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Isothermal elastohydrodynamic lubrication of point contacts. IV - Starvation results

Previously developed basic theory for isothermal elastohydrodynamic lubrication of point contacts is used to study the effect of lubricant starvation on pressure and film thickness within the conjunction. A simple expression for the dimensionless inlet boundary distance is derived. This inlet boundary distance defines whether a fully flooded or a starved condition exists in the contact. Simple expressions for the minimum and central film thickness under starvation condition are presented. Contour plots of pressure and film thickness in and around the contact are shown in order to gain a better insight into what occurs in going from fully flooded to lubricant starvation condition. Theoretical predictions are compared with earlier results.

Hamrock, B. J.↗

The contribution of space observations to water resources management; Proceedings of the Symposium, Bangalore, India, May 29-June 9, 1979

The symposium focused on hydrology, soil moisture estimation and ground water exploration, wetlands monitoring and water quality estimation, hydrometeorology, snow and ice monitoring, and evapotranspiration estimation. Other problems discussed include surface water and flood mapping, watershed runoff estimation and prediction, and new space systems contributing to water resources management.

Salomonson, V. V.↗

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Reichle, Rolf↗

Assimilation of Smos Observations to Generate a Prototype SMAP Level 4 Surface and Root-Zone Soil Moisture Product

The Soil Moisture Active and Passive (SMAP; [1]) mission is being implemented by NASA for launch in October 2014. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high-resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. The Soil Moisture and Ocean Salinity (SMOS; [2]) mission was launched by ESA in November 2009 and has since been observing L-band (1.4 GHz) upwelling passive microwaves. In this paper we describe our use of SMOS brightness temperature observations to generate a prototype of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product [5].

Reichle, Rolf H.↗

Anticipated Improvements in Precipitation Physics and Understanding of Water Cycle from GPM Mission

The GPM mission is currently planned for start in the late-2007 to early-2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation s orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, involving existing, pending, projected, and under-study partnerships which will link NASA and NOAA in the US, NASDA in Japan, ESA in Europe, ISRO in India, CNES in France, and possibly AS1 in Italy, KARI in South Korea, CSA in Canada, and AEB in Brazil. Additionally, the program is actively pursuing agreements with other international collaborators and domestic scientific agencies and institutions, as well as participation by individual scientists from academia, government, and the private sector to fulfill mission goals and to pave the way for what is expected to become an internationally-organized operational global precipitation observing system. Notably, the broad societal applications of GPM are reflected in the United Nation s identification of GPM as a foremost candidate for its Peaceful Uses of Space Program. An overview of the GPM mission design is given, followed by an explanation of its scientific agenda as an outgrowth of making improvements in rain retrieval accuracy, microphysics dexterity, sampling frequency, and global coverage. All of these improvements offer new means to observe variability in precipitation and water cycle fluxes and to achieve improved predictability of weather, climate, and hydrometeorology. Specifically, the scientific agenda of GPM has been designed to leverage the measurement improvements to improve prognostic model performance, particularly quantitative precipitation forecasting and its linked phenomena at short, intermediate, and extended time scales. The talk addresses how GPM measurements will enable better detection of accelerations and decelerations in regional and global water cycle processes and their relationship to climate variability, better impacts of precipitation data assimilation on numerical weather prediction and global climate reanalysis, and better performance from basin scale hydrometeorological models for short and long term flood-drought forecasting and seasonal fresh water resource assessment. These improvements become possible by using more accurate, more microphysically-centric, more frequent, and fully global precipitation observations to achieve better water budget closure and to provide more realistic forcing and assessment of prediction models.

Smith, Eric A.↗

Neglecting Model Parametric Uncertainty Can Drastically Underestimate Flood Risks

Abstract Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi‐sector dynamics and the design of risk‐management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns, for example, the uncertainties surrounding the model parameters. This approach neglects the impacts of key uncertainties on hazards and system dynamics. Here we mainstream a recently developed method for Bayesian inference to calibrate a computationally expensive distributed hydrologic model. We compare three different calibration approaches: (a) stepwise line search, (b) precalibration or screening, and (c) the Fast Model Calibrations (FaMoS) approach. FaMoS deploys a particle‐based approach that takes advantage of the massive parallelization afforded by modern high‐performance computing systems. We quantify how neglecting parametric uncertainty and data discrepancy can drastically underestimate extreme flood events and risks. Precalibration improves prediction skill score over a stepwise line search. The Bayesian calibration improves the uncertainty characterization of model parameters and flood risk projections.

54 ENVIRONMENTAL SCIENCES↗

Evaluating near-real time satellite flood mapping for humanitarian early action: a case study on the 2020 Cambodia floods

Forecast-based early action is an increasingly popular framework advocating for the use of numerical weather prediction to set objective, automatic conditions for roll-out of proactive flood risk reduction efforts. Within this field, there is a relatively young discourse regarding the potential value of satellite Earth observations and the optimal role that remote sensing should play in improving the efficacy and value of forecast-based early action for flood management. The Hydrological Remote Sensing Analysis for Floods tool (HYDRAFloods) was developed to provide automated, near real-time satellite-based flood extent maps to local governments, disaster managers, and humanitarian organizations. This research evaluates (a.) whether HYDRAFloods satisfactorily met needs identified by humanitarian partners during the October 2020 floods in Cambodia, and (b.) whether the novel additions of near real-time data and flood extent mapping resulted in demonstrable advantages over previous forecast-based flood early action systems as identified in the literature. From these results, the authors identify the technological and logistical limitations of the HYDRAFloods methodology and synthesize actionable recommendations for Earth observations practitioners seeking to better support forecast-based early action.

floods↗

Leveraging Improvements in Precipitation Measuring from GPM Mission to Achieve Prediction Improvements in Climate, Weather and Hydrometeorology

The main scientific goal of the GPM mission, currently planned for start in the 2007 time frame, is to investigate important scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like "core" satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing Operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, currently involving a partnership between NASA in the US and the National Space Development Agency in Japan. Additionally, the program is actively pursuing agreements with other international partners and domestic scientific agencies and institutions, as well as participation by individual scientists from academia, government, and the private sector to fulfill mission goals and to pave the way for what ultimately is expected to become an internationally-organized operational global precipitation observing system. Notably, the broad societal applications of GPM are reflected in the United Nation s identification of this mission as a foremost candidate for its Peaceful Uses of Space Program. In this presentation, an overview of the GPM mission design will be presented, followed by an explanation of its scientific agenda as an outgrowth of making improvements in rain retrieval accuracy, microphysics dexterity, sampling frequency, and global coverage. All of these improvements offer new means to observe variability in precipitation and water cycle fluxes and to achieve improved predictability of weather, climate, and hydrometeorology. Specifically, the scientific agenda of GPM has been designed to leverage the measurement improvements to improve prognostic model performance, particularly quantitative precipitation forecasting and its linked phenomena at short, intermediate, and extended time scales. The talk will address how GPM measurements will enable better detection of accelerations and decelerations in regional and global water cycle processes and their relationship to climate variability, better impacts of precipitation data assimilation on numerical weather prediction and global climate reanalysis, and better performance from basin scale hydrometeorological models for short and long term flood-drought forecasting and seasonal fresh water resource assessment. Improved hydrometeorological forecasting will be possible by using continuous global precipitation observations to obtain better closure in water budgets and to generate more realistic forcing of the models themselves to achieve more accurate estimates of interception, infiltration, evaporation/transpiration fluxes, storage, and runoff.

Smith, Eric A.↗

Soil Moisture and Mesoscale Convective Complex Development During the 1993 US Midwest Flood: Results from the MM5-PLACE Atmosphere/Land-Surface Model

The 1993 US Midwest Flood produced record levels of flooding, in the Mississippi River Basin. This flooding resulted from repeated frontal passages and mesoscale convective complexes (MCCs) during the months of June and July. A better understanding of processes that influenced MCC development during the 1993 Flood may lead to improved forecasts of heavy precipitation and flooding. Here, we consider the impact of soil moisture on MCC development during a two-day period (June 23-24) of the 1993 US Midwest Flood. The purpose of this study is to assess the importance of soil moisture distribution on the timing, intensity, and location of heavy precipitation. In this study, the MM5-PLACE Atmosphere/Land-Surface Model is utilized. The atmospheric component consists of the Penn State/NCAR MM5 mesoscale model, and the land-surface component consists of the Goddard Parameterization for Land Atmosphere-Cloud Exchange (PLACE). Initial soil moisture is provided from two sources: 1) NCEP reanalysis, and 2) Antecedent Precipitation Index (API) using NOAA rain gauge measurements as a proxy for soil moisture. NCEP reanalysis provides coarse resolution initial soil moisture (2.5 degree), while API provides high resolution initial soil moisture (10-200 km depending on NOAA rain gauge spacing). Initial results indicate that the distribution of soil moisture has a significant impact on the timing and location of heavy precipitation during this two-day flood event. Precipitation in simulations with high resolution initial soil moisture agrees more closely with observed precipitation. These results suggest that high resolution soil moisture observations are necessary to accurately predict severe storm development, heavy precipitation, and subsequent flooding.

Baker, R. David↗

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Hong, Yang↗

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗

Variability in soil redox response to seasonal flooding in a vernal pond

Vernal ponds are ephemeral landscape features that experience intermittent flooding and drying, leading to variable saturation in underlying soils. Redox potential (E h ) is an important indicator of biogeochemical processes that changes in response to these hydrological shifts; however, high-resolution measurements of E h in variably inundated environments remain sparse. In this study, the responses of soil E h to ponding, drying, and rewetting of a vernal pond were investigated over a 5-month period from late spring through early autumn. Soil E h was measured at 10-min frequencies and at multiple soil depths (2–48 cm below the soil surface) in shallow and deep sections within the seasonally ponded lowland and in unsaturated soils of the surrounding upland. Over the study period, average E h in surface soils (0–8 cm) was oxidizing in the upland (753 ± 79 mV) but relatively reducing in the shallow lowland (369 ± 49 mV) and deep lowland (198 ± 37 mV). Reducing conditions (E h <300 mV) in surface soils prevailed for up to 6 days in the shallow lowland and up to 24 days in the deep lowland after surface water dried out. Intermittent reflooding resulted in multiple shifts between reducing and oxidizing conditions in the shallow lowland while the deep lowland remained reducing following reflooding. Soil E h in the uplands was consistently oxidizing over the study period with transient increases in response to rain events. Reducing conditions in the lowland resulted in greater Fe-oxide dissolution and release of dissolved Fe and P into porewater than in the surrounding uplands. We determined that change in water depth alone was not a good indicator of soil E h , and additional factors such as soil saturation and clay composition should be considered when predicting how E h responds to surface flooding and drying. These findings highlight the spatial and temporal variability of E h within ponds and have implications for how soil processes and ecosystem function are impacted by shifts in hydrology at terrestrial-aquatic interfaces.

54 ENVIRONMENTAL SCIENCES↗

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

Limaye, Ashutosh S.↗

A Physical Validation Program for the GPM Mission

The GPM mission is currently planned for start in the late 2007 - early 2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycling. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. A major requirement before the retrieved rainfall information generated by the GPM mission can be used effectively by prognostic models to improve weather forecasts, hydrometeorological forecasts, and climate model reanalysis simulations is a capability to quantify the error characteristics of the retrievals. A solution for this problem has been upheld in past precipitation missions because of the lack of suitable error modeling systems incorporated into the validation programs and data distribution systems. An overview of how NASA intends to overcome this problem for the GPM mission using a physically-based error modeling approach within a multi-faceted validation program is described. The solution is to first identify specific user requirements and then determine the most stringent of these requirements that embodies all essential error characterization information needed by the entire user community. In the context of NASA s scientific agenda for the GPM mission, the most stringent user requirement is found within the data assimilation community. The fundamental theory of data assimilation vis-a-vis ingesting satellite precipitation information into the pre-forecast initializations is based on quantifying the conditional bias and precision errors of individual rain retrievals, and the space-time structure of the precision error (i.e., the spatial-temporal error covariance). By generating the hardware and software capability to produce this information in a near real-time fashion, and to couple the derived quantitative error properties to the actual retrieved rainrates, all key validation users can be satisfied. The talk will describe the essential components of the hardware and software systems needed to generate such near real-time error properties, as well as the various paradigm shifts needed within the validation community to produce a validation program relevant to the precipitation user community.

Smith, Eric A.↗

SMAP Mission Status, New Products, and Extended-Phase Goals

NASA's Soil Moisture Active Passive (SMAP) Project now has completed its prime-phase (three years) mission and has entered a new five-year extended phase. The global L-band radiometry from SMAP has enabled diverse scientific investigations in water, energy and carbon cycle research, terrestrial ecology and ocean science. These include eliciting the role of soil moisture control on the evaporation regime and vegetation gross primary productivity, observing soil-vegetation continuum water relations, analysis of flood and droughts, climate modeling and weather prediction, detecting ocean high-winds during tropical storms, and observing fresh-water outflow in coastal oceans. This paper highlights the recent enhancements to the SMAP suite of science products (from instrument level-1 to geophysical retrievals level-2 and level-3).

NASA Soil Moisture Active Passive (SMAP)↗

Linkages between riverine flooding risk and economic damage over the continental United States

Economic damages from riverine flooding are expected to grow because of climate change. Yet, there are few 7 studies analyzing flooding damages in the U.S. that clearly measure the roles of hazard, exposure, and vulnerability 8 separately and locally. A lack of this knowledge prohibits spatially detailed predictions of future damages. By being 9 able to separate into these three risk factors, we provide all necessary inputs for uncertainty analysis of the flooding-10 damages forecasts that can incorporate new predictive scenarios for each component. To analyze the flooding risk 11 factors of non-coastal counties within the contiguous U.S. between 1999-2018, we gathered information on (1) 12 property and human damages from flooding, (2) maximum annual river discharge, (3) the number of housing units 13 and the years in which they were built, and (4) the incidence of flooding events. We used the method of trimmed 14 least absolute deviated and trimmed least square estimators to obtain the individual impact of hazard, exposure, and 15 vulnerability in the context of censored flooding damages for panel data. The resulting estimates indicate that 16 exposure has been the main driver of flooding risk for most counties in the U.S. Here, we use these estimates to describe 17 the main source of flooding risk for non-coastal counties for the 1999-2018 period.

54 ENVIRONMENTAL SCIENCES↗

The Hurricane-Flood-Landslide Continuum

In August 2004, representatives from NOAA, NASA, the USGS, and other government agencies convened in San Juan, Puerto Rim for a workshop to discuss a proposed research project called the Hurricane-Flood-Landslide Continuum (HFLC). The essence of the HFLC is to develop and integrate tools across disciplines to enable the issuance of regional guidance products for floods and landslides associated with major tropical rain systems, with sufficient lead time that local emergency managers can protect vulnerable populations and infrastructure. All three lead agencies are independently developing precipitation-flood-debris flow forecasting technologies, and all have a history of work on natural hazards both domestically and overseas. NOM has the capability to provide tracking and prediction of storm rainfall, trajectory and landfall and is developing flood probability and magnTtude capabilities. The USGS has the capability to evaluate the ambient stability of natural and man-made landforms, to assess landslide susceptibilities for those landforms, and to establish probabilities for initiation of landslides and debris flows. Additionally, the USGS has well-developed operational capacity for real-time monitoring and reporting of streamflow across distributed networks of automated gaging stations (http://water.usgs.gov/waterwatch/). NASA has the capability to provide sophisticated algorithms for satellite remote sensing of precipitation, land use, and in the future, soil moisture. The Workshop sought to initiate discussion among three agencies regarding their specific and highly complimentary capabilities. The fundamental goal of the Workshop was to establish a framework that will leverage the strengths of each agency. Once a prototype system is developed for example, in relatively data-rich Puerto Rim, it could be adapted for use in data-poor, low-infrastructure regions such as the Dominican Republic or Haiti. This paper provides an overview of the Workshop s goals, presentations and recommendations with respect to the development of the HFLC.

Negri, Andrew J.↗

Flood and Landslide Applications of Near Real-time Satellite Rainfall Products

Floods and associated landslides are one of the most widespread natural hazards on Earth, responsible for tens of thousands of deaths and billions of dollars in property damage every year. During 1993-2002, over 1000 of the more than 2,900 natural disasters reported were due to floods. These floods and associated landslides claimed over 90,000 lives, affected over 1.4 billion people and cost about $210 billion. The impact of these disasters is often felt most acutely in less developed regions. In many countries around the world, satellite-based precipitation estimation may be the best source of rainfall data due to lack of surface observing networks. Satellite observations can be of essential value in improving our understanding of the occurrence of hazardous events and possibly in lessening their impact on local economies and in reducing injuries, if they can be used to create reliable warning systems in cost-effective ways. This article addressed these opportunities and challenges by describing a combination of satellite-based real-time precipitation estimation with land surface characteristics as input, with empirical and numerical models to map potential of landslides and floods. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg. By careful integration of remote sensing and in-situ observations, and assimilation of these observations into hydrological and landslide/debris flow models with surface topographic information, prediction of useful probabilistic maps of landslide and floods for emergency management in a timely manner is possible. Early results shows that the potential exists for successful application of satellite precipitation data in improving/developing global monitoring systems for flood/landslide disaster preparedness and management. The scientific and technological prototype can be first applied in a representative test-bed and then the information deliverables for the region can be tailored to the societal and economic needs of the represented affected countries.

Hong, Yang↗