integrated hydrologic flow characterization of...
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INOM EXAMENSARBETE SAMHÄLLSBYGGNAD,AVANCERAD NIVÅ, 30 HP
, STOCKHOLM SVERIGE 2016
INTEGRATED HYDROLOGIC FLOW CHARACTERIZATION OF THE KRYCKLAN CATCHMENT (SWEDEN)
ELIN JUTEBRING STERTE
KTHSKOLAN FÖR ARKITEKTUR OCH SAMHÄLLSBYGGNAD
INTEGRATED HYDROLOGIC FLOW
CHARACTERIZATION OF THE KRYCKLAN
CATCHMENT (SWEDEN)
Elin Jutebring Sterte
Degree project no. 2016:14
KTH Royal Institute of Technology
Architecture and Built Environment
Division of Land and Water Resources Engineering
SE-100 44 Stockholm, Sweden
TRITA-LWR Degree Project
ISSN 1651-064X
LWR-EX-2016:14
Abstract
Currently there are urgent water related problems, such as use of groundwater and
surface water resources, which need a more integrated view on the hydraulic cycle and how
the different processes interact with each other. This has led to new ways of thinking in
management of watersheds, which sparked the creation of new integrated tools for flow
characterization. Characterization of a watersheds flow is an important step in future
research regarding water quality and climate change issues.
The Krycklan catchment, located in the northern part of Sweden, has been under
research for many years. With a great deal of measurements regarding stream water
chemistry as well as climate measurements (evaporation, transpiration and temperature),
the catchment has great potential regarding solute transportation and climate change
investigation.
This thesis was made to aid in future research by characterization of the catchments
groundwater and surface flow, by the use of an integrated model software tool, MIKE-SHE.
The model have been calibrated and validated with the help of real time observed
measurements at Krycklan combined with model data from SMHI:s HYPE-model.
Throughout the calibration it was discovered that the hydraulic conductivities were
important for the surface and groundwater interaction, regulating base flow as well as peak
flows. The shape and timing of the spring flood was also affected by the snow melt while
the summer peaks for the upstream rivers, probably due to the relatively large difference in
topography elevation, were more affected by the representation of the topography created
by the grid size.
A smaller grid-size resulted in a finer representation of the topography, which resulted
in a quicker runoff to the upstream rivers without an increase of base flow. This gave better
fitted hydrographs of the flows in the upstream rivers compared to observed
measurements. The final model created was able to capture the discharge-hydrograph and
groundwater fluctuations with small error and high correlation coefficients compared to
observed data and model data from SMHI.
The results as well as the calibration process helped with a deeper understanding of the
modeling tool itself as well. Future improvements that can be considered are to introduce
new calibration data and the use of an even smaller grid size. This can improve the
understanding of the catchment as well as the representation of the flow in the upstream
rivers. However, the effects of a smaller grid size must be reflected upon. The model will
most likely become more unstable and the run time of the model will greatly increase. One
suggestion to solve this issue is to look into a sub-catchment to reduce these complications.
Key words: Krycklan, MIKE-SHE, Integrated Model, Groundwater, Surface
water
Summary in Swedish
Vattenrelaterade problem som t.ex. användandet av vattenresurser, så som gund- och
ytvatten, har lett till att det idag krävs en mer integrerad syn på hur de olika processerna i
den hydrauliska cykeln samverkar med varandra. Det nya synsättet samt hanteringen av
vattenresurser i avrinningsområden har krävt nya metoder och verktyg för
flödeskarakterisering, då flödeskarakterisering av ett avrinningsområde är ett viktigt steg i
forskning om exempelvis vattenkvalitet och klimatrelaterade frågor.
Krycklan avrinningsområde, som är beläget i norra Sverige, har varit ett forsknings
objekt under många år. Mätningar av vattenkemin i området samt klimat mätningar
(avdunstning, evapotranspiration och temperatur), har gett området en stor potential när
det gäller framtida forskning inom transport och klimatförändringar.
Denna avhandling gjordes för att underlätta framtida forskning genom karaktärisering
av avrinningsområdets grundvattenflöden och ytflöden, med hjälp av att skapa en
integrerad modell i datorprogrammet MIKE-SHE. Modellen har kalibrerats och validerats
med hjälp av observerade mätningar vid Krycklan i kombination med modelldata från
SMHI: s modell HYPE.
Under kalibreringprocessen observerades det att de hydrauliska konduktiviteterna var
mycket viktiga för interaktionen mellan yt- och grundvatten och reglerade både bas och
toppflöden för bäckarna i området. Formen och tidpunkten för vårfloden påverkades även
av snösmältning medan sommartoppar för bäckarna uppströms påverkades mer av
representationen av topografin i området. Detta troligtvis för att de var lokaliserade i de
högst belägna områdena där skillnaden i topografin var som störst.
En mindre cell-storlek gav en finare representation av topografin, vilket hade en
märkbart positiv effekt på resultaten. Det gav en snabbare avrinning till bäckarna
uppströms utan en ökning av basflöde och resulterade i en slutlig modell med hade hög
korrelation och relativt små fel jämfört med observerad data.
Resultaten samt kalibreringsprocessen har hjälpt till med en djupare förståelse av
modelleringsverktyget. Framtida förbättringar som kan ytterligare förbättra modellen
innefattar mindre cell-storlek storlek samt ny kalibreringsdata. Nya data kan underlätta
förståelsen för hur avrinningsområdet fungerar och den mindre cell-storleken kan
ytterligare förbättra representationen av flödena i området. Emellertid måste en mindre
cell-storlek övervägas, då en mindre storlek kommer sannolikt öka instabilliteten av
modellen samt öka körtiden av programmet. Ett förslag för att lösa detta problem är att
istället modellera en mindre del av avrinningsområdet.
Acknowledgments
I like to firstly acknowledge my supervisor Sofie Soltani (Doctoral student at KTH) and
thank her for all her support, help and guidance throughout my thesis work. It has been an
honor to work with such a passionate teacher and researcher. Her insight in the modeling
tool and the modeling process, as well as her background in hydrology was very profitable
for the work. Secondly, I would also like to recognize my examiner Vladimir Cvetkovic
(Professor, Water Resources Engineering Deputy head and program director of research
studies), who didn’t just lend me his office, but also his computer during my stay at KTH.
Furthermore, a shout out should also be made to the researcher at Krycklan,
Hjalmar Laudon (Professor at the Department of Forest Ecology and Management) and
Johannes Tiwari (Experiment Technician at the Unit for Field-based Forest Research
Vindeln), who gave me quick answers regarding Krycklan whenever I needed their
assistance. Their knowledge and information about the catchment was very important for
my work, and I wouldn’t have been able to get this deep of an insight into the catchment
without them. Finally, I also like to thank my loving family, especially my mother, Monica
Jutebring, and my boyfriend, Anton Lövmar, for supporting me through the whole process
as well as keeping me happy and well fed.
TABLE OF CONTENTS
1. Introduction 1
1.1. Problem formulation 2
1.2. Aim and objectives 2
2. Background Theory 3
2.1. Hydrologic cycle and processes 3
2.1.1. Precipitation and evaporation 3
2.1.2. Infiltration and groundwater flow 4
2.1.3. Overland and stream flow 4
2.2. Distributed watershed models 5
2.2.1. MIKE-SHE 5
2.2.2. MIKE 11 6
2.3. Krycklan catchment and conceptual model 7
2.3.1. Model domain 8
2.3.2. Soil, geology and land use 9
2.3.3. General water balance 13
3. Material and method 14
3.1. Data 14
3.1.1 Topography 14
3.1.2 Climate data 15
3.1.3 Land use 16
3.1.4 Saturated and unsaturated zone 17
3.1.5 Rivers (MIKE 11) 19
3.2. Method 21
3.2.1 Boundary conditions and initial values 21
3.2.2 MIKE-SHE Model Setup 23
3.2.3 Calibration and Validation 24
4. Calibration procedure and early runs 27
5. Result 34
5.1 Calibrated and validation result – observed measurements 34
5.2 Calibrated and validation results – modeled measurements 37
6. Discussion 40
6.1 Model grid size 40
6.2 Unsaturated zone 40
6.3 Snow melt 41
6.4 Calibration Data 41
6.5 Calibration and Validation results 41
7. Conclusions and final thoughts 42
8. References 43
9. Other sources 44
Appendix A I
Appendix B II
Definitions and Abbreviations
Definitions
1 Aquifer A geological formation (e.g. a porous soil or a fractured
bedrock), with an amount of water that is profitable to
extract, e.g. as drinking water
2 Base flow The flow in a river which comes from groundwater.
Groundwater is the primary source of water for a river
or stream during dry weather.
3 Catchment An area where water is collected due to the landscape
and where precipitation and runoff is flowing towards
the same point
4 Discharge The rate of flow in a specific point in a channel
calculated as m3/s
5 Esker/Ice river sediments Long ridge of sand, sand and gravel or gravel, formed
during the last deglaciation.
6 Glacial deposit A soil created by a glacier. Examples are esker/ice river
sediments and tills.
7 Hydraulic conductivity A soils or bedrocks ability to release water taking into
account the properties of the fluid
8 Hydraulic head elevation Represents a fluids potential to flow through a porous
media and is calculated as the pressure head (m) added
to the elevation of the fluid above a reference elevation
(usually the sea level) (m).
9 Peak flow The maximum flow of a stream created by base flow and
surface runoff created during rainy events.
10 Permeability A soils or bedrocks ability to release water measured in
m2.
11 Porosity The amount of voids in % of a soil or bedrock
12 Precipitation The product off all atmospheric water vapour that falls
to the ground. Some of the main forms of precipitation
include snow and rain. Often measured in mm.
Abbreviations
1 m.a.s.l. Measurement that stands for “meter above sea level”.
2 m.b.g.s Measurement that stands for “meter below ground
surface”.
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1. INTRODUCTION
Flood impacts, water quality and water shortage are some of the more urgent water
related problems today. Traditionally surface and groundwater related issues have been
treated separately. However, lately there has been an increased understanding that these
issues cannot be handled individually, since they often are connected to one another. Use
of surface and groundwater resources requires an integrated management of both surface
and groundwater flow together with ecology and chemistry to allow a sustainable use of
water. Therefore, instead of looking at different parts of the hydraulic cycle, the focus has
been shifted to look at the interactions of the different parts hydraulic cycle of entire
watersheds (Singh & Frevert, 2005).
The shift in focus didn’t only need new ways of managing watersheds, but also new tools
for flow investigation. Traditional models couldn’t answer more complex questions
regarding water quality, wetland management, changes in land-use and impact of
groundwater and surface water use. For example, impacts of water pollution and urban
development are far from fully understood (Singh & Frevert, 2005). Furthermore, a
growing interest in the impacts of climate change has also increased the amount of
research relating to the complex interaction between the atmosphere and surface and
groundwater flow (Scibek, et al., 2007; Singh & Frevert, 2005). To be able to take in
consideration these interactions new types of modelling tools were needed, the so called
fully integrated modelling tools.
Integrated models are based on a petrophysical model combined with a traditional flow
simulator. The combination of these models allows calculations that can aid to monitor e.g.
fluid movements in porous media (Fanchi, John, 2000). Since they take different parts of
the hydrogeological cycle into consideration at the same time they have an advantage when
looking into transport and climate scenarios. A well characterized groundwater and surface
water flow in one of these integrated models can therefore later be used when looking into
e.g. transport of pollutants were exchange between different hydrologic processes are
important, such as overland flow and groundwater flow (Singh & Frevert, 2005).
A watershed catchment in Sweden that has been undergoing long term research
regarding climate and water quality is the Krycklan catchment. The catchment is situated
in the northern part of Sweden, northwest of the city Umeå (Laudon, et al., 2013), and
consists of a landscape which is characteristic for around 30 % of the world’s forest areas.
The landscape is made up of mires, streams, lakes and forests, which also is a
representative landscape for 70 % of Sweden (Laudon, 2013). The catchment is about 6780
ha large and is a part of Svartberget, which is an experimental park and a field station. The
Swedish Forestry Service created the park in the 1920th and today the park belongs to the
Swedish University of Agricultural Science (Taberman, 2015). It provides a long-term field
research that is easily accessible and since the start over a thousand scientific publications
and about a hundred PhD-theses has contained results from the park. Half of the
information is presumed to come from the Krycklan catchment (Laudon, 2013).
About 30 % of the Swedish ICOS sites (Integrated carbon observatory system) are
located at Svartberget. These include two ecosystem sites and one atmospheric tower. The
tower, which is located in Krycklan, is 150 m high and integrates the carbon signal for the
northern part of Sweden. At lower levels in the terrain the tower is complimented by
sensors which locally measure exchanges rates of carbon, energy and water between the
soil/forest canopy and the atmosphere (Laudon, 2013).
2
Thinning effects and forest paludification were some of the early study areas related to
the catchment. In the 1970s, during the time the Svartberget field station was created, the
research focus changed into biogeochemical cycling and forest hydrology. This research
was followed by about 10 years of an intensive study regarding acid deposition in the
1990th (Laudon, et al., 2013). Some of the more recent studies made on the area includes
research on boreal streams (Laudon, et al., 2007) and discharge variability in a boreal
landscape (Lyon, et al., 2012).
1.1. Problem formulation
During the autumn of 2016, Sofie Soltani (Doctoral student and teacher at KTH Royal
Institute of Technology) will make a more intensive research regarding natural attenuation
in Krycklan. Natural attenuation (self-purification) consists of all processes that directly or
indirectly change the structure or phase of pollutants. These processes can be divided into
two main groups; abiotic attenuation (e.g. hydrolysis, radioactive decay, redox reactions,
sorption, precipitation, volatilization and complexation) and biological attenuation
(degradation and recycling of pollutants directly made by microorganisms). To contribute
to the future research of Sofie Soltani, an integrated model over the catchment area is to be
made. This type of model could be very important in order to have a basis for further
investigation regarding water quantity and quality matters.
1.2. Aim and objectives
The aim of this study is to get a better understanding of the hydrology of the Krycklan
catchment in an integrated manner. The tool to be used to evaluate the flow in the
catchment is the distributed integrated flow model MIKE-SHE.
The integrated model will include a saturated zone, an unsaturated zone, a runoff model
as well as a model for river flow (MIKE 11). To achieve a model that later can be used for
research of e.g. natural attenuation, the model must also be calibrated and validated
through field data and measurements from the catchment area. More specific objectives
are specified below:
To set up a working groundwater model in MIKE-SHE and couple it with a river flow
model made in MIKE 11.
Base the model on local meteorological data and including all metrological aspects in
the model (precipitation, potential evapotranspiration, temperature and snowmelt).
Create an unsaturated zone and saturated zone based on field data acquired from the
researchers at Krycklan.
Include land use in the model, e.g. differences in vegetation types, root depth etc.
Manually calibrating the model by the use of time varying groundwater level
measurements and surface runoff measurements.
Validating the model by ensuring that it works for another time period than used for the
calibrating process.
Evaluate the models performance and look in to future possible model improvements
Get a better understanding about the model tool and what parameters that effects the
different processes in MIKE-SHE
3
2. BACKGROUND THEORY
The MIKE-SHE software program is an integrated model based on the hydrological
cycle. Important input data that is needed is e.g. a description of the soil and geology, as
well and climate data. To get a better understanding for these different parts, this section is
dedicated for describing the important parts of the hydrologic cycle as well as the modeling
tool and the Krycklan catchment.
2.1. Hydrologic cycle and processes
The hydrological cycle is a major part of hydrology and describes the important
hydrological processes on earth and how these processes are connected to each other
(Chow, et al., 1988). These processes main energy source is the solar energy and the mayor
parts of the hydrological cycle are (Fig 1.) (Rast, et al., 2014):
Precipitation and evaporation
Infiltration and groundwater flow
Surface runoff and stream flow
2.1.1. Precipitation and evaporation
Precipitation is the part of the hydrological cycle that includes e.g. rain, and snow,
which are processes when water falls onto the ground surface. The process when water is
later transformed from a liquid to a vapor is called evaporation. The process mainly gets its
energy from the solar radiation which provides the latent heat that is needed for the
vaporization process. One of the most important factors for evaporation is the temperature
at the surface. The higher the temperature, the more effective the evaporation is. At
locations with large water content (e.g. mires) or locations with open water surfaces (e.g.
lakes and oceans) the majority of the water evaporates, but there is also a significant
Figure 1 – The main parts of the hydraulic cycle
4
amount of water which evaporates from surfaces with vegetation. This type of evaporation
is called transpiration (Andréasson, 2006).
Transpiration is the part of water which evaporates from vegetation through plant
leaves (Andréasson, 2006). Factors that define the effectiveness of a plant to do
transpiration are the plants stages of development as well as the characteristics of the
plants leaves and roots. All plants are different, and different crops will also absorb
different amount of solar energy to preform transpiration (Tanguy, 2013). Evaporation and
transpiration are together called evapotranspiration (Andréasson, 2006).
2.1.2. Infiltration and groundwater flow
The part of the precipitation that doesn’t evaporate is called net precipitation (Knutsson
& Morfeldt, 1993). This is the part of the precipitation that has the ability to land on the
ground and create overland flow, ponded water or seeping through the ground surface,
which is also known as infiltration.
Factors that affect the infiltration and the infiltration rate are e.g. the soils hydraulic
conductivity, the local vegetation and the soils moisture content. When a soil reaches the
maximum rate at which a soil can absorb water in a specific condition (infiltration
capacity), ponded water is created (Chow, et al., 1988). The water that has infiltrated is
firstly stored in the root zone and unsaturated zone (the part of the soil which pores is not
completely filled with water) and is available for the vegetation. When the soil reaches the
field capacity (the amount of water a soil can hold) the water percolates to the ground
water.
The saturated zone is the zone which soils pores are completely filled with water
(Andréasson, 2006). Water in the ground is driven from areas with higher potential energy
to areas with lower potential energy. A simplified description of the flow in the saturated
zone, assuming the soil to be uniform in all directions, can be described by Darcy’s law as
(Knutsson & Morfeldt, 1993):
𝑄 = 𝐾 × 𝑖 × 𝑎 (1)
𝑄 = 𝐷𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒 [𝑚3
𝑠]
𝐾 = 𝐻𝑦𝑑𝑟𝑎𝑢𝑙𝑖𝑐 𝑐𝑜𝑛𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 [𝑚
𝑠]
𝑖 = 𝑝𝑜𝑡𝑒𝑛𝑡𝑎𝑖𝑙 𝑔𝑟𝑎𝑑𝑖𝑒𝑛𝑡 [𝑚
𝑚]
𝑎 = 𝑐𝑟𝑜𝑠𝑠 − 𝑠𝑒𝑐𝑡𝑖𝑜𝑛 𝑎𝑟𝑒𝑎 [𝑚2]
2.1.3. Overland and stream flow
Overland flow occurs only when the saturated zone reaches the ground surface or if the
infiltration capacity is reached due to e.g. high rain intensity (Rumynin, 2015). On its way
downhill it will be gradually concentrated into channels. The flow depth and velocity of
these streams and rivers can be described with the help of Manning’s equation which states
that (Chow, et al., 1988):
𝑉 = 𝑅2
3 × 𝑆1
2 ×1
𝑛 (2)
𝑉 = 𝑉𝑒𝑙𝑜𝑐𝑖𝑡𝑦 𝑜𝑓 𝑤𝑎𝑡𝑒𝑟 [𝑚/𝑠]
𝑆 = 𝑆𝑙𝑜𝑝𝑒 𝑜𝑓 𝑐ℎ𝑎𝑛𝑛𝑒𝑙 𝑏𝑜𝑡𝑡𝑜𝑚 [𝑚/𝑚]
𝑅 = 𝐻𝑦𝑑𝑟𝑎𝑢𝑙𝑖𝑐 𝑟𝑎𝑑𝑖𝑢𝑠 [𝑚]
𝑛 = 𝑀𝑎𝑛𝑛𝑖𝑛𝑔′𝑠 𝑟𝑢𝑔ℎ𝑛𝑒𝑠𝑠 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑒𝑛𝑡 [𝑠/𝑚1
3]
5
2.2. Distributed watershed models
It is important when modelling large scale catchment to take in consideration the
spatial variability since it usually have more various hydrological conditions than smaller
catchments. Furthermore, watersheds that include varied topography generally have
greater diversity in geology, soil, vegetation and climate. Thus larger catchment areas
usually pose a greater challenge from a modelling stand point than smaller catchments
(Wang, et al., 2012).
There has been a surge for developing distributed watershed models due to the
increasing availability of spatial data (Sorooshian, et al., 2008). The characteristics of a
catchment are represented by giving data to grid points in a network. Sometimes there is a
need to use about a 1000 grid points which are assigned several different variables and
parameters. This is one of the main differences between a distributed watershed model and
a lumped model. The lumped model is usually regarded as a single unit with some
parameters and variables used to characterize the model area (Refsgaard, 1997). Spatial
variability is disregarded in these types of models and one is instead trying to relate the
input and outputs of the model. Here the inputs usually works as forcing data (Sorooshian,
et al., 2008).
The amount of parameters that can be changed during calibration has been a critique
against distributed watershed models. The concern is that the potential for
overparameterization is greater for a distributed model than a lumped model (Beven,
1996). However the parametersation procedure is considered essential to avoid
methodological issues in the later stage of model calibration and validation (Refsgaard,
1997). During the parameterization process, the range of the parameters should be
established so that they reflect the acquired field data, e.g. by using representative values
for different soil types. This can significantly reduce the amount of “free” (excessive)
parameters that will be needing adjustments during the calibration process (Refsgaard,
1997), since excessive parameters are regarded as the main source of errors in distributed
models (Sorooshian, et al., 2008).
2.2.1. MIKE-SHE
A distributed watershed model that is capable of simulating the major parts of the
hydrologic cycle is MIKE-SHE (Rahim, et al., 2012). The model is based on the tool named
Système Hydrologique Européen (SHE) which was firstly operational in 1982. DHI
(Danish Hydraulic Institute), one of the model developers continued to improve the model
and today it consists of several water quality modules and a water movement module
(Zhang, et al., 2008). The version used for this project is 2016, powered by DHI (Danish
Hydraulic Institute).
Through the model the catchment area is discretized both vertically and horizontally by
the creation of a grid network. The grid network enables spatial variability in parameters
in the catchment such as land cover (evaporation and transpiration parameters) and
hydraulic parameters for soil and bedrock (Yan & Zhang, 2001). The equations that
represent the different processes in the model are listed below. Equations for interception
and snowmelt are solved by empirical equations which have been obtained from research
made by DHI. The following partial equations are however solved by finite difference
methods (Rahim, et al., 2012):
6
Overland flow: Two-dimensional (2D) diffusive wave approximation Saint Venant
equation
Channel flow: One-dimensional (2D) diffusive wave approximation Saint Venant
equation
ET – The methods of Kristensen and Jensen
Unsaturated flow: One-dimensional (1D) Richards equation
Saturated flow (subsurface flows): Three-dimensional (3D) Boussinesq equation
In MIKE-SHE a modified degree-day method is used to describe snowmelt. The
program uses two snow storage methods; one for frozen and one for melted snow. Melted
snow storage is used to simulate the fact that snowmelt does not become runoff until it’s
too wet for the snowmelt to hold the water. During melting, dry snow is firstly converted to
wet snow and later becomes runoff when the user specified storage fraction is met.
Freezing occurs when the temperature falls below the freezing point. At this temperature
melted snow is also refrozen (DHI, 2007).
The St. Venants equation is used for the overland flow. This equation neglects
momentum losses due to inflows from the sides which are perpendicular to the flow
direction. It also neglects the momentum losses due to local and convective acceleration
(DHI, 2007).
In MIKE-SHE, evaporation includes transpiration, interception and evaporation from
open waters, snow covers and soil moisture. The soil moisture content as well as the
evapotranspiration is calculated through the Kristensen and Jensen method by taking in
consideration root depth, leaf area index and the potential evapotranspiration. The leaf
area index describes the ratio between the area of a plant and the total leaf area covered by
it (Bosson, et al., 2010; DHI, 2007).
Unsaturated flow in MIKE-SHE is based on the one dimensional Richards equation,
which is a sufficient method for most applications since gravity is the dominant force
acting on infiltration. For the saturated zone, however, a three-dimensional (3D)
Boussinesq equation is used. The two modules (the saturated zone and unsaturated zone)
works parallel to each other to allow them different time steps. The saturated zone usually
has a time step of hours to days, while the unsaturated zone usually has a time of minutes
to hours. If the groundwater level reaches ground level, exchange of water can be done
directly between the saturated zone and the overland flow (DHI, 2007).
Model limitations are that the model requires extensive amount physical parameters
and data, which may not be available in all cases. The model is also proprietary, which
means that the model code cannot be changed by the user to fit specific projects better. The
model has however been well tested prior to release and gives the user the additional
capabilities for graphical pre- and post-processing which often is a missing features in
other model tools (Yan & Zhang, 2001).
2.2.2. MIKE 11
MIKE 11 is a modelling tool that can be used to simulate e.g. flows and channels. It is a
fully dynamic one dimensional modelling tool that can be used on both simple and
complex river systems. The model can be linked to the groundwater simulation made in
MIKE-SHE so that water may be exchanged between the two modules (DHI, 2003a). There
are several different methods for coupling MIKE-SHE with MIKE 11 described in (DHI,
2003b). However, in this model the overbank spilling option is used as in (Bosson, et al.,
2010). This option treats the river banks as weirs allowing water from a river to spill onto
7
the MIKE-SHE model. Overbanking occurs when the water level is above either left or
right bank elevation or if the water level in MIKE 11 is higher than the elevation of ponded
water in MIKE-SHE. If the MIKE-SHE model however has a depth of overland water
which allows overland flow, this will be added to the MIKE 11 model as lateral flow.
Weather water will spill from the MIKE 11 model onto the MIKE-SHE model is based on
the weir formula (Bosson, et al., 2010):
𝑄 = ∆𝑥 × 𝐶 × (𝐻𝑢𝑠 − 𝐻𝑤)𝑘 × (1 − (𝐻𝑑𝑠−𝐻𝑤
𝐻𝑢𝑠−𝐻𝑤)
𝑘)
0.385
(3)
𝑄 = 𝐹𝑙𝑜𝑤 𝑎𝑐𝑐𝑟𝑜𝑠 𝑡ℎ𝑒 𝑤𝑖𝑒𝑟 [𝑚3
𝑠]
∆𝑥 = 𝐶𝑒𝑙𝑙 𝑤𝑖𝑑𝑡ℎ [𝑚]
𝐶 = 𝑊𝑖𝑒𝑟 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 [𝑚1
2/𝑠]
𝐻𝑢𝑠 𝑎𝑛𝑑 𝐻𝑑𝑠 =
𝐻𝑖𝑔ℎ𝑡 𝑜𝑓 𝑤𝑎𝑡𝑒𝑟 𝑢𝑝𝑠𝑡𝑟𝑒𝑎𝑚 𝑎𝑛𝑑 𝑑𝑜𝑤𝑛𝑠𝑡𝑟𝑒𝑎𝑚 𝑡ℎ𝑒 𝑤𝑖𝑒𝑟 [𝑚]
𝐻𝑤 = 𝐻𝑖𝑔ℎ𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑤𝑒𝑖𝑟 [𝑚]
𝑘 = ℎ𝑒𝑎𝑑 𝑒𝑥𝑝𝑜𝑛𝑒𝑛𝑡
MIKE 11 is built up on several editors. The main editors used for flow simulations are
called:
Simulation editor
River network editor
Cross-section editor
HD editor
Boundary editor
The simulation editor is used to start the MIKE 11 simulation as well as connect the
different editors to the network editor. The network editor is the key editor of the program
and gives an overview of all the components in the model and it is here the rivers
coordinates/location and connections to MIKE-SHE are made. Here, the locations of the
cross-sections made in the cross-section editor are also visible. The cross-sections are used
to describe the shape and slope of the rivers and streams and it is necessary to at least have
one cross-section for each river or stream used in the MIKE 11 model. The HD
(hydrodynamic) editor includes additional data which is needed for the simulation.
However, most of these parameters have default values that are sufficient for most
simulations. The last editor is the boundary editor which is used to specify boundaries to
the MIKE 11 model (DHI, 2003b). All upstream and downstream ends of the model require
boundary conditions. In MIKE 11, the upstream boundary conditions are usually based on
a discharge hydrograph or a constant discharge from e.g. a reservoir. The downstream
boundary conditions are instead based on either a constant water level (if the river
discharges into a large water body), a time series for a water level or a well-defined rating
curve (DHI, 2009).
2.3. Krycklan catchment and conceptual model
The conceptual model contains a description of the model domain, soil and geology and
a description of the rivers and lakes in the area. The section ends with a rough estimation
of the water balance.
8
2.3.1. Model domain
Krycklan catchment, the model domain, is located in the northern part of Sweden (64°,
14’N, 19°46’E). The topography of the area defines the catchment, where the mountains to
the east, northwest and south is assumed to act as water divides (Fig. 2). These include the
mountains:
Näverliden, Buberget and Ö Kryckeltjärn (east)
Koverberget and Abborrtjärn (northwest)
Mullkälen and Riskälen (south)
Figure 2 – The Krycklan Catchment boundaries. The catchment is marked in purple. The figure was acquired
from (©Sveriges geologiska undersökning; ©Lantmäteriet, 2016a)
Outside of the catchment area, close to the borders there are some larger rivers called
Yttersjön (north) and Abborrtjärnen (southwest). The river Vindälven is located to the west
of the catchment. Within the catchment area, there are some smaller lakes and pounds.
There are also some streams in the area. The main streams are called Åhedbäcken,
Långbäcken, Nymyrbäcken and Krycklan. There is also a smaller creek at site 7, were
discharge rates have been measured since 1980th (Fig. 3).
9
The catchment have been divided into 18 smaller sub-catchments for research purposes,
where the oldest monitoring station is located at site 7, which was established in 1980.
Later in 1984, site 2 and 4 were established and were later expanded to 18 sites in 2002
(Fig. 2). At Site 7, the discharge from the main sub-catchment creek has been monitored,
and daily data is available on Krycklan database (www.slu.se). There is also available data of
the chemistry of the main streams of the sub catchment alongside daily climate data
measurements of temperature, precipitation and potential evapotranspiration made at
Svartbergets climate station.
Figure 3 – Research sites in Krycklan (red circles) and location of Svartberget field station. The figure was
acquired from (Laudon, 2013).
2.3.2. Soil, geology and land use
Krycklan is mostly covered by till, sand and silt, with some smaller areas covered by
other soils such as peatlands (Fig. 4 and 5). The areas with silt/clay and postglacial
deposits are mostly located alongside the small streams within the catchment area
(©Sveriges geologiska undersökning; ©Lantmäteriet, 2016a), below what was once the
highest postglacial sea level at approximately 257 m.a.s.l (Laudon, et al., 2013). Above the
highest postglacial sea level the area is mostly covered by till, where areas with peat is
10
located alongside the rivers. The elevation of the area ranges between 405 to 114 m.a.s.l
and is undergoing isostatic rebound due to the last deglaciation (Laudon, et al., 2013).
In the south the esker Vindelälvsåsen is located (Fig. 6). The esker has a
recharge/discharge area outside of the catchment located close to the city Häggnäs, where
the esker is exposed. Around the esker the soil is of a sandy character.
Figure 4 - Soil types of the catchment of Krycklan, taken from (©Sveriges geologiska undersökning;
©Lantmäteriet, 2016a). At the higher elevations the soil mainly consist of till, while sandy sediments is the
dominating soil type downhill.
11
Figure 5 – Soil types of
Krycklan, acquired from
(Laudon, 2013). At the
higher elevations of the
catchment the main soil
consists of till, while more
silty materials dominates
the soils in the valleys.
Figure 6 – The esker
Vindälvsåsen and its
withdrawal opportunities.
The figure was acquired
from (©Sveriges geologiska
undersökning. &
©Lantmäteriet, 2016c).
12
Granite, gneiss, pegmatite and schist are some of the bedrock types that are located
within the area (© Sveriges geologiska undersökning; © Lantmäteriet, 2016b) and 94 % of
the area covered by bedrock classified as Svecofennian metasediments (Laudon, et al.,
2013). Furthermore, two deformation zones are connected within the catchment area (Fig.
7).
Through the contact with Hjalmar Laudon (Professor at the Department of Forest
Ecology and Management) and Johannes Tiwari (Experimental Assistant at the
Department of Forest Ecology and Management) some soil samples could be obtained.
The drilling samples have been gathered from five different sites; site 2, 9, 13, 16 and 22.
Whit these drilling samples, combined with information of soil types from (©Sveriges
geologiska undersökning; ©Lantmäteriet, 2016a) an overall soil layer map could be made
(Fig. 8). This soil layer map is the basis for the soil layers for the MIKE-SHE model. It is
assumed that the catchment area is mostly covered by a sandy/silty till. At high altitudes,
where water may have been trapped, peatlands and small lakes have been created. These
peatlands are assumed to be approximately 5 m in depth with an underlying clay layer (L1
and L5), going by the information given in (Laudon, et al., 2013). Furthermore, going by
information from the soil samples, combined with information from SGU, there seems to
be a silty/sandy layer covering most of the glacial sediments (L3).
Figure 7 – Deformation zones in Krycklan, acquired from (© Sveriges geologiska undersökning; ©
Lantmäteriet, 2016b)
13
Figure 8 – Conceptual soil layer map
The predominated vegetation type is forest, which covers almost 90 % of the catchment
and the dominating tree species are Scots pine and Norway spruce, which makes up about
63 % and 26 % of the tree population respectively. Beneath the trees the undergrowth
mainly consists of ericaceous shrubs on a mat of moss. Dominating moss species are
Pleurozium schreberi and Hylocomium splendens while the ericaceous shrubs mainly
consist of bilberry and cowberry and the peatlands are mostly covered by
Sphagnum species (Laudon, et al., 2013). Even though about approximately 25 % of the
area have been under protections since 1922, the main land use is still forestry and second
growth forest. There have also been around 76 deforestation areas identified within the
area between 1922 and 2010. This is about 7 % of the catchment area. The amount of
people living in the area is however rather low, with only about 100 inhabitants and with
only about 2 % of the area is made up of farmland (Laudon, et al., 2013).
2.3.3. General water balance
The water balance is based on a rough estimation of average annual precipitation over
the catchment area during the year 2012-2014. The precipitation is based on measured
data from Krycklan field station. Since most the boundaries are assumed to be no flow
boundaries (see section 4.2.1.), the precipitation is assumed to be the main input of water
into the area. To make an estimation of net precipitation (the water left for infiltration after
evapotranspiration) the average annual evapotranspiration have been used for the same
time period. Furthermore, for this rough estimation, the infiltration fraction (the amount
of water that will become groundwater recharge) is assumed to be 20 % (the model will
however base the infiltration on the hydrological prosperities of the unsaturated zone). The
remainder of water is assumed to become overland flow (Table 1).
14
2012 2013 2014
Annual average
Unit Table 1 – General water
balance. The water balance is
based on assumptions and
average yearly values
between the years 2012 and
2014
Catchment area
6780 ha
67.8 km2
Precipitation 927 646 584 729 mm/year
Evapotranspiration 379 489 513 460 mm/year
Net precipitation 530 155 71 269 mm/year
Net precipitation ratio
57 24 12 37 %
Infiltration fraction 20 %
Groundwater recharge
106 31 14 54 mm/year
Overland flow 424 123 57 215 mm/year
The precipitation and evaporation values are higher than the values presented in
(Laudon, et al., 2013). The values presented in (Laudon, et al., 2013) are however based on
measurements from 1981 to 2010. The mean annual precipitation during these years was
614 mm and the mean annual evaporation was 303 mm with a net runoff ratio (net
precipitation ratio) of approximately 50 %.
3. MATERIAL AND METHOD This section is dedicated to describe the most important parts of data used in the model
as well as the method used to calibrate and validate the model. Furthermore, this section
also introduces important information regarding boundary conditions and
calibration/validation data.
3.1. Data
The data used in the MIKE-SHE model was mostly acquired from the Krycklan data
service (Laudon, 2013), SGU and SMHI. The data is in more detail described below.
3.1.1 Topography
The topography is based on a 2*2m grid file acquired from GSD (2011). In MIKE-SHE
the model uses bilinear interpolation to resample the data to the same cell size as the
model domain (Fig. 9)
15
Figure 9 – Topographical map in m a.s.l. based on GSD (2011)
3.1.2 Climate data
The climate data has been acquired from Krycklan database (Fig. 10 and 11).
Measurements of the different climate factors have been made from Svartbergets climate
station and the data includes daily measurements of precipitation, evapotranspiration and
air temperature which dates back to 1981. The air temperature is measured in Celsius, the
precipitation is calculated in mm and the potential evapotranspiration is calculated in mm.
All climate data is assumed to be uniform for the whole catchment area. When data has
been missing for the potential evapotranspiration due to e.g. equipment failure at the
measuring station, the value from the same date the year before has been used. The
periods with missing evaporation data are:
2012-09-21 to 2012-10-14
2013-01-01 to 2013-01-31
2013-11-01 to 2014-02-28
2014-08-02 to 2014-08-04
2014-11-01 to 2014-12-31
16
Figure 10 – Climate data used in the MIKE She model, including Precipitation and evapotranspiration measured in mm
Figure 11 – Temperature data used in the MIKE-SHE model. The temperature is measured in degree Celsius
3.1.3 Land use
The vegetation file used in MIKE-SHE is a 25×25 m size grid file acquired from (GSD,
2010). In MIKE-SHE, the model uses bilinear interpolation to resample the data to the
same cell size as the model domain. The land cover data (Fig. 12) is based on the classification and interpretation of:
Landsat TM satellite data with input from mainly Lantmäteriets general map databases
(Terrain Map, GGD, Road Map, vegetation maps, orthophotos, etc.),
The National Forest Survey Data from SLU (Swedish University of Agricultural
Sciences)
Data from SMHI (Swedish Meteorological and Hydrological Institute )
Data from SCB (Statistics Sweden)
Data from Sweden (SGU geological survey)
Data from Environmental Protection Agency
Data from the County Administrative Board environmental devices
-10
0
10
20
30
40
50
60
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
mm
Climate Data
Precipitation Reference evaporation
-25
-15
-5
5
15
25
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
Tem
pera
ture
(C
)
Temperature
17
Figure 12 – A 25×25 vegetation grid file based on GSD (2010)
MIKE-SHE also requires a land use set up file. The one used in this model is based on
(Bosson, et al., 2010) and includes values for leaf area index (LAI), root depths and crop
coefficients (Kc). LAI is described as the area of leaves divided by the area of ground and
depends on the vegetation type. The root depth also depends of the vegetation type, but
also varies during the year. The reference evaporation of a specific crop is then adjusted to
the actual evapotranspiration with the help of the Kc values (DHI, 2007).
3.1.4 Saturated and unsaturated zone
The soil map in MIKE-SHE is based on ©Sveriges geologiska undersökning and
©Lantmäteriet (2016a), Laudon (2013) and the soil samples acquired from Krycklan (Fig.
13). The maximum soil depth has been taken from SGU, where the soil depth data has been
interpolated between wells in Sweden. SGU, however, points out that the soil depth is more
insecure the further away from a well the interpolation has been made. When it comes to
specific yield values and specific storage values, they have been set to an average for each
soil type in relation the values presented in Bosson, et al (2010). The unsaturated model
data setup for the soil layers is also taken from Bosson, et al (2010). In the model, the soil
layers are based on the schematic soil stratigraphy described in section 2.4. Because there
is little information regarding the differences in the vertical and horizontal hydraulic
conductivities in the area, these have been initially set to the same value in the model
(Table 2)
18
The vertical discretization was taken from (Bosson, et al., 2010) (Table 3). To avoid that
the saturated zone falls below the bottom level of the unsaturated zone (causing errors in
the MIKE-SHE model), the bottom level had to be extended to 52 m.b.g.s.
In the model there is also a 50 m deep bed rock layer with the bedrock deformation
zones seen in section 3.3.2. The deformation zones have been given a high hydraulic
conductivity of 1E-3 m/s to allow flow in the fractures, while the rock has been given a
lower hydraulic conductivity of 1E-7. At lower depth than 50 m, the bedrock is given a very
low hydraulic conductivity (1E-10 m/s) to take in consideration the rock stresses at lower
depth.
Figure 13 – Soil map constructed by the use of soil samples from Krycklan as well as the soil maps
acquired from ©Sveriges geologiska undersökning and ©Lantmäteriet (2016a) and Laudon (2013)
19
Table 2 – Unsaturated zone model set up and saturated zone properties assigned to the model. The
hydraulic conductivities are the initial conditions set for the model (see section 5.1.)
Unsaturated zone Saturated zone
Soil type Layer
Layer
symbol m.b.g.s
Hydraulic
conductivity (m/s)
Specific
yield (-)
Specific
storage (1/m)
Sandy/silty
sediments
Silt L3 1.2 1E-7 0.1 0.003
Sand L2a 3.8 5e-5 0.2 0.004
Silty clay L3b 4 5E-8 0.1 0.003
Sand L2b 10 5e-5 0.2 0.004
Sand/Gravel L8 Bottom
of Soil 1E-4 0.2 0.004
Sandy
sediments
Sand L2a 0.8 5e-5 0.2 0.004
Silty clay L3b 3 5E-8 0.1 0.003
Till L7 Bottom
of Soil 5E-6 0.03 0.001
Glacial
deposits Sand/Gravel L8
Bottom
of Soil 1E-4 0.2 0.004
Water (Lake
sediments)
Clay L5 5 1E-8 0.1 0.003
Till L7 Bottom
of Soil 5E-6 0.03 0.001
Till Till L7 Bottom
of Soil 5E-6 0.03 0.001
Bedrock
outcrops
Bedrock
outcrops L6
Bottom
of Soil 1E-10 0.15 0.001
Silty clay
Silty Clay L3b 3 5E-8 0.1 0.003
Till L7 Bottom
of Soil 5E-6 0.03 0.001
Peat
Peat L1 5 1E-6 0.2 0.006
Clay L5 7 1E-8 0.1 0.003
Till L7 Bottom
of Soil 5E-6 0.03 0.001
From depth To depth Cell height No of cells Table 3 – Vertical discretization of MIKE-SHE
model. The distances are measured in m 1 0 1 0.1 10
2 1 5 0.5 8
3 5 10 1 5
4 10 52 3 14
3.1.5 Rivers (MIKE 11)
The main streams in Krycklan have been extracted using the 2×2m topography grid file
from GSD (2011). The streams included in the model are Site 7, Nymyrbäcken Långbäcken,
Åhedbäcken and Krycklan (Fig. 14). The cross-sections for these streams were made with
the help of Jaremalm & Nolin (2006), which is a field survey over the streams of Krycklan
(Fig. 15). The bed resistance of the streams were described using a uniform value of
manning’s n (Manning’s n is equal to 1/Manning M). According to Chow (1959), a natural
20
channel can have a manning n between 0.1 and 0.03 s/m(1/3). This is approximately equal to
Manning M 10 to 30 m(1/3)/s. The initial value were set to 20 m(1/3)/s, but was later
calibrated (see section 3.2.3).
Figure 14 – Streams included in
the MIKE-SHE model. The red
circles displays the locations
were discharge calibration data
have been obtained from
Krycklan database and SMHI
Figure 15 – Krycklan streams in
the network editor together with
the location of the cross-section
made in MIKE 11. The cross-
sections are marked with a red
square and the start and end of
the streams are marked with a
blue square
21
3.2. Method
Using new soil sample information gathered from Krycklan catchment, alongside updated
soil type information from SGU, a new unsaturated and saturated zone layering could be
crated and implemented in MIKE-SHE. Some of the model parameters (the parameters
which had the most influence on the model result) were then calibrated through manual
calibration (see section 3.2.3). Using visual estimation and statistical evaluation, the
parameters were optimized to fit the time varying calibration data acquired from Krycklan
data service, SGU and SMHI (see section 3.2.3.).
3.2.1 Boundary conditions and initial values
Since the boundaries are topographical boundaries it is assumed that these are of the type
no flow (Fig. 16). However, to allow subsurface flow in the glacial sediments, a constant
head have been used as a boundary for the west and southeast. The constant head to the
west is based on the water level in the lake Gröntjärnen (171.3 m a.s.l.) (SMHI, 2012). This
lake is located within the glacial sediments themselves and is closely located to the
boundary of the catchment. To the southeast, the constant head have been calculated as an
average of the groundwater level measurements recovered from site 16 (-0.85 m.b.g.s).
Figure 16 – Boundary conditions used in the Model. Two fixed heads are used to the west and east of the
model, while the others are regarded as no-flow boundaries
22
The initial groundwater level is set to a level made from an earlier run when the initial
conditions were set to a global value of 0.5 m.b.g.s (base case). However, a six month run
up period is used before the calibration period to ensure that the initial conditions don’t
have to large influence on the model result. The calibration model start date is set to 2012-
06-30 and the end date is set to 2013-12-31, where the period between 2012-06-30 and
2013-01-01 is seen as a run up period and is not included when calibrating the model.
The boundary conditions for the river model made in MIKE 11 are upstream set to a
fixed discharge of zero flow and the boundary condition downstream was set to be a water
level time series as recommended by DHI (2009). The downstream boundary condition,
however, had to be calculated using Manning’s equation and the discharge rate at Krycklan
outlet. Discharge rate values, which include daily discharge values from the catchment,
have been acquired from SMHI:s model for runoff (HYPE). To solve the Manning’s
equation for y (water level) the mathematical computing software program MATLAB was
used since y had to be iterated for each time step. The water level was calculated through
the following relationships (Fig.17):
Figure 17 – Manning equation for a non-rectangular channel. The water depth is calculated as y
23
The values for the variables connected to the area of the outflow cross-section were
taken from (Jaremalm & Nolin, 2006). The slope (S) of the channel was obtained by
extracting the elevation difference between the Krycklan river outlet and the elevation of
the river 1000 m downstream by the use of the 5 m grid map also used for the topography.
A 5 m drop in elevation was obtained, giving the slope a value of 0.005 m/m. Manning M
(M=1/n) was initially assumed to be 20 m(1/3)/s, but was later manually calibrated.
3.2.2 MIKE-SHE Model Setup
Some model parameters were initially assumed as of the previous modeling studies on
sites with rather similar hydrologic characteristics (Bosson, et al., 2010) (Table 4). A few of
these parameters underwent calibration, since they have a great effect on the peak flows
and the magnitude of overland flow. For more specific information about the unsaturated
zone and the saturated zone, please read section 3.1.4 and for more information about the
calibration see section 3.2.3. Even though the model set up is foremost based on the model
set up presented in (Bosson, et al., 2010), the grid size is smaller (200 m instead of 1000
m) to get a better representation of the surface topography.
Unit Included in calibration Table 4 – MIKE-SHE
model set up. Some
model set up
parameters will
undergo calibration
and are therefore
marked with a “yes”
Simulation specification
Simulation period
Start date 2012-06-30
End date 2014-12-31
Time step control
Initial time step 1 hrs
Max allowed OL time step 1 hrs
Max allowed UZ time step 1 hrs
Max allowed SZ time step 3 hrs
Model domain
Cell size 200 m
Snow melt
Melting temperature 0.5 Yes
Overland flow
Manning M 10 m1/3/s Yes
Detention storage 2 mm Yes
Saturated zone
Drainage
Drain depth -1 m.b.g.s Yes
Drain constant 1e-6 Yes
24
3.2.3 Calibration and Validation
Three groundwater level series were used for calibration. These comes from
groundwater measurements from the middle of the catchment area and have the area
codes; 33_101, 33_104 and 33_105 (Fig. 18). The data was acquired from SGU (2016) and
includes e.g. coordinates and groundwater elevation time series (both in m.b.g.s and
m.a.s.l.). The m.b.g.s measurement was used, instead of m.a.s.l to take in consideration
that with a course grid of 200 m, the elevation level will be smoothen out and not get the
exact same elevation as reality, making m.a.s.l. real measurements in m.a.s.l. ending up
ether much lower or higher the ground surface compared to when measuring the
groundwater level in m.b.g.s.
Figure 18 – Location of measuring wells in Krycklan Catchment
25
There was also available discharge data for one of Krycklans sub-catchment, site 7. This
data was acquired from Krycklan database service. For the other parts of the catchment
calibration data was acquired by using model runoff data created by SMHI. The runoff data
comes from a conceptual hydrological model called HYPE (HYdrological Predictions for
the Environment) which calculates the water balance for watersheds and sub-watershed
based on land use, elevation and soil type. Available was e.g. daily measurements in m3/s
and it could be acquired for the streams Krycklan, Åhedbacken, Långbäcken and
Nymyrbäcken (Table 5).
Calibration data Type Source Table 5 – Summary of
calibration data Site 7 Discharge (Laudon, et al., 2013)
Well 101 Groundwater level (SGU, 2016)
Well 104 Groundwater level (SGU, 2016)
Well 105 Groundwater level (SGU, 2016)
Åhedbäcken Modeled discharge (SMHI, 2016)
Nymyrbäcken Modeled discharge (SMHI, 2016)
Långbäcken Modeled discharge (SMHI, 2016)
Krycklan Modeled discharge (SMHI, 2016)
The model was manually calibrated. During the manual calibration, the model
performance was evaluated using the visual difference between the models simulated
values and the observed/modeled values. For discharge measurements this was combined
with the statistical evaluation of RMSE (root mean square error), ME (mean error) MAE
(absolute error, and R (Pearson Correlation coefficient) and for groundwater
measurements the visual calibration was combined with ME and MAE.
𝑀𝐸 =∑ (𝑂𝑏𝑠𝑖,𝑡−𝑆𝑖𝑚𝑖,𝑡)𝑡
𝑁 (4)
𝑀𝐴𝐸 =∑ |(𝑂𝑏𝑠𝑖,𝑡−𝑆𝑖𝑚𝑖,𝑡)|𝑡
𝑁 (5)
𝑅𝑀𝑆𝐸 = √1
𝑁∑ (𝑂𝑏𝑠𝑖,𝑡 − 𝑆𝑖𝑚𝑖,𝑡)2𝑁
𝑖=1 (6)
𝑅 =∑ (𝑂𝑏𝑠𝑖,𝑡−𝑂𝑏𝑠𝑖,𝑡 )(𝑆𝑖𝑚𝑖,𝑡−𝑆𝑖𝑚𝑖,𝑡 )𝑁
𝑖=1
√∑ (𝑂𝑏𝑠𝑖,𝑡−𝑂𝑏𝑠𝑖,𝑡 )2𝑁𝑖=1 √∑ (𝑆𝑖𝑚𝑖,𝑡−𝑆𝑖𝑚𝑖,𝑡 )2𝑁
𝑖=1
(7)
OBS = Observed measurement Sim = simulated measurement 𝑂𝑏𝑠𝑖,𝑡
=Mean Observed measurement 𝑆𝑖𝑚𝑖,𝑡
= Mean simulated measurement
26
The closer ME, MAE and RMSE is to zero, the better the result. R, however, should be as
close to 1 as possible and describes how well the simulated values correlate to the observed
values. According to Evans (1996), the strength of the Pearson coefficient can be
interpreting as:
0.00-0.19 very weak
0.20-0.39 weak
0.40-0.59 moderate
0.60-0.79 strong
0.80-1.00 very strong
The parameters selected to undergo calibration (Table 6) seemed to have the most
influence on the model result. During the calibration phase, the modeled calibration data
from HYPE was given a lower priority than the real measured discharge and groundwater
levels in Krycklan.
Table 6 – Initial values and upper/lower limits for the parameters undergoing calibration
Upper limit Lower limit Initial value Unit
Hydraulic conductivities
L2a and L2b – Sand 1e-3 1e-6 5e-5 m/s
L3a – Silt 1e-6 1e-8 1e-7 m/s
L3b - Silt/clay 1e-7 1e-9 5e-8 m/s
L7 – Till 1e-3 1e-8 5e-6 m/s
L8 – Glacial deposits 1e-3 1e-7 1e-4 m/s
Other parameters
Melting temperature 0.5 0 0.5 C
Melting constant 4 2 2 mm/C/day
Manning Number overland flow (M) 20 2.5 10 m(1/3)/s
Detention Storage 50 1 2 mm
Drainage level -0.5 -1 -1 m.b.g.s
Drain constant 1e-6 1e-7 1e-6
Manning number channel flow (MIKE 11) 30 10 20 m(1/3)/s
The drainage depth was initially set to 0.5 m.b.g.s because a typical drainage depth is
usually between 0.5 to 1 m (Larsen, et al., 2010). Drainage is directed downhill based on
neighboring drain levels. Subsurface flow as drain is allowed as long as there is a
downward slope located within the model and will continue until the drain flow crosses a
river or the model boundary. The drain constant will affect the velocity of the drain flow
(DHI, 2007). It is usually set to a value between 1e-7 and 1e-6 (DHI, 2007) and will mostly
affect the peaks of the hydrographs (Larsen, et al., 2010).
For overland flow, manning M is used as the bed resistance. A lower M value will
decrease the velocity of the overland flow, leaving more water time to infiltrate. This will
reduce the amount of overland flow and therefore reduces the peaks of runoff flow (Larsen,
et al., 2010). According to Cronshey (1986), Manning’s n for overland flow seems to
depend on the vegetation. A fallow or a flat surface can have Manning’s n values down to
0.05 and 0.011s/m(1/3) respectively while woods with dense overgrowth can have Manning’
27
n values up to 0.80s/m(1/3). For this model the upper and lower limits for Manning’s n for
overland flow is set to 0.05 to 0.8 s/m(1/3). These are approximately equal to Manning’s M
of 1 to 20 m(1/3)/s. For channel flow (natural flow), Manning M is usually set between about
10 and 30 m(1/3)/s (Chow, 1959).
Before overland flow can occur, the overland water depth must have reached the
detention storage. A larger detention storage will reduce overland flow and let more water
infiltrate to the ground surface. More ponded water will therefore have a potential to
increase the water table in an area (Dai, et al., 2010). According to DHI (2007), a detention
storage could be set to around 2 mm, but there have been instances when a much larger
detention storage have been seen giving an optimum result for a MIKE-SHE model (up to
50mm) (Dai, et al., 2010). The upper and lower limits of this model have been set to 1 to 50
mm.
The hydraulic conductivities for the saturated zone influence both the base flow to the
rivers, as well as the peak flows. The vertical hydraulic conductivity effects mostly the
infiltration (if the soil is completely saturated) and larger vertical values increase the
infiltration rate and reducing overland flow. Larger vertical values will therefore result in
smother hydrograph, i.e. reducing peak flows. The horizontal values will both affect the
base and peak flows. By lowering the value of the horizontal hydraulic conductivities, the
subsurface flow can be delayed (Larsen, et al., 2010).
There is a large uncertainty regarding the composition of the glacial deposits in the area,
since there haven’t been any drilling samples taken directly from them. That includes
depth, width and material composition. The upper and lower limits of the hydraulic
conductivity of glacial deposits have therefore been taken from (Stephenson, et al., 1988)
which states that glacial deposits from ice river outwash usually consist of sand or of a
mixture of sand and gravel with a hydraulic conductivity ranging from 102 to 10-2 m/d
(approximately 10-3 to 10-7 m3/s). The calibrated value from (Bosson, et al., 2010) at 10-4
m/s will however stand as an initial condition for the model. The remaining upper and
lower limits of the hydraulic conductivities have been taken from (Knutsson & Morfeldt,
1993). Areas with silt/clay have however been given a slightly lower limits than silt, but a
slightly higher limit than clay.
The calibration was made for the period 2013-01-01 to 2013-12-31 with a run up period
of 6 month to reduce influences from the initial conditions. Model validation is made for a
period that is not used for calibration, nor for run up period. The period is run without
changing the values adjusted during the calibration stage. It’s said that the model is
validated if the calibrated model is able to be used for the validation period within some
predefined limits of acceptance (Henriksen, et al., 2003). 2014-01-01 to 2014-12-31 is
therefore used as a validation period and the level of acceptance is set to plus 10 % of the
RMSE error optimized during the calibration period.
4. CALIBRATION PROCEDURE AND EARLY RUNS
In this section the procedure of the calibration will be described in further detail to get a
better understanding of some of the calibration decisions made. During the earlier part of
the procedure the calibration was made mainly through looking at the visual effects of the
groundwater and discharge charts developed by MIKE-SHE. These charts were combined
with analyzation of the water balance of the domain. The combined information was used
to decide the next step of model calibration.
28
Without changes to the initial values the downstream rivers experienced too large base
flows while the upstream rivers did not receive enough water during the summer, i.e. no
peak flows during the summer month. All rivers also experienced a too early spring flood
created by the snow melt. It was therefore concluded that the base flow had to be reduced
and the overland flow to the upstream rivers increased. A water balance over the situation
was created for a better understanding of the hydrologic interactions in the catchment
(Fig.19).
Through the water balance chart, it could be established that the main contribution to
peak flows were overland flow, while base flow mainly came from groundwater. Drain
appeared to increase both peak flows and base flows, since it contributes with waters to the
rivers as soon as the groundwater level reaches the drain level assigned in the model.
During calibration of the parameters presented in section 3.1.3 it was established that
some parameters had more influence than others.
Figure 19 – Water balance
created from the initial
values. The water balance is
measured in mm,
accumulated flow and is
calculated for the calibration
year 2013 for the whole
catchment. Too much
groundwater is going to the
rivers as base flow
The hydraulic conductivities with the most influence on the base flow were the till (L7) for
site 7 and the glacial deposits (L8) and sand (L2b) for the streams Krycklan and
Åhedbäcken. The drain level mostly had effect on the amount of extra base flow that was
given to the rivers, not taking into account the peak flows. Lastly the melting constant had
the most influence on the shape of the spring flood.
In comparison of the initial trial with test A it could be concluded that the snow melt
and base flow could be calibrated by the parameters listed in section 3.1.3, however the
upstream peak flows was very little or not at all influenced by the calibrated parameters
(Fig. 20). Neither increasing Manning M for overland flow nor decreasing the detention
storage improved the results. Therefore the attention was switched to the vertical hydraulic
conductivity of the unsaturated zone, since the vertical hydraulic conductivity is
responsible for the infiltration rate. The purpose was to try to increase the overland flow
29
and drain to the uphill rivers, without increasing the base flow, nor peak flows for the
downstream rivers.
Figure 20 a. Discharge hydrograph using the initial
model set up. The initial trial is compared against
observed data at the site. The river receives no
peak flows during the summer months and the
spring flood arrives early and is slightly small
Figure 20 b. Discharge hydrograph using with
calibrated hydraulic parameters of the saturated
zone and snow melt. Test A is compared against
observed data at the site. Good timing and shape
of spring flood, although it’s large. No peak flows
during the summer months
Figure 20 c. Discharge hydrograph using the initial
model set up. The initial trial is compared against
model acquired from SMHI:s HYPE-model. The
river receives a large base flow compared to
observed data
Figure 20 d. Discharge hydrograph using with
calibrated hydraulic parameters of the saturated
zone and snow melt. Test A is compared against
model acquired from SMHI:s HYPE-model. Both
peak flows and base flows are well represented
Figure 20 – An example of one of the upstream rivers, Site 7, and the downstream river Åhedbäcken. The
figure. displays the impact on the discharge of test A compared to the initial trial
0
0,5
1
1,5
2013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3/s
Åhedbäcken
Initail trial Observed
0
0,02
0,04
0,06
2013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3/s
Site 7
Observed Test A
0
0,5
1
1,5
20
13-0
1-0
1
20
13-0
2-0
1
20
13-0
3-0
1
20
13-0
4-0
1
20
13-0
5-0
1
20
13-0
6-0
1
20
13-0
7-0
1
20
13-0
8-0
1
20
13-0
9-0
1
20
13-1
0-0
1
20
13-1
1-0
1
20
13-1
2-0
1
m3/s
Åhedbäcken
Test A Observed
0
0,02
0,04
0,062013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3/s
Site 7
Observed Initail trial
30
The unsaturated hydraulic conductivities, especially of the soil type till, had a larger
impact on the peak flows than the other already calibrated parameters. Test A and B
concluded that there was an increase in overland flow using a finer till but the groundwater
fluctuation decreased (Fig. 21) as well as a reduction of drain to the rivers (Table 7 and 8).
Most noticeable are the small peak flows for the upstream rivers due to more overland flow
and reduction of the spring flood for the downstream rivers du to less total flow to the
rivers (Fig. 21).
To ensure groundwater fluctuations, the unsaturated hydraulic conductivity of the till
had to be set to around 1e-6 m/s. Lower values gave a non-responsive groundwater (Fig.
20) and low drain (Table 10). This hydraulic conductivity gave however no peak flows for
the upstream rivers, but worked well for the downstream rivers. Therefore the till was
divided into two parts; one uphill site 7 and one downhill site 7.
Figure 21 - Groundwater
fluctuation example chart. The
initial trial, Test A and G all
experience groundwater
fluctuation during approximately
the same time period as the
observed measurements. When
using a fine till (a till with a
hydraulic conductivity around 1e-7
m/s) for the whole catchment the
groundwater fluctuations levels
out as in Test B
A layer of finer till had to be placed on top of a courser till uphill to get groundwater
fluctuation, but still getting enough water for peak flows during the summer month. It was
decided to further evaluate some of the test to see how the water balance was affected by
changes in the hydraulic conductivity in the unsaturated zone (Table 7 and 8). For an
overall evaluation of all tests A to F, see appendix A. Water balance charts for the tests in
Table 7 and 8 are also available in Appendix B.
Test E and G concluded that there was a slight improvement of the summer peak flows
with a fine till on top of the coarser till uphill without a reduction of the downstream spring
flood (Fig. 22 and Table 8). The most amount of water given to the rivers in these tests
were to test G, which had slightly more overland flow than test A, without a large reduction
in drain (Table 7). The overland flow also seemed to end up in the uphill rivers, without
increasing the peak flows in the downhill rivers (Fig, 22). However, the uphill river peak
flows were still very small and hardly visible and there were still some problems with a
reduced spring flood for these rivers.
254
254,5
255
255,5
m.a
.s.l.
Groundwater fluctuations well 101
Initail trial Test A Test B
Test G Observed
31
Figure 22 a. Discharge hydrograph of site 7 using
a finer till in the whole catchment. Test B is
compared against observed data at the site.
Delayed spring flood and reduced peak flows early
autumn. However, there are visible summer peak
flows
Figure 22 b. Discharge hydrograph of site 7 using
a finer till on top of the courser till uphill. Test G is
compared against observed data at the site.
Good shape and timing of the spring flood,
however it is reduced. Small, but visible peak flows
during summer and autumn
Figure 22 c. Discharge hydrograph over
Åhedbäcken using a finer till in the whole
catchment. Test B is compared against model
acquired from SMHI:s HYPE-model. Reduced
spring flood compared to observed measurements
Figure 22 d. Discharge hydrograph using a finer till
on top of the courser till uphill site 7. Test G is
compared against model acquired from SMHI:s
HYPE-model. Both peak flows and base flows
are well represented
Figure 22 – Discharge diagram example for one of the downstream rivers in Krycklan, Åhedbäcken.
0
0,02
0,04
0,06
2013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3/s
Site 7
Observed Test B
0
0,02
0,04
0,06
2013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3/s
Site 7
Observed Test G
0
0,5
1
1,5
2013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3/s
Åhedbäcken
Test B Observed
0
0,5
1
1,5
2013-0
1-0
1
2013-0
2-0
1
2013-0
3-0
1
2013-0
4-0
1
2013-0
5-0
1
2013-0
6-0
1
2013-0
7-0
1
2013-0
8-0
1
2013-0
9-0
1
2013-1
0-0
1
2013-1
1-0
1
2013-1
2-0
1
m3 /
s
Åhedbäcken
Test G Observed
32
In an attempt to improve the results further the grid size was reduced from 200 m to
100 m to give a better representation of the topography in the area. The model became very
unstable and was unable to completely run (Test H and I). It could however run long
enough to be able to evaluate the discharge hydrographs, but not long enough to provide a
complete water balance (Table 7 and 8). Without a finer till uphill there were some peak
flows for the upstream rivers, however, they were very small. It could however be resolved
by the introduction of a fine till layer above the courser till uphill.
To stabilize to model, a finer till had also to be used in the bottom of the till soil profile
(Test J). Furthermore, the hydraulic conductivities of the saturated zone had to be re-
calibrated to slightly adjust the base flows. However, this model worked well for both
groundwater fluctuations and peak flows and the results ended up to be the best of the
model simulations. The model gave the most water for peak flows (drain and overland
flow) to the streams of all models, while still having a good base flow. Most noticeable is
the increase of drainage to the rivers (Table 7).To ensure that the fine till in the bottom of
the soil profile did not affect the water balance more than to stabilize the model, a new test
was made in a 200 m grid (Test K), with the same settings as in test G. The model gave the
same results as test G, i.e. did not have any noticeable effect on water balance results of the
model (Table 7 and 8).
Table 7 – Water balance evaluation of the tests. The table displays the main parts of the water balance
calculated as mm accumulated flow for year 2013
Test
A
Test
B
Test
E Test G Test H Test I Test J Test K
Total P 646 646 646 646 - - 646 646
Total E 488 486 487 486 - - 485 486
P-E 158 160 159 160 - - 161 160
Error 2 3 3 3 - - 3 3
Total flow to river
Total river flow 204 185 204 208 - - 212 208
OL to river 40 43 40 45 - - 46 45
Base flow to river 52 51 52 52 - - 40 52
Drain to river 112 91 112 111 - - 126 111
Different ET components
Snow 43 43 43 43 - - 43 43
Interception 149 149 149 149 - - 149 149
Open water 18 18 18 18 - - 20 18
Soil 57 57 57 57 - - 56 57
Transpiration 219 218 219 218 - - 217 218
SZ 1 0 0 0 - - 0 0
Recharge and infiltration
Infiltration from
OL to UZ 757 663 720 707 - - 660 707
UZ deficit change 0.42 -17 -9 -10 - - 0.43 -10
Recharge from UZ
to SZ 491 407 455 446 - - 390 446
SZ storage change -54 -24 -60 -60 - - -63 -60
33
Table 8 – Evaluation results of the main impact of changes in the unsaturated zone and of the grid size
Test
A
Test
B
Test
E
Test
G
Test
H
Test
I
Test
J
Test
K
Un
satu
rate
d z
on
e d
escri
pti
on
Depth
m.
H. C
on.
Depth
m.
H. C
on.
Depth
m.
H. C
on.
Depth
m.
Depth
m.
Depth
m.
H. C
on.
Depth
m.
H. C
on.
Depth
m.
H. C
on.
Depth
m.
H. C
on.
Un
it
m
m/s
m
m/s
m
m/s
m
m/s
m
m/s
m
m/s
m
m/s
m
m/s
Up
str
eam
To b
edro
ck
1e-6
To b
edro
ck
1e-7
0.2
1e-7
0.2
1e-8
To b
edro
ck
1e-6
0.2
1e-8
0.2
1e-8
0.2
1e-8
To b
edro
ck
1e-6
To b
edro
ck
1e-6
To b
edro
ck
1e-6
5.3
1e-6
5.3
1e-6
To b
edro
ck
1e-7
To b
edro
ck
1e-7
Do
wn
str
eam
To b
edro
ck
1e-6
To b
edro
ck
1e-7
To b
edro
ck
1e-6
To b
edro
ck
1e-6
To b
edro
ck
1e-6
To b
edro
ck
1e-6
5.3
1e-6
5.3
1e-6
To b
edro
ck
1e-7
To b
edro
ck
1e-7
Gri
d s
ize
(m)
200
200
200
200
100
100
100
200
Evalu
ati
on
Peak f
low
s
up
hil
l
No
Sm
all
Very
Sm
all
Sm
all
Sm
all
Good
Good
Sm
all
Peak f
low
s
do
wn
hill
Good
Good
Good
Good
Good
Good
Good
Good
Sp
rin
g f
loo
d
up
hil
l
Good
Good, b
ut
dela
yed
Reduced
Reduced
Good
Good
Good
Reduced
Sp
rin
g f
loo
d
do
wn
hill
Good
Reduced
Good
Good
Good
Good
Good
Good
Gro
un
d-w
ate
r
flu
ctu
ati
on
s
Good
Very
Sm
all
Good
Good
Good
Good
Good
Good
Sta
ble
Model
Sta
ble
Model
Sta
ble
Model
Sta
ble
Model
Non-
sta
ble
model
Non-
sta
ble
model
Sta
ble
Model
Sta
ble
Model
34
Test J (100 m grid) combined with the final calibrated values (Table 9) gave the
optimum result of the manual calibration. The groundwater and discharge results of this
model can be seen in section 5.1 and 5.2.
Table 9 – Calibrated parameters used in the final model called test J
5. RESULT
In this section the result of the calibration and the validation will be presented. Since
the calibration data from HYPE have been given a lower importance compared to the
observed measurements at Site 7, well 101, well 104 and well 105, these have been
separated from each other.
The calibration was made manually to reduce the ME and MAE of well measurements
and to establish a close visual fit to the calibration measurements. The statistical
evaluation of ME and MAE was combined with RMSE and R for the discharge
measurements.
5.1 Calibrated and validation result – observed measurements
These calibrated results include the real time measurements for site 7, well 101, well 104
and well 105 compared with the model values for these sites. Site 7 is made up by discharge
measurements in m3/s and well 101, well 104 and well 105 includes groundwater
measurements in m.a.s.l.
The RMSE for the validation period site 7 was slightly lowered compared to the
calibration period, while the ME and MAE was slightly increased (Fig 23). The correlation
coefficient stayed high during both calibration and validation period (over 0.6) and it was
also increased between the calibration and the validation period. The model succeeds in
capturing the timing of the peaks and the base flow for both periods and the size of the
peak flows are often captured, even though they are at moments too high or too low.
Furthermore, the snow seams to melt somewhat early and too fast during April and May,
Horizontal hydraulic
conductivity
Vertical hydraulic
conductivity Unit
Hydraulic conductivities
L2a - Sand 1.0e-6 1.0e-6 m/s
L2b – Sand 8.2e-6 3.6e-6 m/s
L3a – Silt 1.0e-7 1.0e-7 m/s
L3b - Silt/clay 1.0e-8 1.0e-8 m/s
L7 - Till 1.0e-6 1.0e-7 m/s
L8 – Glacial deposits 1.0e-5 1.0e-5 m/s
Other parameters
Melting temperature 0 C
Melting constant 2 mm/C/day
Manning Number overland flow (M) 10 m(1/3)/s
Detention Storage 1 mm
Drainage level -0.96 m.b.g.s
Drain constant 1e-6
Manning number channel flow (MIKE 11) 30 m(1/3)/s
35
mostly visible during the validation period. The fast snowmelt results in a high and short
peak flow during these months, which should be lower and stretched out more during a
longer time period according to observed measurements.
Figure 23 – Modeled and
observed discharge
measurements at site 7,
including run up period from
2012-06-30 to 2012-12-31,
calibration period from 2013-
01-01 to 2013-12-31 and
validation period from 2014-
01-01 to 2014-12-31
Calibration (2013) Validation (2014)
Unit m3/s
RMSE 0.00590 0.00495
ME 0.00037 0.00168
MAE 0,00272 0.00286
R 0.64 0.70
The groundwater fluctuations captured by the model have an MAE varying between 1.25
to 0.20 m, with the best statistical result for well 104 and well 105. Well 101, do however
capture the groundwater fluctuations better, though the groundwater lever is slightly
higher than observed measurements (Fig 24 to 26).
The flatter groundwater fluctuations in well 104 and 105 can however be due to the
drain level. At this level, water is transported downhill to the streams in the area, resulting
in a flatter groundwater levels at places where the groundwater level reaches the drain
level. All groundwater level measurements are however sustainable, meaning that the areas
aren’t drained faster than what they are refilled, which are shown by the ground water
levels not dipping in mean level with time.
0
0,01
0,02
0,03
0,04
0,05
0,06
0,07
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
m3/s
Site 7
Observed discharge Site 7 Modeled discharge Site 7
36
Figure 24 - Modeled and
observed discharge
measurements for well 101,
including run up period from
2012-06-30 to 2012-12-31,
calibration period from 2013-
01-01 to 2013-12-31 and
validation period from 2014-
01-01 to 2014-12-31
Calibration (2013) Validation (2014)
Unit m
ME -1.25 -0.98
MAE 1.25 0.98
Figure 25 - Modeled and
observed discharge
measurements for well 104,
including run up period from
2012-06-30 to 2012-12-31,
calibration period from 2013-
01-01 to 2013-12-31 and
validation period from 2014-
01-01 to 2014-12-31
Calibration (2013) Validation (2014)
Unit m3/s
ME 0.15 0.20
MAE 0.20 0.20
254,5
255
255,5
256
256,5
257
257,52012-0
7-0
2
2012-0
9-0
2
2012-1
1-0
2
2013-0
1-0
2
2013-0
3-0
2
2013-0
5-0
2
2013-0
7-0
2
2013-0
9-0
2
2013-1
1-0
2
2014-0
1-0
2
2014-0
3-0
2
2014-0
5-0
2
2014-0
7-0
2
2014-0
9-0
2
2014-1
1-0
2
m a
.s.l.
Well 101
Modeled GW-level 101 Observed GW-level
254,4
254,8
255,2
255,6
20
12-0
7-0
2
20
12-0
9-0
2
20
12-1
1-0
2
20
13-0
1-0
2
20
13-0
3-0
2
20
13-0
5-0
2
20
13-0
7-0
2
20
13-0
9-0
2
20
13-1
1-0
2
20
14-0
1-0
2
20
14-0
3-0
2
20
14-0
5-0
2
20
14-0
7-0
2
20
14-0
9-0
2
20
14-1
1-0
2
m a
.s.l.
Well 104
104 Observed GW-level Modeled GW-level 104
37
Figure 26 - Modeled and
observed discharge
measurements for well 105,
including run up period from
2012-06-30 to 2012-12-31,
calibration period from 2013-
01-01 to 2013-12-31 and
validation period from 2014-
01-01 to 2014-12-31
Calibration (2013) Validation (2014)
Unit m3/s
ME -0.13 0.04
MAE 0.34 0.25
5.2 Calibrated and validation results – modeled measurements
These results includes the MIKE-SHE calibrated model discharge levels for the rivers
Krycklan, Åhedbäcken, Nymyrbäcken and Långbäcken together with the modeled values
from SMHI Hype-model. Since these calibrated values are compared to already modeled
values, they have been seen as a lower priority than Site 7, well 101, well 104 and well 105.
However, since there is little data for the overall model area, these have still been included
to represent other parts of the model area.
Compared to site 7, the shape of the snow melt peak flows fits these streams better;
however, it is slightly low for Nymyrbäcken and Långbäcken (Fig. 27, 28, 29 and 30 ). The
model does however capture the size and timing of the peak flows for both calibration and
validation period for all streams, with a reasonable base flows. The highest correlation
coefficient was obtained for Långbäcken (0.97 during validation period) and the lowest was
obtained for Åhedbäcken (0.77 during the calibration period). The correlation coefficient
was however increased during the validation period for Åhedbäcken to 0.80 (Fig. 28 and
30).
Krycklan and Åhedbäcken are the two largest streams in the area, with an observed
maximal discharge at 5.1 m3/s and 1.4 m3/s respectively. The model manages to capture
both streams peak and base flows with strong correlation coefficients at 0.80 (Fig 27 and
28). The upstream rivers Långbäcken and Nymyrbäcken also had strong correlation with
the observed data, with correlations coefficients at 0.8 or above (Fig. 29 and 30).
233
234
235
2012-0
7-0
2
2012-0
9-0
2
2012-1
1-0
2
2013-0
1-0
2
2013-0
3-0
2
2013-0
5-0
2
2013-0
7-0
2
2013-0
9-0
2
2013-1
1-0
2
2014-0
1-0
2
2014-0
3-0
2
2014-0
5-0
2
2014-0
7-0
2
2014-0
9-0
2
2014-1
1-0
2
m a
.s.l.
Well 105
105 Observed GW-level Modeled GW-level 105
38
Fig. 27 - Modeled and
observed discharge
measurements at stream
Krycklan, including run up
period from 2012-06-30 to
2012-12-31, calibration
period from 2013-01-01 to
2013-12-31 and validation
period from 2014-01-01 to
2014-12-31
Calibration (2013) Validation (2014)
Unit m3/s
RMSE 0.50 0.32
ME 0.15 0.19
MAE 0.25 0.22
R 0.80 0.89
Figure 28 - Modeled and
observed discharge
measurements at stream
Åhedbäcken, including
run up period from 2012-
06-30 to 2012-12-31,
calibration period from
2013-01-01 to 2013-12-
31 and validation period
from 2014-01-01 to 2014-
12-31
Calibration (2013) Validation (2014)
Unit m3/s
RMSE 0.17 0.13
ME 0.06 0.08
MAE 0.09 0.09
R 0.77 0.80
0
2
4
6
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
m3/s
Krycklan
HYPE discharge Krycklan Modeled discharge Krycklan
0
0,4
0,8
1,2
1,6
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
m3/s
Åhedbäcken
HYPE discharge Åhedbäcken Modeled discharge Åhedbäcken
39
Figure 29 - Modeled
and observed
discharge
measurements at
stream Nymyrbäcken,
including run up
period from 2012-06-
30 to 2012-12-31,
calibration period from
2013-01-01 to 2013-
12-31 and validation
period from 20'14-01-
01 to 2014-12-31
Calibration (2013) Validation (2014)
Unit m3/s
RMSE 0.06 0.06
ME 0.02 0.04
MAE 0.03 0.04
R 0.91 0.88
Figure 30 - Modeled and
observed discharge
measurements at stream
Långbäcken, including
run up period from 2012-
06-30 to 2012-12-31,
calibration period from
2013-01-01 to 2013-12-
31 and validation period
from 2014-01-01 to 2014-
12-31
Calibration (2013) Validation (2014)
Unit m3/s
RMSE 0.10 0.08
ME 0.05 0.06
MAE 0.05 0.06
R 0.79 0.97
0
0,2
0,4
0,6
0,8
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
m3/s
Nymyrbäcken
HYPE discharge Nymyrbäcken Modeled discharge Nymyrbäcken
0
0,2
0,4
0,6
0,8
1
2012-0
6-3
0
2012-0
8-3
1
2012-1
0-3
1
2012-1
2-3
1
2013-0
2-2
8
2013-0
4-3
0
2013-0
6-3
0
2013-0
8-3
1
2013-1
0-3
1
2013-1
2-3
1
2014-0
2-2
8
2014-0
4-3
0
2014-0
6-3
0
2014-0
8-3
1
2014-1
0-3
1
2014-1
2-3
1
m3/s
Långäcken
HYPE discharge Långbäcken Modeled discharge Långbäcken
40
6. D ISCUSSION
The manually calibrated model was able to capture the main shape of the modelled
(HYPE) and observed calibration data. The major fluctuation of the groundwater was also
captured by the model. Even though the other hydrographs had less priority than Site 7,
the calibration still gave a rather well fitted hydrograph compared to HYPE measurements
with high correlations coefficients. However, there are still improvements and
uncertainties within the MIKE-SHE model that can be further analyzed and improved.
6.1 Model grid size
To get a better representation of the topography, the modelled grid size should be
reduced. At a grid size of 100 m times 100 m, there are some problems at the steepest
valleys of the area. The slopes get too blocky and create isolated cells. During rain events,
these cells fill up with water, creating pools of water where there should be none. The
simulation time step could also be reduced to provide a more stable model. However, a
smaller grid and time step will greatly increase the simulation time and would slow down
the calibration procedure. To avoid this issue a smaller area could be chosen for more in
depth simulation, e.g. the sub-catchment site 7. Decreasing the model domain would also
allow a smaller grid size which should improve the representation of the topography and
the interaction between MIKE-SHE and MIKE 11 through overbanking.
It is recommended by DHI forum that the grid is not larger than the rivers themselves
to get a well-functioning exchange between the MIKE-SHE and MIKE 11 model. This is to
make sure that the river bed level in MIKE 11 is at the same level as the topography in the
MIKE-SHE model. With a 100 m grid size, the bed level is not completely well represented
and there are differences between bed level and topography more or less in the model,
which can cause errors. However, the reduction of the grid size from 200 to 100 m was still
enough to be able to simulate the summer peak flows for the uphill rivers. Most noticeable
were the increase in drain to river, without the base flow increasing.
6.2 Unsaturated zone
During the calibration it was noticed that the upstream rivers weren’t given enough
water to create peak flows during this time period. The water was infiltrated before it could
reach the rivers. There are three major parts in the model that can reduce the infiltration
rate in the model; the vertical hydraulic conductivities (especially in the unsaturated zone),
the Manning M for overland flow and the detention storage. During the model calibration
it was discovered that the Manning M and the detention storage parameters had no, to very
little impact on the upper streams in the model. By trying to firstly reduce the model grid
from 200 m to 100 m, the issue was however improved.
To further improve the model, the upper part of the till in the unsaturated zone had to
be given a lower hydraulic conductivity. Since the model was improved by the model grid
size, it could be that it’s rather the topography that is not well represented by the grid and
that the low hydraulic conductivity of the upper part of the till only was needed to
compensate for that. A smaller grid size might resolve the issue by itself but would have
greatly increased the model time and could therefore not be implemented in this thesis
work due to time limit. To avoid increasing the model time, while still testing out a smaller
grid size, the model domain could be decreased in future work.
41
6.3 Snow melt
The snow created in the model is what generated the large flows during April and May.
The shape of the hydrograph during this time period is heavily depended on evaporation,
temperature, melting temperature and the melting coefficient. Of these parameters it was
only the melting temperature and the melting coefficient that could be calibrated, since the
other two were based on real measured data. The melting temperature was set to zero as
recommended by DHI and the melting coefficient was calibrated to 2 mm/C/day.
According to DHI, the melting coefficient is normally between 2 and 4 mm/C/day. A larger
melting coefficient will increase the speed of snowmelt, resulting to a higher and earlier
snow melt. A lower coefficient will slow down the melting process resulting in a flatter
snowmelt curve with a peak later on the year. Looking at the result of the model compared
to the observed discharges levels at site 7, it can be concluded that the snow melt constant
might be needed to be reduced even further than the recommended values given by DHI
and could be further looked into in the future.
6.4 Calibration Data
To improve the model, more calibration data can be used. Especially the modeled
discharge values made taken from HYPE could be replaced with real observed
measurements to get more secure flow estimation in the area. Since this type of
measurements was lacking, the HYPE measurement was used to at least get an estimation
of the flow in the other parts of the model domain. This is however a large insecurity with
the model since it is now partly calibrated against already modeled data. However, since
the HYPE model data and the observed discharge rates in Site 7 had very similar shapes
with peaks occurring during the same time periods, the HYPE measurements were still
considered to give a good estimation of the flow in the area.
The water level used as the boundary condition in MIKE 11 is also based on HYPE
modeled measurements which is insecurity in the model. To improve the model, the water
level in the Krycklan outlet should be modeled against observed measurements.
6.5 Calibration and Validation results
The timing of the peaks and the base flow is well represented by the model. However,
some peaks are smaller and some peaks are larger than compared to the calibration data
used in the model. The peaks during April and May are mainly based on the snowmelt
parameters (see section 5.3) while the other peaks and the base flow were heavy affected by
the hydraulic conductivities and unsaturated zone composition as well as the topography
representation. During calibration it was noticed that the base flow for the rivers
Åhedbäcken and Krycklan was mainly affected by the saturated conductivity in the glacial
material, while the upstream rivers were heavily influenced by the horizontal hydraulic
conductivity of the till.
The peak flows were mainly affected by the hydraulic conductivity of the unsaturated
zone, as discussed in section 6.2, as well as the representation of the topography. The
vertical hydraulic conductivity of the unsaturated zone seemed to manly affect the amount
of overland flow in the area, while the representation of the topography both had an impact
on the overland flow, but also the drainage to the rivers. Especially the upstream rivers
were affected by the representation of the topography. In the model, water is drained from
one cell to the other based on the topography, when the drain level is met. At a too large
42
grid size, it can be that the topography is not well enough represented which results in a
lower amount of drain and overland flow, especially for the upstream rivers which are
located were the topography has the largest inclinations in elevation in the catchment.
The calibrated values could be improved in the future; especially the composition, depth
and width of the glacial deposits in the area can be further looked in to. At a calibrated
hydraulic conductivity of 1e-5 m/s the glacial deposits mainly consists of coarse sand in the
model. If it would be concluded that the material mainly consists of a more gravelly
material this value may indicate that either the depth or the width of the material has been
overestimated in model. If it however would be concluded that the material would consist
of finer sand, the depth and width of material have probably been underestimated.
7. CONCLUSIONS AND FINAL THOUGHTS
The final model created is able to capture the discharge-hydrograph and groundwater
fluctuations with small error and high correlation coefficients compared to observed data
and model data from SMHI. However, even though the model today can represent the
channel flow and groundwater fluctuations in the catchment, some improvements should
be considered.
The main improvement of the model is to decrease the grid size to get a better
representation of the topography as well as the interactions between MIKE 11 and MIKE-
SHE. A reduced grid-size can resolve the differences between bed level and topography
elevation level in the MIKE-SHE and MIKE 11 model, since there can be an issue with the
size of the rivers. In Krycklan, the rivers are approximately about a half to one meter wide,
compared to MIKE-SHE:s grid size of 100 m. The size difference can cause errors between
the connections between overland flow and overbanking. Larger rivers might be able to
have a better connection between the MIKE-SHE model and the MIKE 11 model, resulting
in that larger grid sizes could be used, even at areas with steep hills. This is something that
however needs further evaluation.
Decreasing the grid size to get a better representation of the topography could also
affect the flow to the rivers in such an extent that a finer till on top of the courser till uphill
no longer is necessary to produce the peak flows uphill. To not greatly increase the model
time however, the model domain might be needed to be reduced to e.g. the sub-catchment
at Site 7, which is the sub-catchment with the most real time observed data. There can also
be issues regarding instability of the model whit to small cell-sizes.
Due to the relatively large impact the grid size had on the models ability to simulate
peak flows for the uphill rivers, it might not be recommended to use the MIKE-SHE
program for large catchments with steep hills and very small rivers. Especially if short
calibration times are desired the necessary grid size might become an issue. On flatter
areas, as in (Bosson, et al., 2010), a larger grid size seems to work a lot better, even for
large catchments. However, if the whole domain size is required some of the model
calibration data from SMHI is recommended to be replaced with real time measurements.
This would reduce some of the models insecurities since it is now partly calibrated against
already modeled data. Other improvements that can be considered in the future are also
that the composition of the glacial sediments in the area can be further studied.
The model could either be used in its current state or by incorporating some of the
suggested improvements discussed above for investigation of e.g. climate and transport
related questions. Although there are things to be considered before the model is used in
future work it is still a great first step in the characterization of the flow in the model area,
43
and both the new knowledge about model itself and the new information regarding the
catchment, can be of a great importance in upcoming work.
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berggrund-1-miljon-
sv.html?zoom=714900.721613,7120360.293097,751624.868449,7146157.154166
©Sveriges geologiska undersökning., & ©Lantmäteriet. (2016c, 04 18).
Grundvattenmagasin. [image online]. Retrieved 04 18, 2016, from
45
http://apps.sgu.se/kartvisare/kartvisare-grundvattenmagasin-
sv.html?zoom=714900.721613,7120360.293097,751624.868449,7146157.154166
©Sveriges geologiska undersökning; ©Lantmäteriet. (2016a, 04 18). Jordarter 1:25 000–
1:100 000. [image online]. Retrieved 04 18, 2016, from
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sv.html?zoom=714900.721613,7120360.293097,751624.868449,7146157.154166
Laudon, H. (2013). A field guide to the Krycklan Catchment Study. Retrieved 02 20, 2016,
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management/research/krycklan-catchment-study-new/history/
I
APPENDIX A – EVALUATION OF TEST A TO F
This section includes a general evaluation of the tests A-F. The evaluation also includes a
description of the unsaturated soil profile till.
Evaluation of the unsaturated zone setup of the till with focus on groundwater fluctuation as well as discharge
peak flows.
Te
st
A
Te
st
B
Te
st
C
Te
st
D
Te
st
E
Te
st
F
De
sc
rip
tio
n
De
pth
m.
H. C
on
.
De
pth
m.
H. C
on
.
De
pth
m.
H. C
on
.
De
pth
m.
H. C
on
.
De
pth
m.
H. C
on
.
De
pth
m.
H. C
on
.
Up
str
ea
m
un
sa
tura
ted
zo
ne
To
be
dro
ck
1e-6
To
be
dro
ck
1e-7
To
be
dro
ck
1e-8
0.5
1e-7
0.2
1e-7
0.1
1e-7
To
be
dro
ck
1e-6
To
be
dro
ck
1e-6
To
be
dro
ck
1e-6
Do
wn
str
eam
un
satu
rate
d
zo
ne
To b
edro
ck
1e-6
To b
edro
ck
1e-7
To b
edro
ck
1e-8
To b
edro
ck
1e-6
To b
edro
ck
1e-6
To b
edro
ck
1e-6
Gri
d
siz
e
(m)
200
200
200
200
200
200
Eff
ect
des
cri
pti
on
Gro
un
dw
ate
r
Flu
ctu
ati
on
s
Good
Very
Sm
all
Good
Good
Good
Good
Sp
rin
g f
loo
d
up
str
eam
Larg
e
Good
Reduced
Reduced
Slig
htly
Reduced
Good s
pring
flood
Peak f
low
s
su
mm
er
up
str
eam
No p
eak f
low
s
Very
sm
all
pe
ak
flow
s
Very
sm
all
pe
ak
flow
s
Very
sm
all
pe
ak
flow
s
Very
sm
all
pe
ak
flow
s
No p
eak f
low
s
Peak f
low
s a
nd
sp
rin
g
flo
od
do
wn
str
eam
Good p
eak flo
ws a
ll year
Good
peak f
low
s a
nd
reduced s
pring f
lood
Larg
e p
eak flo
ws a
nd
reduced s
pring f
lood
Good p
eak flo
ws a
ll year
Good p
eak flo
ws a
ll year
Good p
eak flo
ws a
ll year
II
APPENDIX B – WATER BALANCE CHARTS
The water balance evaluations made in the calibration procedure (section 4.2) include
the water balance for test A, B, E, K, J and G. These are calculated for year 2013 in mm as
accumulated flow.
Water balance for test A. The grid size is 200*200m.
Water balance for test B. The grid size is 200*200m and the till soil profile consists completely of a fine till
III
Water balance for test E. A
fine till is placed on top of the
till uphill site 7. The grid size
is 200*200m
Water balance for test K
and G. A very fine till is
placed on top of the till
uphill site 7. The grid size is
200*200m
IV
Water balance for test J. A
very fine till is placed on top
of the till uphill site 7. The
grid size is 100*100m
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