THE IMPACT OF ROADS ON HYDROLOGICAL RESPONSES: A CASE STUDY IN
SWEDEN
Alireza Nickman 1, Per-Erik Jansson 1, Steve W. Lyon 2,
Bo Olofsson 1, Zahra Kalantari 1
1
Department of Sustainable Development, Environmental Science
and Engineering
Royal Institute of Technology (KTH)
SE-100 44 STOCKHOLM, Sweden
2
Department of Physical Geography and Quaternary Geology,
Stockholm University,
SE-106 91 Stockholm, Sweden
Manuscript
Abstract
A method engaged for simulating and assessing the alterations excreted by
road topography within watersheds and estimating the road effects on
hydrologic responses. The method uses Geographic Information System
(GIS) to allocate and eliminate roads from the elevation data. HEC-HMS was
used to model surface and near surface hydrological responses of watersheds
with roads and without roads in response to three storms with different
intensities. A detailed study of the simulated flow duration curves showed
differences between 20 watersheds for three different storms based on a
digital elevation data with and without roads. To compare flow duration
curves, L-moment ratios were calculated and their variation compared. An
increase in peak flow and reduced delay occurred with increased storm
intensity. Variations of the L-moment ratios were larger in larger watersheds.
However, the impact of the roads was much smaller and only possible to
identify by detailed examination of statistical descriptors. The results are
useful to gain a better estimating of the effect of road topography in
hydrological processes and responses especially in high storm intensities.
Key words: Road topography; HEC-HMS; Flow Duration Curves;
L-moment ratios.
Nickman et al
Manuscript
1. I NTRODUCTION
Any alteration in the physical characteristics of a watershed,
especially manmade changes, will influence the natural flow of
water (Bergmann et al, 1990). Among typical manmade
disturbances to the environment, the development of road
networks are among the most common geomorphological
alterations in watersheds and natural river sections (Jones et al
2000, Wemple et al 2001, Ziegler et al 2007). Roads and their
margins affect routing of flow paths, infiltration rates, surface
permeability, near surface flows, and the production of finegrained sediments associated with roads by changing hydrologic
and geomorphologic characteristics of the watershed (Wemple et
al, 2001; Tague and Band, 2001; Ziegler et al, 2004; Dutton et al,
2005; Cuo et al, 2006; Ziegler et al, 2007). Modified sections of
river networks at road-stream crossings are the most vulnerable
spots to road damage and loss due to high level of water or
torrents of debris flow (Erickson, 2004; de Moel et al, 2009;
Magnusson et al, 2009).
The hydrological effects of a road in a catchment can change peak
flow magnitude and timing (King and Tennyson, 1984; Wemple et
al, 1996; Jones and Grant, 1996: Bruno and Bardossy, 1998; Jones
et al, 2000; Iroumé et al, 2005). Road networks and their related
structures influence hydrologic responses by alteration of
connectivity within fluvial systems and shortening of stream flows
especially during extreme events when surface flow processes
dominate the hydrological response (Ziegler et al, 2004; Borga et
al, 2005; Cuo et al, 2006; Ziegler et al, 2007; Blanton and Marcus,
2009). The effect of surface runoff concentration by roads and
subsurface interception by ditches increases the effective drainage
density and shortens the fluvial routes on hillslopes thereby
increasing peak flow of the main stream (Luce and Wemple, 2001).
The magnitudes of those influences typically depend on the
configuration of the road-stream network in the catchment, the
type of embankment construction (i.e., cut or fill), and the road
location (Ziegler et al, 2007; Blanton and Marcus, 2009). Alteration
of peak flows and timing may result in quick flows larger than
those anticipated prior to road construction, which is important in
view of flood prediction.
There have been several approaches to investigate the effects of
road types on hydrology, slope stability, erosion and ecosystems
across scales. Wemple et al. (1996) studied the timing influence of
road networks by investigating the interaction between road
routing effect and drainage networks at a full basin scale. Ziegler et
al (1996) examined variations in soil physical properties near and
above abandoned logging road surfaces and surroundings to
investigate the effect of roads in producing excess runoff in a
watershed in Northern Thailand. At the landscape scale, the
influence of road network configuration on biological and
ecological processes (Jones et al, 2000) was studied by
implementation of conceptual models based on observations from
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The impact of roads on hydrological responses: A case study in Sweden
H.J. Andrews Watershed, Oregon (USA). Macdonald et al. (2001)
measured sediment yield and runoff generated from unpaved
roads in the steep and highly dissected landscape of St John Island.
Some methods include hydrological modeling of the effect of road
cut depths and drainage patterns on hillslope soil moisture and
runoff generation (Tague and Band, 2001). In addition, Dutton et
al. (2004) looked at near surface permeability variation caused by
surface compaction of forest roads at the basin scale in Oregon,
USA. Spatial comparison and scenario analysis of road networks
have been carried out to investigate the influence of roads on
neighboring landscapes and ecosystems in China (Liu et al, 2008).
Assessments of geographical distribution of road networks and
their potential impact on stream networks in the continental
United States was done by Blanton and Marcus (2009).
Hydrological evaluation of the contributing area upstream of road
networks especially at road-stream crossings can lead to better
understanding of road effects on hydrological responses of
watersheds in extreme storm events. There are several studies that
have used different approaches and models to identify and address
the various impacts of different road types on hydrologic response
of watersheds. Jones (2000) studied magnitude, seasonality and
duration of peak discharge responses to roads in 10 pairs of
experimental watershed utilizing a physically-based model of water
balance components and hydrologic mechanisms. The Distributed
Hydrologic Soil Vegetation Model (DHSVM) was used by La
Marche and Lettenmaier (2000) to study the effect of forest roads
on peak flow in logged catchments of Deschutes River,
Washington, USA. Loague and VanderKwaak (2002) simulated
hydrological response of a small experimental watershed to
investigate the impact of roads by comparing two near surface
hydrological response models. They used a single rainfall-runoff
event to compare results from two models: the quasi-physically
based rainfall-runoff model (QPBRRM) of Horton overland flow
and the integrated hydrology model (InHM). DHSVM was applied
by Cuo et al. (2006) to investigate impact of roads on the water
balance of a mountainous, 94 ha experimental watershed in
northern Thailand.
The main objective of this study is to investigate the impact of
road topography on a forested catchments hydrologic response to
storm events using an efficient hydrological model. In this current
study, HEC-HMS was chosen to model storm runoff generated
from watersheds. HEC-HMS (Hydrologic Engineering CenterUSACE) is quasi-distributed precipitation-runoff modeling
software that has a dendritic arrangement of hydrologic elements
(Davis, 1993). The HEC-HMS model is widely used in numerous
hydrological studies and supplies explicit and applicable results in
flood related studies in a wide range of geographic areas
(Hellweger and Maidment, 1999; Ahrens and Maidment, 1999;
Anderson et al., 2002; Cantone and Schmidt, 2009). Although
HEC-HMS has not been previously used for studying the effects
of roads, it has been widely used to assess the impact of
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Nickman et al
Manuscript
morphological changes in various hydrology studies (Yusop et al.,
2007; Beighley and He, 2009). HEC-HMS can describe the process
of conversion of excess rainfall to overland flow and channel
runoff (USACE, 2000b; Knebl et al., 2005). In this study, time to
peak and peak discharge are important parameters that can be
computed adequately in HEC-HMS. We, thus, expect to simulate
storm hydrographs from different watersheds in response to
several storms implemented in the model environment. The results
might be useful for evaluation of possible effect of climate changes
in planning and design of the sustainable road structures.
1.1. Study area and data
The study area is located in the western part of Sweden north of
Karlstad City. This area covers nearly 390 km2 of the region
between Hagfors and Munkfors municipalities in the county of
Värmland in Western Sweden (Fig. 1). The width of the study area
is 15 km and the length is 26 km. The area was chosen because
severe damages to roads due to extreme floods have been
frequently reported in the region.
Elevation in the area, which has typical boreal forest
characteristics, ranges from 62 m to 475 m above sea level and the
slopes range from 0% to 80%. The dominant land cover in this
region is mixed coniferous forests. Other major land covers in the
area include grassland and agricultural land. The main soil types in
the area are glacial till, glacial river sediment, sand and rock
outcrops. The region has a moderate to cold climate with average
maximum temperature of 15 oC in July and an average minimum
temperature of -5 oC in February. According to the Swedish
Meteorological and Hydrological Institute (SMHI) the mean
annual precipitation in the region for the period (1960-2011) is 798
mm of which the highest and lowest average monthly precipitation
occurred in August (80 mm) and February (30 mm), respectively.
The elevation data used in this study have 2 m resolution from
National Land Survey of Sweden (Lantmäteriet) which efficiently
depicts the road topography. The soil data and land cover map
have resolutions of 25 m and were acquired from Geological
Survey of Sweden (SGU) and Lantmateriet, respectively. The
precipitation data used in this case study were from an August
2004 storm rainfall recorded at the Råda and Sunnemo SMHI
stations in the region (Fig.1). This extreme event caused flash
floods and torrents of debris flow that resulted in sever damages to
infrastructures (Erickson, 2004; Magnusson et al, 2009). The storm
washed away roads and caused failure of embankments, drums,
and culverts in some of the watersheds in the study area (Erickson,
2004; Magnusson et al, 2009). Based on the recorded storm on
August 2004 two other storms were designed with half and double
intensity (with the same volume of rainfall) to assess hydrologic
response of watersheds to different storm rainfalls (Fig.2). It is
expected that increasing in storm size will increase the effect of
road structures on peak flows realized (Cuo et al, 2006).
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The impact of roads on hydrological responses: A case study in Sweden
1.2. Aims and objectives
The main objective is to investigate the role of roads on
hydrological response of watersheds. The study intended to fulfill
the main objective in two sections:
1. Investigating the interaction between PCDs and road
network in a watershed and study the distribution of flood
risk along roads. Study will be relevant to evaluate road
network susceptibility to flooding.
2. Simulate the impact of road topography on hydrological
response in watersheds using a hydrological modeling
system (HEC-HMS).
The main intention in the study was to identify the important
driving factors, which affect hydrological responses. In the second
section, the objective was to simulate the impact of how the roads
affect the topography and by that the hydrological response to
extreme storm events in watersheds with no measured stream
flows.
2. M ETHODS
The method for this case study consists of several steps: 1) define
watersheds in the study area (20 watersheds) with similar
characteristics; 2) synthetically remove the road network from the
elevation models; 3) hydrological modeling of watersheds both
with road and without roads by HEC-HMS applying three storms
4) Flow duration curve and statistical approach to investigate road
impact on hydrologic responses of the watersheds.
2.1. Delineating watersheds in the study area and removing road
from DEM
Road Twenty watersheds with approximately similar physical
characteristics were delineated and selected in the study area. In all
the watersheds, a main road passes through the watershed area and
the outlet is close to the road-stream junction where the main road
crosses the main stream. For this purpose, ArcHydro - an
extension available within ArcGIS (ESRI) - was used to delineate
and define the contributing area upstream of each main roadstream cross section. Roads were classified based on their
operational type and their width into two classes: main roads and
other roads. The reason for this was to distinguish between the
main roads that could have possibly more effective topography
and tributary roads and streets with less or no significant
topography.
Thus to simulate and compare hydrologic responses of watersheds
with roads and without roads, all the roads were removed from the
delineated watersheds. For this purpose the width of different
classes of the roads and their embankments were extracted from
available elevation data. A buffer of 5 m from the edge of
embankments was considered as the boundary of road
topography. Then roads topography was removed from the DEM
and missing values were interpolated.
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Nickman et al
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Fig. 2. Map of the study area in Värmland County in W Sweden. Studied
watersheds and the mian roads are illustrated in the map.
Fig. 3. Three storms with different intensities implemented in HEC-HMS
model. The bold line is the original storm recorded on 4 August 2004.
6
The impact of roads on hydrological responses: A case study in Sweden
Elevation maps of the area were regenerated from these essentially
new DEMs. Exclusion of roads from the elevation resulted in
changes in boundaries of some watersheds where the roads’
topography had formed watershed divides. Therefore, new
watersheds were delineated considering the upstream contributing
areas of the same outlets used for the watershed delineation. Some
physical descriptors of the watersheds such as watershed area,
main flow path, basin length, basin slope drainage density and road
density were extracted before and after DEM manipulation (Table
1). Drainage density (the ratio of total length of the streams to the
area of a watershed) calculated both for watersheds with roads and
without roads.
2.2. Hydrologic simulation of the Watershedslood
HEC-HMS (Davis, 1993) was used to model hydrological
responses of the watersheds to the three storm events. In building
the hydrological model for a given storm event in HEC-HMS the
following data must be provided: A Hyetograph (rainfall data),
Loss model parameters and Transform model parameters
(USACE, 2000b). The hyetographs used in the modeling were the
three storms (Fig.2) that assumed to be uniformly distributed over
the test watersheds. This assumption conforms to the basic
supposition of uniformly and spatially distributed rainfall in all the
methods that are used in HEC-HMS (USACE, 2000b).
Table 1- Some physical catchment descriptors of the study watersheds.
Watershed
WS Area
WS Area Averag DDensity
DDensity Total Road Main Road
With
Without
e Basin WS With
WS Without Density
Density
roads(km2) roads(km2) Slope roads(m/ha) roads(m/ha)
(m/ha)
(m/ha)
WS 01
1.00
1.29
8.4
36.8
39.8
0.0950
0.0440
WS 02
1.60
2.09
9.9
36.7
35.7
0.2729
0.0531
WS 03
1.70
1.40
9.6
35.6
32.7
0.2932
0.0212
WS 04
2.10
2.30
10.5
34.5
27.3
0.2268
0.0544
WS 05
2.20
2.15
8.1
40.5
32.5
0.1464
0.0872
WS 06
2.60
2.42
9.4
36.2
33.9
0.1083
0.0156
WS 07
2.60
2.90
7.3
37.2
34.7
0.0954
0.0074
WS 08
2.70
2.55
10.5
30.3
26.2
0.0301
0.0137
WS 09
3.00
2.91
6.9
45.5
39.1
0.0686
0.0230
WS 10
3.60
3.50
7.7
37.7
33.5
0.1084
0.0223
WS 11
3.70
3.95
7.7
37.5
35.1
0.0616
0.0185
WS 12
4.30
4.46
7.1
33.9
26.1
0.0709
0.0207
WS 13
4.70
5.10
5.7
34.1
30.3
0.2533
0.0310
WS 14
5.00
4.24
9.6
37.0
36.7
0.0670
0.0219
WS 15
5.10
5.24
9.5
34.3
30.8
0.1437
0.0190
WS 16
5.40
5.13
10.0
33.5
31.7
0.1331
0.0092
WS 17
6.90
7.15
9.9
36.5
37.6
0.1330
0.0195
WS 18
8.70
8.68
8.4
39.6
38.8
0.0950
0.0298
WS 19
8.70
7.77
9.9
35.6
33.1
0.2729
0.0213
WS 20
9.10
8.88
9.6
32.6
30.9
0.2932
0.0019
7
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Among the models available to simulate the different processes
involving in the primary structure of runoff modeling in HECHMS the methods of computing runoff volume, direct runoff, and
channel flow were used. HEC-HMS computes runoff volume by
computing losses such as interception, infiltration, surface storage
and evapotranspiration and subtracting them from the
precipitation (USACE, 2000b). Infiltration is due to penetration of
water through soil surface to deeper layers. Evaporation and
transpiration from leaves and soil surface are another form of
losses which are not considered in this simulation due to relatively
short length of the event (USACE, 2000b). In this study the runoff
volume method used was SCS curve number (USDA NEH-4,
1956, 2004) to take into account the land use properties and soil
characteristics to compute infiltration rate and surface runoff
losses. This method is suitable for event based simulations (Ponce
and Hawkins, 1996; Mishra and Singh, 1999, 2006) and is quasidistributed method to calculate excess runoff considering the
location of each cell and distance to the outlet, taking into account
the cell CN (USACE, 2000b).
The direct runoff model that was used here was SCS Unit
Hydrograph Method (USACE, 2000b). In this model direct runoff
is implicitly the product of near surface flow and overland flow
(USACE, 2000b). Interception and surface storage which are the
result of local depressions in landscape e.g., soil cracks and storage
were taken into account by application of Cn. Muskingum-Cunge
(standard section) method for river routing calculations was used
in this study (USACE, 2000b). This method is suitable when there
is no observed hydrograph data available for calibration (USACE,
2000b, Takeuchi, 2009) and uses the continuity equation and the
diffusion form of the momentum equation (Miller and Cunge,
1975; Kousis, 1978; Ponce, 1978). Because base flow data was not
available, simulations were repeated considering no losses due to
infiltration to resemble a fully saturated condition of the
watersheds.
2.3. Satistical approach
Flow duration curves (Foster, 1924, 1934) were used to display the
flow characteristics of streams in each watershed in the range of
the simulated discharges. FDCs are widely used in hydrology that
have applications including but not limited to management of
water resources (Alaouze, 1989), estimating dilution of domestic or
industrial discharge intended for a river (Male and Hogawa, 1984),
evaluation of available water for hydropower (Warnick, 1994),
study low flow regimes in un-gauged basins (Hughes and
Smakhtin, 1996), and predict flow regimes in un-gauged sites by
regionalizing methods (Hughes and Smakhtin, 1996). FDCs were
constructed based on the complete period of the simulated
discharge and normalized by dividing by the area of the
watersheds.
L-moment ratio estimators, termed L-skewness τ3, and L-kurtosis τ4
were used to explain the distribution of the FDCs. L-moments
8
The impact of roads on hydrological responses: A case study in Sweden
ratio diagrams have many applications in analyzing stream flow
data especially in the study of ungauged basins (Asquith, 2002;
Castellarin et al., 2004; Archfield et al., 2007; Castellarin et al.,
2007; Booker and Snelder, 2012) and results are more reliable in
comparison to conventional product moments (Vogel and
Fennessey, 1993). L-moments are analogous to ordinary moments
and can be used for parameter estimation and hypothesis testing
(Vogel and Fennessey, 1993). Sample estimators of L-moments are
always linear and are nearly unbiased for small samples (Vogel and
Fennessey, 1993). The latter is counter to product moment ratio
estimators that have been widely used in hydrological applications
and render substantial bias for small (n≤100) samples (Vogel and
Fennessey, 1993) and are distribution dependent (Wallis et al.,
1974). L-moments are linear functions of probability weighted
moments (PWMs) in which PWMs can be described using:
∑
(
[(
)
)
]
( )
(1)
Where ( ) represents the ordered stream flow in which ( ) is
the smallest observation and ( ) is the largest and r is the order
of moments. The first four L-moments for any distribution can be
computed from the PWMs using:
(2)
(3)
(4)
(5)
Hosking (1990) defines the L-moment ratios
analogous to the
product moment ratios, for r=1,..,4 as the first four L-moments
being:
(6)
(7)
(8)
3. R ESULTS
Drainage density for the watersheds before and after the DEM
manipulation was calculated and their measure of variations
plotted using box and whisker plots and illustrated in Fig. 3.
Hydrographs resulted from the hydrological modeling of the
watersheds normalized according to the watershed areas.
Normalized hydrographs used to construct flow duration curves.
L-moment ratios as the shape indicators for analyzing the FDCs
calculated and illustrated in Fig. 4 showing L-Skewness of FDCs
and Fig.5 showing L-Kurtosis of the FDCs. L-moment ratios
showed that the range of L-skewness and L-kurtosis increased
both for watersheds with roads and without roads. More variations
in the shape of FDCs were obtained as a result of an increase in
area and storm intensity. This might explain the intensity of the
9
Nickman et al
Manuscript
storm as the main driving factor in magnifying the effect of road
topography in alteration of hydrologic responses. Less variation
can be seen in the L-moment ratio diagram for the FDCs
considering no losses due to infiltration. Each box in the plots
demonstrates interquartile range in which lower and upper sides
represent lower quartile and upper quartile respectively. The
whiskers represent 25 % of the data in which the uppermost and
lowest edges are largest and smallest values that are not outliers.
The line in middle of the boxes represents the median (center of
tendency). The outliers are the values greater than 1.5 interquartile
ranges away from upper and lower quartile.
4. D ISCUSSION
Box plots illustrated in Fig.3 describes the variation in the total
length of the streams in the watersheds before and after removal
of the roads from topography. Investigation of the variations in
drainage density of the watersheds demonstrates a decrease in the
stream lengths after removing roads from topography. This result
was expected regarding the positioning of the roads on a hill slope
(Luce and Wemple, 2001). Because the road networks are
commonly developed perpendicular to the streams, natural streams
are interrupted by the road embankments. The magnitude of those
alterations depends on the type of embankment construction that
directly influences the effective drainage density especially during
extreme events (Ziegler et al, 2004; Borga et al, 2005; Cuo et al,
2006).
Flow duration curves show the differences in hydrologic responses
due to existence of road network in the watersheds. The FDCs
demonstrated different possible responses to the new topographic
patterns as was created by the roads in the model. The effects were
both with respect to the timing of the peak flow, the rate of the
peak flow and to the total amount of outflows. It was interesting
Figure 3 Plot showing the measure of variation in darinage
density for watersheds with roads and after removal of road
topography from the watersheds.
10
The impact of roads on hydrological responses: A case study in Sweden
to note that from FDCs that the effect of road topography was
not only as an increase in the peak flow rate or in the timing of to
the peak. The differences in the impact are unique to each of the
watersheds because of the specific physical characteristics and
configuration of the road networks. Thus understanding the
hydrological role of road networks in each watershed needs to be
investigated according to physical properties of that watershed.
Investigating the box plots of the L-moment ratios showed an
increase in the variation ranges as storm intensity increases. This
might indicate the intensity of the storm as the main driving factor
in magnifying the effect of road topography in alteration of the
hydrologic response. Comparing the box plots for L-moments
ratios shows the fact that median and quartile range of L-moments
is higher in watersheds with roads regardless of differences in
storm intensities. This may explain the magnifying effect of roads
on hydrological response to storms by increasing the peak outflow.
The positive increase in the median, upper quartile and maximum
of the L-skewness can explain the role of roads in advancing in
time to peak of the watershed outflows.
Less variation can be seen in the L-moment ratio results for the
FDCs considering no losses due to infiltration. The upper quartile
ranges of L-skewness and L-kurtosis have fairly similar values for
both watersheds with roads and without the roads. Considering no
losses due to infiltration may not assist studying the effect of road
topography on outflow characteristics. Simulations without losses
due to infiltration are less realistic for real world conditions.
However it can help to predict maximum outflow from the
ungauged watersheds which is not the case in this study.
5. C ONCLUSION
The role of road topography on hydrological response of boreal
watersheds was simulated in this study. Road network change the
hydrological response of watersheds due to alteration in
topography and geology of landscapes. The impact of road
network on changing the hydrological response is magnified with
increase in storm intensity. Due to different road-stream
configurations, location on landscapes and various types of roads,
responses were different. Both increase and decrease in peak
outflow and shift forward and backward of the time to peak were
observed. The impact of removing the topographic features as
created by the roads was generally small and is may be smaller than
what we can observe in real world conditions. This may be because
the model did not consider additional coupled soil and vegetation
properties. Change of hydraulic properties and influence on the
subsurface hydrology on the flow patterns was not considered in
the model which limits it implication for general conclusions. On
the other hand the specific role of changing the surface
topography has a specific interest and for that the results are
considered to be of high interest.
11
Nickman et al
Manuscript
Figure 4 Box plots showing variations in the L-Skewness
with losses and without losses (1.1) and (1.2) and the LKurtosis with losses and without losses (2.1) and (2.2)
respectively. Watersheds without roads are represented
in whit boxes and with roads in white boxes.
12
The impact of roads on hydrological responses: A case study in Sweden
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