Introduction
Soil water is a fundamental resource for the components of the
ecosystem; it plays a vital role in determining the functioning of
plants and other soil biota (Brevik et al., 2015). Soil physics is
largely related to the interaction between soil and water; therefore
the physical, chemical and biological processes that take place in
soil depend on the amount and composition of water (Brevik et al.,
2015). With this in mind, knowledge of the hydraulic properties of
soils is important in many scientific disciplines, from agriculture
to ecology, since the amount of water, and the strength by which it
is held by soil, represents the characteristics of soil behaviour and for the vegetation and all
other organisms' development.
Land use can significantly affect soil properties, such as bulk
density, saturated hydraulic conductivity, infiltration rate and
available soil water content (Haghighi et al., 2010), and it has
been shown to be one of the main factors controlling soil water
variability (Qui et al., 2001; Pan and Wang, 2009). Because soil
properties are the main factor controlling soil water variation
(Vachaud et al., 1985, Famiglietti et al, 1998; Hu et al., 2010),
land use could influence soil water variations by changing soil
properties (Gao et al, 2014). In recent studies, the effects of land
use on soil water variation have been investigated via statistical
analysis (Fu et al., 2003; Chen et al., 2007; Gross et al., 2008),
simulation, or physical-based models (Li et al., 2009). Gao et
al. (2014) demonstrate, through a study in a small catchment of the
Chinese Loess Plateau, that land use can lead to spatial variation
of soil water but has a negligible effect on soil water temporal
patterns.
Soil moisture influences soil behaviour; it takes an important role, for
example, in soil erosion. Antecedent soil moisture content, together with rainfall
intensity, slope steepness and land use/land cover are factors influencing
soil erosion and runoff (Ziadat and Taimeh, 2013). The effect of
antecedent soil water content on soil erosion
is still a matter of debate, as an opposing effect has been reported on
aggregate breakdown and seal formation (Vermang et al.,
2009). Wet
soils double the runoff coefficient and shorten the time to runoff, compared
with the same soil when dry (Li et al., 2011). Greater soil erosion was
observed during the wet season in Spain (Cerdà, 2002; Ziadat and Taimeh,
2013).
Soil water/moisture is also a key factor affecting vegetation
structure in a water-limited environment (Rodriguez-Iturbe et al.,
1999); in turn, vegetation exerts vital control on the entire water
balance (Rodriguez-Iturbe et al., 2001) via complex and mutually
interacting hydrological processes (Porporato et a., 2002; Gao et
al. 2014).
In this paper, the study of hydraulic properties of soil is
presented, by laboratory analysis, by using predictive models and by
studying soil vegetation cover.
Direct measurements of soil hydraulic properties are rarely
performed because they require lengthy and costly analysis; as an
alternative, analysis of existing databases of measured soil
hydraulic data may result in pedotransfer functions (PTFs)
(Wösten et al., 2001). These functions often prove to be good
predictors for missing soil hydraulic data. The PTFs show empirical
relationships between soil hydraulic properties and some more easily
measurable basic
soil properties such as texture, bulk density and organic carbon
content (Baker, 2008; Bouma and van Lanen, 1986; Pachepsky and
Rawls, 2004; Vereecken et al., 2010; Wösten et al., 2001). To
derive the PTFs, databases of soils from all over the world were
used. Generally soil databases emphasize soil taxonomy and provide
limited unsaturated soil hydraulic data. With this in mind, the
international Unsaturated Soil Database (UNSODA) (Leij et al., 1996)
and subsequently, the European database of soil hydraulic properties
(HYPRES) (Nemes et al., 2001a; Wösten et al., 1999; Wösten
and Lilly, 2004) were developed. Both these databases contain a
wealth of information about soil hydraulic data, measurement methods
and other relevant soil data (Nemes et al., 2001a).
The processing of the PTFs can be performed using computer programs such as
CalcPTF 3.0 (Guber and Pachepsky, 2010), ROSETTA (Schaap M.G., et al., 2001)
(which is available as stand-alone program and also as a part of the
simulation model HYDRUS 1D; Simunek, et al., 2008), SOILPAR (Acutis and
Donatelli, 2002) and SPAW (Saxton and Willey, 2006).
The relationship between volumetric water content and matric
potential is shown by the soil water retention curve, which allows
the derivation of available water for plants by comparing the water
content at different applied suction (negative pressure) values.
In recent decades the increase in human population and human
activity has resulted in an ongoing depletion of soil resources, to
the point that the authorities have included the recovery of
degraded areas in their priorities. The lower ability to make water
available for plants and microorganisms is
characteristic of a degraded soil; thus,
in order to carry out soil restoration, it is important to know its
hydraulic properties.
In this work a degraded cover soil of a landfill located in Piacenza
was studied. The soil used to closed the landfill is a natural soil,
which comes from different areas near Piacenza, and it can be
classified as an Anthrosol (FAO World Reference Base for Soil
Resources): a soil formed or profoundly modified through long-term
human activity, such as from addition of organic waste or household
waste, irrigation or cultivation. This soil has shown very low
fertility for more than 30 years; there is no chemical contamination
justifying its condition, so the soil can be described as a degraded
soil.
Recently the landfill soils and the vegetation were studied, and so
the site environmental quality is described, including the
relationship between soil chemical analysis and ecological
indicators (Manfredi et al., 2012), the floristic–vegetational
indexes (Giupponi et al., 2013b) and the presence and development of
Onopordum acanthium subsp. acanthium (Giupponi et al., 2013a). The
area is actually involved in a Life + project (Life 10
ENV/IT/000400 New Life, http://www.lifeplusecosistemi.eu),
which includes among its objectives the treatment of degraded soils
through an innovative reconstitution method to improve their
quality, and the restoration of the closed landfill.
Restoration of closed landfills is essential to minimize the adverse
effect on the environment and to render the landfills safe for
further use (Chen et al., 2015). A lot of studies on landfills can
be found in the literature – about root contamination by gas
(Gilman et al., 1982), methane production (Themelis and Ulloa,
2007), microbiological studies (Boeckx et al., 1996) and ecological
performance after the restoration of plant and animal communities
(Chen et al., 2015; Wong et al., 2015) – but nothing can be found
about hydrological properties of cover soil in relation to plant
coverage.
The study of the vegetation cover of an area can be very useful as a
tool to compare and corroborate the results of chemical and physical
analysis performed on soil. The integrated study of different
scientific disciplines in the description of an area is always
preferred in order to have as complete an overview as possible. The study of the relationship
between soil hydraulic properties and plant coverage, and the use of
plant communities to assess the soil quality is a very interesting
research field. This new way of studying an area can be applicable
not only in describing degraded areas, but also when applied in
other research fields, such as rural areas, road embankments,
mining, badlands or border areas.
Novara et al. (2011) demonstrate that an appropriate choice of cover
crops assists in very effective soil management in vineyards in
Sicily. A natural reforestation following a different land use on
the flood plain in the Dragonja sedimentation basins has resulted in
a change in sedimentation rate (Keesstra, 2007; Keesstra et al.,
2009). A study performed in a restoration program in South East New
Territories landfill in Hong Kong, between pioneer species and
native species – including the investigation of different planting
techniques, the use of different types of soil ameliorants and a
focus on understanding what factors are most important in the growth
of plants – provided valuable information for restoring subtropical
engineering landfills (Wong et al., 2015). The vegetation, climate
and environmental change have been used to explain the reasons of
the severe soil erosion in the Loess Plateau of China (Zhao et al.,
2013). Zornoza et al. (2015) use vegetation cover for the
development of an index to assess the state of human disturbances in
alpine grassland with different levels of degradation based on plant
cover, production, proportion of primary plant and height of the
plant. Studies of the vegetation biodiversity, together with
chemical and physical soil analyses and the testing of the
presence/abundance of soil microbes and soil fauna, are also used to
assess the soil quality in some farms in Iceland and Austria (van
Leeuwen et al., 2015).
Considering the importance of soil moisture and vegetation cover,
the aim of this work is to relate the hydraulic properties of
landfill soil with its vegetation, and to assess whether predictive
systems (PTFs) are suitable for predicting these data.
Materials and methods
Study area
The closed landfill of municipal solid waste of Borgotrebbia is
located in the territory of Piacenza (Po Valley, Italy, coordinates:
45∘03′58′′ N, 09∘39′06′′ E) at an altitude
of 60 m. It has an area of 200 000 m2 and is located along
the right bank of the Trebbia River near its confluence with the Po
River. Climatic data show that the average annual temperature is
13.3∘ C, while the average annual rainfall amounts to
778 mm, most of which is concentrated in the periods of March and
September.
The landfill was opened from 1972 to 1985 and then was closed and
covered with a layer, about 50 cm in depth, of different degraded
soils left to be spontaneously colonized by plants. The soils used
to close the landfill are loamy soils with a predominantly
multi-faceted structure; they have low porosity and, by their
nature, they are compact. Further compaction of the soil was induced
by compression, caused by operations carried out in order to close
the landfill so that the leakage of gas and infiltration by rain
could be avoided.
Soil
Physical-chemical analysis of the
soil
Eleven sampling points were chosen as being representative of the
closed landfill area after a preliminary study. Initially they were
sampled in the area at 51 points, following a grid division NE–SW,
NW–SE; and the distribution of the observed different vegetation
types – the plant communities differ in structure and floristic
composition according to the different environmental factors such
the type of soil. By statistical elaboration of the 51 chemical
analyses, 11 soils resulted in being the most representative of the
area.
The 11 soil samples were taken at 25 cm depth and chemical and
physical analyses were carried out based on the Methods of Soil
Chemical and Physical Analysis as described in the Official Gazette
of the Italian Republic: texture and grain size (Italian position
Method II.5 Suppl. Ord. G.U. no. 248/21.10.1999; international
position ISO 11277), primary and secondary structure, organic carbon
(Italian position Method VII.3, Suppl. Ord. G.U. no. 248/21.10.1999,
Walkley-Black,), salinity (Italian position Method IV.1 Suppl. Ord.
G.U. no. 248/21.10.1999, international position ISO 11265, aqueous
extract 5 : 1), total limestone (Italian position Method V.1,
Suppl. Ord. G.U. no. 248/21.10.1999, international position ISO
10693) and water potential (Italian position Method VIII.3, Suppl.
Ord. G.U. no. 173/02.09.1997, international position ISO/DIS 11274,
sand box and Richards plates; measurements performed on undisturbed
samples). The results of the physical–chemical analyses were used
as input for the elaboration of 18 different PTFs (Tables 1 and 2).
As the bulk and particle density of samples aren't measured, the
literature values for loamy soils were used: bulk density
1.3 g cm-3 and particle density 2.3 g cm-3.
Results of chemical and physical analyses performed on
soils. Legend: A.B.: angular blocky; Sa.B.: subangular blocky; G.:
granular; P.: platy; S.G.: single grain.
Sample
Organic
CaCO3
Electrical
Sand
Silt
Clay
Soil
Structure
carbon
conductivity
thickness
of soil
content
%
g kg-1
ds m-1
%
%
%
cm
1
1.94
130.2
0.197
21.9
12.3
65.8
55
A.B.–Sa.B.
2
4.13
147.7
0.212
17.5
12.9
69.6
30
G.–Sa.B.
3
4.14
190.4
0.152
27.9
12.3
59.8
60
G.–Sa.B.
4
1.67
38.5
0.232
11.5
14.7
73.8
30
Sa.B.–G.
5
1.04
134.8
0.167
12.2
12.4
75.4
62
P.
6
1.35
57.4
0.196
10.3
14.7
75
32
Sa.B.–G.
7
1.92
229.8
0.130
33.3
12.5
54.2
45
S.G.–Sa.B.
8
4.10
266.7
0.288
16.7
16.8
66.5
47
A.B.–G.
9
2.35
138.1
0.252
25
12.3
62.7
47
A.B.–Sa.B.
10
2.68
59.9
0.136
18
9.8
72.2
50
Sa.B.–A.B.
11
3.63
128.9
0.248
17.8
12.3
69.9
40
Sa.B.–G.
Volumetric water content (θ %) from instrumental analysis
at different suction values.
Sample
Suction (-kPa)
0.10
0.25
1
3
6
10
33
1500
1
49.45
43.58
39.21
37.23
35.88
34.54
27.60
24.66
2
48.75
44.27
41.05
38.62
37.61
36.98
28.46
27.91
3
47.77
45.12
41.83
37.00
34.80
33.83
25.71
13.57
4
49.42
45.87
40.40
35.46
32.77
31.13
22.91
22.32
5
44.09
41.77
37.31
33.07
31.20
30.01
21.73
18.92
6
47.46
45.06
41.60
38.08
36.02
34.85
25.29
14.59
7
44.55
40.98
38.32
33.25
30.97
29.48
19.37
10.86
8
45.63
45.15
44.21
43.46
42.71
42.30
37.02
26.50
9
51.01
47.71
42.76
37.37
33.58
30.55
23.27
20.84
10
54.43
52.41
47.81
41.39
38.38
35.18
26.08
14.02
11
52.16
43.94
39.52
37.90
37.27
36.78
29.09
25.69
Water retention models
Most mathematical models that describe soil hydrologic behaviour are
based on non-linear relationships between the volumetric water
content in the soil, θ, the suction applied by the soil,
h, and the hydraulic conductivity (Hillel, 1998); the functions
θ(h) and K(h) describe the hydraulic properties of a
soil through a parametric equation (Leij et al., 1997). Some
predictive methods for estimating hydraulic conductivity are based
on direct observations of water content in the soil measured at
different values of suction (Romano and Palladino, 2002). To
compensate for all the cases in which it is not possible to measure
it, a group of functions called pedotransfer functions (PTFs) has
been developed. PTFs correlate the water retention and hydraulic
conductivity with some easily measurable chemical and physical
properties of the soil such as texture, density, porosity, and
organic carbon content (Elsenbeer, 2001; Tietje and Hennings, 1996;
Tapkenhinrichs and Tietje, 1993). Most PTFs are regression equations
that are derived from data collected during specific campaigns and
are reliable for describing the soil hydraulic properties (Romano
and Palladino, 2002).
In this work, the measured water retention curves were compared with
those obtained using 17 PTFs proposed in the literature that are
based on databases of soils distributed worldwide following two
models: Brooks and Corey (1964) and van Genuchten (1980), (Rawls et
al., 1998, 1992, 1982a; Saxton and Rawls, 2006; Saxton et al., 1986;
Tanij, 1990).
The functions used to describe water retention properties are the
following: the van Genuchten (1980) water retention equation, as in
θ-θrθs-θr=11+αhnm
and the Brooks and Corey (1964) equation:
θ-θrϕ-θr=hhbλ,h>hb1,h≤hb,
where θ is the volumetric soil water content
(cm3 cm-3); θr is the residual soil water
content (cm3 cm-3); θs is the saturated
soil water content, (cm3 cm-3); ϕ is the soil
porosity, (cm3 cm-3); λ is the pore size
distribution index (dimensionless); h is the capillary pressure
(cm); hb is the air-entry pressure (cm); α is the
parameter of the van Genuchten equation, corresponding approximately
to the inverse of the air-entry value, (cm-1); m,n are the
empirical shape-defining parameters in the van Genuchten equation,
(dimensionless).
The values of the parameters (θ, θr,
θs, ϕ, λ, hb, α, m,n) are predicted by PTFs, which are developed from the measured
data set (Wösten et al., 2001).
In this study the processing of the PTFs was performed using the
program CalcPTF 3.0 (Guber and Pachepsky, 2010). This contains a
class of PTFs generated from the HYPRES database; see Table 3.
CalcPTF 3.0 is a computer program developed to calculate PTFs in order
to estimate parameters of the Brooks and Corey model and the
van Genuchten model. The inputs used in this program are: soil
texture, organic carbon content, bulk density and particle density.
Authors and localization of database and model used for the
different PTFs. Legend: VG represents van Genuchten, BC represents
Brooks–Corey.
PTF
Region
Model
HYPRES
Europe
VG
Saxton et al. (1986)
USA, nationwide
BC
Campbell and Shiosawa (1992)
None particular
BC
Rawls and Brakensiek (1985)
USA, nationwide
BC
Williams et al. (1992)
Australia
BC
Williams et al. (1992)
Australia
BC
Oosterveld and Chang (1980)
Canada, Alberta
BC
Mayr and Jarvice (1999)
UK
BC
Wösten et al. (1999)
Europe
VG
Varallyay et al. (1982)
Hungary
VG
Vereecken et al. (1989)
Belgium
VG
Wösten et al. (1999)
Europe
VG
Tomasella and Hodnett (1998)
Brazil
VG
Rawls et al. (1982b)
USA, nationwide
VG
(corrected for OM according
to Nemes et al., 2009)
Gupta and Larson (1979)
Central USA
VG
Rajkai and Varallyay (1992)
Hungary
VG
Rawls et al. (1983)
USA, nationwide
VG
(corrected for OM according to
Nemes et al., 2009)
The database HYPRES (Hydraulic Properties of European Solis;
Wösten et al., 1999) draws together some basic soil information
and soil hydraulic data from which PTFs applicable to Europe can be
derived (Nemes et al., 2001b). Using the HYPRES database, two
different sets of PTFs were derived: class pedotransfer functions
and continuous pedotransfer functions. Class PTFs predict the
hydraulic characteristics for each of the five texture classes
(coarse: clay < 18 % and sand > 65 %,
18 % < clay < 35 % and
15 % < sand; medium: clay < 18 % and
15 % < sand < 65 %; medium fine:
clay < 35 % and sand < 15 %; fine:
35 % < clay < 60 %; very fine:
60 % < clay) and for two pedological classes within
them (topsoils and subsoils) plus an additional class which
encompassed the organic soil horizons. Continuous pedotransfer
functions can predict hydraulic properties from individual
measurements of soil texture, organic carbon content and bulk
density.
The goodness of the PTFs and their ability to describe the hydraulic
characteristics of the landfill coverage soils was calculated
through the root mean square error (RMSE) test based on the
difference between the values of volumetric content of water at
different suction values, measured and estimated, starting from the
following equation:
RMSE=1N∑i=1Nθi-θi∗2,
where N is the number of measurements; θi and θi*
is the volumetric water content (θ %), measured and
estimated.
The hydraulic data of the landfill cover soils obtained
instrumentally and through PTFs were also compared with those of a
reference soil. The reference soil chemical-physical properties are
chosen to describe a non-degraded natural soil with the same
texture, i.e. silt loam, with a bulk and particle density of respectively 1.3 and
2.3 g cm-3 of landfill soils but with an average organic carbon
content of 1 %, which is typical of Piacenza natural soils, well
structured and with a depth of 1 m. The volumetric water content of
the reference soil at different suction values was calculated
through the arithmetic mean of the water contents from the 17 PTFs,
so it is possible to achieve an estimate of available water content.
Flora and vegetation
The vegetation data were collected by making up 52 phytosociological
relevés using the Zurich–Montpellier school method
(Braun-Blanquet, 1964). The sampling sites were selected to
summarize the vegetation of the whole area. Each relevé included
an area of 16 m2 (4 m × 4 m) and was georeferenced.
For each sampling site, the plant species present were listed and
their cover was estimated using the values of the Braun–Blanquet
conventional scale (r= sporadic species; += < 1 %, 1 = 1–5 %, 2 = 5–25 %,
3 = 25–50 %, 4 = 50–75 %, 5 = 75–100 %).
The relevés were periodically monitored from April to September
2012.
Pignatti (1982) was consulted for the identification of the species,
while the specific nomenclature is according to Conti et al. (2005).
In order to process the biological spectrum of the plant list, the
data concerning the biological form according to Raunkiaer (1934)
(therophytes – T: annual herbs; hemicryptophytes – H: perennial
herbs; geophytes – G: perennial herbs with underground storage
organs; chamaephytes – Ch: woody plants with buds at no more than
25 cm above the soil surface; phanerophytes – P: trees and shrubs
with buds over 25 cm above the soil surface) were taken from Romani
and Alessandrini (2001).
Landolt's F index (soil moisture) (Landolt, 1977), updated by
Landolt et al. (2010), provides a guide on the need of water by
plant species during their growth period. The F values range from
1 to 5 (1 is very dry, 1.5 is dry, 2 is moderately dry, 2.5 is
fresh, 3 is moderately moist, 3.5 is moist, 4 is very moist, 4.5 is
wet and 5 is flooded or submerged) and were attributed to all the
species, recorded in order, to obtain information on the degree of
humidity of the landfill soil cover. To each species was also
assigned its respective life strategy according to Grime (2001,
1979) (c describes competitive strategists, r describes ruderal
strategists and s describes stress-tolerant strategists); this
information was retrieved from Landolt et al. (2010), according to
the adjustments proposed by the author. Starting from the climate,
soil and vegetation data, reference crop evapotranspiration (ETo),
the total available moisture (TAM) and the readily available
moisture (RAM) were calculated using the CropWat 8.0 software
(©FAO 2009) according to Allen et
al. (1998) and Doorenbos and Kassam (1979).
Water retention curves of sampled soils.
![]()
Results
Soil
By the measurement of volumetric water content, it is possible to
describe the water retention curve for all of the samples. Table 2
shows the measured volumetric water contents at the different
suction values investigated and Fig. 1 shows their water retention
curves. The water retention curves, with the exception of sample 8,
display a similar trend. For suction values less than 10 kPa, the
values are not very different, while in the end part – when the
suction is high – there are some differences. The curve's slope
increases from 10 to 33 kPa due to the different water extractor
used – a sand box for 10 kPa and a Richards plate for 33 kPa.
Sample 5: actual (black) and PTF water retention curves;
the curves by Wösten et al. 1999 are highlighted.
![]()
As one of the study aims is to compare the landfill soil with a
natural reference soil, in the first part of the paper, sample 5 is
analysed. Sample 5 is the only landfill soil showing the same amount
of organic carbon as the reference one.
Matrix representing the result of the RMSE test – each
pixel for a combination of the soil's PTF and RMSE.
![]()
Results of the calculation of RMSE.
PTF
RMSE % (for samples)
1
2
3
4
5
6
7
8
9
10
11
HYPRES
4.6
4.2
3.6
5.5
6.2
3.2
5.3
2.3
4.5
3.7
4.4
Saxton et al. (1986)
5.9
6.3
3.2
6.7
6.8
4.0
4.5
5.6
6.0
5.6
6.2
Campbell and Shiosawa (1992)
3.7
3.6
2.8
5.7
6.0
4.6
4.8
2.4
4.7
5.2
3.9
Rawls and Brakensiek (1985)
5.4
5.9
2.3
6.0
5.9
3.4
2.9
5.5
4.9
5.0
5.9
Williams et al. (1992)
3.6
4.0
2.0
4.2
4.2
2.8
4.2
3.8
4.0
4.8
4.2
Williams et al. (1992)
4.5
5.0
2.7
5.0
5.0
2.7
3.0
3.5
4.5
4.8
5.0
Oosterveld and Chang (1980)
4.4
5.1
1.7
5.0
4.8
2.4
2.8
4.9
4.0
4.8
5.1
Mayr and Jarvice (1999)
14.5
16.0
12.7
12.6
11.2
13.2
10.0
18.9
12.6
14.5
15.6
Wösten et al. (1999)
3.7
5.7
1.9
5.7
5.6
3.2
4.5
5.4
4.0
4.8
4.4
Varallyay et al. (1982)
6.5
7.7
3.7
4.7
3.6
3.2
1.5
8.2
5.4
7.9
7.5
Vereecken et al. (1989)
4.8
4.7
3.1
7.5
6.4
5.5
5.2
2.0
5.0
4.4
4.7
Wösten et al. (1999)
4.7
4.3
3.0
5.2
5.7
2.6
4.6
3.2
4.5
4.2
4.5
Tomasella and Hodnett (1998)
13.6
15.2
12.2
17.5
19.4
16.8
12.4
13.1
12.4
12.1
14.8
Rawls et al. (1982b)∗
5.5
7.1
6.5
7.2
6.8
4.7
5.9
4.1
6.4
5.5
6.6
Gupta and Larson (1979)
8.3
9.2
8.4
11.5
12.5
10.3
9.6
6.3
8.9
7.8
8.9
Rajkai and Varallyay (1992)
9.8
7.3
8.8
12.2
14.5
11.6
12.4
4.2
10.5
9.4
8.0
Rawls et al. (1983)∗
4.7
5.4
4.6
6.1
5.6
3.6
4.8
2.7
5.5
5.3
5.3
∗ corrected for OM according to Nemes et
al. (2009).
Using sample 5 chemical–physical data as inputs of PTFs, the
sample 5 predictive water retention curve is compared with the
measured one. This comparison is shown in Fig. 2; in this Figure,
the curves by Wösten et al. (1999)(PTFs
applicable to Europe soils) are highlighted. From the comparison it
clearly emerges that for suction values lower than 100 kPa, all
PTFs except one overestimate the measured data, whereas for suction
values of 1500 kPa for 12 cases the measured value is higher than
the predicted one.
Comparison between sample 5 water retention curve and the
reference curve – described as the arithmetic mean of PTFs values.
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To identify which of the authors, and thus of the models, are more
accurate in describing the hydraulic behaviour of the landfill
soils, samples of chemical–physical data are used as inputs of
PTFs, so all water retention curves are developed and then the RMSE
test was conducted (Fig. 3, Table 4). It emerges that the curve by
Wösten al. (1999), showing a continuous pedotransfer function,
is the closest to the measured data. The results of this test and
the comparisons indicate a need to conduct studies to develop new
parameter values which are able to describe the behaviour of
degraded soils.
To compare natural soils with a reference one, reference soil water
retention curves were developed using the PTFs. The reference soil
water retention curve is described as the arithmetic mean of
volumetric water content at different suction values obtained from
processing PTFs. The sample 5 water retention curve is compared with
the reference one (Fig. 4). This comparison reveals that the
reference soil PTFs data always overestimate the measured data for
all suction values lower than 100 kPa, whereas for suction values
higher than 300 kPa, measured data are greater than the reference
soil.
To compare the measured hydraulic properties of the landfill soil
with the reference soil, their volumetric water contents – at
suctions 0.10 kPa, at field capacity, at wilting point and the
available water for plants – are compared. The histogram in Fig. 5
shows the water content at a suction of 0.10 kPa; soils have values
similar to each other (average θ % is 48.61 %,
SD 3.18 %), and also similar to the reference soil (θ % is 46.32 %).
The field capacity is described as the optimal relationship between
water and air in the soil; this condition is verified when the
micropore volume is entirely occupied by water while macropore
volume is entirely occupied by air. In the literature the field
capacity is represented by the water content at suction values in
the range of 10 kPa and 33 kPa (10 kPa for sandy soil and 33 kPa
for other soils). At field capacity (histogram Fig. 6), the sample
soil average θ % is 26.05, SD 4.68 %; this value is
lower than that of the reference soil (θ % is
30.16 %).
The histogram in Fig. 7 shows the soils at a suction of 1500 kPa
(wilting point); the average of volumetric water content of soils
sampled is θ % is 19.98 %, SD 5.97 %; the trend
in this case is very variable, with one soil that has a water
content of θ % = 27.91 % and another θ % is 10.86 %. The reference soil instead has a value of
θ % is 13.66 %; in nine soils the water content is
higher than that of the reference soil.
In general terms, the available water for plants is defined as the
difference between soil water content at suction 33 kPa – soil
water content at field capacity – and 1500 kPa – soil water
content at wilting point (histogram Fig. 8). For the investigated
soils the average amount of available water has a value of θ % = 6.06 %, very high SD 4.70 %, with a minimum
value of θ % = 0.55 % and a maximum of θ % = 12.14 %; the reference soil has a value of θ % = 16.50 %.
Volumetric water content (θ %) at suction 0.10 kPa: comparison between reference soil and landfill soils.
![]()
Volumetric water content (θ %) at field capacity:
comparison between reference soil and landfill soils.
![]()
Volumetric water content (θ %) at a suction of
1500 kPa: comparison between reference soil and landfill soils.
![]()
Available water to plants (θ %): comparison
between reference soil and landfill soils.
![]()
Biological spectrum of flora.
Biological spectrum of flora (%)
Therophytes
45
Hemicryptophytes
41
Geophytes
11
Phanerophytes
3
All the sampled soils have a much lower available water θ % than the reference soil, despite having an organic carbon
content about twice as high as in the reference soil. Generally,
high values of organic carbon correspond to high levels of organic
matter, which enhances permeability and water availability in the
soil. It would be interesting to study why a soil presenting
characters of physical degradation i.e. compaction, associated with
a lack of organic carbon content, has, on the contrary, a high
organic carbon content. With this in mind, it would be interesting, also, to study the carbon
decomposition in humic and fulvic acids in association with
limestone content.
Flora and vegetation
The total number of plant species sampled amounts to 90 (see
Appendix A); almost all of them are very common and abundant in the
province of Piacenza (Bracchi and Romani, 2010; Romani and
Alessandrini, 2001). Most of the species were found to be
competitive–ruderal (43 %) and ruderal (13 %) (Grime, 2001)
and belonging to the phytosociological class Stellarietea mediae R. Tx. Lohm. et PRSG. in Tx. 1950 which includes
nitrophilous annual vegetation (Mucina et al., 1993; Oberdorfer,
1993; Ubaldi, 2008).
Monthly rainfall and evapotranspiration (ETo). Climate data
source: San Lazzaro Alberoni weather station (Piacenza 1961–2005).
![]()
F index (soil moisture). Percentages are weighted by the
frequency of the species in the monitoring sites (see column
“Presence” in the Appendix). Legend: 1 is very dry, 1.5 is dry, 2
is moderately dry, 2.5 is fresh, 3 is moderately moist, 3.5 is
moist, 4 is very moist, 4.5 is wet and 5 is flooded or submerged.
![]()
Water lost from agricultural soil (a) and from the
landfill cover soil (b) by Crop Wat 8.0 software. Legend:
RAM represents readily available moisture; TAM represents total
available moisture.
![]()
Table 5 shows a list of the flora biological spectrum. The study
area has a particularly high percentage of therophytes (45 %)
when compared to the values of the biological range of the province
of Piacenza (23 %; Romani and Alessandrini, 2001) and
Emilia-Romagna (28 %; Pignatti et al., 2001). Typically,
ephemeral annual species tend to be concentrated in urban
environments (Sukopp and Werner, 1983) and in Italy, regardless of
human disturbance, their percentage increases gradually from north
to south in response to the emergence of a distinctly arid climate
(Pignatti, 1994, 1976).
Fig. 9 represents the monthly rainfall and evapotranspiration and it should
be noted that the ETo is greater than the rainfall in the period from May to
August, indicating a summer drought.
The histogram referring to the F index (Fig. 10) shows that most
of the species found require soils with a moisture content ranging
from moderately dry to moderately moist. The typically xerophyte
species and those found in submerged soils are absent, while there
are two ( Bolboschoenus maritimus (L.) Palla and Eleocharis palustris (L.) Roem. & Schult) that need wet soil.
In Fig. 11 the graphs referring to the amount of water lost from a
common agricultural soil of medium texture 1 m deep (a), and the
soil cover of the landfill (b) are presented, considering both the
climatic conditions of Piacenza and the cover of grassland
vegetation of perennial grasses (cool season grass varieties
including bluegrass, fescue and ryegrass; Allen et al., 1998). The
soil of the landfill has less water available to vegetation compared
to agricultural soil.
Discussion and conclusions
In this study, the attempt to relate the hydraulic properties of
degraded soil with plant coverage is presented.
The hydrological properties of a degraded soil are described through a
comparison between the laboratory tests and the results of predictive
systems by PTFs, showing that the PTFs are not able to describe them.
The study of the hydraulic properties of landfill cover soils has
outlined that these soils have less water content available in
comparison with a natural reference soil; this is a characteristic
of degradation.
On the basis of PTFs, some conclusions can be formulated. PTFs have
the advantage of being relatively inexpensive and easy to derive and
use, but for application at a specific point and for soils that are
outside the range of soils used to derive them, prediction using
PTFs might be inadequate. In this case, direct measurement is the
only option (Wösten et al., 2001) and it can be interesting to
conduct studies to develop degraded soils using new PTFs parameters
and to relate them to the type of soil organic content. Generally,
high values of soil organic carbon correspond to high levels of
organic matter, which enhances permeability and water availability.
With this in mind, it would
be interesting to study why a soil presenting characters of physical
degradation i.e. compaction, associated with a lack of organic
carbon content, has, on the contrary, a high organic carbon content.
It would be interesting, also, to study the carbon decomposition in
humic and fulvic acids in association with limestone content.
Analysing vegetation, it can be said that the landfill vegetation is
mainly related to the soil character. The low water content,
together with the lack of depth and compacted structure, would
justify the current presence of a vegetation cover which consists
predominantly of therophytes instead of a more developed and stable
perennial vegetation with shrubs and trees, as observed for other
landfills several years after their coverage (El-Sheikh et al.,
2012; Huber-Humer and Klug-Pümpel, 2004; Rebele and Lehmann,
2002). The high frequency of therophyte does not seem to be
justified by summer drought and by the low level of human
disturbance that affected the area in recent years, given that,
under the same climatic conditions, the potential vegetation of the
area should be represented by riparian forests of Populetalia albae Br.-Bl. 1935 (Puppi et al., 2010). These forests,
although not very widespread, are present and contiguous to the
landfill.
The presence of Bolboschoenus maritimus (L.) and Eleocharis palustris (L.), which need wet soil, is explained by the
fact that F refers to soil water availability during the time of
year when the species carry out their vegetative cycle (Landolt et
al., 2010). In this case the above-mentioned hydrophilic plants were
detected only in the spring months when the monthly
evapotranspiration is less than or equal to rainfall.
In comparison with agricultural soil in the same climatic
conditions, the landfill soil has less water available to vegetation,
and this contributes to water stress for plants over a
longer period (March to September) and is more pronounced as the
amount of water absorbed by plants during the summer is close to
their permanent wilting point (TAM line).
The low water content in association with high organic carbon,
the lack of depth, the compacted structure of these soils and the
current presence of a vegetation cover, which consists predominantly
of therophytes, are important studied aspects of the aims of the New
Life project, which seeks to establish a treatment for restoring
degraded soils. This treatment – the reconstitution – produces a
new soil, called reconstituted soil. The comparison between chemical-physical
characters of degraded and reconstituted soil is very important. In this
comparison it will be interesting to study their hydraulic properties in relation to their plant coverage.
Edited by: A. Cerdà