Presentation by Dr. Veronika Ustohalova & Manuel Claus, BIOPROTA meeting, Munich, 13. - 14.05.2019

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TRANS-LARA
BMBF* - Joint Project
“Transport and transfer behaviour of long-lived radionuclides
along the causal chain groundwater-soil-surface-plant under
consideration of long-term climatic changes“
Veronika Ustohalova
Manuel Claus
BIOPROTA meeting
Munich, 13.- 14.05.2019
*Bundesministerium für Bildung und Forschung/Federal
Ministry of Education and Research

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Project Partners
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
funded by
coordination
Institute of Resource Ecology

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Main Tasks and Work Packages
Source picture: TRANSLARA Project Description
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
● Mechanisms of radionuclide
transport
groundwater →soil →plants
under long term climatic
changes
● Maintain competence and
promote young scientists in
safety research on final
disposal of radioactive
waste
● Focus on radionuclides Pu,
Tc, I, Se; also involved U,
Cm, Am

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Works of Project Partners: Interlinking Multiple
Experimental and Modeling Scales
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
Behavior of radionuclides in
the rhizosphere and their
interaction with the plasma
membrane of roots
Transport of radionuclides
into plant components
through ion-channels and
transport proteins
Redox behavior and speciation of
radionuclides in different soils and the
influence on the transfer in plants
Radionuclide transport in
soil: lysimeter experiments
and mezo-scale modeling
Modeling of speciation and
sorption of radionuclides in
soils depending on soil
parameters
Pedogenesis and soil
parameters under long-
term climate change,
radioecological biosphere
modeling

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Framework Soil Experiment Design and Modeling
(Öko-Institut+LUH IRS+Fsu AnGeo)
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
Boundary conditions Temperature and water
level fluctuation (ÖI)
Extrapolation climatic development (ÖI)
German Soil genesis (ÖI)
Soils to be investigated
(ÖI+LUH IRS+Fsu AnGeo)
Experiment design soil/plant
ÖI+LUH IRS+Fsu AnGeo)
Model of RN transport and transfer in shorter and
long term and relevant parameter (ÖI+P-Partner)
Database development: parameter values and approaches (ÖI)
Experiments Lysimeter (LUH IRS+Fsu AnGeo)
Modeling
PHREEQC –
Speciation+Smart
Kd (UB-IUP)

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Framework Plants Uptake of RN into and within plants
LUH-IRS/LUH-IfB/HZDR-IRE
Which plant metabolite transporters
are able to transport radionuclides into
the plants? (e.g. Cm/Am; U; Pu, Tc)
● LUH-IRS: Transfer factors of RNs
from the reference soils in selected
plants, RN root uptake and
interaction of RN with root exudates
● LUH-IfB/HZDR-IRE: RN-Transport
into he cells by Ionentransporter
und Ionenpumps / kinetics in
injected oocytes
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019

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Long-term climatic developments and soil genesis
Selection of the current and predicted soils to be
investigated in German regions above potential
repository sites (according to document K-MAT
21b of the Repository Commission)
● ArcGIS analysis of the most common soil
types (WRB/RefeSol system) above potential
repository sites -> two current soils to be
investigated + GW-Fluctuations
● Extrapolation warm / cold climate develop-
ment of repository sites regions and influence
on genesis of two selected current soils
● Identification of two predicted soils to be
investigated
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019 Source: Map of geological formations that are worth for investigating
(crystalline, clay, salt; from K-MAT 21b of the Repository Commission)
(AP1: Kooperation ÖI, LUH-IRS, FSU-AnGeo)

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RN: Tc, Pu, Am, I, Se, Np
Model
Hydraulic/Transport Model
lysimeter/shorter time scale
(months)
FSU Jena
Experiments under defined conditions
Interfaces Experiments/Modeling
Source Pictures: IRS Hannover, FSU Jena|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
Experiment Soil
Laboratory scale / lysimeter
(LUH-IRS, FSU Jena)
Water movement with GWL +
RN transport
Soil Parameter: KAK, Corg, pH,
Hydraulic Parameter: Kf, pf
Experiment Plant
micro and mesoscale (lysimeter)
(LUH-IRS/IfB)
RN transfer
content in various
plant components / cells
Hydraulic/Transport
RN transfer in plants
Resulting radiation exposure
Field/micro & long time scale
Öko-Institut
ECOLEGO tools:
1D Model: selected transport issues
M-C Sensitivity Analysis
RN transfer soil/plant
Radiation exposition tool
UB-IUPInterfacePHREEQC
+ Database

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Multiple processes and scales:
simplifications in time and space
Transport direction downwards
(percolation) or upwards
(capillary forces in pores):
RN accumulation in long time
Sources pictures: Öko-Institute.V., Flühler et al. 1998, Sitte et al. 2002|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
ground water
capillary water rise
evaporation
Plants: water
availability and
uptake
precipitation
plant transpiration
seepage
water
distance

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Upscaling the experimental scale
● Simplification: lysimeter scale → large scale
of planted agriculture area (retention curve
simplification)
● Consideration of layered soil profile
● Transfer soil-plant from tracer experiments
Sources pictures: FSU-AnGeo, IRS-LUH; Flühler, H.: Physik der Ungesättigten Zone,
ETH, 2004
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019

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Long term radionuclide transfer at field scale in
ECOLEGO: processes and model components
● Climate change and soil genesis:
defining soil types, horizons/layers
and schematization, parametrization
● Water flow: GW-level variation,
capillary effects, precipitation (FSU-
AnGeo / UB-IUP) → upscaling
● Radionuclide transport by soil water
(FSU-AnGeo/LUH–IRS) and
transfer to / within plants (LUH-IfB)
● Ingestions paths and Biosphere
Dose Conversion Factors
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
● Upscaling / suitable
averaging in time and
space
● Parameter data basis
development
● Parameter uncertainties –
Monte Carlo Analysis:
variation and probabilistic
functions

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ECOLEGO Model
Tools Transport & Water Flow & Plant Transfer
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
Transport
Waterflow
Longtermconsideration Radiation
exposureInput: Data Bank
Experiments/
M-C -Analysis
Source: Öko-Institut e.V.
Transfer in Plant

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Overall Compartment Model - Ingestions Paths and
Biosphere Dose Conversion Factors
Source: Öko-Institut presentation at the Trans-LARA meeting in HZDR|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
Transfer in plant
Waterflowvialayersofsoilhorizon
Transportthroughlayersofsoilhorizon
Exposureviatransferpaths

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Vielen Dank für Ihre Aufmerksamkeit!
Thank you for your attention!
Haben Sie noch Fragen?
Questions are welcome! ?

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|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
Contact
Manuel Claus
Öko-Institut e.V.
Office Darmstadt
Rheinstraße 95
64295 Darmstadt
phone: +49 6151-8191-143
e-Mail: m.claus@oeko.de
Dr. Veronika Ustohalova
Öko-Institut e.V.
Office Darmstadt
Rheinstraße 95
64295 Darmstadt
phone: +49 6151-8191-151
e-Mail: v.ustohalova@oeko.de

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Governing parameters of Soil-Water-Retention curve
Sources: Flühler, H. Roth, K.: Physik der Ungesättigten Zone, ETH, 2004; Likos et all.: Hysteresis and
Uncertainty in Soil Water-Retention Curve Parameters, Journal of Geotechnical and Geoenvironmental
Engineering, © ASCE, 2013
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
● Richards Equation:
● Hydraulic soil characteristic: water
retention curve as relation
between water content θ and
water potential /suction pressureΨ
(pF curve) in dependence on pore
size distribution
● Water diffusivity: hydraulic
conductivity K at a given water
content θ multiplied by slope of
relationship between suction
pressure and water content D(θ)
= K(θ)dh/dθ
● Relation between water content
and water conductivity K
𝜕𝜕θ
𝜕𝜕𝑡𝑡
=
𝜕𝜕
𝜕𝜕𝑥𝑥
𝐷𝐷(θ)
𝜕𝜕θ
𝜕𝜕𝜕𝜕
−
𝜕𝜕𝐾𝐾 𝜃𝜃
𝜕𝜕𝜕𝜕
−W

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Transport: Finite Volume Method
i-1
i
i+1
𝐴𝐴 𝑡𝑡 = 0 = 𝐴𝐴0[𝐵𝐵𝐵𝐵]
∆𝐴𝐴𝑖𝑖
∆𝑡𝑡
=
𝑞𝑞
𝑅𝑅∆𝑥𝑥
𝐴𝐴𝑖𝑖−1 − 𝐴𝐴𝑖𝑖
∆𝐴𝐴𝑖𝑖
∆𝑡𝑡
= −
𝐷𝐷𝑒𝑒𝑒𝑒𝑒𝑒
𝑅𝑅(∆𝑥𝑥)2
𝐴𝐴𝑖𝑖+1 + 2𝐴𝐴𝑖𝑖 − 𝐴𝐴𝑖𝑖−1
𝑁𝑁
∆𝑥𝑥
∆𝑥𝑥
𝐿𝐿
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA
Munich|13.05.2019
Source: Öko-Institut e.V.
𝐴𝐴 … 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 [𝐵𝐵𝐵𝐵]
𝜕𝜕𝑐𝑐
𝜕𝜕𝑡𝑡
=
𝜕𝜕
𝜕𝜕𝑥𝑥
𝐷𝐷𝑒𝑒𝑒𝑒𝑒𝑒
𝑅𝑅
𝜕𝜕𝑐𝑐
𝜕𝜕𝜕𝜕
−
𝑞𝑞
𝑅𝑅
𝜕𝜕𝜕𝜕
𝜕𝜕𝜕𝜕
− 𝜆𝜆𝜆𝜆

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Symbols
● 𝑅𝑅 = 1 +
𝜌𝜌
𝜃𝜃
𝐾𝐾𝑑𝑑
𝑅𝑅 … 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 −
𝜃𝜃 … 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 (𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐) [−],
𝜌𝜌 … 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 [𝑘𝑘𝑘𝑘 𝐿𝐿−1]
𝐾𝐾𝑑𝑑 … 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 [𝐿𝐿 𝑘𝑘𝑔𝑔−1]
● 𝐷𝐷𝑒𝑒𝑒𝑒𝑒𝑒 =
𝐷𝐷𝜃𝜃𝛿𝛿
𝜏𝜏
𝐷𝐷𝑒𝑒𝑒𝑒𝑒𝑒 … effective Diffusion m2d−1
𝐷𝐷 … molecular Diffusion m2d−1
𝜏𝜏 … 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 [−],
𝛿𝛿 … 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 [−],
● 𝑁𝑁𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 =
𝐿𝐿 𝑞𝑞
𝐷𝐷𝑒𝑒𝑒𝑒𝑒𝑒
𝑁𝑁𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 … 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁
𝐿𝐿 … 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝑜𝑜𝑜𝑜 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
𝑞𝑞 … 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 [𝑚𝑚 𝑑𝑑−1]
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019

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Water Movement (Richards Equitation):
Finite Volume Method
i-1
i
i+1
𝐴𝐴 𝑡𝑡 = 0 = 𝐴𝐴0[𝐵𝐵𝐵𝐵]
∆ϴ𝑖𝑖
∆𝑡𝑡
= 𝐾𝐾(θ)𝑖𝑖+1 − 𝐾𝐾(θ)𝑖𝑖
𝑁𝑁
∆𝑥𝑥
∆𝑥𝑥
𝐿𝐿
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA
Munich|13.05.2019
Source: Öko-Institut e.V./ Finite Volume Method adapted by considering Wei Mao et
al.: An efficient soil water balance model based on hybrid numerical and statistical
methods, Journal of Hydrology, 2018
𝜕𝜕θ
𝜕𝜕𝑡𝑡
=
𝜕𝜕
𝜕𝜕𝑥𝑥
𝐷𝐷(θ)
𝜕𝜕θ
𝜕𝜕𝜕𝜕
−
𝜕𝜕𝐾𝐾 𝜃𝜃
𝜕𝜕𝜕𝜕
−W
∆ϴ𝑖𝑖
∆𝑡𝑡
= −
1
(∆𝑥𝑥)2
𝐷𝐷(θ)𝑖𝑖+1/2ϴ𝑖𝑖+1 + 2𝐷𝐷(θ)𝑖𝑖ϴ𝑖𝑖 − 𝐷𝐷(θ)𝑖𝑖−1/2ϴ𝑖𝑖−1

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Symbols
● θ … water content [𝑚𝑚3/𝑚𝑚3]
● ϴ … water content in a finite volume / compartment [mm]
● 𝐾𝐾 θ = 𝐾𝐾𝑠𝑠
θ−θ𝑓𝑓
θ𝑠𝑠−θ𝑓𝑓
…unsaturated hydraulic conductivity,
where parameters for each soil layer are
‒ 𝐾𝐾𝑠𝑠 … 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 ℎ𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 [
𝑚𝑚
𝑑𝑑
]
‒ θ𝑓𝑓 … field capacity [𝑚𝑚3/𝑚𝑚3]
‒ θ𝑠𝑠 … saturated water content [𝑚𝑚3/𝑚𝑚3]
● 𝐷𝐷 θ … Matrix Diffusion [𝑚𝑚2/𝑑𝑑], derived from an auxiliary function (see ref.1)
● W…the source/sink term [d-1] to account for soil evaporation and root uptake
term of crop transpiration (estimated as reference evapotranspiration
according to Penman-Monteith, see ref. 2)
1) Wei Mao et al.: An efficient soil water balance model based on hybrid
numerical and statistical methods, Journal of Hydrology, 2018
2) http://www.fao.org/3/X0490E/x0490e08.htm#TopOfPage
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019

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Exemplifying results (1)
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
0
5
10
15
20
25
0
8
16
24
32
40
48
56
64
72
80
88
96
104
112
120
128
136
144
152
160
168
176
184
192
200
208
216
224
232
240
248
256
264
272
280
288
296
304
312
320
328
336
344
352
360
[mm/d]
days
Precipitation
Evapotranspiration
percolation in loam
● Precipitation

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Preliminary results (1)
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
-0,01
-0,005
0
0,005
0,01
0,015
0,02
0,025
0,03
0 50 100 150 200 250 300 350
m/d
days
capillary potential 4,3
capillary potential 3,4
percolation 3 (loam),4 (clay-loam)
capillary flow 3 (loam), 4 (clay-loam)

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Preliminary results (2)
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019
0
200
400
600
800
1000
1200
0 50 100 150 200 250 300 350 400
Bq[I-129]
Tage
Layer_E_Clay.Activity_total[I-129][Water]
Layer_D_ClayLoam.Activity_total[I-129][Water]
Layer_C_Loam.Activity_total[I-129][Water]

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Typical Analysis: DCC in Sv for I-129 per Bq/m³ GW
|Ustohalova/Claus|TRANS-LARA|Meeting BIOPROTA Munich|13.05.2019