ALBERT

Description: As required by the Harmful Algal Bloom and Hypoxia Research Control Act of 1998, the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force issued the 2001 Gulf Hypoxia Action Plan (updated in 2008). In response to the Gulf Hypoxia Action Plan of 2001 (updated in 2008), the EPA Gulf of Mexico Hypoxia Modeling and Monitoring Project has established a detailed model for the Mississippi-Attchafalaya River Basin which provides a capability to forecast the multi-source nutrient loading to the Gulf and the subsequent bio-geochemical processes leading to hypoxic conditions and subsequent effects on Gulf habitats and fisheries. The primary purpose of the EPA model is to characterize the impacts of nutrient management actions, or proposed actions on the spatial and temporal characteristics of the Gulf hypoxic zone. The model is expected to play a significant role in determining best practices and improved strategies for incentivizing nutrient reduction strategies, including installation of on-farm structures to reduce sediment and nutrient runoff, use of cover crops and other agricultural practices, restoration of wetlands and riparian buffers, improved waste water treatment and decreased industrial nitrogen emissions. These decisions are currently made in a fragmented way by federal, state, and local agencies, using a variety of small scale models and limited data. During the past three years, EPA has collected an enormous amount of in-situ data to be used in the model. We believe that the use of NASA satellite data products in the model and for long term validation of the model has the potential to significantly increase the accuracy and therefore the utility of the model for the decision making described above. This proposal addresses the Gulf of Mexico Alliance (GOMA) priority issue of reductions in nutrient inputs to coastal ecosystem. It further directly relates to water quality for healthy beaches and shellfish beds and wetland and coastal conservation restoration.

Description: The Nile basin River system spans 3 million km(exp 2) distributed over ten nations. The eight upstream riparian nations, Ethiopia, Eretria, Uganda, Rwanda, Burundi, Congo, Tanzania and Kenya are the source of approximately 86% of the water inputs to the Nile, while the two downstream riparian countries Sudan and Egypt, presently rely on the river's flow for most of the their needs. Both climate and agriculture contribute to the complicated nature of Nile River management: precipitation in the headwaters regions of Ethiopia and Lake Victoria is variable on a seasonal and inter-annual basis, while demand for irrigation water in the arid downstream region is consistently high. The Nile is, perhaps, one of the most difficult trans-boundary water issue in the world, and this study would be the first initiative to combine NASA satellite observations with the hydrologic models study the overall water balance in a to comprehensive manner. The cornerstone application of NASA's Earth Science Research Results under this project are the NASA Land Data Assimilation System (LDAS) and the USDA Atmosphere-land Exchange Inverse (ALEXI) model. These two complementary research results are methodologically independent methods for using NASA observations to support water resource analysis in data poor regions. Where an LDAS uses multiple sources of satellite data to inform prognostic simulations of hydrological process, ALEXI diagnoses evapotranspiration and water stress on the basis of thermal infrared satellite imagery. Specifically, this work integrates NASA Land Data Assimilation systems into the water management decision support systems that member countries of the Nile Basin Initiative (NBI) and Regional Center for Mapping of Resources for Development (RCMRD, located in Nairobi, Kenya) use in water resource analysis, agricultural planning, and acute drought response to support sustainable development of Nile Basin water resources. The project is motivated by the recognition that accurate, frequent, and spatially distributed estimates of the water balance are necessary for effective water management. This creates a challenge for watersheds that are large, include data poor regions, and/or span multiple nations. All of these descriptors apply to the Nile River basin, yet successful management of the Nile is critical for development and political stability in the region. For this reason, improved hydrological data to support cooperative water management in the Nile basin is a priority for USAID, the US State Department, the World Bank and other international organizations. In this project, the U.S. based research team is working with partners at RCMRD, Nile Basin Initiative (NBI), and their member national-level agencies to develop satellite-based land cover maps, satellite-derived evapotranspiration estimates (using the ALEXI algorithm), and NASA's Land Data Assimilation System (LDAS) customized to match identified information needs. The cornerstone applied sciences product of the project is the development of a customized "Nile LDAS" that will produce optimal estimates of hydrological states and fluxes, as vetted against the in situ observations of NBI and RCMRD member organizations and independent satellite-derived hydrological estimates. Nile LDAS will be applied to improve the reliability of emerging Decision Support Systems in applications that include drought monitoring, reservoir management, and irrigation planning. The end-users such as RCMRD, NBI, Ethiopian and Kenya Meteorological and Famine Early Warning System Network (FEWSNet) will be the eventual benefactors of this work. There will be a capacity building process involving the above end-user organizations and transfer the models and the results for these organizations to execute for future use. The team has already initiated this study and the early results of first years' work are shown. The plan is to complete this work by late 2013.

Description: This slide presentation reviews a system that uses the SensorWeb connected to the cloud computing, assist in disaster response, specifically flood warning in Namibia.

Description: The Gulf of Mexico Modeling Framework is a suite of coupled models linking the deposition and transport of sediment and nutrients to subsequent bio-geo chemical processes and the resulting effect on concentrations of dissolved oxygen in the coastal waters of Louisiana and Texas. Here, we examine the potential benefits of using multiple NASA remote sensing data products within this Modeling Framework for increasing the accuracy of the models and their utility for nutrient control decisions in the Gulf of Mexico. Our approach is divided into three components: evaluation and improvement of (a) the precipitation input data (b) atmospheric constituent concentrations in EPA's air quality/deposition model and (c) the calculation of algal biomass, organic carbon and suspended solids within the water quality/eutrophication models of the framework.

Description: The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, it was used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. Disasters are the perfect arena to use SensorWebs. One SensorWeb pilot project that has been active since 2009 is the Namibia Early Flood Warning SensorWeb pilot project. The Pilot Project was established under the auspices of the Namibian Ministry of Agriculture Water and Forestry (MAWF)/Department of Water Affairs, the 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 began by identifying and prototyping technologies which enabled 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. This was followed by an international collaboration to build small portions of the identified system which was prototyped during that past few years during the flood seasons which occurred in the February through May timeframe of 2010 and 2011 with further prototyping to occur in 2012. The SensorWeb system features EO-1 data along with other data sets from such satellites as Radarsat, Terra and Aqua. Finally, the SensorWeb team also began to examine the socioeconomic component to determine the impact of the SensorWeb technology and how best to assist in the infusion of this technology in lesser affluent areas with low levels of basic infrastructure. This paper provides an overview of these efforts, highlighting the EO-1 usage in this SensorWeb.

Description: Since the beginning of operation of the MODIS instrument on the NASA Terra satellite at the end of 1999, an exceptionally useful sensor and public data stream have been available for many applications including the rapid and precise characterization of terrestrial surface water changes. One practical application of such capability is the near-real time mapping of river flood inundation. We have developed a surface water mapping methodology based on using only bands 1 (620-672 nm) and 2 (841-890 nm). These are the two bands at 250 m, and the use of only these bands maximizes the resulting map detail. In this regard, most water bodies are strong absorbers of incoming solar radiation at the band 2 wavelength: it could be used alone, via a thresholding procedure, to separate water (dark, low radiance or reflectance pixels) from land (much brighter pixels) (1, 2). Some previous water mapping procedures have in fact used such single band data from this and other sensors that include similar wavelength channels. Adding the second channel of data (band 1), however, allows a band ratio approach which permits sediment-laden water, often relatively light at band 2 wavelengths, to still be discriminated, and, as well, provides some removal of error by reducing the number of cloud shadow pixels that would otherwise be misclassified as water.

Description: SERVIR-Africa is an ambitious regional visualization and monitoring system that integrates remotely sensed data with predictive models and field-based data to monitor ecological processes and respond to natural disasters. It aims addressing societal benefits including floods and turning data into actionable information for decision-makers. Floods are exogenous disasters that affect many parts of Africa, probably second only to drought in terms of social-economic losses. This paper looks at SERVIR-Africa's approach to floods disaster management through establishment of an integrated platform, floods prediction models, post-event flood mapping and monitoring as well as flood maps dissemination in support of flood disaster management.