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Caroline Schwab

Caroline Schwab

Cohort III, Summer Bridge Students, Undergraduate

B.E, Environmental Engineering , Undergraduate

Cohort Level: Cohort - III

Career Goal: Once I graduate, I would like to pursue a PhD in environmental engineering, with a focus on water and resources, and incorporation of policy.

Expected Graduation Date: June 1, 2023

Degree: B.E Environmental Engineering

Research Title: Predicting Agricultural Drought Using Historical Crop Yield Data

Research Synopsis: This project aims to model agricultural yield using climate variables. The project is 4-part, the first being a visualized study of how centers of drought shift across the United States. The second part implemented a conditional analysis of the probability of agricultural yield being less than average as a result of years of water stress. We then identified and conducted a case study on New York, Colorado, Montana, and Pennsylvania - states whose probability of yield being less than average either increased drastically, or decreased (the opposite of the expected response) in response to increasing water stress. The 4th part aims to model forecasts of decreased yield, using statistical analysis of drought, yield, and irrigation fraction. These four parts will repeated for wheat and other crops, as well as including climate variables beyond drought. This work is increasingly important as climate change threatens to increase extreme water events. These models would allow us to predict agricultural production up to a month in advance based on current climate conditions, rather than on prediction of drought, so as to guide farmers as how to adapt. Relying on climate conditions and models would allow farmers to circumvent the rise in uncertainty of when seasons of drought will occur as brought on by climate change.

This project aims to model agricultural yield using climate variables. The project is 4-part, the first being a visualized study of how centers of drought shift across the United States. The second part implemented a conditional analysis of the probability of agricultural yield being less than average as a result of years of water stress. We then identified and conducted a case study on New York, Colorado, Montana, and Pennsylvania - states whose probability of yield being less than average either increased drastically, or decreased (the opposite of the expected response) in response to increasing water stress. The 4th part aims to model forecasts of decreased yield, using statistical analysis of drought, yield, and irrigation fraction. These four parts will repeated for wheat and other crops, as well as including climate variables beyond drought. This work is increasingly important as climate change threatens to increase extreme water events. These models would allow us to predict agricultural production up to a month in advance based on current climate conditions, rather than on prediction of drought, so as to guide farmers as how to adapt. Relying on climate conditions and models would allow farmers to circumvent the rise in uncertainty of when seasons of drought will occur as brought on by climate change.

CESSRST Consortium

CESSRST is led by The City University of New York and brings together Hampton University, VA; University of Puerto Rico at Mayaguez, PR; San Diego State University, CA; University of Maryland Baltimore County, MD; University of Texas at El Paso, TX.