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The University of Massachusetts Amherst

The Connecticut River Flow Restoration Study: A watershed-scale assessment of the potential for flow restoration through dam re-operation

Authors:

Katie Kennedy

Kim Lutz

Christopher Hatfield

Leanna Martin

Townsend Barker

K Kennedy

Richard Palmer

Luke Detwiler

Jocelyn Anleitner

J Hickey

Publication Type:
Journal Article
Year of Publication:
2018
Publisher:
the Nature Conservancy, U.S. Army Corps of Engineers, and University of Massachusetts Amherst.
City:
Northampton, MA. ​
Year:
2018
Date:
06/2018
URL:
https://www.nae.usace.army.mil/Portals/74/docs/Topics/CTRiver/CT-River-FlowRestorationStudy-June2018.pdf

Abstract

To evaluate current operations and develop operational alternatives, three model frameworks were used. The Connecticut River Unimpaired Streamflow Estimator (CRUISE) is a model developed by the U.S. Geological Survey to estimate unimpaired streamflow at any perennial stream location within the watershed. The U.S. Army Corps of Engineers (USACE) Hydrologic Engineering Center's Reservoir Simulation Model (HEC-ResSim) is a rule-based operations model that was used to simulate the operations of 73 major reservoirs throughout the watershed. The Connecticut River Optimization Modeling Environment (CROME) is a goal- based linear programming optimization model developed by the University of Massachusetts Amherst. The CROME model searches all potentially optimal combinations of flow release strategies among 54 dams in the watershed to find the one that best matches a desired system state given an objective function, such as provision of prescribed streamflows, maintenance of reservoir storage targets, generation of revenue from hydroelectric production, or allowance of water for municipal supply. The objective function used to represent ecological value in the CROME model was related to minimizing the deviations between operational flow and estimated natural flow, given "acceptable deviations" that were developed from expert-elicited ecological flow recommendations.