Lost Energy of Water Spilled over Hydropower Dams

Predin, Andrej; Fike, Matej; Pezdevšek, Marko; Hren, Gorazd

doi:10.3390/su13169119

Cited by 4 publications

(2 citation statements)

References 18 publications

(21 reference statements)

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“…Slovenia's strategic goal of increasing sustainable energy has resulted in the planning and construction of multiple hydroelectric power plants on the Sava River [8,9]. Fortyone large dams are identified in Slovenia [10], and these water control structures are listed on the Slovenian National Committee on Large Dams (SLOCOLD) [11].…”

Section: Introductionmentioning

confidence: 99%

Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies for the Sava River Basin (Slovenia)

et al. 2023

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The Sava River Basin (SRB) extends across six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro) and is a major tributary of the Danube River (DR). The Sava River (SR) originates in the alpine region of Slovenia, and, in support of a Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including energy production, information about past (paleo) drought and pluvial periods would provide important information to water managers and planners. Seasonal (April–May–June–July–August–September—AMJJAS) streamflow data were obtained for two SRB gauges (Jesenice and Catez) in Slovenia. The Jesenice gauge is in the extreme headwaters of the SR, upstream of any major water control structures, and is considered an unimpaired (minimal anthropogenic influence) gauge. The Catez gauge is located on the SR near the Slovenia–Croatia border, thus providing an estimate of streamflow leaving Slovenia (entering Croatia). The Old World Drought Atlas (OWDA) provides an annual June–July–August (JJA) self-calibrating Palmer Drought Severity Index (scPDSI) derived from 106 tree-ring chronologies for 5414 grid points across Europe from 0 to 2012 AD. In lieu of tree-ring chronologies, this dataset was used as a proxy to reconstruct (for ~2000 years) seasonal streamflow. Prescreening methods included the correlation and temporal stability of seasonal streamflow and scPDSI cells. The retained scPDSI cells were then used as predictors (independent variables) to reconstruct streamflow (predictive and/or dependent variables) in regression-based models. This resulted in highly skillful reconstructions of SRB seasonal streamflow from 0 to 2012 AD. The reconstructions were evaluated, and both low flow (i.e., drought) and high flow (i.e., pluvial) periods were identified for various filters (5-year to 30-year). When evaluating the most recent ~20 years (2000 to present), multiple low-flow (drought) periods were identified. For various filters (5-year to 15-year), the 2003 end-year consistently ranked as one of the lowest periods, while the 21-year period ending in 2012 was the lowest flow period in the ~2000-year reconstructed-observed-historic period of record. The ~30-year period ending in 2020 was the lowest flow period since the early 6th century. A decrease in pluvial (wet) periods was identified in the observed-historic record when compared to the paleo record, again confirming an apparent decline in streamflow. Given the increased activities (construction of water control structures) impacting the Sava River, the results provide important information to water managers and planners.

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Section: Introductionmentioning

confidence: 99%

Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies for the Sava River Basin (Slovenia)

et al. 2023

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“…Predictability of water discharge along the SRB is a key element for water use planning and managing. This is especially important in Slovenia because of its strategic objective of developing multiple hydropower plants on the SR with the intent of increasing sustainable energy production in the country [11,12]. Recent research has used tree-ring-based proxies to reconstruct streamflow in the SRB, highlighting the relationship between streamflow and climate variability [13].…”

Section: Introductionmentioning

confidence: 99%

Machine-Learning-Based Precipitation Reconstructions: A Study on Slovenia’s Sava River Basin

Ramírez Molina,

Bezak,

Tootle

et al. 2023

Hydrology

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The Sava River Basin (SRB) includes six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro), with the Sava River (SR) being a major tributary of the Danube River. The SR originates in the mountains (European Alps) of Slovenia and, because of a recent Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including hydropower (energy production), information about past (paleo) dry (drought) and wet (pluvial) periods would provide important information to water managers and planners. Recent research applying traditional regression techniques and methods developed skillful reconstructions of seasonal (April–May–June–July–August–September or AMJJAS) streamflow using tree-ring-based proxies. The current research intends to expand upon these recent research efforts and investigate developing reconstructions of seasonal (AMJJAS) precipitation applying novel Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques. When comparing the reconstructed AMJJAS precipitation datasets, the AI/ML/DL techniques statistically outperformed traditional regression techniques. When comparing the SRB AMJJAS precipitation reconstruction developed in this research to the SRB AMJJAS streamflow reconstruction developed in previous research, the temporal variability of the two reconstructions compared favorably. However, pluvial magnitudes of extreme periods differed, while drought magnitudes of extreme periods were similar, confirming drought is likely better captured in tree-ring-based proxy reconstructions of hydrologic variables.

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Retrieving Energy from an Inline Hydro Turbine of Irrigation-Dependent Hydropower Plant Under Part Flow Conditions

Kurulekar,

Kumar,

Joshi

2024

Lecture Notes in Mechanical Engineering

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Lost Energy of Water Spilled over Hydropower Dams

Cited by 4 publications

References 18 publications

Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies for the Sava River Basin (Slovenia)

Streamflow Reconstructions Using Tree-Ring-Based Paleo Proxies for the Sava River Basin (Slovenia)

Machine-Learning-Based Precipitation Reconstructions: A Study on Slovenia’s Sava River Basin

Retrieving Energy from an Inline Hydro Turbine of Irrigation-Dependent Hydropower Plant Under Part Flow Conditions

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