P O S I V A O Y
O l k i l u o t o
F I -27160 EURAJOKI , F INLAND
Te l +358-2-8372 31
Fax +358-2-8372 3709
Tuomo Karvonen
December 2009
Work ing Repor t 2009 -128
Hydrological Modelling in Terrain andEcosystem Forecasts 2009
(TESM-2009)
December 2009
Working Reports contain information on work in progress
or pending completion.
The conclusions and viewpoints presented in the report
are those of author(s) and do not necessarily
coincide with those of Posiva.
Tuomo Karvonen
W a t e r H o p e
Work ing Repor t 2009 -128
Hydrological Modelling in Terrain andEcosystem Forecasts 2009
(TESM-2009)
Base maps: ©National Land Survey, permission 41/MML/09
Hydrological modelling in Terrain and Ecosystem Forecasts 2009 (TESM-2009)
ABSTRACT
The Finnish nuclear waste disposal company, Posiva Oy, is planning an underground
repository for spent nuclear fuel to be constructed on the island of Olkiluoto on the
south-west coast of Finland. This study is part of the biosphere assessment (BSA)
within the safety case for the repository. For simulating the land uplift driven or other
changes in the biosphere a GIS toolbox named UNTAMO has been developed. The
Olkiluoto surface hydrological model uses raster files created by the UNTAMO-toolbox
as model input data.
Transport of radionuclides from sediment-bedrock interface to surface waters or root
zone in forest, agricultural or wetland areas were computed using the particle tracking
algorithm. Initial location of radionuclides was taken from the radionuclide release and
transport analysis RNT-2008. Both in 1 000 and 10 000 year cases majority of radio-
nuclides will be in lake/sea nodes after the computation period: 71.5 % in the 1 000
year case and 61 % in the 10 000 year case. 5.4 % of the radionuclides ended to root
zone in the 1 000 year case and the corresponding value was 1.7 % for the 10 000 year
case.
Based on the UNTAMO forecasts, continuous and sufficiently homogeneous segments
of the modeled area, possibly receiving any radionuclides released from the repository,
have been identified. These segments are called biosphere objects. Olkiluoto surface
hydrological model was used to calculate the vertical and horizontal fluxes for the
biosphere objects. Average measured value for stand throughfall in FIP-areas (Forest
Intensive monitoring Plot) was 399 mm a-1
and measured interception was 160 mm a-1
.
The average values computed in this study for biosphere forest objects were 417 mm a-1
for throughfall and 131 mm a-1
for interception. Measured transpiration in the FIP-areas
was between 160 and 220 mm a-1
. Average transpiration rate computed for the
biosphere objects was 200 mm a-1
(range 175-233 mm a-1
).
The main goal of the sensitivity and uncertainty analysis was to recognize the most
important factors that need to be studied in future biosphere assessments. The relative
concentration of solutes (radionuclides) in the root zone was the main criteria for
evaluating how sensitive and uncertain the model results are for different parameters.
The main factors that influence solute concentration profile in the biosphere forest
objects are stream density, horizontal hydraulic conductivities in overburden soils,
distribution of precipitation to throughfall, interception and transpiration, discharge
through bedrock interface and thickness of the overburden profile. In biosphere
cropland objects the results are most sensitive to drainage density, horizontal hydraulic
conductivities in overburden soils, transpiration and discharge through bedrock
interface.
Keywords: Radionuclide, biosphere, assessment, surface hydrology, particle tracking,
water flux, transpiration, interception, surface runoff, soil moisture
Olkiluodon pintahydrologian mallin käyttö maasto- ja ekosysteemiennusteiden laadinnassa (TESM-2009)
TIIVISTELMÄ
Posiva Oy suunnittelee loppusijoituslaitoksen rakentamista käytetylle ydinpolttoaineelle
Eurajoen Olkiluodon kallioperään. Tämä raportti on osa biosfäärianalyysiä, joka liittyy
yhtenä osana Posivan turvallisuusperusteluihin. Olkiluodon pintahydrologian malli
käyttää lähtötietoina maasto- ja ekosysteemiennusteiden laadintaan kehitetyn GIS-
työkalun UNTAMO tuottamia korkeus-, maalaji-, kerrospaksuus- ja uomarastereita.
Partikkelien kulkeutumismallilla laskettiin radionuklidien liikeradat kallion ja maa-
kerrosten rajapinnasta joko pintavesiin, metsä- ja peltoalueiden juuristokerrokseen tai
soiden pintakerrokseen. Liikeratojen alkupaikat saatiin radionuklidien vapautumis- ja
kulkeutumisanalyysin RNT-2008 tuloksista. Suurin osa partikkeleista kulkeutui
pohjasedimenttien kautta joko meriin tai järviin: 71.5 % 1 000 vuoden ja 61 % 10 000
vuoden laskentatapauksessa. 5.4 % radionuklideista kulkeutui juuristokerrokseen 1 000
vuoden ja 1.7 % 10 000 vuoden laskentatapauksessa.
Olkiluodon saarelta ja sen lähialueelta eroteltiin UNTAMO-mallilla maankäytöltään
yhtenäisiä ja riittävän homogeenisia alueita (biosfääriobjektit), joille loppusijoitustilois-
ta mahdollisesti vapautuvat radionuklidit voivat kulkeutua. Olkiluodon pintahydro-
logian mallilla laskettiin näiden alueiden vesitase, sekä veden virtaukset vaaka- ja
pystysuunnassa. Biosfääriobjektien laskettuja vesitasekomponentteja voitiin verrata
FIP-alueiden (Forest Intensive monitoring Plot) mitattuihin arvoihin. Mitattu sadanta
kasvuston alapuolella oli keskimäärin 399 mm a-1
ja vastaava laskettu arvo oli
metsäobjekteille 417 mm a-1
. Mitattu latvustopidäntä oli 160 mm a-1
ja mallilla laskettu
keskimääräinen arvo oli 131 mm a-1
. Metsäalueiden mitatun transpiraation vaihteluväli
oli 160 – 220 mm a-1
ja laskettu transpiraatio oli keskimäärin 200 mm a-1
(vaihteluväli
175 – 233 mm a-1
).
Herkkyys- ja epävarmuustarkastelun keskeisin tavoite oli kartoittaa ne hydrologisen
mallin lähtötiedot ja parametrit, joiden arviointiin on syytä keskittyä tulevissa biosfääri-
analyyseissä. Herkkyys- ja epävarmuusanalyysissä käytettiin tärkeimpänä kriteerinä
mallilla laskettua juuristokerroksen liukoista konsentraatiota (radionuklidipitoisuutta).
Metsäalueilla radionuklidien kulkeutumiseen vaikuttavat tärkeimmät tekijät ovat uoma-
tiheys, vaakasuuntainen vedenläpäisevyys maakerroksissa, transpiraatio, veden virtaus-
nopeus kallioperän ja maakerrosten rajapinnassa, sekä maakerrosten paksuus. Pelto-
alueilla juuristokerroksen konsentraatioon vaikuttavat voimakkaimmin ojaväli ja oja-
syvyys, vaakasuuntainen vedenläpäisevyys maakerroksissa, transpiraatio ja veden
virtausnopeus kallioperän ja maakerrosten rajapinnassa.
Avainsanat: Radionuklidi, biosfääriarviointi, pintahydrologia, partikkelien kulkeutu-
minen, maaveden virtaus, transpiraatio, latvustopidäntä, pintavalunta, maankosteus
1
TABLE OF CONTENTS
ABSTRACT TIIVISTELMÄ
1 INTRODUCTION ................................................................................................ 3
1.1 Safety case ................................................................................................... 3 1.2 Biosphere assessment ................................................................................... 3 1.3 Scope of the present report. ........................................................................... 4
2 MATERIAL AND METHODS ............................................................................... 7 2.1 Input data provided by UNTAMO-toolbox ....................................................... 7 2.2 Meteorological input data ............................................................................... 7 2.3 Site dependent input data for surface hydrological modelling ......................... 8 2.4 Input data for transport of radionuclides. ...................................................... 14 2.5 Delineation of biosphere objects. ................................................................. 15 2.6 Description of the surface hydrological model .............................................. 19 2.7 Description of the solute transport models ................................................... 20
3 RESULTS ......................................................................................................... .25 3.1 Particle transport from bedrock to surface waters ....................................... 25 3.2 Vertical and horizontal water fluxes in biosphere objects ............................ 32 3.3 Soil water content in biosphere objects ....................................................... 43
4 SENSITIVITY AND UNCERTAINTY ANALYSIS. ............................................... 45 4.1 Introduction ................................................................................................. 45 4.2 Biosphere forest objects. ............................................................................. 45 4.3 Biosphere cropland objects. ......................................................................... 49 4.4 Other biosphere objects .............................................................................. .51
5 SUMMARY ...................................................................................................... .53 REFERENCES .......................................................................................................... 57 APPENDIX A: Parameter values used in the models ................................................. 63 APPENDIX B: Description and code verification of the solute transport model............ 67
2
3
1 INTRODUCTION
Posiva Oy (Posiva) is responsible for implementing a final disposal program for spent
nuclear fuel from the five Finnish nuclear power reactors. The spent nuclear fuel is
planned to be disposed of in a KBS-3 type of repository to be constructed at a depth of
about 400 meters in the crystalline bedrock at the Olkiluoto site. The Finnish Parliament
ratified in 2001 the Government’s favorable Decision in Principle on Posiva’s
application to locate a repository at Olkiluoto. This decision represents the milestone
prior to entering the phase of confirming site characterization (Posiva 2008; Hjerpe et
al. 2010). This study has been funded by Posiva and supervised by Ari Ikonen on behalf
of the company. The study is part of the biosphere assessment (Hjerpe et al. 2010)
within the safety case for the spent nuclear fuel repository.
1.1 Safety case
Posiva is currently producing a safety case to support the construction license
application for a KBS-3 type of repository at the Olkiluoto site. A safety case is a
synthesis of evidence, analyses and arguments that quantify and substantiate the safety,
and the level of expert confidence in the safety, of a geological disposal facility for
radioactive waste (IAEA 2006, NEA 2004, Hjerpe et al. 2010). Posiva's plan for the
safety case was initially prepared in 2004 (Vieno & Ikonen 2005), and has recently been
revised (Posiva 2008).
1.2 Biosphere assessment
A vital component when producing the safety case is the biosphere assessment (BSA).
The overall aims of the biosphere assessment in the safety case are to describe the
present, future and relevant past conditions at, and prevailing processes in, the surface
systems of the Olkiluoto site, model the transport and fate of radionuclides
hypothetically released from the repository through the geosphere to the surface
environment, and assess possible radiological consequences to humans and other biota
(see Figure 1-1). Conducting biosphere assessment has conceptually been implemented
as a process divided into five main sub-processes, or components (Hjerpe et al. 2010):
Biosphere description process – performing environmental studies and
monitoring, and the compilation of a description of the present properties and
on-going processes at the Olkiluoto site; this is the main activity in.
Terrain and ecosystems development process – predicting the development of
the topography, overburden, hydrology, flora and fauna at the site. This is called
forecasting and is carried out by terrain and ecosystems development modelling
(TESM).
Landscape model set-up process – defining the landscape model, which is a site-
specific state-of-the-art coupled time-dependent radionuclide transport model.
Radionuclide transport modelling process – defining the ecosystem-specific
radionuclide transport models underlying the landscape model, and analyse the
release of radionuclides resulting from the geosphere modelling. A screening
4
approach is first applied, to screen out radionuclides that have insignificant
radiological consequences.
Radionuclide consequence analysis process – assessing potential radiological
consequences to humans and other biota and putting them into the context of
regulatory requirements.
Radiological
consequence
analysis
Radionuclide
transport
modelling
Landscape
model set-up
Terrain &
ecosystem
development
Biosphere
description
Integration of site dataProcesses Forecasting Transport modelling Compliance assessment
Safety indicators
Outcome
BIOSPHERE
ASSESSMENT
CLIMATIC ENVELOPE
Surface hydrological modelling
Groundwater flow
modelling
Near-field modelling
Geosphere modelling
Env. studies Monitoring
Stylizedrelease pattern
Figure 1-1. Stylized illustration of the Biosphere assessment process. The five major
components are marked in bold; the main activities (bold text under the components)
are indicated by colours in the components. Selected key inputs and links are also
included, especially regarding hydrological modelling (adapted from Hjerpe et al.
2010).
1.3 Scope of the present report
The surface hydrological model described in this report is aimed at providing links
between Terrain and ecosystems development and Landscape model set-up components
of the BSA as illustrated in Figure 1-1. For simulating the land uplift driven or other
changes in the biosphere until and beyond the time when the potential releases would
reach it, a GIS toolbox named UNTAMO has been developed (Ikonen et al. 2010b).
The Olkiluoto surface hydrological model (Karvonen 2008, 2009a-b) uses raster files
created by the UNTAMO-toolbox as model input data.
Based on the UNTAMO forecasts, continuous and sufficiently homogeneous segments
of the modeled area, possibly receiving any radionuclides released from the repository,
have been identified (Hjerpe et al. 2010). These segments are called biosphere objects.
The possible release paths from the repository to the biosphere objects have been
identified based on deep groundwater modeling (Nykyri et al. 2008) and surface
hydrology modeling (this report). The biosphere object delineation process has been
described in detail in Hjerpe et al. (2009). It should be noted that this report has not
been intended to be fully stand-alone but to be digested together with the other
biosphere assessment documentation, especially (Hjerpe et al. 2010).
The contents of this report can be summarized as follows:
take input data provided by the UNTAMO toolbox in Terrain and ecosystems
development component
5
compute vertical and horizontal water fluxes and soil water content for the
whole computational area using the Olkiluoto surface hydrological model
compute radionuclide transport from the interface between bedrock surface and
overburden soils or sediments to surface waters or root zone
compute areally averaged vertical and horizontal fluxes and soil moisture
contents for biosphere objects delineated in Hjerpe et al. (2009); these fluxes are
used as input data in the Radionuclide transport modelling process
compute fluxes for years 2020, 2520, ... 12520 (in 500 year interval) using input
data provided by the UNTAMO toolbox
6
7
2 MATERIAL AND METHODS Olkiluoto is an island (currently approximately 12 km
2) on the coast of the Baltic Sea,
separated from the mainland by a narrow strait. The predicted conditions for the surface environment at year 2020, upon the emplacement of the first canister, define, in this context, the initial state of the biosphere. This is the starting point for the landscape modelling (Hjerpe et al. 2010). The predictions are based on the forecast resulting from the terrain and ecosystem modelling, UNTAMO toolbox (Ikonen et al. 2010b) and surface hydrology modelling; in turn based on the latest available site-specific data and models, such as the terrain (elevation) model (Pohjola et al. 2009), the land uplift model (Vuorela et al. 2009) and the ecosystem models describing the present surface environment (Haapanen et al 2009). 2.1 Untamo toolbox
The terrain and ecosystems development modelling (TESM) was carried out using the
GIS toolbox UNTAMO, which consists of following main parts (Ikonen et al. 2010b,
Hjerpe et al. 2010):
Land uplift and delineation of the sea area,
Surface water bodies,
Terrestrial and aquatic erosion,
Accumulation of organic matter,
Terrestrial vegetation,
Aquatic vegetation,
Fauna habitats,
Human settlement and land use, and
Simulation control.
The surface hydrological models used in this study (Karvonen 2008, Karvonen 2009a-
b) take the spatial and temporal data needed in the model from the rasters provided by
the UNTAMO toolbox. The computational grid was created automatically from the
input rasters produced by UNTAMO: soil surface elevation, thickness of overburden
layers, bedrock elevation and soil type of overburden layers. The boundary conditions
needed in the model come also from UNTAMO-toolbox: location of coastal areas, lakes
and stream network. The terrain and ecosystem forecasts were carried out for years
2020, 2520, ... 12520 (in 500 year interval). The grid size of the rasters produced by
UNTAMO toolbox was 10x10 m2.
2.2 Meteorological variables
Meteorological observations are mandatory for a nuclear power plant in order to assess
possible effects of discharges mainly in a potential accident situation, thus a
comprehensive database of major meteorological parameters is available. Currently
Olkiluoto has a continental climate, with some local marine influence due to its location
on the eastern coast of the Bothnian Sea, which is north of the Baltic proper. The long-
term statistics for Olkiluoto and the reference sites have been given by Ikonen (2007).
8
Within the forest intensive monitoring plots (FIP4, 10 and 11) stand meteorological
measurements are recorded once an hour (Haapanen 2008, Karvonen 2009b). The
parameters are air temperature, minimum and maximum temperature inside the crown
layer and above the canopy, relative humidity, precipitation (1 m above ground level),
soil moisture content, and soil temperature. Depth of ground frost and the thickness of
the snow cover are measured manually on FIP4. Photosynthetically active radiation
(PAR), solar radiation, air pressure, wind speed and its direction are measured only on
FIP4. The detailed data provided forest intensive plots were used in estimating
interception and transpiration components of forest canopy (Karvonen 2009b).
All the simulations were carried out using the ―Present climate scenario‖ (Hjerpe et al.
2010) indicating that climate remains unchanged during dose assessment time window.
Other climate scenarios are to be treated in future assessments.
2.3 Site dependent input data for surface hydrological modeling
The rasters created by UNTAMO toolbox in the 10x10 m2 grid were used as input data
to the surface hydrological models of the present study.
Soil surface elevation
The site is located in an area of significant continuing postglacial land uplift (currently
approximately 6–6.8 mm/y; Eronen et al. 1995, Kahma et al. 2001). This leads to new
land areas continuously emerging. The effects of this process are accentuated by a rather
flat topography and anthropogenic eutrophication of the Baltic Sea, which increases
primary production, and consequently accumulation of organic matter especially in
shallow bays. In the archipelago area south-southwest of Olkiluoto, relatively early
emergence of smaller-scale lake and river systems is expected. Another important factor
for the development of the landscape is a large river (Eurajoki), which has its outlet
northeast of the island. It is expected that this river will flow north of the planned
repository in the future. This will significantly affect the mass balances within the
region arising from erosion and sedimentation processes (Ikonen et al. 2010a, Hjerpe et
al. 2010).
The influence of land uplift on soil surface elevation, extent of sea areas and location of
lakes and rivers is shown in Figure 2-1 for six different time points: present day, 1 000,
2 000, 4 000, 8 000 and 10 000 years after start of operation, i.e. years 2 020, 3 020, 4
020, 6 020, 10 020 and 12 020. Present island boundaries are shown in all graphs. The
highest and lowest surface elevation for each time point are given in the graphs. The
lowest value represents sea bottom elevation. The flow accumulation raster produced
by the UNTAMO toolbox was used to delineate the location of streams. Moreover,
UNTAMO predicts the location and average water level of lakes that will be formed in
large depressions indicated by the flow accumulation rasters (Ikonen et al. 2010b).
9
a) Present day
b) Year 3020
c) Year 4020
Figure 2-1.a)-c). Influence of land uplift on soil surface elevation, extent of sea areas
and location of lakes and rivers. Present island boundaries are shown in all graphs. a)
Present day, b) year 3020 and c) year 4020.
10
d) Year 6020
e) Year 10020
f) Year 12020
Figure 2-1.d)-f). Influence of land uplift on soil surface elevation, extent of sea areas
and location of lakes and rivers. Present island boundaries are shown in all graphs. d)
year 6020, e) year 10020 and f) year 12020.
11
Soil type and land use classification
Finland is located on a stable and old bedrock area (Fennoscandian Shield) and its relief
is mainly determined by the bedrock. Sandstones, Rapakivi granites and volcanic-
sedimentary rocks are typical of Southwestern Finland. The sediments, in turn, have
mainly been formed during the Quaternary period when continental ice sheets
repeatedly covered the northern Europe. In Southwestern Finland, the glacial till is
sandy. Clay soil types cover about one-third of the soils. Also rock outcrops are typical
of the coastal landscape. The Baltic Sea and its gulfs occupy a depression in the
Fennoscandian Shield. Thus, the bedrock and the landforms are very similar on both the
sea bottom and the adjacent land (Hjerpe et al. 2010).
Finland belongs mainly to boreal coniferous forest zone with cool-temperate, moist
climate, short growing season and wintertime snow cover. Due to the climate, soil types
and also consequently low population pressure, the landscape is dominated by forests
and mires. Southwestern Finland belongs into the raised bog zone. Most of the mires
there have been initiated on land uplift shores (primary mire formation) and are in
various stages developing into ombrotrophic conditions. The most common soil types
in Olkiluoto Island are fine-textured and sandy till. Soils are on average acid, except for
the alder stands growing near seashores on clayish soils. The forests in Olkiluoto are
growing on slightly more fertile sites than in Southwestern Finland. There is also a
greater amount of Norway spruce and deciduous species in Olkiluoto, mainly due to the
higher fertility of the soils and the great proportion of coastline. Black alder typically
forms a belt right behind the treeless shore vegetation zones. Pine is more common in
the younger age classes (Hjerpe et al.2009).
Top soil type classification was made based on the present-day data and extended to
future conditions. Accumulation of organic material is modelled for reed beds and
wetlands. The peat growth is simulated with the model of Clymo (1984), based on
productivity-driven accumulation constrained by the hydrology (summer droughts) and
the decay in deeper layers (Ikonen et al. 2010a). In addition to these modules for
organic material accumulation, thickness of the humus layer is predicted by the
vegetation modules. In the simulation of the vegetation on upland soils, vegetation stand
classes are formed based on the differences of fertility of soil types (Haapanen et al.
2009).
Examples of top soil classification maps produced by UNTAMO toolbox are shown in
Figure 2-2 for the present condition and 10 000 years after start of operation (year
12 020). The most notable difference between the present-day data and future
conditions is the increase in the area covered by the peat soils.
As land use types, at the moment only locations of croplands are identified based on the
generic soil suitability for the purpose and the preference in the region at present
(Ikonen 2007). The correspondence used in the surface hydrological model between top
soil type and future land use type is given in Table 2-1.
12
a) Present day (year 2 020)
b) 10 000 years after start of operation (year 12 020)
Figure 2-2. Top soil type classification based on UNTAMO toolbox. a) Present day
(initial state), b) 10 000 years after start of operation (year 12 020).
13
Table 2-1. The correspondence between top soil type and future land use type (Ikonen
2007).
Thickness of overburden soils and elevation of bedrock surface
The input data needed by the surface hydrological models include bedrock elevation and
thickness and type of overburden soils. UNTAMO toolbox provides output rasters that
include the thickness of the overburden profile for different soil types (one band for
each soil type). These rasters were combined into soil thickness (see Figure 2-3) and
type of bottom soil data.
Figure 2-3. Example of soil profile thickness map produced by UNTAMO toolbox:
10 000 years after start of operation (year 12 020).
14
Boundary conditions
Lakes, rivers and their catchment areas are identified in UNTAMO toolbox using
standard GIS (geographical information system) processing tools. Sea and lake water
levels are used as areas where hydraulic head is known (Dirichlecht type boundary
condition). Flow accumulation raster is used to delineate the location of streams and all
stream pixels are used as sink points: water flows from land areas to streams if water
level in the surrounding cell is greater than the bottom elevation of river/stream. The
river depth data estimated in UNTAMO toolbox is used to compute the bottom
elevation of the river.
2.4 Input data for transport of radionuclides
The radionuclide release and transport analysis RNT-2008 (Nykyri et al. 2008) presents
the results from the release of radionuclides from spent nuclear fuel to their arrival in
the interface between bedrock surface and overburden soils or sediments. RNT-2008
results include computation of flow paths of around 39 000 radionuclide particles
released from different panels in the final repository area and cases 1 000 and 10 000
years after start of operation. The starting locations of migration paths are divided into
six separate panels. Figure 2-4 shows a map of Olkiluoto and six groups of flow path
starting locations. The three western panels are located in the WCA (well characterized
area), below the major hydro-structure HZ20. The three eastern panels are located
outside of the WCA, above the structure HZ20. All the starting locations are placed 420
m below ground surface. It needs to be pointed out that panels 3, 4 and 6 are at this
stage only tentative for possible extension of repository to the eastern area. Panels 3, 4
and 6 are not based on any existing layout unlike panels 1, 2 and 5, which do have a
layout plan.
Nykyri et al. (2008) have studied the geometry of the flow paths starting from each
panel by particle tracking for the model-top boundary conditions representing the water
table both at 1 000 years and at 10 000 years after start of operation. According to
Nykyri et al. (2008) the geometry of the flow paths does not vary much between the
realisations. The discharge locations are governed by the lineaments that surround
Olkiluoto. There is only a little mixing between the flow paths starting from different
panels. The discharge locations at the ground surface disperse over a wide area,
although they are originated in a very limited area of the starting points at the repository
level (see Figure 2-5). Changes in the water table caused by land up-lift do not influence
on the geometry of flow paths. The flow path simulations for 1 000 years and 10 000
years after start of operation give similar type of results. In general, the geometry of the
flow paths is also quite similar in different realizations (Nykyri et al. 2008).
The RNT-2008 (Nykyri et al. 2008) analysis does not take into account the influence of
overburden soils on radionuclide flow paths and travel times: the end points of the
RNT-2008 flow paths are at the interface between bedrock surface and overburden
soils. The aim of the computations described in this report is to calculate the transport of
radionuclides (pathways) from sediment-bedrock interface to surface waters or root
zone in forest, agricultural or wetland areas (see section 3.1). The end point location of
15
Figure 2-4. Starting locations of the flow paths are grouped to six different panels. The
panels 1, 2 and 5 are located below the major hydro-structure HZ20 and the panels 3, 4
and 6 are above HZ20 (data from Nykyri et al. 2008). Present boundaries of Olkiluoto
Island are shown in the graph.
the radionuclide flow paths from RNT-2008 computation are used as the initial data for
the surface hydrological model.
2.5 Delineation of biosphere objects
The predicted conditions for the surface environment at year 2020, upon the
emplacement of the first canister, define, in this context, the initial state of the
biosphere. This is the starting point for the set-up of the landscape model. Based on the
forecasts, the biosphere objects are identified (delineated). A biosphere object represents
a continuous and sufficiently homogeneous segment of the modelled area, possibly
receiving any radionuclides released from the repository. To identify the biosphere
objects, the release pattern is determined. The release pattern is a stylized representation
of the geosphere release paths in to the biosphere, based on surface hydrology
modelling and deep groundwater modeling (Hjerpe et al. 2010). Each biosphere object
is described by one, or more, ecosystem types and one set of data, and is associated with
a corresponding radionuclide transport model. The connections between the objects are
derived from terrain forecasts for the period from the present (initial state) to the end of
the assumed time window when regulatory dose constraints apply. The combination of
the connected biosphere objects and the release pattern is the landscape model (Hjerpe
et al. 2010).
16
a) 1 000 years after start of operation (year 3 020)
b) 10 000 years after start of operation (year 12 020)
Figure 2-5. The end points of the flow paths at year 3 020 (1 000 years after start of
operation, upper graph) and at year 12 020 (10 000 years after start of operation, lower
graph). The starting panel of the are indicated by different colours. Streams, coastal
area (3 020), lakes (12 020)and present boundaries of Olkiluoto Island are shown in the
graph.
17
An important step in the delineation of the biosphere objects is to link the locations of
the release point with a biosphere object in the landscape model. This is made based on
the type of ecosystem in the landscape model coinciding with the location of the release
point into the biosphere. Basically, the release is going to the object coinciding with the
release point. In the present assessment, the radionuclide release paths with advective
travel time up to 15 000 years are included, and those with longer travel times are
cropped off from the further consideration. The other assumptions done in connecting
the release with the biosphere objects are defined in Hjerpe et al. (2009).
The transitions between ecosystem types due to the evolution of the biosphere (e.g.
when new terrestrial ecosystems are formed from the sea due to land uplift) are also
regulated in the landscape modelling, see Figure 2-6 for the allowed paths.
The UNTAMO toolbox was used to delineate the ecosystem type of these objects for
years 2020, 2520, ... 12520 (in 500 year interval). Nine different types of ecosystems
were delineated for each time step: coast, lakes, reed areas, dried part of lakes, part of
lakes formed into mires, mires, forests, croplands and rivers. Certain rules for the
delineated objects were also applied in order to not underestimate doses to most
exposed people. Most important rules are regarding areas of terrestrial objects; rules for
maximum areas were applied, in order to avoid excess dispersion (―dilution‖) of
radionuclides (Hjerpe et al. 2010).
The extent and location of biosphere objects are given in Figure 2-7 for three different
time steps for an area surrounding the Olkiluoto Island. Time point 1 000 years after
start of operation (year 3 020) represents the case when sea is still partly surrounding
the Olkiluoto Island. The other time steps, 4 000 and 10 000 years after start of
operation, show the evolution of terrestrial and lake objects caused by land uplift. The
end point locations of the radionuclide flow paths computed by Nykyri et al. (2008).
The radionuclide flow paths with advective travel times longer than 15 000 years have
been cut out.
One specific goal of the computations described in this report is to calculate the areally
averaged vertical and horizontal fluxes and soil moisture contents for delineated
biosphere objects for all time steps 2 020, 2 520, .., 12 020 (500 year time step). These
fluxes are used as input data in the Radionuclide transport modelling process.
lake (or river)
coast wetland
forest
cropland
open sea
Figure 2-6. The allowed paths for ecosystem evolution in the landscape model. The
dashed paths represent alternative paths, evaluated as what-if cases. Also the reversed
situation is allowed, for example in the case of sea level rise (adapted from Hjerpe et al.
2010).
18
a) 1 000 years after start of operation (year 3 020)
b) 4 000 years after start of operation (year 6 020)
c) 10 000 years after start of operation (year 12 020)
Figure 2-7. Location and extent of biosphere objects for three different time points.
a)1 000 years after start of operation, b) 4 000 years after start of operation and c)
10 000 years after start of operation. The end point locations of the radionuclide flow
paths are show in the graph (travel time smaller than 15 000 years).
19
2.6 Description of the surface hydrological models
Olkiluoto surface hydrological model (Karvonen 2008 and 2009a) is a 3D-model that is
used to study the water balance components on Olkiluoto Island and to evaluate the
effect of ONKALO on groundwater level in overburden soils and in shallow bedrock
drillholes. In the model overburden and bedrock are combined into one single numerical
solution and overburden-bedrock interface can be seen as the layer where hydraulic
properties change from soil values to bedrock data. The model links unsaturated and
saturated soil water in the overburden and groundwater in bedrock into one continuous
pressure system. Horizontal and vertical fluxes can be obtained as output values.
Moreover, flux at the interface between overburden and bedrock - recharge to bedrock
or discharge out of bedrock - can be calculated since the location of the first bedrock
node in the vertical direction can be obtained from bedrock elevation data. During 2008
an option was added to model that allows ArcView raster files to be used as input data,
which ensures consistency with the output data provided by the UNTAMO toolbox.
A so called SVAT (Soil-Vegetation-Atmosphere-Transfer) model was developed to
analyze the different water and energy balance components of the FIP (Forest Intensive
Monitoring Plots) plots (Karvonen 2009b). The SVAT model is an extension to the
Olkiluoto surface hydrological model. The SVAT model utilizes the soil water models
available in the Olkiluoto surface hydrology model. In the SVAT model soil profile can
be divided up to 30 layers and both vertical and horizontal water fluxes are computed.
Interception and transpiration of different vegetation types are at a very crucial role in
SVAT models (Soil-Vegetation-Atmosphere-Transfer). Very sophisticated multi-layer
model models exist which consider water uptake and transpiration of each tree species
individually (e.g. Oltchev 2002; Kellomäki and Wang 2000). However, the data
available from Olkiluoto Forest Intensive Monitoring Plots (FIP) do not support model
of this complexity. Therefore, a simpler model was adopted which divides forest to two
layers: overstorey (trees) and understorey canopy (Karvonen 2009b). Water and energy
balance will be computed separately for the two layers. Two-layer models require a
limited number of input parameters and can be applied to describe forest
evapotranspiration and land surface-atmosphere interactions at site and regional scales.
Hydrological processes that are quantified in the Olkiluoto SVAT model of forest
stands include precipitation, interception, evaporation, transpiration, snow accumulation
and melt, soil and ground water movement, overland flow, horizontal subsurface flow
and flow to forest ditches.
The surface hydrology model calculates horizontal and vertical water fluxes in a 3D-
grid but various type of spatial and temporal simplifications - conceptualizations - of the
complete model have been programmed in such a way that model results can be used in
estimating the water fluxes for the biosphere objects (see Figure 2-8). Olkiluoto surface
hydrology model can utilize the delineation of the biosphere objects and compute
average yearly water fluxes and average water content in the compartments. The SVAT
model computes the yearly values of the above ground water fluxes. Computation will
20
Figure 2-8. Conceptualization of fluxes computed in the Olkiluoto SVAT model and in
the Olkiluoto surface hydrology model. Fluxes are computed in 3D-grid but summaries
from fluxes can be computed at various spatial and temporal resolutions (scales).
be done separately for each delineated site-specific biosphere object for all time steps
(2 020, 2 520, .., 12 020).
2.7 Description of the radionuclide transport models
Radionuclide transport modeling is carried out using both particle tracking algorithm
and numerical solution of the partial differential equation that can take into account the
influence of advection, diffusion, dispersion, adsorption and radioactive decay on
behavior of radionuclides. The role of numerical model is to verify the results obtained
from particle tracking algorithms (see Chapter 4). The results of the surface
21
hydrological models will be used to calculate water fluxes for biosphere object modules
used in the landscape model (Hjerpe et al. 2010). The structure of the biosphere object
modules is briefly described here as a reference to conceptualization of the surface
hydrological model shown in Figure 2-8.
Particle tracking algorithm
Particle tracking algorithm is used to calculate the flow paths of radionuclides from the
interface between bedrock surface and overburden soils as they are transported by water
flow within the model volume. Each particle is moved inside the grid depending on the
3D velocity field computed by the surface hydrological model as given by Eq. (2-1):
ZZttt
YYttt
XXttt
tVZZ
tVYY
tVXX
(2-1)
where Xt, Yt and Zt (m) are x-,y- and z-coordinates of the initial location of the particle
at the beginning of time step t (d). Xt t, Yt tt and Zt t are coordinates of the particle
at the end of the time step and velocities in three directions are denoted by VX, VY and
VZ (m d-1
). It is also possible to add a random component X, Y and Z (m) in each
direction. Random component is very often linked with the velocity vector: the higher
the velocity, the greater the random term. So far the random term has not been used in
the computations.
Numerical solute transport model
Preferential flow of water and solutes in structured media (both macroporous soils and
fractured rocks) can be described using a variety of dual-porosity, dual-permeability,
multi-porosity, and/or multi-permeability models (Pruess and Wang, 1987; Gerke and van
Genuchten, 1993a; Gwo et al., 1995; Jarvis, 1998). Dual-porosity and dual-permeability
models both assume that the porous medium consists of two interacting regions, one
associated with the fracture system, and one comprising the soil and/or the rock matrix.
While dual-porosity models assume that water in the matrix is stagnant, dual-permeability
models allow for water flow in the matrix as well. A dual-permeability approach was
chosen as the basis for the coupled water and solute transport model in the overburden
soils of the Olkiluoto biosphere objects. A 3D-version was developed but it can also be
used as 1D- or 2D-version. The use of numerical solute transport model in this study is
described in Chapter 4
The description of the solute transport model is given in Appendix B. The processes
included in the numerical solution are advection caused by water flow, diffusion and
hydrodynamic dispersion, adsorption of solutes and first-order decay.
In this study the code verification of the solute transport model is carried out by
comparing the numerical solutions of the models with selected analytical solutions. An
analytical solution gives exact values for soil water content or solute concentration for
defined initial and boundary conditions and with known soil hydraulic properties or
22
solute transport parameters. The drawback of the analytical solutions is that their
applicability is usually restricted to homogenous soil properties and simplified boundary
conditions. However, analytical solutions are very useful in verifying the numerical
solutions.
The aim of the code verification is to show that the model produces accurate results for
solute concentrations if initial and boundary conditions and the model parameter values
(app. B) are known precisely. This implies that the numerical discretization does not
produce error to the solution if the grid is dense enough.
The biosphere object modules
The biosphere object modules used in the landscape model represent a typical
ecosystem identified to exist during any time point in the developing landscape. In the
biosphere assessment process described in Hjerpe et al. (2009), biosphere object
modules for the following ecosystem types are applied: forest, wetland, cropland, lake,
river and coast. The modules are consistent on a conceptual level, meaning that the
structure of compartments is very similar in all models. This facilitates the coupling
between ecosystems existing at the same time, and the transition between ecosystem
types due to the landscape development (e.g. when new terrestrial ecosystems are
formed from the sea due to land uplift). All included ecosystem-specific models (forest,
wetland, cropland, lakes, rivers, sea and coastal areas) could, in principle, be illustrated
in on generic conceptual model. However, for clarity, two conceptual models are used,
one terrestrial and one aquatic; these are presented in Figures 2-9 and 2-10 (Hjerpe et al.
2010).
The conceptualization of the surface hydrological model (see Figure 2-8) was carried
out in such a way that it is consistent with the biosphere object modules given in
Figures 2-9 and 2-10. The fluxes between compartments of Figure 2-8 can be used as
input data for the compartments of the biosphere object modules. Moreover, soil
moisture contents computed with the conceptualization of the surface hydrological can
be used to compute moisture content and water amounts in the biosphere object
modules.
The models used in the biosphere assessment process to compute the behavior of
radionuclides in object modules of Figures 2-9 and 2-10 fall outside the scope of this
study. These models are in described in Hjerpe & Broed (2009).
23
Figure 2-9. The conceptual radionuclide transport model for terrestrial ecosystems.
The indices in the compartment names define for which ecosystem(s) they are valid,
where: (F) is forest, (W) is wetland (W) and (C) is cropland (adapted from Hjerpe et al.
2010).
Figure 2-10. The conceptual radionuclide transport model for aquatic ecosystems
(lake, river, and coast). (adapted from Hjerpe et al. 2010).
24
25
3 RESULTS 3.1 Particle transport from bedrock to surface waters
The radionuclide release and transport analysis RNT-2008 (Nykyri et al. 2008) presents
the results from the release of radionuclides from spent nuclear fuel to their arrival in
the interface between bedrock surface and overburden soils or sediments. RNT-2008
results include computation of flow paths of around 39 000 radionuclide particles
released from different panels in the final repository area and cases 1 000 and 10 000
years after start of operation.
The goal of the model described here was to compute the transport of radionuclides
(pathways) from sediment-bedrock interface to surface waters or root zone in forest,
agricultural or wetland areas. The end point location of the radionuclide flow paths from
RNT-2008 computation were used the initial data for the surface hydrology model.
The surface hydrological model used raster files created by the UNTAMO toolbox as
model input data. The computational grid for the surface hydrological model was
clipped in such a way that all the radionuclides pathways computed in the RNT-2008
(Nykyri et al. 2008) will end inside this area and radionuclides can flow out of this area
only through rivers or to sea or lake. The following rasters were converted from the
original UNTAMO output to model input data rasters:
soil surface elevation (DTM)
bedrock elevation raster (computed by subtracting soil thickness raster from
DTM)
top soil type raster and soil thickness raster
streams/rivers from flow accumulation raster
location of coastal areas and lakes
Soil water retention curve parameters were defined separately for overburden soils and
bedrock (Karvonen 2009a). Each soil type was treated as isotropic and homogenous.
The parameters of the soil water retention curve and hydraulic conductivities of the soil
types are given in Appendix A.
In the first step steady-state recharge/discharge through the bedrock-overburden
interface was first computed for all grid points (pixels). In the second step vertical and
horizontal water fluxes were computed for a period of nine years (daily data) using
precipitation, air temperature and potential evapotranspiration data from the present
climate. Steady-state recharge/discharge through the bedrock interface - calculated in
the first step -was used as the lower boundary condition of the model.
Average seasonal fluxes were computed for all the pixels. The seasons were defined as
1=JAN-MARCH, 2=APRIL-MAY, 3=JUN-AUG and 4=SEPT-DEC. The radionuclide
pathways were calculated for a period of 2 000 years ahead starting from final points of
the RNT-2008 computations and using the seasonal average fluxes over and over again
(2 000 times corresponding to the 2 000 years).
26
End point location of radionuclide flow paths
The results of the computations include the end point locations of the around 39 000
flow paths in cases 1 000 and 10 000 years after start of operation. Flow path may end
to watercourses (sea, lake, or river), to the root zone of forest or agricultural areas or
acrotelm/catotelm layer of the peat areas. In addition to the end point location of the
flow paths the time it takes for an unretarded radionuclide to be transported to these
locations is computed.
The lake or sea nodes are located at depressions and therefore horizontal fluxes out of
the area are negligible indicating that if the initial point of flow path is at sea or lake,
then the only movement direction of the radionuclide is from bedrock interface towards
sediment top surface and the water body. Both in 1 000 and 10 000 year cases majority
of radionuclides will be in lake/sea nodes (see Table 3-1): 71.5 % in the 1 000 year case
and 61 % in the 10 000 year case.
In land areas the vertical movement is equal to the recharge from bedrock up to the
transition zone, i.e. depth from soil surface where seasonal groundwater level
fluctuation influences. Above this transition zone the particle moves upward due to
capillary forces caused by roots. In wet seasons the precipitation causes downward flux
which delays the vertical movement of the particle or during very wet periods the
radionuclides are transported temporarily to deeper layers. Therefore, the time needed
to reach the root zone can be very high and some of the radionuclides may move
horizontally to streams before they reach the root zone.
Table 3-1. Summary of the initial and end point locations of the radionuclides based on
the results of Olkiluoto surface hydrological model.
27
Location of the end points of flow paths starting from bedrock interface are shown in
Figure 3-1. Flow paths that did end to root zone are indicated by bigger circles.
Moreover, flow paths starting from different panels are also indicated in Figure 3-1. 5.4
% of the radionuclides ended to root zone in the 1 000 year case and the corresponding
value was only 1.7 % for the 10 000 year case. The main reason for the difference is the
a) Year 3 020
b) Year 12 020
Figure 3-1. Location of the end points of flow paths starting from bedrock interface.
Flow paths that have ended to root zone are indicated by bigger circle. Present island
boundaries and ONKALO layout are shown in the graphs. a) Case 1 000 years after
start of operation (year 3 020) and b) Case 10 000 years after start of operation (year
12 020).
28
the fact the spatial distribution of the location of the radionuclides flow paths after the
RNT-2008 computation was different for cases 1 000 and 10 000 years after start of
operation as can be seen from Figure 3-2. More RNT-2008 flow paths end at future
land areas in the case 1 000 years after start of operation (year 3 020) which is reflected
in the results in such a way that bigger proportion of flow paths of the surface
hydrological model go to root zone of terrestrial areas.
a) Year 3 020
b) Year 12 020
Figure 3-2. Initial location of radionuclide flow paths for surface water computation.
The location of the area is shown in upper left corner of the map. a) Case 1 000 years
after start of operation (year 3 020) and b) Case 10 000 years after start of operation
(year 12 020). The different number of initial points for flow paths inside the encircled
area shows the main reason for the fact that more flow paths end up at root zone in the
1 000 year case.
29
Distribution of radionuclide transport distances
A big proportion of flow paths of the RNT-2008 computations (Nykyri et al. 2008) end
below sea areas or future lakes (see Table 3-1). The transport distance from bedrock
interface to water body is for these flow paths the same than the thickness of the
sediment layer (see Figure 3-3). The distribution is very similar in cases 1 000 and
10 000 years after start of operation. Average thickness of sediment layer (50 % point
in the cumulative distribution) is around 5.6 m for 1 000 year case and 5.9 m for the
10 000 year case.
Figure 3-3. Cumulative distribution of sediment thickness at radionuclide discharge
points for cases 1 000 and 10 000 years after start of operation (years 3 020 and
12 020, respectively).
In land areas both vertical and horizontal movement of radionuclides can be seen.
Discharge from bedrock and capillary forces caused by roots move the radionuclides in
vertical direction and lateral movement is due to the groundwater flow towards rivers,
lakes or sea. The distribution of horizontal transport distances for radionuclide flow
paths starting from land areas and ending at a watercourse (sea, lake or river) are shown
in Figure 3-4 for cases 1 000 and 10 000 years after start of operation (years 3 020 and
12 020, respectively). The 50 %-point of the cumulative distribution is only around 20
m indicating that in most cases the horizontal travel distances are very small. The
transport distance distribution is influenced mainly by two factors: 1) what is the
distance from initial location of flow paths to nearest lake or sea and 2) what is the
density of the delineated stream network. The flow accumulation raster created by
UNTAMO toolbox can be used to create a stream network by applying a threshold
value to select cells with a high accumulated flow. The lower the threshold value, the
bigger the stream density. Example of radionuclide flow paths in overburden soils is
given in Figure 3-5 for the case 1 000 years after start of operation (year 3 020). The
graph shows the flow paths of those radionuclides that that move laterally in overburden
soils and end at sea or rivers. The threshold value for stream delineation was 5 ha (500
pixels in 10x10 m2 grid). The selection of the threshold value is discussed more in
Chapter 4.
30
Figure 3-4. Cumulative distribution of transport distance for radionuclide flow paths
starting from land areas and ending at a watercourse (sea, lake or river). Cases 1 000
and 10 000 years after start of operation (years 3 020 and 12 020, respectively).
Transport time distribution in overburden soils and sediments
In sea or lake sediments the transport time distribution depends both on thickness of the
sediment layers and discharge rate through the bedrock-overburden interface. Both
factors include uncertainty which needs to be examined more thoroughly in future
biosphere assessments. Thickness of sediment layers below the present sea or future
lake areas is dependent on the difference between sediment accumulation and erosion
processes. Hydraulic conductivity of the bedrock can be considered to be known
accurately enough inside the well characterized area of the Olkiluoto Island. Outside the
island boundaries the bedrock hydraulic conductivity values are assumed to be the same
than for areas inside the island.
Cumulative distribution of transport time for flow paths from bedrock-sediment
interface through sediment layers to water body is shown in Figure 3-6 for cases 1 000
and 10 000 years after start of operation (years 3 020 and 12 020, respectively). Average
travel time (50 %-point in cumulative distribution) is around 750 years for both cases
.
The cumulative distribution of transport time for radionuclide flow paths from land
areas to sea, lake or river is given in Figure 3-7. The 50 %-point in the distribution is
around 30 years and transport time is longer than 100 years in around 30 % of the flow
paths for the 1 000 year case and in 10 % of the flow paths for the 10 000 year case. In
wet seasons precipitation causes downward flux of radionuclides which delays the
horizontal movement towards watercourses since lateral velocities are highest close to
the soil surface. Therefore, the time needed to reach the water courses can be very high.
The uncertainties related to horizontal travel times are discussed in Chapter 4.
31
Figure 3-5. Example of radionuclide flow paths in overburden soils. The lines show the
transport flow paths of those radionuclides that move laterally in overburden soils. The
location of the area is shown in the upper left corner of the map. Case 1 000 years after
start of operation (year 3 020).
Figure 3-6. Cumulative distribution of transport time for flow paths from bedrock-
sediment interface through sediment layers to water body. Cases 1 000 and 10 000
years after start of operation (years 3 020 and 12 020, respectively).
32
Figure 3-7. Cumulative distribution of transport time for radionuclide flow paths from
land areas to sea, lake or river. Cases 1 000 and 10 000 years after start of operation
(years 3 020 and 12 020, respectively). The x-axis scale is logarithmic.
3.2 Vertical and horizontal water fluxes in biosphere objects
The location and maximum extent of terrestrial and surface water areas (coastal area,
lakes, rivers) that can possibly receive radionuclides from the repository area were
identified based on results obtained from the RNT-2008 radionuclide pathway
simulations (Nykyri et a. 2008) and the results shown in section 3.1 of the present
report. UNTAMO-toolbox was used to delineate the ecosystem type of these objects for
years 2020, 2520,.. 12520 (500 year interval). Nine different types of ecosystems were
delineated for each time step: coast, lakes, lakes with reed areas, lakes that will dry out,
lake areas that will turn to peatlands, mires, forests, croplands and rivers. Olkiluoto
surface hydrological model (Karvonen 2008 and Karvonen 2009a) was used to calculate
the vertical and horizontal fluxes for the ecosystem objects.
The method for calculating fluxes proceeds in two steps. In the first step of the analysis
steady-state recharge/discharge to/from bedrock was computed for all computational
pixels and these results were stored as a raster file and used as the lower boundary
condition of the model in the second step. The computational area was at this stage
much larger than in the radionuclide transport computations (see Figure 3-8). Upper
boundary conditions for the model were precipitation and potential evapotranspiration
rates. Parameterization of the transpiration and interception processes were based on the
results of the SVAT model that was used for computing water and energy balance
components of the Forest Intensive Monitoring Plots on Olkiluoto Island (Karvonen
2009b).
The second step included compilation of fluxes for each biosphere object (see Table 3-2
and Figure 3-8) at each time step. Vertical fluxes were areally averaged values from all
33
pixels inside the delineated ecosystem objects. The vertical fluxes were aggregated at
this stage to correspond the storages of the conceptualized version of the model (see
Figure 2-8 and the equivalent biosphere object modules shown in Figures 2-9 and 2-10).
The number of vertical layers in the 3D surface hydrological model was 10 and results
from several layers of the 3D-model were combined into four storages shown in Fig. 2-
8 (or Figure 2-9). Horizontal fluxes were computed by summing the horizontal inflows
and outflows through the biosphere object boundaries. Moreover, soil water content and
water amount in deep soil/deep sediment, intermediate soil/intermediate sediment, root
zone/active sediment layer and humus/acrotelm were computed. The method adopted
here is based on calculating average vertical and horizontal fluxes for biosphere objects
from the results of the full 3D-model, i.e. it was not necessary to develop any simplified
hydrological model for the biosphere objects.
Table 3-2. Object numbers, downstream object number, maximum area of objects (ha),
final type of object and object name.
34
Whole area
a) Western part
b) Eastern part
Figure 3-8. Names and locations of biosphere objects at time 10 000 years after start
of operation (year 12 020). a) Whole area. b) Western part of area and c) Eastern part
of area.
35
The spatial and temporal data needed in the model was provided by the UNTAMO-
modelling: soil surface elevation, type and thickness of soil layers, location of coastal
areas, lakes and rivers and flow accumulation raster.
The output of computations include 28 variables for each ecosystem type and time step:
12 vertical flux components, 8 horizontal flux components, four water content values
and four water amount values (see Figure 3-9).
Area of ecosystems as a function of time
The time evolution of total area of biosphere objects and its distribution as a function of
time is given in Table 3-3. The first lakes appear at the location of delineated biosphere
objects around 1 500 years after start of operation (year 3 520). Lake total area increases
to 770 ha after 2 000 years and remains practically the same throughout the period
under consideration. Area of lakes that dry out during the landscape evolution is minor
(maximum area around 33 ha). Reed areas increase to the maximum value around the
year 6 020 (156 ha) and slowly decrease to value 128 ha towards the end of the
computation period (year 12 020). Mire and forest areas are relatively small compared
to aquatic objects. The sum of mire and forest areas is around 73 ha at maximum and
the trend is that mire areas are increasing and forest areas are decreasing as a function of
time. Area of croplands rises to value 160 ha during the first 1 500 years and increases
after that slowly to its final value, which is almost 200 ha.
Table 3-3. Total area and areas of different ecosystem types as a function of time based
on results obtained from UNTAMO-modelling (Ikonen et al. 2010b).
36
Figure 3-9. Conceptualization of storages and fluxes in biosphere objects. Storages:
WS1=overburden layers (below 1.0 m depth and above bedrock), WS2=intermediate
mineral soil in (depth 0.3-1.0 m),WS3=root zone in forests and croplands and catotelm
layer in mires (depth 0-0.3 m) and WS4=humus layer in forests and acrotelm in mires,
does not exist in croplands (thickness assumed to be 0.1 m).Vertical and horizontal
fluxes indicated in the graph. Numbers 1-16 refers to fluxes (m a-1
), 17-20 to moisture
content in storages (m3 m-3
) and 21-24 amounts of water in storages (m).
Discharge from bedrock to biospehere objects
The cumulative distribution of discharges from bedrock to aquatic and terrestrial objects
are given in Figure 3-10. The discharge values are given in unit % from average
precipitation 550 mm a-1
. The estimates disharges are small compared to average
precipitation rate. The results are well in accordance with the results computed earlier
using the Olkiluoto surface hydrological models (Karvonen 2008 and 2009a).
37
a) Aquatic objects
b) Terrestrial objects
Figure 3-10. Cumulative distribution of discharge (% from precipitation) through
bedrock-overburden interface. a) Aquatic objects, b) terrestrial objects.
Water balance components of the biosphere forest objects
The functioning of forest ecosystems on the Olkiluoto island is studied in Forest
Intensive monitoring Plots (FIP). Three plots have been established in the Liiklansuo
catchment area: FIP4 (Scots pine forest), FIP10 (Norway spruce forest) and FIP11
(young Norway spruce/birch forest) (Haapanen 2006, 2008). FIP4 and FIP10 represent
Oxalis-Myrtillus/grove-like mineral soil forest site types growing on fine-textured till.
38
The third intensive monitoring plot (FIP11) was established in a young Norway spruce
and birch stand nearby in late 2006, and the installation of equipment was finished
during 2007. The results of the measurements carried out in FIP-areas have been
presented by (Haapanen 2006, 2007, 2008) and Karvonen (2009b) has developed a
SVAT-model (Soil-Vegetation-Atmosphere-Transfer) for analyzing the water and
energy balances of the FIP-areas. The parameters of the SVAT-model were also utilized
in this study in estimating the interception and transpiration components of the overall
water balance.
Cumulative distributions of the water balance components of the forested biosphere
objects are shown in Figure 3-11 and in Table 3-4. The results of the present study were
computed using the ―present climate scenario‖ and therefore it is possible to compare
the results of Figure 3-11 and Table 3-4 with the water balance components measured in
FIP-areas in Olkiluoto (Haapanen 2008) and values computed with the SVAT-model
(Karvonen 2009b). The results of the comparison are given below for all the key
components of the biosphere forest object water balances.
Precipitation throughfall and interception
Measured precipitation, throughfall and interception rates in FIP-areas and in stand
throughfall experimental areas (MRK) have been reported by Haapanen (2006, 2007,
2008). Average measured value for stand throughfall scaled for yearly precipitation rate
(550 mm a-1
) was 399 mm a-1
and measured interception was 160 mm a-1
. The
corresponding average values computed in this study for biosphere forest objects were
417 mm a-1
for throughfall and 131 mm a-1
for interception. The throughfall calculated
for biosphere objects is around 5 % bigger than the measured value for FIP- and MRK-
areas. This can be partly explained by the fact that computed value for forested object
includes sparse forest areas where throughfall is bigger than in FIP-areas. Cumulative
distributions for throughfall and interception are shown in Figures 3-11a and 3-11c. The
range of computed values is 390-455 mm a-1
, which is narrower than the range of
measured values (330-475 mm a-1
). In future biosphere assessments it would be useful
to include estimation of forest type and forest biomass as UNTAMO output to get
consistent forest evolution prediction both in terrain and ecosystems development
modelling (TESM) and in surface hydrological models. This would improve the
throughfall, interception and transpiration prediction for biosphere objects.
Transpiration
Measurements of tree-level transpiration started in May - June 2007 in the forest
intensive monitoring plots FIP4 and FIP10 using the sap flow measurement system and
continued in 2008. The aim was to measure tree-level transpiration as a basis to
calculate stand transpiration rate and variability. The approach, the measurement
methods, and results have been reported by Haapanen (2009) and Hökkä (2008). There
has been difficulties in some of the sensors attached to individual trees for measuring
the sap flow and therefore the range in measured values has so far been quite large: 160-
220 mm a-1
. Average transpiration rate computed for the biosphere objects was 200 mm
a-1
(range 175-233 mm a-1
) as shown in Table 3-4. In future assessment more data from
measured sap flow rates are expected to be available.
39
a) b)
c) d)
e) f)
Figure 3-11. Cumulative distribution of various fluxes in forest objects. a) Precipitation
throughfall, b) transpiration flux, c) interception flux, d) surface runoff, e) subsurface
runoff including flux to streams and f) horizontal inflow to object.
40
Table 3-4. Average, maximum and minimum values of flux components in forested
objects. All fluxes are given in unit mm a-1
. Average precipitation is 550 mm a-1
.
Downward flux from root zone
The amount of percolation water is being monitored in FIP-areas using the plate
lysimeters located at the depth of 0.05 m (Haapanen 2008). The collection period starts
in the spring when the ground is no longer frozen and snow has been melted. Measured
data is available on all three FIP plots. Measured amount of percolation water passing
down to a depth 5 cm during the snow free periods in 2004-2007 was around 20-55 mm.
The average computed downward flux from root zone in biosphere forest objects was
170 mm a-1
(range 114-211 mm a-1
). This value is much bigger than the measured rate
at depth z=0.05 m since computed values include also the snowmelt period when
approximately 100-150 mm of water is infiltrated into soil profile and roots are not yet
active. Another reason for difference between measured and computed downward flux
rates is that surface hydrological model takes transpiration flux from the 0.3 m thick
root zone. This implies that a large proportion of infiltrated water must pass the depth
0.05 m. Moreover, measurement of downward flux in FIP-areas includes uncertainty
factors since according to Haapanen (2008), the plate lysimeters did not function
properly in 2005 and difficulties with high groundwater level have been encountered
especially on plot FIP10. Considering the uncertainties in measuring downward flux in
FIP-areas and the influence of snowmelt period it can be concluded that the computed
downward flux from root zone is of the correct order of magnitude. In future
assessments it is necessary to calculate the output from surface hydrological model
separately for the snow-free period so that computed fluxes can be compared directly
with the measured percolation rates.
Other water balance components
Measured values from FIP-areas were available only for throughfall, interception,
transpiration and downward infiltration rate at depth z=0.05 m. The magnitude of the
other water balance components cannot be compared with measured values.
The horizontal inflow component shown in Figure 3-f and Table 3-4 was computed in
such a way that the sum of the horizontal fluxes through the object boundaries (m3 a
-1)
41
was dived with the area of the object. In this way the horizontal inflow to object was
converted to the same unit that the vertical fluxes (m a-1
or mm a-1
). Average value for
horizontal inflow was 22 mm a-1
(range 7-83 mm a-1
), which is much smaller than the
sum of the outflows via surface runoff (47 mm a-1
) and subsurface runoff (161 mm a-1
).
Subsurface runoff includes both the horizontal outflow through the object boundaries
and flow to streams and ditches. In future assessments it is necessary to make a
sensitivity analysis on the effect of distribution of total runoff to surface and subsurface
components on radionuclide transport pathways near the surface of the overburden
layers.
Water balance components of the biosphere cropland objects
Average, maximum and minimum values of flux components in cropland objects are
shown in Table 3-5. All fluxes given in unit mm a-1
. Measured values of water balance
components in cropland areas are not available from Olkiluoto area. However,
experiments have been carried out in drained clay soils in other parts of Finland. The
water balance components of the biosphere cropland objects can be compared against
the results presented by Paasonen-Kivekäs et al. (2008) for Sjökulla area in southern
Finland. Warsta (2007) has modeled the water balance of the same experiments.
Vakkilainen (2009) has reported results from clay fields in Hovi in southern Finland. In
the above mentioned experiments drainage flux and surface runoff were measured.
Average drainage flux for computed for the biosphere cropland objects was 130 mm a-1
(range 119-137 mm a-1
). The corresponding measured flux in Sjökulla and Hovi were
around 100-150 mm a-1
, which is of the same magnitude than in biosphere cropland
objects.
Average surface runoff of cropland objects (69 mm a-1
) was smaller than the surface
runoff measured in Sjökulla and Hovi (100-150 mm a-1
). The difference can be
explained by the fact that in Sjökulla and Hovi the yearly precipitation is around 650-
700 mm a-1
, i.e. around 100-150 mm a-1
higher than in Olkiluoto.
Total evapotranspiration (sum of transpiration, interception and soil evaporation) for
cropland objects was 355 mm a-1
is within the range estimated by Vakkilainen (2009)
for typical conditions in western Finland.
Downward flux from root zone is higher for cropland objects (235 mm a-1
) when
compared to the corresponding value for forest objects (170 mm a-1
). The reason for this
is that crop is harvested after summer and evapotranspiration is smaller during autumn
rains.
Horizontal inflow to cropland objects is small (average value 13 mm a-1
) since the
lateral movement of surface runoff from areas outside the cropland is prevented by
ditches that surround the fields.
42
Table 3-5. Average, maximum and minimum values of flux components in cropland
objects. All fluxes are given in unit mm a-1
. Average precipitation is 550 mm a-1
.
Water balance components of the biosphere mire objects
Average, maximum and minimum values of flux components in mire objects are given
in Table 3-6. Water balance of mire objects has not been measured in Olkiluoto area
and it was not possible to find any experimental area to be used as a reference site. The
difficulty in measuring the water balance components of mire areas is that they are
usually so flat that weirs used for measuring discharges do not function properly.
Moreover, mire areas receive additional water from surrounding forest areas via
subsurface and surface runoff and this complicates the experimental set-up
Table 3-6. Average, maximum and minimum values of flux components in mire objects.
All fluxes are given in unit mm a-1
. Average precipitation is 550 mm a-1
.
43
3.3 Soil water content in biosphere objects
Average, maximum and minimum yearly soil moisture content in biosphere forest,
cropland and mire objects for different compartments are given in Table 3-7. Maximum
and minimum refer to average values computed for object. Inside each object maximum
and minimum can seasonally be lower or higher than the values given in Table 3-7.
Computed moisture content values can be compared to measured value given in several
field experiments. E.g. Jauhiainen (2004) and Laine-Kaulio (2008) have reported
measured soil water content values in forested soils and Paasonen-Kivekäs et al. (2008)
and Warsta (2007) in cropland soils. The values given in Table 3-7 fall within the range
given in these publications.
Table 3-7. Average, maximum and minimum yearly soil moisture content (m3 m
-3) in
biosphere forest, cropland and mire objects for different compartments.
44
45
4 SENSITIVITY AND UNCERTAINTY ANALYSIS
4.1 Introduction
The computation of water fluxes and soil water contents both in particle transport
analysis and in computation of fluxes in biosphere objects was carried out using full 3D
surface hydrological model. The benefit of the method adopted here is that it was not
necessary to develop any simplified hydrological model for the biosphere objects.
Fluxes for biosphere objects were obtained by averaging vertical and horizontal fluxes
over the boundaries of each biosphere object during each time step. The drawback of
the method used here is that computations are very time consuming and during this
assessment process it was not possible to do a sensitivity and uncertainty analysis by
varying the key parameters of the full 3D model. This will be one of the topics of future
assessments. Instead, sensitivity was studied by calculation water balance and solute
transport separately for forest and cropland objects.
In sensitivity and uncertainty analysis it is very essential to evaluate the influence of
different parameters and other input data on the solute concentration profile. How big
proportion of solutes can reach the root zone and what are the factors that have the
biggest effect on this? Amount of solutes that reach the root zone is strongly influenced
by the vertical and horizontal fluxes in the biosphere objects.
The model was not computed for the whole grid but for typical forest and cropland
profiles (see sections 4.2 and 4.3). The water fluxes were computed first and these
values were used as input data to the numerical solution of the solute transport model
(see Appendix B). Parameters studied were those that influence the magnitude of fluxes
both in horizontal and vertical direction (hydraulic conductivities). Moreover, in forest
objects the effect of threshold value in stream delineation process was studied and in
cropland object the influence of drain spacing on concentration distribution was
examined.
The main goal of the sensitivity and uncertainty analysis described in this Chapter was
to find the most important factors that need to be studied in future biosphere
assessments. Detailed sensitivity and uncertainty analysis for examining the influence of
various input data and parameters on solute concentration profiles in biosphere forest
and cropland objects are to be done during the next round of the biosphere assessment
process.
4.2 Biosphere forest objects
Very many simulation runs were carried out with water flow model and the numerical
solute (radionuclide) transport model described in Appendix B. Concentration of water
flowing from bedrock to overburden soils was assumed to be 100 units and relative
concentration profiles were calculated. The solutes were assumed to flow with the
velocity of water (unretarded transport, i.e. distribution coefficient Kd=0 and radioactive
decay was not taken into account). The parameters varied in computations were soil
hydraulic conductivities, parameters of soil water retention curves, thickness of
46
overburden layers, discharge from bedrock to overburden soils and the parameters of
the SVAT model affecting throughfall, interception and transpiration. Moreover, the
influence of threshold value in stream delineation process was studied. The relative
concentration of solutes in the root zone was the main criteria for evaluating how
sensitive and uncertain the model results are for different parameters.
According to results of the numerical solute model the main factors that influence solute
concentration profile in the biosphere forest objects are:
stream density
horizontal hydraulic conductivities in overburden soils
distribution of precipitation to throughfall, interception and transpiration
discharge through bedrock interface (hydraulic conductivity in bedrock and
location of fracture zones)
thickness of the overburden profile
Stream density
UNTAMO toolbox is used to create stream network by applying a threshold value to
select cells with a high accumulated flow. The lower the threshold value, the bigger the
stream density. Stream density has a very strong influence on vertical distribution of
solutes: the higher the stream density, the smaller the concentration of solutes in the root
zone (see Figure 4-1). This can be explained by the fact streams act as sinks in the
surface hydrological model: water flows horizontally towards streams and high stream
density implies that more water flows horizontally in subsurface soils below the root
zone. If stream density is low groundwater level will reach root zone more often and the
consequence of this is that there will be bigger solute flux from deeper layers to root
zone with the upward water flow caused by transpiration.
Influence of stream density on solute concentration of biosphere forest objects can be
seen from Figure 4-1. The graphs show the computed profiles after solutes they have
emerged from bedrock to overburden soils. For this case a steady-state profile is reached
approximately after 300 years. The relative solute concentration in the root zone at
depth 0.3 m is very small (around 1-2 %, upper graph in Figure 4-1) if stream density is
high. The relative concentration at depth 0.3 m is around 10 % if stream density is low
(lower graph in Figure 4-1).
According to particle tracking results shown in section 3.1 5.4 % of the solute pathways
ended at root zone in the 1 000 year case and 1.7 % in the 10 000 year case. These
values fall within the range indicated in Figures 4-1: 10 % relative concentration in root
zone in steady-state condition implies that approximately 10 % of the solutes would
reach the root zone.
Horizontal hydraulic conductivities in overburden soils
Horizontal hydraulic conductivity influences much more on the solute concentration in
the root zone than the vertical hydraulic conductivity: the higher the lateral
conductivity, the smaller the concentration in the root zone. The reason for this is that
high lateral conductivity influences in the corresponding way than dense stream
47
network. More water will flow in subsurface soils below the root zone when K-values
are high as compared to the case when horizontal conductivities are small.
In vertical direction the distances that solutes need to be transported are much smaller
than in horizontal direction and therefore, the uncertainty in vertical hydraulic
conductivity is influences less on fraction of solutes that reach the root zone.
Distribution of precipitation to throughfall, interception and transpiration
The most important parameters of the SVAT-model (Soil-Vegetation-Atmosphere-
Transfer) are snow and rainfall interception capacities, leaf area index (or biomass),
vegetation height, sky-view fraction and maximum fraction of stem flow (see Karvonen
2009b). The higher the fraction of transpiration from the total water balance, the higher
the concentration of solutes in root zone. Detailed sensitivity analysis of this
complicated system should be taken as an important topic in future assessments.
Discharge from bedrock to overburden soils
Soil surface elevation, soil and bedrock hydraulic conductivities, extent of fracture
zones and location of forest objects with respect to watercourses will influence most on
recharge to or discharge from bedrock. According to the results of the numerical solute
transport model discharge from bedrock influences mainly on the time it takes for
solutes to reach the root zone. The effect of discharge rate on relative concentration in
the root zone is very small if discharge rate varies in the range 0-2 % from precipitation
(0 - 11 mm a-1
). The reason is that vertical water fluxes close to soil surface are very
high compared to the discharge rate and other factors (stream density, horizontal
hydraulic conductivity in overburden soils) than discharge from bedrock have bigger
influence on the steady-state concentration profile of solutes.
Thickness of the overburden profile
The thickness of the overburden profile influences primarily on the time needed for
solute to reach the root zone. Solute concentration in the root zone seem to be almost
similar if thickness of overburden soil profile is between 1-5-3.0 m: it only takes more
time to reach the steady-state concentration if profile is thick. According to Hjerpe et al.
(2009) the overburden model of the UNTAMO toolbox is still in development stage and
uncertainties in the soil and sediment layer thicknesses are large. Therefore, the
uncertainty related to the depth of the bedrock-overburden interface is to be examined in
future assessments.
48
Figure 4-1. Sensitivity of solute concentration of biosphere forest objects to the density
of stream network. Upper graph=dense stream network (high stream density); Lower
graph=low stream density. Density of the stream network is based on flow
accumulation raster. Fine till, profile depth =1.5 m, discharge from bedrock = 5 mm a-1
(0.9 % from precipitation), unretarded solutes (Kd=0).
49
4.3 Biosphere cropland objects
According to the preliminary sensitivity runs carried out with the model the main
factors that influence solute concentration profile in the biosphere cropland objects are:
drainage density
horizontal hydraulic conductivities in overburden soils
discharge through bedrock interface
transpiration
Drainage density
In Finnish conditions clay soils have to be drained to ensure planting in spring and
harvest in autumn. Most often the drainage is carried out using subsurface drains
installed to a depth of 1.0 m. Moreover, soils need to be drained if irrigation water is
applied. Drain spacing has a very big influence on solute concentration profile as shown
in Figure 4-2. Steady-state relative solute concentration in root zone is very low, around
0-3 % from the concentration at the bedrock interface, if drain spacing is 12 m (high
drainage density). In the case that drainage density is low (drain spacing 20 m), the
relative concentration at the depth 0.3 m can be 10-12 % from its maximum value. The
explanation is that for high drainage density (small drain spacing) horizontal flow below
the root zone towards drains is higher than for low drainage density.
Horizontal hydraulic conductivities in overburden soils
Drainage flux will higher if horizontal hydraulic conductivities are increased and this
results in lower solute concentration in the root zone, i.e. high K-values in lateral
direction have the same type of effect than increase in drainage density. In vertical
direction the distances that solutes need to be transported are much smaller than in
horizontal direction and therefore, the uncertainty in vertical hydraulic conductivity
influences less on solute profile. During this study vertical and horizontal hydraulic
conductivities were the same, but in future assessment influence of anisotropy in
overburden soils should be examined.
Discharge through bedrock interface
Discharge rate from bedrock influences mainly on the time it takes for solutes to reach
the root zone. The effect of discharge from bedrock on relative concentration in the root
zone is very small if discharge rate varies in the range 0-2 % from precipitation (0 - 11
mm a-1
). The reason is that drainage density and horizontal hydraulic conductivity have
a much bigger effect on the steady-state concentration profile of solutes.
Transpiration
The higher the fraction of transpiration from the total water balance, the higher the
concentration of solutes in root zone. The sensitivity analysis of this system (e.g. type of
crop) should be taken as an important topic in future assessments.
50
Figure 4-2. Sensitivity of solute concentration of biosphere cropland objects to drain
spacing. Upper graph=very good drainage, drain spacing=12 m; Lower graph=poor
drainage, drain spacing =20 m. Clay soil, profile depth =1.5 m, discharge from
bedrock = 5 mm a-1
(0.9 % from precipitation), unretarded solutes (Kd=0).
51
4.4 Other biosphere objects
Mire objects
The most important factors that influence solute concentration profile in the biosphere
mire objects are:
stream density
horizontal hydraulic conductivity in peat soils
discharge through bedrock interface
thickness of the peat profile
land area of forests that feed the mire area
The influence of stream density and horizontal hydraulic conductivity in peat soils
influence in the corresponding way than in forest objects. The higher the stream
density, the lower the steady-state solute concentration in the acrotelm and catotelm
layers of the mire object. Low value in horizontal hydraulic conductivity tends to
increase solute concentration in the acrotelm and catotelm compartments.
Discharge through bedrock interface and thickness of the peat profile influence mainly
on the transport time of solutes.
Mire areas are very often surrounded by forests. Surface and subsurface flow from
forested areas are partly discharging to rivers and lakes via the peat areas. The
additional water flux from surrounding forests influences solute transport in mire
objects in a very complicated way. In most cases the horizontal flux from forest areas
has a flushing effect. However, the effect of surrounding forest areas should be
examined in future biosphere assessments.
Aquatic objects
For aquatic objects (coastal area, lakes and rivers), discharge from bedrock and
thickness of sediment profiles influence mainly on the time needed for solute to be
transported from bedrock interface to the active layer of the sediments.
52
53
5 SUMMARY
The surface hydrological model described in this report is aimed at providing links
between Terrain and ecosystems development and Landscape model set-up components
of the Olkiluoto biosphere assessment (BSA) carried out during 2009. Based on the
UNTAMO forecasts, continuous and sufficiently homogeneous segments of the
modeled area, possibly receiving any radionuclides released from the repository, have
been identified in the BSA. These segments are called biosphere objects.
Based on input data provided by the UNTAMO toolbox in Terrain and ecosystems
development component vertical and horizontal water fluxes and soil water content were
computed for the whole computational area using the Olkiluoto surface hydrological
model.
Radionuclide transport modeling was carried out using both particle tracking algorithm
and numerical solution of the partial differential equation that can take into account the
influence of advection, diffusion, dispersion, adsorption and radioactive decay on
behavior of solutes. The numerical models were used in sensitivity and uncertainty
analysis for recognizing the most important factors that influence solute distribution in
forest and cropland objects.
Transport of radionuclides (pathways) from sediment-bedrock interface to surface
waters or root zone in forest, agricultural or wetland areas were computed using the
particle tracking algorithm. In the analysis the end points of around 39 000 flow paths in
cases 1 000 and 10 000 years after start of operation were computed. The final points of
flow paths may be in watercourses (sea, lake, or river), in the root zone of forest or
agricultural areas or acrotelm/catotelm layer of the peat areas. In addition to the end
point location of the flow paths the time it takes for an unretarded radionuclide to be
transported to these locations is computed.
Both in 1 000 and 10 000 year cases majority of radionuclides will be in lake/sea nodes
after the computation period: 71.5 % in the 1 000 year case and 61 % in the 10 000 year
case. 5.4 % of the radionuclides ended to root zone in the 1 000 year case and the
corresponding value was 1.7 % for the 10 000 year case.
The second step of analysis included the computation of vertical and horizontal fluxes
in the biosphere objects. Nine different types of ecosystems were delineated for each
time step: coast, lakes, lakes with reed areas, lakes that will dry out, lake areas that will
turn to peatlands, mires, forests, croplands and rivers. Olkiluoto surface hydrological
model was used to calculate the vertical and horizontal fluxes for the ecosystem objects.
Vertical fluxes were areally averaged values from all pixels inside the delineated
ecosystem objects. Horizontal fluxes were computed by summing the horizontal inflows
and outflows through the biosphere object boundaries. Moreover, soil water content and
water amount in deep soil/deep sediment, intermediate soil/intermediate sediment, root
zone/active sediment layer and humus/acrotelm were computed. The method adopted
here is based on calculating average vertical and horizontal fluxes for biosphere objects
from the results of the full 3D-model, i.e. it was not necessary to develop any simplified
hydrological model for the biosphere objects.
54
The water balance results of the present study were computed using the ―present climate
scenario‖ and therefore it is possible to compare the results computed in this study with
the water balance components measured in FIP-areas in Olkiluoto. Average measured
value for stand throughfall in FIP-areas scaled for yearly precipitation rate (550 mm a-1
)
was 399 mm a-1
and measured interception was 160 mm a-1
. The average values
computed in this study for biosphere forest objects were 417 mm a-1
for throughfall and
131 mm a-1
for interception. Measurements of tree-level transpiration in the forest
intensive monitoring plots using the sap flow measurement system have so far indicated
that transpiration rate varies between 160 and 220 mm a-1
. Average transpiration rate
computed for the biosphere objects was 200 mm a-1
(range 175-233 mm a-1
).
Average drainage flux for computed for the biosphere cropland objects was 130 mm a-1
(range 119-137 mm a-1
). The corresponding measured flux in Finnish field experiments
in other areas for clay soils have been reported to be around 100-150 mm a-1
, which is
of the same magnitude than in biosphere cropland objects. Average surface runoff of
cropland objects (69 mm a-1
) was smaller than generally measured in Finnish
experiments (100-150 mm a-1
). There are two main reasons for this. Firstly, yearly
precipitation in Olkiluoto is around 100-150 mm a-1
smaller than in southern Finland
where most of the reference field experiments are located. Secondly, surface runoff is
low since the topography of cropland areas is very flat in Olkiluoto. Total
evapotranspiration (sum of transpiration, interception and soil evaporation) for cropland
objects was 355 mm a-1
is within the range estimated for typical conditions in western
Finland.
The main goal of the sensitivity and uncertainty analysis described in Chapter 4 was to
recognize the most important factors that need to be studied in future biosphere
assessments. Detailed sensitivity and uncertainty analysis for examining the influence of
various input data and parameters on solute concentration profiles in biosphere forest
and cropland objects should be done during the next round of the biosphere assessment
process.
Simulation runs were carried out with water flow model and the numerical solute
transport model (unretarded transport). The relative concentration of solutes in the root
zone was the main criteria for evaluating how sensitive and uncertain the model results
are for different parameters. The main factors that influence solute concentration profile
in the biosphere forest objects are stream density, horizontal hydraulic conductivities in
overburden soils, distribution of precipitation to throughfall, interception and
transpiration, discharge through bedrock interface and thickness of the overburden
profile. In biosphere cropland objects the results are most sensitive to drainage density,
horizontal hydraulic conductivities in overburden soils, transpiration and discharge
through bedrock interface.
The study is part of the biosphere assessment within the safety case for the spent nuclear
fuel repository. Based on the results of this study the most important research topics
regarding the combined use of UNTAMO-model and Olkiluoto surface hydrological
model in computing water balance components for the biosphere object modules are:
55
i. Estimate influence of uncertainty in soil thickness data provided by the
UNTAMO-model on vertical and horizontal fluxes in biosphere objects with
specific interest in vertical upward flux to root zone/catotelm-acrotelm.
ii. Include estimation of forest type and forest biomass as UNTAMO output to get
consistent forest evolution prediction both in terrain and ecosystems
development modelling and in surface hydrological model.
iii. Evaluate the influence of forest type and forest biomass on distribution of
precipitation between throughfall, interception and transpiration and estimate
what is the effect of these data on vertical upward flux to root zone.
iv. Develop procedures for automatic delineation of forest areas that feed mire areas
(forest that discharge through peat areas to rivers and lakes). Compute the effect
of horizontal flux from forest areas on water balance components of peat bogs.
v. Examine the influence of stream density in forest and mire objects and drainage
density in cropland objects on vertical upward flux to root zone.
vi. Estimate the effect of uncertainty in bedrock hydraulic conductivity on discharge
through bedrock interface.
56
57
REFERENCES
Beven, K., 1991. Modeling preferential flow: an uncertain future?. In: Gish, T.J.,
Shirmohannadi, A. (Eds.), Preferential Flow, American Society of Agricultural
Engineers, St Joseph, MI, pp. 1–11.
Celia, M.A., E.T. Bouloutas, and R. Zarba. 1990. A general mass- conserved numerical
solution for the unsaturated flow equation. Water Resour. Res. 26:1483–1496.
Chittaranjan, C., Ellsworth, T.R., Valocchi, A.J. and Boast, C.W. 1997. An improved
dual porosity model for chemical transport in macroporous soils. J. of Hydrology 193
(1997), 270-292.
Clymo, R.S. 1984. The limits to peat bog growth. Philosophical Transactions of the
Royal Society of London. Series B, Biological Sciences, Volume 303, no. 1117, p.
605–654.
Dolman, A.J. and Nonhebel, S. 1988. Modelling forest water consumption in the
Netherlands. Agricultural Water Management, 14 (1988), 413-422.
Eronen, M., Glückert, G., van de Plassche, O., van de Plicht, J. & Rantala, P. 1995.
Land uplift in the Olkiluoto-Pyhäjärvi area, southwestern Finland, during last 8000
years. Nuclear Waste Commission of Finnish Power Companies (YJT), Helsinki,
Finland. Report YJT-95-17, 26 p.
Gerke, H.H., van Genuchten, M.Th., 1993a. A dual-porosity model for simulating the
preferential movement of water and solutes in structured porous media. Water Resour.
Res. 29, 305–319.
Gerke, H.H., van Genuchten, M.Th., 1993b. Evaluation of a first order water transfer
term for variably saturated dual-porosity flow models. Water Resour. Res. 29, 1225–
1238.
Gerke, H.H., van Genuchten, M.Th., 1996. Macroscopic representation of structural
geometry for simulating water and solute movement in dual-porosity media. Adv. Water
Resour. 19, 343–357.
Gwo, J.P., Jardine, P.M., Wilson, G.V., Yeh, G.T., 1995. A multiple-pore-region
concept to modeling mass transfer in subsurface media. J. Hydrol. 164, 217–237.
Haapanen, R. 2006. Results of Monitoring at Olkiluoto in 2005. Environment. Posiva
Working Report 2006-68.
Haapanen, R. 2007. Results of Monitoring at Olkiluoto in 2006. Environment. Posiva
Working Report 2007-52. 111 p.
Haapanen, R. 2008. Results of Monitoring at Olkiluoto in 2007. Environment. Posiva
Working Report 2008-25. 155 p.
58
Haapanen, R. 2009. Results of Monitoring at Olkiluoto in 2008. Environment. Posiva
Working Report 2009-45. 272 p.
Haapanen, R., Aro, L., Ilvesniemi, H., Kareinen, T., Kirkkala, T., Lahdenperä, A.-M.,
Mykrä, S., Turkki, H. & Ikonen, A. T. K. 2007. Olkiluoto Biosphere Description 2006.
POSIVA 2007-02; www.posiva.fi
Hjerpe, T., Ikonen A.T.K. & Broed, R. 2010. Biosphere assessment 2009. Posiva Oy,
POSIVA report, in preparation.
Hökkä, H. 2008. Tree stand transpiration in forest intensive monitoring plots (FIP) on
Olkiluoto Island – Measurement system and tentative results from summer 2007. Posiva
memo POS-003795. 15 p.
IAEA 2006. Geological Disposal of Radioactive Waste – Safety Requirements. IAEA
Safety Standards Series WS-R-4, International Atomic Energy Agency, Vienna, May
2006.
Ikonen, A.T.K. 2006. Posiva Biosphere Assessment: Revised structure and status 2006.
POSIVA 2006-07. www.posiva.fi
Ikonen, A.T.K. 2007. Meteorological Data and Update of Climate Statistics of
Olkiluoto 2005 – 2006. Posiva Working Report 2007-86.
Ikonen, A.T.K., Hjerpe, T., Aro, L., & Leppänen, V., 2007. Terrain and ecosystems
development model of Olkiluoto site, version 2006. Posiva Working report 2007-110.
Posiva Oy, Olkiluoto, Finland.
Ikonen, A.T.K., Aro, L. Haapanen, R. Kirkkala, T., Koivunen, S., Lahdenperä, A-M,
Puhakka, L., Salo, T. 2010a. Site and regional data for biosphere assessment in 2009.
Posiva Oy, Working Report, in preparation.
Ikonen, A.T.K., Gunia, M. & Helin J. 2010b. Terrain and ecosystems development
model of Olkiluoto site, version 2009. Posiva Oy, Working Report, in preparation.
Jauhiainen, M. 2004. Relationships of particle size distribution curve, soil water
retention curve and unsaturated hydraulic conductivity and their implications on water
balance of forested and agricultural hillslopes TKK-VTR-12. Doctoral thesis, Helsinki
University of Technology, Laboratory of Water Resources. 167 p.
Jarvis, N.J., 1998. Modeling the impact of preferential flow on nonpoint source
pollution. In: Selim, H.M., Ma, L. (Eds.), Physical Nonequilibrium in Soils: Modeling
and Application, Ann Arbor Press, Chelsea, MI, pp. 195–221.
Kahma, K. Johansson, M. & Boman, H. 2001. Meriveden pinnankorkeuden jakauma
Loviisan ja Olkiluodon rannikolla seuraavien 30 vuoden aikana (in Finnish: The
distribution of the sea water level at the coasts of Loviisa and Olkiluoto in the following
30 years). Helsinki, Finland: Merentutkimuslaitos. 28 p.
59
Karvonen, T. 1988. A model for predicting the effect of drainage on soil moisture, soil
temperature and crop yield. Helsinki University of Technology, Publications of the
Laboratory of Hydrology and Water Resources Engineering, 1, 215 pp.
Karvonen, T. 2008. Surface and near-surface hydrological model of Olkiluoto Island.
Posiva Working Report 2008-17.
Karvonen, T. 2009a. Increasing the reliability of the Olkiluoto surface and near-surface
hydrological model. Posiva Working Report 2009-07.
Karvonen, T. 2009b. Development of SVAT model for computing water and energy
balance of the Forest Intensive Monitoring Plots on Olkiluoto Island. Posiva Working
Report 2009-23.
Kellomäki S., Wang K-Y. 2000. Modelling and measuring transpiration from Scots pine
with increased temperature and carbon dioxide enrichment. Annals of Botany 85, 263–
278.
Keskitalo, K. 2008. Slug tests in PP- and PVP-holes at Olkiluoto in 2007. Olkiluoto,
Finland: Posiva Oy. Working Report 2008-21. 81 p.
Keskitalo, K. & Lindgren, S.. 2007. Slug tests in PP- and PVP-holes at Olkiluoto in
2006. Olkiluoto, Finland: Posiva Oy. Working Report 2007-93. 81 p.
Koivusalo, H. and Kokkonen, T. 2002. Snow processes in a forest clearing and in a
coniferous forest, Journal of Hydrology, 262, 145-164.
Kuusisto, E. 1984. Snow accumulation and snowmelt in Finland. Publications of the
Water Research Institute 55, National Board of Waters, Helsinki, Finland, 149 pp.
Laine-Kaulio, H. 2008. Subsurface flow in a forested till slope: soil analysis, tracer
experiments and physics-based modelling. Thesis for the degree of Lic. Sci. in Tech.,
Helsinki University of Technology. Department of Civil and Environmental
Engineering, Laboratory of Water Resources.
NEA 2004. Post-closure safety case for geological repositories – Nature and purpose.
Organisation for Economic Co-operation and Development, Nuclear Energy Agency.
Nykyri, M., Nordman, H., Marcos, N., Löfman, J., Poteri, A. Hautojärvi, A. 2008.
Radionuclide Release and Transport - RNT-2008. Posiva Report 2008-06.
Oltchev, A., Cermak, J., Nedezhdina, N., Tatarinov, F., Tishenko, A., Ibrom, A. and
Gravenhorts, G. 2002. Transpiration of a mixed forest stand: field measurements and
simulation using SVAT models. Boreal Environment Research 7: 389-397.
Oreskes N, Shrader-Frechette K, Belitz K. 1994. Verification, validation and
confirmation of numerical models in the earth sciences. Science 1994;264:641–6.
60
Paasonen-Kivekäs M., Vakkilainen, P., Karvonen, T., 2008. Nutrient transport trough
tiledrains on a clayey field. In Publication Proceedings of the 10th intenational
drainage workshop of ICID working group on drainage. Helsinki University of
Technology, Water Resources Publications, TKK VTR-16, Espoo. 142-152.
Pohjola, J., Turunen, J. & Lipping, T. 2009. Creating high-resolution digital elevation
model using thin plate spline interpolation and Monte Carlo simulation. Posiva Oy,
Working Report 2009-56.
Posiva 2008. Safety Case Plan 2008. Posiva Oy, Report POSIVA 2008-05.
Posiva, 2009. Olkiluoto Site Description 2008. Posiva Oy, Report POSIVA 2009-01.
Pruess, K., Wang, J.S.Y., 1987. Numerical modeling of isothermal and non-isothermal
flow in unsaturated fractured rock—a review. In: Evans, D.D., Nicholson, T.J. (Eds.),
Flow and Transport through Unsaturated Fractured Rock, Geophysics Monograph, vol.
42. American Geophysical Union, Washington, DC, pp. 11–22.
Päivänen, J. 1973. Hydraulic conductivity and water retention in peat soils. Seloste:
Turpeen vedenläpäisevyys ja vedenpidätyskyky. Acta Forestalia Fennica 129:170.
Refsgaard, J.C. and Henriksen, H. J. 2004. Modelling guidelines––terminology and
guiding principles. Advances in Water Resources 27 (2004) 71–82.
Simunek, J., Jarvis, N., van Genuchten, M.Th., Gärdenäs, A. 2003. Review and
comparison of models for describing non-equilibrium and preferential flow and
transport in the vadose zone. Journal of Hydrology 272 (2003) 14–35.
Sun N.-Z., Mathematical Modeling of Groundwater Pollution, Springer-Verlag New
York Inc. and Geological Publishing House, 1996, 377 p.
Tammisto, E. & Hellä, P. and Lahdenperä, J. 2005. Slug tests in PP- and PVP-holes at
Olkiluoto in 2004. Olkiluoto, Finland: Posiva Oy. Working Report 2005-76. 87 p.
Tammisto, E. & Lehtinen, A. 2006. Slug tests in PP- and PVP-holes at Olkiluoto in
2005. Olkiluoto, Finland: Posiva Oy. Working Report 2006-100. 93 p
Tracy, F. T.,1995. 1-D, 2-D, 3-D analytical solutions of unsaturated flow in
Groundwater, Journal of Hydrology 170, pp. 199-214.
Vakkilainen, P. 2009. Hydrologian perusteita (Basics of hydrological cycle). In
Publication Maan vesi- ja ravinnetalous. Kuivatus, kastelu ja ympäristö (Water and
nutrient balance of soils. Drainage, irrigation and environment). Ed. Paasonen-
Kivekäs, Peltomaa, R., Vakkilainen, P. and Äijä, H. Salaojayhdistys ry, 2009.
van Genuchten, M. Th., 1980. A Closed form equation for predicting the hydraulic
conductivity of unsaturated soils. Soil Sci. Soc. Am. J., 44, 892-898.
61
van Genuchten, M. Th., 1981. Analytical solutions for chemical transport with
simultaneous adsorption, zero-order production and first-order decay, Journal of
Hydrology vol. 49, pp. 213-233.
Vehviläinen, B. 1992. Snow cover models in operational watershed forecasting.
Publications of Water and Environment Research Institute 11, National Board of Waters
and the Environment, Finland, 112 pp.
Vieno, T. & Ikonen, A. T. K. 2005. Plan for Safety Case of Spent Fuel Repository at
Olkiluoto. POSIVA 2005-11.
Vuorela, A. Penttinen, T. & Lahdenperä, A-M. 2009. Review of Bothnian Sea shore-
level displacement data and use of a GIS tool to estimate isostatic uplift. Posiva Oy,
Working Report 2009-17. 191 p.
Warsta, L. 2007. Modelling overland and subsurface drainage runoffs at an agricultural
field. Thesis for the degree of Lic. Sci. in Tech., Helsinki University of Technology.
Department of Civil and Environmental Engineering, Laboratory of Water Resources.
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APPENDIX A: PARAMETER VALUES USED IN THE MODELS
Table A-1. Parameters of the van Genuchten soil water retention curve: θS is saturated
water content, θR is residual water content, α [m-1
], β [-] are empirical constants.
64
Table A-2. Saturated hydraulic conductivity value (m s-1
).
Table A-3. The parameters of the overstorey (trees) interception sub model.Interception
model described in Karvonen (2009b).
65
Table A-4. The parameters of the understorey interception sub model.Interception
model described in Karvonen (2009b).
Table A-5. Parameter values of canopy conductance model. Canopy model described in
Karvonen (2009b).
66
Table A-6. Parameter values of snow models. Snow model described in Karvonen
(2009b).
67
APPENDIX B: DESCRIPTION AND CODE VERIFICATION OF THE SOLUTE TRANSPORT MODEL
B.1 Introduction
Radionuclide transport modeling results described by in Section 3.1 were computed using
the particle tracking algorithm that is very useful in finding flow pathways of
radionuclides. However, the tracking method cannot easily be used in estimating
concentrations of radionuclides in biosphere objects. Therefore, it is necessary to develop
numerical solution methods for solute transport. The numerical models can take into
account the influence of advection, diffusion, dispersion, adsorption and radioactive decay
on behavior of solutes.
In this study the role of numerical model is to verify the results obtained from particle
tracking algorithms (see Chapter 4) but in future assessments it is very likely that
numerical methods should be used to estimate the influence of channeling and preferential
flow paths on local concentration maxima inside biosphere objects.
Preferential flow in structured media (both macroporous soils and fractured rocks) can be
described using a variety of dual-porosity, dual-permeability, multi-porosity, and/or multi-
permeability models (Pruess and Wang, 1987; Gerke and van Genuchten, 1993a; Gwo et
al., 1995; Jarvis, 1998). Dual-porosity and dual-permeability models both assume that the
porous medium consists of two interacting regions, one associated with the inter-
aggregate, macropore, or fracture system, and one comprising micropores (or intra-
aggregate pores) inside soil aggregates or the rock matrix. While dual-porosity models
assume that water in the matrix is stagnant, dual-permeability models allow for water flow
in the matrix as well. The dual-permeability version is most suitable for computation of
preferential flow in overburden soils and it will be described here.
B.2 Soil water balance
Different types of dual-permeability approaches may be used to describe flow and
transport in structured media. Several assume similar governing equations to describe
flow in the fracture and matrix regions, while others use different formulations for the
two regions. The approach selected in this study has been suggested by Gerke and van
Genuchten (1993a, 1996) and Chittanjan et al. (1997) who both applied Richards
equations to each of two pore regions. The flow equations for the fracture (subscript f)
and matrix (subscript m) pore systems are, respectively,
wqqqS
x
HK
xt
HhC
wqqqS
x
HK
xt
HhC
wBmLmDmm
j
mm
i
mmm
wBfLfDff
j
f
f
i
f
ff
1)(
)(
(B-1)
where xi (i=1,3) is the coordinate, t is time, H is total hydraulic head (H=h+x3), h is the
pressure head (m), is the water content (m3 m
-3), K is the unsaturated hydraulic
68
conductivity function, S is a sink term (m3 m
-3d
-1), qD is drainage flux term (open ditch
or subsurface drain) (m3 m
-3d
-1), qL is lateral flux term from biosphere object to a
neighbouring object (m3 m
-3d
-1), qB is flux to bedrock system (negative if flux from
bedrock to overburden layers) (m3 m
-3d
-1), Γw is the mass transfer function and w is the
ratio of volumes of the fracture and the total pore systems [-]. Matrix and fracture pore
systems are coupled with the mass transfer function Γw, and a macroscopic approach
suggested by Chittanjan et al. (1997) was adopted here:
(B-2)
where αw is the first order mass transfer coefficient.
This dual-permeability approach is relatively complicated in that the model requires
characterization of water retention and hydraulic conductivity functions (potentially
of different form) for both pore regions, as well as the hydraulic conductivity function
of the fracture–matrix interface.
van Genuchten model of soil water retention curve
Van Genuchten (1980) proposed an approximation for the water retention characteristic
(B-3)
where h is soil pressure head (soil matric potential), α [m-1
], β [-] are empirical
constants and γ = 1 - 1/β. Effective saturation Se of the soil is defined as
(B-4)
where θ is the volumetric water content of the soil, θS is saturated water content and θR
is residual water content. Water content θ can be solved from equations (B-3) and (B-4)
when the pressure head h is known. Unsaturated hydraulic conductivity K(h) of a soil
can be described with the product of saturated hydraulic conductivity KS and relative
hydraulic conductivity KR(h).
(B-5)
B.3 Solute transport model
Analogous to Eqs. (B-1) and (B-2), the dual-permeability formulation for solute
transport can be based on convection–dispersion type equations for transport in both the
fracture and matrix regions as follows (modified from Gerke and van Genuchten,
1993a):
69
)1()(
)1(
)(
wCkCqqqS
x
Cq
x
CD
xt
sf
t
C
wCkCqqqS
x
Cq
x
CD
xt
sf
t
C
SmmmBmLmDmm
i
mm
j
mmm
i
mmm
SfffBfLfDff
i
ff
j
f
ff
i
fff
(B-6)
where sub index f refers to preferential flow (fractures, macro pores), C is solute
concentration in pore water (e.g. Bq l-3
), s is solute concentration in the solid phase (Bq
kg-1
), f is the dimensionless fraction of sorption sites in contact with the fractures
(mobile water),q is the volumetric flux density (Darcy flux) (m d-1
), k is a first-order
decay constant (d-1
), is the soil bulk density (kg dm-3
), and D is the dispersion and
diffusion coefficient (m2 d
-1). The transfer rate, Γs, for solutes between the fracture and
matrix regions is usually given as the sum of diffusive and convective fluxes, and can
be given as (Chittanjan et al. 1997):
(B-7)
where S is solute transfer coefficient (d-1
), is dimension conversion coefficient which
has a value of unity and d is flow direction switch. d is zero if flow is from macropore
to matrix (Γw >0) and d=1 if Γw <0.
B.4 PRINCIPLE OF CODE VERIFICATION OF THE SOLUTE TRANSPORT
MODEL
Models describing water flows, water quality and ecology are being developed and
applied in increasing number and variety. With the requirements imposed by the EU
Water Framework Directive the trend in recent years to base water management
decisions to a larger extent on model studies and to use more sophisticated models is
likely to be reinforced. Refsgaard and Henriksen (2004) have proposed a framework for
model quality assurance guidelines, including a consistent terminology and a foundation
for a methodology bridging the gap between scientific philosophy and pragmatic
modelling.
According to modelling guidelines suggested by Refsgaard and Henriksen (2004) and
previously by Oreskes et al. (1994) one essential step in model building is called code
verification. The ability of a given model code to adequately describe the theory and
equations defined in the conceptual model by use of numerical algorithms are evaluated
through the verification of the model code. The methodologies used for code
verification include comparing a numerical solution with an analytical solution or with a
numerical solution from other verified codes. However, some programme errors only
70
appear under circumstances that do not routinely occur, and may not have been
anticipated. Furthermore, for complex codes it is virtually impossible to verify that the
code is universally accurate and error-free. Therefore, the term code verification must
be qualified in terms of specified ranges of application and corresponding ranges of
accuracy.
In this study the code verification the solute transport model was carried out by
comparing the numerical solutions of the models with selected analytical solutions. An
analytical solution gives exact values for soil water content or solute concentration for
defined initial and boundary conditions and with known solute transport parameters.
The drawback of the analytical solutions is that their applicability is usually restricted to
homogenous soil properties and simplified boundary conditions. However, analytical
solutions are very useful in verifying the numerical solutions.
The final aim of the code verification is to show that the model produces accurate
results for solute concentrations if initial and boundary conditions and the model
parameter values are known precisely. This implies that the numerical discretization
does not produce error to the solution if the grid is dense enough. In real applications
the influence of grid density has to be examined separately for each case and it is not
possible to give any general rules on selection of number of cells needed to get accurate
results.
B.5 Code verification of the solute transport sub model
Van Genuchten (1981) and Sun (1996) have given analytical solutions for solute
transport including advection, dispersion, adsorption and radioactive decay. The 1D-
analytical solution giving exact concentration in an infinite soil profile is given in Eq.
(B-4) together with the appropriate initial and boundary conditions (Sun 1996).
0
220
220
),0(;0)0,(
/2
/4/4
/2exp
/2
/exp
2
/2
/4/4
/2exp
/2
/exp
2),(
CtCxC
RDt
RkDvtxerfcRkDv
RD
x
RD
RvxC
RDt
RkDvtxerfcRkDv
RD
x
RD
RvxCtxC
(B-8)
where C(x,t) is solute concentration at point x (m) and at time t (d), v is pore water velocity
(m d-1
), D is dispersion coefficient (m2 d
-1), k is the exponential radioactive decay
coefficient (d-1
), and R is the retardation coefficient that takes into account linear,
instantaneous adsorption. Retardation factor R can be computed from
dKR 1 (B-9)
where is soil bulk density (kg dm-3
), is soil moisture content (porosity if pores are
saturated) and Kd is the distribution coefficient (dm3 kg
-1). Kd is zero if the solute is not
71
adsorbed to soil particles. The higher the distribution coefficient the greater the amount of
adsorption. Adsorbed amount S (mg kg-1
) san be computed from Eq. (B-6).
CKS d (B-10)
The code verification test was such that solute was assumed to enter the soil profile from
the bottom with constant input reference concentration C0=100 units. The thickness of the
soil profile (overburden layer) was assumed to be 3.0 m and soil was divided to 0.05 m
thick layers (60 nodes).
Test case 1 with no adsorption and no decay
In the first test example only advection and dispersion were included. Pore water
velocity v was 0.01 m d-1
, hydro-dynamic dispersion coefficient D was 0.002 m2 d
-1,
distribution coefficient Kd and radioactive decay coefficient k were zero. Comparison of
analytical solution given by Eq. (B-8) and the numerical solution is given in Figure B-1
and shows excellent agreement indicating the model code does not produce numerical
errors with the parameters selected above.
Test case 2 with adsorption and radioactive decay included
In the second test example advection, dispersion, adsorption and radioactive decay were
included. Pore water velocity v was 0.01 m d-1
, hydro-dynamic dispersion coefficient D
was 0.001 m2 d
-1, distribution coefficient Kd was 0.5 and radioactive decay coefficient k
was 0.005 d-1
(half life 139 d). Comparison of analytical and numerical solution is given
in Figure B-2 and results are very good also in this test example.
Test case 3 with fast radioactive decay included
The purpose of test example 3 is to see if the numerical model can reproduce the case
when radioactive decay is so rapid that the concentration front does not advance with
time but stabilizes to a certain steady state condition. The following parameter values
were used: pore water velocity v=0.01 m d-1
, hydro-dynamic dispersion coefficient
D=0.002 m2 d
-1, distribution coefficient Kd=0 and fast radioactive decay (k=0.05 d
-1,
half life 14 d). The agreement between analytical and numerical solutions shown in
Figure B-3 is very good also this test case.
72
Figure B-1. Comparison of analytical and numerical solution of solute transport.
Analytical solution given by Sun (1996). Pore water velocity v=0.01 m d-1
, hydro-
dynamic dispersion coefficient D=0.002 m2 d
-1, no adsorption (distribution coefficient
Kd=0) and no radioactive decay (k=0).
Figure B-2. Comparison of analytical and numerical solution of solute transport.
Analytical solution given by Sun (1996). Pore water velocity v=0.01 m d-1
, hydro-
dynamic dispersion coefficient D=0.001 m2 d
-1, distribution coefficient Kd=0.5 dm
3 kg
-
1,and radioactive decay k=0005 d
-1.
73
Figure B-3. Comparison of analytical and numerical solution of solute transport.
Analytical solution given by Sun (1996). Pore water velocity v=0.01 m d-1
, hydro-
dynamic dispersion coefficient D=0.002 m2 d
-1, no adsorption (distribution coefficient
Kd=0) and fast radioactive decay (k=0.05 d-1
).
74
