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This paper introduces the alternating conditional expectation (ACE) algorithm of Breiman and Friedman (1985) in multiple regression problems in groundwater monitoring data analysis. This special inverse nonparametric approach can be applied easily for estimating the optimal transformations of different groundwater monitoring data from the Bükk Mountains to obtain maximum correlation between observed aquifer variables. The approach does not require a priori assumptions of a mathematical form, and the optimal transformations are derived solely based on the groundwater data set. The advantages and applicability of the proposed approach to solve different multiple regression problems in hydrogeology or in groundwater management are illustrated by means of case studies from a Hungarian karst aquifer. It is demonstrated that the ACE method has certain advantages in some fitting problems of groundwater science over the traditional multiple regression.In the past, different groundwater monitoring data (like groundwater level, groundwater temperature and conductance, etc.) had been used for groundwater management purposes in the Bükk Mountains. One of the difficulties in earlier approaches has been the need to make some kind of assumption of the expected mathematical forms among the investigated reservoir and petrophysical variables. By using nonparametric regression, the need to assume a specific form of model is avoided, and a clearer vision of the relationships between aquifer parameters can be revealed in the Bükk Mountains, where karst water is the main source of potable water supply. Complex monitoring data from the Bükk Mountains were analyzed using the ACE inverse method, and results were verified successfully against quantitative and qualitative field observations.

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the same for both figures, units are in meters In situ tests An often-used method of instrumental monitoring in Bátaapáti is the mechanical convergence measurement

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-Holand Geodesy, the concept Vyskočil P 1989: Procedures for Monitoring Recent Crustal Movements. ICG, CRCM, ICRCM Praha Procedures for Monitoring

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Juhász, I. 2006: Soil conditions in Hungary based on the data from the Soil Conservation Information and Monitoring System (SIMS). - Ministry of Agriculture and Rural Development, Budapest, 90 pp. Juhász I

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determines the rate of evapotranspiration and the speed at which solar radiation is absorbed. If this is the case, then vegetation monitoring in urban ecosystems is an important endeavor and simultaneously, is a valuable tool in the reduction of atmospheric

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The investigation of the stability of large objects, such as towers, buildings, bridges, etc.\ without disturbing the function of the object plays a very important role. This paper deals with the problem how Earth tide waves can be used as input signals for this investigation. Two large objects, the TV tower and the church Kecske in Sopron (Hungary) were chosen for tidal measurements. The results prove that tidal signals can be detected and under special circumstances these signals can be used for health monitoring of large objects.

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This work focuses on the assessment of seismic risk and the need of long-term studies on the territory of the only terrestrial Bulgarian salt deposit (Provadia, NE Bulgaria, 27.43E, 43.2N) in connection with the observed higher seismic activity and probable manifestations of technogenic seismicity in the region.The necessity of regular monitoring of the geodynamic situation, surface subsidences and control of the mining excavations are discussed. A review of the manifestations of some observed problems due to the long-term mining is done. Some results of the performed monitoring at the site during the 1989–2009 are provided. Results of the analyses of the geological and seismotectonic situation, assessment of the stress-strain state of the salt diapir, surface subsidence, analysis of the recorded accelerograms, analyses of the seismic regime variation are discussed. The use of these analyses and their possible applications for the general stability assessment of the cavern-pillar system is formulated.

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In autumn of 1997 two borehole tiltmeters, type AppliedGeomechanics, A722 were installed for monitoring recentmovements of the Mecsekalja fault in Southwest Hungary. Beside the continuous tilt measurements a geodetic network for GPS and electronic distance measurements (EDM) and a levelling line crossing the fault were established. The borehole tiltmeters are continuously recording and the geodetic measurements (GPS, EDM, precision levelling) are repeated twice in a year, in spring and in autumn. This paper presents experiences and results of the tiltmeter measurements and analyses the disturbing effects e.g. earth tide, tilt caused by ground water level variations, precipitation of the surrounding vegetation, etc.  superposed to the tilt signal. The paper shows some of these effects which can use to prove the goodness of the coupling between the instrument and the ground.

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The problem of handling outliers in a deformation monitoring network is of special importance, because the existence of outliers may lead to false deformation parameters. One of the approaches to detect the outliers is to use robust estimators. In this case the network points are computed by such a robust method, implying that the adjustment result is resisting systematic observation errors, and, in particular, it is insensitive to gross errors and even blunders. Since there are different approaches to robust estimation, the resulting estimated networks may differ. In this article, different robust estimation methods, such as the M-estimation of Huber, the “Danish”, and the L 1 -norm estimation methods, are reviewed and compared with the standard least squares method to view their potentials to detect outliers in the Tehran Milad tower deformation network. The numerical studies show that the L 1 -norm is able to detect and down-weight the outliers best, so it is selected as the favourable approach, but there is a lack of uniqueness. For comparison, Baarda’s method “data snooping” can achieve similar results when the outlier magnitude of an outlier is large enough to be detected; but robust methods are faster than the sequential data snooping process.

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Abstract

Ferromagnetic grains in airborne dust are important indicators of vehicle traffic, some industrial sources and combustion/heating. Settled dust consists mainly of diamagnetic material; therefore accessory ferromagnetic grains are readily indicated by magnetic measurements. In this paper settled dust samples collected on a monthly basis in the years 2008–2011 were studied. Non-destructive magnetic measurements were followed by geochemical and mineralogical analyses. In selected samples we identified airborne anthropogenic materials (e.g. silicate and magnetite spherules), minerals from the natural environment and organic material. Seasonally appearing materials (e.g. soot in winter, plant fragments and pollen in summer) increased the mass of the settled dust, but not the magnetic susceptibility. Thus, we realized that the generally interpreted mass susceptibility in environmental magnetic studies would not always appropriately characterize the magnetic pollution. In the interpretation we gave preference to total susceptibility because of its direct connection to the pollution, except in comparison with metal concentrations.

Trends in magnetic pollution were eventually analyzed for 19 sampling sites. Irrespective of the degree and source of the pollution the monthly variation curves of magnetic susceptibility exhibit a general maximum (March-April), followed by gradual decrease. A corresponding peak is observed in the amounts of dust. Both can be explained by re-suspension of dust settled in winter. The additional maxima in the mass of the dust (June and August, respectively) are probably due to contribution from vegetation and/or an artifact from algaecide. For three key sampling sites comparison was made between the concentrations of 12 metals and the respective mass susceptibilities and good linear correlation was found for Fe, Mn and Zn for all, for Cr, Cu, Pb, V, Ba, Sr and Zr for two sampling sites. Cd, which is enriched in all samples, does not correlate with the magnetic susceptibility.

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