9 Advances in Geologic Mapping, Databases, and Dissemination: Student Posters

This session will showcase student projects associated with new geologic maps, mapping techniques, and advances in data management, web accessibility, and applications. We welcome submissions with relevance to hazards, natural resource evaluations, and water-land management.

Monday, 9 March 2026
9:00 AM - 5:00 PM
RCC, Lower Level Hall

Evaluating High-Resolution Flood Models for the Edisto Island Region, South Carolina

Paper number: 9-11
Program: Technical Sessions
Time: 9:00 AM – 9:00 AM

Authors

Abstract

This study is a part of a larger NSF funded grant that develops and evaluates high-resolution flood models for Edisto Island and Edisto Beach, South Carolina, using an integrated geospatial framework. The modeling combines 2-ft resolution LiDAR elevation data, 1-m land use/land cover (LULC), SSURGO soil attributes, and the most up-to-date road and transportation infrastructure datasets. Together, these inputs represent the highest spatial resolution flood modeling effort currently available for the region and allow for detailed representation of surface conditions influencing runoff generation and inundation dynamics.

Model development focuses on rainfall–runoff processes using the TR-55 SCS Curve Number (CN) methodology, enabling event-based flood simulations across a wide range of precipitation scenarios. Over fifty modeled scenarios were generated, including 1-, 10-, 20-, 50-, 100-, and 500-year return periods with rainfall durations of 15 minutes, 30 minutes, 60 minutes, 12 hours, and 24 hours. These scenarios were first driven by NOAA Atlas 14 precipitation estimates and then repeated using Atlas 15 values to evaluate the sensitivity of flood extent and infrastructure impacts to updated rainfall frequency standards.

To assess model performance and applicability, results are compared against the First Street Foundation flood models acquired by the South Carolina Office of Resilience. Comparative analyses examine percent spatial overlap, spatial patterns of flood extent, roadway inundation, and areas of agreement and divergence between modeling approaches. Preliminary findings reveal strong correspondence in many upland areas but systematic discrepancies in low-lying coastal and back-marsh environments, where modeling assumptions, elevation resolution, and hydrologic representation exert greater influence.

These findings directly inform statewide resilience planning by helping identify when commercially available flood products are appropriate for screening-level decision-making and when higher-resolution, locally calibrated models are necessary for infrastructure investment, evacuation planning, and hazard mitigation prioritization. The results provide technical guidance to support the South Carolina Office of Resilience in developing consistent flood-risk standards, evaluating precipitation atlas transitions, and improving transparency in flood-risk communication across South Carolina’s low-gradient coastal systems.

Geological Society of America Abstracts with Programs. Vol. 58, No. 1

doi: 10.1130/abs/2026SE-411802

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