Nearshore Evidence in Support of the Bruun Rule on Shore Erosion: Reply

1977 ◽  
Vol 85 (4) ◽  
pp. 492-494
Author(s):  
Roger N. Dubois
Keyword(s):  
Bruun Rule ◽  
Shore Erosion

Nearshore Evidence in Support of the Bruun Rule on Shore Erosion

1976 ◽  
Vol 84 (4) ◽  
pp. 485-491 ◽  
Author(s):  
Roger N. Dubois
Keyword(s):  
Bruun Rule ◽  
Shore Erosion

U.S. Army Coastal Engineering Research Center's Ecology Program

1984 ◽  
Vol 16 (3-4) ◽  
pp. 525-532
Author(s):  
E J Pullen ◽  
P L Knutson ◽  
A K Hurme
Keyword(s):  
Coastal Engineering ◽  
Coastal Vegetation ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Engineering Research ◽  
Navigation Channel ◽  
Biological Environment ◽  
Ecology Program ◽  
The U.S ◽  
Shore Erosion

The Coastal Engineering Research Center at Fort Belvoir, Virginia, is responsible for research that supports the U.S. Army Corps of Engineers' Civil Works program. This research involves coastal navigation, channel design and maintenance, storm flooding, shore erosion control, and coastal ecology. The ecology research is focused on two major areas: (1) use of coastal vegetation for engineering purposes and (2) effects of coastal engineering activities on the biological environment. The objectives and accomplishments of the ecology research are discussed and specific examples of field guidance are presented.

scholarly journals Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

2021 ◽  
Vol 13 (8) ◽  
pp. 1424
Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Management ◽  
Google Earth ◽  
Environmental Data ◽  
Planetary Scale ◽  
Bruun Rule ◽  
Source Models ◽  
Google Earth Engine ◽  
Bathtub Model

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.

Estimating the benefits of shore erosion protection in Ohio's Lake Erie Housing Market

1993 ◽  
Vol 29 (4) ◽  
pp. 795-801 ◽  
Author(s):  
Warren Kriesel ◽  
Alan Randall ◽  
Frank Lichtkoppler
Keyword(s):  
Housing Market ◽  
Lake Erie ◽  
Erosion Protection ◽  
Shore Erosion

scholarly journals Development of Tools for Coastal Management in Google Earth 2 Engine: Uncertainty Bathtub Model and Bruun Rule

2021 ◽  
Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Management ◽  
Google Earth ◽  
Environmental Data ◽  
Bathymetric Data ◽  
Bruun Rule ◽  
Source Models ◽  
Very High ◽  
Bathtub Model

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence 15 of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal 16 management. This study aims to develop and to validate two different models to predict the 17 sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for plan-18 etary-scale environmental data analysis. The first model is a Bathtub Model based on the uncer-19 tainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and 20 Modeling System software. The validation process performed in the Rio Grande do Sul coastal 21 plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule for-22 mula implemented in GEE and is capable to determine the coastline retreat of a profile through the 23 creation of a simple vector line from topo-bathymetric data. The model shows a very high correla-24 tion (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE 25 platform seems to be an important tool for coastal management. The models developed have been 26 openly shared, enabling the continuous improvement of the code by the scientific community.

scholarly journals Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

2021 ◽  
Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Management ◽  
Google Earth ◽  
Environmental Data ◽  
Planetary Scale ◽  
Bruun Rule ◽  
Source Models ◽  
Google Earth Engine ◽  
Bathtub Model

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal man-agement. This study aims to develop and to validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule formula implemented in GEE and is capable to determine the coastline retreat of a profile through the creation of a simple vector line from topo-bathymetric data. The model shows a very high cor-relation (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE platform seems to be an important tool for coastal management. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific commu-nity.

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