Exploring sensitivities to hydropeaking in Atlantic salmon parr using individual‐based modelling

Abstract

Hydropeaking (the release of water pulses at hydropower plants) results in temporary reductions in river channel water‐covered area downstream, which may cause fish mortality through stranding. We used a mechanistic modelling approach to examine how both the form of the hydropeaking cycle and the characteristics of the affected fish control how hydropeaking may cause stranding mortality of fish. We modelled the response of Atlantic parr to hydropeaking in a regulated watercourse in central Norway (the River Nidelva) using an individual‐based population model designed explicitly to examine fish behaviour and stranding mortality during hydropeaking. A response to hydropeaking, involving migration from the riverbanks towards the mid‐channel on down‐ramping and a return to the riverbanks on up‐ramping, was based on individuals being parameterized to migrate to habitat properties that spatially changed throughout the hydropeaking cycle. We found that stranding mortality was strongly dependent on both the form of the hydropeaking cycle and on the fish response. Total stranding mortality was more dependent on the down‐ramping speed than the duration of the minimum flow period. Total stranding mortality was greatest when there was a low movement speed, leading to individuals being stranded, combined with a high probability of dying per unit of time when stranded. Given the sensitivity of mortality to the fish response and the lack of detailed field studies quantifying this, we conclude that this area requires further controlled studies for parameterizing models used to predict effects of hydropeaking on fish. Simulation‐based modelling, where there is a 100% control of and knowledge of fish characteristics, where a range of deterministic functions can be evaluated and in which boundary conditions can be easily controlled, may be a useful research tool to complement empirical studies.

A jump-driven self-exciting stochastic fish migration model and its fisheries applications

“…Furthermore, our developed stochastic process model can be directly used to describe the population dynamics in the long-term resource management problem [68]. A more sophisticated model can be pursued by clarifying the interaction between fish migration and hydrological disturbance [69,70], while the challenge will be the identification of their parametric relationship. Finally, the contribution of diadromous fish species to the global carbon transport [71] can be re-examined by using the proposed model.…”

Classification of River Sediments Fractions over a Wide Range including Shallow Water Areas Based on Aerial Images from Uav with Convolution Neural Network

“…The accuracy is shown as the confusion matrix in Table 2. Various confounding factors cause such a reduction of the accuracy [49]. In this case, the decrease in accuracy is a natural result because the classification of the underwater samples was performed using a network trained on terrestrial samples.…”

“…These targets are stagnant water areas where there is no current and no diffuse reflection of waves from the surface of the water. On the other hand, in river channels, as Hedger et al [49] pointed out, automated extraction of information on river habitats from remote sensing imagery is difficult due to a large number of confounding factors. There are some attempts to apply artificial intelligence techniques to map surface cover types [50], hydromorphological features [51], mesohabitats [52], salmon redds [53], etc., but there is a possibility of misclassification due to water surface waves [54].…”

Impact of interbasin transfer hydroelectric project on downstream aquatic habitat

“…A hydropeaking dam upstream can affect the biodiversity of the downstream ecosystem through hydrologic alterations (Bürgler et al, 2023; Meile et al, 2011; Moreira et al, 2019; Ray & Sarma, 2011; Wang et al, 2019). Artificial flow fluctuations due to hydropeaking can hinder the sustenance rate of aquatic organisms (Glowa et al, 2023; Greimel et al, 2018; Hedger et al, 2023). Thus, to protect the ecosystem and to acquire the maximum benefit of electricity generation, there is a need for an integrated water resources management of regulated rivers (Widén et al, 2022).…”