Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...

This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.

This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.

Data and models for exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise

Authors:
Owners:		This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type:	Resource
Storage:	The size of this resource is 811.8 MB
Created:	Jan 24, 2020 at 10:56 p.m.
Last updated:	Mar 18, 2020 at 9:38 p.m.
DOI:	10.4211/hs.5148675c6a5841e686a3b6aec67a38ee
Citation:	See how to cite this resource

Sharing Status:	Published
Views:	1505
Downloads:	341
+1 Votes:	Be the first one to this.
Comments:	No comments (yet)

Abstract

This resource contains data and models that were used to produce results for a paper published in the Journal of Hydrology. The models are for a neighborhood in Norfolk, Virginia USA that suffers from frequent coastal flooding. The paper describes the use of active stormwater controls to mitigate this problem which will worsen with sea level rise. The particular type of control approach explored was model predictive control (MPC) and the Stormwater Management Model (SWMM) was used to simulate the stormwater system. The swmm_mpc Python package (https://github.com/UVAdMIST/swmm_mpc) was used to simulate MPC in the SWMM model. MPC was simulated for a number of sea level rise scenarios and the amount of flooding was compared to the system with no controls. The Python script that ran swmm_mpc for the sea level rise scenarios is "models/runs/hgv11.py." The results were compiled and plotted with scripts in the "models/results/" directory.

The citation to the Journal of Hydrology paper is
Jeffrey M. Sadler, Jonathan L. Goodall, Madhur Behl, Benjamin D. Bowes, Mohamed M. Morsy, Exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise, Journal of Hydrology, Volume 583, 2020, 124571, ISSN 0022-1694, https://doi.org/10.1016/j.jhydrol.2020.124571.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

North Latitude

36.9694°

East Longitude

-76.1771°

South Latitude

36.8208°

West Longitude

-76.3335°

Content

Learn more about the BagIt download

Select a file to see file type metadata.

Related Resources

This resource is referenced by

https://doi.org/10.1016/j.jhydrol.2020.124571

Credits

Funding Agencies

This resource was created using funding from the following sources:

Agency Name	Award Title	Award Number
National Science Foundation	CRISP Type 2: dMIST: Data-driven Management for Interdependent Stormwater and Transportation Systems	1735587
National Science Foundation	SCC-IRG Track 1: Overcoming Social and Technical Barriers for the Broad Adoption of Smart Stormwater System	1737432

How to Cite

Sadler, J. (2020). Data and models for exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise, HydroShare, https://doi.org/10.4211/hs.5148675c6a5841e686a3b6aec67a38ee

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

Comments

There are currently no comments