Date of Award


Document Type


Degree Name


Organizational Unit

College of Natural Science and Mathematics, Geography and the Environment

First Advisor

Michael J. Keables

Second Advisor

Matthew J. Taylor

Third Advisor

Michael W. Kerwin

Fourth Advisor

Jing Li


Catchment-scale, Data-limited regions, Flood hydrology, Hydrogeomorphic processes, Hydrologic modeling, Mixed methods


Coastal flooding is expected to be more frequent and severe from amplified flooding from sea level rise (SLR) and upstream anthropogenic activity, particularly in tropical regions. Improved hydrologic modeling and characterization are needed to better understand, predict, and manage flooding where these amplifications are expected. Yet tropical catchments are often ungauged or have limited hydrogeomorphic data. Thus, locally calibrated models that incorporate local knowledge and alternative data can be used to provide greater information. This doctoral dissertation quantifies relationships between land use, precipitation, discharge, and downstream sediment accretion in a representative ungauged catchment using a locally calibrated rainfallrunoff model validated by proxy measures and participant observations. The primary research objectives are to characterize the hydrologic regime of tropical coastal catchments and to provide insight into how climate change and land use/land cover (LULC) change may affect their hydrologic functioning. Specific research objectives are to (1) assess the flood hydrology of the study area using a combination of paleohydrology, survey, and modeling methods, (2) quantify catchment-scale LULC changes using remote sensing methods to determine effects to hydrology, and (3) assess the downstream sediment archives to estimate longer-term sediment accretion rates over centennial to millennial timescales.

The study methods and results are critical to improve catchment-scale flood modeling and forecasting improve planning and management in data-limited regions. Given that the 2020 Atlantic hurricanes season was one of the most active on record, with two late season hurricanes hitting Nicaragua weeks apart, this study increases understanding of current and historic magnitude and timing of peak floods. The transformative mixed study methods demonstrate that an extreme event hydrograph can be reconstructed and help reduce uncertainty in rainfall-runoff modeling. Results provide a more accurate description of how LULC and climatic patterns influence the hydrogeomorphic response of coastal catchments and their associated features. This project also provides guidance to improve analyses of downstream sediment cores to better understand the hydrogeomorphic connection between highly dynamic mangrove environments and upstream hydrology, currently underrepresented in the literature. Lastly the project demonstrates the value of using local knowledge to better understand flood hydrology, advance understanding, and improve flood management in any data-limited region.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Shannon L. Jones


Received from ProQuest

File Format




File Size

228 pgs


Geomorphology, Physical geography, Hydrologic sciences

Available for download on Friday, April 11, 2025