Article

Modeling Water Flow and Phosphorus Sorption in a
Soil Amended with Sewage Sludge and Olive
Pomace as Compost or Biochar
Vilim Filipović 1,*, Marko Černe 2, Jiří Šimůnek 3, Lana Filipović 1, Marija Romić 1,
Gabrijel Ondrašek 1, Igor Bogunović 1, Ivan Mustać 1, Vedran Krevh 1, Anja Ferenčević 1,David Robinson 4, Igor Palčić 2, Igor Pasković 2, Smiljana Goreta Ban 2, Zoran Užila 2 andDean Ban 2
Faculty of Agriculture, University of Zagreb, Svetošimunska 25, 10000 Zagreb, Croatia;
lfilipovic@agr.hr (L.F.); mromic@agr.hr (M.R.); gondrasek@agr.hr (G.O.); ibogunovic@agr.hr (I.B.);
imustac@agr.hr (I.M.); vkrevh@agr.hr (V.K.); anjaferencevic7@gmail.com (A.F.)
2 Institute of Agriculture and Tourism, Karla Huguesa 8, 52440 Poreč, Croatia; marko@iptpo.hr (M.Č.);palcic@iptpo.hr (I.P.); paskovic@iptpo.hr (I.P.); smilja@iptpo.hr (S.G.B.); zoran@iptpo.hr (Z.U.);
dean@iptpo.hr (D.B.)
3 Department of Environmental Sciences, University of California Riverside,
Riverside, CA 92521, USA; jiri.simunek@ucr.edu
4 UK Centre for Ecology & Hydrology, ECW, Bangor LL57 2UW, UK; davi2@ceh.ac.uk* Correspondence: vfilipovic@agr.hr; Tel.: +385-1-239-3711
1

Received: 15 July 2020; Accepted: 6 August 2020; Published: 8 August 2020

Abstract: Organic amendments are often reported to improve soil properties, promote plant growth,and improve crop yield. This study aimed to investigate the effects of the biochar and compost
produced from sewage sludge and olive pomace on soil hydraulic properties, water flow, and P
transport (i.e., sorption) using numerical modeling (HYDRUS-1D) applied to two soil types (Terra
Rosa and Rendzina). Evaporation and leaching experiments on soil cores and repacked soil columns
were performed to determine the soil water retention, hydraulic conductivity, P leaching potential,
and P sorption capacity of these mixtures. In the majority of treatments, the soil water retention
showed a small increase compared to the control soil. A reliable fit with the modified van Genuchten
model was found, which was also confirmed by water flow modeling of leaching experiments (R20.99). The results showed a high P sorption in all the treatments (Kd 21.24 to 53.68 cm3 g–1), and ahigh model reliability when the inverse modeling procedure was used (R2 0.93 - 0.99). Overall,adding sewage sludge or olive pomace as compost or biochar improved the Terra Rosa andRendzina water retention and did not increase the P mobility in these soils, proving to be asustainable source of carbon and P-rich materials.
Keywords: soil amendments; inverse estimation; numerical modeling; phosphate; HYDRUS

1. Introduction
The application of biochars or composts to soil may improve soil properties, promote plant
growth, or have a positive effect on crop yield [1–4]. Biochar is a pyrogenic carbon derived fromcarbon-rich waste materials, primarily agricultural residuals [5,6]. It is uncertain how it will impact
soil physical properties, as its properties often vary [7] depending on the means of production,
especially temperature [8]. Compost can alter soil physicochemical properties and promote plant
growth [9]. Producing biochars or composts from different organic materials is also an effective way
to reduce agricultural biomass waste while recycling and sterilizing it. Substantial amounts of waste
are produced annually worldwide, including agricultural residues, sewage sludge, and municipal
Agronomy 2020, 10, 1163; doi:10.3390/agronomy10081163

www.mdpi.com/journal/agronomy

Agronomy 2020, 10, 1163

2 of 20solid waste, all of which can provide an important supply of raw materials for recycling as biochar
or compost. China and the USA are estimated to produce ~1.4 billion Mtons of annual agricultural
biomass waste, which has the potential to produce ~420 million Mtons of biochar or compost per year
[10,11]. Compost and biochar are commonly applied to soil to improve the quality of the so-called“problem soils” [12]. Both biochar and compost soil amendments are usually applied to the soil under
the guidance of safety regulations to avoid possible harmful effects on soil, vegetation, animals, andhumans [13].
The application of soil organic amendments is known to alter soil physical properties, forexample by reducing the bulk density, increasing the infiltration rate and hydraulic conductivity,
increasing the water retention, and enhancing the aggregate stability [4,11,14]. In turn, this supports
improvements in plant growth [15,10]. Villagra-Mendoza and Horn [16] studied the effects of woodbased biochar on two soils with different textures and their hydrological properties, such as water
retention, shrinkage behavior, and hydraulic conductivity. The biochar amendments tested were
found to increase the soil water retention in coarse-textured sand compared to unamended soil. The
pore size distribution of the sandy substrate was also significantly altered by reducing the fraction oflarge coarse pores while increasing the mesoporosity. Repeated soil wetting and drying cycles
enhanced the structural stability of the pore system while increasing the saturated hydraulicconductivity. A similar study was conducted by Mohawesh and Durner [17], who tested the effectsof hydrogel (Luquasorb hydrogel, BASF SE Company, Germany), bentonite (smectite clay), andbiochar as soil amendments on soil hydraulic properties. The results revealed that the control soil
retained less water at any matric potential compared to the amended soils. However, the soil
hydraulic conductivity also decreased with an increase in these soil amendments.
Various elements, including nutrients, are present in soil amendments, depending on the typeand origin of waste from which they are produced. Phosphorus (P), a macronutrient required for
optimal plant growth [18], often needs to be added to agricultural soils in a fertilizer form. It isfrequently present in various soil amendments and needs to be recycled, as it cannot be synthesized
and is currently mined from finite sources [19]. Three factors largely control P availability: the pH
and mineralogy, organic matter levels, and fertilizer additions. P deficiency may occur due to acid or
alkali conditions (pH 6–7 is optimal), or due to a naturally slow release from mineral inorganic P.
Adding inorganic or organic P as a fertilizer to arable soils with P deficiency, or simply to replenish
the P removed by crops, helps maintain productivity. However, P leaching or P removal by soil
erosion from heavily fertilized agricultural lands leads to aquatic pollution. The increased
concentration of phosphorus in aquatic ecosystems is one of the main causes of water eutrophication[20]. Incorporating P-rich organic amendments, such as compost or biochar, can possibly reduce or
prevent negative environmental effects caused by P leaching while ensuring optimal conditions forcrop growth due to amendments to the sorption properties.
Numerical models use different mathematical and numerical approaches, which can simulate avariety of vadose zone processes, including the leaching and sorption of P throughout the soil profile.
For example, Morrison et al. [21] first used the DRAINMOD model to simulate soil water flow in thefield. They then performed a linear regression analysis, according to water flow, to predict the P loss.
Van der Salm et al. [22] used the PLEASE model to simulate the P losses from soils in Denmark andthe Netherlands based on the P concentrations in tile drains, suction cups, and groundwater. Larsson
et al. [23] used the dual-porosity ICECREAM model to simulate the P losses in tile drainage from clay
soil. The HYDRUS code is also widely used for modeling water and solute dynamics in the(un)saturated soil zone in one, two, or three dimensions [24]. Kadyampakeni et al. [25] used
HYDRUS-1D to predict the temporal movement of P in two soil types using the laboratory-derived
sorption coefficient (Kd). Ben-Gal and Dudley [26] used HYDRUS-2D for analyzing data from agreenhouse study of the effects of continuous and intermittent drip irrigation regimes on the water
movement and P distribution in soil monolith lysimeters. Their results showed that a high-frequency
or continuous low-volume irrigation could maintain uniform distribution patterns of water and P
and improve the conditions for plant growth and water and nutrient uptake. Although the simulated
and measured P concentrations (soluble vs. bicarbonate-extractable P) were not directly comparable,

Agronomy 2020, 10, 1163

3 of 20the observed differences were explained by the variability in the soil parameters, preferential flow,
and the use of the Langmuir sorption kinetic model. On the other hand, Elmi et al. [27], in their studyof phosphate (PO4) vertical distribution and transport processes in reconstructed soil columns,
described sorption kinetics using the Freundlich equation. The model overpredicted the PO4 sorption,
which was explained by preferential flow and difficulty in quantifying nonlinear reaction types.
HYDRUS (its 3D version) was also used in the study of Naseri et al. [28], who assessed the effects ofdifferent water flux densities on the P transport in soil columns. While the soil water content was
successfully reproduced, the linear sorption kinetics still overestimated the final adsorbed PO4
concentrations.
One way to obtain a better description of experimental data is to inversely reproduce sorption
kinetics using the final P concentrations, additionally avoiding overestimation by the model. Using theinverse modeling approach, the unknown soil hydraulic or solute transport and reaction parameters
can be estimated or further optimized by minimizing deviations between the observed and modelsimulated variables (e.g., concentrations, water contents, fluxes) collected during leaching experiments[29]. This approach allows the estimation of parameters which are difficult or even impossible tomeasure directly. The inverse parameter optimization approach is commonly used for the estimationof soil hydraulic [30,31] or solute transport and reaction (e.g., sorption) parameters [32].
Organic amendments can significantly improve crop production while, at the same time,decreasing the amount of organic waste. However, ensuring we do not swap the problem of waste
for the problem of pollution is important. Therefore, studies focused on understanding the main soil
properties and processes affected by the amendment application are important, especially whenevaluated from an agricultural and environmental perspective for decision-making. For example,
when applying amendments to agricultural soil, it is important to estimate the soil water flow andelement sorption kinetics [33,34], as these processes will determine its agricultural significance andthe environmental impact.
The aim of this study was, therefore, to investigate the effects of biochar and compost produced
from sewage sludge and olive pomace on soil hydraulic properties, water flow, and P transport (i.e.,
sorption) using numerical modeling (HYDRUS-1D). The objectives were threefold:i. Conduct a controlled set of column experiments on two common agricultural soils todetermine how two amendments (biochar and compost) from two waste sources (sewage sludge andolive pomace) applied at two concentrations (a guideline rate and (10 × ) higher) affect soil hydraulicproperties and P sorption and mobility;
ii. Simulate water flow and use inverse modelling to estimate the P sorption coefficient (Kd) ineach treatment;
iii. Analyze the results to determine how the amendments impact the soil hydraulic functions
and P mobility.
2. Materials and Methods
2.1. Soil Types and Amendments
The Terra Rossa and Rendzina soils (Cambisol Rhodic and Leptosol Calcaric, according to IUSSWRB (2015) [35] used in the experiment were collected from topsoil (0–30 cm depth) at selected sites
from the Istrian peninsula, Croatia. These two soil types (Terra Rossa and Rendzina) were selected
because of their contrasting organic C (0.7% and 6.1%) and P contents (350.2 and 301.8 mg kg–1) andtheir similar pH (6.55 and 7.69). The Terra Rosa had a texture of 7% sand, 57% silt, and 36% clay,
while Rendzina had a texture of 3% sand, 50% silt, and 47% clay. Furthermore, the municipal
dewatered and aerobically stabilized sewage sludge (SS) was obtained from the local wastewater
treatment facility. At the same time, the olive pomace (OP) produced using a two-phase extraction
system was obtained from a local olive mill facility. These were used as raw materials to produce
compost and biochar amendments. Additional information regarding the soil properties and theproperties of SS and OP (chemical and physical properties with processing information presented)
are explained in detail in Černe et al. [36] and in the Supplementary Material.

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The Compost Sewage Sludge (CSS) and Compost Olive Pomace (COP) were produced at theexperimental farm of the Institute of Agriculture and Tourism, Croatia. For composting, an enclosure
with inner dimensions of 77 × 77 × 77 cm constructed from concrete blocks was used. The composting
mixture consisted of aerobic SS and wheat straw at a ratio of 40 kg of straw per 1 m–3 of SS to adjust
the C/N ratio. The OP was composted without any additional material. For efficient aerobic
degradation, standard agricultural measures were applied [37]. For instance, the temperature wasmonitored daily in the center of a pile using temperature sensors (ONSET HOBO series). The relative
humidity (RH) was maintained at between 55% and 60% and controlled according to EPA (2001) [38].
Aeration was performed monthly by turning the pile by hand. After three months, the compost
maturity and quality were evaluated according to Canet et al. [37].
The Biochar Sewage Sludge (BSS) and Biochar Olive Pomace (BOP) were produced using asystem following the Kon-Tiki model [39]. An amount of 30 L of SS and OP material was combusted
during one pyrolytic cycle, which lasted approximately 3 hours. To monitor the pyrolysis process,the temperature was measured using a NiCrNi thermoelement and ranged from 410 to 470 °C. At theend of the pyrolytic cycle, the process was stopped using water quenching. More details regarding
the chemical properties and processing information of the soil amendments can be found in Černe etal. [36] and in the Supplementary Material. The trace metals and macro- and microelements were
determined by inductively coupled plasma-optical emission spectrometry, ICP-OES (Vista-MPX,
Varian, Inc., USA), after microwave digestion according to HRN ISO 22036:2011. The soil pH andelectrical conductivity (EC) were measured using the Mettler Toledo MPC 227 conductivity/pHmeter in water (pH H2O) (HRN ISO 10390:2005), while the organic C content was determined using
sulfochromic oxidation (HRN ISO 14235:1998), and N concentration according to the adapted
Kjeldahl method (HRN ISO 11261:2004).
2.2. Experimental Set-up
A column study was conducted in a greenhouse of the Institute of Agriculture and Tourism,
Poreč, Croatia. The compost (CSS and COP) and biochar (BSS and BOP) were sieved (2 mm) to assure
their homogeneous distribution in the soil-amendment mixture. The amendments were added at
rates calculated on a P content basis; (P) according to the Croatian legislation on sewage sludge
agricultural use, the NN 38/08 (i.e., 12 mg P L–1) and (P+) 10 times higher rate than recommended by
the Croatian legislation (i.e., 120 mg P L–1). On September 13th, 2017, repacked soil columns (20 cm
diameter × 20 cm height) were filled with soil (Terra Rossa or Rendzina) amended with a) compost
sewage sludge (CSS), b) biochar sewage sludge (BSS), c) compost olive pomace (COP), and d) biochar
olive pomace (BOP), with each at the P and P+ application rates. Terra Rossa or Rendzina control
soils were also used in the experiment as non-modified soils (_0) and control soils with added
phosphorus (_P) at concentration levels recommended by the Croatian legislation (i.e., 12 mg P L–1).
The columns were prepared in four replicates to reduce the effects of unknown systematic bias.
A four-factor experimental column design was used: two soils—Terra Rossa (T) and Rendzina (R);
two organic materials—sewage sludge (SS) and olive pomace (OP); two soil amendments—compost(C) and biochar (B)—applied at two amendment application rates (P and P+); and two controls foreach soil type (_0 and _P). A total of 16 treatments and four controls were used (Tables 1 and 2).
Table 1. Description of treatments from a greenhouse pot experiment with the Terra Rosa (T) soil
amended with biochar (B) or compost (C) produced from sewage sludge (SS) or olive pomace (OP) at
two application rates calculated on a P content basis (according to legislation, P; and a 10 times higher
rate, P+).

Treatment Abbreviation
TBSS_P
TBSS_P+
TBOP_P
TBOP_P+
TCSS_P

Soil
Terra Rossa
Terra Rossa
Terra Rossa
Terra Rossa
Terra Rossa

Treatment methodbiocharbiocharbiocharbiocharcompostWaste typesewage sludge
sewage sludge
olive pomace
olive pomace
sewage sludge

P-levelP-regulation
P-10× higher
P-regulation
P-10× higher
P-regulation

Agronomy 2020, 10, 1163

TCSS_P+
TCOP_P
TCOP_P
T_P
T_0

5 of 20

Terra Rossa
Terra Rossa
Terra Rossa
Terra Rossa
Terra Rossa

compostcompostcompost//sewage sludge
olive pomace
olive pomace//

P-10× higher
P-regulation
P-10× higher
P-regulation
0

Table 2. Description of treatments from a greenhouse pot experiment with the Rendzina (R) soil
amended with biochar (B) or compost (C) produced from sewage sludge (SS) or olive pomace (OP) at
two application rates calculated on a P content basis (according to legislation, P; and a 10 times higher
rate, P+).

Treatment Abbreviation
RBSS_P
RBSS_P+
RBOP_P
RBOP_P+
RCSS_P
RCSS_P+
RCOP_P
RCOP_P
R_P
R_0

Soil
Rendzina
Rendzina
Rendzina
Rendzina
Rendzina
Rendzina
Rendzina
Rendzina
Rendzina
Rendzina

Treatment methodbiocharbiocharbiocharbiocharcompostcompostcompostcompost//Waste typesewage sludge
sewage sludge
olive pomace
olive pomace
sewage sludge
sewage sludge
olive pomace
olive pomace//

P-levelP-regulation
P-10× higher
P-regulation
P-10× higher
P-regulation
P-10× higher
P-regulation
P-10× higher
P-regulation
0

2.3. Column Leaching Experiment and Chemical Analysis
During the experiment, the night temperatures ranged from 8 to 12 °C, and the daytime
temperatures ranged from 15 to 25 °C, while the relative humidity varied between 35% and 70%. The
columns were irrigated with tap water using a handheld sprayer to maintain the amended soil watercontent at near 75% of the water-holding capacity. Before the leaching experiments, the columns weresaturated and left to drain excess water to reach steady-state (matching) conditions to achieve thesame initial conditions. At the beginning of the experiment, soil samples were taken (from all 16
treatment columns and 4 control columns) for the determination of the total P concentration in thesoil using the aqua regia extraction method, and measured using optical emission spectrometryinductively coupled plasma (Vista MPX AX, Varian). For the leaching experiment, the columns were
irrigated three times with 500 ml of water at each irrigation event during one week. The leachingexperiment was conducted on columns without the crop for the purpose of evaluating the P mobility
when no crop is present in the field. The leachate was collected from the columns after each irrigation
event, and its volume was measured. The leachate samples were transported to the laboratory where
they were stored under low-temperature conditions (4 °C) until the orthophosphates (PO4-P) wereanalyzed using a continuous flow auto-analyzer (San++ Continuous Flow Analyzer, Skalar). The
leaching experiment and soil (treatments) total P results are presented in Table 3.
Table 3. Total phosphorus concentration in the soil before the leaching experiment, and the volumesof irrigation water added in columns filled with the Terra Rosa (T) or Rendzina (R) soils amended
with biochar (B) or compost (C) produced from sewage sludge (SS) or olive pomace (OP) at two
application rates, calculated on a P content basis (according to legislation, P; and a 10 times higher
rate, P+) (n = 4).

Treatment
abbreviation
TBSS_P
TBSS_P+

Total P
concentration
in soil (mg kg–
1)
323.2
474.1

Irrigation
volume(mL)

Treatment
abbreviation

500 (3×)500 (3×)

RBSS_P
RBSS_P+

Total P
concentration
in soil (mg kg–
1)
270.4
366.9

Irrigation
volume (mL)
500 (3×)500 (3×)Agronomy 2020, 10, 1163

TBOP_P
TBOP_P+
TCSS_P
TCSS_P+
TCOP_P
TCOP_P+
T_P
T_0

6 of 20

308.4
317.7
312.8
350.9
313.1
358.7
422.8
320.6

500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)

RBOP_P
RBOP_P+
RCSS_P
RCSS_P+
RCOP_P
RCOP_P+
R_P
R_0

249.8
258.9
254.8
294.4
247.7
333.2
490.5
251.5

500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)500 (3×)

2.4. Soil Hydraulic Parameters Estimation
The soil physical properties were measured for each treatment and control separately, first for
the unamended soil, and then again after the biochar/compost addition. The particle size distribution
was determined using a combination of sieving and sedimentation analysis from bare soil (Terra Rosaand Rendzina) according to Gee and Or [40]. The soil hydraulic properties were determined on
undisturbed soil cores of 250 cm3 volume (n = 2 per treatment) by pushing the rings into the columns(for all 16 treatments and 4 controls). The soil hydraulic properties were estimated using the extended
evaporation method [41]. The undisturbed soil samples (250 cm3) were saturated from the bottom
and allowed to drain, then sealed at the bottom. Two tensiometers were inserted into each soil sample
at depths of 1.5 and 4.6 cm. The tensiometers (5.0 and 2.5 cm in length) were inserted in the upward
direction to minimize the amount of water draining from the tensiometers into the soil during theexperimental stage. The experiments were started by removing the upper cap of the soil samples toexpose the soil surface to evaporation. The overall mass and pressure heads were recorded every 30
minutes using the HYPROP system (METER Group, Inc., Pullman, WA 99163, USA). The
experiments continued until the measurement limit of about –800 cm of the upper tensiometer was
reached. An additional point of the air-entry pressure of the tensiometer’s porous ceramic cup wasused for the quantification of hydraulic functions close to the wilting point, which extended themeasurement range of the evaporation method [41].
The modified analytical model of van Genuchten (the VC model [42]), describing theunsaturated soil hydraulic functions (i.e., the soil water retention curve and the unsaturated
hydraulic conductivity function), was used for the modeling. The model was used to add flexibility
to the description of the hydraulic conductivity near saturation. The soil water retention, θ(h), andhydraulic conductivity, K(h), functions are then given by:𝜃 +(𝜃(ℎ) =

|

ℎ< 0
,
ℎ≥ 0

| )

𝜃
𝐾 𝐾 (ℎ)𝐾(ℎ) =

𝐾 +

(

ℎ≤ℎ

)(

)

ℎ <ℎ <ℎ ,

𝐾
(

)
)

=

( )
(
/

𝐹(𝜃) = 1 −
𝑆

(2)

ℎ≥ ℎ
(

𝐾 =

(1)

,

,

)

,

(3)
(4)
(5)

where θ(h) and K(h) are the volumetric water contents [L3 L–3] and unsaturated hydraulicconductivities [L T–1] at the soil water pressure heads h [L], respectively; θr and θs denote the residual
and saturated soil water contents [L3 L–3], respectively; Se is the effective saturation; Ks is the saturated
hydraulic conductivity [L T–1]; α is the inverse of air-entry value or bubbling pressure [L–1]; n is thepore size distribution index [-]; and l is the pore connectivity parameter [-]. The above Equation 2

Agronomy 2020, 10, 1163

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assumes that the predicted hydraulic conductivity function is matched to a measured value of thehydraulic conductivity, Kk=K(θk), at a particular water content, θk, less than or equal to the saturated
water content—i.e., θk ≤ θs and Kk ≤ Ks [42,43]. The Sek is the effective saturation at θk. This model allows
using the evaporation data for the soil matrix and extension of the K(h) function to independently
determine Ks using a linear transition. The Ks rate was initially calculated based on the collected
outflow from the leaching experiment. The residual water content θr was set to 0, as it was previously
found not to affect the soil water retention curve [44,45].
2.5. Numerical Modeling of Water Flow and P Transport
Numerical modeling was performed using the HYDRUS-1D program [46]. The water flow
simulations in a one-dimensional soil profile were based on the numerical solution of the Richards
equation for variably saturated porous media:
( )

=

𝐾(ℎ)

+1 ,

(6)

where θ is the volumetric water content [L3L–3], h is the water pressure head [L], t is the time [T], z is
the spatial coordinate [L] (positive upward), and K is the hydraulic conductivity [LT–1].
Solute transport (PO4-P) was described using the Fickian-based advection-dispersion equation:
+

(

)

=

𝜃𝐷

− 𝑞𝑐 − ∅,(7)

where c is the solute concentration in the liquid phase [M L–3]; q represents the volumetric water flux
density [L T–1]; ρ is the bulk density of the soil [M L–3]; s is the adsorbed concentration [M M–1]; ∅ isthe rate of change of the solute mass per unit volume of soil by chemical or biological reactions orother sources (negative) or sinks (positive) [M L–3 T–1]; and D is the dispersion coefficient [L2 T–1],
which is defined as follows:𝜃𝐷 = 𝐷 |𝑞| + 𝜃𝐷 𝜏,(8)where Dm is the coefficient of molecular diffusion [M L2 T–1], τ is the tortuosity factor [-], and DL
represents the longitudinal dispersivity [L].
The phosphorus sorption to soil particles was simulated considering equilibrium linear
adsorption (Eq. 9), which describes the relationship between the sorbed and liquid phase
concentrations:𝑠 = 𝐾 𝑐,(9)where Kd [L3 M–1] is the P distribution (sorption) coefficient.
The initial conditions for the water flow modeling were set to the pressure head of 0 at thebottom and -20 cm at the top (hydrostatic equilibrium) of the soil column to match the experimental
conditions. A time-variable atmospheric flux boundary condition (applied irrigation andevaporation) was used at the top, and a seepage face boundary condition was applied at the bottomof the column.
Phosphorus can exist in the soil in various chemical forms [47,48], all of which cannot be taken
into consideration by the model, so the reaction model used for the simulation of P sorption is basedon a simplified P soil chemistry. As bidirectional transformations of multiple solutes cannot be
simulated using the conventional advection-dispersion equation solved by HYDRUS (or any known
mechanistic model), the numerical analysis focused instead on the dissolved P (orthophosphate, PO4P). Orthophosphate present in the soil solution is desorbed, and therefore available and leachable asa soil P fraction. Thus, PO4-P was selected for the numerical analysis due to its water-soluble nature,
its presence in soil solution at near-neutral pH, and its major role in crop uptake and leaching.
Furthermore, the measured initial soil total P concentration was considered in the model as the sumof soluble orthophosphates and labile adsorbed P, with the remaining P assumed to be nonreactive
during the P sorption simulation. The phosphorus concentration in the soil solution was consideredas the dissolved reactive P fraction (DRP) [47]. Similar approaches have been previously used innumerous modeling studies [28,25,49]. Phosphorus sorption in soil was simulated for 7 days (168 h).

Agronomy 2020, 10, 1163

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2.6. Inverse P Dynamics Modeling
The Levenberg–Marquardt optimization algorithm [50], in combination with the HYDRUS-1D
numerical code [46], was used to inversely estimate the sorption coefficient for various treatments.
Different approaches that are routinely used in inverse modeling are provided in Hopmans andŠimůnek [51] and Vrugt et al. [32]. The optimized solute reaction parameters were determined byminimizing the differences between the observed and simulated state variables (i.e., PO4-P fluxes).
The sum of squares of these the differences is expressed using an objective function, ∅, which may be
defined as [29]:∅(𝛽, 𝑦) = ∑𝑤 , 𝑦 ∗ (𝑧, 𝑡 ) − 𝑦 (𝑧, 𝑡 , 𝛽) ,

𝑣 ∑

(10)

where the right-hand side represents the residuals between the space-time variables, which aremeasured (𝑦 ∗ ) and model-predicted (𝑦 ) using the solute reaction parameters of the optimized
parameter vector, 𝛽. The first summation sums the residuals for all measurement types my (i.e.,leachate solute fluxes). The variable nj in the second summation denotes the number of measurements
for a particular measurement type j. Assuming that the measurement errors in a specificmeasurement type are independent and uncorrelated, the weighting factor vj can be selected so thatdifferent data types are weighted equally using the reciprocal of the variance of the measurement
type j [52]. The sorption coefficient Kd for P was estimated inversely using the PO4-P concentrations
measured in the leachate (which were transformed into the cumulative PO4-P flux).
The quality of the fit was evaluated by comparing the simulated and measured leachate volumes
and leachate concentrations using the coefficient of determination (R2):
𝑅 =

∑
∑

(

(
)

)(
,

∑

)
(

)

,

,

(11)

where Oi are the observation data points, Pi are the model predictions, Ō is an average observation,
𝑃 is an average prediction, and N is the sample size.
3. Results and Discussion
3.1. Impact of Amendments on Soil Water Retention and Hydraulic Properties
The effects of the compost and biochar addition on the shape of the soil water retention andhydraulic conductivity curves of two soil types—i.e., Terra Rosa and Rendzina—are illustrated in
Figure 1 and Figure 2. For the majority of treatments, the soil water retention increased compared tothe control, resulting in an increase in the saturated water content, field capacity, and available watercontent. Similar results were obtained by Villagra-Mendoza and Horn [16] and Mohawesh andDurner [17] for soils amended with biochar, and Karbout et al. [53] for soils amended with compost.
An increase in soil water retention is related to an increase in the number of macro and medium poresdue to the addition of compost or biochar, which affects the total porosity and the pore size
distribution. In two treatments of the Terra Rosa soil type (TCSS_P, TCSS_P+), the addition ofcompost or biochar resulted in a lower/identical saturated water content. For these particulartreatments, θs decreased from 0.450 to 0.437 (TCSS_P), or it stayed unchanged at 0.450 cm3 cm–3
(TCSS_P+, Table 4), which may be associated with the heterogeneity of the soil-amendment mixture
and uncertainties during the retention curve estimation. The control soils, Terra Rosa (T_0, T_P) andRendzina (R_0, R_P), had saturated water contents of 0.45 and 0.36 cm3 cm-3, respectively (Table 4 &5), thus the increase due to the amendments was not particularly high (0.01–0.07 cm3 cm–3; Fig. 1).
Razzaghi et al. [4] conducted a statistical meta-analysis of the literature published between 2010 and2019 and quantified biochar’s impacts on soil water retention variables (Field capacity—FC; wilting
point—WP; available water content—AW). FC and WP significantly increased for the coarse-textured
soils (by 51% and 47%, respectively), and moderately for the medium-textured soils (by 13% and 9%,
respectively). For the fine-textured soils, the FC remained unchanged (< 1%), but the WP marginallydecreased by 5%. Biochar significantly increased the AW in the coarse-textured soils (by 45%)
compared to the medium- and fine-textured soils (by 21% and 14%, respectively), suggesting that

Agronomy 2020, 10, 1163

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biochar may provide a greater benefit for coarse-textured soils. A similar effect was seen in thepresented experiments where both soil types, Terra Rosa and Rendzina, had a silty clay loam texture
with < 7% sand.

Figure 1. Measured soil water retention points and reproduced soil water retention curves for the
Terra Rosa (T) and Rendzina (R) soils amended with biochar (B) or compost (C) produced fromsewage sludge (SS) or olive pomace (OP) at two application rates, calculated on a P content basis(according to legislation, P; and 10 times higher rate, P+): (a) Terra Rosa with biochar waste, (b) Terra
Rosa with composted waste, (c) Rendzina with biochar waste, and (d) Rendzina with composted
waste.

On the other hand, the effect of the addition of compost or biochar on the unsaturated hydraulicconductivity (K) was not so distinctive (Figure 2). In both soils, Terra Rosa and Rendzina, with theadded amendments, the shape of the hydraulic conductivity curve and the measured data range
showed slight changes following the retention data, with some larger changes seen in TBSS_P,
TBSSP+, TCSS_P, and RBSS_P compared to the control columns. Schneider et al. [54] compared theeffects of two types of composts (urban waste and co-compost of green wastes and sewage sludge)
at a field scale on near-saturated infiltration using a tension disc infiltrometer. The effect on the nearsaturated hydraulic conductivity was not identifiable when analyzing only the average plot-scalevalues. Still, it could be shown when accounting for additional heterogeneity: application date,structure, and tillage. In our experiment, the time needed for structure development, settling, and acolumn scale limited the apparent effects of the amendment treatments. Therefore, it should befurther tested in a long-term study conducted on a field scale. Similar to minor changes in water
retention properties, the hydraulic conductivity was also altered only slightly.

Agronomy 2020, 10, 1163

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Figure 2. Measured points and reproduced hydraulic conductivity curves for the Terra Rosa (T) andRendzina (R) soils amended with biochar (B) or compost (C) produced from sewage sludge (SS) or
olive pomace (OP) at two application rates, calculated on a P content basis (according to legislation,
P; and 10 times higher rate, P+): (a) Terra Rosa with biochar waste, (b) Terra Rosa with composted
waste, (c) Rendzina with biochar waste, and (d) Rendzina with composted waste.

The fitting of the VC model to the soil water retention curves and the resulting set of soil
hydraulic parameters are presented in Table 4 for Terra Rosa and in Table 5 for Rendzina. The
accuracy of the soil hydraulic property estimation is generally limited by the error of themeasurement method. The saturated hydraulic conductivity (Ks) is reported to be one of the mostvariable soil properties, having predictions with large uncertainty. Thus, various approaches likedeveloping new piecewise-continuous hydraulic functions based on in situ and laboratory
measurements [55], estimating Ks from pedotransfer functions (PTFs) [56]), or using inverse modeling[57] have been proposed. Here, the K(h) function near saturation was obtained by the linear
interpolation between the measured values Kk (from the evaporation experiment) and Ks (from theleaching experiment).
The addition of soil amendments did not show an apparent effect on Ks. However, to properly
evaluate this, a more focused experiment is needed. The total range of Ks was from 4.71 to 7.23 cm d–
1 in all the treatments, including the controls. However, in both soil types, the evaluated K-h curves
and Ks shifted in both directions, showing an increase or decrease compared to the control. Similar
observations were made by Villagra-Mendoza and Horn [16], who reported a decrease in thesaturated hydraulic conductivity when amendments were added. This is somewhat contrary to thefindings of the positive impact of compost and biochar amendments on soil hydraulic properties [11].
In our study, the compost and biochar were sieved through a 2 mm sieve before mixing with the soil,
with a relatively short period available for soil-amendment mixture settling in the columns, probably
insufficient for the development of a defined structure and aggregate formation in the soil [54].

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Table 4. The soil hydraulic parameters for the VC model determined using the evaporation
experiment on the Terra Rosa (T) soil amended with biochar (B) or compost (C) produced fromsewage sludge (SS) or olive pomace (OP) at two application rates, calculated on a P content basis(according to legislation, P; and a 10 times higher rate, P+).

Treatment
abbreviation
TBSS_P
TBSS_P+
TBOP_P
TBOP_P+
TCSS_P
TCSS_P+
TCOP_P
TCOP_P+
T_P
T_0

θs(cm cm–3)
0.480
0.481
0.493
0.519
0.437
0.450
0.480
0.515
0.450
0.450
3

α
(cm-1)
0.00247
0.00238
0.02340.032
0.00195
0.011
0.04610.01350.00895
0.00914

n
(-)
1.12
1.15
1.16
1.19
1.16
1.10
1.08
1.11
1.17
1.16

Ks
(cm d–1)
7.07
6.68
5.72
7.07
6.59
6.68
6.94
6.11
6.37
6.81

l
(-)
–4.80
–4.51
–5.08
–3.57
–3.57
4.89
10.00
–6.00
4.59
3.99

θk
(cm cm–3)
0.480
0.480
0.457
0.437
0.437
0.448
0.441
0.513
0.434
0.446
3

Kk
(cm d–1)
0.019
0.022
0.282
0.759
0.026
0.047
0.525
0.158
0.575
0.093

Table 5. Soil hydraulic parameters for the VC model determined using the evaporation experimenton the Rendzina (R) soil amended with biochar (B) or compost (C) produced from sewage sludge (SS)or olive pomace (OP) at two application rates, calculated on a P content basis (according to legislation,
P; and a 10 times higher rate, P+).

Treatment
abbreviation
RBSS_P
RBSS_P+
RBOP_P
RBOP_P+
RCSS_P
RCSS_P+
RCOP_P
RCOP_P
R_P
R_0

θs(cm3 cm–3)
0.412
0.432
0.400
0.420
0.422
0.430
0.403
0.418
0.372
0.346

α
(cm–1)
0.015
0.002720.00180.00430.00230.002190.00930.001460.001070.00062

n
(-)
1.16
1.17
1.18
1.12
1.21
1.18
1.10
1.19
1.18
1.25

Ks
(cm d–1)
5.97
4.71
7.07
6.94
7.16
6.94
7.07
7.24
6.94
6.94

l
(-)
–0.15
–6.00
–6.00
–6.00
–5.95
–5.80
–6.00
–6.00
–6.00
–6.00

θk
(cm3 cm–3)
0.398
0.432
0.399
0.419
0.420
0.429
0.397
0.418
0.371
0.346

Kk
(cm d–1)
0.537
0.029
0.024
0.065
0.047
0.019
0.525
0.019
0.014
0.005

The measured cumulative leachates from columns filled with the Terra Rosa (T) and Rendzina(R) soils amended with biochar (B) or compost (C) produced from sewage sludge (SS) or olive pomace(OP) at two application rates, calculated on a P content basis (according to legislation, P; and a 10
times higher rate, P+), are presented in Figures 3 and 4, respectively. The R2 values for the simulation
efficiency show that the HYDRUS-1D model successfully estimated the water flow with a highefficiency (0.99, Table 6), which was expected because the water flow in non-structured homogeneous
soils under controlled conditions is usually very well predicted using HYDRUS-1D [28,27,58].

Agronomy 2020, 10, 1163

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Figure 3. (a to j) Measured (dots) vs. simulated (HYDRUS-1D; line) cumulative leachates fromcolumns filled with the Terra Rosa (T) soil amended with biochar (B) or compost (C) produced fromsewage sludge (SS) or olive pomace (OP) at two application rates, calculated on a P content basis(according to legislation, P; and a 10 times higher rate, P+).

Agronomy 2020, 10, 1163

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Figure 4. (a to j) Measured (dots) vs. simulated (HYDRUS-1D; line) cumulative leachates fromcolumns filled with the Rendzina (R) soil amended with biochar (B) or compost (C) produced fromsewage sludge (SS) or olive pomace (OP) at two application rates, calculated on a P content basis(according to legislation, P; and a 10 times higher rate, P+).

Terra Rosa

Table 6. An averaged leachate amount (cm) measured in a column experiment and simulated with
HYDRUS-1D using optimized VC parameters for the Terra Rosa (T) and Rendzina (R) soils amended
with biochar (B) or compost (C) produced from sewage sludge (SS) or olive pomace (OP) at two
application rates, calculated on a P content basis (according to legislation, P; and a 10 times higher
rate, P+) (n = 4).

Measu
red
vol.
(cm)
Simula
ted
vol.
(cm)
R2

TBSS
_P

TBSS_
P+

TBOP
_P

TBOP_
P+

TCSS
_P

TCSS_
P+

TCOP
_P

TCOP
_P+

T_
P

T_
0

4.38

4.24

3.89

4.54

4.39

4.44

4.54

4.43

4.3
8

4.3
9

4.71

4.72

4.72

4.72

4.72

4.72

4.71

4.71

4.7
2

4.7
2

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.9
9

0.9
9

Rendzina

Agronomy 2020, 10, 1163

Measu
red
vol.
(cm)
Simula
ted
vol.
(cm)
R2

14 of 20

RBSS
_P

RBSS_
P+

RBOP
_P

RBOP
_P+

RCSS
_P

RCSS
_P+

RCOP
_P

RCOP
_P+

R_
P

R_
0

4.46

4.13

4.55

4.09

4.33

4.56

4.71

4.54

4.6
5

4.4
4

4.72

4.72

4.73

4.72

4.72

4.73

4.73

4.73

4.7
2

4.7
2

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.9
9

0.9
9

3.2. Soil Amendments and PO4-P Leaching Potential
After the water flow was successfully simulated, the P transport for each treatment and control
was modeled using the measured PO4-P cumulative fluxes (Figures 5 and 6) in inverse numericalsimulations to estimate the distribution coefficient, Kd (Table 7).

Figure 5. (a to j) Measured (dots) vs. simulated (HYDRUS-1D; line) cumulative PO4-P leachate fluxes
from columns filled with the Terra Rosa (T) soil amended with biochar (B) or compost (C) produced
from sewage sludge (SS) or olive pomace (OP) at two application rates, calculated on a P content basis(according to legislation, P; and a 10 times higher rate, P+).

Agronomy 2020, 10, 1163

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Figure 6. (a to j) Measured (dots) vs. simulated (HYDRUS-1D; line) cumulative PO4-P leachate fluxes
from columns filled with the Rendzina (R) soil amended with biochar (B) or compost (C) produced
from sewage sludge (SS) or olive pomace (OP) at two application rates, calculated on a P content basis(according to legislation, P; and a 10 times higher rate, P+).

The sorption coefficient is one of the most relevant parameters during the estimation of element
mobility in soils [59]. The simulated and experimental data showed that the P transport was limited
in both the Terra Rosa and Rendzina soils amended with either compost or biochar produced fromsewage sludge or olive pomace and applied at two application rates (i.e., P and P+) due to its highsorption in soil. The sorption was in the range from 21.24 to 53.68 cm3 g–1 and showed a relatively
uniform sorption capacity for all the treatments and controls in the experiment (Table 7). This finding
is in agreement with a literature review that showed that the Kd in most soils with similar
physicochemical characteristics ranged from 19 to 185 cm3 g-1 [60,61]. Furthermore, the sorption
coefficient values were found to vary among all the treatments. Their sensitivity in estimation in thefield, laboratory, and numerical studies is well known [33]. The dissolved P was found to interact
strongly with particulates, such as aluminosilicates (clays), metal oxides, and hydroxides, particularlyof iron (Fe) and aluminum (Al) [62], thus showing the high sorption potential. An increase inparticular treatments was assumed to be in response to adding the organic material (olive pomace orsewage sludge), which was confirmed to be the right approach in many studies [63–66]. In both soil
types, a minimal leaching potential was found, ranging from 0.03 to 0.05 mg cm-2 for the Terra Rosa
treatments and from 0.02 to 0.04 mg cm–2 for the Rendzina treatments (cumulative PO4-P flux). The
high sorption coefficient found in the Rendzina control (R_P: 52.83 cm3 g–1) can be associated with

Agronomy 2020, 10, 1163

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the higher values of organic C (6.1%). Also, as reported recently by [67], carbon-rich materials suchas biochars can increase the P adsorption affinity. Overall, the results showed a very poor P mobility
even at high P concentrations in the soil (e.g., a P+ amendment application rate). The modeling results
and Kd estimations corresponded well with the experimentally obtained P concentrations in theleachate, which were in the range from 0.01 to 0.04 mg L–1. Therefore, the results showed that the
majority of the P applied with the soil amendments was strongly adsorbed in the topsoil layer, even
if applied in elevated amounts. The same conclusion was obtained by, e.g., Elmi et al. [27], Naseri etal. [28], or Kadyampakeni et al. [25], who showed that 98% of the added P remained in approximately
the top 20 cm of the soil columns, indicating the low P mobility through the soil profile. As found by
previous researchers, biochar application improves soil quality and fertility for crop productivity,
providing ecosystem services such as the immobilization and transformation of contaminants [68]—in our case, P. Similar results are found for compost, which can result in an increased cation exchange
capacity and nutrient content—e.g., N, P, K, and Mg [69].

Rendzina

Terra Rosa

Table 7. Inversely estimated P sorption coefficients, Kd (cm3 g–1), in the Terra Rosa (T) and Rendzina(R) soils amended with biochar (B) or compost (C) produced from sewage sludge (SS) or olive pomace(OP) at two application rates, calculated on a P content basis (according to legislation, P; and a 10
times higher rate, P+), using HYDRUS-1D.

K
d
R
2

K
d
R
2

TBSS
_P

TBSS_
P+

TBOP
_P

TBOP_
P+

TCSS
_P

TCSS_
P+

TCOP
_P

TCOP_
P+

T_
P
29.9
8

35.13

53.68

27.27

22.51

28.34

26.48

26.23

23.07

37.5
7

0.99

0.98

0.98

0.99

0.98

0.95

0.96

0.92

0.99

0.96

RBSS
_P

RBSS_
P+

RBOP
_P

RBOP_
P+

RCSS
_P

RCSS_
P+

RCOP
_P

RCOP_
P+

28.38

21.24

44.89

R_
P
52.8
3

34.67

30.01

27.11

34.41

25.22

30.6
4

0.99

0.99

0.93

0.94

0.99

0.93

0.99

0.97

0.96

0.93

T_0

R_0

4. Conclusions
The addition of compost or biochar produced from sewage sludge or olive pomace at two P
application rates (low: 12 mg L–1; high: 120 mg L–1), calculated on a P content basis, slightly changed
the Terra Rosa and Rendzina soil hydraulic properties and influenced the P immobilization in thesoil. Compared to the control, the soil water retention increased with the majority of amendment
treatments, resulting in minor increases in the saturated water content and field capacity (for both
Terra Rosa and Rendzina soil). The time needed for the structure development and soil particle
settling, as well as the column scale at which this study was conducted, limited the apparent effectsof the amendments on the soil hydraulic conductivity. The soil hydraulic properties showed a reliable
fit when a modified van Genuchten model was used, which was also confirmed for water flow
modeling using HYDRUS-1D in a leaching experiment (R2 0.99). The results showed a high P sorption
capacity in all the amendment treatments, with a Kd ranging from 21.24 to 53.68 cm3 g–1, and a highreliability when an inverse modeling procedure was used to estimate the Kd (R2 0.93 - 0.99). Adding
sewage sludge or olive pomace composts or biochars at two application rates calculated on a P
content basis (according to legislation and a 10 times higher rate) improved the Terra Rosa andRendzina soil water retention and did not increase the P mobility in soil. The experiment showed aminimal P mobility even when P was applied in higher amounts through amendment additions, thus
not posing any environmental concerns. Contrary, it is indicative that organic amendments (compost
or biochar) improve soil properties it terms of nutrient retention as one of the ecosystem services.
Additional long-term field-scale experiments are needed to clarify further the full agricultural

Agronomy 2020, 10, 1163

17 of 20potential of these amendments and their effects on soil hydrology, as well as to confirm that the P
added with the amendments does not pose an environmental concern.
Author Contributions: Conceptualization, V.F., M.Č., M.R., I.P. (Igor Pasković), and I.P. (Igor Palčić);methodology, V.F., M.Č., M.R., and I.P. (Igor Pasković); software, V.F., and J.Š.; formal analysis, V.F., L.F., G.O.,
I.B., I.M., V.K., I.P., I.P., S.G.B., Z.U., and D.B.; data curation, M.Č., I.P. (Igor Pasković), I.P. (Igor Palčić), S.G.B,
Z.U., and D.B.; writing—original draft preparation, V.F., J.Š., L.F.,. I.B., I.M., and A.F.; writing—review andediting, V.F., J.Š., L.F., G.O., I.B., V.K., and D.A.R.; visualization, V.F. and V.K.; project administration, I.P. (Igor
Pasković) and I.P. (Igor Palčić); funding acquisition, D.B. All authors have read and agreed to the publishedversion of the manuscript.
Funding: This research was funded by the Croatian Science Foundation (HRZZ) Program for encouraging
research and development activities in the field of climate change, and The Environmental Protection andEnergy Efficiency Fund (contract No. PKP-2016-06-9041). David Robinson was supported by the Natural
Environment Research Council award number NE/R016429/1 as part of the UK-SCaPE program delivering
National Capability. The APC was covered by the Open Access Publication Fund, University of Zagreb Facultyof Agriculture.
Acknowledgments: The authors would like to thank the staff of the municipal companies for their cooperation
and assistance during the experiment set-up.
Conflicts of Interest: The authors declare no conflict of interest.

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