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  • Assay of runoff conditions using a Digital Elevation Model
    124-129
    Views:
    91

    We can get information about water conditions of plane areas by analyzing their relief. By using the Digital Elevation Model, we can get proper information about runoff conditions in the terrain surface, which is the basis for ponding analysis. In our study, a Digital Elevation Model of the sample plot in Hajdúsági-löszhát (loess ridge) was created that makes possible the determination of runoff conditions of the surface. Convergence and divergence of runoff direction showed the rate of ponding and the location of possible inland-water spots. By using this model, concrete location of those areas that tend to be overmoistured could be determined. Knowledge of this phenomenon can be an effective instrument for farmers in optimizing crop growing, and additionally in performing water management interventions in proper time and space.

  • Analysis of the Relation Between the Relief and the Surface Water Network
    90-93
    Views:
    53

    The Bihar plain situated in the Great Hungarian Plain has altitudinal values between 87 and 108 meters above Baltic level and these low average values decreases from East to West. We can find on this place a surface water network with a high density; the most of them was created for diversion of inland water.
    The GIS is the best practice for modelling and simulating the relief and the water network. Towards the creation of the TIN model and relief- analysis we need the digital elevation model as well as the digital water network dataset for the whole territory. The source of the data was topographic maps on high scale level (1:10.000).

  • Characterisation of basic water balance parameters of Debrecen
    35-40
    Views:
    148

    This work aims to develop a hydrological modelling tool to help managers make the right decisions for Debrecen, in the face of water scarcity and the increase in agricultural and domestic needs over time. The methodology was based on the creation of a climatic database, at monthly time steps, from 2016 to 2019, and cartographic (land use, digital elevation model, and hydrological network). As a next step, the watershed was delimitated into sub-basins to determine the shape and the physiographic characteristics of sub-watersheds. Finally, a hydrological study was prepared by calculating the time of concentration to build a database of water resources in the study area. This water resource will be used as an input parameter for urban farming.

  • Classification of a diffuse heavy metal polluted mining site using a spectral angle mapper
    119-123
    Views:
    84

    Characterization of heavy metal polluted abandoned mining sites is complicated, as the spatial distribution of pollutants often changes dramatically.
    In our study, a hyperspectral data analysis of the Gyöngyösoroszi abandoned Pb-Zn mine, located in northern Hungary, where Záray (1991) reported serious heavy metal contamination, was carried out using ENVI 4.3. In this area, galena (PbS), goethite (FeO(OH)), jarosite (KFe3(SO4)2(OH)6), sphalerite ((Zn, Fe)S) and pyrite (FeS2) were the predominant minerals in the alteration zones was chosen as the target mineral.
    Spectral angle mapper (SAM) and BandMax classification techniques were applied to obtain rule mineral images. Each pixel in these rule images represents the similarity between the corresponding pixels in the hyperspectral image to a reference spectrum.
    As a result of hyperspectral imagery the distribution of pyritic minerals (sphalerite, galena) in the area was defined. Both of the mineral formations occur, especially in mine tailings, the area of the ore preparatory, and the Szárazvölgyi flotation sludge reservoir. According to the results, jarosite and goethite have similar distributions to sphalerite and galena. The results showed that hyperspectral remote sensing is an effective tool for the
    characterization of Pb, Zn and Fe containing minerals at the examined polluted sites and for modelling the distribution of heavy metals and minerals in extensive areas.
    This classification method is a basis of further detailed investigations, based on field measurements, to map the heavy metal distribution of the studied area and to quantify the environmental risks caused by erosion, which include DEM (digital elevation model) and climatic and hydrological data sources. Furthermore, it can be used primarily to support the potentially applicable phytostabilization technique and to isolate hot spots where only ex-situ remediation techniques can be applied.