A trap-and-haul fishway for upstream transfers of migrating fish at a challenging dam site

Harris, John H.; Roberts, David T.; O’Brien, Steven; Mefford, Brent; Pitman, Kris S.

doi:10.1080/24705357.2019.1669080

Cited by 13 publications

(11 citation statements)

References 31 publications

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“…It also helps to understand whether the predicted ow will meet the environmental ow. In the present study, it is found that ow is reduced in the post-dam period and it is likely to be reduced by35-43% in the coming 10 years. This nding is quite similar to the ndings of Poff and Zimmerman, (2010), Wang et al (2016),Liu et al (2016), Rahman et al (2017), Kumar and Jayakumar (2018, 2021), Pal and Talukdar (2020), Mezger et al (2020), Li et a.…”

supporting

confidence: 50%

Flow Forecasting and Measuring Environmental Flow Using Machine Learning Techniques

Pal

Saha

2022

Preprint

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Flow alteration study in rivers persuaded by damming is well studied and reported significant flow failure. But how far the existing flow is ecologically ambient, in near future and what will be such situation are less addressed. Particularly, no such work is available in Atreyee river, a transboundary river between India and Bangladesh, the present area of interest. But it is essential from socio-ecological and ecosystem standpoints. Considering this, the present study has tried to predict river flow and assess its ecological relevance using soft computing advanced machine learning techniques like ANN, SVM and RF. Eco-deficit and surplus were assessed using a flow duration curve (FDC). The results indicate all the months' recorded eco-deficit conditions. Estimated environmental flow is moderately modified at present as per Environmental Management Class (EMC). The observed flow is 37.8m3/sec which is less than FDC estimated environmental flow (42.3m3/sec). Predicted flow in 2028, as per the best suited ANN, would be 56% lesser than present indicating the further departure of flow from the required environmental flow. It will perhaps pose an excessive burden to the ecosystem and socio-ecological fabrics.

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supporting

confidence: 50%

Flow Forecasting and Measuring Environmental Flow Using Machine Learning Techniques

Pal

Saha

2022

Preprint

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“…Trap and haul innovations for application at large dams (Harris et al 2019); Innovative solutions to provide passage for small bodied-fish (Knapp et al 2019;Marsden and Stuart 2019); Importance of ensuring hydrology and biology are considered at design phase (Baumgartner et al 2019);…”

Section: Global Advances In Fish Passage Research and Practicementioning

confidence: 99%

Global advances in fish passage research and practice

Baumgartner

Silva

2019

Journal of Ecohydraulics

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“…In the context of fisheries research, technology growth has experienced a similar, albeit not as quite as steep, upward trajectory. From new, improved ways of collecting and analyzing big data, to using drones for surveying fish populations in remote, hard‐to‐reach areas (Harris et al 2019a, 2019b), the opportunities to benefit from advanced technology in fisheries research and management are endless. Where technological innovation and refinement in fisheries has lagged is in the monitoring, study, and improvement of fish passage; concrete fish ladders and trap‐and‐haul via truck were conceived generations ago, yet these remain the primary methods for managing migratory species around waterway barriers such as dams.…”

Section: Figurementioning

confidence: 99%

Upstream and Downstream – Exciting Advances to Modernize Fish Passage and Improve Data Collection

2021

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Considering the myriad of ways in which advanced technology is being used in fisheries research, keeping atop of the newest developments is a challenge. The transfer of such specialized knowledge, even within the fisheries community, can be difficult, thereby hindering more widespread use of advanced technology in fisheries research. This predicament can be further compounded when information exchange between the freshwater and marine fisheries communities is limited. In a constantly shifting technological landscape, effecting stronger information transfer about technology within the fisheries community will lead to greater innovation, broader application, and more efficient and accurate science. This is the goal of the AFS Fisheries Information and Technology Section (FITS). This is the third article in a series that FITS has coordinated with Fisheries to highlight some of the ways in which the latest advanced technologies are being used in marine and freshwater fisheries research. To learn more, check out https://units.fisheries.org/fits/, find us on Facebook and Twitter (@AFSFITS).

show abstract

A trap-and-haul fishway for upstream transfers of migrating fish at a challenging dam site

Cited by 13 publications

References 31 publications

Flow Forecasting and Measuring Environmental Flow Using Machine Learning Techniques

Flow Forecasting and Measuring Environmental Flow Using Machine Learning Techniques

Global advances in fish passage research and practice

Upstream and Downstream – Exciting Advances to Modernize Fish Passage and Improve Data Collection

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