{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/141180"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/141180","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Modeling the Effects of Sea-Level Rise on Flooding in the Lower Ozama River Basin, Santo Domingo, Dominican Republic","abstract":"Sea-level rise (SLR) and extreme precipitation increasingly threaten low-lying tropical cities, yet flood assessments in the Dominican Republic have relied primarily on static, elevation-based approaches. This study develops a multi-model framework to evaluate the impacts of SLR and compound fluvial and tidal interactions on flooding in the lower Ozama River Basin, Santo Domingo. A one-dimensional (1D) HEC-RAS model was reconstructed from Belliard (2020) with newly incorporated bathymetric data, while a two-dimensional (2D) unsteady flow HEC-RAS model and a static bathtub model were used to simulate present and future inundation scenarios. The 1D simulations showed that including bathymetry increased hydraulic accuracy and produced larger flood extents for higher return period events. The 2D model captured spatial and temporal flood dynamics across SLR scenarios of 0.30–1.00 m and in compound configurations combining SLR with 25-, 50-, and 100-year discharges. Compared with the bathtub model, which predicted 1.97 km² of inundation, the 2D simulations yielded 0.52 km² for equivalent SLR levels, indicating that static methods overestimate flood area by neglecting flow connectivity and backwater effects. Compound scenarios produced the most extensive and prolonged flooding, confirming that interactions between river discharge, tides, and SLR amplify inundation nonlinearly. Results identify Domingo Savio, Los Tres Brazos, and Los Guandules as the most flood-prone neighborhoods and highlight the need for dynamic hydraulic modeling in urban adaptation planning. The framework developed here provides a physically consistent basis for improving flood risk mapping and advancing scientific understanding of coastal and riverine flooding in the Dominican Republic.","abstract_html":"Sea-level rise (SLR) and extreme precipitation increasingly threaten low-lying tropical cities, yet flood assessments in the Dominican Republic have relied primarily on static, elevation-based approaches. This study develops a multi-model framework to evaluate the impacts of SLR and compound fluvial and tidal interactions on flooding in the lower Ozama River Basin, Santo Domingo. A one-dimensional (1D) HEC-RAS model was reconstructed from Belliard (2020) with newly incorporated bathymetric data, while a two-dimensional (2D) unsteady flow HEC-RAS model and a static bathtub model were used to simulate present and future inundation scenarios. The 1D simulations showed that including bathymetry increased hydraulic accuracy and produced larger flood extents for higher return period events. The 2D model captured spatial and temporal flood dynamics across SLR scenarios of 0.30–1.00 m and in compound configurations combining SLR with 25-, 50-, and 100-year discharges. Compared with the bathtub model, which predicted 1.97 km² of inundation, the 2D simulations yielded 0.52 km² for equivalent SLR levels, indicating that static methods overestimate flood area by neglecting flow connectivity and backwater effects. Compound scenarios produced the most extensive and prolonged flooding, confirming that interactions between river discharge, tides, and SLR amplify inundation nonlinearly. Results identify Domingo Savio, Los Tres Brazos, and Los Guandules as the most flood-prone neighborhoods and highlight the need for dynamic hydraulic modeling in urban adaptation planning. The framework developed here provides a physically consistent basis for improving flood risk mapping and advancing scientific understanding of coastal and riverine flooding in the Dominican Republic.","abstract_has_math":false,"creators":["De Los Santos, Maria"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Geosciences","degree_department":"Geosciences","school":null,"contributors":[],"advisors":[],"committee_chairs":["Willis, Michael John"],"committee_members":["Cisneros, Julia","Allen, George Henry","Heijkoop, Eduard"],"year":2026,"date_issued":"2026-02-05","date_published":"2026-02-05","updated_at":"2026-07-22T22:18:50Z","subjects":["Sea-level rise","Compound flooding","HEC-RAS modeling","Inundation mapping","Santo Domingo"],"languages":["en"],"rights":["Creative Commons Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:45308"],"render_values":[{"text":"vt_gsexam:45308","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/141180","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Willis, Michael John"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Cisneros, Julia","Allen, George Henry","Heijkoop, Eduard"]},{"key":"dc:contributor.department","label":"Department","values":["Geosciences"]},{"key":"dc:creator","label":"Author","values":["De Los Santos, Maria"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-02-06T09:00:20Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-02-06T09:00:20Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-02-05"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geosciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Sea-level rise","Compound flooding","HEC-RAS modeling","Inundation mapping","Santo Domingo"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Creative Commons Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:45308"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/141180"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Sea-level rise (SLR) and extreme precipitation increasingly threaten low-lying tropical cities, yet flood assessments in the Dominican Republic have relied primarily on static, elevation-based approaches. This study develops a multi-model framework to evaluate the impacts of SLR and compound fluvial and tidal interactions on flooding in the lower Ozama River Basin, Santo Domingo. A one-dimensional (1D) HEC-RAS model was reconstructed from Belliard (2020) with newly incorporated bathymetric data, while a two-dimensional (2D) unsteady flow HEC-RAS model and a static bathtub model were used to simulate present and future inundation scenarios. The 1D simulations showed that including bathymetry increased hydraulic accuracy and produced larger flood extents for higher return period events. The 2D model captured spatial and temporal flood dynamics across SLR scenarios of 0.30–1.00 m and in compound configurations combining SLR with 25-, 50-, and 100-year discharges. Compared with the bathtub model, which predicted 1.97 km² of inundation, the 2D simulations yielded 0.52 km² for equivalent SLR levels, indicating that static methods overestimate flood area by neglecting flow connectivity and backwater effects. Compound scenarios produced the most extensive and prolonged flooding, confirming that interactions between river discharge, tides, and SLR amplify inundation nonlinearly. Results identify Domingo Savio, Los Tres Brazos, and Los Guandules as the most flood-prone neighborhoods and highlight the need for dynamic hydraulic modeling in urban adaptation planning. The framework developed here provides a physically consistent basis for improving flood risk mapping and advancing scientific understanding of coastal and riverine flooding in the Dominican Republic."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Flooding along the Ozama River in Santo Domingo is becoming more frequent and severe as sea levels rise and heavy rainfall events intensify. This research used computer models to understand how water moves through the river and nearby neighborhoods under different conditions: today's climate, future sea-level rise, and combined river and coastal flooding. Two types of models were compared. The bathtub model simply \"fills\" areas below a specified threshold height, while the HEC-RAS model simulates how water actually flows, rises, and drains over time. By adding detailed information about the river depth (bathymetry), the HEC-RAS results showed that flooding is concentrated in specific low-lying neighborhoods especially Domingo Savio, Los Tres Brazos, and Los Guandules rather than spreading evenly across the city as the bathtub model suggests. When rising sea levels were combined with heavy rainfall, floods became both deeper and longer, lasting because higher ocean levels slowed the river's ability to drain. These results show that realistic, dynamic models are essential for protecting people and infrastructure in Santo Domingo. The study's methods can also help guide national adaptation efforts to manage flood risk in other Dominican coastal cities."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Modeling the Effects of Sea-Level Rise on Flooding in the Lower Ozama River Basin, Santo Domingo, Dominican Republic"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Willis, Michael John"],"dc:contributor.committeemember":["Cisneros, Julia","Allen, George Henry","Heijkoop, Eduard"],"dc:contributor.department":["Geosciences"],"dc:creator":["De Los Santos, Maria"],"dc:date.accessioned":["2026-02-06T09:00:20Z"],"dc:date.available":["2026-02-06T09:00:20Z"],"dc:date.issued":["2026-02-05"],"dc:description.abstract":["Sea-level rise (SLR) and extreme precipitation increasingly threaten low-lying tropical cities, yet flood assessments in the Dominican Republic have relied primarily on static, elevation-based approaches. This study develops a multi-model framework to evaluate the impacts of SLR and compound fluvial and tidal interactions on flooding in the lower Ozama River Basin, Santo Domingo. A one-dimensional (1D) HEC-RAS model was reconstructed from Belliard (2020) with newly incorporated bathymetric data, while a two-dimensional (2D) unsteady flow HEC-RAS model and a static bathtub model were used to simulate present and future inundation scenarios. The 1D simulations showed that including bathymetry increased hydraulic accuracy and produced larger flood extents for higher return period events. The 2D model captured spatial and temporal flood dynamics across SLR scenarios of 0.30–1.00 m and in compound configurations combining SLR with 25-, 50-, and 100-year discharges. Compared with the bathtub model, which predicted 1.97 km² of inundation, the 2D simulations yielded 0.52 km² for equivalent SLR levels, indicating that static methods overestimate flood area by neglecting flow connectivity and backwater effects. Compound scenarios produced the most extensive and prolonged flooding, confirming that interactions between river discharge, tides, and SLR amplify inundation nonlinearly. Results identify Domingo Savio, Los Tres Brazos, and Los Guandules as the most flood-prone neighborhoods and highlight the need for dynamic hydraulic modeling in urban adaptation planning. The framework developed here provides a physically consistent basis for improving flood risk mapping and advancing scientific understanding of coastal and riverine flooding in the Dominican Republic."],"dc:description.abstractgeneral":["Flooding along the Ozama River in Santo Domingo is becoming more frequent and severe as sea levels rise and heavy rainfall events intensify. This research used computer models to understand how water moves through the river and nearby neighborhoods under different conditions: today's climate, future sea-level rise, and combined river and coastal flooding. Two types of models were compared. The bathtub model simply \"fills\" areas below a specified threshold height, while the HEC-RAS model simulates how water actually flows, rises, and drains over time. By adding detailed information about the river depth (bathymetry), the HEC-RAS results showed that flooding is concentrated in specific low-lying neighborhoods especially Domingo Savio, Los Tres Brazos, and Los Guandules rather than spreading evenly across the city as the bathtub model suggests. When rising sea levels were combined with heavy rainfall, floods became both deeper and longer, lasting because higher ocean levels slowed the river's ability to drain. These results show that realistic, dynamic models are essential for protecting people and infrastructure in Santo Domingo. The study's methods can also help guide national adaptation efforts to manage flood risk in other Dominican coastal cities."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:45308"],"dc:identifier.uri":["https://hdl.handle.net/10919/141180"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["Creative Commons Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:subject":["Sea-level rise","Compound flooding","HEC-RAS modeling","Inundation mapping","Santo Domingo"],"dc:title":["Modeling the Effects of Sea-Level Rise on Flooding in the Lower Ozama River Basin, Santo Domingo, Dominican Republic"],"dc:type":["Thesis"],"thesis:degree_discipline":["Geosciences"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:18:50Z"}