The Flash Factor: Creating a Flood Forecasting Framework

This is an article from the Summer 2015 VPS. For more VPS articles, click here

Maps of Malawi showing various data from Jan. 15, 2015: Output of an unsupervised iso-cluster analysis of soil moisture, land use/land cover and soil moisture. Image Credit: Malawi Disasters II Team

Maps of Malawi showing various data from Jan. 15, 2015: Output of an unsupervised iso-cluster analysis of soil moisture, land use/land cover and soil moisture. Image Credit: Malawi Disasters II Team

Category: Responding to Hydrologic Disasters
Project Team: Malawi Disasters II
Team Location: International Research Institute for Climate and Society (IRI) – Palisades, New York

Authors:
Andrew Kruczkiewicz
Helen Cen
Brigitte Moneymaker

Mentors/Advisors:
Dr. Pietro Ceccato (International Research Institute for Climate and Society, The Earth Institute, Columbia University)

Abstract:
The African country of Malawi experiences a strong seasonal rainy season stretching from October to April, which provides about 95 percent of its annual precipitation. In addition to this high seasonality, about 20 percent of Malawi’s land cover is comprised of surface water from Lake Malawi, one of the Great African Lakes. These unique features contribute to the country’s increased vulnerability to riverine floods and flash floods. In January 2015, extended periods of extreme rainfall caused a series of flood events throughout Malawi, which resulted in the displacement of more than 230,000 residents and caused 276 fatalities. In order for local authorities and humanitarian agencies to provide post-disaster relief, these organizations often rely on remotely-sensed satellite data to evaluate initial disaster impact and design response programs. In partnership with the Malawi Red Cross, this project aimed to expand on the findings from previous research in Spring 2015 by first comparing ground-truth data (locations of shelter site of internally displaced people (IDPs) and origins of IDPs) with previous term data and second, by integrating European Space Agency (ESA) remotely sensed data to explore the potential predictive capabilities of soil moisture for flash flood detection. In addition to data from NASA sensors (MODIS, TRMM, SSM-I and AMSU-A data), this project incorporated Advanced Scatterometer (ASCAT) data from ESA. The results of this study will increase the ability to forecast and monitor flood events, benefiting organizations involved with disaster relief efforts in Malawi and potentially allowing for more efficient response and allocation of emergency flood relief efforts.

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