Geology topics

Maya Kumari Hayden

Publications and source records attributed to Maya Kumari Hayden.

3 recordsLinked to original sources

USGS2026

Lessons learned from a hybrid approach to collecting user feedback on coastal science products

Science products play a critical role in assisting environmental decision-makers to manage coastal systems; yet there are challenges to developing products that align with needs of end-users. By combining aspects of usability testing and contextual inquiry methods, we describe a hybrid approach for collecting user feedback, especially applicable within the federal government context. This paper presents results of this hybrid testing approach on two of U.S. Geological Survey’s science products, the Coastal Change Likelihood (CCL) and Hazard Exposure Reporting and Analytics (HERA). Both science products synthesize coastal hazard exposure at different geographies and scales. By comparing two science products in different stages of development, we identify common usability issues across both products; the importance of defining a target audience; requested functionalities beyond the products’ scope; and the effect of previous stakeholder engagement on how testers describe technical issues and barriers. Results from user feedback contribute to understanding needs and barriers of coastal decision-makers for science product development. This paper broadens the understanding of environmental decision-makers in the science product development cycle, and how social dimensions can be integrated in project design through iteratively working with end-users and product developers. Further, we present general lessons in usability for development cycles and how these lessons can inform development of actionable science products in coastal management.

Environmental Management↗

USGS2024

Projections of multiple climate-related coastal hazards for the US Southeast Atlantic

Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US \ $ 1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50% of all coastal residents and US \ $ 770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.

Florida, Georgia, North Carolina, South Carolina, ↗

USGS2024

Scalable, data-assimilated models predict large-scale shoreline response to waves and sea-level rise

Coastal change is a complex combination of multi-scale processes (e.g., wave-driven cross-shore and longshore transport; dune, bluff, and cliff erosion; overwash; fluvial and inlet sediment supply; and sea-level-driven recession). Historical sea-level-driven coastal recession on open ocean coasts is often outpaced by wave-driven change. However, future sea-level-driven coastal recession is expected to increase significantly in tandem with accelerating rates of global sea-level rise. Few models of coastal sediment transport can resolve the multitude of coastal-change processes at a given beach, and fewer still are computationally efficient enough to achieve large-scale, long-term simulations, while accounting for historical behavior and uncertainties in future climate. Here, we show that a scalable, data-assimilated shoreline-change model can achieve realistic simulations of long-term coastal change and uncertainty across large coastal regions. As part of the modeling case study of the U.S. South Atlantic Coast (Miami, Florida to Delaware Bay) presented here, we apply historical, satellite-derived observations of shoreline position combined with daily hindcasted and projected wave and sea-level conditions to estimate long-term coastal change by 2100. We find that 63 to 94% of the shorelines on the U.S. South Atlantic Coast are projected to retreat past the present-day extent of sandy beach under 1.0 to 2.0 m of sea-level rise, respectively, without large-scale interventions.

North Carolina↗