Hydrological Studies in the Danube Delta Part A

Hydrological Studies in the
Danube Delta
Part A
Aljosja Hooijer
December, 2002
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Hydrological Studies in the Danube Delta
Part A
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December, 2002
Contents
List of Tables and Figures
1
2
Introduction...........................................................................................................1–1
1.1
Background................................................................................................1–1
1.2
This report..................................................................................................1–1
1.3
Objectives and planning ............................................................................1–1
Study methods and results....................................................................................2–1
2.1
Key Concepts.............................................................................................2–1
2.2
Determining the possibility of plaur flow..................................................2–2
2.3
Water balances for lake systems: assessing flow through reedlands by
difference ...................................................................................................2–4
2.3.1
2.3.2
2.3.3
2.3.4
Measuring flow in channels..........................................................2–4
Determining lake water balances ..................................................2–5
Assessing reed flow by difference ................................................2–7
Observing flow through standing reed in the field: mainly
through 'micro-channels'...............................................................2–7
2.4
Assessing lake-lake and lake-river connectivity: water level monitoring
in lakes .......................................................................................................2–8
2.5
Water level monitoring in reed areas .........................................................2–9
2.6
Assessing source and residence time of lake water from Chloride
contents ....................................................................................................2–10
3
Main conclusions...................................................................................................3–1
4
Recommendations.................................................................................................4–1
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List of tables and figures
Figure 1 Some field observations (from top to bottom): .......................................................................2
Figure 2 Measurement locations in the Lake Isac system; hydrological field studies, June 2002.........3
Figure 3 Flow measurements in the Lake Isac system; hydrological field studies, June 2002..............3
Figure 4 Measurement locations in the Lake Isac system; hydrological field studies, September 2002.
...................................................................................................................................4
Figure 5 Flow measurements in the Lake Isac system; hydrological field studies, September 2002 ....4
Figure 6 Definition of the Isac lake system ...........................................................................................5
Figure 7 Comparison of measured and modelled flow rates, around the Isac lake System, 3-14 June
2002...........................................................................................................................6
Figure 8 Discharge measurements in the Lake Rosu system.................................................................7
Figure 9 Water level record for the northern edge of lake Isac, in channel Isac 2. ...............................8
Figure 10 Comparison of monitored water levels in Lake Isac with river water levels. .......................8
Figure 11 Left: Installing a 'diver' water level recorder in reedland. .....................................................9
Figure 12 Right: Locations of divers, installed 8 and 9 September 2002..............................................9
Table 1 The difficulty of defining 'lake systems' ...................................................................................5
Table 2 Comparison of measured and modelled flow rates (old situation) ...........................................6
Table 3 Historical information on flows in the Litcov-Isac system.......................................................7
Table 4 Chloride contents in the Lake Isac system, 4-12 June 2002 .....................................................7
Table 5 Location descriptions and installation/retrieval procedures for 'divers'....................................9
Table 6 Water balance for the lake Isac / Isacel / Gerasimova system, September 2002 ....................10
Table 7 Tentative water balance for the Perivolovka channel, September 2002 .................................11
Table 8 Provisional water balances for the Lake Isac system and subsystems, June 2002 .................12
Table 9 Proposed experiment to measure the internal water balance of reedland ...............................13
Table 10 Proposed experiment to estimate flow rates through reeed in a 2D model...........................14
ANNEX 1 - Discharge measurements during the June 2002 mission.
ANNEX 2 - Flow profiles during the September mission
ANNEX 3 - Diver location photos (for retrieval)
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Introduction
1.1
Background
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Since 1997, WL | Delft Hydraulics assists DDNI in developing a hydraulic model for the
Danube Delta, based on SOBEK. As water quality management is a crucial part of the
conservation and restoration of the Danube Delta ecological system, there is a need to
extend the hydraulic model towards a water quality model that takes into account
biochemical processes.
Before the Hydrological Studies of 2002, reported upon here, the hydraulic model could
only be calibrated using flows and water levels in the main Danube branches, as only little
data are available on flows and water levels within the lake complexes that form the Delta.
Also, no information was available on the hydrological interactions between the different
types of reservoirs within the Delta: open water bodies, standing reed swamps and floating
reed ‘plaur’ areas. For modelling of biochemical processes, these flows, levels and
interactions within the lake systems should be understood better, and used for further
development of the hydrological model. The 'hydrological studies' reported here aim to
assist in filling this gap in data and understanding.
1.2
This report
This is a mission report describing project activities - not a scientific report on the
hydrology of the Danube Delta. The two hydrological field missions reported upon here (in
June and September) were very distinct in character: outcomes from the first mission were
reported in June, as the basis for discussing goals for the second mission, as well as for
further development of the model. As the time available for reporting is very limited, this
Final Report consists of two progress reports that were merged - outcomes from the June
and September missions are reported separately in two blocks within each section. Frequent
reference is made in the text to location names - these can be found on the map in Figure 5.
1.3
Objectives and planning
Objectives of the field studies
The objectives stated in the Terms of Reference for the 2002 Hydrological Studies can be
summarised as:
•
•
•
WL | Delft Hydraulics
To determine if, and how, water flow under plaur occurs – focussing on the
Gorgova- Isac System.
To determine how these flows under plaur can be implemented in the existing
hydraulic model.
To report upon the above.
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The first field findings (and discussions with RIZA and DDNI colleagues during the field
visit) made clear that:
A) flow under plaur is possible, but
B) it is unlikely (and even impossible from a 'hydrological model' point of view) that this
flow component can be separated from flow through standing reed, while
C) quantification of net flow through any type of reed can only be quantified from the
overall water balance, not from direct measurements of 'reed flow'.
These early findings caused a change in the focus of the hydrological study: from looking at
‘plaur flow' only to analysing the entire hydrological system - including plaur flow. In
consultation with RIZA and DDNI colleagues, the tasks were soon rephrased to:
•
•
•
•
•
•
To determine if, and how, the process of water flow under plaur can occur.
To assess to what degree water flow under plaur and through standing reed is
actually likely form a significant component of the lake water balance - focussing
on the Isac-Uzlina, Gorgova-Potcoava, Gorgostel-Cuibul cu Lebede and Iacob-Rosu
lake systems.
To collect water flow- and level data that will allow calibration of the flows within
and between the lake systems – which has been limited so far, due to lack of data –
and to assist in setting up a field monitoring scheme that will enable DDNI in
collecting these data in the coming years.
To assist in determining if, and how, these flows under plaur and through standing
reed can be incorporated in the existing hydraulic model.
To assist in deciding how the model schematisation can give a realistic simulation
of water flows (and therefore biochemical processes) in the Isac-Uzlina, GorgovaPotcoava, Gorgostel-Cuibul cu Lebede and Iacob-Rosu lake systems.
To report upon the above.
The June and September field missions
Almost all the work within the hydrological studies took place in Romania: in the field and
in the DDNI office. Some field observations are shown in Figure 1. The main tasks during
both the June and the September missions were field surveys, data collection and data
analysis; not much literature research has been done. The conditions, during the two
missions were the following:
•
•
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In June, water levels in the Danube Delta system were more or less 'average', but
falling. Both intense rainstorms and strong winds occurred.
In September, water levels in the Danube Delta are usually low, and it was expected
that 'near-stagnant' conditions could be measured in this period. However, as a result
of the rain events that caused flooding in much of Central Europe, water levels were
actually very high (higher than they had been all year) and peaking. No rain
occurred during the fieldwork period, but wind activity was considerable.
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Objectives and approach of the two missions were:
June:
• The specific question regarding plaur flow (question 1 above) was answered in the first
days.
• Following that, in- and out-flows of a large number of lake systems
(Gorgova/Isac/Cuibul cu Lebede/Rosu/Puiu; see Figure 5 for map; Annex 1 for
measurements) were determined with rapid flow measurements (with relatively low
accuracy), to establish of the connectivity between lakes and channels, develop lake
water balances and to get an idea of the 'non-measured flows' i.e. the flows through reed
that can only be determined by difference. Flows in the Rosu-Puiu systems were as
determined (Figure 8).
• A single water level recorder ('diver') was installed in Lake Isac for retrieval in
September.
September:
• The water balance of a single lake system (Isac/Isacel/Gerasimova) was determined in far
greater detail, by measuring all in- and outflows through full cross sections, every day.
• divers were installed in different lakes, and 1 in a reed plain, to monitor water levels until
2003.
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Study methods and results
Several unorthodox study methods and experimental set-ups have been used during the field
missions. To understand the results, one must understand the method - therefore, the two are
presented together. Some key concepts in the following text are rather specific for this (type
of-) study and therefore need to be explained before describing the methods used.
2.1
Key Concepts
Lakes, lake systems and lake complexes
It is difficult to define a 'lake' in the Delta: open water bodies may be separated by ridges of
mineral soil, by extensive plains of reed, by mozaics of reed and smaller patches of open
water, or even by channels through reed. These are not always easily distinguished.
Moreover, the boundary types change with changing water levels. For the purpose of
determining a water balance, most inputs and outputs of water bodies must be through
channels - clearly, this requirement is rarely met for individual lakes. Therefore, an attempt
has been made to delineate 'lake systems' within which lakes are connected (for most of the
year), while they are clearly separated (for most of the year) from other lakes. The way this
is done for the Lake Isac System is illustrated in Figure 6 and Table 1.
It should be noted that the connectivity between lakes is only partly shaped by natural
processes - the effects of human activities may now be more important, in three ways:
•
•
•
Water flow between many water bodies has been increased by channels. The
intensive canalisation in the Delta has created ‘water highways’, reducing the need
for water transport through reedbeds.
Less obvious but as important is the effect of the embankments along channels,
which have compartemented the Delta and separated formerly connected water
bodies.
As connectivity is a function of water level, the changes in water levels caused by
embanking the main river channels, opening and closing connection channels
between the river and the lakes, as well as the changes in the river hydrograph itself
through river regulation and upstream land use changes, all have an effect on the
way water flows between lakes.
Note: where the text refers to a 'lake complex', a geographic area within the Delta is
indicated by the most prominent lake in it, without implying hydrological connectivity.
'Net flow' versus 'storage change flow'
There are two fundamentally different types of flow in a lake system:
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'Net flow' is part of the overall flow through the Delta, and will be in the direction of
the overall gradient. This flow component is expressed in the water balance of lake
systems and can be considered 'steady state': if we assume that storage does not
change, lake system inflow must equal outflow.
Superimposed in this flow component is 'storage change flow' (sometimes called
'pulse flow'). When a lake system fills up and water level rises, lake water will enter
the reedlands and smaller 'satellite' lakes within the system. When water levels fall,
the direction of this flow component will be reversed and 'reedwater' will enter the
lake. Though this flow component is not important to the water balance of the lake
system as a whole, it is very important to water quality in the lakes.
The discussions of flow rates in this report pertain only to net flows. The occurrence of
'storage change flow' is assumed, not measured. This flow component would have to be
separated from net flows in field observations, and this is only possible in a prolonged and
thorough field monitoring program. While such a study would be interesting, and possibly
useful if linked to water quality studies, it is not necessary from a hydrological point of
view: the fact that water flows in and out of reedlands when lake water levels go up and
down is obvious. The delay which this introduces in the response of the system is unknown,
but probably insignificant compared to the delays in channels between lake systems, and
therefore insignificant from a 'hydraulic model point of view'.
2.2
Determining the possibility of plaur flow
Before analysing the importance of plaur flow, it must first be determined whether such flow
is possible in the first place. This was done using two methods that allow direct point
measurement (i.e. at a certain moment and location) of the flow rate under the reed mat. It is
emphasised that such point measurements can only be indicative: they may be accurate, but
cannot be extrapolated to other points and moments, nor can they be translated into a
general 'plaur flow rate' that can be used in the water balance or the hydrological model.
Direct flow measurements under plaur
An Ott-Nautilus electromagnetic flow meter was used to directly measure flow under plaur.
To this aim, a hole was cut out in the floating reed mat with a 45-centimetre corer and the
depth of the reed mat and the lake bottom underneath was assessed - with rather limited
accuracy as a layer of almost fluid organic detritus is usually found (or suspected) under the
plaur. This method may result in an underestimation of the flow under plaur, as some peat
from the hole will inevitably drop under the plaur, obstructing flow.
Result: two successful experiments were carried out using this method.
1 . 4 June 2002. Along the southern edge of Pojarnia Lake (see map, Figure 5), the only
channel to a satellite lake was recently blocked with plaur. It was assumed that if any flow
occurred under plaur between the two lakes, it would be here. Plaur depth was 1.3 m and the
‘solid’ channel bottom 2.5 m, so a water column of 1.2 m was available for water flow – at
least in theory (the salt experiment suggested an ‘open’ water column of a few centimetres
only, see experiment B.1.). The flow meter recorded no water movement at this location.
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2 . 8 June 2002. Local experts reported that fishermen use the southward water movement
under the plaur ridge between the Lumina and Puiu lakes by setting nets on the outflow side,
on the south. Such flow was indeed found. Reference flow in a channel (8 m wide, 3 m
deep) 200 m W of the experiment location was 0.04 m/s. Plaur depth was 1.2 m and the
‘solid’ channel bottom 2.45 m, so a water column of 1.25 m was available for water flow. A
flow between 3 and 7 mm/s (with an average of 0.005 m/s) at this location, which indicates
that flow under the plaur forms a major water balance component at this location: over a
cross section of 1000 metres of uniform plaur, a throughflow of 6.25 m3/s would be
possible.
Flow assessments under plaur using a salt-solution tracer
Salt dispersion in water under plaur provides a ‘tracer’ for flow direction and flow rates. To
achieve a clear signal, a significant amount of salt (10 to 20 kilos, dissolved in local water)
was injected through a plastic pipe. The movement of hyper-saline water was then followed
using a ‘prikstok’ device (used by some Dutch soil scientists): an Electrical Conductivity
meter on a metal rod which penetrates through the plaur into the water underneath - while
‘normal’ EC is around 500, the saline water would give readings well into the thousands. EC
is measured in narrow circles around the injection point until a signal is picked up and the
direction of the saline flow plume is clear. After that, the ‘peak’ of the plume is followed for
several meters until a flow rate can be established.
Result: two successful experiments were carried out, at the same locations as the direct flow
measurements.
1 . 4 June 2002. Along the southern edge of Pojarnia Lake, it was first established that salt
water can indeed move under the plaur: the ‘salt peak’ moved by approximately 3 meters in
30 minutes. However, this flow was not due to a natural gradient but appeared to be caused
by 5 heavy researchers ‘squeezing’ water from the plaur by their weight (despite working
from a wooden platform), as the plaur was in fact lying on the substrate. This was concluded
from the following:
•
•
•
The main flow direction appeared towards the middle of the channel, not along it.
Saline water also moved in the opposite direction from the ‘main’ direction.
Water flow occurred only through a very thin zone (1-2 centimetres) under the plaur
– above and below this zone, EC remained natural. Interestingly, using a gauge it
was found that plaur depth was 1.3 m and the ‘solid’ channel bottom 2.5 m, so a
water column of 1.2 m should theoretically be available for water flow.
This lack of actual water flow at this location is consistent with the measurement using the
EM flow meter (see above). It is concluded that:
1. Water flow under plaur is possible, but will not naturally occur once the plaur rests on
the substrate, which is often the case - certainly at lower water levels.
2. In hydrological terms, the ‘substrate’ may not be the mineral lake bottom (as determined
with a soil auger) but the top of a layer of almost fluid organic detritus which precipitates
from the plaur and accumulates – especially when flow velocities are low.
3. The bottom-surface of the plaur appears to be quite sharply defined: otherwise a straight
horizontal contact zone of only 1-2 centimetres deep would not be possible. This may
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mean that the surface roughness under plaur is also limited – allowing significant flow
velocities, in theory, when water levels are higher and the plaur is floating.
2. 8 June 2002. Under the plaur ridge between Lumina and Puiu lakes, the salt-method
indicated a strong southward flow: in 2 minutes, the ‘salt peak’ had moved by over 60
centimetres. In fact, the flow was so fast that after this measurement the ‘pocket’ of saline
water, moving under the plaur, was lost and could not be located anymore. If we assume a
flow velocity of 100 cm in 2 minutes, or 8 mm/s, this would be even higher than the result
as found using the EM flow meter (see above), but it is encouraging that the two methods
can give consistent results.
At this location, the depth of the open water column where saline water could be found was
over 30 centimetres; the EC device would not penetrate deeper than this. This may indicate
that no detritus layer is formed under plaur when flow velocities are this high.
2.3
Water balances for lake systems: assessing flow through
reedlands by difference
The idea behind determining water balances for lake systems was:
1. While most flow occurs through canals and can be measured, flow through reedlands
may also be an important water balance component; this flow can not be measured
directly but can be estimated ‘by difference’ from the water balance.
2. The flow measurements needed to determine water balances were also needed for
calibration and further development of the hydraulic model. If an estimate of nonmeasured flows is possible, the water balance can also serve as a double-check for the
accuracy of measurements: if a major measurement error is made, or an important
in/outflow channel overlooked, the water balance will not add up.
Only partial water balances were possible in this study, as no accurate evaporation of
rainfall data were available for the study period.
2.3.1 Measuring flow in channels
June
Flows were measured repeatedly (with an Ott-Nautilus electromagnetic flow meter) at a
large number of locations (Annex 1), in all channels in the Isac / Cuibul cu Lebede /
Gorgova lake systems (Figure 2, 3), as well as in the Rosu /Puiu systems (Figure 8). The
velocity measurements were part of a rapid assessment program and therefore approximate.
However, they are estimated to be accurate within 25% in most cases (on the basis of
comparisons of measurements at different moments, and on the basis of the water balance
results; see below):
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In order to minimise flow variation across the channel, all measurements were taken
at straight channel sections, well away from tributaries, with little floating or
submerged vegetation along the sides (unless indicated otherwise) and preferably
with good tree shelter (on windy days). Due to regular dredging, most channel cross
sections are quite uniform and very suitable for flow measurements: most are
between 10 and 30 metres in width and 2 to 3 metres deep, with relatively little
depth variation across or along it.
The narrow (in order to minimise flow obstruction) working-boat was stabilised
(with sticks and ropes) at a point about 1-third from the channel-side, and the
electromagnetic sensor (Ott Nautilus) was placed upstream of the bow, 1 metre from
the channel bottom (independent of channel depth). The average flow velocity over
5 seconds was measured 5 times, and averaged again. Flow velocities were
generally rather uniform across channels, but where this was not the case a second
measurement was made one-quarter from the opposite side of the channel and the
two measurements were averaged again.
September
The flow measurements in September ware far more accurate, but also far more labour
intensive, than those in June, because A) better equipment was used to stabilise the sensor,
B) the boat was this time stabilised in the stream by ropes to the sides as well as sticks to the
channel bottom, C) the channel cross sections were measured accurately at 2 m intervals
across, or less and D) multiple measurements were made at different depths and across the
channel. The measurement error is estimated to be well within 10%, on the basis of
comparison of repeated measurements, using both the Ott-Nautilus electromagnetic flow
meter and a conventional backup 'propeller' flow meter.
As these measurements were repeated several times (every day in some cases) at each
location around the Isac/Isacel/Gerasimova system (Figure 4, 5; Annex 2), it was possible to
get an accurate record of total inflow as and outflows to the system, over a week.
2.3.2 Determining lake water balances
June
In Table 8, a series of water balances for ‘sub-systems’ is presented for June. As the flow
measurements in these period were not highly accurate, they can not be used to determine
flows through reed by difference - this flow component is of the same order as the
measurement error. However, the water balance shows that the difference between surface
water inflows and outflows is not too large to be explained by measurement errors and other
uncertainties listed below - also considering the consistency between repeated
measurements at the same location (see Table 8). This has two implications:
•
•
June measurements are accurate enough to be used for calibration of the model.
The unknown 'reed-flow' water balance component may not be a major water
balance component.
The fact that at the outlet in of the Eastern Litcov channel into the Crisan channel there is an
‘outflow deficit’ of 36% (or 6,3 m3/s) may be due to the following:
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The lake system may not actually be in steady state during the study period, i.e.
inflows have significantly exceeded outflows and the storage has been increasing.
Figure 9 shows that water levels in Lake Isac have indeed risen by 1 or 2
centimetres in the last seven days of the mission, when flow measurements were
made. This may not seem much, but assuming a ‘contributing surface area’ of 120
km2 for the Isac- Perivolovka system (S of the Litcov channel) an average rise by 2
mm/day would be equivalent to a ‘lost outflow’ of 2,8 m3/s – explaining almost half
of the outflow deficit. This also indicates that, considering the limited throughflow
rates in the system (after closing the Uzlina and Litcov E inflow channels), local
inputs and outputs due to rainfall and evapotranspiration are important water
balance components which should ideally be included in the model.
An even larger part of the ‘lost outflow’ may be explained by evapotranspiration,
that is likely to have been around 4 mm/d during the study period, as water
availability was not a limiting factor, and there were many sunny and windy days.
Following the above calculation, this could potentially reduce outflow by 5.6 m3/s.
However, this output may partly be balanced by rainfall inputs. Ideally, this should
be checked with weather data, but it was not possible to obtain such data in time.
There are ‘diffuse’ outflows through reedlands and open water to the north of the
Eastern Litcov channel (east of Perivolovka channel), which could not be measured.
Finally, a similar ‘outflow deficit’ of 22% along the Western Litcov channel (West
of Perivolovka) was attributed to acceptable measurement errors (partly caused by
the fact that measurements were made on different days) – this channel is confined
by ‘embankments’ of dredging material along its entire length and there it is not
likely that major ‘unmeasured’ outflows occur. A similar error is also possible in the
Eastern Litcov channel.
September
In Table 6, the water balance for the Lake Isac system (Isac/Isacel/Gerasimova) is presented,
as determined over 4-11 September 2002. A tentative balance for the Perivolovka channel is
also given , in Table 7. Apart from the far more accurate measurements during this period,
there are several other reasons to believe that this water balance is far more accurate than the
one established:
•
•
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The fieldwork period exactly (and very luckily) covered the peak of a high-water
event. The water level in Lake Isac was the same on the first and last day; after
having risen and fallen by 4 cm in between (Table 6, Figure 9, Figure 10). As a
result, flow conditions approach a steady state: it can be assumed that surface water
inflows equalled outflows over the study period, and no allowances have to be made
for changes in storage.
Measurements were repeated several times. In the case of the channel Isac III to the
SE of lake Isac, for example, flows are highly variable (mainly due to variations in
wind directions and strength) and only an average over multiple measurements has
some validity. From the measurements in Channel Isac II (to the NE) it can be seen
that variations show a trend: outflow from lake Isac increased when water levels
first stabilised, then started falling towards the end of the fieldwork period.
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The way in which the separate lakes were combined into 'the Lake Isac system'
differed from the way this was done during the first mission, on the basis of
improved understanding of the connectivity between lakes. Such a system is defined
here as the combination of lakes which allows all inflows to be measured in
channels.
2.3.3 Assessing reed flow by difference
From the descriptions of measurements and water balance analyses above, it will be clear
that error margins in June were far greater than in September. Therefore, the assessment of
the amount of flow through reed will also be far more accurate for September. In Table 6, it
is shown that in September 1.4 m3/s of outflow from the Lake Isac System occurs through
the reedlands to the east. This would be 17.4% of total outflow. Considering the fact that
water levels were very high during the study period, this figure may be close to the
maximum. This is confirmed by doing the same calculation using the June data, which yield
a figure of only 1.3%. It should be kept in mind that there are uncertainties in both
calculations, but that the error margin for the June calculation is especially large.
Nevertheless, it can be concluded that outflow through reedland is only a minor component
of the water balance of the Lake Isac System, and that the connections between lakes and
lake systems are well represented by channels in the hydraulic model - additional channels
to represent flow through reedland are not needed.
2.3.4 Observing flow through standing reed in the field: mainly through
'micro-channels'
During the September mission, several attempts were made to directly measure flow rates
within the flooded reed area between Lake Isac and Lake Gerasimova, as well as between
Lake Gerasimova and Channel Perivolovka. This was done using sawdust as a 'visual
tracer', on different days and early in the morning, when there was no wind. On all 4
locations, no movement was observed after 5 minutes - only unstable random movements of
a few cm at most.
In Table 6, it is estimated that, if 17% of the outflow from the Lake Isac System is through
the reedland to the east, and this flow would be evenly distributed over a cross-section of 5
km wide and 0.5 m deep, flow velocity would be in the order of 0.6 mm/s. Insignificant as
this may seem, it would still add up to 18 cm over 5 minutes. There are two ways to explain
this:
•
•
even this low proportion of lake system outflow occurring through reedland may be
an overestimation, or
this flow through reedland occurs very unevenly distributed, mainly through a few
preferential pathways: probably narrow channels kept open by local fisherman.
An argument for the latter explanation is that outflow from the Lake Isac System was indeed
observed in two channels of 2 and 3 metres wide, to the west of channel Perivolovka (Figure
5). The flow in this channels (0.36 plus 0.21 m3/s) forms already 40% of total calculated
outflow (1.4 m3/s) and it is not hard to imagine that there may be more such channels that
are harder to find.
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Part A
2.4
Q3230
December, 2002
Assessing lake-lake and lake-river connectivity: water level
monitoring in lakes
From the June 2002 study period onwards, water levels were monitored continuously (at 1hour intervals) using a ‘diver’ recorder in the NE of Lake Isac, at the entrance of Channel
Isac 2. In addition to this, 4 more recorders were placed on September 8 and 9 at the
Gorgostel inlet, the Gorgova outlet, the Uzlina outlet and in the reed N of Lake Isac. Further
details are given in Table 3. Results for the latter 4 recorders will only be available by spring
2003. Here, preliminary results based on a single recorder are presented.
While results for a single recorder do not allow full analysis of connectivities between lakes
and river branches, the following observations can be made at this point:
•
•
•
A graph of hourly water level measurements for the summer of 2002 (Figure 9)
shows that the water table fluctuates relatively 'smoothly' for most of the time,
rarely changing by more than 1 or 2 centimetres in a day - including 'noise' caused
by waves and wind activity. On a few occasions however (e.g. around June 15 and
August 5) there are sudden 'jumps' in water level by some 5 centimetres, followed
by a gradual decline. It seems logical to attribute these jumps to heavy rainstorms,
in the order of 50 mm/day.
Comparison of Isac water levels with those in the Sulina and Sf. Gheorge Danube
branches (at the entrances of the Perivolovka and Crisan channels; the 'outflow
pints' of the lake complex around Isac) during the August 2002 high-water event
shows that:
— The response in lake levels is delayed (more then the 3 days lag-time between
Tulcea and the river branches N and S of Isac) but especially greatly weakened,
indicating a limited connectivity between lakes and river branches - certainly
after closing several channels.
— The lake water level is closer to the level in the Sulina branch than in the Sf.
Gheorge branch, suggesting that connectivity to the Sf. Gheorge branch is
lower. As the only supply of river water to these lakes is from Sf. Gheorge
through the Litcov channel, this means that the discharge capacity in the Litcov
channel (upstream of lake Gorgova) must be very limited.
During the fieldwork period of September 4-11, water levels in the lake were stable
while those in the Danube branches were falling rapidly. This confirms the
observation that discharges from the system were increasing throughout the period
(Table 6).
The following can be concluded at this stage:
•
WL | Delft Hydraulics
The closure of the 2 channels between Sf. Gheorge and the lakes (to Lake Uzlina
and to the Litcov channel near Lake Gorgova) has strongly reduced the connectivity
between the Danube and the lakes. The large difference between the water levels
(0.6 m on September 7) on the river- and lake-sides of the Uzlina blockage indicates
that lake levels would have been controlled largely by river levels if this connection
had been open. The huge inflow (tens of m3/s) measured in the past years in the
now-blocked channels when they were still open, compared to the 1 m3/s now
passing the Uzlina dam, confirms this (Table 3).
2–8
Hydrological Studies in the Danube Delta
Part A
•
•
Q3230
December, 2002
It appears that over short time periods the impact of the river level on the water
level in the lake is relatively minor compared to the local effects of rainfall,
evaporation and wind. This should be taken into account during future field studies
over such short time periods.
The decreased connectivity has increased the relative importance of local rainfall
and evapotranspiration - for the hydrology and for water quality.
In other words: closing the connection channels between river and lakes not only changes
throughflow and water quality but also water level regime – making the lakes far less
dynamic in general. As the Uzlina-dam was already partly re-opened (by the local
population) in September, after only a few months service, it can be assumed that this
channel will be opened further, if only by natural erosion, if nothing is done about it. This
will again change the hydrological dynamics of the lakes. The question is whether such
repeated changes in lake dynamics are beneficial.
2.5
Water level monitoring in reed areas
The close association of plaur, standing reed areas and patches of open water, combined
with the occurrence of water flow through these area – evident both from the observation of
‘outflow areas’ along channels and from the water balance for the lake systems – leads to
the conclusion that water can flow through these reed areas by three or four pathways: under
plaur, through standing reed, through open water and possibly even through the peat itself,
when lake water levels drop below the level of the peat surface.
In Table 9, an experiment is described which would allow the analysis of the water balance
of reedlands throughout the year. This experiment could not be carried out in 2002, for
logistical reasons and because the required large expanse of uniform standing reed was not
found. Instead, a single 'diver' water logger was placed in a reed area, as far away from Lake
Isac as possible (see Figure 12; Table 5). The diver was placed in a hole dug in the soil,
some 20 cm below the surface. Comparison of this record with that obtained in Lake Isac
will provide insight in the way water levels in the reedland response to a 'flood pulse' in the
Delta. When installed, during high water on September 9, water levels in the reedland were
some 50 cm above the soil surface (see photo Figure 11). The water level is therefore
expected to be at or below the soil level for most of the year and the water level will be
monitored in three situations:
1. As long as the water table is well above the soil surface, the surface water interaction
between lake and reedland is monitored. This should provide valuable information on
the hydraulic roughness in reedlands, which can be used in the model.
2. When the water table is near (above or below) the soil surface, there will be a limited
connectivity with the lake. If lake water levels are plotted against reedland water levels,
it will be interesting to see if there is a sharp breaking point where this connectivity is
lost.
3. When connectivity with lake surface water is lost, water levels in the reedland respond
only to local inputs and outputs: useful techniques exist which allow determination of
actual evapotranspiration rates in wetlands using the diurnal water table records in dry
periods, while the storage coefficient of the soil can be determined from the response to
rainstorms.
WL | Delft Hydraulics
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Hydrological Studies in the Danube Delta
Part A
Q3230
December, 2002
With high water levels, it may also be possible to analyse the effect of wind activity on
water storage in reed. It was found that winds can be strong in the Delta, and it is suspected
this constant in- and outflow (even when lake levels are relatively constant) may enhance
the water exchange between lake and reed, and may therefore be important to water quality.
However, it is not sure whether the accurate wind data that are required for this analysis are
available.
Note: the diver is placed quite close to the surface, in a hole that should be water-filled even
when the reedland is not flooded. This means that the sensor temperature may fall below
zero during prolonged freezing conditions. It should be made sure that A) the monitoring
data are not lost from the memory during such conditions, or that B) the diver is removed
before such conditions start.
2.6
Assessing source and residence time of lake water from
Chloride contents
Because chloride is considered a 'conservative' ion - its concentration only affected by
dilution and concentration - it is often used as a tracer in hydrological studies. In wetland
hydrology, this tracer is often used to 'map' stagnant parts (where salt accumulates due to
evapotranspiration), identify relative inputs of river water versus rainwater, and determine
mixing rates between lakes. To find out if this could also be done in the Danube Delta, 16
samples from different types of locations around Lake Isac were compared. The analysis
results presented in Table 4 show that chloride contents in most lakes are quite uniform,
between 0.2 and 0.3 mg/l. However, they appear lower around the L. Gorgova lake system
(samples 12-13), presumably due to relatively high fraction of rainwater inputs (i.e. lower
river water inputs), while a higher concentration was found in water taken from under plaur
(sample 16), possibly indicating stagnant conditions. Somewhat unexpectedly, the water in
C. Litcov, which largely originates from the river, does not have high chloride contents
(sample 14).
It is concluded that in this case, when water levels and throughflow rates are high, and after
a winter/spring period of low evapotranspiration, chloride is not a good tracer in these lakes.
However, it is worth trying to use the method when water levels are low, and after a period
of high evapotranspiration - by late summer. It is recommended that chloride contents are
determined systematically in water samples analysed in the DDNI laboratory, in order to
build up a database that allows analysis of temporal and spatial patterns in chloride
content.
WL | Delft Hydraulics
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Hydrological Studies in the Danube Delta
Part A
3
Q3230
December, 2002
Main conclusions
Flow under plaur is possible, but not an important water balance
component
It has been shown that an open-water column can exist under plaur, and that this allows flow
in particular conditions. However, the flow measurements in channels and findings of the
water balance show that only a small part of the net flow across lake systems is through
reed, and only part is that through plaur. Therefore, flow under plaur is not likely to be a
significant component of the water balance of lake systems. Field surveys and discussions
with DDNI confirm that net flow under plaur can occur at high rates (see the results of the
flow measurements), but it also seems clear that this only happens in a few places –
especially under narrow ridges of plaur between two lakes with a significant water level
difference. In most places, flow under plaur is limited, for the following reasons:
•
•
•
•
•
WL | Delft Hydraulics
Large expanses of solid, uninterrupted plaur are rare – in fact, they could not be
identified in the Isac lake system, during the field surveys. Instead, there is a mosaic
of plaur, standing reed and open water. This means there are many blockages for
uninterrupted flow under plaur over long distances, but also that there are many
opportunities for flow through open water bodies (‘creeks’ or 'rivulets') in the
standing reed, between open water bodies.
Most plaur is not floating on deep open water. Comparison between the bathymetric
and vegetation maps shows a close relation between plaur distribution and the
occurrence of shallow lake soils between and along lakes. The water column under
the plaur is therefore not as deep as when it would be located over deeper water
bodies. Also, this observation indicates that the plaur is not uniformly free-floating
– it must clearly be ‘anchored’ to the lake bottom (possibly through patches of
standing reed), or it would simply float away with high water levels.
Build-up of a layer of organic detritus below the reed mat is common, and is likely
to prevent flow under most conditions. A significant depth of open water under
plaur is found only during high water, except from a few locations where permanent
flow removes detritus under narrow 'plaur ridges between lake, as in the case of the
plaur between Rosu and Puiu described above.
The intensive canalisation in the Delta has not only created ‘water highways’,
reducing the need for water transport through reedbeds, but has also created
embankments where dredging material is deposited along channels, which in many
cases block flow across channels, from and to reedbeds.
Also, water flows under plaur will be strongest when water levels are highest, in
early spring, while the most important time for hydrological water quality processes
may be in summer, when water levels are lower.
3–1
Hydrological Studies in the Danube Delta
Part A
Q3230
December, 2002
Flow through reedlands is not a major water balance component
At least in the case of the Lake Isac System, at most 17% of outflow occurs through
reedland. This was determined during the high-water period of September 2002. When
water levels are lower, this flow component will be even smaller - a tentative figure of 1.3%
was found for June. This means that the connections between lakes and lake systems are
well represented by channels in the hydraulic model - additional channels to represent flow
through reedland are not needed.
It should be kept in mind that human activities - especially the building of channels and
embankments along them - have completely altered the connectivity and hydrology of the
lake systems, and reduced the amount of flow through reedlands. There are indications that
flow through reedland is far more important in situations that are more 'natural': where lakes
are separated by 'open' reedland and not connected by channels. Examples are the
connection between L. Isacel and L. Isac, and between L. Chiril and L. Cuibul cu Lebede.
An implication of the currently very 'unnatural' situation is that nature restoration can not be
based on the assumption that the original hydrology can be restored - but this discussion
goes beyond the scope of this study.
Comparison of field measurements and model results
In Table 2, the field flow measurements during June are compared with model results at that
time - the channels from Sf. Gheorge to Uzlina and to Litcov near Gorgova were already
closed in the schematisation, as in reality. It can be seen that there were large differences
between observed and modelled flows. From Figure 7 it is clear that in some cases also the
direction of modelled flows differed from observed directions, and that a few important
connections were missing in the model.
At the time of finishing this report (November 2002), the model has been developed further
- modelled flow rates are now close to observed rates. Further model improvement will be
possible when water level records from the divers that were installed in September become
available.
One conclusion from this comparison is the confirmation of the need for data collection for
model development. This is not surprising to anyone, yet data collection is too often
forgotten too long in this type of study, and it is important that collection of hydrological
data continues in the Danube Delta. To know what further data will be needed, an idea is
needed of the precise objectives for the model. For instance, the improvements in modelled
discharges between June and November 2002 were partly achieved by increasing the
hydraulic roughness in lakes. This may be fine if the model is used to model flows and
travel times in the current situation. However, if the aim would be to also predict water level
fluctuations (e.g. for analysis of bird breeding areas), or to be able to predict the
hydrological effects of changes to the system (e.g. scenario studies for opening and closing
channels), it should be made sure that roughness in the model indeed reflects the physical
reality.
WL | Delft Hydraulics
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Hydrological Studies in the Danube Delta
Part A
Q3230
December, 2002
It is likely that the water level information now collected by 5 divers around lake Isac will
allow further improvement of the model to the stage where water level predictions and
scenario studies in the Isac complex become possible. However, it is expected that model
refinement will be a continuous process and that further data will be needed.
WL | Delft Hydraulics
3–3
Hydrological Studies in the Danube Delta
Part A
4
Q3230
December, 2002
Recommendations
Some recommendations made during the field missions, on model development and the
need to monitor water levels in lakes, have now been implemented:
•
•
•
Recalibration of the model using flow measurements.
Inclusion of evapotranspiration and rainfall in the model.
Monitoring of water levels in lakes for further calibration.
In order to make full use of the water level information from the divers, it is necessary to
determine the absolute water level at each diver location. This may require a rather complex
topographic survey as there are only few reliable benchmarks. Over such large distances, it
is not an option to simply assume that 'the water surface is horizontal' and link diver records
to this water level - this would result in there being no gradient in the modelled Isac lake
complex. In discussions at DDNI, it was agreed that it may be a good idea to carry out the
topographic survey at a time when channels and lakes are frozen and can be walked on.
Further work needed on model development and hydrological studies depends on the needs
of DDNI and other researchers. The model can be further refined to the stage where water
quality predictions and water level predictions in the entire Delta have a high level of
accuracy and detail, but the question of purpose should first be answered. Therefore, only
tentative further recommendations can be given at this stage:
•
•
•
•
WL | Delft Hydraulics
It is recommended to collect information on flows and water levels, similar to the
data collected in the Isac complex, for the rest of the Delta if the model is to be used
for management decisions.
Apart from the intensive monitoring campaigns aiming to determine the water
balance for a system at one time, it would be helpful to make regular (e.g. 3monthly) flow measurements at selected locations along the main channels within
the lake complexes (such as Litcov and Perivolovka).
If further research into lake-water interactions is needed, it could be helpful to
simulate specific cases in a 2-dimensional model (as in Delft FLS or Delft 1D2D). A
tentative idea for a simple simulation is suggested in Table 10.
For some applications it may be considered to further develop the model so as to
better simulate the different connectivities at different water levels. Maybe there
could be 3 water level stages in the model, characterised by different hydrological
connectivities:
— high water levels: full connectivity between lakes and river.
— low water levels: connectivity only through channels.
— intermediate water levels: transition stage where an increasing part of the flow
occurs through reedbeds, with increasing water levels. It is hoped that the
current hydrological studies will result in a tentative relation between water
level and the proportion of flow going through reedbeds, which can be used in
the model. However, measurements at higher water levels will be needed to
finalise this relation.
4–1
Hydrological Studies in the Danube Delta
Part A
•
•
WL | Delft Hydraulics
Q3230
December, 2002
For further model development and future hydrological studies, it would be useful
to set up a systematic database of data relevant to future hydrological studies - of
the type that is offered by HYMOS at WL | Delft Hydraulics. This could include also
topographic data (elevations of reference locations), channel descriptions, weather
data (rain, evaporation, wind) and water quality data. A database not only gives
access to data collected over a long period, but also allows easy interpretation and
standardised quality control.
Once sufficient data have been collected, other lake complexes could be analysed as
we have now done for the Lake Isac complex.
4–2
Hydrology and Water Quality
Modelling in the Danube Delta
Part B
Ronald Bakkum
December 2002
Q3230
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Contents
1
2
3
4
5
Introduction...........................................................................................................1–1
1.1
Background................................................................................................1–1
1.2
Objectives ..................................................................................................1–2
1.3
This report..................................................................................................1–2
Hydrology / SOBEK-CF.......................................................................................2–1
2.1
Introduction................................................................................................2–1
2.2
Model outline.............................................................................................2–2
2.3
Meteorology data .......................................................................................2–3
2.4
Calibration and results ...............................................................................2–6
Eutrofication (DANUBS)......................................................................................3–1
3.1
Main characteristics (changes)...................................................................3–1
3.2
Some results...............................................................................................3–3
Eutrofication (BLOOM).......................................................................................4–1
4.1
Introduction................................................................................................4–1
4.2
Required input ...........................................................................................4–1
4.3
Some results.............................................................................................4–10
Conclusions and recommendations .....................................................................5–1
5.1
Conclusions................................................................................................5–1
5.2
Recommendations......................................................................................5–2
Appendices
A000
WL | Delft Hydraulics
Update of DANUBS module description........................................................... A–1
i
Hydrology and Water Quality Modelling in the Danube Delta
Part B
B000
WL | Delft Hydraulics
Q3230
December, 2002
BLOOM subset details ....................................................................................... B–1
ii
Hydrology and Water Quality Modelling in the Danube Delta
Part B
1
Introduction
1.1
Background
Q3230
December, 2002
Since 1997, WL | Delft Hydraulics assists DDNI in developing a hydraulic model for the
Danube Delta, using SOBEK. As water quality management is a crucial part of the
conservation and restoration of the Danube Delta ecological system, in 2001 a beginning
was made in extending the hydraulic model towards a water quality model that takes into
account biochemical processes. During a six-week mission of Ronald Bakkum in autumn
2001, a successful first step in the extension was made in close collaboration with Adrian
Constantinescu. At the end of the mission the water quality model had been incorporated
and three different modules had been developed; DANUBS, for predicting nutrient removal in
the Delta on a coarse scale, SEDIMENT, for examination of sedimentation zones and DDNIEUTRO, for studying eutrofication phenomena in more detail.
By then the hydraulic model had been calibrated mainly using flows and water levels in the
main Danube branches, as only little data were available on flows and water levels within
the lake complexes that form the Delta. Moreover, no information was available on the
hydrological interactions between the different types of reservoirs within the Delta: open
water bodies, standing reed swamps and floating reed ‘plaur’ areas. For appropriate
modelling these flows, levels and interactions within the lake systems had to be understood
better, both for further development of the hydrological model as well as the modelling of
biochemical processes. To be able to make a distinction in biochemical processes in reed
beds and open water bodies it was necessary to separate both parts in the hydrological
model. In 2001 the model had been calibrated (or fitted) using nutrient removal coefficients
for each complex based upon weight factors between open water and reed beds of each of
the complexes and depending on a function based upon the water level at Tulcea. Finally it
was claimed, both from a hydrological as a water quality point of view, that meteorological
conditions as wind, precipitation and evaporation play a significant role in the dry period
and should not be ignored in the model.
In 2002 two field visits were paid to the Delta to focus on analysing the entire hydrological
system, and how it compares with the model outcomes. The results of these field visits are
described in part A. The objectives were to determine if and how water flow under plaur can
occur and to what degree water flow under plaur and through standing reed is actually
likely form a significant component of the lake water balance. During these visits he
focused upon the Isac-Uzlina, Gorgova-Potcoava, Gorgostel-Cuibul cu Lebede and IacobRosu lake systems.
Based upon the findings of the hydrological survey and the needs claimed in 2001, Adrian
Constantinescu collected meteorological data and prepared a new model schematisation this
summer, in which reed beds are separated from open water bodies.
All of this formed the starting point for the autumn 2002 hydrological and water quality
modelling mission.
WL | Delft Hydraulics
1–1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
1.2
Q3230
December, 2002
Objectives
The objectives stated in the Terms of Reference for the 2002 hydrological and water quality
modelling mission can be summarised as:
1.
3.
Hydrology; adapt in close cooperation with Adrian the outline of the model (i.e. (1)
separation of reed beds and open water and (2) introduce precipitation and
evaporation) and calibrate the hydrology using data gathered by data loggers and
the field trips.
Update and improve the water quality model regarding eutrofication by introducing
the BLOOM component. This task has been split into:
•
adapting the existing DANUBS module to the new model outline, redefining
the process formulations for reed beds, implement recent monitoring results,
calibrate the DANUBS module again, and finally
•
redefinition and calibration of DDNI-EUTRO by replacing the algae by
BLOOM processes and introduction of a sediment layer and accompanying
processes.
To report upon the above.
1.3
This report
2.
This report presents the results and preliminary conclusions of the work performed during
the period September-October 2002. This report is NOT a calibration report of a model
application. In stead of this, it contains technical support information for its potential users.
The changes in the model outline, meteorology data and the calibration of the hydrology
model are briefly described in chapter 2. In chapter 3 the recalibrated DANUBS, simple
eutrofication model is discussed. Based upon this work the model has been extended (on
request) with a different more complex algae bloom module and sediment layer. A technical
description of this so-called DDNI-BLOOM module is described in chapter 4, followed by the
main conclusions and recommendations, which can be made at this stage.
WL | Delft Hydraulics
1–2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
2
Hydrology / SOBEK-CF
2.1
Introduction
December, 2002
Based upon the field measurements of June 2002 it was concluded that there are large
differences between field measurements and model results. This in fact was true, but we
have to keep in mind that flow measurements had never be done before in the Delta. The
calibration of the Delta was only based upon limited monitored water levels. The challenge
now was to benefit from the availability of field data and the new insights.
In the June mission report two tentative recommendations for improving the model were
made:
1. A way should be found to simulate the situation with high water levels, when lakes are
connected to the degree it is effectively a single body of water and water levels are
practically equal to those in the main river branches. Maybe there should be 3 water
level stages in the model, characterised by different hydrological connectivity’s:
• high water levels: full connectivity between lakes and river.
• low water levels: connectivity only through channels.
• intermediate water levels: transition stage where an increasing part of the flow
occurs through reed beds, with increasing water levels.
2. When water levels are intermediate and low, local rainfall and evapotranspiration form a
significant part of the water balance of many lakes. In the 2001 version of the model it
is impossible to truly represent the hydrological functioning of the lakes, because the
full water balance is not included.
With respect to the 3 connectivity layers, it does not make sense to use a 1-dimensional
model for the really high water levels in the Delta. It is just out of range of the model, which
already was known on the forehand. Maybe SOBEK1D2D can play a role with respect to
flooding in future, but for the moment it is suggested to be familiar with the fact this
hydrological model is not suitable for predicting the conditions in the Delta during flood
periods. Therefore also in the present updated model outline the first connectivity layer has
been neglected.
During the second hydrology mission, water balances proved that reed bed flow is from a
water balance point of view not significant during low water and probably will play only a
modest role during intermediate conditions. Which means, with respect to the model outline,
it could be sufficient to use a connectivity outline in which flow between the different lakes
only occurs via channels. Within the lakes itself a separation has been introduced between
open water and reed bed parts. So within lakes now it is possible to study on the exchange
of water in between open water and reed. The separation between water and reed has been
created based upon surface areas and cross sections. At present the model itself has not been
calibrated on these specific flows. In the next section the model outline will be discussed in
more detail.
WL | Delft Hydraulics
2–1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
With respect to the recommendation introducing evaporation and precipitation within the
model it can be stated this has been done. Further reference is made to the section
“meteorological data”.
2.2
Model outline
With respect to the models outline, as created in 2001, it has been changed in two ways:
1. Distinction in open water and reed bed parts: physical and chemobiological processes
are totally different in reed beds in comparison with open water. As stated in October
2001 for the purpose of water quality modelling it was necessary to make a distinction
in the model between open water and reed bed area’s (plaur plus standing reed). Of
secondary importance it is to make a further distinction between standing reed beds and
plaur. In the new outline the distinction between open water and reed beds has been
implemented for all areas.
2. Implementation of precipitation and evaporation: this has been done by definition of
lateral discharges on branches, which refer to a meteorological database. Also a
distinction has been made between precipitation and evaporation in reed bed parts and
the open water.
The new outline principle is shown in figure 2.1.
2001
2002
Figure 2.1
WL | Delft Hydraulics
Modelling principle for reed beds versus open water and evaporation and precipitation
2–2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
2.3
Q3230
December, 2002
Meteorology data
In order to assess the relative importance of local rainfall and evapotranspiration within the
water balance, it was necessary to collect data or make assumptions. With respect to the
water quality model also data on surface water temperature and effective radiance have been
collected. In table 2-1 the long term monthly average values of these data are presented.
Table 2-1
Long term monthly average meteorological date for the Delta
Month
Precipitation
1
2
3
4
5
6
7
8
9
10
11
12
[mm/day]
1.2
1
1
1.2
1.5
1.8
1.5
1.2
1.2
1
1.2
1.2
Evaporation
literature
[mm/day]
0
0
-2.26
-3.27
-4.97
-7
-8.58
-7.58
-6.53
-3.61
-1.87
0
Evaporation
Open water
[mm/day]
0
0
-1.63
-2.35
-3.58
-5.04
-6.18
-5.46
-4.70
-2.60
-1.35
0
Evaporation
reed
[mm/day]
0
0
-2.51
-3.63
-5.52
-7.77
-9.52
-8.41
-7.25
-4.01
-2.08
0
Temp
[Celsius]
1.1
2.5
7.0
10.3
17.2
22.8
25.4
25.2
20.5
16.0
9.1
3.9
Effective
radiance
[W/m2.day]
24
37
64
92
106
115
123
102
71
36
26
18
The precipitation data used by the model originate from Gorgova and Tulcea meteorological
stations; these data consist of monthly precipitation amounts for each year. The Evaporation
data used are taken from DDNI projects based on Gorgova and Tulcea meteorological
stations data and “The monograph of the Danube Delta reed” by L.Rudescu, 1965,
especially for deducing the balance between evapotranspiration from water surface and reed
surface. Because these data are the total evaporation for the Delta it is subdivided into
evaporation from open water and evaporation from reed bed areas. This has been done using
a:
•
•
weight factor of 1.54 for the conversion of evaporation from open water to reed
beds and
total Delta area average weight factor for the area proportion distribution; 30% open
water, 70% reed beds.
In figure 2.2 and 2.3 the evaporation and precipitation model data for the year 2000 are
shown. Also the figures for Schiphol, The Netherlands, are shown as a reference. As can be
seen the evaporation in the Delta is lower in winter and higher in summer and autumn, as
could be expected. Evaporation in reed beds reaches values up to a maximum of 10 mm/day
in July. With an area cover of 70% reed in the Delta, this is an amount, which can not be
ignored in the water balance. Especially not during low water periods with a rather stable
water level.
WL | Delft Hydraulics
2–3
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
0.0
20.0
P_Sc hiphol
18.0
-2.0
30 per. Mov . A v g. (P_Sc hiphol)
14.0
m m /da y
-4.0
-6.0
-8.0
10.0
8.0
6.0
E_Sc hiphol
E_DDNI_openw ater
E_DDNI_reed(1.54)
30 per. Mov . A v g. (E_Sc hiphol)
-10.0
12.0
4.0
2.0
Example of evaporation and precipitation in the Delta (and as a reference for Schiphol, the
Netherlands) as monthly average values.
40.0
P-E Sc hiphol
Net: P-Eow DDNI
Net: P-Ereed DDNI
30 per. Mov . A v g. (P-E Sc hiphol)
35.0
30.0
m m /da y
25.0
20.0
15.0
10.0
5.0
0.0
-5.0
Figure 2.3
01-dec -00
01-nov -00
01-okt-00
01-s ep-00
01-aug-00
01-jul-00
01-jun-00
01-mei-00
01-apr-00
01-mrt-00
01-f eb-00
01-jan-00
-10.0
Example of the net precipitation in open water and reed beds in the Delta for the year 2000 (and
as a reference for Schiphol, the Netherlands)
Data on surface water temperature are based on monitoring data near Tulcea. In figure 2.4
the average surface water temperature for the period 1994-2002 is presented, as well as the
minimum and the maximum in this period.
WL | Delft Hydraulics
2–4
01-dec -00
01-nov -00
01-okt-00
01-s ep-00
01-aug-00
01-jul-00
01-jun-00
01-mei-00
01-mrt-00
01-jan-00
01-dec -00
01-nov -00
01-okt-00
01-s ep-00
01-jul-00
01-aug-00
01-jun-00
01-mei-00
01-apr-00
01-mrt-00
01-f eb-00
01-jan-00
Figure 2.2
01-apr-00
0.0
-12.0
01-f eb-00
m m /da y
P_DDNI
16.0
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
30.00
25.00
20.00
Average of tem p
15.00
M in of tem p
M ax of tem p
10.00
5.00
0.00
1
2
3
4
5
6
7
8
9
10
11
12
13
A v erage of temp
1.11
2.47
7.02
10.31
17.25
22.75
25.39
25.21
20.48
16.02
9.12
3.88
13.33
Min of temp
0.50
0.51
1.45
7.30
15.63
21.42
23.40
21.50
18.10
14.03
8.00
1.60
0.50
Max of temp
2.00
5.60
9.40
12.40
21.00
24.10
26.38
28.00
23.88
17.80
11.03
5.29
28.00
Figure 2.4
Monthly average surface water temperature data at Tulcea (1994-2002)
Actual Radiation data (necessary for the computation of algae bloom) are not available. A
monthly average value was estimated based on literature. Literature stated that 73% of the
annual radiation falls within the period April-September. Furthermore the maximum is 20
kcal/cm2 (radiance value) in the month July. These values should however be corrected for
e.g. clouds and the wavelength spectrum. It is assumed that 10% of the light is reflected and
50% of the radiance is the amount of visible light (available for algae bloom). The radiance
in the model is expressed in W/m2. Literature data from 1963 gave us some idea about the
monthly average values, ranging from 3.4 kcal/cm2.month in November till 18.8
kcal/cm2.month in July. These values match approximately with values from Venice
(available from a former Delft Hydraulics study) which has more or less the same latitude.
In figure 2.5 the monthly average data used in the model are presented, as well as the
minimum and the maximum values in this period. The average values from Venice have
been used in the Danube Delta applications, without any variations over different years.
160
140
120
100
A verage of rad
M in of rad
80
M ax of rad
60
40
20
0
1
2
3
4
5
6
7
8
9
10
11
12
13
A v erage of rad
24
37
64
92
106
115
123
102
71
36
26
18
67
Min of rad
10
12
51
70
85
91
110
92
54
17
17
8
8
Max of rad
39
55
83
113
135
139
132
116
93
47
47
27
139
Figure 2.5
WL | Delft Hydraulics
Average effective solar radiation (corrected for clouds, reflection and visible light) from Venice
(Italy) which are used in the Delta application.
2–5
Hydrology and Water Quality Modelling in the Danube Delta
Part B
2.4
Q3230
December, 2002
Calibration and results
After implementing the improved outline, in which reed beds are separated from open water,
and incorporation of precipitation, evaporation and wind effects, the hydraulic model was
calibrated again. All of this assuming the boundary conditions, model outline and definition
of cross-sections are not anymore points of discussion. In fact this means calibration has to
be performed on water levels and discharges or velocities.
The discharge/velocity on each location in the model is a computational result of the CF
module. It is mainly driven by the water levels as defined at the up stream boundary in the
Danube near Tulcea. Of secondary importance in this are meteorological data like wind
speed and direction.
During calibration of the model measurement data regarding water levels and discharges in
the Uzlina districts have been used. Water level data have been recorded by data loggers,
which resulted in the availability of a time series (spring 2002 up till September 2002). The
data regarding flow velocity are based upon two individual monitoring moments in June and
September this year. Discharges at the in and outflow points of several lakes in the Uzlina
districts have been monitored during the field missions (see Part A). To be able to obtain a
good fit between measurement data and model data we were forced using a rather
extraordinary value of the bed roughness value in the lake and reed bed areas. Using normal
values of this roughness coefficient the gradient in water levels became too large. At the
same moment we were not able to compute discharges in the same order of magnitude as
monitored in June and September.
Within the river and channel branches the present model uses Manning roughness values in
the order of magnitude 0.04-0.08, rather normal values for a system like the Danube Delta.
Within the lakes (open water and reed beds) at present an extraordinary Manning value of
about 5 is used. This is a ridiculous value for empirical relations derived for rivers and
channels. However we are dealing with a 1-dimensional model scheme for lakes, including
reed beds and open water, a situation no literature values for Manning or Chezy values
could be found. Moreover, the very high value for the Manning coefficient is not unusual to
represent laminar flow (pers. com. Adri Verwey)
An example of the discharges as modelled by the model in comparison with field
measurements in the Uzline-Isacova region is given in figure 2.6. In this figure momentum
measurements are compared with the average modelled flow (average, minimum and
maximum) during both the June and the September 2002 field trips. As can be seen the in
and out flows of Isacova lake are predicted very well by the model.
WL | Delft Hydraulics
2–6
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
dis charges: m onitoring versus m odelled
3
disc harges : m onitoring versus m odelled
6
2
1
dis cha rg e (m 3/s )
dis charge (m 3/s )
5
4
3
2
0
-1
-2
discharges: m onitoring versus m odelled
2
-3
-4
1.5
-5
1
1
d is charg e (m 3/s )
-6
-7
0
0.5
0
-0.5
-1
-1.5
-2
-2.5
dis c harges : m onitoring vers us m odelled
4
3
disc harges : m onitoring vers us m odelled
2
1
0
1
-1
-2
-3
-4
dis cha rge (m 3 /s )
dis charge (m 3/s )
2
0
-1
-2
-3
-4
-5
Figure 2.6
Monitored discharges around lake Isacova during the field trips in June (3-11) and September (410) in comparison with average, minimum and maximum modelled discharges for the same
period.
In figure 2.7 an overview is given of new water level monitoring locations in the Delta. In
figure 2.8 both the monitored and modelled water levels in Isacova are presented for a low
water period in April 2002. As can be concluded, the model predicts the water levels very
well. It should be noted that this has been achieved by using the extreme (out of range)
value of the Manning coefficient in the lakes. With Manning roughness values within the socalled expected range we were not able to produce such nice results.
The Black Sea zero reference (MNS) had been delivered by the topographical team and has
been deduced from the original zero reference Black Sea 75 (MN75). The conversion
formula between both locations is: H_MNS = H_MN75 + 0.35 (m). The average difference
between the monitored water level in the diver (H_diver) and the modelled level (H_model)
data is 0.33 m, which represents the constant value used to correct the levels form MN75 to
MNS. This observation is according to the Aljosja Hooijer report from September 2002. It
means that the initial value of the reference point (cnl.Litcov and cnl.Perovolovca crossing)
is according to the Black Sea Sulina zero reference location (H_diver_correction) and it is
not necessary to correct again by adding 0.35 m.
A check of all the zero reference points will be done by the DDNI topographical team for all
the new divers that have been installed in Gorgova-Uzlina aquatic complex.
WL | Delft Hydraulics
2–7
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Black Sea Sulina zero
reference point (M NS)
Diver cnl. Isac 2
Isac lake level (model)
Figure 2.7
Figure 2.8
WL | Delft Hydraulics
Map of diver and topographic point location (Black Sea Sulina zero reference)
Monitored and modelled water levels
2–8
Hydrology and Water Quality Modelling in the Danube Delta
Part B
3
Q3230
December, 2002
Eutrofication (DANUBS)
For an update of the technical description of the process configuration for DANUBS reference
is made to appendix A. The calibration of the DANUBS processes configuration focused upon
the lakes Uzlina, Isacova and Cuibulcuelebede for the years 1996-1997. Other locations and
other years were used for verifying the process coefficient settings.
3.1
Main characteristics (changes)
Shear stress (sedimentation)
The bed shear stress, which is used by the water quality model, is calculated as the sum of
the shear stress caused by wind, flow and ship movements. If the directions of the flow
(FlowDir) and the wind (WindDir) are supplied the wind and flow stresses are summed as
vectors, otherwise as scalars. The stress by ship movements is always added as a scalar as it
is assumed to be independent of direction (and assumed to be equal to zero in this
application).
The calculation method of the shear stress uses the formulations according to Tamminga
(1987) or Soulsby et al. (1993). For shear stress caused by flow this means:
Within our model we are using quite normal roughness values for river and channel
branches, but extraordinary values for the lake and reed parts. Using these extraordinary
values we obtained reasonable discharge values (and so velocity values) at the in and
outflow point of the lakes.
We should take into account that the roughness value has become a model calibration
parameter in stead of a value with a real physical meaning. However its value is used to
compute a shear stress, which of course then also loses its physical value. The shear stress
caused by flow in this case is order of magnitude 1000 out of range. The shear stress within
the water quality model is used to calculate the sedimentation of particles.
The final result is that with respect to the calibration values obtained for critical shear stress
for sedimentation the value should by multiplied by 1000 as well.
WL | Delft Hydraulics
3–1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Reaeration
The driving force for gas transport across the air-water interface is the difference between
the actual dissolved concentration and the saturated concentration. The reaeration flux can
thus have a positive or a negative value. The reaeration rate constant (RCRear) can be
supplied directly by the user or is calculated by the model. In literature, there are many
empirical relations available.
Several empirical relations representing the effect of depth and stream velocity on RCRear
are implemented in the process library as options (SWREAR switches 2 until 6). One option
for the combined effect of wind velocity, stream velocity and depth on RCRear has been
implemented as well as options for the combined effect of wind velocity and depth.
The update of the DANUBS subset uses a scaled version of the Connor O’ Dobbins equations
(SWREAR = 4) to derive the oxygen exchange flux with the atmosphere.
In which:
KLRear = scale factor for RCRear (-)
RCRear = reaeration rate constant (d-1)
Depth = water depth (m)
Veloc =stream velocity water (m.s-1)
KLRear has a default value of 1 (which means the original Connor O’Dobbins is used), but
has been set to 0 in reed beds and uses a higher value for the lakes. The zero value is chosen
to disable the exchange with the atmosphere in reed beds, because the surface water is
covered. The higher value for lakes is chosen to compensate for the extra exchange caused
by wind and waves, which is not part of the equation.
With respect to the field situation probably formula number 7 (reckoning with wind, flow
and depth) within the library would be more suitable for a model outline including rivers
and lakes, but with this formula it is impossible to switch of the rearation in reed beds.
Reed bed modelling
Now reed beds are separated from open water it is possible to define specific conditions for
this surface water type. As the process library of the water quality model does not contain
specific biochemical process formulations for reed bed conditions we have to use the same
formulations as for open water. However some specific conditions are created. For detailed
information reference is made to appendix A, and the process library of SOBEK-WQ.
WL | Delft Hydraulics
3–2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
The main reed bed assumptions are:
1. No algae bloom can take place in reed beds. Within the model this has been assured by
means of “switching of the light” by introduction of a dummy huge background
extinction (ExtVLBak = 99). This does not mean there are no algae in reed beds. Caused
by inflow from open water there is a transport of algae towards the reed beds, where
they will die.
2. Second assumption is that there is no oxygen exchange possible between air water,
assuring conditions of low oxygen contents or even without oxygen.
3. It is known a lot of nitrogen is removed in reed beds. Denitrification is the process,
which removes nitrogen from the system. The removal is forced by the coefficients
RcDenSed (denitrification rate in sediment = 0.06 1/d) and RcDenWat (denitrification
in surface water = 0.2 1/d). The process takes part on nitrate. To be sure that nitrate does
exist, the nitrification in reed beds continues even till oxygen concentrations of zero
(OOXNit and COXNit settings).
4. Sedimentation rates within reed beds are double in comparison with open water and no
resuspension is possible.
5. Mineralisation rates in reed beds are high in comparison with open water.
6. A higher background sediment oxygen demand has been defined (representing the
higher organic matter content in reed bed sediments) (remark: sediment oxygen demand
has been forced, modelling with the DANUBS subset does mean you are not modelling
the sediment layer itself).
3.2
Some results
Underneath some results of the calibration of the DANUBS-2002 subset are presented in
figure 3.1 and 3.2. The result of the new application is at least as good as the fitting, which
has been performed last year. But in contradiction of last year, we now are using surface
water type related coefficients in stead of district coefficients. It is not necessary anymore to
scale coefficients according to their weight factors between open water and reed areas, as
well as to use the denitrification function related to the water level at Tulcea.
In Figure 3.1 the total phosphorus contents of three lakes in the Gorgova-Uzlina are
presented. Figure 3.2 gives the chlorophyll levels for the same lakes. Last year we faced
difficulties in the calibration procedure with both these parameters. Phosphorus because of
its contradictory monitoring results, which provided us with boundary conditions.
Chlorophyl because of the fact we did not have a separation between reed beds and open
water areas. The present application shows for both parameters in trend a reliable fit. Some
more results for the same district are presented in Appendix B. For results of other districts
reference is made to the application itself.
WL | Delft Hydraulics
3–3
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Total phosphorous (mg/l)
0.3
0.25
0.2
0.15
Cuibul
cu Lebede
0.1
0.05
0
94
95
96
97
98
99
00
01
02
0.3
0.25
0.2
Isacova
0.15
0.1
0.05
0
94
95
99
00
96
97
98
99
00
01
02
0.3
Uzlina
0.25
0.2
0.15
0.1
0.05
0
94
Figure 3.1
95
96
97
98
01
02
Modelled total phosphorus contents in the Gorgova-Uzlina district in comparison with monitoring
data.
100
90
Chlorophyl-a (μg/l)
80
70
60
50
40
Cuibul
cu Lebede
30
20
10
0
100
94
95
96
97
98
99
00
01
02
90
80
70
60
Isacova
50
40
30
20
10
0
94
95
96
97
98
00
01
02
99
00
01
02
100
Uzlina
90
80
70
60
50
40
30
20
10
0
94
Figure 3.2
WL | Delft Hydraulics
95
96
97
98
99
Modelled chlorophyll-a contents in the Gorgova-Uzlina district in comparison with monitoring
data.
3–4
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
4
Eutrofication (BLOOM)
4.1
Introduction
December, 2002
Due to eutrophication the complex and varied ecosystems of the Danube Delta have
deteriorated over past few decades. High nutrient loads in the Danube River as it enters the
Delta are seen as one of the reasons. The DANUBS subset has been developed to give more
insight in nutrient removal processes on a lake-district scale. Complex processes have been
modelled on a simple way. For example, the model does not contain a sediment layer, so any
interaction between surface water and sediment is neglected. Sedimentation parameters have
to be interpreted as net removal. Release of phosphorus from sediments in dry periods,
which is supposed to be relevant in reed beds, can not be described by this subset. Another
example is the modelling of the algae content. Although it has proven to make a rather
reliable prediction, all algae-species have been lumped in one species and an important issue
as gracing by zooplankton has been compensated by a higher mortality rate.
With the process library however, it is possible to describe these and other phenomena in
more detail. It was asked to extend the model with BLOOM functionality on algae, in order to
describe several algae-species, and to incorporate relevant sediment processes. The specific
challenge of this module should be replication of the chlorophyll and turbidity
characteristics of the lake types, which have been identified in the TROFDD project
(Oosterberg et al. 2000, Ecological gradients in the Danube Delta), as well as the
distribution of these lake types over the Danube Delta.
This chapter provides in a short introduction in the DDNI-DBS water quality model, its
process definition and model assumptions. This model has been created in the period
October 2002.
For detailed information on the processes, the coefficients and the general model
assumptions reference is made to the DELWAQ technical reference manual and the SOBEK
help file.
Final remark, which has to be made, is that during the calibration of this module only is
focused upon the Uzlina-Isacova region. Calibration has been performed for the years 1997
and 1998, verification for the years 2000 and 2001.
4.2
Required input
The water quality model requires data on boundary conditions, initial conditions,
meteorological conditions and process coefficients. The meteorological data used by the
model have already been described in the hydrology chapter. The others are discussed
briefly below.
Boundary conditions
WL | Delft Hydraulics
4–1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
For the hydrological model of the Danube Delta area the most important boundary is the
upstream inflow at Reni. Another relevant source within the Danube Delta, which has been
incorporated in the model, is atmospheric deposition. Point-source waste loads and nonpoint source waste loads are considered to be of minor importance. Model outflow locations
are the downstream boundaries at the Black Sea and evaporation. Within the water quality
model it is assured that evaporation only extracts water and no substances.
The DDNI-DBS model distinguishes the following model variables:
Surface Water
• continuity
• dissolved oxygen (OXY);
• inorganic nutrients: NH4, NO3, Si, PO4 (dissolved), AAP (adsorbed phosphorus), PAP
(irreversible adsorbed phosphorus);
• inorganic suspended matter in two fractions: IM1, IM2;
• 11 algae; Diatoms energy type, Diatoms P/Si type, Greens energy type, Greens N type,
Greens P type, Blue-greens energy type, Blue-greens N type, Blue-greens P type,
Microcystes energy type, Microcystes N type, Microcystes P type;
• organic detritus: DetC, DetN, DetP, DetSi.
• other organic matter: OOC, OON, OOP, OOSi
Sediment layer
• adsorbed ortho phosphorus in sediment (AAPS1)
• inorganic matter in sediment (IM1S1, IM2S1)
• organic matter in sediment (DetC, DetN, DetP, DetSi)
For all of these variables the model has to be provided with initial and boundary conditions
water. Of course, not all of these items are directly available within the DDNI monitoring
database. Within the SOBEK framework so called calculation rules have been incorporated
to define the relation between monitoring data and model variables. By using these kinds of
calculation rules, it is possible to "feed" the model with data directly from the database.
Presently we use monitoring data on total suspended solids (SS), oxygen (O2), dissolved
nitrogen (NO3_2, NH4), dissolved phosphorus (PO4) and chemical oxygen demand (CCO)
from the DDNI laboratory for the deduction of model variables. Total phosphorus (TotP)
measurements are expected to be unreliable. Separate analysis in the RIZA laboratory
showed significant higher values. Also total phosphorus monitoring data used within the
DANUBS project at station Reni show higher values (source: v.Gils). At present the total
phosphorus data from the Reni station are used. Except for these data also computational
results by the DANUBS model for the upstream region (v.Gils) have been used for the
estimation of the upstream conditions regarding total inorganic matter (sTIM) and algae
carbon (sALGC) content. This is motivated by the relative big importance of these
parameters in relation to the availability of reliable data. For the period after 1997 monthly
average computational results of the previous period have been used. Detritus carbon is
assumed to be equal to the algae carbon and for deducing the other organic carbon content
the difference between monitored CCO data and the sum of the algae and detritus part is
used.
WL | Delft Hydraulics
4–2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
The results of this for the upstream inorganic-matter concentrations and the algae content
are presented in Figure 4.1. At the bottom end it means that in comparison with previously
derived boundary conditions the suspended solids data at station Reni are not longer used.
Diat _DDNI
2.5
Diat _Danubs
A lgC- suggest ion
2
1.5
1
0.5
0
1994
1995
1996
1997
1998
1999
2000
2001
120
IM 1 _ d d ni
100
IM 1 _ d anub s
IM 1 sug g est
80
60
40
20
0
1994 1995 1996 1997 1998 1999 2000 2001
16
14
AlgC-suggest ion
12
Det Csuggest
OOCsuggest
10
8
6
4
2
0
1993 1994 1995
Figure 4.1
WL | Delft Hydraulics
1996 1997 1998 1999
2000
Deduction of organic and inorganic suspended matter for the upstream boundary.
4–3
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
To estimate values for non-monitored variables standard coefficients and relations from the
water quality process library are used. Examples are the nutrient to carbon ratio’s in organic
matter (NCratio = 0.16, PCRatio = 0.02, SiCRatio = 0.49) and a dry matter conversion
factor between carbon and dry matter (DMCF = 2.5 gDM/gC).
Currently calculation rules as presented in table 4-1 are used (file name is substanc.def) for
estimating the upstream Danube river boundary conditions:
Table 4-1
List of model variables and calculation rules to determine them out of monitoring data.
Sobek-WQ
Variable
monitoring database related
calculation rule (user defined substances)
Oxygen (OXY)
Nitrate (NO3)
Ammonium (NH4)
Ortho Phosphorus (PO4)
Adsorbed ortho phosphorus (PAP)
Adsorbed ortho phosphorus (AAP)
Dissolved Silica (Si)
Detritus (organic) Carbon (DetC)
Detritus Nitrogen (DetN)
Detritus phosphorus (DetP)
Detritus Silica (DetSi)
Other Oorganic Carbon (OOC)
Other Organic Nitrogen (OON)
Other Organic Phosphorus (OOP)
Other Organic Silica (OOSi)
DIATOMS energy type
DIATOMS P/Si type
GREENS energy type
GREENS nitrogen type
GREENS phosphorus type
BLUEGREENS energy type
BLUEGREENS nitrogen type
BLUEGREENS phosphorus type
MICROCYS energy type
MICROCYS nitrogen type
MICROCYS phosphorus type
Inorganic Matter (IM1)
Inorganic Matter (IM2)
O2
NO32
NH4N
OPO4
PTot - OPO4 – sALGC * 0.033
0.0 * OPO4
0.80 * CCO
1.0 * sALGC
0.23 * sALGC
0.02 * sALGC
0.60 * sALGC
0.80 * CCO – 2.0 * sALGC
0.19 * CCO – 0.47 * sALGC
0.016 * CCO – 0.04 * sALGC
0.48 * CCO – 1.2 * sALGC
0.40 * sALGC
0.0
0.30 * sALGC
0.0
0.0
0.30 * sALGC
0.0
0.0
0.0
0.0
0.0
0.5*sTIM
0.5*sTIM
Limit
MIN 0.0
MIN 0.0
MIN 0.0
MIN 0.0
MIN 0.0
Initial conditions
Initial conditions imply the initial concentrations of the substances in the model. By default,
global initial conditions are used for all segments in the model (table 4-2). If desired the user
is able to vary the initial conditions per segment by using a binary restart file, in which for
every segment the modelled conditions on the last time step of a previous simulation have
been stored.
Residence times in some parts of the complex could be very high and consequently a chosen
global initial value still can have influence on the model outcome. It is advised to simulate
at least one year for creating a restart file (preferable is even a longer period). However, at
present (i.e. during the calibration procedure) has been chosen for global initial values.
WL | Delft Hydraulics
4–4
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Table 4-2
Q3230
December, 2002
List of the default global initial conditions.
Sobek-WQ
Variable
Oxygen (OXY)
Nitrate (NO3)
Ammonium (NH4)
Ortho Phosphorus (PO4)
Adsorbed ortho phosphorus
(PAP)
Adsorbed ortho phosphorus
(AAP)
Dissolved Silica (Si)
All algae types
Detritus (organic) Carbon (DetC)
Detritus Nitrogen (DetN)
Detritus phosphorus (DetP)
Detritus Silica (DetSi)
Other Organic Carbon (OOC)
Other Organic Nitrogen (OON)
Other
Organic
phosphorus
(OOP)
Other Organic Silica (OOSi)
Inorganic Matter first fraction
(IM1)
Inorganic Matter second fract.
(IM2)
Initial
Value
10
1.9
0.2
0.06
0.0
Unit
mg/l
mgN/l
mgN/l
mgP/l
MgP/l
0.02
mgP/l
1
0
0.05
0.013
0.0015
0.04
0.04
0.012
0.0014
mgSi/l
MgC/l
mgC/l
mgN/l
mgP/l
mgSi/l
mgC/l
mgN/l
mgP/l
0.04
29
mgSi/l
mg/l
28
mg/l
Sobek-WQ
variable in sediment
Initial
value
Unit
Adsorbed
(AAPS1)
phosphorus
1
gP/m2
Detritus Carbon (DetCS1)
Detritus Nitrogen (DetNS1)
Detritus phosphorus (DetPS1)
Detritus Silica (DetSiS1)
1
1
1
1
gC/m2
gN/m2
gP/m2
gSi/m2
Inorganic Matter first fract.
(IM1S1)
Inorganic Matter sec. fract.
(IM2S1)
1
g/m2
1
g/m2
Processes
The model equations for the variables mentioned above include a number of processes from
SOBEK'S Processes Library, some of which will be described below briefly. For a more
extended description we refer to the Theoretical Reference Manual (TRM) for the individual
processes of the Processes Library or the SOBEK help file.
It should be noted that in the greater part of the Danube Delta area transport has the biggest
influence on the internal fluxes within the model. A good calibration of the hydrological
model therefore always is a pre-condition for the calibration of the water quality model.
An overview of the processes within the DDNI-DBS subset regarding the nutrients is
presented in Figure 4.2 and Figure 4.3. A total overview of all processes, which presently
are incorporated in the model, is given in Appendix C.
WL | Delft Hydraulics
4–5
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
N2
= Transport
Denitrification
Denitrification
in reed beds
N2
OON
NO3
Nitrification
Uptake
&Release
Mineralisation
NH4
Algae
Algae
Growth
uptake
C:N:P:Si
(2 diatoms)
Mortality and
Grazing release
DetN
Grazing by
zooplankton
Growth
uptake
Resuspension
Mortality
(3 greens)
Sedimentation
(3 bluegreens)
(3 microcystes)
Mineralisation
DetNS1
Burial
Figure 4.2
Processes overview regarding nitrogen components.
= Transport
PAP
Decay
Uptake
&Release
OOP
Mineralisation
NH4
PO
Ad/desorption
IM1
IM2
Growth
uptake
AAP
Mortality
release
Algae
Algae
(2 diatoms)
Sedimentation /
Resuspension
Desorption
and release
IM1S1 AAPS1
IM2S1
(3 greens)
(3 bluegreens)
(3 microcystes)
Mineralisation
Burial
Figure 4.3
WL | Delft Hydraulics
DetP
Grazing by
zooplankton
C:N:P:Si
Resuspension
Mortality
Sedimentation
DetPS1
Burial
Processes overview regarding phosphorus components.
4–6
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
The following assumptions are made for this application (amongst others and apart from the
assumptions, which have been mentioned for the DANUBS application):
•
•
•
No sedimentation of algae and the other organic matter does occur.
Burial in the present application is defined as a “surface water type” dependent
constant.
In the field situation, algae and detritus in the water column can be consumed by
grazing zooplankton and zoobenthos. In the DBS application biomass of grazers is
defined as a forcing function.
Some of the processes will be discussed at the end of this chapter.
Coefficients
There are four types of process coefficients that may be specified in the model input are
used in water quality model:
•
•
•
•
model constants;
model parameters f(x);
model functions f(t);
segment functions f (x,t)
The model constants are separated into algae coefficients and constants, which have been
set on “editable” by the user interface. For the algae coefficients reference is made to a fixed
bloom algae coefficient database. It is strongly not advised to edit these coefficients. An
overview of the so-called editable coefficients is available in the model application (settings
menu).
Parameters are constant in time but may differ for the computational elements. If they are
used, they need to be specified for all computational elements or for element types. In the
Danube Delta model outline 4 geographically based surface water types have been defined,
in order to be able to define specific conditions for each type of water. In the DANUBS
application currently the parameter settings as presented in table c) are used:
WL | Delft Hydraulics
4–7
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Table 4-4.
Q3230
December, 2002
Parameter settings used for calibrating the DDNI-DBS application
Surface water types
KLRear
ExtVLBak
Rc0AAPS1
VsedDetC
TauCSDetC
VsedIM1
TaucSIM1
VsedIM2
TaucSIM2
VburDMS1
FResS1DM
RcNit
COXNIT
OOXNIT
RcDenWat
Rc0DenSed
RcDetC
RcDetN
RcDetP
RcDetSi
Danuberiver
1
DistrictChannels
1
LakesOpen-water
1.5
LakesReed
0
1.5
0
0
0.001
0
0.01
0
0.01
0
0
0.1
1
5
0.1
0
0.12
0.12
0.12
0.12
1.
0
0
0.001
0.1
0.01
0.05
0.01
0
0
0.1
1
5
0.1
0.01
0.12
0.12
0.12
0.12
0.5
0
0
1
0.2
10
0.07
0.5
0.005
2
0.1
1
5
0.1
0.01
0.15
0.15
0.15
0.15
999
0.01
0.1
1
0.3
10
0.1
0.5
0.01
0
0.2
-1
0
0.2
0.06
0.2
0.2
0.2
0.2
These parameters are related to oxygen climate, light, sedimentation behaviour,
(de)nitrification and mineralisation.
Oxygen:
KLRear
=
reaeration transfer coefficient.
KLRear has been made space dependent (= parameter) to be able to define different
exchange velocities with the atmosphere. At present the reaeration formulation uses a scaled
version of the Connor O’ Dobbins equations to derive its exchange flux. The scale factor is
the KLRear. KLRear has a default value of 1 (which means the original Connor O’Dobbins
is used), but has been put to 0 in reed beds and uses a higher value for lakes. The zero value
is chosen to disable the exchange with the atmosphere in reed beds, because the surface
water is covered. The higher value for lakes is chosen to compensate for the extra exchange
caused by wind and waves, which is not part of the equation. (With respect to this formula
number 7 in the library would be more suitable for a model outline including rivers and
lakes, but with this formula it is impossible to switch of the rearation in reed beds).
Light climate:
ExtVLBak = background extinction
ExtVLBak has been made space dependent to be able to include the effect of different
concentrations of humified acids and non modelled suspended particles on the light climate
and the effect of reed beds and other vegetation on the limitation of light availability for
algae bloom. The high value for reed beds is chosen to switch of all possibilities for algae
bloom in reed beds.
WL | Delft Hydraulics
4–8
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Sediment behaviour:
VSedDetC = sedimentation velocity of detritus carbon
TauCSDetC = critical shear stress for sedimentation of detritus carbon
VsedIM1 = sedimentation velocity of inorganic suspended matter
TauCSIM1 = critical shear stress for sedimentation of inorganic suspended matter
VsedIM2 = sedimentation velocity of second fraction of inorganic suspended matter
TauCSIM2 = critical shear stress for sedimentation of second fraction inorganic
suspended matter
FResS1DM = zero order resuspension flux
VBurDMS1= burial of dry matter
Regarding sedimentation it is assumed that organic matter only is due to sedimentation in
reed bed areas. Inorganic matter settles also in the channels and lakes (more or less to lose
adsorbed phosphorus), but has a higher sedimentation rate in reed beds.
Regarding the critical shear stress values of organic and inorganic matter reference is made
to the section “main characteristics”, “shear stress”. The higher value (factor 1000) is related
to the extreme value of the Manning roughness value, which has been used in lakes for the
calibration of the hydrology.
Finally, a resuspension flux has been introduced in the lakes. No sediment layer has been
modelled in this application, but is it known that resuspension due to wind does occur. In
this application it has been chosen to use a constant factor for resuspension. This eventually
results in a more constant suspended solids content in the lakes in comparison with the
monitoring data, but its goal is to model average values.
Nitrification and denitrification:
RcNit
= first order nitrification rate
COXNit
= critical oxygen content for nitrification
OOXNit = optimal oxygen content for nitrification
RcDenWat = first order denitrification rate for surface water
Rc0DenSed = first order denitrification rate for sediment
The nitrification rate in reed beds is assumed to be twice the rate of the surface water. Also,
with help of the COXNit and OOXNit values it has been adjusted for reed beds to have
nitrification in lower oxygen conditions in comparison with the open water (it is known that
the nitrification process continues due to transport of oxygen via the reed to the sediment
layer).
The denitrification rates in surface water and in sediments are used to simulate the nitrogen
removal in the districts. Most of the removal will be due to denitrification in reed beds,
explaining the higher values used in these cases. Using the 0.06 value for RcDenSed, the
removal fluxes as in the old application are approached.
Mineralisation:
RcDetC
= first order mineralisation rate for detritus carbon contents
RcDetN
= first order mineralisation rate for detritus nitrogen
RcDetP
= first order mineralisation rate for detritus phosphorus
RcDetSi
= first order mineralisation rate for detritus silicate
For mineralisation regular literature values have been used. Only for reed beds higher values
have been chosen (to stimulate nutrient removal).
WL | Delft Hydraulics
4–9
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Phosphorus release:
Rc0AAPS1 = desorption rate phosphorus in sediment
The Delta area is not only a sink regarding phosphorus. It is known that release of
phosphorus from the sediment layer may increase the phosphate levels in the lakes. During
low water periods the release could be higher then the sum of adsorption and sedimentation.
Functions are constant all over the area, but follow a prescribed sequence over time. Most
common examples are temperature and solar radiation, which both are defined within the
Meteo data task. No additional functions are used within the DANUBS application.
Table 4-5
Model functions
Parameter id
Temp
Rad
Zooplankton
Description
Water temperature
Solar radiation at the water surface
Zooplankton concentration
Recommended value
f(t)
f(t)
f(t)
Unit
deg C
W/m2
gC/m3
For the temperature and radiation functions reference is made to the chapter “Hydrology”.
Data from the TROFDD report have been used for deducing the average biomass of
zooplankton (gC/m3) of the lakes Uzlina, Isacova and Cuibul cu Lebede for the years 19971998, both calibration years. For 1997 the zooplankton content has been put to 0.5 gC/m3
till July and 0.4 foor the rest of the year. For 1998 a constant value of 0.5 gC/m3 is used. It
should be noted that the zooplankton contents are very heterogeneous in space and time. At
present zooplankton is defined as a model wide function. Grazing is one of the key factors
regulating the algae contents in the lakes, so different values can give completely different
results.
A second point of order is that I corrected the 1998 data by a factor 10; the values in the
graphs in the report seem to be out of range. Using the original data from the TROFDD
graphs as input for the model, it is not possible to compute any algae concentrations.
Anyway, they are anyhow far out of range of all the other data, while the DDNI monitoring
data regarding algae concentrations are not.
4.3
Some results
Underneath some results of the calibration of the DDNI-BLOOM subset are presented in
picture 4.1 till 4.3. No detailed output is presented and discussed in this report, which
mainly focuses on giving a technical description of the BLOOM subset. In Figure 4.1 the
chlorophyll levels for the Uzlina-Isacova lakes are presented. In Figure 4.2 the species types
are given. It can be concluded that according to the model in summertime the N- and P-type
green algae are dominant in the lakes, and for Uzlina also energy and N-limited microcystes
are modelled. In Figure 4.3 the chlorophyll levels for the Uzlina-Isacova lakes in case
grazing is switched of are presented.
WL | Delft Hydraulics
4–10
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
140
Chlorophyl-a (μg/l)
130
120
110
100
Cuibul
cu Lebede
90
80
70
60
50
40
30
20
140
10
0
jan-97
apr-97
jul-97
okt-97
jan-98
apr-98
jul-98
okt-98
jan-99
130
120
110
100
90
80
70
60
Isacova
50
40
30
20
10
0
jan-97
140
apr-97
jul-97
okt-97
jan-98
apr-98
jul-98
okt-98
jan-99
130
120
110
100
Uzlina
90
80
70
60
50
40
30
20
10
0
jan-97
Figure 4.1
apr-97
jul-97
okt-97
jan-98
apr-98
jul-98
okt-98
jan-99
Chlorophyll-a concentrations in Uzlina, Isacova and Cuibul cu Lebede for 1997-1998.
5.5
Algae (mgC/l)
5
4.5
4
Cuibul
cu Lebede
3.5
3
2.5
2
5.5
1.5
5
1
4.5
0.5
4
0
m rt-97
jun-97
sep-97
dec-97
m rt-98
jun-98
sep-98
dec-98
3.5
3
2.5
Isacova
2
1.5
1
0.5
0
mrt-97
jun-97
sep-97
dec -97
m rt-98
jun-98
s ep-98
dec -98
2.4
2.2
2
Uzlina
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
m rt-97
Figure 4.2
WL | Delft Hydraulics
jun-97
sep-97
dec-97
m rt-98
jun-98
sep-98
dec-98
Algae types (in gC/m3) in Uzlina, Isacova and Cuibul cu Lebede for 1997-1998.
4–11
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
Chlorophyl-a (μg/l)
220
200
without grazing
180
160
Cuibul
cu Lebede
140
120
100
80
220
60
200
40
180
20
0
jan-97
160
140
apr-97
jul-97
okt-97
jan-98
apr-98
jul-98
okt-98
jan-99
120
100
Isacova
80
60
40
20
0
jan-97
apr-97
jul-97
okt-97
apr-98
jul-98
jan-98
apr-98
jul-98
okt-98
jan-99
220
200
Uzlina
180
160
140
120
100
80
60
40
20
0
jan-97
apr-97
jul-97
okt-97
jan-98
okt-98
jan-99
Figure 4.3 Algae concentration in Uzlina, Isacova and Cuibul cu Lebede for 1997-1998 in case grazing is
ignored.
WL | Delft Hydraulics
4–12
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
5
Conclusions and recommendations
5.1
Conclusions
December, 2002
Objective 1: adapt in close cooperation with Adrian the outline of the model (i.e. (1)
separation of reed beds and open water and (2) introduce precipitation and evaporation)
and calibrate the hydrology using data gathered by data loggers and the field trips.
•
•
•
Separation of reed beds and open water has been successfully fulfilled within the
lakes. Exchange of water between reed beds and channels, as well as exchange of
water between lakes via reed beds is not covered by the present application. The big
reed bed areas in the model are assigned to the lakes (as well in the old as the new
model outline). Exchange of water between reed beds and open surface water, is
driven by advection and dispersion.
As a result of the introduction of precipitation and evaporation in the lakes the
Danube river is not any more the only “regulator” for the flow regime in the
districts. Additionally also wind speed and direction has been defined and taken into
account in predicting the flows in the districts.
Based upon the flow measurements gathered in June and September the hydrology
has been recalibrated. The roughness value proved to be as well a necessary as a
successful key to assure a good fit between modelled and modelled discharges in
the districts. According to hydraulic experts it is allowed to define a extreme high
Manning roughness coefficient in lakes with adjoining big areas of reed in order to
introduce a linear flow.
Objective 2: Update and improve the water quality model regarding eutrofication by introducing the BLOOM
component. This task has been split into:
(c)
adapting the existing DANUBS module to the new model outline, redefining the process
formulations for reed beds, implement recent monitoring results, calibrate the DANUBS module again,
and finally
(d)
redefinition and calibration of DDNI-EUTRO by replacing the algae by BLOOM processes and
introduction of a sediment layer and accompanying processes.
•
•
•
•
•
WL | Delft Hydraulics
The DANUBS application is finished, actually is more than required for its goal.
The BLOOM application is technically functioning and tested on the lakes Uzlina,
Isacova and Cuibul cu Lebede for the period 1997-1998. Grazing is one of the key
parameters in predicting algae contents.
As a result of separating reed beds and open water it now is possible to create
separate mass balances and study on process phenomena in reed beds and open
water.
Transport is on most of the locations and for most substances observed from a
process scale the main contributor. Algae bloom in the open water bodies of the
lakes is the exception and is for the greater part steered by nutrient availability (and
light climate).
The phosphorus release flux from the sediment may exceed the removal during long
periods with low water levels.
5–1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
5.2
Q3230
December, 2002
Recommendations
General model items:
• It is important that the possibilities and limitations of the model are discussed and
known to the people who use its results. It seems that several ecological studies
have been based on the model results, without taking into account these limitations.
• On the other hand, the present model is probably suitable to support more ongoing
surveys then is the case at present.
Hydrology model:
• At the moment there are 5 data loggers in the field (Uzlina-Gorgova district) which
will provide us with more detailed information regarding the water levels in the
district. It is strongly advised to compare these data with the modelled data by the
model for the same period. Adrian Constantinescu is fully capable performing this
task.
• During the June and September field missions cross section profiles were registered
while performing flow measurements. Compared with the cross sections in the
model, the areas seem to be significantly smaller. It is advised to check the cross
sections for the channels once more, especially at the entrances of river water to the
districts.
• The present model is able to provide its user with information for each lake on (1)
volumes in reed beds and open water, (2) exchange flows between reed and open
water in lakes (mainly driven by meteorology). If information on this is required,
the model may be a useful support tool, although the model has not been calibrated
on these flows (no measurements available).
Water Quality Model:
• The DANUBS application is more then sufficient for its goal (predicting nutrient
removal in the Lake districts on a large scale), the BLOOM application gives may
provide its user in insight in specific process influence and relevance. Models can
always be improved and developed further on. In our opinion the present model is a
very suitable tool to support others with information, which might be useful for
them. Especially the BLOOM application is and should give food to healthy
discussions. Possibly this will raise questions to the model and if necessary wishes
for further development or improvement.
• Especially the definition of the reed bed processes is very interesting for further
investigation.
• If the present BLOOM application is used for other years then 1997-1998 or for other
lake areas it is necessary to define new grazing biomasses as a function of time,
based upon monitoring data from DDNI’s laboratory.
• At present the model uses radiation data from Venice, due to lack of reliable own
data. Although nutrient availability seems to be the number one component in
limiting algae bloom, it is always prefered to use data from a meteorological station
nearby.
WL | Delft Hydraulics
5–2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
•
WL | Delft Hydraulics
Q3230
December, 2002
The BLOOM application has been applied for a 2-year simulation, the DANUBS
application for almost 10-year period. In the BLOOM application nutrient release
from sediments has been described. It might be that the release flux now is
overestimated, or the removal underestimated. This can be examined by performing
a long year simulation, which at present has not been done. If long year simulations
are wished, this has to be examined.
5–3
Hydrology and Water Quality Modelling in the Danube Delta
Part B
A000
Q3230
December, 2002
Update on DANUBS module description
processes
The model equations for the variables mentioned above include a number of processes from
SOBEK’s Processes Library, some of which are described below briefly. For a more
extended description we refer to the Theoretical Reference Manual (TRM) for the individual
processes of the Processes Library.
It should be noted that in the greater part of the Danube Delta area transport has the biggest
influence on the internal fluxes within the model. A good calibration of the hydrological
model therefore is a pre-condition for the calibration of the water quality model.
The most important processes in the DANUBS subset which are working on the variables
are presented in the table below.
Table a) The most important processes for the DANUBS subset.
Variable
OXY
(+/-)
+
+/+/+
+
+
-/+
+
+
+/+
+
NH4
NO3
PO4
AAP
Si
IM1
Diat
DetC,
DetSi
WL | Delft Hydraulics
DetN,
+/DetP,+
-
Processes acting on it
Denitrification in water column
Nitrification of ammonium
Reaeration of oxygen
Mineralisation detritus carbon
Sediment oxygen demand (additional)
Net primary production and mortality of algae
Nitrification of ammonium
Mineralisation detritus nitrogen
Uptake of nutrients by growth of algae
Release (nutrients/detritus) by mortality algae
Denitrification in sediment (N-Removal in reed beds)
Denitrification in water column (N-Removal in reed beds)
Nitrification of ammonium
Uptake of nutrients by growth of algae (although algae are NH4 preferent)
Ad(De)Sorption ortho phosphorus to inorg. Matter
Mineralisation detritus phosphorus
Uptake of nutrients by growth of algae
Release (nutrients/detritus) by mortality algae
Ad(De)Sorption ortho phosphorus to inorg. Matter
Sedimentation AAP (adsorbed PO4) Æ Removal of phosphorus
Mineralisation detritus silica
Uptake of nutrients by growth of algae
Sedimentation
Resuspension Æ only in lakes, as a zero order resuspension, for the rest
is sedimentation a removal flux (incl. AAP)
Net primary production and mortality green algae
Mineralisation detritus
Release (nutrients/detritus) by mortality algae
Sedimentation detritus carbon (removal of nutrients out of system)
A – 1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
The interactions between the different substances and the processes involved are also
presented in next figures.
N2
Denitrification
N2
NO3
Denitrification
in reed beds
Nitrification
Org-N
Mineralisation
(Det)
Growth
uptake
NH4
Algae
Growth
uptake
C:N:P:Si
(Diat)
Mortality
Sedimentation
Figure 1
Sedimentation
Nitrogen processes cycle in DANUBS subset (excl. transport and waste loads)
Reaeration
Det
c/n/p/si
Mineralisation
O2
Denitrification
NO3 --> N2
O2 consumption
Nitrification
O2 production
NH4 --> NO3
Algae
Sediment
oxygen use
AAP
(IM1)
Ad/desorption
PO4
Mineralisation
Org-P
(Det)
Growth
uptake
Algae
C:N:P:Si
(Diat)
Mortality
Sedimentation
Figure 2 Processes in the oxygen balance
Sedimentation
Figure 3 Phorphorus balance
More detailed information on the most important processes including some special remarks
regarding the DANUBS subset is given in Annexes A till D. For more detailed information
on the other processes reference is made to the SOBEK-WQ theoretical (or technical)
reference manual, or the SOBEK help files.
WL | Delft Hydraulics
A – 2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
coefficients
There are principally four types of process coefficients that may be specified in the model
input to be used in water quality modelling:
• model constants
• model parameters f(x)
• model functions f(t)
• segment functions f(x,t) (see section 2.2.4)
Constants are constant for the whole area to be modelled and do not differ in time.
Stoichiometric constants, temperature dependency constants for bacteriological processes and
solubility constants can be examples. They are specified as a number of single values, one for
each constant.
Most processes can be fine tuned using the constants in the equations governing the process.
In the table underneath an overview is given of the most relevant process constants of the
DANUBS subset that can be modified by the user (in the "Processes Library Coefficient
Editor").
The present values used in the DANUBS project are presented in table 4. Understanding the
parameter id’s of the water quality model is a matter of experience. However some
mnemomics for the user could be helpful for a start:
• Tc….
is always a Temperature Coefficient
• C….
is always a Critical variable (e.g. temperature or oxygen) coefficient
• Rc….
is always a reaction Rate Constant
• V….
is always related to a Velocity
• S1/S2
is always related to a Sediment layer 1 or 2 (note: no sediment in this
application)
• SW….
is always a switch to select a formula (the WQ library often offers different
formulas to compute a process(flux)
WL | Delft Hydraulics
A – 3
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Table b)
Q3230
December, 2002
Model constants
Model Parameter id
Description
Unit
phorphorus ad/desorption
SWAdsP
RcAdPO4AAP
KdPO4AAP
Switch formulation <0=Kd|1=Langmuir|2=GEM> Rate constant for adsorption PO4->AAP
1/d
Partition coefficient PO4-AAP
m3/gDM
Suggested
Value
0
0.5
1.0
nitrification/denitrification in surface water
RcDenWat
First-order denit. rate in water (N-removal)
TcDenWat
Temp. coefficient for denitrification
OOXDEN
Optimum oxygen conc. for denitrification
COXDEN
Critical oxygen conc. for denitrification
CTDEN
Ctritical temp. for denitrification
RcNit
First-order nitrification rate constant
TcNit
Temperature coefficient for nitrification
OOXNIT
Optimum oxygen conc. for nitrification
COXNIT
Critical oxygen conc. for nitrification
CTNit
Ctritical temperature for nitrification
1/d
g/m3
g/m3
oC
1/d
g/m3
g/m3
oC
f(x) – parameter
1.07
1
3
2
0.1
1.07
f(x) – parameter
f(x) – parameter
3
denitrification in sediment (reed bed N-removal)
ZDenSed
Zeroth-order denit. flux in bottom
RcDenSed
First-order denit. rate const. Bottom
TcDen
Temp. coefficient for denitrification
CTDen
Critical temperature for denitrification
gN/m2/d
m/d
degrees
0
f(x) – parameter
1.12
2
reaeration and sediment oxygen demand
SWRear
Switch for oxygen reaeration formulation <1-11>
KLRear
Reaeration transfer coefficient
TCRear
Reaeration temperature coefficient
fSOD
zeroth-order oxygen demand flux
RcSOD
decay reaction rate SOD at 20 oC
m/d
gO2/m2/d
1/d
4
f(x) – parameter
1.02
f(x) – parameter
0.1
sedimentation (in)organic matter (is removal in this application)
VSedDetC
sedimentation velocity DetC
TauCSDetC
critical shear stress sedimentation DetC
VSedIM1
sedimentation velocity IM1
TaucSIM1
critical shear stress sedimentation IM1
fResS1DM
resuspension flux dry matter from S1
SWTau
Switch <1=Tamminga|2=Bijker>
m/d
N/m2
m/d
N/m2
gDM/m2/d
-
f(x) – parameter
f(x) – parameter
f(x) – parameter
f(x) – parameter
f(x) – parameter
1
mineralisation organic matter
RcDetC
TcDetC
RcDetN
TcDetN
RcDetP
TcDetP
RcDetSi
TcDetSi
CTMin
1/d
1/d
1/d
1/d
oC
f(x) – parameter
1.08
f(x) – parameter
1.08
f(x) – parameter
1.08
f(x) – parameter
1.08
3
WL | Delft Hydraulics
first-order mineralisation rate constant
temperature coefficient for mineralisation
first-order mineralisation rate constant
temperature coefficient for mineralisation
first-order mineralisation rate constant
temperature coefficient for mineralisation
first-order mineralisation rate constant
temperature coefficient for mineralisation
critical temperature for mineralisation
A – 4
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Table b) (continued)
Q3230
December, 2002
Model constants
Model Parameter id
Description
Unit
Suggested
Value
Algae related coefficients
PPMaxDiat
MrespDiat
GrespDiat
Mort0Diat
PrfNH4diat
NCRatDiat
PCRatDiat
SCRatDiat
TcGroDiat
TcDecDiat
OptDLDiat
RadSatDiat
ExtVlDiat
ExtVlDetC
ExtVlIM1
ExtVlBak
pot. max. pr. prod. rc. diatoms st.temp
maintenance respiration diatoms st.temp
growth respiration factor diatoms
mortality rc of diatoms st. temp
ammonium preferency over nitrate diatatoms
Nitrogen-Carbon ratio in diatoms
Phosphorus-Carbon ratio in diatoms
Silicate-Carbon ratio in diatoms
temp. coeff. for growth processes diatoms
temp. coeff. for resp./mort. diatatoms
daylength for growth saturation diatoms
total radiation growth saturation diatoms
Vl specific extinction Diats
Vl specific extinction coefficent DetC
Vl specific extinction coefficent IM1
background extinction visible light
1/d
1/d
gN/gC
gP/gC
gSi/gC
d
W/m2
m2/gC
m2/gC
m2/gDM
1/m
2.3
0.036
0.11
0.3
1.0
0.16
0.02
0.49
1.06
1.05
0.65
90
0.3
0.47
0.03
f(x) – parameter
General other coefficients
Latitude
RefDay
Cl
latitude of study area (Danube Delta)
daynumber at start of the simulation
Chloride
degrees
d
g/m3
45
0
30.0
Notes:
• Some of the items in the table are printed bold; these are coefficients, which are either
specific for Romania (like the Latitude value), or used for the calibration procedure.
• Some of the coefficients in the table are defined as a parameter or function in the
DANUBS application. Nevertheless they are in this table to give an overview of the
most important process coefficients which are related to the processes mentioned.
Parameters are constant in time but may differ for the computational elements. If they are
used, they need to be specified for all computational elements or for element types. In the
Danube Delta model outline 4 geographically based surface water types have been defined, in
order to be able to define specific conditions for each type of water. In the DANUBS
application currently the parameter settings as presented in table c) are used:
WL | Delft Hydraulics
A – 5
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Table c).
Surface water types
KLRear
fSOD
ExtVLBak
VSedDetC
TauCSDetC
VSedIM1
TaucSIM1
fResS1DM
RcNit
COXNIT
OOXNIT
RcDenWat
RcDenSed
RcDetC
RcDetN
RcDetP
RcDetSi
Q3230
Parameter settings for DANUBS application
Normal
DanubeDistrictLakesriver
Channels
Open-water
1
1
1
1.5
0
0
0.5
0.5
1
1.5
1.5
1
0.03
0
0
0
0.001
0.001
0.001
1
0.5
0
0.1
0.1
0.01
0.01
0.01
10
0
0
0
2
0.1
0.1
0.1
0.1
1
1
1
1
5
5
5
5
0.1
0.1
0.1
0.1
0
0
0.01
0.01
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
December, 2002
Lakesreed
0
1
999
0.1
1
0.3
10
0
0.2
-1
0
0.2
0.06
0.2
0.2
0.2
0.2
These parameters are related to oxygen climate, light, sedimentation behaviour,
(de)nitrification and mineralisation.
Oxygen:
KLRear
fSOD
=
=
reaeration transfer coefficient.
zeroth order sediment oxygen demand flux
KLRear has been made space dependent (= parameter) to be able to define different
exchange velocities with the atmosphere. At present the reaeration formulation uses a scaled
version of the Connor O’ Dobbins equations to derive its exchange flux. The scale factor is
the KLRear. KLRear has a default value of 1 (which means the original Connor O’Dobbins
is used), but has been put to 0 in reed beds and uses a higher value for lakes. The zero value
is chosen to disable the exchange with the atmosphere in reed beds, because the surface
water is covered. The higher value for lakes is chosen to compensate for the extra exchange
caused by wind and waves, which is not part of the equation. (With respect to this formula
number 7 in the library would be more suitable for a model outline including rivers and
lakes, but with this formula it is impossible to switch of the rearation in reed beds).
fSOD, the additional sediment oxygen demand, has been made space dependent to be able
to reckon with different types of sediments. For example in a peat layer normally the
sediment oxygen demand will be higher in comparison with a mineral sediment type.
Light climate:
ExtVLBak
=
background extinction
ExtVLBak has been made space dependent to be able to include the effect of different
concentrations of humified acids and non modelled suspended particles on the light climate
and the effect of reed beds and other vegetation on the limitation of light availability for
algae bloom. The high value for reed beds is chosen to switch of all possibilities for algae
bloom in reed beds.
Sediment behaviour:
WL | Delft Hydraulics
A – 6
Hydrology and Water Quality Modelling in the Danube Delta
Part B
VSedDetC
TauCSDetC
VsedIM1
TauCSIM1
FResS1DM
=
=
=
=
=
Q3230
December, 2002
sedimentation velocity of detritus carbon
critical shear stress for sedimentation of detritus carbon
sedimentation velocity of inorganic suspended matter
critical shear stress for sedimentation of inorganic suspended matter
zero order resuspension flux
Regarding sedimentation it is assumed that organic matter only is due to sedimentation in
reed bed areas. Inorganic matter settles also in the channels and lakes (more or less to lose
adsorbed phosphorus), but has a higher sedimentation rate in reed beds.
Regarding the critical shear stress values of organic and inorganic matter reference is made
to the section “main characteristics”, “shear stress”. The higher value (factor 1000) is related
to the extreme value of the Manning roughness value, which has been used in lakes for the
calibration of the hydrology.
Finally, a resuspension flux has been introduced in the lakes. No sediment layer has been
modelled in this application, but is it known that resuspension due to wind does occur. In
this application it has been chosen to use a constant factor for resuspension. This eventually
results in a more constant suspended solids content in the lakes in comparison with the
monitoring data, but its goal is to model average values.
Nitrification and denitrification:
RcNit
=
first order nitrification rate
COXNit
=
critical oxygen content for nitrification
OOXNit
=
optimal oxygen content for nitrification
RcDenWat
=
first order denitrification rate for surface water
RcDenSed
=
first order denitrification rate for sediment
The nitrification rate in reed beds is assumed to be twice the rate of the surface water. Also,
with help of the COXNit and OOXNit values it has been adjusted for reed beds to have
nitrification in lower oxygen conditions in comparison with the open water (it is known that
the nitrification process continues due to transport of oxygen via the reed to the sediment
layer).
The denitrification rates in surface water and in sediments are used to simulate the nitrogen
removal in the districts. Most of the removal will be due to denitrification in reed beds,
explaining the higher values used in these cases. Using the 0.06 value for RcDenSed, the
removal fluxes as in the old application are approached.
Mineralisation:
RcDetC
=
RcDetN
RcDetP
=
RcDetSi
first order mineralisation rate for detritus carbon contents
=
first order mineralisation rate for detritus nirtrogen
first order mineralisation rate for detritus phosphorus
=
first order mineralisation rate for detritus silicate
For mineralisation regular literature values have been used. Only for reed beds higher values
have been chosen (to stimulate nutrient removal).
Functions are constant all over the area, but follow a prescribed sequence over time. Most
common examples are temperature and solar radiation, both defined within the Meteo data
task. No additional functions are used within the DANUBS application.
Table d).
Parameter id
WL | Delft Hydraulics
Model functions
Description
Recommended value
Unit
A – 7
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Temp
Rad
WL | Delft Hydraulics
Q3230
Water temperature
Solar radiation at the water surface
December, 2002
f(t)
f(t)
deg C
W/m2
A – 8
Hydrology and Water Quality Modelling in the Danube Delta
Part B
B000
Q3230
December, 2002
BLOOM subset details
Underneath more detailed information regarding the processes of the DDNI-BLOOM subset is given.
Nitrogen
N2
= Transport
Denitrification
N2
OON
NO3
Denitrification
in reed beds
DetN
Nitrification
Uptake
&Release
Mineralisation
NH4
Growth
uptake
Growth
uptake
Algae
Algae
Grazing by
zooplankton
C:N:P:Si
Resuspension
(2 diatoms)
Mortality
Mortality and
Grazing release
(3 greens)
(3 bluegreens)
Sedimentation
(3 microcystes)
Mineralisation
DetNS1
Burial
Substance
DetN
+
+
DetNS1
-
BLOOM_P
WM_DetN
SedN_Det
ResN_Det
CONSBL
SedDetC
BMS1_DetN
+
+
-
SedN_Det
SedPhBlo_P
ResN_Det
BurS1N_Det
+
CONSBL
NH4
+/-
BLOOM_P
+
Nitrif_NH4
BMS1_DetN
+
+
+/-
WM_DetN
WM_OON
GroMrt_DS1
+
WL | Delft Hydraulics
Processes
CONSBL
Description
Detritus Nitrogen (DetN)
BLOOM II algae module
Mineralisation detritus nitrogen
Sedim. Nutrients in detritus
Resuspension nutrients in detritus
Grazing module
Sedimentation detritus carbon
DetN in sediment 1
Mineralisation detritus nitrogen in
sediment S1
Sedim. nutrients in detritus
Sum sedimentation of algae – Bloom
Resuspension nutrients in detritus
Burial nutrients in detritus from
sediment S1
Grazing module
Ammonium (NH4)
BLOOM II algae module
unit
(gN/m3)
remark
(gN)
(gN/m3)
+ autolysis, - primary
production
Nitrification of ammonium
Mineralisation detritus nitrogen in
sediment S1
Mineralisation detritus nitrogen
Mineralisation other organic nitrogen
Nett primary production and mortality
diatoms
Grazing module
B – 1
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Substance
NO3
+
+/OON
+
-
Q3230
December, 2002
Processes
Description
Nitrate (NO3)
BLOOM_P
BLOOM II algae module
DenSed_NO3 Denitrification in sediment
DenWat_NO3 Denitrification in water column
Nitrif_NH4
Nitrification of ammonium
GroMrt_DS1 Nett primary production and
mortality diatoms
Other Organic Nitrogen (OON)
BLOOM_P
BLOOM II algae module
WM_OON
Mineralisation other organic
nitrogen
SedN_OOC
Sedim. nutrients in OOC
Sed_OOC
BLUEGRN
FDIATOMS
GREENS
MICROCY
S
+/BLOOM_P
-
SEDALG
-
CONSBL
unit
(gN/m3)
remark
(gN/m3)
sedimentation of other organic
matter is zero
sedimentation of other organic
matter is zero
Sedimentation other organic carbon
Blue green algae
Freshwater diatoms
Green algae
Microcystis
(gC/m3)
(gC/m3)
(gC/m3)
(gC/m3)
BLOOM II algae module
+ primary production, - mortality
& respiration
sedimentation of other organic
matter is zero
Sedimentation of algae species
Grazing module
Phosphorus
= Transport
PAP
Decay
OOP
Uptake
&Release
NH4
PO
Mineralisation
DetP
Ad/desorption
IM1
IM2
Growth
uptake
AAP
Mortality
release
Algae
Algae
(2 diatoms)
Sedimentation /
Resuspension
Desorption
and release
(3 greens)
(3 bluegreens)
(3 microcystes)
IM1S1 AAPS1
IM2S1
Burial
WL | Delft Hydraulics
Mineralisation
Grazing by
zooplankton
C:N:P:Si
Resuspension
Mortality
Sedimentation
DetPS1
Burial
B – 2
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
substance Processes description
unit
Remark
AAP
adsorbed ortho phosphorus
(gP/m3)
+/AdsPO4AA Ad(De)Sorption ortho phosphorus
P
to inorg. matter
Sed_AAP Sedimentation AAP (adsorbed
PO4)
+
Res_AAP Resuspension AAP (adsorbed PO4)
AAPS1
adsorbed O-PO4 in sediment 1
(gP)
Deso_AAP Desorption of adsorbed phosphates
S1
in sediment S1
+
Sed_AAP Sedimentation AAP (adsorbed
PO4)
+
Sed_PAP Sedimentation PAP (adsorbed
PO4)
Res_AAP Resuspension AAP (adsorbed PO4)
BurS1_AA Burial of AAP (adsorbed PO4)
P
from sediment S1
DetP
Detritus phosphorus (DetP)
(gP/m3)
+
BLOOM_P BLOOM II algae module
WM_DetP Mineralisation detritus phosphorus
SedN_Det Sedim. nutrients in detritus
+
ResN_Det Resuspension nutrients in detritus
+
CONSBL Grazing module
SedDetC Sedimentation detritus carbon
DetPS1
DetP in sediment layer 1
(gP)
BMS1_Det Mineralisation detritus phosphorus
P
in sediment S1
+
SedN_Det Sedim. nutrients in detritus
+
SedPhBlo_PSum sedimentation of algae Bloom
ResN_Det Resuspension nutrients in detritus
BurS1N_De Burial nutrients in detritus from
t
sediment S1
CONSBL Grazing module
OOP
Other Organic Phosphorus (OOP) (gN/m3)
+
BLOOM_P BLOOM II algae module
WM_OOP Mineralisation other organic
phosphorus
SedN_OOC Sedim. nutrients in OOC
sedimentation of other organic
matter is zero
Sed_OOC Sedimentation other organic carbon
sedimentation of other organic
matter is zero
PAP
adsorbed ortho phosphorus
(gP/m3)
(irreversible)
WM_PAP Mineralisation (desorption)
irreversible particula
Sed_PAP Sedimentation PAP (adsorbed
PO4)
PO4
Ortho Phosphorus (O-PO4)
(gP/m3)
+/BLOOM_P BLOOM II algae module
+ autolysis, - primary
production
+/AdsPO4AA Ad(De)Sorption ortho phosphorus
P
to inorg. matter
+
WM_PAP Mineralisation (desorption)
irreversible particula
WL | Delft Hydraulics
B – 3
Hydrology and Water Quality Modelling in the Danube Delta
Part B
Q3230
December, 2002
substance Processes
+
BMS1_Det
P
+
Deso_AAP
S1
+
WM_DetP
+
WM_OOP
description
unit
Remark
Mineralisation detritus phosphorus
in sediment S1
Desorption of adsorbed phosphates
in sediment S1
Mineralisation detritus phosphorus
Mineralisation other organic
phosphorus
+/GroMrt_DS Nett primary production and
1
mortality diatoms
+
CONSBL Grazing module
Blue green algae
(gC/m3)
BLUEGR
N
FDIATOM
Freshwater diatoms
(gC/m3)
S
GREENS
Green algae
(gC/m3)
MICROCY
Microcystis
(gC/m3)
S
+/BLOOM_P BLOOM II algae module
+ primary production, mortality & respiration
SEDALG Sedimentation of algae species
sedimentation of other organic
matter is zero
CONSBL Grazing module
IM1
inorganic matter (IM1)
(gDW/m
3)
Sed_IM1 Sedimentation IM1
+
Res_IM1 Resuspension 1th inorganic matter
IM1S1
IM1 in sediment 1
(gDW)
+
Sed_IM1 Sedimentation IM1
Res_IM1 Resuspension 1th inorganic matter
BurS1_IM1 Burial 1th-inorganic matter from
S1
IM2
inorganic matter (IM2)
(gDW/m
3)
Sed_IM2 Sedimentation IM2
+
Res_IM2 Resuspension 2th inorganic matter
IM2S1
IM2 in sediment 1
(gDW)
+
Sed_IM2 Sedimentation IM2
Res_IM2 Resuspension 2th inorganic matter
BurS1_IM2 Burial 2th inorganic matter from S1
Oxygen
OXY
+/- BLOOM_P
+
DenWat_NO
3
- Nitrif_NH4
+/- RearOXY
- BMS1_DetC
-
WL | Delft Hydraulics
WM_DetC
WM_OOC
Oxygen
BLOOM II algae module
(g/m3)
+ primary production, - mortality &
respiration
Denitrification in water column
Nitrification of ammonium
Reaeration of oxygen
Mineralisation detritus carbon in
sediment S1
Mineralisation detritus carbon
Mineralisation other organic
carbon
B – 4