ABSTRACT:

You can access the app using the following link: https://turnkey-aleph-386916.projects.earthengine.app/view/geefastfloodmonitoring

This App provides intuitive web-based visualization tools to facilitate easy assessment of flood extents.

We hope this app provides tools to facilitate flood monitoring tasks. For example, users can define a flood period, select a location, and draw a boundary to observe the flood extent conditions in their area of interest. Through this App, our aim is to empower decision-makers, first responders, and other stakeholders with clear, useful information, enabling them to better understand, prepare for, and respond to treacherous flooding hazards. This information is crucial, considering the populations, infrastructure facilities, urban area, and cropland at risk.

App created by Ebrahim Hamidi (University of Alabama) and reviewed by Brad G. Peter (University of Arkansas), funded by the National Science Foundation INFEWS Program and the U.S. Army Corps of Engineers. Also, partial support for development of this App is awarded through CUAHSI’s 2023 Hydroinformatics Innovation Fellowship (HIF).

ABSTRACT:

You can access the app using the following link: https://turnkey-aleph-386916.projects.earthengine.app/view/geefastfloodmonitoring

This App provides intuitive web-based visualization tools to facilitate easy assessment of flood extents.

We hope this app provides tools to facilitate flood monitoring tasks. For example, users can define a flood period, select a location, and draw a boundary to observe the flood extent conditions in their area of interest. Through this App, our aim is to empower decision-makers, first responders, and other stakeholders with clear, useful information, enabling them to better understand, prepare for, and respond to treacherous flooding hazards. This information is crucial, considering the populations, infrastructure facilities, urban area, and cropland at risk.

App created by Ebrahim Hamidi (University of Alabama) and reviewed by Brad G. Peter (University of Arkansas), funded by the National Science Foundation INFEWS Program and the U.S. Army Corps of Engineers. Also, partial support for development of this App is awarded through CUAHSI’s 2023 Hydroinformatics Innovation Fellowship (HIF).

ABSTRACT:

Data created during the CUASHI Summer Institute 2022 as part of the "Coupling coastal and hydrologic models through BMI and Nextgen National Water Model Framework in low gradient coastal regions of Galveston Bay, Texas, USA" report for the National Water Center. The purpose of this report was to create a coastal model that could run in the Next Gen Framework.

This resource contains results from running the Python CFE BMI (https://github.com/jmframe/cfe/tree/master/py_cfe), GeoClaw (http://www.clawpack.org/), and GeoClaw with discharge (using a plugin). For code obtaining these results can be found at https://github.com/henrichsen/GeoClaw_BMI.