Modelling of potassium availability in agriculturalsoils by coupling HYDRUS-1D and PHREEQC
Charalampos Doulgeris*, Zacharenia Kypritidou, Vasiliki Kinigopoulou andEvangelos Hatzigiannakis
Hellenic Agricultural Organisation
Soil & Water Resources Institute (SWRI)*email: ch.doulgeris@swri.gr

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Introduction➢ Excessive and long-term of inorganic fertilization in agricultural soils cancause soil degradation, nutrient leaching and, consequently, groundwaterpollution and surface water eutrophication.
➢ Biochar, a promising organic fertilizer, is a carbon-rich solid material, formedby the thermal decomposition of biomass under conditions of a limited
presence or a complete absence of oxygen (pyrolysis).
➢ A lot of research efforts have emphasised the effect of biochar on soil andplants with respect to nutrient uptake; biochar application has a positiveeffect on the physicochemical and hydrodynamic properties of agriculturalsoils.
➢ However, in many assessments, either experimental or numerical ones,
nutrient availability and related hydrogeochemical processes are examinedin saturated soil moisture conditions.
➢ Is it sufficient to study nutrients release from biochar and their availability inagricultural soils under saturated conditions?

Objective
This work assess the availability of potassium in agricultural
soil/biochar mixtures under either saturated or unsaturated soil
moisture conditions, by examining either an equilibrium ion exchange
or a kinetic ion exchange release mechanism.

FERTICHAR project outcomesAssays prior to modelling
Loamy soil was collected from upper soil layer (0–20 cm) and fully mixed with biochar.
Soil/biochar mixtures: 0,5%, 1% και 2%Parameter

Value

Sand (%)

44.8

Silt (%)

29.6

Clay (%)

25.6

Soil Texture

LoamBiochar Fraction

7.07/10.3

in SoilpH of soil/biochar
Electrical conductivity (mS cm−1) ofsoil/biochar

0.38/7.56

Concentration of the exchangeable cations(in mg kg−1) of the biochar/soil mixtures

KNaCa

Mg

0%

159

48470

224

0.5%

196

52472

223

ESP (%) of soil/biochar

1.13/28.01%

232

57473

222

Οrganic matter (humified) (%)

2.122%

306

66

477221Οrganic carbon (%)

1.06

Biochar

7500

930

81867

CaCO3 equivalent (%)

0.48

Cation exchange capacity (cmol kg−1)

18.5

Wilting point at 15 atm (% w/w)

24.8

Field capacity at 0.3 atm (% w/w)

33.8

Bulk density (g cm−3)

1.63

Main physicochemical characteristicsof the agricultural soil

Conceptual model
Irrigation water mobilises
the water-soluble and exchangeable fraction ofions (K+, Na+, Ca2+, Mg2+)
from the solid phase of thesoil/biochar mixture andtransported downwards tothe soil column.

Ions/nutrients releasefrom soil/biochar.

4 approaches/simulations
equilibrium ion exchange(E.E. approach)saturatedconditions

unsaturatedconditions

kinetic ion exchange(K.E. approach)saturatedconditions

unsaturated
conditions

Water flow andgeochemicalprocessesComputational tools
Water flow (saturated/unsaturated) and mass transport𝜕θ
𝜕
=K h
𝜕t 𝜕z

𝜕h+1𝜕z

𝜕θci
𝜕
𝜕ci
𝜕qci=
θDi−+ Ri
𝜕t𝜕z
𝜕z
𝜕z

Source/sink term related to geochemical processes(equilibrium/kinetic ion exchange)

HYDRUS-1DPHREEQC➢ HP1 couples HYDRUS-1D with PHREEQC➢ Richards equation and mass transport equation are solved by HYDRUS-1D➢ Source/sink term is the key link between HYDRUS-1D and PHREEQC➢ PHREEQC (employing phreeqc.dat database) is called by HYDRUS-1D for thesimulation of geochemical processes➢ PHREEQC ensures that cations (K+, Na+, Ca2+, Mg2+) are in dynamic equilibrium
among soil solution and soil/biochar mixture. Cations’ exchange is simulated eitherwith the Equilibrium Exchange (E.E.) or the Kinetic Exchange (K.E.) approach.

Saturated/Unsaturated – Equilibrium/Kinetic➢ For saturated conditions, at the top and bottom of
the soil column a zero pressure head is applied➢ For unsaturated conditions, at the top of the soil
a water inflow is applied that represent typicalirrigation and rainfall of Northern Greece; at thebottom a free drainage condition is applied

Irrigation/rainfall at the top of soil column➢ The E.E. approach assumes that the exchangeable cations are in equilibrium withthe soil solution and that the ion exchange reactions mainly determine the cation
mobility within the soil/biochar mixture➢ The K.E. approach assumes a time-dependent release of cations from the solidsurface (e.g., dissolution reactions as well as exchange reactions) expressed as afirst-order reaction➢ In both approaches is considered that, the soil solution is in equilibrium withatmospheric CO2, and an amount of calcite exist initially, as estimated from CaCO3
equivalent in the soil

Time Step and Spatial Discretisation
Time step and number of finite element nodes were evaluated on the accuracy of themodel results under unsaturated flow conditions:➢ three values for the maximum time step (0.1/0.5/1 day) were tested, and➢ three discretisation schemes applied in the flow area (21/31/41 nodes).

Soil moisture variation at the bottom of soil column, for (a) different time steps (using 21nodes), and (b) different nodes (using dtmax = 1 day)E.E. for saturated/unsaturated conditions

Saturated flow

Unsaturated flow

Potassium release for the E.E. approach and different soil/biochar mixtures➢ Potassium is higher as biochar increases, and thus potassium in the lower part of theagricultural soil will be higher, and available for plant nutrition.
➢ For saturated flow conditions, we notice a rapid release of the total available
potassium in soil solution that is completed within 2 to 3 days.
➢ For unsaturated conditions, the release of potassium lasts until 55 to 70 days,depending on the amount of biochar in the soil.

Comparative evaluation
saturated vs unsaturated
K concentration
versus cumulative
water volume
K accumulated
mass

K release rate➢ the total released mass ofpotassium is practically thesame for the two different
water flow conditions (Fig. b)➢ released potassium is highly
dependent on thecumulative water volume
that outflows from the soilcolumn (Fig. a)➢ potassium is gradually
released into the soil
solution after each irrigation
for unsaturated conditions,in contrast to the rapid
release of total potassium
for saturated conditions in
the first days (Fig. c)

K.E. for saturated/unsaturated conditions

Saturated flow

Unsaturated flow

Potassium release for the K.E. approach and different soil/biochar mixtures➢ Similar to E.E. approach, a faster release of the total available potassium exists under saturatedconditions, compared to unsaturated conditions.
➢ For the K.E. approach, a considerably lower concentration of potassium exists and for a quite
longer period, compared to E.E. approach.
➢ For saturated conditions, potassium is released after 80 days (3 days in E.E. approach)➢ For unsaturated conditions it takes more than 5 years, (70 days in E.E. approach)➢ K.E. approach, apart from ion exchange, assumes also a kinetically controlled release due tointeractions occurring at the solid–solution interface.

Effect of rate constant in K.E. approach

Saturated flow

Unsaturated flow

Effect of different values of the rate constant (k) in potassium release➢ For higher values of the rate constant, the mass of potassium isreleased faster to the soil solution➢ Characteristic peaks appeared after each irrigation dose in the case of
unsaturated flow conditions

Conclusions➢ Coupling of HYDRUS-1D with PHREEQC was proven quite efficient to simulate
potassium release by soil/biochar mixtures.
➢ Potassium release from the top 20 cm of the soil is significantly affected by theproportion of biochar in the soil; potassium availability to plants increases for a higher
biochar dose.
➢ For unsaturated flow conditions, potassium is released gradually, while for saturatedconditions, the entire amount of potassium is released over a short time period.
➢ The simplification and adoption of saturated flow conditions (using only PHREEQC)
may lead to unrealistic estimates of nutrient availability in agricultural fields.
➢ K.E. approach estimates a significantly higher time for the total release of potassium,compared to the E.E. approach.
➢ Further experimental work will enlighten the prevailing geochemical mechanisms andwill decrease the uncertainty of the parameter estimation for K.E. approach.

THANK YOU FOR
YOUR ATTENTION

Any comments?
ch.doulgeris@swri.gr