Estimation of the reference hydrological conditions in Slovenia with application of clustering analysis
<p>The reference hydrological conditions describe the natural discharge as ... more <p>The reference hydrological conditions describe the natural discharge as it would be without the exploitation of the water resources. The measured values of the discharge are obtained in the scope of national hydrological monitoring and are in most cases reduced for the amount of abstracted water. Therefore, the values measured in this way provide information on the amount of residual water in the river and not the total amount of water that would be available without abstraction. However, knowing the natural hydrological state is important when calculating the ecological flow and planning the future water use. For this purpose, our goal was to established the methodology for estimating the reference discharge on any water body in Slovenia with catchment size larger than 10 km<sup>2</sup>. The development of the methodology was based on detailed simulations of reference hydrological conditions for 56 selected cases. As those simulations require extensive data preparation and are very time consuming, we intended to generalize the results obtained for selected cases to the whole country using clustering analysis. The hierarchical clustering and K-means approach were applied taking into account different model arguments (e.g. number of clusters, distance metrics, number of iterations). First we have grouped the simulation points to check which of the attribute data influence the classification the most. Than clustering was repeated on the data set representing points distributed over the whole country as well as simulation points. However, the further analysis of the clustering results and application of other methods for generalization showed, that clustering analysis is in this case suitable for analysis of patterns in data and identification of influential variables, while generalization turned out to be better performed applying multiple regression analysis.</p>
HPP Vrhovo operation amendment on reservoir sediment management aspect
HPP Vrhovo is the first powerplant in the chain of the lower Sava River Basin, built in 1993 and ... more HPP Vrhovo is the first powerplant in the chain of the lower Sava River Basin, built in 1993 and as an object, spatially positined across the full width of the river, influences hydraulic conditions within the reservoir. Operation rulebook of the HPP Vrhovo determines dam gates and flaps operation only according to upstream flows, without considering sediment influence in the reservoir. At first, the role of hydroenergy as an renewable energy source in the electricity production is presented, followed by a short literature review from the expert field of sediment influence on reservoir hydraulic conditions and historical review of key sediment transport analyses of the HPP Vrhovo reservoir as one of later validation tools of the sediment transport simulation results. In the analytical section of the thesis, temporal changes of the HPP Vrhovo reservoir volume are analysed initially, followed by sediment transport theoretical basis, short introduction of used sediment transport model,...
Decision support system for evaluation of available surface water resources for use in Slovenia – development of the basis
<p>According to the Water Law of the Republic of Slovenia anyone who wants to use water res... more <p>According to the Water Law of the Republic of Slovenia anyone who wants to use water resources in addition to the general use (e.g. drinking, swimming and other recreational uses) needs to acquire a water right. Approving the water rights is in principal based on two conditions: (i) the discharge downstream from the withdrawal should be at least equal to ecologically acceptable flow and (ii) the withdrawal of the water should not influence the natural conditions or other already present uses and needs of water resources. Through the development of the system&#8217;s basis we have focused on the first condition, the hydrologically available water resources.</p><p>The information about the amount of the water in a river or a stream is provided by the discharge measurements, performed at locations of the water gauging stations by the Slovenian Environmental agency (ARSO). However, when granting a water permit, the location of certain water withdrawal can be anywhere along the watercourse. Therefore, we have tested seven advanced statistical models to connect characteristic discharges (mean and mean minimal discharge for a selected 30-year period) at measured points with attribute data describing the properties of the corresponding catchment. The 49 attribute values were gathered through analysis of spatial data in GIS environment and provided information about precipitation, temperature, geological structure, land use and water use in the area. According to the comparison of models performance we have selected the neural networks. They were used to estimate characteristic discharges in 340 selected points on the water courses all over the country. These values provide the basis for calculation of the ecologically acceptable flow and the amount of discharge available for use under certain terms. In addition, for the selected points (340 points) also the natural (reference) discharge was estimated as a discharge which would be observed without any water use present upstream. Simulations of natural discharge situation were performed for various scenarios and multiple selected test cases. The estimated differences between natural and measured discharge for selected points was than generalized for all the other points using the hierarchical clustering approach. So far the basic information about the amount of water available for use on watercourses with basins larger than 10 km<sup>2</sup> was estimated. However, the project is ongoing with the focus on improving the models, including the complex interactions between surface waters and groundwaters, and taking into account the vulnerability of the natural environment and ecosystem services they provide as well as sectoral needs.</p>
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Papers by Luka Javornik