Logo Lanfrica

tokiror/maple-scholars-2026

Domain:

climategeospatial

Record type:

project
Creator:
tok
Host:
Undergraduate research: satellite data analysis of drought and natural water reservoirs in East Africa # maple-scholars-2026 Undergraduate research: satellite data analysis of drought and natural water reservoirs in East Africa --- ## Overview This project investigates the natural water "reservoirs" — groundwater, soil moisture, and seasonal wetlands — that sustain or end droughts in Kongwa District, central Tanzania. Kongwa is a largely rain-fed agricultural region with very little irrigation or built water storage, which makes it an ideal place to ask: when the rain stops, what holds water in the landscape, and how does the area recover? The research is motivated by a public-health link. A previous study in the region found that a drought appeared to end earlier than rainfall alone could explain, coinciding with a measured drop in crop mycotoxins (toxins produced by fungi under crop stress). If a natural water source eased that drought sooner than expected, understanding it could have implications for food safety and water management across similar dryland farming regions. **Researcher:** Timothy Masaba Okiror **Faculty Mentor:** Prof. Paul Meyer Reimer (Physics) **Institution:** Goshen College --- ## Research Question What natural water reservoirs sustain or end droughts in Kongwa District, and can changes in satellite-measured water storage help explain the early drought recovery observed in prior research? --- ## Data Sets **Raw GRACE / GRACE-FO (NASA JPL MASCON)** Satellite measurements of total water storage anomaly (TWSA), derived from tiny changes in Earth's gravity field. Extracted via Google Earth Engine. Native resolution is coarse (~3 degrees). Units: centimeters of equivalent water height; baseline 2004–2010. **GRACE-SeDA (Gou & Soja, 2024, Nature Water)** A deep-learning-downscaled GRACE product that sharpens the blurry satellite signal to 0.5 degree resolution by fusing it with the WaterGAP global hydrology model. Primary dataset for the fine-scale analysis. Monthly, 2002–2022. Units: millimeters; baseline 2004–2009. DOI: doi.org

Languages