How Will Hydroelectric Power Generation Develop under Climate Change Scenarios? A Case Study in the Upper Danube Basin

The water-energy-food-ecosystem nexus in the Danube River Basin: Exploring scenarios and implications of maize irrigation

The Water-Energy-Food-Ecosystem (WEFE) nexus concept postulates that water, energy production, agriculture and ecosystems are closely interlinked. In transboundary river basins, different sectors and countries compete for shared water resources. In the Danube River Basin (DRB), possible expansion of agricultural irrigation is expected to intensify water competition in the WEFE nexus, however, trade-offs have not yet been quantified. Here, we quantified trade-offs between agriculture, hydropower and (aquatic) ecosystems in the DRB resulting from maize irrigation when irrigation water was withdrawn from rivers. Using the process-based hydro-agroecological model PROMET, we simulated three maize scenarios for the period 2011-2020: (i) rainfed; (ii) irrigated near rivers without considering environmental flow requirements (EFRs); (iii) irrigated near rivers with water abstractions complying with EFRs. Maize yield and water use efficiency (WUE) increased by 101-125 % and 29-34 % under irrigation compared to rainfed cultivation. Irrigation water withdrawals from rivers resulted in moderate to severe discharge reductions and, without consideration of EFRs, to substantial EFR infringements. Annual hydropower production decreased by 1.0-1.9 % due to discharge reductions. However, the financial turnover increase in agriculture (5.8-7.2 billion €/a) was two orders of magnitude larger than the financial turnover decrease in hydropower (23.9-47.8 million €/a), making water more profitable in agriculture. Irrigation WUE was highest for EFR-compliant irrigation, indicating that maintaining EFRs is economically beneficial and that improving WUE is key to attenuating nexus water competition. Current maize production could be met on the most productive 35-41 % of current maize cropland under irrigation, allowing 59-65 % to be returned to nature without loss of production. Maize priority areas were on fertile lowlands near major rivers, while biodiversity priority areas were on marginal cropland of highest biodiversity intactness. Our quantitative trade-off analysis can help identifying science-based pathways for sustainable WEFE nexus management in the DRB, also in light of climate change.

Impacts of LULC and climate changes on hydropower generation and development: A systematic review

There is a growing concern on a global scale that the world should transition towards the utilisation of energy-efficient technologies. Hydropower plays a very significant part in the fight against climate change, and as a result, it lessens the impact that climate changewill have on our ability to achieve the Sustainable Development Goals (SDGs). Both the effectiveness of hydropower generation and the amount of streamflow are impacted by climate change as well as land use and land cover (LULC). Accordingly, the purpose of this study is to conduct a literature review on the topic of the past and future effects of climate, land use, and land cover changes on hydropower generation. This review will be based on the entries found in a number of reliable databases. A systematic literature review was carried out to analyse how LULC and climate change will affect hydropower generation and development. The research was based on 158 pieces of relevant literature that had been reviewed by experts and indexed in Scopus, Google Scholar, and ScienceDirect. The review was carried out to determine three goals in mind: the impact of climate change on hydropower generation and development; the impact of climate change on streamflow; and the combined impact of changes in climate and changes in LULC on hydropower. The findings bring to light the primary factors contributing to climate change as well as shifts in LULC which are essential to the generation of hydropower on all scales. The study identifies factors such as precipitation, temperature, floods, and droughts as examples of climate change. Deforestation, afforestation, and urbanisation are identified as the primary causes of changes in LULC over the past several decades. These changes have a negative impact on the generation and development of hydropower.

A Near Real-Time Hydrological Information System for the Upper Danube Basin

The multi-national catchment of the Upper Danube covers an area of more than 100,000 km2 and is of great ecological and economic value. Its hydrological states (e.g., runoff conditions, snow cover states or groundwater levels) affect fresh-water supply, agriculture, hydropower, transport and many other sectors. The timely knowledge of the current status is therefore of importance to decision makers from administration or practice but also the interested public. Therefore, a web-based, near real-time hydrological information system was conceptualized and developed for the Upper Danube upstream of Vienna (Upper Danube HIS), utilizing ERA5 reanalysis data (ERA5) and hydrological simulations provided by the semi-distributed hydrological model COSERO. The ERA5 reanalysis data led to comparatively high simulation performance for a total of 65 subbasins with a median NSE and KGE of 0.69 and 0.81 in the parameter calibration and 0.63 and 0.75 in the validation period. The Upper Danube HIS was implemented within the R programming environment as a web application based on the Shiny framework. This enables an intuitive, interactive access to the system. It offers various capabilities for a hydrometeorological analysis of the 65 subbasins of the Upper Danube basin, inter alia, a method for the identification of hydrometeorological droughts. This proof of concept and system underlines how valuable information can be obtained from freely accessible data and by the means of open source software and is made available to the hydrological community, water managers and the public.

Machine Learning-Based Small Hydropower Potential Prediction under Climate Change

As the effects of climate change are becoming severe, countries need to substantially reduce carbon emissions. Small hydropower (SHP) can be a useful renewable energy source with a high energy density for the reduction of carbon emission. Therefore, it is necessary to revitalize the development of SHP to expand the use of renewable energy. To efficiently plan and utilize this energy source, there is a need to assess the future SHP potential based on an accurate runoff prediction. In this study, the future SHP potential was predicted using a climate change scenario and an artificial neural network model. The runoff was simulated accurately, and the applicability of an artificial neural network to the runoff prediction was confirmed. The results showed that the total amount of SHP potential in the future will generally a decrease compared to the past. This result is applicable as base data for planning future energy supplies and carbon emission reductions.

Analysis of Small Hydropower Generation Potential: (2) Future Prospect of the Potential under Climate Change

The interest in renewable energy to replace fossil fuel is increasing as the problem caused by climate change has become more severe. In this study, small hydropower (SHP) was evaluated as a resource with high development value because of its high energy density compared to other renewable energy sources. SHP may be an attractive and sustainable power generation environmental perspective because of its potential to be found in small rivers and streams. The power generation potential could be estimated based on the discharge in the river basin. Since the river discharge depends on the climate conditions, the hydropower generation potential changes sensitively according to climate variability. Therefore, it is necessary to analyze the SHP potential in consideration of future climate change. In this study, the future prospect of SHP potential is simulated for the period of 2021 to 2100 considering the climate change in three hydropower plants of Deoksong, Hanseok, and Socheon stations, Korea. The results show that SHP potential for the near future (2021 to 2040) shows a tendency to be increased, and the highest increase is 23.4% at the Deoksong SPH plant. Through the result of future prospect, we have shown that hydroelectric power generation capacity or SHP potential will be increased in the future. Therefore, we believe that it is necessary to revitalize the development of SHP to expand the use of renewable energy. In addition, a methodology presented in this study could be used for the future prospect of the SHP potential.

Development of a Hydropower Turbine Using Seawater from a Fish Farm

Discharge water from fish farms is a clean, renewable, and abundant energy source that has been used to obtain renewable energy via small hydropower plants. Small hydropower plants may be installed at offshore fish farms where suitable water is obtained throughout the year. It is necessary to meet the challenges of developing small hydropower systems, including sustainability and turbine efficiency. The main objective of this study was to investigate the possibility of constructing a small hydropower plant and develop 100 kW class propeller-type turbines in a fish farm with a permanent magnet synchronous generator (PMSG). The turbine was optimized using a computer simulation, and an experiment was conducted to obtain performance data. Simulation results were then validated with experimental results. Results revealed that streamlining the designed shape of the guide vane reduced the flow separation and improved the efficiency of the turbine. Optimizing the shape of the runner vane decreased the flow rate, reducing the water power and increasing the efficiency by about 5.57%. Also, results revealed that tubular or cross-flow turbines could be suitable for use in fish farm power plants, and the generator used should be waterproofed to avoid exposure to seawater.

Impact of Climate Change on the Hydrological Regimes in Bavaria

This study assesses the change of the seasonal runoff characteristics in 98 catchments in central Europe between the reference period of 1981–2010, and in the near future (2011–2040), mid future (2041–2070) and far future (2071–2099). Therefore, a large ensemble of 50 hydrological simulations featuring the model WaSiM-ETH driven by a 50-member ensemble of the Canadian Regional Climate Model, version 5 (CRCM5) under the emission scenario Representative Concentration Pathway (RCP 8.5) is analyzed. A hierarchical cluster analysis is applied to group the runoff characteristics into six flow regime classes. In the study area, (glacio-)nival, nival (transition), nivo-pluvial and three different pluvial classes are identified. We find that the characteristics of all six regime groups are severely affected by climate change in terms of the amplitude and timing of the monthly peaks and sinks. According to our simulations, the monthly peak of nival regimes will occur earlier in the season and the relative importance of rainfall increases towards the future. Pluvial regimes will become less balanced with higher normalized monthly discharge during January to March and a strong decrease during May to October. In comparison to the reference period, 8% of catchments will shift to another regime class until 2011–2040, whereas until 2041–2070 and 2071–2099, 23% and 43% will shift to another class, respectively.

Simulating Reservoir Induced Lhasa Streamflow Variability Using ArcSWAT

Lhasa River Basin being the socio-economic hotspot of Qinghai-Tibetan Plateau is experiencing an increased hydropower capacity in the form of damming and reservoir construction. The Pangduo hydropower station, commenced in 2013, is one of these developments. Lhasa River discharge is analyzed for spatial variability under the reservoir operation at Pondo and Lhasa gauging station. The Mann–Kendall Trend analysis reveals an increased precipitation and a decreased Lhasa River discharge trend upstream and downstream the reservoir. However, the discharge received at Lhasa gauging station is experiencing a greater decline revealed by Sen’s slope estimator. Soil and Water Assessment Tool (SWAT) modelling of the Lhasa River discharge for both the hydrometric stations from 2008–2016 reveals better simulation results for Pondo hydrometric station in terms of R2, NSE and PBIAS values. The modelling results for Pondo station correspond comparatively well to the reservoir operation procedures including water level and inflow despite of data availability constraint. However, the importance of non-simulated processes (e.g., groundwater abstractions) to the accurate prediction of the Lhasa flow regime particularly at the downstream flow gauge is recommended. The study can prove beneficial for local water distribution measures in Lhasa River Basin.

Hydropower Future: Between Climate Change, Renewable Deployment, Carbon and Fuel Prices

Hydropower represents an interesting technology: affordable, renewable, and flexible. However, it must cope with climate changes and new energy policies that jeopardize its future. A smooth transition to sustainability requires decision makers to assess the future perspectives of hydropower: about its future revenue and related uncertainty. This investigation requires a multidisciplinary approach as both streamflow and energy mix will evolve. We simulated future streamflow based on eight climate scenarios using a semi-distributed hydrological model for our case study, the Tremorgio hydropower plant located in southern Switzerland. Next, using a hydropower management model we generated income according to these streamflows and twenty-eight electricity price scenarios. Our results indicate that climate change will modify the seasonality of inflows and volumes exploitable for hydropower generation. However, adaptive strategies in the management of reservoirs could minimize revenue losses/maximize revenue gains. In addition, most market scenarios project an increase in revenues, except in the case of high wind and solar energy penetration. Markets do not provide the right incentive, since the deployment of intermittent energy would benefit from more flexible hydropower.

Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA

The quantity of liquid water in the snowpack defines its wetness. The temporal evolution of snow wetness's plays a significant role in wet-snow avalanche prediction, meltwater release, and water availability estimations and assessments within a river basin. However, it remains a difficult task and a demanding issue to measure the snowpack's liquid water content (LWC) and its temporal evolution with conventional in situ techniques. We propose an approach based on the use of time-domain reflectometry (TDR) and CS650 soil water content reflectometers to measure the snowpack's LWC and temperature profiles. For this purpose, we created an easily-applicable, low-cost, automated, and continuous LWC profiling instrument using reflectometers at the Cooperative Remote Sensing Science and Technology Center-Snow Analysis and Field Experiment (CREST-SAFE) in Caribou, ME, USA, and tested it during the snow melt period (February-April) immediately after installation in 2014. Snow Thermal Model (SNTHERM) LWC simulations forced with CREST-SAFE meteorological data were used to evaluate the accuracy of the instrument. Results showed overall good agreement, but clearly indicated inaccuracy under wet snow conditions. For this reason, we present two (for dry and wet snow) statistical relationships between snow LWC and dielectric permittivity similar to Topp's equation for the LWC of mineral soils. These equations were validated using CREST-SAFE in situ data from winter 2015. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Additionally, the equations seemed to be able to capture the snowpack state (i.e., onset of melt, medium, and maximum saturation). Lastly, field test results show advantages, such as: automated, continuous measurements, the temperature profiling of the snowpack, and the possible categorization of its state. However, future work should focus on improving the instrument's capability to measure the snowpack's LWC profile by properly calibrating it with in situ LWC measurements. Acceptable validation agreement indicates that the developed snow LWC, temperature, and wetness profiler offers a promising new tool for snow hydrology research.

Impact of climate change and water use policies on hydropower potential in the south-eastern Alpine region

Climate change is expected to cause alterations of streamflow regimes in the Alpine region, with possible relevant consequences for several socio-economic sectors including hydropower production. The impact of climate change on water resources and hydropower production is evaluated with reference to the Noce catchment, which is located in the Southeastern Alps, Italy. Projected changes of precipitation and temperature, derived from an ensemble of 4 climate model (CM) runs for the period 2040-2070 under the SRES A1B emission scenario, have been downscaled and bias corrected before using them as climatic forcing in a hydrological model. Projections indicate an increase of the mean temperature of the catchment in the range 2-4K, depending on the climate model used. Projections of precipitation indicate an increase of annual precipitation in the range between 2% and 6% with larger changes in winter and autumn. Hydrological simulations show an increase of water yield during the period 2040-2070 with respect to 1970-2000. Furthermore, a transition from glacio-nival to nival regime is projected for the catchment. Hydrological regime is expected to change as a consequence of less winter precipitation falling as snow and anticipated melting in spring, with the runoff peak decreasing in intensity and anticipating from July to June. Changes in water availability reflect in the Technical Hydropower Potential (THP) of the catchment, with larger changes projected for the hydropower plants located at the highest altitudes. Finally, the impacts on THP of water use policies such as the introduction of prescriptions for minimum ecological flow (MEF) have been analyzed. Simulations indicate that in the lower part of the catchment reduction of the hydropower production due to MEF releases from the storage reservoirs counterbalances the benefits associated to the projected increases of inflows as foreseen by simulations driven only by climate change.

Measuring snow liquid water content with low-cost GPS receivers

The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N₀) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements.