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NASA NTRS2016

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. 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. 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 assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

Ahamed, Aakash↗

NASA NTRS2016

Impact of the Timing of a SAR Image Acquisition on the Calibration of a Flood Inundation Model

Synthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modeled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.

Flood inundation↗

NASA NTRS2013

International Space Station Instmments Collect Imagery of Natural Disasters

A new focus for utilization of the International Space Station (ISS) is conducting basic and applied research that directly benefits Earth's citizenry. In the Earth Sciences, one such activity is collecting remotely sensed imagery of disaster areas and making those data immediately available through the USGS Hazards Data Distribution System, especially in response to activations of the International Charter for Space and Major Disasters (known informally as the "International Disaster Charter", or IDC). The ISS, together with other NASA orbital sensor assets, responds to IDC activations following notification by the USGS. Most of the activations are due to natural hazard events, including large floods, impacts of tropical systems, major fires, and volcanic eruptions and earthquakes. Through the ISS Program Science Office, we coordinate with ISS instrument teams for image acquisition using several imaging systems. As of 1 August 2013, we have successfully contributed imagery data in support of 14 Disaster Charter Activations, including regions in both Haiti and the east coast of the US impacted by Hurricane Sandy; flooding events in Russia, Mozambique, India, Germany and western Africa; and forest fires in Algeria and Ecuador. ISS‐based sensors contributing data include the Hyperspectral Imager for the Coastal Ocean (HICO), the ISERV (ISS SERVIR Environmental Research and Visualization System) Pathfinder camera mounted in the US Window Observational Research Facility (WORF), the ISS Agricultural Camera (ISSAC), formerly operating from the WORF, and high resolution handheld camera photography collected by crew members (Crew Earth Observations). When orbital parameters and operations support data collection, ISS‐based imagery adds to the resources available to disaster response teams and contributes to the publicdomain record of these events for later analyses.

Evans, C. A.↗

NASA NTRS1995

The circum-Chryse region as a possible example of a hydrologic cycle on Mars: Geologic observations and theoretical evaluation

Moore, Jeffrey M.↗

NASA NTRS1995

The circum-Chryse region as a possible example of a hydrologic cycle on Mars: Geologic observations and theoretical evaluation

The transection and superposition relationships among channels, chaos, surface materials units, and other features in the circum-Chryse region of Mars were used to evaluate relative age relationships and evolution of flood events. Channels and chaos in contact (with one another) were treated as single discrete flood-carved systems. Some outflow channel systems form networks and are inferred to have been created by multiple flood events. Within some outflow channel networks, several separate individual channel systems can be traced to a specific chaos which acted as flood-source area to that specific flood channel. Individual flood-carved systems were related to widespread materials units or other surface features that served as stratigraphic horizons. Chryse outflow channels are inferred to have formed over most of the perceivable history of Mars. Outflow channels are inferred to become younger with increasing proximity to the Chryse basin. In addition, outflow channels closer to the basin show a greater diversity in age. The relationship of subsequent outflow channel sources to the sources of earlier floods is inferred to disfavor episodic flooding due to the progressive tapping of a juvenile near-surface water supply. Instead, we propose the circum-Chryse region as a candidate site of past hydrological recycling. The discharge rates necessary to carve the circum-Chryse outflow channels would have inevitably formed temporary standing bodies of H2O on the Martian surface where the flood-waters stagnated and pooled (the Chryse basin is topographically enclosed). These observations and inferences have led us to formulate and evaluate two hypotheses: (1) large amounts of the sublimated H2O off the Chryse basin flood lakes precipitated (snowed) onto the flood-source highlands and this H2O was incorporated into the near surface, recharging the H2O sources, making possible subsequent deluges; and (2) ponded flood-water in Chryse basin drained back down an anti basinward dipping subsurface layer accessed along the southern edge of the lake, recharging the flood-source aquifers. H2O not redeposited in the flood-source region was largely lost to the hydrologic cycle. This loss progressively lowered the vitality of the cycle, probably by now killing it. Our numerical evaluations indicate that of the two hypotheses we formulated, the groundwater seep cycle seems by far the more viable. Optimally, approx. 3/4 of the original mass of an ice-covered cylindrical lake (albedo 0.5, 1 km deep, 100-km radius, draining along its rim for one quarter of its circumference into substrata with a permeability of 3000 darcies) can be modeled to have moved underground (on timescales of the order of 10(exp 3) years) before the competing mechanisms of sublimation and freeze down choked off further water removal. Once underground, this water can travel distances equal to the separation between Chryse basin and flood-source sites in geologically short (approx. 10(exp 6) year-scale) times. Conversely, we calculate that optimally only approx. 40% of the H2O carried from Chryse can condense at the highlands, and most of the precipitate would either collect at the base of the highlands/lowlands scarp or sublimate at rates greater than it would accumulate over the flood-source sites. Further observations from forthcoming missions may permit the determination of which mechanisms may have operated to recycle the Chryse flood-waters.

Moore, Jeffrey M.↗

NASA NTRS1995

The Circum-Chryse Region as a Possible Example of a Hydrologic Cycle on Mars: Geologic Observations and Theoretical Evaluation

The transection and superposition relationships among channels, chaos, surface materials units, and other features in the circum-Chryse region of Mars were used to evaluate relative age relationships and evolution of flood events. Channels and chaos in contact (with one another) were treated as single discrete flood-carved systems. Some outflow channel systems form networks and are inferred to have been created by multiple flood events. Within some outflow channel networks, several separate individual channel systems can be traced to a specific chaos which acted as flood-source area to that specific flood channel. Individual flood-carved systems were related to widespread materials units or other surface features that served as stratigraphic horizons. Chryse outflow channels are inferred to have formed over most of the perceivable history of Mars. Outflow channels are inferred to become younger with increasing proximity to the Chryse basin. In addition, outflow channels closer to the basin show a greater diversity in age. The relationship of subsequent outflow channel sources to the sources of earlier floods is inferred to disfavor episodic flooding due to the progressive tapping of a juvenile near-surface water supply. Instead, we propose the circum-Chryse region as a candidate site of past hydrological recycling. The discharge rates necessary to carve the circum-Chryse outflow channels would have inevitably formed temporary standing bodies of H2O on the Martian surface where the flood-waters stagnated and pooled (the Chryse basin is topographically enclosed). These observations and inferences have led us to formulate and evaluate two hypotheses: (1) large amounts of the sublimated H2O off the Chryse basin flood lakes precipitated (snowed) onto the flood-source highlands and this H2O was incorporated into the near surface, recharging the H2O sources, making possible subsequent deluges; and (2) ponded flood-water in Chryse basin drained back down an anti basinward dipping subsurface layer accessed along the southern edge of the lake, recharging the flood-source aquifers. H2O not redeposited in the flood-source region was largely lost to the hydrologic cycle. This loss progressively lowered the vitality of the cycle, probably by now killing it. Our numerical evaluations indicate that of the two hypotheses we formulated, the groundwater seep cycle seems by far the more viable. Optimally, approximately 3/4 of the original mass of an ice-covered cylindrical lake (albedo 0.5, 1 km deep, 100-km radius, draining along its rim for one quarter of its circumference into substrata with a permeability of 3000 darcies) can be modeled to have moved underground (on timescales of the order of 10(exp 3) years) before the competing mechanisms of sublimation and freeze down choked off further water removal. Once underground, this water can travel distances equal to the separation between Chryse basin and flood-source sites in geologically short (approximately 10(exp 6) year-scale) times. Conversely, we calculate that optimally only approximately 40% of the H2O carried from Chryse can condense at the highlands, and most of the precipitate would either collect at the base of the highlands/lowlands scrap or sublimate at rates greater than it would accumulate over the flood-source sites. Further observations from forthcoming missions may permit the determination of which mechanisms may have operated to recycle the Chryse flood-waters.

Moore, Jeffrey M.↗

NASA NTRS2023

Youngstown and Warren Disasters: Mapping Flood Susceptibility, Vulnerability, and Risk and Tree Canopy Coverage in Northern Ohio to Inform Stormwater Management and Flood Mitigation Efforts

Both pluvial and fluvial flooding events pose direct challenges on urban infrastructure and communities across the United States. Heavy rainfall events oversaturate the ground, overflow waterbodies, and overwhelm stormwater infrastructure. Vulnerable areas receive heavy damage from flooding events due to physical factors like increased impervious surfaces, poor stormwater systems, and limited greenspaces. These vulnerable neighborhoods are comprised of aging populations, minority communities, and lower income levels. Lack of data in these communities have made it difficult to implement policymaking and flood mitigation strategies. Using the Urban Flood Risk Mitigation model (InVEST) and the PlanetScope satellite constellation, the team visualized historical flooding and tree canopy coverage as a measure of flood susceptibility. The team also used the Arc-Malstrom model to provide further insight into where flooding accumulates via surface elevation depressions in the study area. To validate these models, the team explored the spatial variation of rainfall events using NASA’s Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG). The resulting maps highlight areas surrounding the cities of Youngstown and Warren as being the most flood susceptible and socially vulnerable, while the city centers contain the lowest tree canopy coverage. The DEVELOP team collaborated with the Environmental Collaborative of Ohio (ECO) to create products for end users within the City of Warren’s Water Pollution Control Department, the Eastgate Regional Council of Governments and the Healthy Community Partnership of Mahoning Valley. These products help identify target areas for preventative flood mitigation measures as well as areas ideal for green infrastructure intervention.

InVEST Urban Flood Risk Mitigation Model↗

NASA NTRS2023

Real Options Analysis for Valuation of Climate Adaptation Pathways With Application to Transit Infrastructure

Climate change and sea level rise (SLR) are expected to increase the frequency and intensity of coastal flood events, posing risks to coastal communities and infrastructure. While regional climate adaptation investments can provide substantive flood protection, existing plans often neglect uncertainty in future climate conditions and adaptation performance, consequently neglecting the option value of flexibly implementing proposed projects. Addressing this gap, we develop and employ a generalizable real options analysis (ROA) valuation framework that considers how uncertainty in adaptation project costs, SLR, flood severity, and flood losses inform the full range of adaptation performance outcomes. We further propose and apply a novel, computationally efficient flood loss sampling algorithm to estimate the consequences of randomly arriving coastal flood events. We apply this ROA framework to assess the option value of flexibly timing adaptation investments over time, investigating an adaptation pathway proposed by the City of Boston from the perspective of the regional transit system manager. Our results suggest that flexible implementation can provide significant option value in the near-to mid-term(>30 years), with highest option values under low-probability, high consequence scenarios. Our results also suggest adaptation pathway performance in the latter half of the 21stcenturyis most sensitive to uncertainty in sea level rise, flood loss estimates, and flood frequency, underscoring the importance of uncertainty quantification in the long-term valuation of adaptation investments.

Michael V. Martello↗

NASA NTRS2018

Future Nuisance Flooding in Norfolk, VA, From Astronomical Tides and Annual to Decadal Internal Climate Variability

Abstract Increasing sea level rise will lead to more instances of nuisance flooding along the Virginia coastline in the coming decades, causing road closures and deteriorating infrastructure. These minor flood events can be caused by astronomical tides alone, in addition to internal climate variability on annual to decadal timescales. An assessment of nuisance flooding from these two effects is presented up until the year2050 for Norfolk, Virginia. The analysis of water levels indicates that nuisance flooding from tides alone in conjunction with a medium-high sea level scenario will result in flooding beginning in 2030 with frequency increasing thereafter. The addition of climate variability, by use of an empirical mode decomposition, leads to a substantial increase of flooding relative to the tides-alone analysis and shows flood events beginning as soon as 2020. High tides in the future will produce nuisance flooding without the need of other drivers such as coastal storms.

Burgos, A. G.↗

NASA NTRS2004

High-Resolution Mesoscale Simulations of the 6-7 May 2000 Missouri Flash Flood: Impact of Model Initialization and Land Surface Treatment

High-resolution mesoscale model simulations of the 6-7 May 2000 Missouri flash flood event were performed to test the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation. In this flash flood event, a mesoscale convective system (MCS) produced over 340 mm of rain in roughly 9 hours in some locations. Two different types of model initialization were employed: 1) NCEP global reanalysis with 2.5-degree grid spacing and 12-hour temporal resolution, and 2) Eta reanalysis with 40- km grid spacing and $hour temporal resolution. In addition, two different land surface treatments were considered. A simple land scheme. (SLAB) keeps soil moisture fixed at initial values throughout the simulation, while a more sophisticated land model (PLACE) allows for r interactive feedback. Simulations with high-resolution Eta model initialization show considerable improvement in the intensity of precipitation due to the presence in the initialization of a residual mesoscale convective vortex (hlCV) from a previous MCS. Simulations with the PLACE land model show improved location of heavy precipitation. Since soil moisture can vary over time in the PLACE model, surface energy fluxes exhibit strong spatial gradients. These surface energy flux gradients help produce a strong low-level jet (LLJ) in the correct location. The LLJ then interacts with the cold outflow boundary of the MCS to produce new convective cells. The simulation with both high-resolution model initialization and time-varying soil moisture test reproduces the intensity and location of observed rainfall.

Baker, R. David↗

NASA NTRS2019

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗

NASA NTRS2015

Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential

We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA's Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE's coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information.

flood↗

NASA NTRS2016

Optical and Physical Methods for Mapping Flooding with Satellite Imagery

Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

satellite imagery↗

NASA NTRS2001

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/South China Sea (SCS)/China, North America and South America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, PLACE allows for the effect A vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1991 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the South China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗

NASA NTRS2002

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗

NASA NTRS2019

Terrestrial Water Storage

Terrestrial water storage can be defined as the summation of all water on the land surface and in the subsurface. It includes surface soil moisture, root zone soil moisture, groundwater, snow,ice, water stored in the vegetation, river and lake water. Terrestrial water storage (TWS) changes have been observed by the Gravity Recovery and Climate Experiment (GRACE) mission since 2002. GRACE has provided an unprecedented view of the terrestrial water storage variations at large scales. Extremes in water storage often are associated with droughts and flooding events because they are driven by the surplus or deficit of water. Few hydrologic observing networks yield sufficient data for comprehensive monitoring of changes in the total amount of water stored in a region. GRACE observations have helped to fill this gap. This book chapter is divided into 4 sections.Section 1 provides an overview of the GRACE mission. Section 2 reviews the terrestrial water storage solutions that are available. Section 3 describes regional to global applications of GRACE for monitoring extremes in the terrestrial water storage, including droughts and flooding events. Conclusions and future directions are reported in Section 4.

Terrestrial Water Storage↗

NASA NTRS2021

Northern Great Plains Disasters: Using Earth Observations to Enhance Flood Monitoring on Tribal Lands in the Northern Great Plains

In 2019, the Great Plains experienced unprecedented catastrophic flooding. Large flood events are predicted to increase in frequency and severity, posing risks to communities in this region, particularly Tribal Nations. We used data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), imagery from the Sentinel-2 MultiSpectral Instrument (MSI), and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) within Google Earth Engine to map historical floods in the region beginning in 2014 with particular attention to the Rosebud Sioux Reservation and the tribal lands of other Great Plains Tribal Water Alliance members. This historical mapping used C-SAR for a combined method approach with a Z-score algorithm in addition to an index for flooded short vegetation. We also developed a flood risk map by weighting different flood predictor variables according to flood risk literature. These variables included soil drainage from the Soil Survey Geographic Database (SSURGO); elevation, slope, and Topographic Wetness Index (TWI) derived from digital elevation models; precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS); land cover from the National Land Cover Database (NLDC); and Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 Operational Land Imager (OLI). From the flood extent and risk maps, we identified widespread flooding in short vegetation (including cropland) and noted flood susceptibility in regions exhibiting high social vulnerability and low community resilience (FEMA indices). We created an ArcGIS Online StoryMap to share project background, results, and data. Additionally, we provided a written tutorial so partners may replicate the flood mapping for future flood events.

Anna Ballasiotes↗

NASA NTRSDate not supplied

Hourly Stream Heights – A Short-term Deep Learning Prediction Model

River flooding can have a detrimental impact on a community by causing loss of life, loss or damage to property, and damage to infrastructure. Having the capability to forecast flooding events can prevent the loss of life and mitigate damage to property. A programmatic, data-driven approach using deep learning to forecast a stream’s gauge height every 6 hours has been developed by NASA’s Short-term Prediction Research and Transition Center (SPoRT) and is currently in operation. Based on our end user engagement and feedback, this medium-term product has been successfully adopted by several National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC). SPoRT is currently researching and developing a short-term hourly deep learning model which will be useful in forecasting flash flood events.

Michael Antia↗