Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.739460
Title: Optimising river infrastructure placement and mitigation decisions
Author: Ioannidou, Christina
ISNI:       0000 0004 7227 7818
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2017
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Abstract:
We address the problem of locating small hydropower dams in an environmentally friendly manner. We propose the use of a multi-objective optimization model to maximize total hydropower production, while limiting negative impacts on river connectivity. Critically, we consider the so called "backwater effects" that dams have on power generation at nearby upstream sites via changes in water surface profiles. We further account for the likelihood that migratory fish and other aquatic species can successfully pass hydropower dams and other artificial/natural barriers and how this is influenced by backwater effects. Although naturally represented in nonlinear form, we manage through a series of linearization steps to formulate a mixed integer linear programing model. We illustrate the utility of our proposed framework using a case study from England and Wales. Interestingly, we show that for England and Wales, a region heavily impacted by a large number of existing river barriers, installation of small hydropower dams fitted with even moderately effective fish passes can, in fact, create a win-win situation that results in increased hydropower and improved river connectivity. We also propose a novel optimization framework to prioritize fish passage barrier mitigation decisions that incorporates both fish population and dispersal dynamics in order to maximize equilibrium population size. A case study involving a wild coho salmon (Oncorhynchus kisutch) population from the Tillamook basin, Oregon, USA is used to illustrate the benefits of our approach. We consider two extreme homing patterns, river and reach level homing, as well as straying. Under density dependent population growth, we find that the type of homing behavior has a significant effect on barrier mitigation decisions. In particular, with reach homing, our model results in virtually the same population sizes as a more traditional barrier prioritization procedure that seeks to maximize the accessible habitat. With river homing, however, there is no need to remove all barriers to maximize equilibrium population size. Indeed, a stochastic version of our model reveals that removing all barriers actually results in a marginal increase in quasi-extinction risk. We hypothesize that this is due to a population thinning effect of barriers, resulting in a surplus of recruits in areas of low spawner density. Our present study should prove useful to fish conservation managers by assessing the relative importance of incorporating spatiotemporal fish population dynamics in river connectivity restoration planning. Finally, habitat fragmentation is a leading threat to global biodiversity. Restoring habitat connectivity, especially in freshwater systems, is considered essential in improving ecosystem function and health. Various studies have looked at cost effectively prioritizing river barrier mitigation decisions. In none of these, however, has the importance of accounting for the potential presence of unknown or "hidden" barriers been considered. In this study, we propose a novel optimization based approach that accounts for hidden barrier uncertainty in river connectivity restoration planning and apply it in a case study of the US state of Maine. We find that ignoring hidden barriers leads to a dramatic reduction in anticipated accessible habitat gains. Using a conventional prioritization approach, habitat gains are on average 60% lower than expected across a range of budgets when there are just 10% additional but unknown barriers. More importantly our results show that anticipating for hidden barriers can improve potential gains in accessible habitat in excess of 110% when the budget is low and the number of hidden barriers comparatively large. Finally, we find that solutions optimized for an intermediate number of unknown barriers perform well regardless of the actual number of hidden barriers. In other words, we can build-in robustness into the barrier removal planning framework. Dealing with the hidden elephant in the room could lead to a far more realistic approach of the habitat connectivity restoration issue.
Supervisor: O'Hanley, Jesse ; Scappara, Maria Paola Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.739460  DOI: Not available
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