the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Jan 2025
Comprehensive inventory of large hydropower systems in the Italian Alpine Region
Abstract. Climate change raises the critical need to understand its impact on water resources, particularly as hydropower’s role as a flexible, renewable energy source becomes more vital in planning for the energy system's decarbonization. While hydrological modeling represents an established tool for assessing the future evolution of water resources, a key challenge lies in its reliance on data describing the geometry and operation of hydropower systems interacting with the natural stream network. The Italian Alpine Region (IAR) is home to over 300 large hydropower systems (LHS), and its hydrological cycle is expected to suffer major alterations due to climate change. However, detailed and reliable hydrological studies in this region face hindrances due to the absence of a consistent, comprehensive, and openly available LHS source.
We present IAR-HP (Italian Alpine Region HydroPower), a comprehensive inventory specifically designed for the inclusion in hydrological modeling of LHS located in the Italian Alpine Region, to overcome this obstacle. This dataset aims to support modelers in the water-energy nexus by providing crucial information for accurately informing their models. Compiled from various online sources, IAR-HP is openly accessible and reproducible, offering a solution to the scarcity of data hindering effective storage hydropower-related simulations. The dataset was validated through a hydropower production modeling exercise, and was able to reconstruct 96.2 % of the observed hydropower production across the Italian Alpine Region. By presenting this dataset, we contribute a practical tool for scientists to reduce the inherent uncertainty of hydrological models, improving their ability to represent large hydropower systems accurately. IAR-HP holds potential for numerous applications to inform decision-making in the dynamic context of climate change.
- Preprint
(15211 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 18 Mar 2025)
-
RC1: 'Comment on essd-2024-521', Anonymous Referee #1, 11 Feb 2025
reply
The study is interesting and very useful for a better water management in the Alpine context, as well as for hydropower planning.
I have the following comments.
1) The Q_avg, in Excel, was calculated from P_med. From the equation it seems to me that P_med is an energy, not a power, and the term "P" may confuse. I suggest to use P for power and E for energy.
2) Also, I would like to ask you about the capacity factor. I saw that in the equation the author use a coefficient of 0.8, which I believe is the efficiency, and then consider all the annual hours. If the capacity factor were considered (which could generally be around 0.35), the average flow rate during the turbine hours would be approximately 3 times higher. Therefore that average flow rate is spread throughout the year, even during periods when the system is not working.
3) I don't understand, in Excel, what h1, h2, v1, v2 are. If they are water level and volume, the numeration should continue also for the other numbers (h3, v3,...hn, vn..)
4)Â In case I wanted to reconstruct the Reservoir-Intake-Plant system from Excel: in the PLT sheet I take for example the second plant which has ID 13. Its ID_UP are 4 and 12, so I assume that they are the intakes ID4 and ID12? Then, for example, I look at intake ID 4, which in fact has ID_DOWN 13 (that very plant) and ID_UP 1 and ID_UP 3, where ID 1 is actually the reservoir, but ID3 is not in any reservoir, so is it another intake? I suggest to add a "practical example" on how to use the table in order to help the reader.
5) in the PLT sheet there are data that do not appear because they refer to other excel sheets that the authors have, for example the heads
6) I suggest to try to plot Q_max (intake), Q_avg and the Q_des design flow rate of the plant calculated as Qdes=installed_power/(gamma*H*eff). What I expect is Qavg<Q_des<Qmax, where Qavg around 1/3*Qdes and Qmax around X*Qdes (X>1). This would add useful information. Then the ratio Qavg/Qdes and Qmax/Qdes may be related with the head or with the region.
7) I suggest to add a nomenclature list, with units, in the excel file.
8) A comparison with the existing literature in a Discussion section would be useful, for example where this database could be used to replicate some literature studies with more accurate data, or where similar analyses have been carried out.
Citation: https://doi.org/10.5194/essd-2024-521-RC1 -
RC2: 'Comment on essd-2024-521', Anonymous Referee #2, 17 Feb 2025
reply
The manuscript describes a hydropower dataset in the Italian Alpine Regions, covering geographic, technical, and hydrological aspects (including simulated environmental minimum flow). It comes with a publicly available dataset, following an open data policy. Therefore, the data seems valuable for regional decision-making processes and further scientific investigations. However, the manuscript appears somewhat fragmented and could benefit from revisions to improve its fluency.
My major comments are:
- The abstract could contain more quantitative features: the number of power plants in the data, total installed capacity (e.g., on L. 185), total energy production, and the share of national electricity production.
- 38 ff. refer to different nexus but never mention streamflow modification due to the hydropower infrastructure or negative impacts on ecosystems, such as hydropeaking, termopeaking, sediment transport, fish migration, or river network disconnectivity. In addition to the positive aspects of hydropower, these impacts on ecosystems should be mentioned in the introduction to provide a complete overview.
- Could the dataset also be provided as a shapefile? Having the hydrological catchments that contribute to each hydropower plant as a shapefile could be relevant for future work.
- Having information on minimum ecological flow in your data is a great benefit, especially compared to similar databases in other countries. However, I could not find the methodology for estimating these minimum flows. Maybe you can refer to this Italian paper describing the environmental flows in the different regions (Moccia et al. 2020, https://doi.org/10.4081/aiol.2020.8781 ) and describe your approach,
- Figures 2 and 3 together seem to call for a third figure showing the share (%) of your collected hydropower plants (y-axis) contributing to the share (%) of total annual hydropower production of these plants (x-axis) to show, e.g. 20 power plants produce 50% of the total hydropower production.
- Figure 5: I'm not sure the relative error makes sense, as the smaller the annual production gets, the bigger the error becomes, as described in Table 4. I would replace it with the figure proposed in comment 5.
- Section 2.2 (including subsections) provides an overview of the different sources. I suggest fewer subsections, merging the information and the data source and then describing how these datasets are used for the simulations.
- Section 3 provides information for each province. I suggest providing a synthesis paragraph for the entire Italian Alpine Region.
And some minor comments:
- The manuscript and the dataset are full of abbreviations, which makes it challenging to read. I propose a list of abbreviations at the beginning of the manuscript and on an added sheet in the Excel file.
- 22: I guess from the late 19th century. The late 1800s would be early for electricity production.
- 76: The title should be "Materials and Methods" since different data sources are described.
- g., in L. 271, there is a double bracket in the manuscript ‘Bertoldi et al. (2010))’. There are more of these in the manuscript, which should be avoided.
Citation: https://doi.org/10.5194/essd-2024-521-RC2
Data sets
IAR-HP Andrea Galletti et al. https://doi.org/10.5281/zenodo.14040999
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 188 | 26 | 6 | 220 | 5 | 5 |
- HTML: 188
- PDF: 26
- XML: 6
- Total: 220
- BibTeX: 5
- EndNote: 5
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1