Displays

The research presented here is based on an extensive data set of five distinct nationally representative surveys in Austria sampling an average of 1.008 respondents per year. The surveys ran from 2015 to 2019 and were designed to measure respondents’ perceptions and attitudes towards various renewable energy-related issues, including perceptions of and attitudes towards electric vehicles and photovoltaic panels for private consumers but also renewable energy technologies in general and renewable energy production sites, specifically wind turbines, large-scale photovoltaic power plants and small-scale hydropower. Particular attention was paid to the question of local acceptance, or better, support for infrastructure in respondents’ local community. The data presented will thus offer a variety of perspectives. Firstly, longitudinal trends in the acceptance of small-scale hydropower will indicate the relative development of small-scale hydropower in terms of both regional differences but equally with respect to the two other surveyed renewable energy technologies. Comparisons on an aggregate level also offer an in depth and robust multiple regression analysis of the various predictors of social acceptance. Again, comparing these results to the results for both wind and photovoltaic energy technology. From an applied perspective, results are then discussed with respect to their implications for future renewable energy technology scenarios with respect to social acceptance and the role small-scale hydro power can play in these. Equally the rather novel scholarly effort to investigate social acceptance of small-scale hydropower and the potential for comparisons with more extensively studied renewable energy technology forms will offer an interesting ground for debate among academics and practitioners.

How to cite: Sposato, R. and Hampl, N.: Social Acceptance of Small-Scale Hydropower in Austria from 2015 to 2019, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18433, https://doi.org/10.5194/egusphere-egu2020-18433, 2020.

Although there have been numerous advances in production cost modeling techniques over past decade, the characterization of hydropower operations has remained relatively unsophisticated in common usage, largely ignoring the water-energy nexus.  We believe that there are two key reasons for this simple representation.  First, hydropower operational constraint data (including technical constraints, water-use priorities and rules, environmental constraints, and drought mitigation plans) are often not readily available or easily expressed in the Mixed Integer Linear Programming (MILP) problems that represent unit commitment and economic dispatch of generating assets.  Second, the water availability uncertainties involved in hydropower planning often span many days, months, or even years.  These uncertainties do not align well with the day-ahead unit commitment problem that is solved for grid operations.  This makes it difficult for unit commitment models to comprehensively include and make best use of water and hydropower production.

Recent trends toward increased reliance on variable generation and emerging concerns about the impacts of climate and weather uncertainty on infrastructure systems have highlighted the growing need for improved hydropower modeling capabilities within grid operations models.  To address this challenge, the United States Department of Energy’s National Renewable Energy Laboratory (NREL) is working with RTI International to develop an open-source modeling platform that enables the flexible specification of power system scheduling problems, including enhanced representation of water resource availability, hydropower constraints, and multi-stage stochastic programming capabilities.  The platform combines the flexibility of NREL’s Scalable Integrated Infrastructure Planning (SIIP) grid operations model with a generalized river basin decision support system and network flow model (MODSIM-DSS), allowing optimization across both grid and river basin operations.  Our work will leverage this novel framework to explore emerging approaches to scheduling hydropower under uncertainty at time scales raging from minutes to decades. Demonstration use cases focus on research and enhanced planning in the water-energy nexus domain, including how to predict and make best use of water availability for hydropower production, discover tradeoffs between water supply and hydropower generation, and how to predict and quantify the space-time dependencies and feedback connections between variable generation (wind and solar), the water cycle and other weather-related events, and hydropower.

How to cite: Stark, G., Barrows, C., Brinkman, G., Carney, S., and Triana, E.: A Novel Framework for Hydropower Scheduling Under Uncertainty, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12054, https://doi.org/10.5194/egusphere-egu2020-12054, 2020.

The viability of a renewable electricity system depends on long-term climate variations, uneven spatiotemporal distribution of renewable energy, and technical constraints. A major problem is to achieve a sustainable balance of water usage and consumption, as well as adequate energy and water distribution and storage capacities. In particular, hydropower offers a large capacity for energy storage and production flexibility, but only stands for a minor part of the total energy potential. In this study we explored the spatial and temporal variance of hydropower availability for a 35-year period based on historical hydro-meteorological data from large parts of Europe. A spectral analysis of these historical time-series shows that spatiotemporal coordination of the hydropower system covered in the Global Reservoir and Dam Database (GRanD) can potentially contribute with a “virtual” energy storage capacity that is up to four times the actual energy storage capacity contained in the existing hydropower reservoirs. Such virtual energy storage capacity implies reduced water storage demand, hence, indirectly contributes to reduced constraints of the food-water-energy nexus also in a wider system perspective. We found that the most significant benefits from a spatiotemporal management arise at distances of 1,200 – 3,000 km, i.e. on the continental scale, which can have implications for a future renewable energy system at large. The analysis also covers what we denote “energy-domain-specific drought”, which implies a shortage of energy storage capacity to avoid a deficit of energy for a given time period, and which may be reduced by the spatiotemporal coordination of power production.

How to cite: Wörman, A., Crochemore, L., Pechlivanidis, I., Gions Lopez, M., Brandimarte, L., Riml, J., Hao, S., Bertacchi Uvo, C., and Busse, S.: Virtual energy storage-gain due to spatiotemporal coordination of hydropower over Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7939, https://doi.org/10.5194/egusphere-egu2020-7939, 2020.

The strong synergies between water and energy use are becoming increasingly evident nowadays. It is becoming more and more apparent that significant benefits can be gained if both resources are managed in an integrated manner, which can be critical to improve efficiencies, reduce trade-offs, and find better and more sustainable solutions to future energy and water resources scarcity problems. Two types of approaches have drawn attention to integrate water and power system models, namely soft-link and hard-link approaches. Soft-linking approaches involve iterations, wherein the two system models are simulated independently, and their outputs (e.g., water available for hydropower generation) are passed to the other model until convergence is reached. In hard-link approaches, both the water and power systems are simulated with a single optimization model. More research to understand better the implications of different water-energy linking approaches, their computational cost, flexibility, and scalability are critically needed.

In this work water and energy system network models are linked with varying levels of integration (i.e., gradually moving from soft to hard link approaches) to demonstrate the advantages and disadvantages of the different types of links. The water and energy model includes multi-purpose storage reservoirs, irrigation, and domestic water users, renewable energy sources, and conventional power generators. Results show that soft linking approaches are more suitable for water-energy systems with fixed reservoir operation rules. Hard linking approaches are proven to be more suitable for cases with well established water and energy markets and can be computationally cheaper than soft linking approaches. Better joint simulation will help investigate better ways to manage and invest in water-energy systems.

How to cite: Etichia, M., Alejandro Martinez, E., Harou, J., and Panteli, M.: Assessment of soft and hard linking approaches of integrated water-energy simulation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20834, https://doi.org/10.5194/egusphere-egu2020-20834, 2020.

High-voltage transmission lines provide the fundamental service of delivering electricity over long distances, connecting power plants to demand centers. Their role is particularly critical in energy systems characterized by the presence of hydropower, and other renewable resources, whose output exhibits trends and shifts in response to hydro-climatic variability. Yet, the design and operation of transmission networks is rarely placed within a broad water-energy context, often resulting in infrastructures unable to dispatch the available power during peak-production periods. The case in point is Laos: the country has attracted large investments in the hydropower sector, but their effectiveness is severely limited by the capacity of the high-voltage transmission facilities. Here, we show how such challenge could be tackled through the use of process-based models describing the interconnections between water, energy, and power transmission components. Specifically, we run our modelling framework over a broad range of hydro-climatic conditions, so as to identify the transmission lines severely limited by their capacity. With this information at hand, we then explore the potential of both design and management interventions. Potential solutions include the capacity expansion of a few transmission lines and the adoption of a wide area synchronous grid, which facilitates electricity exchange across Laos and Thailand. Results show that both solutions are cost-effective: they require limited investment costs and reduce reliance on fossil fuels, resulting in a significant abatement of CO₂ emissions.

How to cite: Galelli, S., Chowdhury, A. K., and Dang, T. D.: Challenges, trade-offs, and opportunities in the design of power transmission lines: a water-energy perspective, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12347, https://doi.org/10.5194/egusphere-egu2020-12347, 2020.

Reservoirs are important sources of greenhouse gases (GHGs) to the atmosphere and their number is rapidly increasing, especially in tropical regions. Accurately predicting their current and future emissions is essential but hindered by fragmented data on the subject, which often fail to include all emission pathways (surface diffusion, ebullition, degassing, and downstream emissions) and the high spatial and temporal flux variability. Here we conducted a comprehensive sampling of Batang Ai reservoir (Malaysia), and compared field-based versus modeled estimates of its annual carbon footprint for each emission pathway. We further explored the processes fuelling and regulating emissions downstream of the dam, which are important but commonly overlooked. Carbon dioxide (CO₂) surface diffusion and methane (CH₄) ebullition were lower than predicted, whereas moderate surface CH₄ diffusion was accurately predicted. Most GHGs present in discharged water were degassed at the turbines, and the remainder were gradually emitted along the outflow river, leaving time for CH₄ to be partly oxidized to CO₂. Overall, the reservoir emitted 2475 gCO₂eq m^-2 yr^-1, of which 89 % occurred downstream of the dam, mostly in the form of CH₄. These emissions, largely underestimated by predictions, are mitigated by CH₄ oxidation upstream and downstream of the dam, but could have been drastically reduced by slightly raising the water intake elevation depth. Degassing and downstream emissions are largely due to the accumulation of GHGs under the permanent thermocline. Studying the interplay between the processes regulating CO₂ and CH₄ concentrations in the reservoir deep layer highlighted the key role of physical factors on GHGs dynamics. Overall, our results show that exploring morphometry, soil type, and stratification patterns as predictors can improve modeling of reservoir GHGs emissions at local and global scales.  

How to cite: Soued, C. and Prairie, Y.: The carbon footprint of a tropical reservoir: measured versus modeled values highlight the underestimated key role of downstream processes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8956, https://doi.org/10.5194/egusphere-egu2020-8956, 2020.

Renewable bioenergy feedstocks offset the demand for conventional petroleum-based energy resources. Switchgrass (Panicum virgatum L.) is a warm-season perennial C4 grass that has been utilized for lingo-cellulosic ethanol production and direct energy via combustion. However, little is known about its potential as a feedstock in the semi-arid northern Great Plains USA, including the impact of N fertilizer application on biomass production and on environmental quality. A field study initiated in 2009 seeded ‘Sunburst’ switchgrass into 12.2 m by 30.5 m plots. Split plots randomized within each main plot included fertilizer N broadcast each spring at 0, 28, 56, and 84 kg N per ha as urea, with four treatment replicates. Aboveground biomass, allowing a 20 cm stubble height, was harvested, weighed, and dried at 55 deg C each fall beginning in 2011 from four randomly selected 0.25 m sq areas. Soil cores were taken to a depth of 1.2 m in fall 2018, air-dried, and analyzed for soil nitrate. Switchgrass biomass ranged from 1.8 to 12.3 Mg per ha. In most years, N application increased switchgrass biomass, but response to N rates above 28 kg per ha was inconsistent. Biomass from fertilized switchgrass averaged 6.5 Mg per ha compared to 4.4 Mg per ha for the unfertilized control.  Soil nitrate levels indicated the potential of (over)fertilization of switchgrass feedstocks to impact water resources in semi-arid environments.

How to cite: Allen, B., Sainju, U., and Jabro, J.: Fertilizer N rates to optimize bioenergy feedstock production and water quality in semi-arid environments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2447, https://doi.org/10.5194/egusphere-egu2020-2447, 2020.

The world is in a crucial era of energy transition, and green energy will serve as a new engine that drives sustainable development in the future. Renewable energy becomes the core energy to cultivate green energy industries and promote energy self-sufficiency in Taiwan. In recent years, water, food and energy nexus (WFE Nexus) has gained global attention. Therefore, a multi-objective optimization framework is proposed in this study to explore the optimal solution to the WFE Nexus for improving the synergistic benefits of water, food, and energy (hydropower, small hydropower and solar power). The joint multi-objective operation of the Shihmen Reservoir and irrigation ponds in the northern Taiwan constitutes the case study. This study aims at achieving the optimal water supply to fulfill basic demands from different sectors as well as increasing green energy output by utilizing reservoir spilled water to lift up hydropower output, installing small hydropower in river channels, and setting up solar panels over irrigation ponds. The results support the high potential of photoelectric ponds because the installation of solar panels over irrigation ponds can 1) reduce evaporation amount and water temperature and 2) provide water quality conditions suitable for growing fish while increasing solar power output. The results also indicate that the optimal joint operation of the Shihmen Reservoir and irrigation ponds can promote reservoir hydropower output and the small hydropower output in river channels while increasing water supply and food production. This study demonstrates that the intelligent management of the reservoir and photoelectric ponds not only can increase green energy production, water supply and food production but also can enhance the synergistic benefits of the WFE Nexus, which provides long/short term policies for sustainable urban development.

Keywords: Multi-objective reservoir operation; Optimization; Water, food and energy nexus (WFE Nexus); Green energy; Greenhouse

How to cite: Lee, W.-D. and Chang, F.-J.: Intelligent management of reservoir and photoelectric ponds under water-food-energy nexus perspective, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7388, https://doi.org/10.5194/egusphere-egu2020-7388, 2020.

The increasing demand for renewable energy renders the optimal management of the water-energy nexus highly important, and the complexity of global change compromises the sustainability of current water use. Therefore, models representing human interventions on water resource are crucial. This work takes the multipurpose reservoir system of the Aure-Louron Valley in the center of the Pyrenees as a typical study case to establish an integrated hydrological modelling framework. Hydropower and downstream consumption represent the main water uses in the study case. The work is a scientific contribution to the Interreg PIRAGUA project (https://www.opcc-ctp.org/en/piragua). Detailed work aims to develop a modelling chain that integrates a water resource model, a water demand model, and a water management model. This study focuses on the water resource model and the water demand model for energy. Water resource is characterized by the hydrological model GR6J (Riboust et al., 2019), calibrated with the SAFRAN surface reanalysis (Vidal et al., 2010) with a dedicated Pyrenean 2.5 km resolution version, and gap-filled MODIS data (Gascoin et al., 2015) for better robustness of snowpack modelling. The energy demand model is based on the air temperature of France and calendar day (Hendrickx and Sauquet, 2013). It is validated with the historical data of water used for hydropower production over the 2001-2018 period. Tools are being developped to make the models transposable to a wide range of water management contexts. The next steps of the study will focus on establishing a water demand model for downstream consumption, and a water management model. Finally, the modelling chain will be applied under various global change scenarios to assess the vulnerability of the system.

References:

Hendrickx, F. and Sauquet, E. (2013). Impact of warming climate on water management for the Ariège river basin (France). HYDROLOG. SCI. J., 58(5): 976-993.

Riboust, P., Thirel, G., Le Moine, N., and Ribstein, P. (2019). Revisiting a simple degree-day model for integrating satellite data: Implementation of SWE-SCA hystereses. J. HYDROL. HYDROMECH., 67(1): 70-81.

Vidal, J.-P., Martin, E., Franchistéguy, L., Baillon, M., and Soubeyroux, J.-M. (2010). A 50-year high-resolution atmospheric reanalysis over France with the SAFRAN system. INT. J. CLIMATOL., 30(11):1627–1644.

How to cite: Huang, P., Sauquet, E., Vidal, J.-P., and Dariba, N.: Modelling the water-system in the Pyrenean Aure-Louron Valley, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5283, https://doi.org/10.5194/egusphere-egu2020-5283, 2020.

Rivers developed for hydropower production are important electricity generators with an increasing role as a balancing power source in new wind-power dominated energy systems. However, hydropower constructed rivers also provide many ecosystem services, such as habitats for migratory fish species and opportunities for recreational activities. Currently, we see drastic changes in needs from society to use regulated river corridors for multiple purposes, and therefore, new approaches are needed to support the sustainable management of river resources. In our new EcoRiver-project we develop an integrated assessment framework and examine cost and benefits provided by hydropower constructed rivers. We use hydrodynamic modelling to quantify the ecosystem services and variability during short-term regulation practices (hydropeaking). Hydropower and energy markets modelling is used to examine the impacts of increasing demand flexibility on hydropower. Environmental valuation methods are applied to evaluate the ecosystem services monetarily. Finally, we integrate these methods for cost-benefit analysis in order to support well-informed decision making for river management.

How to cite: Marttila, H., Ashraf, F., Haghighi, A. T., Hellsten, S., Kopsakangas-Savolainen, M., Ruokamo, E., Huuki, H., Karhinen, S., Romakkaniemi, A., Pongraczs, E., and Juutinen, A.: Assessing and valuing ecosystem services for managing hydropower constructed rivers systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18171, https://doi.org/10.5194/egusphere-egu2020-18171, 2020.

Small, run of the river hydropower (SHP) has the potential to help provide rural regions in developing countries with access to power. Satellite rainfall products can be used in these often data sparse regions to drive a series of linked models to determine locations feasible SHP sites. However, the inherent uncertainty in satellite rainfall products are a significant source of error, and this must be quantified. Additionally, there is a trade-off between the benefits of power produced from SHP and the cumulative environmental impacts they may produce when multiple are implemented across a basin, and it is important to assess this trade off.  

The first part of this study calculates the uncertainty in predictions of SHP potential due to satellite rainfall uncertainty across a data sparse catchment. Comparisons of predicted power and its uncertainty are then made at locations where known SHP sites are located, to evaluate the model’s usefulness. The second part of the study involves assessing the trade-off between the cumulative power output and cumulative environmental impact of a range of SHP portfolios, to assess at which locations it is best to construct in order to maximise power output benefits and minimise negative environmental impacts.  

A calibrated, linked VIC–LISFLOOD hydrodynamic model driven by different satellite derived rainfall datasets was constructed at 5km resolution on the Pungwe Basin in Mozambique / Zimbabwe. The VIC model was calibrated to a single available GRDC gauging station. A LISFLOOD-FP hydraulic model with sub grid channel representation of small rivers was created from the HYDROSHEDs network, river widths extracted from multiple databases, hydraulic geometry relationships for bed depth, and MERIT DEM. Modelled flow from the 5km VIC cells were routed into each 90m LISFLOOD-FP river pixel. Power Duration Curves were then derived for each river pixel across the basin, and the modelled power predictions were evaluated using six known SHP sites in the upper reaches of the basin. Geostatistical techniques were then applied to generate ensembles of satellite rainfall realisations, which were propagated through the model chain, in order to establish the uncertainty in the modelled power. 

Broad assessment of environmental impact has been made based on impacts SHP impacts on river connectivity, with subsequent multi-objective optimisation to analyse the trade-offs between different portfolios based on cumulative power output and impact on river connectivity using the NSGAII algorithm, and thus suggest optimum locations.  

How to cite: Hatchard, S., Bates, P., Pianosi, F., and Williamson, S.: Estimating Optimal Small Hydropower Portfolios in Data Scarce Southern African Regions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21516, https://doi.org/10.5194/egusphere-egu2020-21516, 2020.

To accelerate the rate of electrification in remote places of sub-Saharan Africa and to be coherent with the COP21 Paris agreement, different studies propose the development of autonomous solar microgrid which have a moderate levelized cost of electricity (LCOE) while ensuring a good quality of service. This LCOE directly depends on the storage and PV oversizing needs required locally. In the present work, using high resolution satellite irradiance data for 20 years period and considering load curves for a panel of productive/domestic uses configurations, we show that the optimal design required locally (storage capacity/oversizing level of PV panel fleet) first depends on the temporal pattern of the demand and are typically lower when the demand is based on productive uses rather than domestic. It next depends on the level of the temporal resource/demand adequacy which typically varies in space according to the local climate features.

The costs of batteries, solar panels and the discount rates, obviously significantly determine the LCOE to be achieved with a given microgrid. These economical drivers could also influence the optimal storage/PV oversizing configuration. We further explore the sensitivity of the optimal design to such drivers. This sensitivity could have obviously important implications for all operational and institutional actors involved in the development of such systems in this area. We explore how this sensitivity varies in space and where the optimal design obtained with chosen values of those economical drivers can be considered as robust.

How to cite: Plain, N., mathy, S., and Hingray, B.: Optimal design and Levelized Cost of Electricity of 100% solar power microgrids in Africa: robustness and sensitivity to meteorological and economical drivers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21963, https://doi.org/10.5194/egusphere-egu2020-21963, 2020.

Hydropower accounts for almost half of all electricity production in Sweden, while also being the most important energy balancing resource. Nuclear power plants are gradually being decommissioned up to 2045 in Sweden according to the government’s plans. It means there is a need for a dramatic expansion of renewable energy production, especially for hydropower as a balancing resource. The availability of renewable energy fluctuates with the weather, seasons, and between years, which is an important factor for the coordination of renewable energy production.

The aim of this research is to investigate how runoff forecasts affect hydropower production planning when the account is taken to hydro-climatic variations. This problem is studied by using production planning models fed by runoff forecasts that exhibit climate-driven periodicity. Statistical ensemble predictions and receding horizon control are implemented to reveal the effect on the production. Further, we utilize half-a-century long daily hydro-climatological data to runoff forecasts that are aggregated in ensembles particularly reflecting the bi-annual climate periodicity apparent from spectral analysis of the data.

Dalälven River Basin is used as a study case, which is a watershed stretching from western Sweden to the Baltic in the east and which has more than 30 hydropower stations. Four forecast ensemble scenarios have been analyzed out by studying the periodicity of discharge data in Dalälven River Basin. According to the seasonal and two-year periodicity, the four scenario ensembles are defined as: a) Odd year, wet month; b) Even year, dry month; c) Odd year, dry month; d) Even year, wet month. [A1] A large-scale optimal hydropower production model was built in MATLAB, in order to simulate hydropower production in Dalälven River Basin. It includes 13 reservoirs and 36 hydropower plants, and applies the sequential-quadratic-programming (SQP ) as the optimization method. Receding horizon control is embedded into the optimal production programming, which can correct the systematic error. The historical data shows that the one-year-long sampling has a consistent biannual periodicity, with wet and dry years of different strength depending on the start month of the data selection in the year. It indicates the discharge data selection start from November and December gives the most dramatic effect on periodicity, while starting from May and July have a lower impact. Dynamic programming of hydropower production shows for both dry and wet runoff conditions that matching the forecast ensemble with the right phase of the actual climate conditions has a significant effect on the production profit.

How to cite: Hao, S., Wörman, A., Brandimarte, L., and Riml, J.: Effects of hydro-climate periodicity on hydropower production operation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2595, https://doi.org/10.5194/egusphere-egu2020-2595, 2020.

In Switzerland, around 57 % of electricity is generated by hydropower (HP), whereof around 25 % are produced by run-of-river (RoR) power plants. This share is expected to only slightly increase in the context of the Swiss energy strategy 2050, by about 10 % (in total 38’600 GWh/a). Nevertheless, growing energy demand coupled to growing ecological awareness is catapulting hydropower into a position of great expectation and responsibility. In this context, the present research project proposes to assess the impact of climate change and of evolving environmental flow constraints on RoR production in Switzerland. The obtained results are compared to the production increase that could potentially be achieved by technical optimization.

To assess climate change impacts, daily runoff until the end of the century was calculated with the hydrological model PREVAH, using a total of 26 climate model chains in transient simulation from the new Swiss Climate Change Scenarios CH2018, corresponding to the two different CO₂ emission scenarios RCP2.6 and RCP8.5. Changes in HP generation under climate change are estimated for 11 RoR power plants based on differences in the flow duration curves (FDCs) between the reference period (1981-2010) and the future periods (2045–2074 and 2070–2099), assuming unchanged installed machinery and residual water flow requirements.

The changes in HP production from RoR power plants are due to changes in precipitation, temperature and evaporation, which in turn have a strong impact on the dominant hydrological processes (snow accumulation and melt, glacier melt and runoff production), and show important spatial and temporal differences. By mid-century (2045–2074) and under concerted mitigation efforts (RCP2.6), annual production will remain roughly the same as during the reference period. Production will decrease slightly (about -3 %) without climate change mitigation (RCP8.5). Exceptions are power plants which are strongly influenced by melt processes. Due to reduced snowfall and increased winter precipitation and ensuing higher winter streamflows, winter production will increase at almost all RoR power plants considered in this study by mid-century, by about 5 % on average.

By the end of the century (2070–2099), a slight decline of the annual production (-1.5 %) is to be expected under RCP2.6. Without climate change mitigation (RCP8.5), annual production will fall further (-7 %). Winter production will increase at virtually all studied RoR power plants. Depending on the emissions scenario, the average winter production increase will be between 5 % (RCP2.6) and 10 % (RCP8.5). However, this increase in winter production will not be sufficient to prevent annual production decline.

These climate change induced reductions of annual HP can be put into context by comparing the production losses that result from residual flow requirements. For the RoR power plants under consideration, compliance with legal constraints on residual flow rates, compared to no residual flow, means a difference of less than 4 %. We will discuss in detail the relevance of ecological constraints and of technical and thereby give a complete picture of emerging challenges and opportunities for Alpine hydropower production under climate and societal change.

How to cite: Wechsler, T., Stähli, M., Zappa, M., Jorde, K., and Schaefli, B.: Future Alpine hydropower production: impacts of climate change, residual flow and technical optimization on Run-of-River power plants in Switzerland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9372, https://doi.org/10.5194/egusphere-egu2020-9372, 2020.

During flood seasons, the water head of the reservoir is kept in flood limited water level (FLWL) to satisfy the flood control objective, but this runs counter to the need for hydropower generation to maintain a high water-head. This paper focuses on the optimal hedging rules by setting an appropriate FLWL to maximize the benefit of hydropower without increasing the flood damage and raise the water level at the end of flood for non-flood season/future use. Two-stage hydropower functions considering the constraint conditions which include the downstream environmental flow and installed capacity are built. On the basis of studying the marginal utilities of the two-stage hydropower functions, the competitive and collaborative relationships between flood damage and hydropower benefit were analyzed qualitatively. A two-stage reservoir operation model with two objectives that are minimum flood damage and maximum hydropower generation is developed, which considers streamflow forecast uncertainty and acceptable flood risk. The derived OHR from the model can be used to make trade-offs between flood damage and hydropower benefit under different levels of streamflow forecast uncertainty or acceptable risk. Finally, the analysis is applied to the Nierji Reservoir in the north of China. The results indicate that the OHR can increase hydropower generation 1.57x106kw·h and decrease the volume of abandoned water30.04x106m3 average annual.

How to cite: Zhang, L., Ding, W., and Wang, G.: Optimal coordination strategies for flood control and hydropower generation of reservoir, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12554, https://doi.org/10.5194/egusphere-egu2020-12554, 2020.

The Soil and Water Assessment Tool (SWAT) model is a watershed-based hydrologic model for simulating water balance at the basin scale. The SWAT model delineates the watersheds and create the Hydrological Response Units (HRUs) in the different watersheds of the basin using Digital Elevation Model (DEM), Land use, Soil and slope, and gives the water balance of the River basin. In this study, the ensemble CORDEX-SA driving GCM experiment are used to predict the water balance of the basin in the historical and future periods under the RCP4.5 and RCP8.5 scenarios. The Banas River Basin is located into the semi-arid region of Rajasthan, covered 13 districts and 5 Agro-climate zones. The basin is divided into the four zones on the basis of Agro-climatic to predict the water yield and understand water security using per capita water availability and metrological variables. It is projected that the per capita water availability will decrease, and drought frequency will increase in the future period under different scenarios. Considering the par capita water availability and meteorological variation, all the four zones are ranked, and it is found that zone 3 is more water-secure compared to other zones in the present and future periods. This study may help to understand the water scarcity status in the basin under different climate change scenarios and need more focus to improve the water management issues at the basin level.

How to cite: Dubey, S. K., Kumar, Dr. P., Sharma, Dr. D., Dubey, A. K., and Saharwardi, Md. S.: Climate Change Impact on Water Yield and Water Security in the Semi-arid Region of Rajasthan, India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12868, https://doi.org/10.5194/egusphere-egu2020-12868, 2020.

Semi-distributed model of SWAT based on physical-chemical spatial information has been an effective tool for simulating hydrological cycle in the basin whereas it can’t completely restore all natural processes. Therefore, uncertainty analysis is needed to be conducted in order to achieve the reliability of the model. Yalong River Basin (YLRB), which is listed as the top ten hydropower bases in China, contains abundant water resources with plentiful runoff. Here a case study in YLRB was conducted to explore the parameter uncertainties of the SWAT model to runoff simulations based on multiple optimization algorithms. The following results were obtained: 1) setting the same objective function of Nash–Sutcliffe Efficiency, three optimization methods including Sequential Uncertainty Fitting version 2 (SUFI-2), Generalized Likelihood Uncertainty Estimation (GLUE) and Particle Swarm Optimization (PSO) all performed satisfactory fitting results and produced similar parameter ranges in YLRB, while SUFI-2 achieved better uncertainty analysis, followed by PSO and the last GLUE; 2) five general sensitive parameters to model output were ALPHA_BF, CH_K2, SOL_K(1), GW_REVAP and ESCO based on above three algorithms; 3) from the contribution network analysis in economics, the positive correlation between ALPHA_BF and CH_K2 exhibited the highest weight among all parameter relationships; and 4) the much lower sensitivity of parameter CN2 to streamflow in YLRB revealed that most commonly modified parameter CN2 was less applicable to land with adequate surface water than dry land. This work will be conducive to further hydrological analysis based on a reliable fitting model for this hydropower watershed. Additionally, this work will provide references and insights for sensitive parameter modification and prediction uncertainty reduction of streamflow simulation furthermore contributing to an optimal water resource management.

How to cite: Liang, Y. and Cai, Y.: Parameter uncertainty analysis for streamflow prediction in a cascade hydropower basin of southwest China , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13444, https://doi.org/10.5194/egusphere-egu2020-13444, 2020.

The extension of the power grid is crucial for the success of the German energy transition (Heimann, 2015). In the past, companies rarely buried high voltage power cables in the ground due to high prices and construction limitations (Kroener et al., 2014). High prices are largely related to the conventional installation technique, the open construction, as it requires the movement of tonnes of soil. Even replacement of soils by filling substrates in the cables´ vicinity can be necessary, if heat conductivities (HCs) of soils are insufficient (Amprion, 2017). Current flow generates heat loss in power cables. If HCs are low, soils trap this heat, which potentially causes harmful temperatures that will reduce the cable´s ampacity and its longevity (Kroener et al., 2014). Therefore, high HCs are favoured, which are soil specific and determined by the soil´s bulk density (de Vries, 1963), whereby denser soils result in higher HCs.

Frank Föckersperger GmbH had developed a multiple cable plough (MCP) by which the protection pipes of power cables can directly be ploughed to required soil depths. This technique is promising to reduce the amounts of excavated soil and to shorten construction times (TenneT, 2019a). In a cooperative project, the TU Berlin scientifically accompanies Frank Föckersperger GmbH to identify what effect the MCP has onto soil properties and to evaluate if natural soils can meet the requirements that the cable bed of the open construction technique needs to meet. These requirements consist of a cavity-free cable bed, minimum bulk densities of 80 percent of the reference soil´s bulk density, and HCs of 0.4 W m^-1 K^-1 for dry and of 1.0 W m^-1 K^-1 for moist soil conditions (Schneider, 2019).

In course of their Wahle-Mecklar project, TenneT TSO GmbH is going to construct a 13 km long underground powerline between Wahle and Lamspringe, Lower Saxony, Germany (TenneT, 2019b). On a test field near the community Wartjenstedt, TenneT TSO GmbH and Frank Föckersperger GmbH tested the MCP on a 200 m strech in July 2019. After the operation, the TU Berlin sampled three trenches regarding their disturbed and undisturbed realms, and investigated the following parameters in the laboratory: soil texture, bulk density, HC, and water retention.

During the MCP procedure, soil layers were drastically mixed causing changes in soil texture. In contrast, the procedure´s effect onto the water retention did not indicate general trends. We found that results for bulk density and HC complied with the requirements. However, a cavity-free cable bed was not present and bulk densities were mostly lower than their references. Concerningly, we detected some of the lowest bulk densities in the cable bed or in close vicinity.

Therefore, Frank Föckersperger GmbH recently carries out modifications on the MCP to ensure cavity-free cable beds with more homogeneous and denser bulk densities to facilitate sufficient HCs thereby. Currently, we run simulations to identify the real impact of the results onto the heat and water transport in power cable containing soils. In the future, we are going to evaluate the MCP modifications after their implementation.

References:

Amprion (2017). Erdkabel im Übertragungsnetz. Eine innovative Technologie für den Netzausbau. Amprion GmbH, pp. 38.

de Vries, D.A. (1963). Thermal properties of soils. In: Van Wijk, W.R. (Ed.). Physics of plant environment. John Wiley & Sons, Inc., New York, pp. 210-235.

Heimann,U. (2015). Trassenplanung in Deutschland. In: Boden und Energiewende. Springer Vieweg, Wiesbaden, pp. 15-26.

Kroener, Eva et al. (2014). Numerical simulations of coupled heat, liquid water and water vapor   in soils for heat dissipation of underground electrical power cables. Applied Thermal Engineering, 70, pp. 510-523.

Schneider, R. (2019). Written notice as email from 12/11/2019. Project management Erdkabel at TenneT. TenneT TSO GmbH.

TenneT TSO GmbH (2019a). Pionierarbeit für die Energiewende: TenneT testet bodenschonendes Pflugverfahren zur Erdkabelverlegung [Online].

Available at: https://www.tennet.eu/de/news/news/pionierarbeit-fuer-die-energiewende-tennet-testet-bodenschonendes-pflugverfahren-zur-erdkabelverlegu/ [Accessed: 01/14/2020].

TenneT TSO GmbH (2019b). Wahle-Mecklar Projektübersicht [Online]. Available at:     https://www.tennet.eu/de/unser-netz/onshore-projekte-deutschland/wahle-mecklar/ [Accessed: 01/14/2020].

How to cite: Gregor, M.: Soil physical investigations for the optimisation of the cable plough procedure for the burial of 380 kV power cables (Miboka-project), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13954, https://doi.org/10.5194/egusphere-egu2020-13954, 2020.

Hydropower, between renewable energy sources, is probably the best candidate for reducing greenhouse emission, 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. Using two models, namely Poly-Hydro and Poly-Power, we assessed present hydrological budget divided by components (i.e., ice/snow melt, rainfall), and hydropower production under optimal reservoirs’ management, respectively. We then project forward hydrological cycle under properly downscaled climate change scenarios (three General Circulation Models, three Representative Concentration Pathways, nine scenarios overall) from IPCC until 2100, and we assess glacier fate and consequences for hydropower production. 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 (-10% to 0%, 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.

How to cite: Stucchi, L., Bombelli, G. M., and Bocchiola, D.: Hydropower in the Era of Climate Change. The Case of the Sabbione Storage Plant in Italy , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20158, https://doi.org/10.5194/egusphere-egu2020-20158, 2020.