Hydrological reliability assessment of water management solution of reservoir storage capacity in conditions of uncertainty

Author(s):  
D Marton ◽  
M Starý ◽  
P Menšík ◽  
S Paseka
10.29007/s5s1 ◽  
2018 ◽  
Author(s):  
Daniel Marton ◽  
Kateřina Knoppová

The aim of this paper is to introduce method of the robust reservoir performance evaluation under the climate change uncertainty. Water resources adaptation on climate change, drought management strategies as well as hydrological and reservoir modeling in the climate change uncertainty have been serious issues. Newly developed lumped water balance model and reservoir simulation model will be used. Based on these tools the approach of robust reservoir storage capacity reliability assessment will be introduced. The hydrological data under climate change will be constructed using the statistical downscaling tool LARS WG. Ensemble of 29 climate scenarios will be created. The hydrology analysis and the temporal reliability of reservoir storage capacity and its robustness assessment against the climate change uncertainty will be presented on the case study of the Vir I reservoir and Svratka river basin in the Czech Republic.


2015 ◽  
Vol 63 (4) ◽  
pp. 287-294 ◽  
Author(s):  
Daniel Marton ◽  
Miloš Starý ◽  
Pavel Menšík

Abstract The paper contains a sensitivity analysis of the influence of uncertainties in input hydrological, morphological and operating data required for a proposal for active reservoir conservation storage capacity and its achieved values. By introducing uncertainties into the considered inputs of the water management analysis of a reservoir, the subsequent analysed reservoir storage capacity is also affected with uncertainties. The values of water outflows from the reservoir and the hydrological reliabilities are affected with uncertainties as well. A simulation model of reservoir behaviour has been compiled with this kind of calculation as stated below. The model allows evaluation of the solution results, taking uncertainties into consideration, in contributing to a reduction in the occurrence of failure or lack of water during reservoir operation in low-water and dry periods.


Abstract The limited amount of shared reservoir monitoring data around the world is insufficient to quantify the dynamic nature of reservoir operation with conventional ground-based methods. With the emergence of the Reservoir Assessment Tool (RAT) driven by a multitude of earth observing satellites and models, historical observation of reservoir operation spanning 35 years was made using open-source techniques. Trends in reservoir storage change were compared with trends of four critical hydrologic variables (precipitation, runoff, evaporation, and Palmer Drought Severity Index) to understand the potential role of natural drivers in altering reservoir operating pattern. It was found that the reservoirs in Africa were losing active storage at a rate of more than 1% per year of total storage capacity. Smaller reservoirs (with a capacity of less than 0.5 km3) in South-East Asia were found to experience a sharp gain in storage of 0.5% to 1% per year of total storage capacity. Storage change trends of large reservoirs with multiple years of residence time that are designed for strategic water supply needs and drought control were found to be less affected by precipitation trends and influenced more by drought and evaporation trends. Over Africa, most reservoir storage change trends were dictated by evaporation trends, while South Asian reservoirs appear to have their storage change influenced by drought and evaporation trends. Finally, findings suggest that operation of newer reservoirs are more sensitive to long-term hydrological trends and the regulated surface water variability that is controlled by older dams in the upstream.


2012 ◽  
Vol 622-623 ◽  
pp. 1152-1156
Author(s):  
Tilahun Derib Asfaw ◽  
Khamaruzaman Wan Yusof ◽  
Ahmad Mustafa Hashim

The cascading reservoirs in Perak, Malaysia, were used to test the sensitivity analysis of hydroelectric power generation during refill and deplete period of the reservoirs. The cascading scheme comprises four reservoirs namely Temenggor, Bersia, Kenering and Chenderoh. The test was conducted after the analysis of water balance and stage-storage relationship of each reservoir in the cascading scheme. The result showed that power generation from the smaller reservoir, Bersia, is more sensitive to the change of headrace level, while the larger storage capacity and rated head reservoir is the most sensitive to the change of release. Therefore, to maximize the power generation from the cascading reservoir, the refill operations should be ranked according to the increasing order of the reservoir storage capacity and a reverse order should be followed during deplete period.


2021 ◽  
Author(s):  
Conrad Brendel ◽  
Alena Bartosova ◽  
Johan Strömqvist ◽  
Charlotta Pers ◽  
René Capell ◽  
...  

<p>Reservoir sedimentation represents a significant threat to the reliability of global water and energy supplies. Over the life of a reservoir, storage capacity is gradually lost due to the deposition of sediments. Hydrological models represent a valuable method to study and evaluate the effects of reservoir storage losses on issues such as energy production, discharge capacity, and flood attenuation. The Hydrological Predictions for the Environment (HYPE) model is a semi-distributed, catchment-based hydrology model that has been used to quantify sediment fluxes across a variety of catchment, country, continent, and global modeling domains. In this study, several methods to estimate reservoir storage capacity losses due to sedimentation were added to HYPE, and their impact on sediment simulations and resulting model performance was tested in multiple landscapes in various parts of the world. Selected methods consider the texture and size of deposited sediment particles, the compaction of deposited sediments over time, and the manner in which reservoirs are operated. Results from the study will be used to inform future model development and improve modeling of sediment fluxes at the global scale.</p>


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