Please wait for the process to complete.
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.
Data and models for exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise
||This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (email@example.com) for information on this 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.
|Citation:||See how to cite this resource|
|+1 Votes:||Be the first one to this.|
|Comments:||No comments (yet)|
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.
|This resource is referenced by||https://doi.org/10.1016/j.jhydrol.2020.124571|
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
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/