41. Synoptic risk assessment of groundwater contamination from landfillsSonja Cerar, Luka Serianz, Katja Koren, Joerg Prestor, Nina Mali, 2022, izvirni znanstveni članek Povzetek: Waste management in Europe has improved in recent years, reducing the amount of waste disposed at landfills. However, there are still many landfills in the countries. It is well known that landfills that do not have measures in place to control leachate entering groundwater can contaminate groundwater long after the landfill is closed. Collecting monitoring results from all landfills allows permitting and management agencies to improve action plans. This relies on a synoptic risk assessment that allows prioritization and milestones to be set for required actions. The developed method of synoptic risk assessment is based on a conceptual model of the landfill and the results of chemical groundwater monitoring tested at 69 landfills in Slovenia. The study confirms that most landfills have a direct or indirect impact on groundwater quality. All landfills were classified into three priority classes on the basis of the synoptic risk assessment. The results show that a total of 24 landfills have a clearly pronounced impact on groundwater. A total of 31 landfills have a less pronounced impact due to the favorable natural attenuation capacity of the soil or the technically appropriate design of the landfill itself. A total of 14 landfills have a less pronounced or negligible impact on groundwater.
Ključne besede: conceptual model, synoptic risk assessment, landfill, groundwater, chemical analysis
Objavljeno v DiRROS: 19.07.2022; Ogledov: 730; Prenosov: 347
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44. Thermal-deformation model of a SR-modified A356 aluminum alloyYongyue Liu, Xianglai Xu, Jiangxiong Cheng, Hongwei Sun, Xueping Ren, Peng Jiang, 2022, izvirni znanstveni članek Ključne besede: A356 aluminum alloy, Sr modification, microstructure, thermal-deformation model
Objavljeno v DiRROS: 22.06.2022; Ogledov: 681; Prenosov: 208
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45. Artificial neural networks as an alternative method to nonlinear mixed-effects models for tree height predictionsMitja Skudnik, Jernej Jevšenak, 2022, izvirni znanstveni članek Povzetek: Tree heights are one of the most important aspects of forest mensuration, but data are often unavailable due to costly and time-consuming field measurements. Therefore, various types of models have been developed for the imputation of tree heights for unmeasured trees, with mixed-effects models being one of the most commonly applied approaches. The disadvantage here is the need of sufficient sample size per tree species for each plot, which is often not met, especially in mixed forests. To avoid this limitation, we used principal component analysis (PCA) for the grouping of similar plots based on the most relevant site descriptors. Next, we compared mixed-effects models with height-diameter models based on artificial neural networks (ANN). In terms of root mean square error (RMSE), mixed-effects models provided the most accurate tree height predictions at the plot level, especially for tree species with a smaller number of tree height measurements. When plots were grouped using the PCA and the number of observations per category increased, ANN predictions improved and became more accurate than those provided by mixed-effects models. The performance of ANN also increased when the competition index was included as an additional explanatory variable. Our results show that in the pursuit of the most accurate modelling approach for tree height predictions, ANN should be seriously considered, especially when the number of tree measurements and their distribution is sufficient.
Ključne besede: height-diameter models, national forest inventory, permanent sample plot, mixed forests, model comparison, principal component analysis
Objavljeno v DiRROS: 08.06.2022; Ogledov: 632; Prenosov: 289
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47. Verjetnostna in količinska napoved sanitarnega poseka smreke zaradi podlubnikov v Sloveniji v 2022Nikica Ogris, Maarten De Groot, 2022, drugi znanstveni članki Ključne besede: gozdovi, varstvo gozdov, navadna smreka, Picea abies, sanitarni posek, napoved, prognoza, ogroženost, model, smrekovi podlubniki, Ips typographus, Pityogenes chalcographus
Objavljeno v DiRROS: 13.04.2022; Ogledov: 680; Prenosov: 414
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48. Catalytic hydrocracking reactions of tetralin biomass tar model compound to benzene, toluene and xylenes (BTX) over metal-modified ZSM-5 in ambient pressure reactorAndrii Kostyniuk, David Bajec, Blaž Likozar, 2022, izvirni znanstveni članek Ključne besede: catalytic hydrocracking reactions, ring opening mechanism, model biomass tar, benzene/toluene/xylenes (BTX), metal-doped HZSM-5 zeolite material, deposited coke deactivation
Objavljeno v DiRROS: 10.03.2022; Ogledov: 817; Prenosov: 599
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49. Carbon flux and environmental parameters data from an eddy covariance tower in a mid-succession ecosystem developed on abandoned karst grassland in Slovenia (2012-2019)Koffi Dodji Noumonvi, Klemen Eler, Dominik Vodnik, Primož Simončič, Mitja Ferlan, 2021, zaključena znanstvena zbirka raziskovalnih podatkov Povzetek: This data set was used to estimate carbon fluxes by comparing eddy covariance tower (Long = 13.916701, Lat = 45.543491) measurements with vegetation indices based estimates.
Ključne besede: eddy covariance, GPP, NEE, empirical model, LUE model, vegetation photosynthesis model, vegetation indices
Objavljeno v DiRROS: 21.02.2022; Ogledov: 932; Prenosov: 733
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50. Primerjava različnih regresijskih modelov za napovedovanje debelinskega priraščanja jelkeAndrej Ficko, Vasilije Trifković, 2021, izvirni znanstveni članek Povzetek: V prispevku na primeru jelke predstavljamo sedem regresijskih modelov za modeliranje priraščanja dreves s podatki periodičnih meritev na stalnih vzorčnih ploskvah. Poleg polinomske regresije, modela z dodanim šumom in mešanega linearnega modela, predstavljamo regresijo z naravnimi zlepki in tri modele z omejenimi odvisnimi spremenljivkami: truncated regression, tobit regression in grouped data regression. Modele lahko uporabimo, kadar se zaradi načina merjenja in zaokroževanja podatkov ter hierarhičnosti podatkov srečamo z rezanimi ali krnjenimi slučajnostnimi spremenljivkami, nezveznostjo odvisne spremenljivke in pristransko oceno prirastka. Pri pojasnitvi debelinskega priraščanja 21.013 jelk na 4.405 ploskvah v obdobju 1990–2014 v raznomernih gozdovih v dinarskih jelovo-bukovjih so vsi modeli pokazali podoben vpliv prsnega premera, sestojne temeljnice, temeljnice debelejših dreves, raznomernosti, nagiba, nadmorske višine in le manjše razlike v regresijskih koeficientih in merah prileganja. Največje povprečne napovedi prirastka daje tobit model, mešani model pa se najbolj prilega podatkom. V primerjavi z drugimi modeli model z zlepki kaže na počasnejše zmanjševanje prirastka zelo debelih jelk po kulminaciji prirastka.
Ključne besede: prirastek, multipla regresija, statistične metode, tobit model, krnjenje, mešani modeli, jelka, modeli z omejenimi odvisnimi spremenljivkami, stalne vzorčne ploskve
Objavljeno v DiRROS: 01.12.2021; Ogledov: 3485; Prenosov: 1990
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