A Code Based Tool for Precipitation Mapping, Infiltration Analysis, and Runoff Prediction on Long Island

Authors: Thomas Amalfitano, Sean Tvelia, Jadon Blessing

SUNY Campus: Suffolk County Community College

Presentation Type: Poster

Location: Old Union Hall

Presentation #: 12

Timeslot: Session D 3:00-4:00 PM

Abstract: Long Island relies entirely on a groundwater aquifer system as its sole source of freshwater; providing drinking water for residents, supporting local agriculture, and aquaculture. Protecting this resource is essential to ensure water quality and sustainability for both human consumption and agricultural use. This research hopes to enhance precipitation mapping and hydrological modeling, contributing to more effective water resource management and environmental protection. The developed computational tool has broad applications, including estimating aquifer recharge rates to support groundwater management, assessing surface runoff volumes for flood prediction and mitigation, and tracking polluted runoff to aid in contamination monitoring. To achieve these objectives, the project integrates doppler radar reflectivity data from the National Weather Service (NWS) with ArcGIS Pro to improve rainfall distribution analysis. A 5-mile by 5-mile grid centered around any given point across Long Island will be generated to track storm systems as they move across defined boundaries within ArcGIS. Beyond precipitation measurement, the project incorporates porosity testing within the study area to determine infiltration rates, which will be validated using USGS well log data and ground-based rain gauge data. By combining precipitation estimates with infiltration rates, the tool will calculate surface runoff during a given storm event. By providing a comprehensive assessment of precipitation, infiltration, and runoff dynamics, this tool offers valuable insights into hydrological processes. Its adaptability to groundwater recharge assessment, flood mitigation, and contaminant tracking makes this a valuable tool in hydrological modeling and environmental monitoring