Micro-hydropower is an excellent source of renewable energy. There is no need to build additional DAMs, so it has the advantages of lower setup costs and construction times and reduces greenhouse gas emissions during the generation process. Central and southern Taiwan is mainly developed by agriculture, especially the Zhuoshui River Basin, which has a large watershed area, developed agricultural irrigation system, abundant water source and stable flow, so it is suitable for the installation of micro-hydropower. Its micro-hydropower generation mainly uses the kinetic energy of water to drive the turbine to generate electricity, and the water in the agricultural channel does not disappear with the installation of the turbine.

Therefore, this study selected Linnei channel in the Zhuoshui River Basin in central Taiwan as the research site. It is Linnei channel, an agricultural irrigation channel with a stable flow rate, and the first group of micro-hydropower generation was installed in Linnei channel in 2018, and the second groups of micro-hydropower generation were installed in 2020. Therefore, this study measured the water level and flow of the Linnei channel from 2018 to 2022 to analyze the flow changes with or without micro-hydropower generation. Using rice planting evaluate the agricultural economic output value brought by irrigation water. Since 2019, the addition of hydropower generation increased the income brought by hydropower generation. The benefits and costs of each year are compared, and the economic analysis method is used to evaluate whether the installation of hydropower generating units is worth the investment and whether they can get benefits. The results showed that the increase of channel water volume could lead to more rice harvest, but there was no positive correlation between power generation and irrigation water volume. The addition of additional micro-hydropower in 2022 with sufficient irrigation increased net profit margin by only 0.02%, compared to 0.07% in 2019 with less irrigation. It shows that the relationship of the water-energy-food nexus has not yet been optimized, and in the future add the interaction between energy and water to optimize the profit of the system.

How to cite: Shih, J.-C., Lin, F.-Y., Hong, M.-D., Lin, H.-R., and Wen, J.-C.: Investigate the Optimization of Micro-hydropower in Agricultural Channels in the Water-energy-food Nexus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2523, https://doi.org/10.5194/egusphere-egu23-2523, 2023.

Climate change and water management are expected to have significant impacts on river flows. Hydropower production is therefore expected to evolve, while low carbon electricity could become more valuable in the context of the transition towards sustainable societies.

Hydrological models have been used to evaluate the potential of hydropower plants based on simulated flows. Some of these studies represent dams and water management. However, dam operation is done independently for each dam or each river basin, without considering the specificities of hydroelectric reservoirs whose operation results from an optimization of the entire power system.

We propose and validate a demand-based method to represent hydropower in the routing module of a land surface model at the scale of a national power grid. First, hydropower infrastructures are placed in coherence with the hydrological network and links are built between reservoir and power plants. Then, coordinated dam operation is simulated by distributing the total electric demand to be satisfied by hydropower over the different power plants.

The method is developed within the routing scheme of the ORCHIDEE land surface model, so that changes in climate or land use can be considered in future studies.

We calibrate and validate the model by simulating hydropower production in France over the period 2012-2018 using SAFRAN climate forcing data and comparing it to available observations of hydropower generation. Several rules for the dispatch of production between the power plants are compared and evaluated.

We show that an operating rule based on climatological inflows, reservoir volumes and hydraulic heads can simulate a dispatch of production that enables the model to replicate hourly hydropower plants output throughout the period.

How to cite: Baratgin, L., Polcher, J., Quirion, P., and Dumas, P.: Simulating French hydropower operations in a land surface model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3396, https://doi.org/10.5194/egusphere-egu23-3396, 2023.

National-scale estimates of flow for determining hydropower suitability are invariably dependant on some form of the Drainage Area Ratio (DAR) method, where flows at a point of interest for hydropower are assumed to be a proportion of flows measured elsewhere in the catchment, based on a fixed ratio of respective catchment areas. This method is widely used globally.

Recent UK national-scale modelling, using a variety of models, has established a significant set of reconstructed daily flows for many locations (G2G model: 260 catchments (flows: 1891-2015); GR4J model: 303 catchments (flows: 1891-2015); Decipher model: 1366 catchments (flows: 1962-2015)). These reconstructed flows supplement the national set of flow observations maintained in the UK National River Flow Archive but have the advantage that in many cases reconstructed timeseries cover a longer period than observed records. Although these are useful datasets, unless the site of hydropower interest approximates a gauged/modelled location, the problem of estimating flows at a different point, remains.

The reconstructed datasets mentioned above include a national scale 1km x 1km grid of monthly flows generated by the G2G model (1891-2015). As these are gridded flows at high spatial resolution, it may be possible to estimate daily flows at a required location, based on a variable ratio of monthly flows for the respective locations – rather than a fixed area ratio.

We propose and test a method for leveraging understanding from gridded monthly output for several locations within the Trent catchment. Daily flows at these locations are already known and were used for validation. We calculated monthly ratios of gridded flows at the sites of interest to those at a driver site, where daily flow is available. This variable monthly flow ratio was then applied to the daily flow at the driver location to estimate daily flow at the site of interest. Flow duration curves were compiled to compare flows using (i) the DAR method, (ii) the proposed flow factor method and (iii) the observed flows. Results generally indicated that the flow factor method provides good estimates (within 5 to 14% of recorded flow), and a significant improvement in flow estimation compared to the DAR method. However, for some locations, both methods performed poorly, and we explore possible reasons.

How to cite: Quinn, N. W., Horswell, M., and Wyrill, D.: Estimating flows for hydropower: leveraging value from national scale hydrological modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8275, https://doi.org/10.5194/egusphere-egu23-8275, 2023.

The viability of hydropower production depends on water and energy distribution, storage capacities, and technical constraints. Understanding the sensitivity of runoff variability to hydroelectricity production is a step to better assess its potential and add value to society. In this study, we explored the decomposition of hourly outflow data of hydropower power plants (HPP) operation for a 22-year period into scale-dependent coefficients using the maximal overlap discrete wavelet transform (MODWT) over the Paranapanema river basin. The wavelet analysis of the historical time series shows that the operational coordination of the cascade hydropower system leads the watershed to behave as a space-time filter. This filtering is applied to the process of temporal aggregation of rainfall into the generation of runoff and results in periodic fluctuations due to retention and release of outflow in regulation sites, from run-of-river facilities and regulation dams. These regulated patterns manifest over several scales, dominated by hydropeaking, and diminished seasonal signals.

We found that MODWT effectively describes the broadband of sub-daily and weekly flow cycles from fluctuating electricity demand. The decomposition analysis, which partitions the signal's energy across detail coefficients and scaling coefficients, also showed that the recognition of site-specific, each HPP, infers the individual filtering contributions of regulation points and provides a complementary metric to identify the practices and policies that affect outflows across the watershed. The increase in total energy by scales, the sum of decompositions, from upstream to downstream indicates the presence of spatial and temporal relationships with outflow magnitude. In addition, it highlights the coordination of the joint operation and how its cumulative effects serve energy generation, which implies matching consumer demand and supply.

How to cite: Fujita, T., Cuartas, L. A., Andrade Campos, J., Rodrigues Capozzoli, C., Alberto Martins, J., Dias de Freitas, E., and Bertacchi Uvo, C.: MODWT-based outflow decomposition and individual contribution of regulation sites over Paranapanema river basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13625, https://doi.org/10.5194/egusphere-egu23-13625, 2023.

Large-scale integration of intermittent renewable sources in Africa, such as solar and wind, can accelerate the transition to low-carbon energy systems, which is critical to mitigate the impacts of climate change and increase electricity access. Hydropower can support this transition because its operational flexibility can be used, in a cost-effective manner, to counteract the variability and seasonality of intermittent renewables. However, using hydropower to provide energy system flexibility services can affect aquatic ecosystems and create intersectoral conflict. We use a multi-objective design framework to address this issue and demonstrate it on a national-scale case study for Ghana. This case study shows that available hydropower flexibility can be deployed to support expanding intermittent renewables by 38%. However, this would increase the sub-daily flow variability of the main national river (Volta) by up to 22 times compared to the historical baseload hydropower operation that does not support intermittent renewables. The increase in sub-daily flow variability is estimated to damage the river ecosystem and reduce national crop yield revenue by up to US$169 million per year. We propose an alternative approach that uses a diversified investment strategy, including intermittent renewables, bioenergy, and transmission network expansion in addition to existing hydropower, and show that such designs can maintain acceptable flow variability and agricultural performance while meeting future national energy service goals and reducing CO₂ emissions. The proposed framework can support governments and power system planners by designing efficient diversified energy investment portfolios and highlighting their sectoral and emission trade-offs.

How to cite: Gonzalez, J. M., Martínez-Ceseña, E. A., Panteli, M., and Harou, J. J.: Integrating intermittent renewables via hydropower alone adversely impacts other sectors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14261, https://doi.org/10.5194/egusphere-egu23-14261, 2023.

We investigate the design of small hydropower plants under multiple sources of uncertainty and contrast it with the conventional deterministic practice that leads to a unique solution. In particular, we emphasize three sources of uncertainty, referring to: (a) the rainfall process, (b) the rainfall-runoff transformation, and (c) the flow-energy conversion. The first is due to the natural (i.e., hydroclimatic) variability, and is represented through stochastic approaches. Regarding the rainfall-runoff uncertainty, this arises from inherent structural shortcomings and poor parameter identifiability across the calibration procedure. In fact, hydrological model parameterizations using only historical data are often insufficient for accurately predicting catchment behavior over the long term, as they may not capture the full range of hydroclimatic conditions that the catchment may be subjected to. To address this issue, we use synthetic time series as drivers to parameterize the model and validate it against observed data. This approach preserves the probabilistic properties and dependence structure of the observed data while also providing a much wider range of hydroclimatic conditions for model training. In addition, it allows for assessing and quantifying the total model uncertainty. The final source of uncertainty is depicted by means of probabilistic efficiency curves. This Monte Carlo simulation-optimization framework is formalized as a modular procedure, where the different sources of uncertainty, as well as the full context, is tested through the design of a small hydropower plant in Epirus, Western Greece.

How to cite: Pagotelis, P., Tsilipiras, K., Lyras, A., Koutsovitis, A., Sakki, G.-K., and Efstratiadis, A.: Design of small hydropower plants under uncertainty: from the hydrological cycle to energy conversion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15407, https://doi.org/10.5194/egusphere-egu23-15407, 2023.

The trade-offs between human water needs and environmental considerations have always been challenging for water resources management and governance. Multi-purpose reservoirs present a particularly challenging decision context where multi-sectoral water and energy demands have to be balanced, while also considering the instream water requirements downstream. A systematic framework to evaluate the trade-offs between demand satisfaction, hydropower production, and satisfaction of minimum environmental flows (MEFs) would help reservoir operators better understand the consequences of various operational choices. In this study, we designed two formulations of a multi-purpose reservoir operation problem; one that prioritized MEF (PF_MEF) releases over demand satisfaction and another that did not (PF_nMEF). We identified Pareto approximate strategies to operate the reservoir for each formulation using the Borg multi-objective evolutionary algorithm considering multiple objectives related to water demand satisfaction, hydropower production, prevention of flood exceedance thresholds, and satisfaction of MEF. We applied the framework to the Nagarjuna Sagar (NS) reservoir in southern India. Reservoir operation strategies were modeled using direct policy search (DPS), where piecewise nonlinear Gaussian radial basis functions (RBFs) are used to condition decisions, and reservoir releases for hydropower in this case, on reservoir storage states. Results show that the Pareto approximate strategies resulting from optimizing for PF_MEF and PF_nMEF attain MEF - MEF in ranges 86-98% and 56- 79%, respectively. However, the ensuing compromises in water demand satisfaction and hydropower production are not considerably higher. Mean volumetric demand deficits and mean annual hydropower production ranged from 99.9 -818.1 Mm3 (48.13-818.8 Mm3) and 3252-3900 Gwh (3394- 3910 Gwh) for PF_MEF (PF_nMEF). Notably, we were able to identify strategies from PF_MEF that attained low values of volumetric demand deficits and high values of hydropower production, indicating that prioritizing MEFs may not necessarily yield compromises for human-related objectives in this case.

How to cite: Sunil, A., Singh, R., and Molakala, M.: Does prioritizing environmental flows compromise demand satisfaction and hydropower production in the Nagarjuna Sagar reservoir?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8318, https://doi.org/10.5194/egusphere-egu23-8318, 2023.

Hydropower is developing rapidly in Asia with limited concerns for long-term sustainability of hydropower plants. In the Indus, a four-fold increase in the 2020 hydropower capacity is envisioned by 2040 in Pakistan alone. Using the Hydropower Potential Exploration (HyPE) model, we investigate the future of hydropower potential in the Upper Indus basin (UIB) to inform such rapid expansion. HyPE uses a spatial cost-minimization framework to evaluate theoretical, technical, financial and sustainable hydropower potential considering the impact of natural, technical, financial, anthropogenic, environmental, and geo-hazard constrains on hydropower development. The model performs optimal siting and sizing of two run-of-river hydropower plant types under these varied constrains to minimize the unit cost of production at both the individual site and the basin scale. HyPE is run with current and future hydrology simulated using a cryosphere-hydrology model to understand the implication of climate change on the available potential in the UIB. Future hydrology is simulated using ensembles of spatially downscaled CMIP6 general circulation models (GCMs) covering a wide range of possible climatic futures under three combinations of the Shared Socio-economic Pathways (SSP) and the Representative Concentration Pathways (RCPs): SSP2-RCP4.5, SSP3-RCP7.0 and SSP5-RCP8.5.

The majority of the projections suggest an increase in annual average discharge. Over 50% increase in average annual discharge and subsequently theoretical potential is seen by the end of the century in the warm-wet corner under SSP5-RCP8.5. Increases in technical, financial and sustainable potential are slightly lower than that for theoretical potential. Some decline as much as -9% is seen only in the cold-dry corner under SSP2-RCP4.5. Higher increases in potential of all classes are seen in the western parts of the basin than in the eastern parts. Also, changes in low flows (-36 to 190%) are more extreme than in high flows (-52 to 109%) resulting in a boom in small projects in the future hydropower potential portfolios. Consequently, the cost curves at the sub-basin scales shift as the nature of hydropower plants vary more across the sub-basin. Furthermore, simulating the actual energy generation of historical and future hydropower portfolios under future hydrology reveals the robustness gained by considering climate change from the initial stages of hydropower design.

Promisingly, even the sustainable potential remains sufficient to establish energy security with intra-basin energy sharing in the UIB in the future. Fulfilling energy security in the downstream regions of the UIB countries, however, will require closer evaluation of how the spatial variation in sustainable hydropower across the UIB may be best leveraged. Sustainable hydropower development should be combined with other renewable energy sources to balance water utilization for hydropower versus other usage throughout the Indus for simultaneous fulfilment of the sustainable development goals (SDG) for water, energy and food security. Most importantly, the positive future of hydropower potential demonstrates that there is already enough leeway to consider factors beyond technical and financial criterion to also incorporate energy justice in sustainable hydropower development.  

How to cite: Dhaubanjar, S., Lutz, A., Pradhananga, S., Khanal, S., Smolenaars, W., Bhakta Shrestha, A., and Immerzeel, W.: Promising future for sustainable hydropower development in the Upper Indus basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11288, https://doi.org/10.5194/egusphere-egu23-11288, 2023.

Hydropower facilities in the United States (US) most often have non-powered objectives, for example storage and release of water for water supply or environmental benefit, or flood control. These objectives can limit the flexibility available to hydropower operations to generate power to provide maximum benefit to the power grid. There does exist however flexibility within a week to optimize hydropower generation while still ensuring non-powered objectives are met. We examine the flexibility available to optimize generation and the value of medium-range inflow forecasts using a dynamic programing reservoir optimization model applied at ~250 hydropower facilities over the US Western Interconnection. Optimization is performed using day-ahead hourly scheduling to reflect existing electricity markets, using Locational Marginal Prices (LMPs) provided by a production cost model, and using three flavors of medium-range inflow forecasts – perfect forecasts representing an upper limit on performance, persistence forecasts representing a lower benchmark, and synthetic forecasts as a surrogate for operational streamflow forecast products. Measures of direct performance and flexibility are examined at the grid-scale for Balancing Authorities within the Western Interconnection. This study highlights where and under what conditions medium-range forecasts influence flexibility in hydropower operations which will be increasingly valuable under an evolving grid with increased renewable penetration.

How to cite: Broman, D., Voisin, N., Kern, J., Steinschneider, S., Ssembatya, H., Wi, S., and Turner, S.: How Hydropower Operations Mitigate Flow Forecast Uncertainties to Maintain Grid Services in the Western US, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16887, https://doi.org/10.5194/egusphere-egu23-16887, 2023.