcase communicator to pick up satellite-relayed signals by means of the small hook-on antenna shown instead of the more elaborate-ground equipment customarily needed. Developed by NASA's Goddard Space Flight Center, the communicator is intended for use in emergency situations. It has utility, for example, in disasters, such as floods and hurricanes, where power failure disrupts conventional communications; for on-the-spot transmissions from major accident sites; or in remote areas where no other means of communication exists

Source record↗
NASA NTRS2012

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.

Molthan, Andrew L.↗
NASA NTRS2021

Hawai‘i Island Disasters: Using NASA Earth Observations to Assess Coastal Flood Risk with Measures of Land Cover Change, Flood Extent, and Vulnerability for Adaptation and Mitigation Planning on Hawai‘i Island

As the County of Hawai‘i faces an increased risk of extreme flooding events, sea-level rise, and other hazards associated with climate change, the need for building geospatial capacity to make better-informed decisions is critical. The County of Hawai‘i and Arizona State University partnered with NASA DEVELOP to complete a macro-scale risk analysis for the island of Hawai‘i analyzing flooding, land cover, vulnerability, and exposure factors using Earth observations and socio-economic data. The team assessed the variation in urban coastal vulnerability around the entire island of Hawai‘i, using satellite imagery of coastal land cover typology from satellite products such as Landsat 8 Operational Land Imager (OLI), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Sentinel-1 Synthetic Aperture Radar (SAR). The team made a sharable geodatabase containing datasets modeling vulnerability to coastal flooding as well as the Hawai‘i Flood Risk Toolbox (HiFloRT) which contains multiple tools for the County to map land cover, extreme rainfall and flood extent across the Island. The end products will allow the County of Hawai‘i to establish a protocol and standard framework for the utilization of Earth observations in future planning.

Garren Kalter↗
DOE OSTI2023

Field surveying data of low-cost networked flood sensors in southeast Texas

Floods are common natural disasters worldwide and pose substantial risks to life, property, food production, and natural resources. Effective measures for flood mitigation and warning are essential. Southeast Texas is still at significant risk of flooding, and Lamar University is assisting the region with asset management of a flood sensor network for flooding events. This network provides real-time water stage information. Lamar University developed a survey program to measure elevation and coordinates at each sensor site location to make this data more useful for flood monitoring and mapping. This paper overviews the measurement of the elevation and coordinates of 74 networked flood sensors and various flood stage thresholds at critical points that flood decision-makers can use for reference at each site. In the first phase of this program, these sensors were deployed throughout a 7-county region spanning nearly 6,000 square miles in Southeast Texas. The latitude and longitude of the sensors and their elevations were determined using survey-grade Global Navigation Satellite System (GNSS) technology. Various Continually Operating Reference Stations (CORS) were utilized for post-processing to achieve sub-inch resolution. The flood stage thresholds, water level sensors elevation, and the elevations and positions of other critical surrounding points are viewable to the public through two online repositories and a web-based sensor management dashboard. The data is used to aid with decisions related to road closures or modeling efforts by mitigation decision-makers, emergency managers, and the public, including the Texas Department of Transportation, Houston Transtar, the National Weather Service, and the Sabine River Authority of Texas (SRA).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

A digital simulation of message traffic for natural disaster warning communications satellite

Various types of weather communications are required to alert industries and the general public about the impending occurrence of tornados, hurricanes, snowstorms, floods, etc. A natural disaster warning satellite system has been proposed for meeting the communications requirements of the National Oceanic and Atmospheric Administration. Message traffic for a communications satellite was simulated with a digital computer in order to determine the number of communications channels to meet system requirements. Poisson inputs are used for arrivals and an exponential distribution is used for service.

Hein, G. F.↗
NASA NTRS2010

Namibian Flood Early Warning SensorWeb Pilot

The major goal of the Namibia SensorWeb Pilot Project is a scientifically sound, operational trans-boundary flood management decision support system for Southern African region to provide useful flood and waterborne disease forecasting tools for local decision makers. The Pilot Project established under the auspices of: Namibian Ministry of Agriculture Water and Forestry (MAWF), Department of Water Affairs; Committee on Earth Observing Satellites (CEOS), Working Group on Information Systems and Services (WGISS); and moderated by the United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER). The effort consists of identifying and prototyping technology which enables the rapid gathering and dissemination of both space-based and ground sensor data and data products for the purpose of flood disaster management and water-borne disease management.

Mandl, Daniel↗
NASA NTRS2017

Automated Mapping of Flood Events in the Mississippi River Basin Utilizing NASA Earth Observations

The Mississippi River Basin is the fourth largest drainage basin in the world, and is susceptible to multi-level flood events caused by heavy precipitation, snow melt, and changes in water table levels. Conducting flood analysis during periods of disaster is a challenging endeavor for NASA's Short-term Prediction Research and Transition Center (SPoRT), Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey's Hazards Data Distribution Systems (USGS HDDS) due to heavily-involved research and lack of manpower. During this project, an automated script was generated that performs high-level flood analysis to relieve the workload for end-users. The script incorporated Landsat 8 Operational Land Imager (OLI) tiles and utilized computer-learning techniques to generate accurate water extent maps. The script referenced the Moderate Resolution Imaging Spectroradiometer (MODIS) land-water mask to isolate areas of flood induced waters. These areas were overlaid onto the National Land Cover Database's (NLCD) land cover data, the Oak Ridge National Laboratory's LandScan data, and Homeland Infrastructure Foundation-Level Data (HIFLD) to determine the classification of areas impacted and the population density affected by flooding. The automated algorithm was initially tested on the September 2016 flood event that occurred in Upper Mississippi River Basin, and was then further tested on multiple flood events within the Mississippi River Basin. This script allows end users to create their own flood probability and impact maps for disaster mitigation and recovery efforts.

Bartkovich, Mercedes↗
NASA NTRS2016

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster (United Nations 2004), causing approximately6.8 million deaths in the twentieth century alone (Doocy et al. 2013).Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD(Munich Re 2013). Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries (Davies et al. 2014).Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change (IPCC 2007). Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assessflooding and extend analytical methods to estimate impacted population and infrastructure.

flood↗
NASA NTRS2019

Evaluating Flood Forecasting System Performance in Cambodia During the 2019 Flood Season

Every year, Cambodia experiences both flash and prolonged riverine flooding as a result of monsoon rains and typhoons. Floods occur frequently in various parts of the region, and result in significant economic cost. Flood forecasting systems are designed to mitigate economic and social impacts, enabling people to prepare for extreme events. However, in order for forecasts to be used effectively, an assessment of the available forecasting systems is needed. In addition, following the onset of flooding, satellite imagery is used to generate flood maps to aid in response efforts. This study demonstrates the performance of regional and global flood forecasting systems over the 2019 flood season. To do this, we assess the flood forecast accuracy at different forecast lead times through a series of forecast verification metrics at gauge locations in Cambodia. We then compare the flood forecast performance to Sentinel 1 flood maps produced by the Hydrological Remote Sensing Analysis of Floods (HYDRAFloods) tool currently being co-developed by SERVIR-Mekong in collaboration with the Myanmar Department of Disaster Management. This assessment of the flood forecasting systems’ performance and comparison to generated flood maps helps provide context to forecasters and disaster managers as they make improvements to their models. Additionally, these results provide support to forecast users as they evaluate the strengths and weaknesses of different systems for taking action.

Nauman, Claire M.↗
DOE OSTI2020

PERSIANN Dynamic Infrared–Rain Rate Model (PDIR) for High-Resolution, Real-Time Satellite Precipitation Estimation

Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; and weather, climate, and hydrological forecasting. Moreover, real-time precipitation estimation with high precision is pivotal for the monitoring and managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data as input are attractive owing to their rich spatiotemporal resolution and near-instantaneous availability, their sole reliance on cloud-top brightness temperature (T b ) readings causes underestimates in wet regions and overestimates in dry regions—this is especially evident over the western contiguous United States (CONUS). We introduce an algorithm, the Precipitation Estimations from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain rate model (PDIR), which utilizes climatological data to construct a dynamic (i.e., laterally shifting) T b –rain rate relationship that has several notable advantages over other quantitative precipitation-estimation algorithms and noteworthy skill over the western CONUS. Validation of PDIR over the western CONUS shows a promising degree of skill, notably at the annual scale, where it performs well in comparison to other satellite-based products. Analysis of two extreme landfalling atmospheric rivers show that solely IR-based PDIR performs reasonably well compared to other IR- and PMW-based satellite rainfall products, marking its potential to be effective in real-time monitoring of extreme storms. This research suggests that IR-based algorithms that contain the spatiotemporal richness and near-instantaneous availability needed for rapid natural hazards response may soon contain the skill needed for hydrologic and water resource applications.

54 ENVIRONMENTAL SCIENCES↗