Evaluating pedotransfer functions for predicting soil bulk density using hierarchical mapping information in Campania, Italy

Nasta, Paolo; Palladino, Maria Teresa; Sica, Benedetto; Pizzolante, Antonio; Trifuoggi, Marco; Toscanesi, Maria; Giarra, Antonella; D'Auria, Jacopo; Nicodemo, Federico; Mazzitelli, Caterina; Lazzaro, Ugo; Fiore, Paola Di; Romano, Nunzio

doi:10.1016/j.geodrs.2020.e00267

Cited by 24 publications

(11 citation statements)

References 75 publications

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“…He evaluated forty-eight PTFs that required particle size distribution, organic matter and organic carbon contents and stated that the functions depending on the organic matter or organic carbon as inputs were characterised by the best performances. What is more, the relationship between soil bulk density and organic matter has been confirmed in many studies, therefore PTFs based on these parameters are commonly used in environmental research [ 15 , 40 ]. It is also well established in soil science that the general trend of the linear correlation between the organic matter or organic carbon content and the bulk density is negative: with the increase in the amount of organic matter in the soil, bulk density decreases, for example [ 41 , 42 , 43 , 44 ].…”

Section: Resultsmentioning

confidence: 99%

Pedotransfer Functions for Estimating Soil Bulk Density Using Image Analysis of Soil Structure

Bryk

Kołodziej

2023

Sensors

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Soil bulk density is one of the most important soil properties. When bulk density cannot be measured by direct laboratory methods, prediction methods are used, e.g., pedotransfer functions (PTFs). However, existing PTFs have not yet incorporated information on soil structure although it determines soil bulk density. We aimed therefore at development of new PTFs for predicting soil bulk density using data on soil macrostructure obtained from image analysis. In the laboratory soil bulk density (BD), texture and total organic carbon were measured. On the basis of image analysis, soil macroporosity was evaluated to calculate bulk density by image analysis (BDim) and number of macropore cross-sections of diameter ≥5 mm was determined and classified (MP5). Then, we created PTFs that involve soil structure parameters, in the form BD~BDim + MP5 or BD~BDim. We also compared the proposed PTFs with selected existing ones. The proposed PTFs had mean prediction error from 0 to −0.02 Mg m−3, modelling efficiency of 0.17–0.39 and prediction coefficient of determination of 0.35–0.41. The proposed PTFs including MP5 better predicted boundary BDs, although the intermediate BD values were more scattered than for the existing PTFs. The observed relationships indicated the usefulness of image analysis data for assessing soil bulk density which enabled to develop new PTFs. The proposed models allow to obtain the bulk density when only images of the soil structure are available, without any other data.

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Section: Resultsmentioning

confidence: 99%

Pedotransfer Functions for Estimating Soil Bulk Density Using Image Analysis of Soil Structure

Bryk

Kołodziej

2023

Sensors

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“…The Alento River Catchment (ARC) is located in the region of Campania in southern Italy (Nasta et al, 2020a) (Figure 1) and forms part of the TERENO (TERrestrial ENvironmental Observatories) long-term ecosystem infrastructure network (Bogena et al, 2012). For the purposes of the present study, we selected two sub-catchments, namely MFC2 and GOR1, located in the Upper Alento River Catchment (UARC), which is a hilly upper part of ARC, with a drainage area of ∼102 km 2 and delimited downstream by the Piano della Rocca earthen dam (Nasta et al, 2017).…”

Section: Site Descriptions and Monitoring Devicesmentioning

confidence: 99%

Integrating Invasive and Non-invasive Monitoring Sensors to Detect Field-Scale Soil Hydrological Behavior

et al. 2020

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“…Nowadays the term PTF has a much wider meaning than in the past and, generally speaking, refers to a way of obtaining difficult-to-retrieve model parameters by transferring knowledge on more easily measurable properties. The downside of a PTF is that it should be considered as strictly valid only within the local area where it was developed because many studies have demonstrated that the accuracy and precision of a PTF can decrease even significantly when it is applied in another environment (e.g., [37]). Instead of developing a new PTF for predicting the soil water retention functions in a certain area, Romano and Palladino [38] put forward the idea that an already established PTF can be locally calibrated by using specific terrain attributes and showed that this procedure can at least reduce the prediction bias within a reasonable value for practical applications.…”

Section: Simplified Estimation Of the Soil Hydraulic Characteristics mentioning

confidence: 99%

Intertwining Observations and Predictions in Vadose Zone Hydrology: A Review of Selected Studies

Romano

2020

Water

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Observing state variables, fluxes, and key properties in terrestrial ecosystems should not be seen as disjointed, but rather as fruitfully complementary to ecosystem dynamics modeling. This intertwined view should also take the organization of the monitoring equipment into due account. This review paper explores the value of the interplay between observations and predictions by presenting and discussing some selected studies dealing with vadose zone hydrology. I argue for an advanced vision in carrying out these two tasks to tackle the issues of ecosystem services and general environmental challenges more effectively. There is a recognized need to set up networks of critical zone observatories in which strategies are developed and tested that combine different measurement techniques with the use of models of different complexity.

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Evaluating pedotransfer functions for predicting soil bulk density using hierarchical mapping information in Campania, Italy

Cited by 24 publications

References 75 publications

Pedotransfer Functions for Estimating Soil Bulk Density Using Image Analysis of Soil Structure

Pedotransfer Functions for Estimating Soil Bulk Density Using Image Analysis of Soil Structure

Integrating Invasive and Non-invasive Monitoring Sensors to Detect Field-Scale Soil Hydrological Behavior

Intertwining Observations and Predictions in Vadose Zone Hydrology: A Review of Selected Studies

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