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Title: A temporal perspective to dam management: influence of dam life and threshold fishery conditions on the energy-fish tradeoff
While hydroelectric dams play a significant role in meeting the increasing energy demand worldwide, they pose a significant risk to riverine biodiversity and food security for millions of people that mainly depend upon floodplain fisheries. Dam structures could affect fish populations both directly and indirectly through loss of accessible spawning and rearing habitat, degradation of habitat quality (e.g., changes in temperature and discharge), and/or turbine injuries. However, our understandings of the impacts of dam life span and the initial fishery conditions on restoration time and hence the dynamic hydropower (energy)-fish (food) nexus remain limited. In this study, we explored the temporal energy-food tradeoffs associated with a hydroelectric dam located in the Penobscot River basin of the United States. We investigated the influence of dam life span, upstream passage rate, and downstream habitat area on the energy-food tradeoffs using a system dynamics model. Our results show that around 90% of fish biomass loss happen within 5 years of dam construction. Thereafter, fish decline slowly stabilizes and approaches the lowest value at around the 20th year after dam construction. Fish restoration period is highly sensitive even to a short period of blockage. The biomass of alewife spawners need 18 years to recover more » with only 1-year of blockage to the upstream critical habitats. Hydropower generation and loss of fish biomass present a two-segment linear relationship under changes in dam life span. When the dam life span is less than 5 years, generating 1 GWh energy cause around 0.04 million kg loss of fish biomass; otherwise, the loss of fish biomass is 0.02 million kg. The loss of fish biomass could be significantly decreased with minimal energy loss through increasing upstream passage rate and/or the size of downstream habitat area. « less
Authors:
;
Award ID(s):
1539071
Publication Date:
NSF-PAR ID:
10114032
Journal Name:
Stochastic Environmental Research and Risk Assessment
ISSN:
1436-3240
Sponsoring Org:
National Science Foundation
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