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    Ecotoxicological Assessment of Sediment Leachates of Small Watercourses in the Brno City Suburban Area (South Moravia, Czech Republic)
    (University of Veterinary and Pharmaceutical Sciences in Brno, 2010-03-01) Beklová, Miroslava; Čelechovská, Olga; Dobšíková, Radka; Haluzová, Ivana; Králová, Helena; Malá, Jitka; Modrá, Helena; Ostrá, Magdalena; Svobodová, Zdeňka
    Sediments of two small watercourses Leskava and Troubsky Brook in the Brno city suburban area were examined for their ecotoxicity. Using a standard procedure, extracts of the sediments were prepared for diagnostic tests. These extracts were tested for acute toxicity to fresh-water organisms. The ecotoxicological tests were performed on the fresh-water alga Pseudokirchneriella subcapitata, the vascular water plant Lemna minor, on a representative of invertebrates, the water flea Daphnia magna and on the Xenopus laevis frog embryo and luminiscent Vibrio fischeri bacteria. Possible toxic effects were evaluated using the test determining the inhibition of the growth of white mustard root Sinapis alba. Results of ecotoxicological assessment of sediment leachates showed that their quality varied significantly during the year. Differences were found between results of sediment evaluations from different collection profiles, which may indicate effects of point source pollution. Of the ecotoxicological tests used, the most sensitive organismsincluded the green algae Pseudokirchneriella subcapitata, bioluminiscent bacteria Vibrio fischeri and the African clawed frog Xenopus laevis. The highest concentrations of arsenic were found by chemical analysis in both spring and autumn sediment leachate samples collected at Site L1 (Leskava). The highest organic pollutant concentrations were found in autumn sediment leachate samples from Site L1. In total PAH sums, phenanthrene was the dominant pollutant at all the sites investigated.
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    Innovative and CostEffective Approaches to the Measurement of Sediment Levels in Small Water Reservoirs
    (WILEY, 2024-10-22) Paseka, Stanislav
    Sedimentation in small water reservoirs poses a critical challenge with significant environmental, economic, and social implications. To address this issue, this study will employ three measurement techniques—GNSS RTK Trimble R8s, Echolot HDS LIVE 7 with Active Imaging 3in1, and the Mivardi Carp Scout bait boat—to assess sediment levels in Žebětínský Pond in Brno, Czech Republic. The research reveals that each method offers distinct advantages and limitations. Through measurement and triangulated networks, the study creates a digital terrain model that facilitates the determination of reservoir volume and sediment levels. The comparison shows that the costeffective alternatives, Echolot HDS LIVE 7 and Mivardi Carp Scout, provide sufficiently accurate results. The evaluation shows that while the GNSS RTK Trimble R8s has the highest level of accuracy and is unique in its ability to measure both along the shoreline of the reservoir and the hard bottom, it comes with increased costs and logistical challenges. The Echolot HDS LIVE 7 and Mivardi Carp Scout offer efficient, costeffective solutions that are suitable for a quick estimate of sediment thickness. This research contributes to the use of reliable mathematical models and water management strategies, advocating for a pragmatic approach to the selection of methods based on the project characteristics. The study provides valuable insights into sediment measurement techniques, guiding future endeavors in reservoir management and environmental conservation. It is also used to easily indicate the loss of arable land in the catchment upstream of the reservoir.
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    Using Predictive Model for Strategic Control of Multi-reservoir System Storage Capacity
    (Elsevier Science Publishers, 2015-09-02) Marton, Daniel; Menšík, Pavel; Starý, Miloš
    The paper will describe the algorithm based on adaptive optimization of multi reservoir control, which the medium-term water flow predictions into the reservoirs for several months ahead repeatedly use. Hydrological prediction model was created using ANN method and values of control outflows are searching by optimization based on evolutionary algorithms optimization technique. The objective function was descripted as the sum of squares deviations between required and actual controlled water outflow from reservoirs where objective function is minimized. The algorithm of adaptive control is applied to the operation storage control of selected reservoir system, which open water reservoirs Vir and Brno are created.
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    Hybrid Optimization Method for Strategic Control of Water Withdrawal from Water Reservoir with Using Support Vector Machines
    (Elsevier Science Publishers, 2017-05-09) Menšík, Pavel; Marton, Daniel
    The aim of strategic control is the effort to achieve optimal water resource management (water reservoir). Classic strategic control of water withdrawal from water reservoir are based mainly on the rules and rules curves, which are created by generalization of historical data of water inflows to the reservoirs and water demand. Discharge series are changing in the time due to expected climate change. It is necessary to looking for intelligent water withdrawal control, which will allow to react on these hydrological changes and contribute to the efficient use of accumulated water for ensure water demand. The paper will describe the algorithm based on adaptive control. The normal adaptive control required knowledge of the water flow medium-term prediction into the reservoir. The created algorithm of intelligent water withdrawal control does not require knowledge of hydrological predictions. This control method is based on a suitable combination optimization method with the Support vector machines method. The control algorithm is one of the possible measures to mitigate the negative impacts of droughts and water scarcity. The algorithm of adaptive control is applied to the control of water withdrawal from selected single-reservoir. The results are compared with usual rules for water withdrawal control.
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    Spatio-temporal analysis of remotely sensed and hydrological model soil moisture in the small Jicinka River catchment in Czech Republic
    (SCIENDO, 2021-01-26) Dukic, Vesna; Eric, Ranka; Dumbrovský, Miroslav; Sobotková, Veronika
    The knowledge of spatio-temporal dynamics of soil moisture within the catchment is very important for rainfall-runoff modelling in flood forecasting In this study the comparison between remotely sensed soil moisture and soil moisture estimated from the SHETRAN hydrological model was performed for small and flashy Jieinka River catchment (75.9 km(2)) in the Czech Republic. Due to a relatively coarse spatial resolution of satellite data, the satellite soil moisture data were downscaled, by applying the method developed by Qu et al. (2015). The sub-grid variability of soil moisture was estimated on the basis of the mean soil moisture for the grid cell and the known hydraulic soil properties. The SHETRAN model was calibrated and verified to the observed streamflow hydrographs at the catchment outlet. The good correlation between the two different soil moisture information was obtained according to the majority of applied criteria. The results of the evaluation criteria indicate that the downscaled remotely sensed soil moisture data can be used as additional criteria for the calibration and validation of hydrological models for small catchments and can contribute to a better estimation of parameters, to reduce uncertainties of hydrological models and improve runoff simulations.