[ home ] [ projects ] [ people ] [ publications ]





Studies of the Food-Energy-Water Nexus in sub-Saharan Africa



Africa is undergoing an energy revolution. Centralized electricity production and grid connections are multiplying electricity access for cities and industry in emerging economies across the globe, while distributed renewable technologies offer opportunities for communities beyond the grid. These changes are transforming societies, and they have diverse impacts on food systems, and ultimately food security, from household to international scale. At the same time, climate change has the potential to impose both local and global hydrological shocks that affect food and energy systems at multiple levels. To understand and predict these dynamics, we are consturcting a systems-based multiscale modeling framework that captures local to national scale food, energy, and water dynamics in a changing climate. The framework is being implemented for Ethiopia and Mali, two rapidly developing but highly climate vulnerable countries that serve as test cases for a more generalizable analysis system. This work is a multi-institution effort led by JHU and supported by the NSF. We also lead a complementary Food-Energy-Water project that applies socio-ecological systems analysis in the Blue Nile basin and is supported by the Belmont Forum.

Improved seasonal hydrological forecasts in South Asia

Hydrological variability presents significant challenges to human safety, agricultural production, and water resource management across South Asia. Producing reliable and actoinable hydrological forecasts for the region is a grand challenge that requires advances in models, observation, and the design and communication of forecast-based decision support products.

In a series of collaborative projects funded by NASA SERVIR and the Skoll Global Threats Fund we have developed a land data assimilation system for hydrological monitoring and analysis across South Asia. We are currently extending this system to provide ensemble seasonal hydrological forecasts, with a focus on the Hindu Kush-Himalaya region. This work is being performed in close partnership with the International Center for Integrated Mountain Development (ICIMOD) and the SERVIR HKH hub, and with research partners at NASA Goddard Space Flight Center and the University of Wisconsin-Madison.


Hydrometeorological information for the countries of the Nile basin

nile basin

We have developed dvanced remote sensing and land surface models for Decision Support on hydrologic variability, climate change, and land management in countries of the Nile basin.  Satellite remote sensing provides high frequency, spatially complete information on landscape processes and characteristics.  This information is integrated with physically-based land surface models to provide best-available estimates of hydrological states and fluxes, which in turn provide actionable information related to flood protection, agricultural planning, drought monitoring, and climate change adaptation.  Current project activities include irrigation mapping, satellite and model based evapotranspiration estimates, and land surface modeling of hydrological states and fluxes.

This project began with a NASA funded project that included partnership with NASA, NOAA, USDA, USAID, the World Bank, the University of Wisconsin, the Regional Center for Mapping of Resources for Development (RCMRD), and other organization in Nile basin states. The work contiues with follow-on collaboration across the region.

A Malaria Risk Monitoring and Early Warning System for the Peruvian Amazon

Almost 90% of malaria in the Western Hemisphere is located in the Amazon, and 50% of the total malaria burden in the Americas is located in 44 municipalities of Peru, Brazil, and Venezuela,where dynamic land use activities place people and Anopheles mosquitoes in close proximity, leading to elevated risk of malaria transmission. The temporal and spatial factors governing risk of exposure, however, are poorly characterized, whichlimits the efficacy of control strategies and the distribution of health resources. There is a need for spatially explicit models that monitor and predict transmission risk on the basis of joint landscape and human behavioral factors. Land Data Assimilation Systems (LDAS) offer a powerful opportunity for informing malaria risk models with spatially explicit, time-varying estimates of hydrological conditions. In a NASA-funded project led by Dr. William Pan of Duke University we are applying LDAS in support of a Malaria Early Warning System for the Peruvian and Ecuadorian Amazon. The project serves as a demonstration of the broad applicability of LDAS to studies of hydrologically and ecologically mediated disease risk.

Climate Change Resilience in the Ethiopian Highlands
Choke Mountain

Coupled processes of low investment capacity and land degradation currently drive a cycle of depressed agricultural yields and persistent poverty through much of the Ethiopian Highlands, including the Blue Nile (Abay River) headwaters (BNH) region. There is reason for concern that conditions in the BNH will deteriorate in coming decades, given a changing climate that could well bring more frequent drought and more intense precipitation events to the region. This is expected to take place in tandem with continued population growth and the potential for external land use pressures. However, the same coupling of natural and human systems that currently reinforces poverty in this region also offers opportunity.

Working closely with collaborators at Addis Ababa University, along with an interdisciplinary research team of social and physical scientists, development practitioners, and local experts, we are identifying methods for applying climate and hydrological analysis in support demonstrated climate resilience building activities in the BNH.

Explaining the Urban Heat Island

Working with partners at the Maryland Institute College of Art (MICA), the City of Baltimore Office of Sustainability, and numerous schools and community groups in Baltimore City and the surrounding area, we are implementing a high density, low cost urban heat monitoring network. This network is being used in combination with satellite data to characterize the city's heat island and its sensitivity to climate variability and land cover. These analyses then feed into high resolution regional climate modeling efforts that are designed to simulate the urban heat island and to inform mitigation strategies.

Heat Island
Heat Waves in the Southeast: Patterns, Trends, and Health Impacts

In collaboration with researchers at Virginia Tech and the University of Alabama at Birmingham, we are investigating the health impacts of extreme heat events in the Southeast United States. Making use of a combination of remote sensing techniques and climate reanalyses, we are examining how various forms of extreme heat events impact urban and rural populations, identifying heat wave diagnostics that most effectively capture these health impacts, and projecting evolving patterns of heat vulnerability on the basis of climate change projections and the vulnerability profiles of different communities.


Satellite Monitoring of Chesapeake Bay

Estuaries like the Chesapeake Bay are dynamic environments, subject to variable currents and mixing processes that produce high temporal and spatial variability in water properties relevant to hydrodynamics, water quality, and ecology. Estuarine and coastal environments are also increasingly vulnerable to adverse environmental, biological, and societal change under pressures of human population growth, sea level rise, land degradation, and climate change. The highly variable and evolving nature of these environments makes them notoriously difficult to survey and monitor. As conditions continue to change in poorly characterized and unpredicted ways, there is a vital need for more advanced and spatially complete monitoring networks.

Working with collaborators at the JHU Applied Physics Lab, the University of Maryland, NOAA, NASA, the University of Rochester, and other institutions, we are developing satellite-derived estimates of surface salinity in Chesapeake Bay in order to inform development of hydrodynamic models and to improve the accuracy and completeness of operational water quality and pathogen models.

Dynamics of East African Precipitation

The hydroclimate research group participates in a multidisciplinary Earth & Planetary Science Department initiative on African climates. Under this initiative, we are currently employing a suite of climate modeling, remote sensing, and geochemical techniques to improve understanding of precipitation dynamics in the East African highlands. This study will advance understanding of atmospheric processes influencing rainfall in the region. It will also contribute to efforts to interpret records of past climate and to evaluation of global climate models used to project future preciptiation patterns under climate change.

Other work under the African climates initiative includes objective regionalization of African climate zones, improved seasonal preciptiation predictions, and satellite-based drought monitoring.

Africa water vapor


Empirical Downscaling and Interpolation


Empirical downscaling employs data-driven, computationally efficient statistical models to reconstruct past climate variability and for projecting future trends at locations that have an adequate meteorological record for calibration. Reliable, long-term in situ meteorological stations are, however, quite limited in many parts of the world, which limits the applicability of empirical downscaling techniques when gridded climate fields are required.

Recognizing this limitation, but also recognizing that the coverage of meteorological observations--both in situ and remotely sensed--has increased dramatically in recent decades, we are developing methods that merge empirical downscaling with geostatistical interpolation techniques and satellite data in order to generate spatially complete gridded climate that can be used to reconstruct and project climate in unmonitored locations and to drive climate change impacts models

The GRACE Data Assimilation System

NASA's Gravity Recovery and Climate Experiment (GRACE) mission has the potential to be extremely valuable for water resources applications and global water cycle research. What makes GRACE unique among Earth Science satellite systems is that it is able to monitor variations in water stored in all forms, from snow and surface water to soil moisture to groundwater in the deepest aquifers. However, the space and time resolutions of GRACE observations are coarse. GRACE typically resolves water storage changes over regions on the order of 100,000 km2 on a monthly basis, while city-scale, daily observations would be more useful for water management, agriculture, and weather prediction.  The GRACE Data Assimilation System integrates GRACE observations into an advanced land surface model, yielding new estimates of water and energy fluxes and storages that are informed by GRACE and that can be produced at high model resolution.

Our group currently collaborates on a NASA/USDA project led by Dr. Matt Rodell (NASA Goddard Space Flight Center) to apply the technique to drought monitoring and drougth and flood forecasting for the United States and all of North America. We also lead a GRACE Science Team project to improve the representation of water withdrawals in GRACE DAS.

grace assimilation
Coupled regional climate modeling


regional climate model frame

Our group works on both the development and application of coupled climate models in order to improve our understanding of regional climate variability. Regional drought processes are a subject of particular interest.

Currently, we are collaborating with researchers at NASA Goddard Space Flight Center to increase functionality and applications of the NASA Unified Weather Research and Forecasting (NU-WRF) modeling system. When fully implemented, LIS-WRF will provide an unprecedented opportunity to study mesoscale interactions between land, cloud, aerosol, and precipitation processes in a fully coupled system. Such coupling is particularly important for drought, as, for example, convection induced by land-atmosphere interactions may be suppressed by aerosol heating aloft, while radiative cooling associated with increased albedo may be counteracted by reductions in cloud cover.