water
Commentary
Development of an Ice Jam Flood Forecasting System
for the Lower Oder River—Requirements for
Real-Time Predictions of Water, Ice and
Sediment Transport
Karl-Erich Lindenschmidt 1, * , Dirk Carstensen 2, Wolfgang Fröhlich 3, Bernd Hentschel 4,
Stefan Iwicki 5, Michael Kögel 2, Michał Kubicki 6, Zbigniew W. Kundzewicz 7,
Cornelia Lauschke 8, Adam Łazarów5, Helena Ło´s 9, Włodzimierz Marszelewski 10,
Tomasz Niedzielski 11, Marcin Nowak 10 , Bogusław Pawłowski 10, Michael Roers 3,
Stefan Schlaffer 12 and Beata Weintrit 6
1
Global Institute for Water Security, University of Saskatchewan, Saskatoon, Saskatchewan, S7N 3H5, Canada
2
Institut für Wasserbau und Wasserwirtschaft, Technische Hochschule Nürnberg, 90489 Nürnberg, Germany;
dirk.carstensen@th-nuernberg.de (D.C.); michael.koegel@th-nuernberg.de (M.K.)
3Landesamt für Umwelt Brandenburg, 15236 Frankfurt/Oder, Germany;
Wolfgang.Froehlich@LfU.Brandenburg.de (W.F.); Michael.Roers@LfU.Brandenburg.de (M.R.)
4Federal Waterways Engineering and Research Institute (BAW), 76187 Karlsruhe, Germany;
bernd.hentschel@baw.de
5Department of Inland Waterways, Regional Water Management Authority, 70-001 Szczecin, Poland;
stefan.iwicki@szczecin.rzgw.gov.pl (S.I.); adam.lazarow@rzgw.szczecin.pl (A.Ł.)
6Astri Polska Sp. z o.o., 02-256 Warsaw, Poland; michal.kubicki@astripolska.pl (M.K.);
beata.weintrit@astripolska.pl (B.W.)
7Institute for Agricultural and Forest Environment, Polish Academy of Sciences, 60-809 Pozna´n, Poland;
kundzewicz@yahoo.com
8Wasser-und Schifffahrtsverwaltung, 16225 Eberswalde, Germany; Cornelia.Lauschke@wsv.bund.de
9Institute of Agrophysics, Polish Academy of Sciences, 20-280 Lublin, Poland; hlos@ipan.lublin.pl
10 Department of Hydrology and Water Management, Nicolaus Copernicus University in Toru ´n,
87-100 Toru ´n, Poland; marszel@umk.pl (W.M.); mnowak@umk.pl (M.N.); bogus@umk.pl (B.P.)
11 Department of Geoinformatics and Cartography, University of Wrocław, 50-137 Wrocław, Poland;
tomasz.niedzielski@uwr.edu.pl
12 German Aerospace Centre (DLR), 82234 Weßling, Germany; Stefan.Schlaffer@dlr.de
*Correspondence: karl-erich.lindenschmidt@usask.ca; Tel.: +1-(306)-966-6174
Received: 17 December 2018; Accepted: 29 December 2018; Published: 8 January 2019
Abstract:
Despite ubiquitous warming, the lower Oder River typically freezes over almost every
year. Ice jams may occur during freeze-up and ice cover breakup phases, particularly in the middle
and lower reaches of the river, with weirs and piers. The slush ice and ice blocks may accumulate
to form ice jams, leading to backwater effects and substantial water level rise. The small bottom
slope of the lower Oder and the tidal backflow from the Baltic Sea enhance the formation of ice
jams during cold weather conditions, jeopardizing the dikes. Therefore, development of an ice jam
flood forecasting system for the Oder River is much needed. This commentary presents selected
results from an international workshop that took place in Wrocław (Poland) on
26–27 November 2018
that brought together an international team of experts to explore the requirements and research
opportunities in the field of ice jam flood forecasting and risk assessment for the Oder River section
along the German–Polish border. The workshop launched a platform for collaboration amongst
Canadian, German and Polish scientists, government officials and water managers to pave a way
forward for joint research focused on achieving the long-term goal of forecasting, assessing and
mitigating ice jam impacts along the lower Oder. German and Polish government agencies are in need
of new tools to forecast ice jams and assess their subsequent consequences and risks to communities
Water 2019,11, 95; doi:10.3390/w11010095 www.mdpi.com/journal/water
Water 2019,11, 95 2 of 20
and ship navigation along a river. Addressing these issues will also help research and ice flood
management in a Canadian context. A research program would aim to develop a modelling system by
addressing fundamental issues that impede the prediction of ice jam events and their consequences
in cold regions.
Keywords:
flood forecasting system; ice breaking; ice jam flooding; river ice monitoring; Oder River;
remote sensing
1. Introduction
Large floods continue to bring death and suffering and immense economic damage throughout
the world. Therefore, it is necessary to reduce the flood risk, understood as a combination of
hazard, exposure and vulnerability, by improving flood risk governance systems. There is a panoply
of structural and non-structural (including flood forecasting) approaches that lend themselves to
applications in order to achieve this effect [
1
]. However, typically, general studies of recent river
flood risk in Europe (using a topography-based flood hazard map together with land-use data and
damage-stage relationship for various land uses, cf. [
2
]) or flood hazard projections for the future that
may strongly disagree between studies (see [3]) do not recognize ice jam floods as a special category.
The Oder River is a large international river in Central Europe flowing from its headwaters in the
Czech Republic, through Poland and along the German–Polish border before draining into the southern
Baltic Sea. Its drainage basin, covering an area of 119,041 km
2
, belongs to three countries: the Czech
Republic, Poland (where 88% of the area of the Oder basin is located) and Germany. The lower Oder
River (see Figure 1) borders along Germany and Poland, a region influenced by continental winds,
and typically freezes over almost every year. Ice jams have occurred during freeze-up and ice cover
breakup along the river, particularly in the middle and lower reaches where the river bottom slope
is small and river structures (weirs and piers) arrest the flow of frazil ice and ice blocks (exemplarily
shown in Figure 2). The slush ice and ice blocks accumulate at these ice bridgings to form ice jams,
which can lead to backwater effects. Water levels can rise up to 1.5 m in a very short time to cause
overbank flooding [
4
]. The small bed slope of the lower reaches of the Oder River and the tidal
backflow from the Baltic Sea promote the formation of ice and ice jam occurrences during cold weather
conditions. Such events make dikes along this part of the river particularly vulnerable to breaches,
a potentially catastrophic outcome of extended flooding throughout the adjacent low-lying area of
the Oderbruch.
An ice jam flood forecasting system is required for the Oder River to help curb ice jam
evolution and mitigate ice jam flooding. At best, an ice cover observation system is currently
in place to track the potential development of ice jams. Such ice jam flood warning systems
require extensive field observations and may have considerable uncertainty [
5
] due to time lags
between observations and reporting. Nonetheless, flood forecasting and risk mapping are urgently
needed by government agencies. Forecasting the occurrence of ice jams is, however, challenging for
several reasons. The processes of ice cover breakup and ice jamming are complex and nonlinear,
and numerous morphological, meteorological and hydrological factors interact during ice jam
formation. Some empirical and process-based attempts have been made by White [
6
,
7
] to develop
forecasting methods, however, these approaches tend to be very site-specific and can only be used
as a first step to determine possible causalities between these factors. Forecasting systems have also
been attempted with neural network and fuzzy logic systems [
8
,
9
], however, the physical processes
underlying the cause–effect relationships of ice jam formation are not considered in such approaches.
Models have been developed to predict backwater levels of ice jamming events, e.g., River2D [
10
] and
HEC-RAS (Hydrologic Engineering Center—River Analysis System) [
11
], but these systems do not
predict the ice jam locations, which must be prescribed in these models to simulate backwater levels.
Water 2019,11, 95 3 of 20
Water 2019, 11, x FOR PEER REVIEW 3 of 20
Figure 1. The lower Oder River flowing along the German–Polish border. The inset provides the
elevations along the Oder’s lower reach with indications of the average slope of the river bed.
On 26–27 November 2018, an international workshop took place in Wrocław, Poland addressing
the topic of “Development of an ice jam flood forecasting system for the Oder River”. All participants
are listed as co-authors of this paper. The workshop is the first step in assembling an international
team of scientists, government officials and water managers to explore a way forward on achieving
the long-term goal of forecasting, assessing and mitigating ice jam impacts along the lower Oder
River. Such a platform can help develop new tools for German and Polish government agencies to
forecast ice jams and assess their subsequent consequences and risks to communities and ship
navigation along the river. The network will also help advance research in river ice processes and ice
flood management with the aim of developing more reliable modelling systems to address
Figure 1.
The lower Oder River flowing along the German–Polish border. The inset provides the
elevations along the Oder’s lower reach with indications of the average slope of the river bed.
On 26–27 November 2018, an international workshop took place in Wrocław, Poland addressing
the topic of “Development of an ice jam flood forecasting system for the Oder River”. All participants
are listed as co-authors of this paper. The workshop is the first step in assembling an international
team of scientists, government officials and water managers to explore a way forward on achieving
the long-term goal of forecasting, assessing and mitigating ice jam impacts along the lower Oder River.
Such a platform can help develop new tools for German and Polish government agencies to forecast
ice jams and assess their subsequent consequences and risks to communities and ship navigation along
Water 2019,11, 95 4 of 20
the river. The network will also help advance research in river ice processes and ice flood management
with the aim of developing more reliable modelling systems to address fundamental issues that impede
the prediction of ice jam events and their consequences in all cold region countries worldwide.
Water 2019, 11, x FOR PEER REVIEW 4 of 20
fundamental issues that impede the prediction of ice jam events and their consequences in all cold
region countries worldwide.
Figure 2. Ice jam on the Oder River at Frankfurt/Oder on 24 February 2012 (photo by Halka Beberstedt;
used with permission).
2. Ice Cover Breakage as an Ice Flood Mitigation Scheme
Currently, ice jamming and ice jam flooding is mitigated by breaking the ice using fleets of ice
breakers from both German and Polish water authorities. Generally, the ice breakers are driven in
the upstream direction so that broken ice can float unhindered downstream into the Szczecin Estuary.
An effective technique in breaking up the ice cover, depicted in Figure 3, is to drive the ice breakers
in circles through the ice around perimeters of large ice sheets that dislodge and break up further as
they float downstream. Operating in parallel through the ice, against the current, as shown in Figure
4, is also quite effective in breaking ice, particularly for thinner ice covers on low sloping waters.
Figure 3. Ice breakers driving in loops to break up large sheets of ice cover (courtesy of Regional Water
Management Authority, Szczecin).
Many ice breakers are equipped with GPS systems for easy location of the vessels and deriving
the extent of ice cover breakage. Information is also acquired through ice observers (personnel that
travel along the shores of the river and make observations of the ice situation and extent). This
Figure 2.
Ice jam on the Oder River at Frankfurt/Oder on 24 February 2012 (photo by Halka Beberstedt;
used with permission).
2. Ice Cover Breakage as an Ice Flood Mitigation Scheme
Currently, ice jamming and ice jam flooding is mitigated by breaking the ice using fleets of ice
breakers from both German and Polish water authorities. Generally, the ice breakers are driven in
the upstream direction so that broken ice can float unhindered downstream into the Szczecin Estuary.
An effective technique in breaking up the ice cover, depicted in Figure 3, is to drive the ice breakers
in circles through the ice around perimeters of large ice sheets that dislodge and break up further as
they float downstream. Operating in parallel through the ice, against the current, as shown in Figure 4,
is also quite effective in breaking ice, particularly for thinner ice covers on low sloping waters.
Water 2019, 11, x FOR PEER REVIEW 4 of 20
fundamental issues that impede the prediction of ice jam events and their consequences in all cold
region countries worldwide.
Figure 2. Ice jam on the Oder River at Frankfurt/Oder on 24 February 2012 (photo by Halka Beberstedt;
used with permission).
2. Ice Cover Breakage as an Ice Flood Mitigation Scheme
Currently, ice jamming and ice jam flooding is mitigated by breaking the ice using fleets of ice
breakers from both German and Polish water authorities. Generally, the ice breakers are driven in
the upstream direction so that broken ice can float unhindered downstream into the Szczecin Estuary.
An effective technique in breaking up the ice cover, depicted in Figure 3, is to drive the ice breakers
in circles through the ice around perimeters of large ice sheets that dislodge and break up further as
they float downstream. Operating in parallel through the ice, against the current, as shown in Figure
4, is also quite effective in breaking ice, particularly for thinner ice covers on low sloping waters.
Figure 3. Ice breakers driving in loops to break up large sheets of ice cover (courtesy of Regional Water
Management Authority, Szczecin).
Many ice breakers are equipped with GPS systems for easy location of the vessels and deriving
the extent of ice cover breakage. Information is also acquired through ice observers (personnel that
travel along the shores of the river and make observations of the ice situation and extent). This
Figure 3.
Ice breakers driving in loops to break up large sheets of ice cover (courtesy of Regional Water
Management Authority, Szczecin).
Water 2019,11, 95 5 of 20
Many ice breakers are equipped with GPS systems for easy location of the vessels and deriving the
extent of ice cover breakage. Information is also acquired through ice observers (personnel that travel
along the shores of the river and make observations of the ice situation and extent). This information is
useful for planning further ice breakage campaigns. The data is made publicly available at the ELWIS
website (https://www.elwis.de/DE/dynamisch/gewaesserkunde/eislage/) (ELWIS—Elektronische
Wasserstraßen-Informationssystem; English = electronic waterways information system) with water
levels to be found at the PEGELONLINE (English = Gauge Online) web service (https://www.
pegelonline.wsv.de/). Ice breaking operations and planning could profit from an ice jam forecasting
service by, for instance, narrowing the distance for the ice observers who generally have to cover
160 km of river.
Water 2019, 11, x FOR PEER REVIEW 5 of 20
information is useful for planning further ice breakage campaigns. The data is made publicly
available at the ELWIS website (https://www.elwis.de/DE/dynamisch/gewaesserkunde/eislage/)
(ELWIS—Elektronische Wasserstraßen-Informationssystem; English = electronic waterways
information system) with water levels to be found at the PEGELONLINE (English = Gauge Online)
web service (https://www.pegelonline.wsv.de/). Ice breaking operations and planning could profit
from an ice jam forecasting service by, for instance, narrowing the distance for the ice observers who
generally have to cover 160 km of river.
Figure 4. Ice breakers operating in parallel to break up thinner ice covers on low sloping waters
(courtesy of Regional Water Management Authority, Szczecin).
A hindrance to ice breakage is low water flow (and depth), which prevents many of the vessels
from being able to drive along the river without grounding on the river bed or sandbars. Too high
water levels can also be a problem for vessels to pass underneath many bridges crossing the Oder
River (see Figure 5).
Figure 5. Ice breakers barely able to drive under a bridge during high flows in the Oder River
(courtesy of Regional Water Management Authority, Szczecin).
3. Requirements for an Ice Jam Flood Forecasting System on the Oder River
When developing an ice jam flood forecasting system, it is important that the whole life-cycle of
the ice jam, from formation, to extension and further to movement, be taken into consideration.
Figure 6 shows a scheme of an ice jam. Highlighted in the figure are the areas of high erosion at the
ice jam toe. Due to increased flow velocities under the ice jam, scour may occur more abrasively at
the river bed and erode ice from the ice jam.
Figure 4.
Ice breakers operating in parallel to break up thinner ice covers on low sloping waters
(courtesy of Regional Water Management Authority, Szczecin).
A hindrance to ice breakage is low water flow (and depth), which prevents many of the vessels
from being able to drive along the river without grounding on the river bed or sandbars. Too high
water levels can also be a problem for vessels to pass underneath many bridges crossing the Oder
River (see Figure 5).
Water 2019, 11, x FOR PEER REVIEW 5 of 20
information is useful for planning further ice breakage campaigns. The data is made publicly
available at the ELWIS website (https://www.elwis.de/DE/dynamisch/gewaesserkunde/eislage/)
(ELWIS—Elektronische Wasserstraßen-Informationssystem; English = electronic waterways
information system) with water levels to be found at the PEGELONLINE (English = Gauge Online)
web service (https://www.pegelonline.wsv.de/). Ice breaking operations and planning could profit
from an ice jam forecasting service by, for instance, narrowing the distance for the ice observers who
generally have to cover 160 km of river.
Figure 4. Ice breakers operating in parallel to break up thinner ice covers on low sloping waters
(courtesy of Regional Water Management Authority, Szczecin).
A hindrance to ice breakage is low water flow (and depth), which prevents many of the vessels
from being able to drive along the river without grounding on the river bed or sandbars. Too high
water levels can also be a problem for vessels to pass underneath many bridges crossing the Oder
River (see Figure 5).
Figure 5. Ice breakers barely able to drive under a bridge during high flows in the Oder River
(courtesy of Regional Water Management Authority, Szczecin).
3. Requirements for an Ice Jam Flood Forecasting System on the Oder River
When developing an ice jam flood forecasting system, it is important that the whole life-cycle of
the ice jam, from formation, to extension and further to movement, be taken into consideration.
Figure 6 shows a scheme of an ice jam. Highlighted in the figure are the areas of high erosion at the
ice jam toe. Due to increased flow velocities under the ice jam, scour may occur more abrasively at
the river bed and erode ice from the ice jam.
Figure 5.
Ice breakers barely able to drive under a bridge during high flows in the Oder River (courtesy
of Regional Water Management Authority, Szczecin).
3. Requirements for an Ice Jam Flood Forecasting System on the Oder River
When developing an ice jam flood forecasting system, it is important that the whole life-cycle
of the ice jam, from formation, to extension and further to movement, be taken into consideration.
Figure 6shows a scheme of an ice jam. Highlighted in the figure are the areas of high erosion at the ice
Water 2019,11, 95 6 of 20
jam toe. Due to increased flow velocities under the ice jam, scour may occur more abrasively at the
river bed and erode ice from the ice jam.
Water 2019, 11, x FOR PEER REVIEW 6 of 20
Figure 6. Illustration scheme of established ice jam with ice erosion from the ice jam toe and scour of
the river bed below the ice jam.
3.1. Ice Jam Formation
The formation of an ice jam depends on many different factors:
Characteristics of the moving ice floes—large vs. small, thick vs. thin;
Flow velocity and temperature of the water—faster flows will tend to increase thrust on the ice
jam front and drag along the underside of the ice jam, which will increase the severity of the jam
and resulting backwater staging; higher water temperatures can ablate the ice quicker;
Form of the river profile—both meandering or varying cross-sectional flow areas influence flow
velocity fields;
Characteristics of the river bed (sediment)—gravel beds will erode less than beds with soft
sediment;
Weather conditions—cold air temperatures will create more ice and also increase cohesion to
consolidate ice covers more quickly.
3.2. Ice Cover Extension
Experience has shown that ice jams generally lead to backwater levels between 0.6 m and 1.5 m
of increased staging. The speed at which the front of the ice cover extends upstream can be very
different. In 2012, the front progressed from Stützkow to Kietz within six days. In 2016, the front
progression only required three days for the same 66 km length. This process is illustrated in Figure
7. From 4–7 February 2016, the front of the ice cover advanced past the four gauges shown. Each time,
the staging is followed by a slight decrease in water levels. This indicates that the highly dynamic ice
and hydraulic processes, particularly at the river bed and the underside of the ice cover, have
subsided. The abrupt decrease in water level immediately after the stage peak at Hohensaaten-Finow
is an indication of high erosion of the river bed at the ice jam location. Once the ice jam has been
established, its upstream extension and thickening will also depend on many factors:
Amount of incoming ice—determines the supply of ice to the jam and its juxtapositioning cover;
more ice supplied from upstream floes and frazil ice may shove and thicken the jams,
exasperating backwater staging;
Weather conditions in the upstream river basin—persistent cold weather will generate more ice;
rain-on-snow or rain-on-frozen ground events can increase discharges and lead to increased
staging before ice jams are flushed out of the river stretch;
Water level (size of flooded area) during ice generation;
Dynamic water level in the ice generation zone;
Structure of the ice floes—e.g., thickness, size and consistency of the ice floes.
deposition
transport
erosion
juxtaposition
ice cover
ice jam
ice jam
toe
ice cover
ice jam
Figure 6.
Illustration scheme of established ice jam with ice erosion from the ice jam toe and scour of
the river bed below the ice jam.
3.1. Ice Jam Formation
The formation of an ice jam depends on many different factors:
•Characteristics of the moving ice floes—large vs. small, thick vs. thin;
•
Flow velocity and temperature of the water—faster flows will tend to increase thrust on the ice
jam front and drag along the underside of the ice jam, which will increase the severity of the jam
and resulting backwater staging; higher water temperatures can ablate the ice quicker;
•
Form of the river profile—both meandering or varying cross-sectional flow areas influence flow
velocity fields;
•
Characteristics of the river bed (sediment)—gravel beds will erode less than beds with
soft sediment;
•
Weather conditions—cold air temperatures will create more ice and also increase cohesion to
consolidate ice covers more quickly.
3.2. Ice Cover Extension
Experience has shown that ice jams generally lead to backwater levels between 0.6 m and 1.5 m
of increased staging. The speed at which the front of the ice cover extends upstream can be very
different. In 2012, the front progressed from Stützkow to Kietz within six days. In 2016, the front
progression only required three days for the same 66 km length. This process is illustrated in Figure 7.
From 4–7 February 2016, the front of the ice cover advanced past the four gauges shown. Each time,
the staging is followed by a slight decrease in water levels. This indicates that the highly dynamic ice
and hydraulic processes, particularly at the river bed and the underside of the ice cover, have subsided.
The abrupt decrease in water level immediately after the stage peak at Hohensaaten-Finow is an
indication of high erosion of the river bed at the ice jam location. Once the ice jam has been established,
its upstream extension and thickening will also depend on many factors:
•
Amount of incoming ice—determines the supply of ice to the jam and its juxtapositioning
cover; more ice supplied from upstream floes and frazil ice may shove and thicken the jams,
exasperating backwater staging;
•
Weather conditions in the upstream river basin—persistent cold weather will generate more
ice; rain-on-snow or rain-on-frozen ground events can increase discharges and lead to increased
staging before ice jams are flushed out of the river stretch;
•Water level (size of flooded area) during ice generation;
•Dynamic water level in the ice generation zone;
Water 2019,11, 95 7 of 20
•Structure of the ice floes—e.g., thickness, size and consistency of the ice floes.
Water 2019, 11, x FOR PEER REVIEW 7 of 20
Figure 7. Backwater staging caused by an ice jam along the lower Oder River in January 2016. Water
levels are shown for the gauges, in the downstream direction at Stützkow (Oder-km 685; values
reduced by 300 cm in the graph), Hohensaaten-Finow (Oder-km 665), Kienitz (Oder-km 632) and
Kietz (Oder-km 615) (data source: Wasser- und Schifffahrtsverwaltung, Eberswalde, Germany).
3.3. Ice Cover Movement
Once the ice jam and its extended cover has been established to persist for, in some cases, several
days, changes occur in the ice that lead to abrupt movements of sections of the cover leading to:
Shifts in the ice causing shear stresses along the bottom of the ice cover to redistribute and break
sections of the cover;
Sections of broken ice sheets submerging under downstream covers to form layers leading to
thickening of ice;
Open leads which often form when ice releases from the cover and submerge to be swept with
the current and deposited on downstream ice covers and established ice jams.
An important consideration of ice jam flooding is the short time frame to issue flood alerts and
warnings if a jam and extreme backwater staging occur. Figure 8 shows an abrupt rise in backwater
levels, approximately within five hours to the peak, recorded at Ratzdorf from a downstream ice jam.
Superimposed are the four stages of flood warnings, loosely translated from the German as: A-I flood
watch (Meldebeginn), A-II flood warning (Kontrolldienst), A-III flood alert (Wachdienst) and A-IV flood
defense (Hochwasserabwehr). The water levels almost attained a level A-IV, for which, generally, an
intensive flood defense notice would have been issued. In this specific case, this would have meant
intensive observations of the dike and the introduction of possible protective measures. Fortunately,
in this case, there were no dike breaches. Hence, an ice jam flood forecasting system will need to
address the following questions:
Where will an ice jam occur?
When will the ice jam occur?
How much backwater staging will result?
What is the time to peak?
Will there be potential water level rises after an ice jam releases?
Figure 7.
Backwater staging caused by an ice jam along the lower Oder River in January 2016.
Water levels are shown for the gauges, in the downstream direction at Stützkow (Oder-km 685;
values reduced by 300 cm in the graph), Hohensaaten-Finow (Oder-km 665), Kienitz (Oder-km 632)
and Kietz (Oder-km 615) (data source: Wasser- und Schifffahrtsverwaltung, Eberswalde, Germany).
3.3. Ice Cover Movement
Once the ice jam and its extended cover has been established to persist for, in some cases,
several days, changes occur in the ice that lead to abrupt movements of sections of the cover leading to:
•
Shifts in the ice causing shear stresses along the bottom of the ice cover to redistribute and break
sections of the cover;
•
Sections of broken ice sheets submerging under downstream covers to form layers leading to
thickening of ice;
•
Open leads which often form when ice releases from the cover and submerge to be swept with
the current and deposited on downstream ice covers and established ice jams.
An important consideration of ice jam flooding is the short time frame to issue flood alerts and
warnings if a jam and extreme backwater staging occur. Figure 8shows an abrupt rise in backwater
levels, approximately within five hours to the peak, recorded at Ratzdorf from a downstream ice
jam. Superimposed are the four stages of flood warnings, loosely translated from the German as:
A-I flood watch (Meldebeginn), A-II flood warning (Kontrolldienst), A-III flood alert (Wachdienst) and
A-IV flood defense (Hochwasserabwehr). The water levels almost attained a level A-IV, for which,
generally, an intensive flood defense notice would have been issued. In this specific case, this would
have meant intensive observations of the dike and the introduction of possible protective measures.
Fortunately, in this case, there were no dike breaches. Hence, an ice jam flood forecasting system will
need to address the following questions:
•Where will an ice jam occur?
•When will the ice jam occur?
•How much backwater staging will result?
•What is the time to peak?
•Will there be potential water level rises after an ice jam releases?
Water 2019,11, 95 8 of 20
Water 2019, 11, x FOR PEER REVIEW 8 of 20
Figure 8. Abrupt rise in water levels at Ratzdorf (Oder-km 542) in February 2012. Water levels almost
reached Level A-IV of the flood warning system, which would have left a short response for
additional protective measures ( source: Wasser- und Schifffahrtsverwaltung, Eberswalde, Germany).
4. Summary of Current Research
4.1. Climate Trends in the Oder River Basin
Along the lower reach of the Oder River, three stations on the Polish side of the river, at
Widuchowa, Gozdowice and Słubice, record meteorological data. Generally, a warming trend is
evident in the mean seasonal (November to March) air temperature records, as shown exemplarily
for Słubice in Figure 9, even if the inter-annual variability is strong. The warming has impacts on the
duration of ice present in the river (duration of ice phenomena, DIP) and the duration of an intact ice
cover (duration of ice cover, DIC), as indicated in Figure 10. Generally, there is a decreasing trend in
DIC, which is particularly steep in records taken at Słubice. Downward trends were less steep for
DIC recorded at Widuchowa and Gozdowice and no trend could be traced for DIP at Słubice. It is to
be expected that even if gradual warming is robustly projected for the future [12], ice breaking will
need to continue for several decades to come to maintain shipping and prevent ice flooding during
ice jam susceptible periods.
Figure 9. Mean air temperature in the months of possible occurrence of ice phenomena (November–
March) in Słubice, 1956–2015 (based on data from the Institute of Meteorology and Water
Management—National Research Institute in Warsaw).
Figure 8.
Abrupt rise in water levels at Ratzdorf (Oder-km 542) in February 2012. Water levels almost
reached Level A-IV of the flood warning system, which would have left a short response for additional
protective measures ( source: Wasser- und Schifffahrtsverwaltung, Eberswalde, Germany).
4. Summary of Current Research
4.1. Climate Trends in the Oder River Basin
Along the lower reach of the Oder River, three stations on the Polish side of the river, at
Widuchowa, Gozdowice and Słubice, record meteorological data. Generally, a warming trend is
evident in the mean seasonal (November to March) air temperature records, as shown exemplarily
for Słubice in Figure 9, even if the inter-annual variability is strong. The warming has impacts on the
duration of ice present in the river (duration of ice phenomena, DIP) and the duration of an intact ice
cover (duration of ice cover, DIC), as indicated in Figure 10. Generally, there is a decreasing trend in
DIC, which is particularly steep in records taken at Słubice. Downward trends were less steep for DIC
recorded at Widuchowa and Gozdowice and no trend could be traced for DIP at Słubice. It is to be
expected that even if gradual warming is robustly projected for the future [
12
], ice breaking will need
to continue for several decades to come to maintain shipping and prevent ice flooding during ice jam
susceptible periods.
Water 2019, 11, x FOR PEER REVIEW 8 of 20
Figure 8. Abrupt rise in water levels at Ratzdorf (Oder-km 542) in February 2012. Water levels almost
reached Level A-IV of the flood warning system, which would have left a short response for
additional protective measures ( source: Wasser- und Schifffahrtsverwaltung, Eberswalde, Germany).
4. Summary of Current Research
4.1. Climate Trends in the Oder River Basin
Along the lower reach of the Oder River, three stations on the Polish side of the river, at
Widuchowa, Gozdowice and Słubice, record meteorological data. Generally, a warming trend is
evident in the mean seasonal (November to March) air temperature records, as shown exemplarily
for Słubice in Figure 9, even if the inter-annual variability is strong. The warming has impacts on the
duration of ice present in the river (duration of ice phenomena, DIP) and the duration of an intact ice
cover (duration of ice cover, DIC), as indicated in Figure 10. Generally, there is a decreasing trend in
DIC, which is particularly steep in records taken at Słubice. Downward trends were less steep for
DIC recorded at Widuchowa and Gozdowice and no trend could be traced for DIP at Słubice. It is to
be expected that even if gradual warming is robustly projected for the future [12], ice breaking will
need to continue for several decades to come to maintain shipping and prevent ice flooding during
ice jam susceptible periods.
Figure 9. Mean air temperature in the months of possible occurrence of ice phenomena (November–
March) in Słubice, 1956–2015 (based on data from the Institute of Meteorology and Water
Management—National Research Institute in Warsaw).
Figure 9.
Mean air temperature in the months of possible occurrence of ice phenomena
(November–March) in Słubice, 1956–2015 (based on data from the Institute of Meteorology and Water
Management—National Research Institute in Warsaw).
Water 2019,11, 95 9 of 20
Water 2019, 11, x FOR PEER REVIEW 9 of 20
Figure 10. Duration of ice phenomena (DIP) in days (blue) and duration of ice cover (DIC) in days
(red) on the Oder River at Słubice with their rates of change (1956–2015) (based on data from the
Institute of Meteorology and Water Management—National Research Institute in Warsaw).
Figure 11 shows the locations of ice jams with thicknesses in excess of 1 m that occurred along
the lower Oder River in 2009–2018. The figure reveals that most of the ice jamming occurs along the
most downstream stretch of the river, the portion that is affected by tides and wind surges from the
Baltic Sea.
Figure 11. Location of sections where ice jams of at least 1 m thickness were recorded in the years
2009–2018 (based on data from the Regional Water Management Authority, Szczecin).
Future predictions of river flows [13] indicate general increases in mean discharge across Poland,
both in the near and far futures (2021–2050 and 2071–2100, respectively). The maps in Figure 12
summarize results obtained from an ensemble of nine bias-corrected EURO-CORDEX (Coordinated
Downscaling Experiment—European Domain) simulations. The Oder River is marked as bold in the
projection maps. Higher discharges in the future may exasperate ice jamming and ice flooding in the
lower reaches of the river.
Figure 10.
Duration of ice phenomena (DIP) in days (blue) and duration of ice cover (DIC) in days (red)
on the Oder River at Słubice with their rates of change (1956–2015) (based on data from the Institute of
Meteorology and Water Management—National Research Institute in Warsaw).
Figure 11 shows the locations of ice jams with thicknesses in excess of 1 m that occurred along
the lower Oder River in 2009–2018. The figure reveals that most of the ice jamming occurs along the
most downstream stretch of the river, the portion that is affected by tides and wind surges from the
Baltic Sea.
Water 2019, 11, x FOR PEER REVIEW 9 of 20
Figure 10. Duration of ice phenomena (DIP) in days (blue) and duration of ice cover (DIC) in days
(red) on the Oder River at Słubice with their rates of change (1956–2015) (based on data from the
Institute of Meteorology and Water Management—National Research Institute in Warsaw).
Figure 11 shows the locations of ice jams with thicknesses in excess of 1 m that occurred along
the lower Oder River in 2009–2018. The figure reveals that most of the ice jamming occurs along the
most downstream stretch of the river, the portion that is affected by tides and wind surges from the
Baltic Sea.
Figure 11. Location of sections where ice jams of at least 1 m thickness were recorded in the years
2009–2018 (based on data from the Regional Water Management Authority, Szczecin).
Future predictions of river flows [13] indicate general increases in mean discharge across Poland,
both in the near and far futures (2021–2050 and 2071–2100, respectively). The maps in Figure 12
summarize results obtained from an ensemble of nine bias-corrected EURO-CORDEX (Coordinated
Downscaling Experiment—European Domain) simulations. The Oder River is marked as bold in the
projection maps. Higher discharges in the future may exasperate ice jamming and ice flooding in the
lower reaches of the river.
Figure 11.
Location of sections where ice jams of at least 1 m thickness were recorded in the years
2009–2018 (based on data from the Regional Water Management Authority, Szczecin).
Future predictions of river flows [
13
] indicate general increases in mean discharge across Poland,
both in the near and far futures (2021–2050 and 2071–2100, respectively). The maps in Figure 12
summarize results obtained from an ensemble of nine bias-corrected EURO-CORDEX (Coordinated
Downscaling Experiment—European Domain) simulations. The Oder River is marked as bold in the
projection maps. Higher discharges in the future may exasperate ice jamming and ice flooding in the
lower reaches of the river.
Water 2019,11, 95 10 of 20
Water 2019, 11, x FOR PEER REVIEW 10 of 20
Figure 12. Changes in the multi-model ensemble means of annual runoff for the Vistula and Oder
river basins, for the near future (NF) and far future (FF) (2021–2050 and 2071–2100, respectively)
under Representative Concentration Pathway (RCP) 4.5 and 8.5 (adapted from [13]).
4.2. Space-Borne Remote Sensing
4.2.1. Optical and Thermal Imagery
The use of both Sentinel-2 and Landsat-8 imagery of the Oder River was discussed to determine
the feasibility of implementing optical and thermal imagery of the river’s ice cover for ice type
detection. Due to the simplicity and small computational effort, the optical imagery constitutes a
good source of data for ice jam studies. It is imperative that image download and processing be
automated so that the images are suitable for operational hydrology and forecasting tasks. The
Sentinel-2 resolution (especially the 10 m bands VIS (visible) and NIR (near infra-red)) is suitable for
Oder River monitoring (an example is provided in Figure 13), while the Landsat-8 data (finest
resolution = 30 m) could be considered as a supplementary source of imagery. Thermal imagery from
Landsat-8 is available at the finest resolution of 100 m and is deemed too coarse to be appropriate for
studies of the thermal state of the Oder River. Cloudiness is the main limitation of space-borne optical
imagery, especially during winter. For the acquisition of thermal imagery, the use of unmanned aerial
vehicles (UAVs), albeit for smaller areas of interest, could be used.
Figure 12.
Changes in the multi-model ensemble means of annual runoff for the Vistula and Oder
river basins, for the near future (NF) and far future (FF) (2021–2050 and 2071–2100, respectively) under
Representative Concentration Pathway (RCP) 4.5 and 8.5 (adapted from [13]).
4.2. Space-Borne Remote Sensing
4.2.1. Optical and Thermal Imagery
The use of both Sentinel-2 and Landsat-8 imagery of the Oder River was discussed to determine
the feasibility of implementing optical and thermal imagery of the river’s ice cover for ice type detection.
Due to the simplicity and small computational effort, the optical imagery constitutes a good source of
data for ice jam studies. It is imperative that image download and processing be automated so that
the images are suitable for operational hydrology and forecasting tasks. The Sentinel-2 resolution
(especially the 10 m bands VIS (visible) and NIR (near infra-red)) is suitable for Oder River monitoring
(an example is provided in Figure 13), while the Landsat-8 data (finest resolution = 30 m) could be
considered as a supplementary source of imagery. Thermal imagery from Landsat-8 is available at the
finest resolution of 100 m and is deemed too coarse to be appropriate for studies of the thermal state of
the Oder River. Cloudiness is the main limitation of space-borne optical imagery, especially during
winter. For the acquisition of thermal imagery, the use of unmanned aerial vehicles (UAVs), albeit for
smaller areas of interest, could be used.
Water 2019,11, 95 11 of 20
Water 2019, 11, x FOR PEER REVIEW 11 of 20
Figure 13. Sentinel-2B image acquired for the Oder River on 2 February 2018. The bridge crosses the
river at 50°30′53.34″ N, 17°57′16.78″ E.
4.2.2. Microwave Imagery
A river ice monitoring service based on satellite data for major Polish rivers, including the Oder
River, has been launched on a pilot project scale. The service is set up to support the authorities in
Poland responsible for water management by regularly providing continuous information about ice-
related events on rivers, thanks to a fully autonomous service equipped with modules for automatic
downloading and satellite data processing which is updated within a few hours after acquisition. The
detection of ice is based on images acquired by the European Space Agency’s Sentinel-1A and
Sentinel-1B microwave satellites. The application of Sentinel radar sensors allows imagery to be
collected every 2–7 days, independent of weather conditions (excluding intensive storms and snow
falls), and processed in near real time. Microwave return signals from snow (including snow layers
on ice), ice and water are distinguishable as long as the ice is not covered with a thick layer of stable
water or wet snow or does not consist of smooth, thermal ice, which is typical for lakes. The data can
be classified into four coverage types within the river (including water) which are available through
the map portal. An example of classification results is shown in Figure 14:
Water—river free of ice phenomena;
Fractured ice—floe or frazil ice floating and free flowing;
Solid ice cover—ice cover not covered with snow, also sections of the river covered with dense
frazil ice or densely arranged floes;
Ice cover by snow—areas of the river bed giving a very strong reflection of radiation in both the
visible and low backscattering in the microwave portion of the spectrum.
Figure 13.
Sentinel-2B image acquired for the Oder River on 2 February 2018. The bridge crosses the
river at 50◦30053.34” N, 17◦57016.78” E.
4.2.2. Microwave Imagery
A river ice monitoring service based on satellite data for major Polish rivers, including the Oder
River, has been launched on a pilot project scale. The service is set up to support the authorities
in Poland responsible for water management by regularly providing continuous information about
ice-related events on rivers, thanks to a fully autonomous service equipped with modules for automatic
downloading and satellite data processing which is updated within a few hours after acquisition.
The detection of ice is based on images acquired by the European Space Agency’s Sentinel-1A and
Sentinel-1B microwave satellites. The application of Sentinel radar sensors allows imagery to be
collected every 2–7 days, independent of weather conditions (excluding intensive storms and snow
falls), and processed in near real time. Microwave return signals from snow (including snow layers
on ice), ice and water are distinguishable as long as the ice is not covered with a thick layer of stable
water or wet snow or does not consist of smooth, thermal ice, which is typical for lakes. The data can
be classified into four coverage types within the river (including water) which are available through
the map portal. An example of classification results is shown in Figure 14:
•Water—river free of ice phenomena;
•Fractured ice—floe or frazil ice floating and free flowing;
•
Solid ice cover—ice cover not covered with snow, also sections of the river covered with dense
frazil ice or densely arranged floes;
•
Ice cover by snow—areas of the river bed giving a very strong reflection of radiation in both the
visible and low backscattering in the microwave portion of the spectrum.
Water 2019,11, 95 12 of 20
Water 2019, 11, x FOR PEER REVIEW 12 of 20
Figure 14. Comparison of Sentinel-2 RGB (red-green-blue) composition (left panel) and classification
of Sentinel-1 data (right panel) (Lower Vistula River, acquired 31 January 2017). The bridge crosses
the river at coordinates 54°15′21.03″ N, 18°56′45.94″ E.
In addition to Sentinel-1, data acquired from other microwave satellite sensors were also
investigated in other applications to test their feasibility in detecting and characterizing ice along the
Oder River. These include the German TerraSAR-X (X-band) and the Canadian RADARSAT-2 (C-
band) sensors. Significant differences were not found in distinguishing ice types between X-band and
C-band data. An important difference between the capabilities of the two sensors is RADARSAT-2 is
able to acquire data in quad-pol and dual-pol, whereas TerraSAR-X data are usually acquired only
in dual-pol or single-pol [14]. However, quad-pol data did not significantly improve classification
results compared to dual-pol data. Characteristics of three microwave sensors, TerraSAR-X (the
German Aerospace Center (DLR) headquarters, Cologne, Germany), RADARSAT-2 (MacDonald,
Dettwiler and Associates headquarters, Richmond, BC, Canada) and Sentinel-1 (operated by the
European Space Agency with headquarters in Paris, France), are provided in Table 1. Imagery
acquired by RADARSAT-2 have also been applied for mapping floods caused by ice jams along the
Oder River in January 2011. Derived map products are available at the website of the Center for
Satellite based Crisis Information (ZKI):
https://activations.zki.dlr.de/en/activations/items/ACT094.html.
Table 1. Characteristics of the three microwave sensors, TerraSAR-X, RADARSAT-2 and Sentinel-1.
TerraSAR-X
RADARSAT-2
Sentinel-1
frequency/wavelength X-band/3 cm C-band/5.6 cm C-band/5.6 cm
polarisation single-pol, dual-pol,
(quad-pol)
single-pol, dual-pol,
quad-pol single-pol, dual-pol
spatial resolution
(SLC)/scene size
0.6 m/4 km
(spotlight)
3.3.m/270 km (wide
ScanSAR)
8 m/50 km (fine mode)
100 m/500 km (ScanSAR
wide mode)
5 m/80 km (StripMap)
20 m/250 km
(interferometric wide
swath
data access commercial
distribution of data
commercial distribution
of data open data policy
4.3. River Discharge and Flood Extent Forecasting
Figure 14.
Comparison of Sentinel-2 RGB (red-green-blue) composition (
left panel
) and classification
of Sentinel-1 data (
right panel
) (Lower Vistula River, acquired 31 January 2017). The bridge crosses the
river at coordinates 54◦15021.03” N, 18◦56045.94” E.
In addition to Sentinel-1, data acquired from other microwave satellite sensors were also
investigated in other applications to test their feasibility in detecting and characterizing ice along
the Oder River. These include the German TerraSAR-X (X-band) and the Canadian RADARSAT-2
(C-band) sensors. Significant differences were not found in distinguishing ice types between X-band
and C-band data. An important difference between the capabilities of the two sensors is RADARSAT-2
is able to acquire data in quad-pol and dual-pol, whereas TerraSAR-X data are usually acquired only in
dual-pol or single-pol [
14
]. However, quad-pol data did not significantly improve classification results
compared to dual-pol data. Characteristics of three microwave sensors, TerraSAR-X (the German
Aerospace Center (DLR) headquarters, Cologne, Germany), RADARSAT-2 (MacDonald, Dettwiler
and Associates headquarters, Richmond, BC, Canada) and Sentinel-1 (operated by the European
Space Agency with headquarters in Paris, France), are provided in Table 1. Imagery acquired by
RADARSAT-2 have also been applied for mapping floods caused by ice jams along the Oder River in
January 2011. Derived map products are available at the website of the Center for Satellite based Crisis
Information (ZKI): https://activations.zki.dlr.de/en/activations/items/ACT094.html.
Table 1. Characteristics of the three microwave sensors, TerraSAR-X, RADARSAT-2 and Sentinel-1.
TerraSAR-X RADARSAT-2 Sentinel-1
frequency/wavelength X-band/3 cm C-band/5.6 cm C-band/5.6 cm
polarisation single-pol, dual-pol, (quad-pol) single-pol, dual-pol, quad-pol single-pol, dual-pol
spatial resolution
(SLC)/scene size
0.6 m/4 km (spotlight)
3.3.m/270 km (wide ScanSAR)
8 m/50 km (fine mode)
100 m/500 km (ScanSAR wide mode)
5 m/80 km (StripMap)
20 m/250 km (interferometric
wide swath
data access commercial distribution of data commercial distribution of data open data policy
Water 2019,11, 95 13 of 20
4.3. River Discharge and Flood Extent Forecasting
4.3.1. Hydrological Modelling
The flood forecasting system HydroProg, developed at the University of Wrocław, was introduced
as an option to forecast flows for the upper basin of the Oder River. Such flows would be imperative
to predict ice cover buildup and ice jamming further downstream along the lower Oder River.
HydroProg produces early warnings of high flows and flood waters and operates in real time,
integrating data from a network of hydro-meteorological gauging stations and numerous hydrologic
models. Data quality control is automated and interpolates missing or incorrect data on the fly.
The system produces ensembles of multi-model hydrograph predictions, an example of which is
provided in Figure 15. An important output in real time is flood maps that are created from the
hydrodynamic modelling component of the system [
15
]. An important novelty for the validation of
flood predictions is the use of unmanned aerial vehicles (UAVs) to compare observed flood extents
with model simulations [
15
]. More details on the system itself can be obtained from [
16
] and [
17
] which
are demonstrated for Kłodzko Land, Poland at http://www.klodzko.hydroprog.uni.wroc.pl.
Water 2019, 11, x FOR PEER REVIEW 13 of 20
4.3.1. Hydrological Modelling
The flood forecasting system HydroProg, developed at the University of Wrocław, was
introduced as an option to forecast flows for the upper basin of the Oder River. Such flows would be
imperative to predict ice cover buildup and ice jamming further downstream along the lower Oder
River. HydroProg produces early warnings of high flows and flood waters and operates in real time,
integrating data from a network of hydro-meteorological gauging stations and numerous hydrologic
models. Data quality control is automated and interpolates missing or incorrect data on the fly. The
system produces ensembles of multi-model hydrograph predictions, an example of which is
provided in Figure 15. An important output in real time is flood maps that are created from the
hydrodynamic modelling component of the system [15]. An important novelty for the validation of
flood predictions is the use of unmanned aerial vehicles (UAVs) to compare observed flood extents
with model simulations [15]. More details on the system itself can be obtained from [16] and [17]
which are demonstrated for Kłodzko Land, Poland at http://www.klodzko.hydroprog.uni.wroc.pl.
Figure 15. Multi-model ensemble prediction of stages together with forecasts based on ensemble
members compared to measurements that were observed.
4.3.2. Hydrodynamic and River Ice Modelling
An ice jam that occurred near Kietz in January 2016 was successfully modelled with the
deterministic river ice model RIVICE [18]. RIVICE is a one-dimensional hydrodynamic model that
can simulate many ice processes such as frazil ice generation, border ice formation, anchor ice
emergence, ice cover juxtapositioning, ice cover shoving/telescoping, ice jamming and hanging dam
formation. Further details on the model’s algorithms are provided in [19]. The model has been
successfully implemented for many rivers, both for freeze-up and breakup ice jams, but mostly in a
Canadian setting. The Oder River stretch modelled with RIVICE extended from Ratzdorf
downstream past Kietz. Flows recorded at Eisenhüttenstadt served as an upstream boundary
condition. Water level elevations measured at Frankfurt/Oder and Kietz provided data for model
calibration. A longitudinal profile of the ice cover and backwater levels from the ice jam are shown
in Figure 16. The underestimated water level simulations due to the absence of spur dikes in the
Figure 15.
Multi-model ensemble prediction of stages together with forecasts based on ensemble
members compared to measurements that were observed.
4.3.2. Hydrodynamic and River Ice Modelling
An ice jam that occurred near Kietz in January 2016 was successfully modelled with the
deterministic river ice model RIVICE [
18
]. RIVICE is a one-dimensional hydrodynamic model that can
simulate many ice processes such as frazil ice generation, border ice formation, anchor ice emergence,
ice cover juxtapositioning, ice cover shoving/telescoping, ice jamming and hanging dam formation.
Further details on the model’s algorithms are provided in [
19
]. The model has been successfully
implemented for many rivers, both for freeze-up and breakup ice jams, but mostly in a Canadian
setting. The Oder River stretch modelled with RIVICE extended from Ratzdorf downstream past Kietz.
Flows recorded at Eisenhüttenstadt served as an upstream boundary condition. Water level elevations
measured at Frankfurt/Oder and Kietz provided data for model calibration. A longitudinal profile of
Water 2019,11, 95 14 of 20
the ice cover and backwater levels from the ice jam are shown in Figure 16. The underestimated water
level simulations due to the absence of spur dikes in the cross-sections used to set up the model was
compensated for by forcing border ice formation along the river banks.
Water 2019, 11, x FOR PEER REVIEW 14 of 20
cross-sections used to set up the model was compensated for by forcing border ice formation along
the river banks.
Figure 16. Longitudinal profile of the water levels and ice cover simulated from the ice jam that
formed at Kietz in January 2016 (adapted from [18]).
4.3.3. Stochastic Modelling
Once a RIVICE model has been set up and calibrated for a river stretch, the model can be
embedded in a Monte-Carlo framework to determine extreme value distributions of the volume of
ice, Vice, required to form jams along the model domain (see Figure 17). Input to the framework
includes extreme value distributions of the boundary conditions, respectively the upstream and
downstream boundaries of the domain. In a forecasting context (see Figure 18), these distributions
can be constrained according to the hydraulic and ice conditions before imminent ice jamming occurs.
The ensembles created from the Monte-Carlo simulations allow the exceedance probabilities of
staging and flood extent to be calculated. The stage exceedance probabilities can match up to the
stage levels of the flood warning system already in place for the Oder River. Further details on the
ice jam flood forecasting methodology can be obtained from [20].
4.4. Designing River Modifications to Reduce Probabilities of Ice Jamming
During cold spells in the winter months, a lot of ice can be generated along the lower reach of
the Oder River. As soon as warmer air temperatures provide some relief from the cold snap, both
German and Polish ice breakers are placed in operation to break up the ice cover and prevent ice
jamming and subsequent flooding from occurring. The ice breakers work their way upstream from
the Szczecin Estuary so that broken ice can float downstream into the estuary without becoming a
threat to jam elsewhere along the course of the river. A precarious situation often evolves at the fork
where the Oder River branches off into two rivers at Widuchowa, the Western and the Eastern Oder
branches. There is a weir in the Western Oder near the branch. The branching redistributes flows
within an area that is very flat and low sloping and is predisposed to jamming of ice floes released
by ice breakers upstream of the fork. A physical model was implemented to determine optimal
conditions of the flow and ice regimes to avoid jamming at this location. The model was built and
operated by the Federal Waterways Engineering and Research Institute (BAW) in Karlsruhe,
Germany. Figure 19 shows the setup of the physical model scaled down 1:150 (horizontal) and 1:30
(vertical) using plastic for the scaled ice floes. At various discharges, flow velocities of water and ice
Wasserspiegellage
infolge Eisbildung
Eisbildung
Wasserspiegellage
vor Eisbildung
Eisstau
Talweg
water level elevation
(m)
Water level before
ice formation
Thalweg
Ice
formation
Ice jam
Water level at
Kietz
08.01.2016
11.64 m a.s.l.
model chainage (km)
water level at
Frankfurt (Oder)
08.01.2016
18.37 m a.s.l.
Water level due to ice
jam formation
↖ Oder-km 582
↖ Oder-km 622
40 50 60 70 80
Figure 16.
Longitudinal profile of the water levels and ice cover simulated from the ice jam that formed
at Kietz in January 2016 (adapted from [18]).
4.3.3. Stochastic Modelling
Once a RIVICE model has been set up and calibrated for a river stretch, the model can be
embedded in a Monte-Carlo framework to determine extreme value distributions of the volume of
ice, V
ice
, required to form jams along the model domain (see Figure 17). Input to the framework
includes extreme value distributions of the boundary conditions, respectively the upstream and
downstream boundaries of the domain. In a forecasting context (see Figure 18), these distributions
can be constrained according to the hydraulic and ice conditions before imminent ice jamming occurs.
The ensembles created from the Monte-Carlo simulations allow the exceedance probabilities of staging
and flood extent to be calculated. The stage exceedance probabilities can match up to the stage levels
of the flood warning system already in place for the Oder River. Further details on the ice jam flood
forecasting methodology can be obtained from [20].
4.4. Designing River Modifications to Reduce Probabilities of Ice Jamming
During cold spells in the winter months, a lot of ice can be generated along the lower reach of the
Oder River. As soon as warmer air temperatures provide some relief from the cold snap, both German
and Polish ice breakers are placed in operation to break up the ice cover and prevent ice jamming and
subsequent flooding from occurring. The ice breakers work their way upstream from the Szczecin
Estuary so that broken ice can float downstream into the estuary without becoming a threat to jam
elsewhere along the course of the river. A precarious situation often evolves at the fork where the
Oder River branches off into two rivers at Widuchowa, the Western and the Eastern Oder branches.
There is a weir in the Western Oder near the branch. The branching redistributes flows within an area
that is very flat and low sloping and is predisposed to jamming of ice floes released by ice breakers
upstream of the fork. A physical model was implemented to determine optimal conditions of the flow
and ice regimes to avoid jamming at this location. The model was built and operated by the Federal
Waterways Engineering and Research Institute (BAW) in Karlsruhe, Germany. Figure 19 shows the
Water 2019,11, 95 15 of 20
setup of the physical model scaled down 1:150 (horizontal) and 1:30 (vertical) using plastic for the
scaled ice floes. At various discharges, flow velocities of water and ice were measured and analyzed
using photogrammetry. The artificial ice floes were able to mimic ice jamming at the forks, whose
probability could be shown to reduce significantly when more water is diverted into the Western
branch of the Oder River. More detailed information is provided in [21].
Water 2019, 11, x FOR PEER REVIEW 15 of 20
were measured and analyzed using photogrammetry. The artificial ice floes were able to mimic ice
jamming at the forks, whose probability could be shown to reduce significantly when more water is
diverted into the Western branch of the Oder River. More detailed information is provided in [21].
Figure 17. Monte-Carlo framework to calibrate the volume of ice, Vice, required to form ice jams along
a stretch of the Oder River. Inputs to the framework include extreme value distributions of flows, Q,
and water levels, W, at the upstream and downstream boundaries of the model domain, respectively.
The location and scale parameters of the extreme value distribution of Vice must first be estimated.
The model is then executed many times with each simulation run with a different set of randomly
extracted parameter and boundary condition values. Water levels at the gauge locations are extracted
from the resulting ensembles from which an extreme value distribution of stage is constructed
(simulated) that is compared to the distribution of the recorded ice jam peak stages (observed). If the
two distributions do not coincide, the simulations are repeated until the location and scale parameters
of Vice are adjusted. When the simulated and observed stage distributions coincide, the Vice
distribution is considered to be calibrated.
water level
profile
ensemble
thalweg
gauge
location
Monte-Carlo simulations
stage
probability
Q
frequency
W
frequency
Vice
frequency
Figure 17.
Monte-Carlo framework to calibrate the volume of ice, V
ice
, required to form ice jams
along a stretch of the Oder River. Inputs to the framework include extreme value distributions of
flows, Q, and water levels, W, at the upstream and downstream boundaries of the model domain,
respectively. The location and scale parameters of the extreme value distribution of V
ice
must first be
estimated. The model is then executed many times with each simulation run with a different set of
randomly extracted parameter and boundary condition values. Water levels at the gauge locations are
extracted from the resulting ensembles from which an extreme value distribution of stage is constructed
(simulated) that is compared to the distribution of the recorded ice jam peak stages (observed). If the
two distributions do not coincide, the simulations are repeated until the location and scale parameters
of V
ice
are adjusted. When the simulated and observed stage distributions coincide, the V
ice
distribution
is considered to be calibrated.
Water 2019,11, 95 16 of 20
Water 2019, 11, x FOR PEER REVIEW 16 of 20
Figure 18. The forecasting framework is based on the same Monte-Carlo framework as in the previous
figure, with the difference that the extreme value distributions of the upstream flow boundary
condition, Q, downstream water level boundary condition, W, and volume of ice, Vice, are constrained
according to the hydraulic and ice conditions immediately before the ice jam event is suspected to
occur.
Figure 19. Setup of physical model of the Oder River near Widuchowa, which forks into the Western
and Eastern channel branches of the river (adapted from [21]).
Figure 18.
The forecasting framework is based on the same Monte-Carlo framework as in the previous
figure, with the difference that the extreme value distributions of the upstream flow boundary condition,
Q, downstream water level boundary condition, W, and volume of ice, V
ice
, are constrained according
to the hydraulic and ice conditions immediately before the ice jam event is suspected to occur.
Water 2019, 11, x FOR PEER REVIEW 16 of 20
Figure 18. The forecasting framework is based on the same Monte-Carlo framework as in the previous
figure, with the difference that the extreme value distributions of the upstream flow boundary
condition, Q, downstream water level boundary condition, W, and volume of ice, Vice, are constrained
according to the hydraulic and ice conditions immediately before the ice jam event is suspected to
occur.
Figure 19. Setup of physical model of the Oder River near Widuchowa, which forks into the Western
and Eastern channel branches of the river (adapted from [21]).
Figure 19.
Setup of physical model of the Oder River near Widuchowa, which forks into the Western
and Eastern channel branches of the river (adapted from [21]).
Water 2019,11, 95 17 of 20
5. A Way Forward
The workshop in Wrocław was successful in providing a venue where scientists, government
officials and water managers from Poland, Germany and Canada could come together (see Figure 20
for a photo of the participants) to highlight ice issues along the Oder River and determine requirements
for a path forward to develop and implement ice jam flood forecasting capabilities for this river.
There are many future climatic conditions that may counter each other, so it is difficult to foresee
how the frequency and severity of ice jam events may change in a future climate. For instance, on the
one hand, it was shown that the mean air temperature will potentially increase in the future, reducing
the duration times of ice phenomena present and intact ice cover forming on the Oder River. On the
other hand, more extreme precipitation events in the headwaters of the Oder River catchment could
supply higher discharges to exacerbate ice jamming and staging. Hence, it is vital that numerical
capabilities be extended so that scenarios with future climatic conditions can be run to determine how
ice behavior and characteristics may change along the Oder River.
An evolution of numerical methods is required for the Oder River to progressively develop
predictive capabilities of the ice processes in the river for management and forecasting tasks. As a start,
simple empirical relationships should be explored to determine correlations that may persist between
morphological and phenological factors of the ice, hydraulic and geomorphological factors of the river
and meteorological factors. Some empirical attempts have been made to develop forecasting methods
by White [
6
,
7
]; these methods can be drawn upon for the Oder River, remembering that the empirical
relationships may be very site-specific.
Water 2019, 11, x FOR PEER REVIEW 17 of 20
5. A Way Forward
The workshop in Wrocław was successful in providing a venue where scientists, government
officials and water managers from Poland, Germany and Canada could come together (see Figure 20
for a photo of the participants) to highlight ice issues along the Oder River and determine
requirements for a path forward to develop and implement ice jam flood forecasting capabilities for
this river.
There are many future climatic conditions that may counter each other, so it is difficult to foresee
how the frequency and severity of ice jam events may change in a future climate. For instance, on the
one hand, it was shown that the mean air temperature will potentially increase in the future, reducing
the duration times of ice phenomena present and intact ice cover forming on the Oder River. On the
other hand, more extreme precipitation events in the headwaters of the Oder River catchment could
supply higher discharges to exacerbate ice jamming and staging. Hence, it is vital that numerical
capabilities be extended so that scenarios with future climatic conditions can be run to determine
how ice behavior and characteristics may change along the Oder River.
An evolution of numerical methods is required for the Oder River to progressively develop
predictive capabilities of the ice processes in the river for management and forecasting tasks. As a
start, simple empirical relationships should be explored to determine correlations that may persist
between morphological and phenological factors of the ice, hydraulic and geomorphological factors
of the river and meteorological factors. Some empirical attempts have been made to develop
forecasting methods by White [6,7]; these methods can be drawn upon for the Oder River,
remembering that the empirical relationships may be very site-specific.
Figure 20. Wrocław workshop participants (from left to right): Stefan Schlaffer, Zbigniew W.
Kundzewicz, Włodzimierz Marszelewski, Marcin Nowak, Karl-Erich Lindenschmidt, Stefan Iwicki,
Adam Łazarów, Michał Kubicki, Bogusław Pawłowski, Tomasz Niedzielski, Bernd Hentschel,
Wolfgang Fröhlich, Dirk Carstensen, Michael Roers, Cornelia Lauschke, Michael Kögel and Beata
Weintrit.
Although the location of ice jam occurrences may appear quite random, hot spots are present
along the Oder River with higher affinities for ice jam formation. Forecasting the locations of ice jam
occurrences is difficult to carry out due to the complexity of the ice jamming processes and the
numerous morphological, meteorological and hydrological interactions involved leading up to ice
jamming. A more reliable approach may be to develop a simplified geospatial model that can
Figure 20.
Wrocław workshop participants (from left to right): Stefan Schlaffer, Zbigniew W. Kundzewicz,
Włodzimierz Marszelewski, Marcin Nowak, Karl-Erich Lindenschmidt, Stefan Iwicki, Adam Łazarów,
Michał Kubicki, Bogusław Pawłowski, Tomasz Niedzielski, Bernd Hentschel, Wolfgang Fröhlich,
Dirk Carstensen, Michael Roers, Cornelia Lauschke, Michael Kögel and Beata Weintrit.
Although the location of ice jam occurrences may appear quite random, hot spots are present
along the Oder River with higher affinities for ice jam formation. Forecasting the locations of ice
jam occurrences is difficult to carry out due to the complexity of the ice jamming processes and
the numerous morphological, meteorological and hydrological interactions involved leading up to
ice jamming. A more reliable approach may be to develop a simplified geospatial model that can
Water 2019,11, 95 18 of 20
estimate the predisposition of river reaches to certain ice cover behaviors and fluvial geomorphological
characteristics. Attempts have been made to correlate river freeze-up [
22
] and ice cover breakup [
23
] to
riverine geomorphological features such as sinuosity, slope and width. Such geospatial models would
need to be extended to include hydraulic and meteorological factors as well. Sediment transport could
also be included in the geospatial modelling. A HEC-6T model (https://mbh2o.com/hec-6t/) has
already been developed for the lower Oder River to indicate sediment depositional and erosional
areas [24].
The next step after empirical and geospatial modelling could be the development of deterministic
models with a more physically-based description of the river ice processes. An example of such a
model that was introduced at the workshop is RIVICE, which was set up and run for a stretch along the
Oder River. More effort is required to implement additional processes that are particular to the Oder
setting, such as the formation of ice cover between spur dikes. Deterministic modelling would also
provide opportunities to extend monitoring capabilities using space-borne (satellite platforms) and
air-borne (unmanned aerial vehicles) remote sensing techniques. An interesting Synthetic Aperture
Radar (SAR) technique was developed for the breakup of ice covers along the Athabasca River in
Canada in the spring of 2018 [
25
] in which the quad-pol backscatter signal was decomposed into
different scattering components—surface, volume and double-bounce scattering—to differentiate
between intact and running ice.
It is recognized that ice jamming and flooding are processes with strong random components,
which inevitably require a probabilistic description of occurrence within a forecasting context.
The hydrological forecasting model that has been set up for the headwaters of the Oder River
would have to extend further downstream to provide discharge forecasts for the lower Oder River.
Revisit times of the satellite image acquisitions need to be more frequent in order for them to
be used operationally in an ice flood forecasting system. Using images from an array of sensors
(TerraSAR-X, RADARSAT-2, Sentinel-1, Sentinel-2, Cosmo SkyMed and potentially the upcoming
RADARSAT Constellation Mission (RCM)), along with cloud-free observations by optical sensors,
such as Sentinel-2 and Landsat, will help fill gaps so that an image can be made available at least once
per day for operational forecasting. A multi-scale earth observation framework was also discussed in
which space-borne observations would be used to create a large-scale overview and, subsequently,
the identified hotspots would be mapped in higher detail using UAVs or ice observers.
Author Contributions:
All authors contributed equally to discussions on the conceptualization of an ice jam flood
forecasting system for the Oder River. The initial text was drafted by K.-E.L. with all authors providing input and
amendments to the text. Z.W.K. provided final refinements to the manuscript.
Funding: The Wrocław workshop expenses were covered by funds from the Global Water Futures program and
hosted by the Global Institute for Water Security, University of Saskatchewan. The development of the HydroProg
system was financed by the National Science Centre of Poland (grant no. 2011/01/D/ST10/04171) and the
National Centre for Research and Development of Poland (grant no. TANGO1/267857/NCBR/2015).
Acknowledgments:
Special thanks to Kelly McShane (Financial Director) and Sherry Olauson (Administrative
Assistant), both at the Global Institute for Water Security, for their help in the organization of the workshop.
Conflicts of Interest: The authors declare no conflict of interest.
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2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
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