ESSIC Visiting Assistant Research Scientist Kimberly Slinski is CO-I on a recently awarded SERVIR Applied Sciences Team grant titled, “In-Situ Data Collection with Remote Sensing for Machine Learning Parameter Estimates and Improved Hydrologic Models for Flood, Drought and Agricultural Yield Forecasting”.
Slinski’s team is partnering with the SERVIR – Eastern and Southern Africa Hub (ESA), hosted by the Regional Centre for Mapping of Resources for Development. Together, they will link remote sensing datasets with the team’s in-situ collection tools currently measuring rainfall, temperature, groundwater use, and land properties in East Africa.
The team will then develop machine learning-supported interpolated data products for localized rainfall, localized temperature, localized groundwater use, forecast groundwater demand, and localized land properties. These products will be used to develop a new SERVIR-ESA service for “Groundwater Use and Demand Forecast” and to support existing local and national services.
Slinski’s research interests are in the development of remote-sensing and model-based tools for hydrologic analysis in data-sparse regions of the world. Slinski’s current work is primarily focused on using land surface models (LSMs) and satellite data to monitor and forecast water availability in Africa, Central Asia, and Central America for USAID’s Famine Early Warning Systems Network (FEWS NET).
