Figure 4. The performance of the re-regulation reservoirs to re-regulate the discharge for P (40%, 2) during 500 hours. (a) illustrates how the reservoir limits the discharge to the thresholds defined in the algorithm and achieves optimal conditions whenever possible. (b) distinctly shows the ramping rates before and after implementing the re-regulation reservoir.
Discussion
Re-regulation reservoirs (RRR) have emerged as a promising method for mitigating the ecological impacts of hydropeaking. While the efficacy of RRRs in mitigating hydropeaking impacts is still being assessed, early studies suggest that this novel approach may be a valuable tool for enhancing the ecological sustainability of hydropower operations. Studies have shown that RRRs can reduce the adverse impacts of hydropeaking downstream of hydropower plants and reduce the deleterious effects of hydropeaking on aquatic ecosystems (Tonolla et al., 2017). Compared to other mitigation measures, such as the installation of downstream flow control devices or modifying the operation of hydropower facilities, RRRs offer several advantages. These include greater flexibility and adaptability to changing environmental conditions, power, and water demand without increasing the operational cost of power systems. While RRRs also possess the potential to provide other services, such as water storage and flood control (Anindito et al., 2019; Premstaller et al., 2017; Tonolla et al., 2017). In practice, RRRs could be an artificial structure, natural water reservoir, flood plain or any other storage possibility near by the HPP. Our study did not prioritize the examination of structural or operational designs. Instead, we focused on exploring theoretical approaches to mitigate hydropeaking and developed a model to operate and estimate the required RRR volumes.
This study tested and determined the RRR volumes required to meet the objectives and priorities outlined in section 2.3 of the Kemijoki River downstream from Taivalkoski HPP using a re-regulation algorithm developed specifically for this study. The flow data of the Taivalkoski HPP was scaled down to create a base case that can be used for other similar HPPs. While we recognize that re-regulation is generally more manageable in smaller river systems due to their smaller reservoir capacities and volumes, our case data from a large river system can still be leveraged to explore theoretical possibilities for re-regulation practices. The results indicate that for most of the tested permutations, the required volume of the RRRs increased as the thresholds for peak and minimum hourly flows and the ramping rates became more stringent (Figure 2). The observed outcome can be attributed to two factors. Firstly, as the thresholds became more stringent, they activated the conditions that enable water storage by the algorithm at more time steps than those that facilitate water release. The flow pattern controls the algorithm’s decision to store or release water. Secondly, a more stringent threshold necessitates storing or releasing larger quantities of water. Considering both factors, i.e., increased water storage events and an increased water volume to be stored in a singular event, led to the requirement of greater RRR volumes as the thresholds became more stringent. Nonetheless, for some permutations, this trend was not observed. One example is the needed reservoir volumes for P (10%, 3.5) and P (10%, 4) were larger than the reservoir volume needed for P (10%, 2.5) that had more stringent ramp rate threshold. For this particular case, the water released in proportion to the water stored for P (10%, 3.5) and P (10%, 4) was less efficient than that of P (10%, 2.5) due to algorithms increased propensity to store water rather than release water. As such, inadequate (i.e., too slow) water release back into the waterway might increase the required RRR volume or lead to small volume availability during high flows. Furthermore, if a flow adjustment of 10% is deemed sufficient, it is more beneficial then to consider permutation P (10%, 2.5) since it has more stringent ramp rate thresholds while requiring a smaller RRR volume. Whereas, if the daily peak and minimum flows are of greater concern than the ramp rates due to the ecological needs of the river, it would be more efficient to consider permutation P (20%, 4) than P (10%, 4) which requires a smaller RRR volume. The increased flow adjustment threshold in P (20%, 4) activated the conditions that enable water release by the algorithm at more time steps than those that allow water storage. Thus, resulting in a reduction of the required RRR volumes when compared to P (10%, 4). This highlights the significance of maintaining a proportional balance between storing and releasing water. As such, choosing the optimal re-regulation of reservoir volume is related to the river regime and sub-daily flow patterns. These findings highlight the importance of careful consideration of the unique characteristics of a given river and its ecosystem when designing RRRs for hydropeaking mitigation.
To achieve greater efficiency, RRRs can be optimized by tailoring their design to the ecological needs of the river and the desired mitigation objectives. Hayes et al. (2019), proposed a mitigation approach that is specific for the life cycle stages of fish. For instance, if the objective is to improve the larval life stage of trout and grayling rather than eliminating the stranding of fish, it might be more efficient then to have less stringent ramp rate thresholds resulting in the reduction of the required volume of RRRs. Another important factor to consider when optimizing the reservoir is the RRR operation period. It might be more efficient to adjust the threshold values and objectives according to the seasons, days, or time steps that are deemed significant to the ecological status of river rather than using constant threshold values for the whole year. Furthermore, excluding periods with less ecological significance from the operation period would reduce the required volume of RRRs. For the case studied in this work, excluding July and August from the operation period would be the most impactful on the required RRR volume as the highest flow occurs in the late spring or early summer. However, the re-regulation operation period should be tailored according to the ecological needs of the river in order to reduce the required RRR volume. Overall, these findings highlight the potential for optimizing the design and operation of RRRs for hydropeaking mitigation, based on the unique needs of the local ecosystem and the desired mitigation objectives. By doing so, a greater efficiency and a reduction in the required RRR volume, while minimizing the impact of hydropeaking on downstream ecosystem can be achieved.
The model design in this work can be used to determine the required RRR volumes for other HPP in any other river system of various sizes and flows. However, the range of thresholds for hydropeaking should be defined to best suit the flow pattern and river size. Furthermore, the model could be enhanced by incorporating additional conditions into the algorithm such as RRR operational period (season), timing of hydropeaking event (day and night), water temperature fluctuations, and sediment loads, while also accounting for water supply, irrigation, and recreational needs. Additionally, it may be useful to investigate a model with a RRR that is distant from the HPP. This would present the opportunity to study corridors connecting HPPs with RRRs as additional storage volumes. Also, a model that incorporates flow velocity and water losses from the RRR would further enhance the understanding, use, and optimization of RRRs.
Conclusion
We investigated in this work the capabilities of RRRs to limit flow components to a range of thresholds, such as peak flow, minimum flow, and ramping rates. The results indicate that as the thresholds become more stringent, the required RRR volume increase. In certain cases, however, this trend was not observed, indicating that the design of RRRs should be tailored according to mitigation objectives and ecological needs of river systems. The model developed in this study can aid HPP operators, authorities, and researchers in designing, optimizing, and rating the feasibility of introducing RRRs to river systems. However, several avenues for future research can be pursued to further advance the understanding, use, and optimization of RRRs. One promising area of investigation is the development of more sophisticated models that incorporate, RRR operational period (season), timing of hydropeaking event (day or night), as well as water temperature fluctuations and sediment loads. Finally, additional research is needed to better understand the ecological impacts of hydropeaking, including its effects on fish populations, water quality, and overall ecosystem health. By advancing our understanding of hydropeaking and its impacts, we can develop more effective strategies for managing our water resources and minimizing the negative impacts of hydroelectric power generation.