A multivariate approach to study the geochemistry of urban topsoil in the city of Tampere, Finland

Buttafuoco, Gabriele; Guagliardi, Ilaria; Tarvainen, Timo; Jarva, Jaana

doi:10.1016/j.gexplo.2017.07.017

Cited by 32 publications

(13 citation statements)

References 23 publications

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“…This is important especially because improved methods of interpolation will enhance the ability to quantify the effects of climate on both natural and managed ecosystems, such as forests, wetlands and agroecosystems (Buttafuoco, Caloiero, Guagliardi, & Ricca, 2016;Price, McKenney, Nalder, Hutchinson, & Kesteven, 2000). Several methods have been developed to interpolate meteorological data, and the choice of the most suitable interpolator may vary depending on the regions (Buttafuoco, Guagliardi, Tarvainen, & Jarva, 2017;Ly, Charles, & Degré, 2011;Xu, Zou, Zhang, & Linderman, 2015) and according to many key factors influencing the climate, such as elevation, large-scale circulation, morphological features and natural vegetation. Within this context, the comparison between deterministic (Agnew & Palutikof, 2000;Hutchinson & Gessler, 1994;Legates & Willmott, 1990;Vicente-Serrano, Saz-Sánchez, & Cuadrat, 2003) and geostatistical (Goovaerts, 1997(Goovaerts, , 1999Isaaks & Srivastava, 1989;Journel & Huijbregts, 1978) techniques is widely adopted providing a tool to support the choice of the most suitable interpolation method.…”

Section: Introductionmentioning

confidence: 99%

The De Martonne aridity index in Calabria (Southern Italy)

2019

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In this paper, the annual rainfall and temperature values, measured in the period 1951-2016 in a region of southern Italy (Calabria), have been spatially interpolated using deterministic and geostatistical techniques in an R environment. In particular, Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Kriging with External Drift (KED) and Ordinary Cokriging (COK) were compared to evaluate the best suitability method in reproducing the actual surface. Then, the spatial variation of aridity in Calabria has been evaluated using the De Martonne aridity index (IDM), which is based on rainfall and temperature data. As a result, geostatistical methods incontrovertibly show a better estimate than the IDW. Specifically, the KED was identified as the best predictor method for both rainfall and temperature data. Moreover, the spatial distribution of the IDM evidenced that the majority of the study area can be classified as humid, with semi-arid conditions mainly identified in the coastal areas.

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Section: Introductionmentioning

confidence: 99%

The De Martonne aridity index in Calabria (Southern Italy)

2019

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“…Then when training is done, the data that were removed can be used to test the performance of the learned model on "new" data. The actual error incurred in this process is measured by the difference between the actual and estimated value [58][59][60].…”

Section: Cross-validationmentioning

confidence: 99%

Comparative Analysis of Different Spatial Interpolation Methods Applied to Monthly Rainfall as Support for Landscape Management

et al. 2021

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Landscape management requires spatially interpolated data, whose outcomes are strictly related to models and geostatistical parameters adopted. This paper aimed to implement and compare different spatial interpolation algorithms, both geostatistical and deterministic, of rainfall data in New Zealand. The spatial interpolation techniques used to produce finer-scale monthly rainfall maps were inverse distance weighting (IDW), ordinary kriging (OK), kriging with external drift (KED), and ordinary cokriging (COK). Their performance was assessed by the cross-validation and visual examination of the produced maps. The results of the cross-validation clearly evidenced the usefulness of kriging in the spatial interpolation of rainfall data, with geostatistical methods outperforming IDW. Results from the application of different algorithms provided some insights in terms of strengths and weaknesses and the applicability of the deterministic and geostatistical methods to monthly rainfall. Based on the RMSE values, the KED showed the highest values only in April, whereas COK was the most accurate interpolator for the other 11 months. By contrast, considering the MAE, the KED showed the highest values in April, May, June and July, while the highest values have been detected for the COK in the other months. According to these results, COK has been identified as the best method for interpolating rainfall distribution in New Zealand for almost all months. Moreover, the cross-validation highlights how the COK was the interpolator with the best least bias and scatter in the cross-validation test, with the smallest errors.

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“…It naturally occurs in the environment or derives from anthropogenic input, commonly found in fertilizers and animal and human wastes. Usually, human activities are altering all biogeochemical cycles [ 1 , 2 ] and tend to particularly affect the natural nitrogen cycle either directly (e.g., industrial, residential, agricultural, farming discharge) or indirectly, by altering soil degradation processes [ 3 , 4 , 5 , 6 , 7 , 8 ]. Furthermore, the dynamics of the hydrogeological systems and their water resource quality can be affected by climate change [ 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Vulnerability to Nitrate Occurrence in the Spring Waters of the Sila Massif (Calabria, Southern Italy)

Infusino

Guagliardi

Gaglioti

et al. 2022

Toxics

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Knowledge of spring waters’ chemical composition is paramount for both their use and their conservation. Vast surveys at the basin scale are required to define the nature and the location of the springs and to identify the hydrochemical facies of their aquifers. The present study aims to evaluate the hydrochemical facies and the vulnerability to nitrates of 59 springs falling in the Sila Massif in Calabria (southern Italy) and to identify their vulnerability through the analysis of physicochemical parameters and the use of the Langelier–Ludwig diagram. A spatial analysis was performed by the spline method. The results identified a mean value of 4.39 mg NO3−/L and a maximum value of 24 mg NO3−/L for nitrate pollution in the study area. Statistical analysis results showed that the increase in electrical conductivity follows the increase in alkalinity values, a correlation especially evident in the bicarbonate Ca-Mg waters and linked to the possibility of higher nitrate concentrations in springs. These analyses also showed that nitrate vulnerability is dependent on the geological setting of springs. Indeed, the Sila igneous–metamorphic batholith, often strongly affected by weathering processes, contributes to not buffering the nitrate impacts on aquifers. Conversely, anthropogenic activities, particularly fertilization practices, are key factors in groundwater vulnerability.

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A multivariate approach to study the geochemistry of urban topsoil in the city of Tampere, Finland

Cited by 32 publications

References 23 publications

The De Martonne aridity index in Calabria (Southern Italy)

The De Martonne aridity index in Calabria (Southern Italy)

Comparative Analysis of Different Spatial Interpolation Methods Applied to Monthly Rainfall as Support for Landscape Management

Vulnerability to Nitrate Occurrence in the Spring Waters of the Sila Massif (Calabria, Southern Italy)

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