Team RAY

Team RAY – Climate Change, Extreme Precipitation, and Farm Vulnerability in Connecticut
Alyssa McDonnell, Ritu Monhanpuria, Yuanlong Dai

Objectives

Agricultural farms in Connecticut face production losses due to flooding because of extreme precipitation events, which can be particularly devastating for small farms that make up the majority of Connecticut’s agricultural land. Traditional crop insurance programs often fail to protect such farms from losses related to these events because of high costs and mismatched policies. To address this gap, our research project focuses on answering the following questions:​​

  1. Which agricultural areas in Connecticut are most vulnerable to flood and excess-moisture impacts? ​
  2. What landscape and infrastructure factors amplify losses (for example, impervious cover, drainage limitations, proximity to wetlands)? ​
  3. Which on-farm actions and support programs can reduce risk and expedite recovery? 

Methods

We will integrate satellite observations, climate data, and state land-use layers data to produce a map indicating spatial risk for decision making. We use Sentinel-2 satellite imagery and rainfall data to monitor flood events in Connecticut’s farmlands by distinguishing between permanent water bodies (e.g., rivers and lakes) and temporary water accumulation caused by excessive rainfall, such as flooding and saturated soils. Key spectral indices (NDWI, NDMI, and SWIR reflectance) are used to detect surface water, with adjustable thresholds and optional use of MNDWI to improve sensitivity in identifying turbid or shallow floodwaters. By integrating precipitation data from sources like NOAA or NASA’s GPM, the analysis correlates recent rainfall with flood extent, enhancing the detection of vulnerable agricultural areas and supporting more effective flood risk assessment and land management.

Progress

We began by facilitating a listening session with the New CT Farmers Alliance to hear from farmers their concerns regarding the extreme weather events. In parallel, we cleaned and analyzed the recent Connecticut Department of Agriculture farm loss survey data to identify who is affected and which hazards drive the agricultural losses. These findings led us to prioritize extreme precipitation and excess-moisture impacts. We are currently processing sentinel-2 imagery data along with weather data and CT land use data.

References:
Runkle, J., Kunkel, K., Champion, S., Easterling, D., Stewart, B., Frankson, R., & Sweet, W. (2017). Connecticut state climate summary. NOAA technical report.
Seth, A., Wang, G., Kirchhoff, C., Lombardo, K., Stephenson, S., Anyah, R., & Wu, J. (2019). Connecticut Physical Climate Science Assessment Report (PCSAR): Observed trends and projections of temperature and precipitation. Connecticut Institute for Resilience and Climate Adaptation.
Jong, B. T., Delworth, T. L., Cooke, W. F., Tseng, K. C., & Murakami, H. (2023). Increases in extreme precipitation over the Northeast United States using high-resolution climate model simulations. Npj Climate and Atmospheric Science, 6(1), 18.