This study evaluates the impact of hydroclimate-driven periodic runoff on hydropower operations and production, with a focus on how the forecasted biennial periodicity of runoff time series could affect the efficiency of hydropower generation. Hydrologic stochastic processes are utilized to forecast long-term runoff, and seven hydroclimate scenarios are developed to be input into a production management model, allowing for an analysis of how periodic hydroclimate variations influence hydropower management and output. The results reveal that the biennial alternation between wet and dry years is a key factor affecting hydropower operations in the Dalälven River Basin. Notable differences between wet- and dry-year scenarios were observed in terms of power efficiency, production output, and forecasting accuracy. Operating hydropower systems based on dry-year runoff forecasts in wet years results in a 1.63% decrease in production efficiency and a reduction of 9,104 MWh in power generation. Conversely, applying wet-year forecasts in dry years slightly boosts production efficiency by 0.31% and increases power generation by 7,832 MWh. Scenarios that adhere to biennial periodicity offer the highest forecasting accuracy, particularly when applying dry-year forecasts in dry years in winter and spring, which produce the most precise predictions. In contrast, using dry-year forecasts in wet years results in the lowest forecasting accuracy.

Hydropower is the largest source of renewable energy in the world and currently dominates flexible electricity production capacity. However, climate variations remain major challenges for efficient production planning, especially the annual forecasting of periodically variable inflows and their effects on electricity generation. This study presents a model that assesses the impact of forecast quality on the efficiency of hydropower operations. The model uses ensemble forecasting and stepwise linear optimisation combined with receding horizon control to simulate runoff and the operation of a cascading hydropower system. In the first application, the model framework is applied to the Dalalven River basin in Sweden. The efficiency of hydropower operations is found to depend significantly on the linkage between the representative biannual hydrologic regime and the regime actually realised in a future scenario. The forecasting error decreases when considering periodic hydroclimate fluctuations, such as the dry-wet year variability evident in the runoff in the Dalalven River, which ultimately increases production efficiency by approximately 2% (at its largest), as is shown in scenarios 1 and 2. The corresponding potential hydropower production is found to vary by 80 GWh/year. The reduction in forecasting error when considering biennial periodicity corresponds to a production efficiency improvement of about 0.33% (or 13.2 GWh/year).

Porosity change is a common characteristic of natural soils in fluid-solid interaction problems, which can lead to an obvious change of the soil-water retention curve (SWRC). The influence of porosity on soil water retention phenomena is investigated by a theoretical model and an experimental test in this study. A model expressing the change in suction with porosity and effective saturation is put forward theoretically. The model is based on an idealization of three-phase porous materials, the pore structures of which are homogeneous and isotropic. It accounts for the porosity effect on soil water retention, using four parameters with clear physical meanings. The presented model can obtain the SWRC at any porosity, which will reduce the test number required in characterizing the hydraulic behavior of soil. A laboratory experiment for loamy sand with different porosities is performed. The test results show that suction has a significant variation with changes in porosity and decreases with the increase of porosity. The formulation is verified by both the test data and the literature data for FEBEX bentonite and Boom clay. The very good agreements between measured and predicted results show that the SWRC model is reliable and feasible for various soils.

The viability of a renewable electricity system depends on a relatively small share of hydropower storage resources to regulate climate variations and the spatially uneven distribution of renewable energy. By spatio-temporal coordination of hydropower production over larger regions, the energy storage demand will be reduced and contribute to a "virtual" energy storage gain that in Europe was found to be almost twice the actual energy storage capacity of hydropower reservoirs. In an attempt to quantify this gain, hydropower availability was simulated for most parts of the European continent for a 35-year period based on historical hydrometeorological data. The most significant benefits from spatio-temporal management arise at distances between 1200 and 3000 km, i.e., on the continental scale, which can have implications for a future renewable energy system at large. Furthermore, we discuss a condition termed "energy-domain-specific drought", which is a risk that can be reduced by the spatio-temporal management of power production. Virtual energy storage gain is not explicitly considered in the management models of hydropower production systems but could in principle complement existing management incentives.