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Revista Brasileira de Ciência do Solo

On-line version ISSN 1806-9657

Rev. Bras. Ciênc. Solo vol.43  Viçosa  2019  Epub June 19, 2019

http://dx.doi.org/10.1590/18069657rbcs20180121 

Division – Soil In Space and Time

Commission – Soil Survey and Classification

Field Description and Identification of Diagnostic Qualifiers for Urban Soils in Brazil

Jéssica Rafaela da Costa(1) 
http://orcid.org/0000-0002-4636-2010

Fabrício de Araújo Pedron(2)  * 
http://orcid.org/0000-0002-5756-0688

Ricardo Simão Diniz Dalmolin(2) 
http://orcid.org/0000-0002-8834-9869

Ricardo Bergamo Schenato(2) 
http://orcid.org/0000-0003-4268-7691

(1) Universidade de São Paulo, Departamento de Geografia, Programa de Pós-Graduação em Geografia Física, São Paulo, São Paulo, Brasil.

(2) Universidade Federal de Santa Maria, Departamento de Solos, Santa Maria, Rio Grande do Sul, Brasil.


ABSTRACT

Human activities often alter soils found in urban areas. These alterations affect their environmental functions and potential for use. However, soils from urban areas in Brazil have not been surveyed and identified, which can pose a technical problem for the development of the city. Considering the importance of urban environments and their soils, this study aimed to evaluate the environmental and morphological characteristics and the physical properties of urban soils in Santa Maria, Rio Grande do Sul, Brazil. The purpose was then to organize a protocol for describing urban soils and to identify diagnostic qualifiers to subsidize establishment of an order that allows proper classification of these soils in the Brazilian Soil Classification System. The protocol containing general and environmental notes and morphological notes and qualifiers was organized based on the experience of this study and the relevant literature. The environmental, morphological, and physical analyses carried out supported interpretation of the urban soils of Santa Maria, their classification in the World Reference Base for Soil Resources system, and identification of diagnostic qualifiers proposed for the Brazilian Soil Classification System. The protocol tested in this study was adequate for data collection in the field. Soils had high variation in layer thickness, particle size composition, color, bulk density, saturated hydraulic conductivity, penetration resistance, stoniness, and the presence of artifacts. Considering the establishment of a Brazilian taxonomy for urban soils, the field data led to the proposal for new qualifiers, such as Saprolitic (residual saprolite material), Impervic (sealed/impermeable layer), Multigranic (layers with contrasting textures), Stonic (layers with stoniness), and Saprorockic (layers constituted of transported saprolite), which can be used as diagnostic attributes in the Brazilian Soil Classification System and even contribute to improvement of the order of Technosols in the World Reference Base For Soil Resources system.

Key words: Anthrosols; Technosols; diagnostic criteria; field protocol

INTRODUCTION

Human influence on the environment can be identified in several places of human occupation and soil is one of the main sources with a record of anthropogenic activities, especially those under urban environments, whose attributes have been described in recent years by several authors, such as Jim (1998) , Morel and De Kimpe (1998) , Pedron et al. (2004) , Greinert (2015) , Gorbov (2016) , and Zalasiewicz (2017) . Urban soils are those found in urban areas, formed from changes imposed by the dynamics of cities and that perform typically urban functions (Azevedo et al., 2004; Pedron et al., 2004 ), even though we can also find natural soil (formed without human influence) in those areas. Urban and suburban areas in Brazil are defined by local legislation and are the space where urban structures are developed.

Anthropogenic materials, technically called “artifacts”, found in urban soils significantly change the physical, chemical, and biological properties of these soils ( Pouyat et al., 2010 ) and their morphology ( Joimel et al., 2016 ). The most common and critical modifications in urban soils are related to increased bulk density, promoted by compaction ( Schueler, 2000 ), and changes in texture, porosity, infiltration, and water retention ( Rokia et al., 2014 ).

The methods of soil description and collection are consolidated for natural environments ( Santos et al., 2015 ), whose soil characterization is based on profile description (sequence and depth of horizons, textural class, color, structure, special features, etc.), sample collection, laboratory analysis (chemical and physical analysis), and data interpretation. However, when it comes to urban soils significantly altered by human activities, there is a lack of information (or field protocol) that guides technicians in this work ( Pedron et al., 2007 ), as well as a lack of a Brazilian taxonomic classification to characterize these specific environments. The few studies on this subject in Brazil have been carried out with adaptations of the procedures used for natural soils, without standardization that would allow qualification of the data and later comparison among the studies.

The lack of taxonomic classification affects the progress of studies in disturbed areas ( Pedron et al., 2007 ). Moreover, a new order describing urban soils in the SiBCS is justified, because their functions and services are altered due to the nature of artifacts that can be hazardous to human and animal health and that weather differently. Their internal structure, fertility, water movement, strength, and carbon storage are different from natural soils.

Several national soil taxonomic classification systems have a specific order for classifying urban soils. The international World Reference Base for Soil Resources-WRB system ( IUSS Working Group WRB, 2015 ) has the order of Technosols, in which urban soils are classified based on attributes organized into qualifiers. In Brazil, the order of Anthroposols was proposed by Curcio et al. (2004) to identify soils modified by human actions, including urban soils, but this was not implemented in the Brazilian Soil Classification System (SiBCS); thus, its present edition ( Santos et al., 2018 ) does not provide support for urban soils.

The difficulty of creating a taxonomic classification for urban land stems from a wide range of changes already mentioned for the soils in these environments. The changes in urban soils favor a diversity of properties that do not obey a natural order and frequently do not exhibit spatial dependence. In addition, many technicians from different areas require specific information about the soils in urban environments, which makes it difficult to define the most appropriate attributes to organize a taxonomic classification ( Pedron et al., 2006 ). In this context, this study aimed to evaluate the environmental, morphological, and physical properties of urban soils in Santa Maria, Rio Grande do Sul, Brazil, for the purpose of organizing a protocol to describe urban soils in the field and to identify diagnostic qualifiers to subsidize an order that allows appropriate classification of these soils in the SiBCS.

MATERIALS AND METHODS

Study area

The study was carried out in the urban perimeter (urban and suburban areas) of Santa Maria, Rio Grande do Sul, Brazil ( Figure 1 ), where 12 soil profiles were described and sampled. The soil profiles were selected from the already existing urban soil survey of Santa Maria ( Pedron et al., 2008 ), considering their representativeness (type of transport/deposition and nature of artifacts). One of the profiles was collected outside the urban perimeter, where the old municipal garbage landfill is located.

Figure 1 Location of soil profiles evaluated within the urban area of Santa Maria, Rio Grande do Sul State, Brazil. 

The city of Santa Maria began as a military camp in 1797 and became an officially recognized city in 1876 ( Marchiori and Noal Filho, 2009 ). It is regionally known for its universities, colleges, and medical centers and nationally known for its military installations. All these activities express the dynamics of Brazilian urbanization in recent decades, concentrating 93 % of its 280 thousand inhabitants (estimated in 2018) in the urban perimeter ( IBGE, 2019 ). The city is located in the middle of the state of Rio Grande do Sul, the most southern state. The entire urban perimeter has sedimentary rocks, such as sandstones and siltstones, with an elevation between 100-250 m a.s.l. The northern part also has volcanic rocks such as basalt and rhyolite, with elevation ranging from 200-450 m a.s.l. ( Sartori, 2009 ). The surface slope ranges from 0 to 25 % in the sedimentary fields and from 20 to 85 % in the volcanic fields. The local climate is humid subtropical, classified as Cfa by the Köppen classification system. The average annual temperature and rainfall are 19.2 °C and 1,708 mm, respectively ( Maluf, 2000 ).

Protocol for describing urban soils

Due to the lack of standard procedures for the description and collection of urban soils, which are generally affected by anthropogenic alterations, this study proposed the organization of a protocol for describing urban soils ( Table 1 ). The proposal was based on adaptations in the procedures found in the Manual of Description and Collection of Soils ( Santos et al., 2015 ), Pedology Technical Manual ( IBGE, 2015 ), SiBCS ( Santos et al., 2018 ), all of them designed for natural soils, where attributes also important for an urban situation were used, for example, color, texture, structure, depth of soil layer, and percentage of coarse fragments. The studies of Curcio et al. (2004) and Santos Junior and Lima (2012) were also taken into account. The diagnostic qualifiers were drawn from the WRB system ( IUSS Working Group WRB, 2015 ) and some were identified in fieldwork. The spelling of the qualifiers followed the WRB convention. It is important to state that the idea of this research is primarily to identify the qualifiers (diagnostic attributes), contributing to the establishment of a future order in the SiBCS. The authors do not intend to organize the qualifiers into a principal or supplementary category as in the WRB system.

Table 1 Protocol for describing urban soils 

GENERAL AND ENVIRONMENTAL NOTES(1)
Project: Persons Responsible:
Date: Slope gradient: Penetration resistance
Profile No.: Relief: Depth 1st 2nd 3rd 4th 5th
Described by: Natural soil of the area: 0.10 m
Drainage: 0.20 m
Location: GPS coordinates:
Erosion: % of surface fragment:
General profile characterization (2) Urban land use (3)
Natural soil profile Urban agriculture
Natural soil profile with artifacts Urban construction
Natural soil profile with outside transported material Residue disposal
Deposition of outside transported materials Permanent preservation
Deposition of outside transported materials with addition of artifacts Exploitation of natural resources
Removed soil Soil deposition area
Removed soil with deposition of outside transported materials Notes:
Removed soil with addition of artifacts
Removed soil with deposition of outside transported materials and addition of artifacts
Mobilized soil
Mobilized soil with deposition of outside transported materials
Mobilized soil with addition of artifacts
Mobilized soil with deposition of outside transported materials and addition of artifacts
Morphological qualifiers (4)
Ekranic Leptic Siltic Relictgleyic Impervic
Linic Reductic Loamic Archaic Stonic
Urbic Hyperskeletic Clayic Artifact Saprorockic
Spolic Transportic Multigranic Hyperartifact
Garbic Saprolitic Densic Skeletic
Isolatic Arenic Gleyic Stagnic
MORPHOLOGICAL NOTES (frame for individual layer) (5)
Layer: Depth (cm): Root ( )Yes ( )No Porosity: visible pores ( )Yes ( )No
Moist color: ( ) mosaic color Mottle: ( )No ( )Yes Moist color:
Transition between layers: Quantity: ( )Few ( )Common ( )Many
Distinctness: ( )Abrupt ( )Clear ( )Gradual ( )Diffuse Size: ( )Fine ( )Medium ( )Coarse
Topography: ( )Smooth ( )Rolling ( )Irregular ( )Broken Number of density samples:
Struture (shape) : ( )Columnar ( )Prismatic ( )Angular blocky ( )Subangular blocky ( )Granular ( )Platy ( )Massive ( )Single Grain
Grade: ( )Structureless ( )Weak ( )Moderate ( )Strong
Size: ( )Extremely coarse ( )Very coarse ( )Coarse ( )Medium ( )Fine ( )Very fine
Texture: ( )Sandy ( )Clayey ( )Very clayey ( )Silty ( )Loamy
Rock fragments: ( )Yes ( )No Kind: ( )Gravel ( )Cobbles ( )Stones ( )Boulders
Shape: ( )Angular ( )Rounded ( )Well rounded
Consistence:
Dry: ( )Loose ( )Soft ( )Slightly hard ( )Hard ( )Very hard ( )Extremely hard
Moist: ( )Loose ( )Very friable ( )Friable ( )Firm ( )Very firm ( )Extremely firm
Wet:
Plasticity - ( )Nonplastic ( )Slightly plastic ( )Plastic ( )Very plastic
Stickiness - ( )Nonsticky ( )Slightly sticky ( )Sticky ( )Very sticky
Artifacts (6) :
Material % Material % Material % Material % Others:
( )Plaster ( )Glass ( )Rubber ( )Wood
( )Cloth ( )Concrete ( )Asphalt ( )Stones
( )Paper ( )Plastic ( )Brick
( )Ceramic ( )Styrofoam ( )Metal

(1) Based on the Manual of Description and Collection of Soils ( Santos et al., 2015 ), Pedology Technical Manual: Practical Field Guide ( IBGE, 2015 ), SiBCS ( Santos et al., 2018 ). (2) Based on Curcio et al. (2004) and Santos Junior and Lima (2012). (3) Based on the experience of this study. (4) Based on the WRB system ( IUSS Working Group WRB, 2015 ) and the experience of this study. (5) Based on the Manual of Description and Collection of Soils ( Santos et al., 2015 ), Pedology Technical Manual: Practical Field Guide ( IBGE, 2015 ), SiBCS ( Santos et al., 2018 ). (6) Based on the experience of this study.

The designation of “layers” rather than “horizons” for subdivision of the soil profiles was considered more suitable, due to the constant anthropogenic interferences that usually alter the pedogenetic processes or even to the absence of these processes in urban environments ( Yuan et al., 2008 ; Rokia et al., 2014 ). Layers in the soil profiles were mainly identified/separated through the use of the following criteria: color, texture, and presence of artifacts (type and volume). The attribute “mosaic color” was added to describe material with three or more colors, because the mixture of materials may lead to absence of a predominant matrix.

Determination of the following physical properties was performed to complement the morphological characterization of the soils: saturated hydraulic conductivity (Ks), microporosity (Mip), macroporosity (Map), total porosity (TP), bulk density (BD), penetration resistance (PR), and particle size analysis

In order to determine the Ks, Mip, Map, TP, and BD, undisturbed samples were collected on the surface of the profile with volumetric rings (85 cm3), according to Teixeira et al. (2017) ; a Stolf impact penetrometer and the Dutch formula were used to obtain the results (Stolf, 1991). The particle size determination of the fine earth (clay, silt, and sand) was performed with NaOH 1 mol L-1 dispersant by the pipette method, according to Teixeira et al. (2017) . Quantification of the coarse fraction (>2 mm) was performed through dry sieving and manual separation for identification of the components and determination of the percentile in relation to the total material collected. In the coarse fraction, the anthropogenic materials (artifacts) were counted.

The soil profiles were classified in the WRB system ( IUSS Working Group WRB, 2015 ) and the data were evaluated for the purpose of identifying new diagnostic qualifiers that can contribute to establishment of an order in SiBCS that supports urban soils.

RESULTS

General and Morphological Characterization

The anthropogenic alterations observed in the 12 soil profiles evaluated ( Figures 2 and 3 ) show that the soils analyzed lost their natural properties. The alterations promoted in the environment by human actions are expressed in different properties, such as the existence of well-demarcated layers in soils 3, 7, 10, and 12, in which there is an abrupt change between the layers, characterized by the different nature of their constituents.

Figure 2 Soil profiles and landscapes (1 to 6) in the urban area of Santa Maria, Rio Grande do Sul State, Brazil. 

Figure 3 Soil profiles and landscapes (7 to 12) in the urban area of Santa Maria, Rio Grande do Sul State, Brazil. 

Morphological variability of soils occurs in a short distance, as was observed in the comparison between soil 1 and 2, 15 meters distant from each other, and is related to land use in the urban environment. The urban land use class that was most predominant was “urban construction” (soils 1, 2, 3, 4, 6, 9, and 12). In addition, organic and inorganic waste disposal areas (soils 7, 8, 10, and 11) and an area of exploitation of natural resources were identified (soil 5). In the selection of the soil profile areas in the urban soil survey of the city and the field trips made during the study, we could not find altered soils with the following land uses: soil deposition area, urban agriculture area, and permanent preservation area, because most of those areas in Santa Maria still maintain a natural soil cover.

Soils formed from deposition of outside transported materials and addition of artifacts ( Table 2 ) were predominant, with nine profiles evaluated. Removed soil and exposure of saprolite material was the second most frequent condition, with two profiles evaluated.

Table 2 Morphological condition of the 12 profiles of urban soils from Santa Maria, Rio Grande do Sul State, Brazil 

Soil profile conditions Profile number
Profile of natural soil with addition of transported material and artifacts 9
Profile with deposition of outside transported materials and addition of artifacts 1, 2, 3, 4, 7, 8, 10, 11, 12
Profile with removed soil 5, 6

The transition between the layers was predominantly abrupt, considering not only color as an indicator but also texture ( Table 3 ). Soil 7 was constructed by deposition of soil and saprolite materials and artifacts that made it difficult to identify the predominant color of the layer. That condition was indicated in the protocol as “mosaic color”. The soils had predominantly sticky and plastic consistency and massive and block structure, which were generally strongly expressed. It was only possible to identify effective depth in soils 3, 8, and 9. In the other soils, the average 1.5 m thickness sampled was not enough to expose the original material.

Table 3 Morphology of urban soil profiles in Santa Maria, Rio Grande do Sul State, Brazil 

Soils Layers Moist color Transition Depth Wet consistency Structure
m
1 1 - abr/cle 0.00-0.10 - -
2 5YR 6/2 abr/cle 0.10-0.25 - -
3 5YR 3/1 abr/cle 0.25-0.80 plt/sti mas/pla
4 5YR 3/1 - 0.80-1.20+ plt/sti mas/pla
2 1 5YR 2.5/2 abr/irr 0.00-0.27 - ang/sang
2 10YR 3/6 abr/irr 0.27-0.45 plt/sti mas
3 5YR 4/6 abr/irr 0.45-0.70 plt/sti mas
4 5YR 4/6 - 0.70-1.20+ plt/sti mas
3 1 2.5YR 2,5/4 abr/irr 0.00-0.40/0.50 plt/sti sang
2 2.5YR 3/2 grd/smo 0.40/0.50-0.70/0.80 plt/sti ang/sang
3 2.5YR 3/2 grd/smo 0.70/0.80-1.05 plt/sti ang
4 5YR 6/2 grd/smo 1.05-1.20 plt/sti mas
5 2.5YR 5/6 - 1.20+ plt/sti mas
4 1 - - 0.00-0.05 - -
2 - - 0.05-0.30 - -
3 2.5YR 3/6 abr/smo 0.30-0.55 slplt/slsti mas
4 2.5YR 4/4 abr/smo 0.55-0.90 slplt/slsti mas
5 2.5YR 3/6 - 0.90-1.50+ slplt/slsti mas
5 1 5YR 4/6 abr/irr 0.00-1.10 noplt/slsti mas
2 5YR 5/4 - 1.10+ noplt/slsti mas
6 1 5YR 4/4 abr/smo 0.00-0.10 plt/sti sang
2 2YR 4/6 - 0.10-1.50 plt/sti mas
7 1 5YR 3/3 abr/wav 0.00-0.40/0.70 plt/nosti mas
2 mosaic abr/wav 0.40/0.70-0.75/0.90 plt/nosti mas
3 mosaic - 0.75/0.90-1.10 plt/nosti mas
8 1 10YR 4/4 abr/smo 0.00-0.43 plt/sti ang/sang
2 2.5YR 3/2 cle/smo 0.43-0.62 noplt/nosti ang
3 2.5YR 3/2 cle/smo 0.62-0.95 noplt/nosti ang
4 2.5YR 3/4 cle/smo 0.95-1.21 slplt/slsti ang
5 2.5YR 4/4 - 1.21-1.50+ slplt/slsti ang/sang
9 1 5YR 2.5/2 abr/smo 0.00-0.20 slplt/slsti pla/mas
2 2.5YR 3/2 grd/smo 0.20-0.40 slplt/slsti ang
3 2.5YR 2.5/4 grd/smo 0.40-0.50 plt/sti ang/sang
4 2.5YR 2.5/4 grd/smo 0.50-0.62 plt/sti ang
5 2.5YR 2.5/4 grd/smo 0.62-0.80 plt/sti ang
6 2.5YR 2.5/4 grd/smo 0.80-1.05 plt/sti ang
7 2.5YR 2.5/4 - 1.05-1.30+ plt/sti ang
Continue
Continuation
10 1 7.5YR 3/4 abr/smo 0.00-0.24 plt/sti mas
2 10YR 4/1 abr/smo 0.24-0.36 slplt/slsti mas
3 10YR 2/1 abr/smo 0.36-0.64 plt/sti mas
4 5YR 3/4 abr/smo 0.64-0.77 plt/sti mas
5 10YR 3/1 abr/smo 0.77-0.90 plt/sti mas
6 7.5YR 5/3 cle/irr 0.90-1.05 plt/sti mas
7 2.5YR 5/4 - 1.05-1.30 slplt/slsti mas
11 1 10YR 4/1 grd/irr. 0.00-0.40 slplt/slsti sang
2 10YR 4/1 - 0.40-1.50 slplt/slsti sang
12 1 2.5YR 3/1 abr/smo 0.00-0.20 plt/sti sang/gra
2 2.5YR 5/6 abr/smo 0.20-0.40 noplt/nosti sgra
3 2.5YR 4/1 - 0.40-0.80+ plt/sti sang/gra

abr = abrupt; irr = irregular; smo = smooth; wav = wavy; cle = clear; plt = plastic; slplt = slightly plastic; noplt = nonplastic; sti = sticky; slsti = slightly sticky; nosti = nonsticky; mas = massive; pla. = platy; gra. = granular; sang = subangular blocky; ang = angular blocky; sgra = single grain.

Soil layers have different compositions that were counted within the coarse fraction ( Table 4 ). The variability of particle size within each profile is high, as can be observed in profile 1, where the clay content ranges from 69 g kg-1 in layer 2 to 393 g kg-1 in layer 4. The percentage of the coarse fraction also varied within each profile. The main coarse fragments found in the soils were rocks, saprolites, tiles, bricks, and concretes. Industrialized materials like plastics and glass were only significant in soil 11, located in the former municipal landfill area.

Table 4 Particle size distribution and composition of the coarse fragments in the urban soils of Santa Maria, Rio Grande do Sul State, Brazil 

Soils Layers Sand Clay Silt Coarse fragments Composition of the coarse fragments (artifacts)
----------------------- g kg-1 ------------------------ %
1 1 - - - 100 100 % asphalt
2 792 69 139 95 96 % stones; 4 % tile, brick, ceramic, concrete
3 176 339 485 49 92 % stones; 8 % tile, brick, ceramic, concrete
4 155 393 453 45 100 % saprolite
2 1 342 212 445 54 100 % stones
2 472 193 335 40 100 % stones
3 657 112 231 84 92 % stones; 7 % tile, brick, ceramic, concrete; 1 % saprolite
4 199 85 715 69 92 % saprolite with small stones; 8 % stones
3 1 361 192 447 42 97 % stones; 3 % plastic
2 191 287 522 40 100 % stones
3 41 568 390 62 100 % saprolite
4 56 219 725 69 100 % saprolite
5 92 125 783 74 100 % saprolite
4 1 - - - 100 96 % asphalt; 4 % stones
2 - - - 100 100 % stones
3 612 245 142 1 96 % stones; 4 % saprolite with small stones
4 565 274 161 1 73 % stones; 27 % saprolite with small stones
5 601 239 161 2 87 % stones; 13 % saprolite with small stones
5 1 669 143 188 1 100 % stones
2 692 128 180 3 100 % stones
6 1 196 133 671 35 98 % saprolite; 1 % plastic; 1 % glass
2 64 89 847 89 100 % saprolite
7 1 339 307 354 54 94 % saprolite; 5 % asphalt; 1 % charcoal
2 676 117 207 14 100 % stones
3 326 288 386 51 92 % saprolite; 5 % asphalt; 3 % stones
8 1 405 318 277 17 100 % stones
2 645 133 222 1 100 % stones
3 570 184 246 1 70 % stones; 30 % glass
4 456 300 243 3 100 % stones
5 375 418 207 1 100 % stones
9 1 356 386 259 49 55 % saprolite with stones; 17 % plaster; 25 % stones; 1 % tile, brick, ceramic, concrete; 1 % charcoal; 1 % plastic
2 384 183 433 2 100 % stones
3 327 289 384 1 100 % plastic and styrofoam
4 306 314 380 0 -
5 261 400 339 0 -
6 219 442 339 1 100 % saprolite
7 183 405 412 1 100 % saprolite
10 1 465 212 324 6 93 % saprolite; 7 % stones
2 603 281 117 0 -
3 160 276 564 14 100 % saprolite
4 458 195 347 29 56 % stones; 31 % saprolite; 13 % tile, brick, ceramic
5 442 219 340 11 72 % stones; 28 % saprolite
6 600 230 170 5 100 % saprolite
7 612 248 140 1 100 % saprolite
Continue
Continuation
11 1 507 187 306 28 88 % Stones; 11 % plastic; 1 % glass
2 502 197 301 65 52 % saprolite; 27 % stones; 12 % plastic; 1 % glass; 3 % tile, brick, ceramic, concrete; 5 % cloth
12 1 398 338 264 1 100 % stones
2 300 401 299 1 100 % stones
3 382 334 284 4 87 % stones; 8 % saprolite; 5 % tile, brick, ceramic, concrete

The coefficient of variation ( Table 5 ) was high for the coarse fraction (95.59 %), Ks (71.95 %), and PR (58.72 %). The amplitude of values (minimum and maximum) highlight the sand, silt, clay, coarse fraction, and PR. The values of standard deviation were higher for sand (164.69), silt (140.47), coarse fraction (278.74), and PR (230.29).

Table 5 Descriptive statistics of the physical data for the urban soils of Santa Maria, Rio Grande do Sul State, Brazil 

Soil properties(1) Medium Minimum Maximum Standard deviation Coefficient of variation
%
Sand (g kg-1) 399.07 41.46 792.03 164.69 41.27
Silt (g kg-1) 356.12 86.00 846.66 140.47 39.44
Clay (g kg-1) 244.88 69.01 568.44 81.23 33.17
Coarse fraction (g kg-1) 291.59 0.33 984.90 278.74 95.59
BD (Mg m-3)(2) 1.51 1.31 1.66 0.10 6.36
Ks (cm h-1)(2) 26.41 13.34 67.76 19.00 71.95
Mip (m3 m-3)(2) 0.41 0.38 0.44 0.01 3.62
Map (m3 m-3)(2) 0.28 0.13 0.36 0.06 20.89
TP (m3 m-3)(2) 0.13 0.06 0.25 0.05 37.01
PR (kgf cm-2)(3) 392.17 78.25 873.91 230.29 58.72

(1) Determined according to Teixeira et al. (2017) ; (2) Analyses performed on samples collected with a volumetric ring in the surface layer of the profiles: 2, 5, 6, 8 and 13; (3) Analysis performed on the surface layer of profiles 2, 3, 4, 5, 6 and 8.

Due to the nature of some soils, it was not possible to collect undisturbed samples, so determination of soil bulk density, hydraulic conductivity, microporosity, macroporosity, and total porosity was only possible in the surface layer of soils 2, 5, 6, 8, and 13, and penetration resistance was only possible in the surface layer of soils 2, 3, 4, 5, 6, and 8.

Soil Classification and Diagnostic Qualifiers

All soil profiles were classified in the reference group “Technosol” ( IUSS Working Group WRB, 2015 ). The data obtained in this study led to the proposal of the following qualifiers ( Table 6 ):

Table 6 Classification of urban soils according to the WRB ( IUSS Working Group WRB, 2015 ) considering only morphological and physical qualifiers 

Soils WRB classification Suggested qualifiers*
1 Urbic Ekranic Technosol (Densic, Relictgleyic, Skeletic) Impervic, Multigranic, Saprorockic
2 Urbic Technosol (Skeletic) Multigranic, Saprorockic
3 Urbic Technosol (Skeletic, Stagnic) Multigranic
4 Ekranic Technosol (Densic, Loamic) Impervic, Saprorockic
5 Technosol Saprolitic
6 Technosol Saprolitic
7 Urbic Technosol (Loamic) Saprorockic, Stonic
8 Technosol Multigranic, Saprorockic
9 Urbic Technosol (Densic) Multigrani, Saprorockic, Stonic
10 Technosol (Transportic) Saprorockic, Stonic
11 Garbic Urbic Technoso (Densic, Loamic) Saprorockic, Stonic
12 Technosol (Transportic) Multigranic, Saprorockic

* Qualifiers suggested from the data of the 12 profiles evaluated in this study.

Saprolitic – the presence of layers ≥0.50 m thick formed by residual saprolite material, exposed from the practice of field cuttings, starting within 0.50 m of the soil surface.

Multigranic – the presence of layers ≥0.20 m thick, within 1.00 m from the surface, with contrasting textures (clayey, silty, loamy, or sandy) due to mixing of materials in the same layer;

Stonic – the presence of layers ≥0.20 m thick, within 1.00 m from the surface, with stoniness ≥40 %;

Impervic – the presence of a sealed/impermeable layer within 1.00 m of the soil surface;

Saprorockic – the presence of layers ≥0.20 m thick, within 1.00 m from the surface, constituted of transported saprolite.

DISCUSSION

The urban soils of Santa Maria have some properties that differ from natural soils. Those differences, for example, type and volume of the artifacts introduced in the soil, bulk density, penetration resistance, sequence and thickness of layers, and the dynamics of profile construction, are essential data for taxonomic and technical interpretation of these soils.

The profiles of the urban soils analyzed, as a consequence of the addition of artefacts in the environment and the actions of turning over and cutting soils and deposition of soils from outside, exhibited different properties, as found in several other studies on this subject ( Séré et al., 2010 ; Gorbov, 2016 ), reinforcing the perception of the heterogeneity of urban soils. As in Hagan et al. (2012) , access to the urban soils was complicated in this study by the existence of continuous buildings and road networks.

The large variability in the number of layers and the thickness of these layers is quite visible, and very well defined boundaries occurred, as in soils 3, 7, 10, and 12. Variability in the number and thickness of the layers is also cited by Simón et al. (2018) in a study of Technosols developed in quarry dumps restored with marble sludge in Spain. The difficulty of identifying the total thickness of the altered soil profile affects the interpretation of the environmental fragility of the area. In the landfill sites, where the area was leveled, the mixing of materials and the formation of soil profiles with uneven characteristics occurs within a small space. In these cases, it is difficult to find a modal profile to characterize the area.

Environmental and morphological attributes used for characterization of natural soils are equally important for urban soils; however, the functionality of some is altered, such as color determination. In the urban sites, the color of the soil was difficult to describe, due to the great mixture of materials, as in the case of layer 1 of soil 7. This situation makes difficult to determine the predominant color, creating the condition of “mosaic color”. In low-disturbance environments, one of the utilities of color is indicating the pedogenetic processes (gleization, podsolization, plinthization, etc.) that occur in the area ( Campos et al., 2003 ). In urban soils, the colors indicate depositional differences, both of the time of the deposit and of the materials that constitute these deposits ( Obour et al., 2017 ).

Determination of texture and consistency can also be difficult in urban soils. Their determination demands direct handling of the soil by the tact method ( Santos et al., 2015 ). This sensory analysis may be impaired by the existence of anthropogenic materials that pose a risk to the technician, such as sharp, contaminated, or toxic objects.

Considerable changes in structure and texture from one layer to another were found, a situation well described and discussed by Hiller (2000) . Field descriptions indicated that abrupt changes in texture and structure are also common among the various packages of materials that may constitute the same layer, as in the layer 4 of soil 10. Annotation of this characteristic is important for the interpretation of soil functions. In a broad sense, sandy or loamy soils increase the propensity of the area to contamination, since they commonly facilitate hydraulic conductivity and contaminant percolation ( Basso and Kiang, 2017 ) that can reach recharge points of aquifers. The same happens when sandstone saprolite layers are exposed by cutting because they compose part of the local aquifer.

The lack of soil structure, indicated in the protocol by the term “massive structure”, found in soils 4, 6, and 10 ( Table 3 ), is a common feature in urban soils ( Lefort et al., 2006 ), affecting physical-chemical soil processes since it alters the circulation of water and gases in the environment ( Morel and De Kimpe, 1998 ).

The collection of undisturbed samples in urban soils is often limited. Although the volumetric ring method is the standard most used in Brazil for analysis of Ks, Mip, Map, TP, and BD, it is not recommended in many urban soils due to the frequent and abundant presence of coarse fragments or surface sealing. In these cases, other methods of collection should be used, such as the paraffin-shaped clod ( Teixeira et al., 2017 ), making the process more complicated and time-consuming.

Although penetrometer resistance data is not proper for classifying soils since resistance is a dynamic property, it is useful for supporting the interpretation of soil compaction. Use of the impact penetrometer was efficient, due to easy handling in the field, making its use possible in areas with a moderate quantity of coarse fragments/artefacts. The device has provided good results in both civil engineering and agronomy tasks ( Stolf, 1991 ). The results show that there is a variation of PR (with high standard deviation) among the urban soils of Santa Maria in the surface layer of the soil profiles. This situation may indicate soil compaction and limitation of the soil in performing environmental services such as plant development and rainwater retention.

The physical properties varied from values commonly found in agricultural and natural soils in a complex way. For example, the Ks had coefficients of variation (CV) higher than developed soils such as Ferralsols, but lower than shallow soils such as Leptosols/Regosols, whereas porosity can have a lower CV and BD a higher CV than Leptosols/Regosols ( Pedron et al., 2011 ). Compared to a Cambisol, the urban soils had the same CV for BD and a higher CV for sand, silt, clay. and TP ( Oliveira et al., 2013 ). Compared to other urban soils from the USA ( Pouyat et al., 2007 ), the CV was the same for clay, higher for sand, and lower for BD. Those variations indicate that the removal, accumulation, and mixing of materials to which urban soils are subjected results in complex layers not always more heterogeneous than agricultural or natural soils.

The international classification system used, the WRB for soil resources ( IUSS Working Group WRB, 2015 ), was able to classify all the altered urban soils in the Technosols reference group. However, for soils 5, 6, 8, 10, and 12, the interpretation was that their surface exposed saprolite or saprolite transported and deposited are considered artifact according to the WRB definition: (1) any substance (solid or even liquid) brought to the surface by human activity from a depth, where it was not influenced by surface processes, and deposited in an environment where it does not commonly occur, with properties substantially different from the environment in which it is placed; and (2) any substance that has substantially the same chemical and mineralogical properties as when first manufactured, modified, or excavated ( IUSS Working Group WRB, 2015 ).

Considering that they are anthropogenic soils typical of urban areas, we highlight their occurrence in Santa Maria, estimated in 20 % of the urban area, and the importance of the qualifier “Saprolitic” to respond to the case of soils 5 and 6 (in situ saprolite exposed by human land cuttings with ≥0.50 m thickness, starting within 0.50 m of the soil surface). These profiles have a sedimentary saprolite derived from sandstone (soil 5) and siltstone (soil 6), which are frequently used as deposition material in the urban area. Saprolite is a residual material at a different stage of alteration, generally with the structure of the parent rock and always susceptible to shovel excavation, being designated as a C or Cr horizon under natural conditions. It has significant water retention and does not allow root penetration, except through fractures that tend to be common ( Pedron et al., 2015 ).

Soils 8, 10, and 12 showed layers of mineral material originating from soils, and saprolites from other sites deposited on natural and altered soils. The layers of transported soils were classified as Transportic. The layers of transported saprolite could not be classified as Urbic (presence of rubble and refuse of human settlements), Spolic (presence of industrial waste such as mine spoil, dredgings, slag, ash, rubble, etc.) or Garbic (presence of organic waste) because they do not fit these definitions. It also could not be classified as Transportic since we understand that these materials are included in the definition of artifacts, as explained above. In this case, these layers require a new qualifier, and we propose the use of Saprorockic (presence of layers ≥0.20 m thick with transported saprolite).

Soils 7, 9, 10, and 11 were classified with the Stonic qualifier, suggested here to characterize the profiles where layers (≥0.20 m thick) with high content of stones (≥40 %) can be found within 1.00 m of the soil surface. This information is important because excessive stoniness of the soil can limit many urban activities, especially environmental services such as water retention and plant development ( Jim, 1998 ). Soils 1 and 4 were classified with the Impervic qualifier, which was suggested to indicate that the soil profile has a sealed layer within 1.00 m of its surface. The Ekranic qualifier used by WRB regarding the presence of a technic hard material within 0.05 m of the soil surface does not demand a sealed layer. A sealed layer can affect soil function in urban areas by altering water infiltration, water runoff, soil erosion, and urban flooding ( Armson et al., 2013 ). The sealing of urban soil is one of the most common and limiting problems in cities ( Greinert, 2015 ).

Considering the different qualifiers proposed, the need to evaluate a larger database for construction of a Brazilian taxonomy suitable for urban soils was evident. Although the dynamics of urban development in Brazil are not different from other countries, some particular cultural and environmental aspects are common. The small number of soil profiles described in urban areas in Brazil explains the difficulty in creating a taxonomic proposal. However, the qualifiers used in the WRB and those presented in this study were efficient in diagnosing the 12 altered soil profiles of Santa Maria. They are important not only to support future organization of an order within the SiBCS, but also to contribute to the improvement of the order of Technosols in the WRB system.

CONCLUSIONS

The protocol tested in this study proved to be adequate for the collection of environmental and morphological field data related to urban soils altered by human activities.

The data of the urban soils of Santa Maria showed property variations not considered in the reference group of Technosols (WRB system). The proposal of the Saprolitic, Impervic, Multigranic, Stonic, and Saprorockic diagnostic qualifiers may support improvement in the WRB and future establishment of a Brazilian taxonomy for urban soils.

The definition of a standard protocol to survey urban soil and the new qualifiers identified in the urban soil profiles of Santa Maria are successful products that demonstrate that this study achieved its objective.

ACKNOWLEDGMENTS

The authors would like to thank the Research Support Foundation of Rio Grande do Sul (FAPERGS), the Coordination of Superior Level Staff Improvement (CAPES), and the Brazilian Council for Scientific and Technological Development (CNPq) for funding this research project. The authors are also obliged to the anonymous reviewers and editors who contributed significantly to enhance this text.

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Received: June 04, 2018; Accepted: March 01, 2019

* Corresponding author: E-mail: fapedron@ufsm.br

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