Performing two independent surveys in 2016 and 2017 over a flat sample plot (6700 m ${}^2$ ), we compare snow-depth measurements from Unmanned-Aerial-System (UAS) photogrammetry and from a new high-resolution laser-scanning device (MultiStation) with manual probing, the standard technique used by operational services around the world. While previous comparisons already used laser scanners, we tested for the first time a MultiStation, which has a different measurement principle and is thus capable of millimetric accuracy. Both remote-sensing techniques measured point clouds with centimetric resolution, while we manually collected a relatively dense amount of manual data (135 pt in 2016 and 115 pt in 2017). UAS photogrammetry and the MultiStation showed repeatable, centimetric agreement in measuring the spatial distribution of seasonal, dense snowpack under optimal illumination and topographic conditions (maximum RMSE of 0.036 m between point clouds on snow). A large fraction of this difference could be due to simultaneous snowmelt, as the RMSE between UAS photogrammetry and the MultiStation on bare soil is equal to 0.02 m. The RMSE between UAS data and manual probing is in the order of 0.20–0.30 m, but decreases to 0.06–0.17 m when areas of potential outliers like vegetation or river beds are excluded. Compact and portable remote-sensing devices like UASs or a MultiStation can thus be successfully deployed during operational manual snow courses to capture spatial snapshots of snow-depth distribution with a repeatable, vertical centimetric accuracy.

Recently, Unmanned Aerial Vehicles (UAV) have opened up unparalleled opportunities for alpine glacier monitoring, as they allow for reconstructing extensive and high-resolution 3D models. In order to evaluate annual ice flow velocities and volume variations, six yearly measurements were carried out between 2015 and 2020 on the debris-covered Belvedere Glacier (Anzasca Valley, Italian Alps) with low-cost fixed-wing UAVs and quadcopters. Every year, ground control points and check points were measured with GNSS. Images acquired from UAV were processed with Structure-from-Motion and Multi-View Stereo algorithms to build photogrammetric models, orthophotos and digital surface models, with decimetric accuracy. Annual glacier velocities were derived by combining manually-tracked features on orthophotos with GNSS measurements. Velocities ranging between 17 m y⁻¹ and 22 m y⁻¹ were found in the central part of the glacier, whereas values between 2 m y⁻¹ and 7 m y⁻¹ were found in the accumulation area and at the glacier terminus. Between 2 × 10⁶ m³ and 3.5 × 10⁶ m³ of ice volume were lost every year. A pair of intra-year measurements (October 2017–July 2018) highlighted that winter and spring volume reduction was ∼1/4 of the average annual ice loss. The Belvedere monitoring activity proved that decimetric-accurate glacier models can be derived with low-cost UAVs and photogrammetry, limiting in-situ operations. Moreover, UAVs require minimal data acquisition costs and allow for great surveying flexibility, compared to traditional techniques. Information about annual flow velocities and ice volume variations of the Belvedere Glacier may have great value for further understanding glacier dynamics, compute mass balances, or it might be used as input for glacier flow modelling.

Ethiopia is growing fast, and the country has a dire need of energy. To avoid environmental damages, however, Ethiopia is looking for green energy polices, including hydropower exploitation, with large water availability (i.e., the Blue Nile, the greatest tributary of Nile river). Besides other dams on the Omo river, the GIBE family, Ethiopia is now building the largest hydropower plant of Africa, the GERD (Grand Ethiopian Renaissance Dam), on the Blue Nile river, leading to tensions between Ethiopia, and Egypt, due to potentially conflictive water management. In addition, present and prospective climate change may affect reservoirs’ operation, and this thereby is relevant for downstream water users, population, and environment. Here, we evaluated water management for the GERD, and GIBE III dams, under present, and future hydrological conditions until 2100. We used two models, namely, Poli-Hydro and Poli-Power, to describe (i) hydrological budget, and flow routing and (ii) optimal/maximum hydropower production from the two dams, under unconstrained (i.e., no release downstream besides MIF) and constrained (i.e., with fair release downstream) simulation. We then used climate change scenarios from the reports CMIP5/6 of the Intergovernmental Panel on Climate Change (IPCC) until 2100, to assess future hydropower production. Our results demonstrate that the filling phase of the GERD, particularly critical, have optimal filling time of 5 years or so. Stream flows at GERD could be greater than the present ones (control run CR) at half century (2050–2059), but there could be large decrease at the end of century (2090–2099). Energy production at half century may increase, and then decrease until the end of century. In GIBE III discharges would increase both at half century, and at the end of century, and so would energy production. Constrained, and unconstrained simulation provide in practice similar results, suggesting potential for shared water management in both plants.

Greenhouse gas reduction policies will have to rely as much as possible upon renewable, clean energy sources. Hydropower is a very good candidate, since it is the only renewable energy source whose production can be adapted to demand, and still has a large exploitation margin, especially in developing countries. However, in Europe the contribution of hydropower from the cold water in the mountain areas is at stake under rapid cryospheric down wasting under global warming. Italian Alps are no exception, with a large share of hydropower depending upon cryospheric water. We study here climate change impact on the iconic Sabbione (Hosandorn) glacier, in the Piemonte region of Italy, and the homonymous reservoir, which collects water from ice melt. Sabbione storage plant has operated since 1953 and it was, until recently, the highest altitude dam of Europe at 2460 m asl, and the former second largest dam of the Alps with 44 Mm³. We use two models, namely Poly-Hydro and Poly-Power, to assess (i) present hydrological budget and components (i.e., ice/snow melt, rainfall), and (ii) hydropower production under optimal reservoirs’ management, respectively. We then project forward hydrological cycle including Sabbione glacier’s fate, under properly downscaled climate change scenarios (three General Circulation Models, three Representative Concentration Pathways, nine scenarios overall) from IPCC until 2100, and we assess future potential for hydropower production under the reservoir’s re-operation. Mean annual discharge during 2000–2017 is estimated at 0.90 m³ s⁻¹, with ice melt contribution of ca. 11.5%, and ice cover as measured by remote sensing changing from 4.23 km² in 2000 to 2.94 km² in 2017 (−30%). Mean hydropower production during 2005–2017 is estimated as 46.6 GWh. At the end of the century ice covered area would be largely depleted (0–0.37 km²), and ice melt contribution would drop largely over the century (0%–10%, 5% on average at half century, and null in practice at the end of century). Therefore, decreased ice cover, and uncertain patterns of changing precipitation, would combine to modify the future stream fluxes (−22% to −3%, −10% on average at half century, and −28% to 1%, average −13%, at the end of century). Power production, driven by seasonal demand and water availability, would change (decrease) in the future (−27% to −8%, −15% on average at half century, and −32% to −5%, −16% at the end of century). Our results demonstrate potential for decrease of cold water in this area, paradigmatic of the present state of hydropower in the Alps, and subsequent considerable hydropower losses under climate change, and claim for adaptation measures therein.

On the basis of theoretical considerations, the technical note presents two practical formulas for the dimensioning of air valves when filling a pipe with water. One is to be used for designing air valves on the basis of the maximum allowed water hammer overpressures; the other when the maximum in pipe water velocity is set. The reliability of these formulas was tested with a numerical model based on the same hypothesis, which was in turn verified with experimental tests.

The assessment of the effect of the electricity price on energy production is important when studying the profitability and benefits of energy systems. The demand and price of electricity depends upon societal and economic development, but it is subject to a seasonal, weather-dependent variability, and possibly to long-term variation under climate change. Here, we developed a methodology to model the energy demand and electricity price in response to gross domestic product (GDP), temperatures, and random factors, usable for the purpose of cost/benefit analysis of production systems. The method was applied to the case study of the Italian electricity market, showing acceptable capacity of modelling recently observed price fluctuations. Then, we gathered climate projections until 2100 from three global climate models of the IPCC AR5, under RCP2.6, RCP4.5, and RCP8.5, and we produced future scenarios of price fluctuations for two reference decades, half-century 2040–2049, and end-of-century 2090–2099. Our scenarios displayed a potential for the reduction of energy demand in winter, and an increase in summer and spring, and for the similarly-changing electricity price throughout the 21st century. We discuss the application of our model with the specific aim of the projection of future hydropower production, as controlled by climate, hydrology, demand, and price constraints, with examples from recent studies. Our results provide a tool for modelling the behaviour of energy systems based upon knowledge of external factors, usable for further investigation of energy systems, such as hydropower, and others, taking into account the key variables affecting energy production and energy price.