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Susan Strömbom

EXAMENSARBETE TRITA-KET-IM 2004:16

STOCKHOLM 2004

O NE - DIMENSIONAL M ODELING OF M ACROBYTE

GROWTH - part of the study Macrophytes

and nutriments Dynamics in the upper-

reaches of the Scheldt Bassin

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Abstract

Massive macrophyte development in the Flemish running waters in the northern part of Belgium is a result of the improved water quality regarding organic loads in combination with a continuous high nutrient input. Since the macrophytes, higher aquatic plants with roots and stems, are contributing to the flooding problem in the Flemish regions by raising the water level in rivers where the water level already is high, the macrophyte management is an important issue in the Flemish areas.

There are few existing studies of the influence of macrophytes on the nutrient dynamics in running waters. Several studies indicate however that macrophytes act as a biological filter, lowering the nutrient concentrations in the flowing waters. This would mean that the macrophyte communities would contribute to a biological cleaning of the water masses, playing a part in the solution of the eutrophication problem in the estuary.

This study is a part of a project stretching over 3 years, which in the end will result in a predictive tool for macrophyte management, taking into account the risk of flooding as well as the possible filtering effect of the macrophytes. The Mike 11 software from DHI in Denmark is used to simulate the longitudinal hydrodynamics and transport properties of a small river reach of the Aa-river. An integrated process modeling tool in the Mike software, the Ecolab modeling tool, is used to build up the biogeochemical model. This will result in a realistic description of the macrophyte growth in the near future, in particular regarding its influence on the nutrient dynamics.

At this stage, it is possible to describe the hydrodynamics well for a typical winter period, whereas the hydrodynamic description is more complex during the summer period due to macrophyte growth. More data are required to have a precise description of the hydrodynamics in the summer, and for the validation of the hydrodynamics in the winter. The transport properties of the river reach should be further validated using conductivity data and results from tracer studies for high and low flow discharges, and the influence of the dead- zones will be further investigated using a stochastic one-dimensional model. The biochemical model set-up is only in the starting phase, and process studies of the nutrient uptake by the macrophytes have to be undertaken in order to further develop the biochemical model.

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Table of Contents

1 INTRODUCTION ... 8

2 DESCRIPTION OF THE NETE AND THE AA RIVER SYSTEM ... 11

2.1 THE NETE BASIN 11 2.2 THE TEST RIVER-REACH 15 2.2.1 Hydrological description... 15

2.2.2 Biochemical description... 16

3 THE HYDRODYNAMICS OF THE RIVER SYSTEM ... 25

3.1 EVALUATION OF HYDRODYNAMIC DATA 25 3.1.1 Data used in the hydrodynamic simulation... 25

3.1.2 Macrophyte influence on the water velocity ... 31

3.2 THE MIKE 11 HYDRODYNAMIC SIMULATION 35 3.2.1 Bathymetry ... 36

3.2.2 The Saint Venant Equations ... 38

3.2.3 Model parameters ... 39

3.2.4 Boundary and initial conditions... 40

3.2.5 Model stability condition... 43

3.3 RESULTS 44 3.3.1 Results from the historical data ... 44

3.3.2 Results from the wave simulation... 47

4 THE ADVECTIVE-DISPERSIVE TRANSPORT ... 49

4.1 INTRODUCTION 49 4.2 THE SIMPLE ADVECTION-DISPERSION MODEL FOR PREPARATION OF A TRACER STUDY 50 4.2.1 Calculation of distance from the injection point to the first measuring station.. 51

4.2.2 Calculation of mass to be injected in the tracer study ... 52

4.3 THE MIKE 11 ADVECTION-DISPERSION MODEL SET UP 54 4.3.1 The continuity and advection-dispersion transport equation ... 54

4.3.2 Model parameter ... 55

4.3.3 Boundary and initial conditions... 55

4.3.4 Model stability conditions ... 56

4.3.5 Results ... 57

5 WATER-QUALITY DESCRIPTION ... 62

5.1 WATER QUALITY DATA INTERPRETATION 62 5.1.1 Oxygen concentration ... 62

5.1.2 Macrophyte and phytoplankton concentration ... 66

5.2 THE MIKE WATER-QUALITY SET-UP IN ECOLAB 70 5.2.1 Introduction... 70

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5.2.10 The equations for the state variables ... 80

5.2.11 Boundary conditions ... 81

5.2.12 Results ... 83

6 DISCUSSION ... 86

6.1 THE HYDRODYNAMIC PART 86 6.2 THE ADVECTION-DISPERSION PART 87 6.3 THE WATER-QUALITY PART 88 6.4 TO BE DONE 90 7 CONCLUSIONS... 91

8 APPENDIX 1 ... 95

9 APPENDIX 2 ... 108

Table of figures

FIGURE 1. MAP OF THE THREE CATCHMENT AREAS [12] ... 11

FIGURE 2. MAP OF THE MOST IMPORTANT RUNNING WATER AND CHANNELS OF THE NETE AREA [12]... 12

FIGURE 3. MAP OF THE KEMPISCH LOWPLAIN AND THE KEMPISCH PLATEAU RESPECTIVELY [12] 13 FIGURE 4. CATTLE DIKE AT TURNHOUT, YEAR 1865 AND CATTLE DIKE AT TURNHOUT, YEAR 1990 RESPECTIVELY [12] ... 14

FIGURE 5. THE OVERFLOW STRUCTURE THAT IS SITUATED IN THE BEGINNING AND THE END OF THE TEST RIVER REACH... 15

FIGURE 6. SCANNED MAP OF THE TEST RIVER REACH WITH ITS NEAR ENVIRONMENT... 16

FIGURE 7. HISTORICAL DATA FOR THE BIOLOGICAL OXYGEN DEMAND IN THE RIVER REACH. 17 FIGURE 8. HISTORICAL DATA FOR THE CHEMICAL OXYGEN DEMAND IN THE RIVER REACH.... 17

FIGURE 9. HISTORICAL DATA FOR THE DISSOLVED OXYGEN CONCETRATION IN THE RIVER REACH 18 FIGURE 10. HISTORICAL DATA FOR THE NITRATE CONCENTRATIONS IN THE RIVER REACH.. 19

FIGURE 11. HISTORICAL DATA FOR THE AMMONIUM CONCENTRATIONS IN THE RIVER REACH 19 FIGURE 12. HISTORICAL DATA FOR THE INORGANIC NITROGEN CONCENTRATION IN THE RIVER REACH... 20

FIGURE 13. HISTORICAL DATA FOR THE ORTHO-PHOSPHATE CONCENTRATION IN THE RIVER REACH 21 FIGURE 14. HISTORICAL DATA FOR THE TOTAL PHOSPHORUS CONCENTRATION DEMAND IN THE RIVER REACH... 21

FIGURE 15. MACROPHYTE BIOMASS EVOLUTION IN THE RIVER REACH FOR 2003... 23

FIGURE 16. EVOLUTION OF THE PLANT SPECIES DURING THE SEASON 2003 ... 23

FIGURE 17. POTAMOGETON PECTINATUS... 24

FIGURE 18. SPARGANIUM EMERSUM... 24

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FIGURE 24. COMPARISON OF THE DISCHARGE OBTAINED FROM THE Q/H RELATION AND THE DISCHARGE OBTAINED FROM THE CORRELATION EQUATION... 28 FIGURE 25. THE POSITION OF THE MEASURING POLES ALONG THE RIVER REACH... 29 FIGURE 26. THE WATER LEVEL WITH THE DISTANCE FROM THE UPSTREAM STATION, STATION

3 30

FIGURE 27. THE WAVE ELEVATION AT VARIOUS DISTANCES FROM THE UPSTREAM STATION

(STATION 3) ... 31 FIGURE 28. TYPICAL FLOW PROFILE IN AN OPEN CHANNEL [4]... 32 FIGURE 29. THE PRINCIPLE FOR THE VELOCITY PROFILE MEASUREMENT IN AUGUST AND

NOVEMBER 2003... 32 FIGURE 30. VELOCITY PROFILE AT STATION 3 IN AUGUST 2003 ... 33 FIGURE 31. VELOCITY PROFILE THE 5-6 OF NOVEMBER 2003 AT STATION 3 ... 33 FIGURE 32. THE DISTRIBUTION OF MACROPHYTE WET WEIGHT WITHIN THE SECTION AT

STATION 3... 34 FIGURE 33. WET WEIGHT OF MACROPHYTES PER SQUARE METER IN 2003 AT STATION 3, AT

THE MIDDLE STATION AND AT STATION 4... 35 FIGURE 34. CROSS-SECTIONS OF THE DOWNSTREAM PART OF THE RIVER REACH... 37 FIGURE 35. THE PLACEMENT OF THE RESULT GRID ALONG THE RIVER REACH... 38 FIGURE 36. TIME-SERIES USED AT THE UPSTREAM AND DOWNSTREAM BOUNDARY FOR THE

SIMULATION OF THE UPSTREAM WATER LEVEL AT STATION 3 FOR A TYPICAL SUMMER PERIOD 41

FIGURE 37. TIME-SERIES USED AT THE UPSTREAM AND DOWNSTREAM BOUNDARY FOR THE SIMULATION OF THE UPSTREAM WATER LEVEL AT STATION 3 FOR A TYPICAL WINTER PERIOD 41

FIGURE 38. BOUNDARY CONDITION FOR THE DISCHARGE RESULTING IN A WATER ELEVATION THAT RESSEMBLES THE EXPERIMENTAL WATER ELEVATION AT 10 M... 42 FIGURE 39. SIMULATION OF THE UPSTREAM WATER LEVEL FOR QUASI-STEADY AND

UNSTEADY SIMULATION MODE... 44 FIGURE 40. JANUARY 2000: SIMULATION OF THE UPSTREAM WATER LEVEL FOR DIFFERENT

MANNING NUMBERS... 45 FIGURE 41. JANUARY 2001: SIMULATION OF THE UPSTREAM WATER LEVEL FOR DIFFERENT

MANNING NUMBERS... 45 FIGURE 42. FEBRUARY 2001: SIMULATION OF THE UPSTREAM WATER LEVEL FOR DIFFERENT

MANNING NUMBERS... 46 FIGURE 43. AUGUST 1999: SIMULATION OF THE UPSTREAM WATER LEVEL FOR DIFFERENT

MANNING NUMBERS... 46 FIGURE 44. PROPAGATING WAVE AND THE BACK WAVE... 47 FIGURE 45. CONDUCTIVITY MEASUREMENT IN NOVEMBER AT STATION 3 AND STATION 4 .. 50 FIGURE 46. THE RESULTING CONCENTRATION CURVES AT DIFFERENT DISTANCES FROM

STATION 3... 53 FIGURE 47. UPSTREAM BOUNDARY CONDITION FOR THE ADVECTIVE-DISPERSIVE SIMULATION

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FIGURE 52. SIMULATED CURVES IN MIKE 11 SHIFTED TO FIT THE EXPERIMENTAL PEAK AT

STATION 4 FOR THE 5-6 OF NOVEMBER 2003 ... 59

FIGURE 53. SIMULATION IN MIKE 11 FOR DL = 2 THE 21 TO 28 OF APRIL 2004... 60

FIGURE 54. SIMULATION IN MIKE 11 FOR DL = 3 THE 21 TO 28 OF APRIL 2004 ... 60

FIGURE 55. SIMULATION IN MIKE 11 FOR DL = 4 THE 21 TO 28 OF APRIL 2004 ... 61

FIGURE 56. SIMULATION IN MIKE 11 FOR DL = 5 THE 21 TO 28 OF APRIL 2004 ... 61

FIGURE 57. DATA ACQUISITION AT STATION 3 OF OXYGEN CONCENTRATION AND TEMPERATURE... 63

FIGURE 58. PERCENT OF OXYGEN SATURATION AT STATION 3 AND STATION 4 THE 21-22 OF AUGUST 2003... 64

FIGURE 59. PERCENT OF OXYGEN SATURATION AT STATION 3, THE MIDDLE STATION AND AT STATION 4 THE 5-6 OF NOVEMBER 2003 ... 64

FIGURE 60. OXYGEN PROFILE IN THE EVENING THE 21 AND IN THE MORNING THE 22 OF AUGUST 2003... 65

FIGURE 61. OXYGEN SATURATION CONCENTRATION AT STATION 3 AND STATION 4 THE 22-28 OF AUGUST 2003... 66

FIGURE 62. THE DISTRIBUTION OF THE SAMPLING ALONG THE CROSS-SECTIONS AND THE RIVER REACH, MADE BY SOFIE VAN BELLEGHEM AT THE UNIVERSITY OF ANTWERP... 67

FIGURE 63. EVOLUTION OF THE MACROPHYTE SPECIES IN THE RIVER REACH FOR 2003 ... 68

FIGURE 64. THE CHLOROPHYLL AAND PHAEOPIGMENT CONCENTRATION THE 21-22 OF AUGUST 2003... 69

FIGURE 65. THE CHLOROPHYLL ACONCENTRATION THE 5-6 OF NOVEMBER 2003 ... 69

FIGURE 66. THE SIMPLIFIED MACROPHYTE LIFE CYCLE... 71

FIGURE 67. AN OVERVIEW OF THE RELATION BETWEEN THE STATE VARIABLES, THE PROCESSES, THE AUXILIARY VARIABLES, THE CONSTANTS AND THE FORCINGS... 72

FIGURE 68. IMPLEMENTED PROCESSES IN THE MACROPHYTE LIFE CYCLE... 73

FIGURE 69. THE RATE FOR PRIMARY PRODUCTION AS A FUNCTION OF THE SOLAR IRRADIATION... 76

FIGURE 70. THE LIGHT AVAILABLE FOR MACROPHYTE GROWTH... 77

FIGURE 71. UPSTREAM BOUNDARY CONDITIONS USED AT STATION 3 FOR THE OXYGEN CONCENTRATION VERSUS REAL-TIME DATA... 82

FIGURE 72. MACROPHYTE BIOMASS FROM FIELD DATA INVENTORY VERSUS IN ECOLAB SIMULATED ACTIVE AND INACTIVE BIOMASS... 83

FIGURE 73. DEGRADABE ORGANIC MATTER AND LABILE ORGANIC MATTER (LOM) SIMULATED IN ECO-LAB... 84

FIGURE 74. DEGRADABLE ORGANIC MATTER (DOM), DIN AND DIP SIMULATED IN ECO- LAB 85 FIGURE 75. DATA ACQUISITION VERSUS SIMULATED OF DISSOLVED OXYGEN AT STATION 3 AND STATION 4 FOR THE 22-28 OF APRIL 2004 ... 85

FIGURE 76. PERCENTAGE OF DIFFERENT MACROPHYTE TYPES IN THE SUMMER OF 2003... 89

FIGURE 77. NITRATE CONCENTRATION, 21-22 OF AUGUST 2003... 97

FIGURE 78. AMMONIUM CONCENTRATION, 21-22 OF AUGUST 2003... 97

FIGURE 79. NITRATE CONCENTRATION 5-6 OF NOVEMBER 2003 ... 98

FIGURE 80. SHIFTED CURVE OF NITRATE CONCENTRATION, 21-22 OF AUGUST 2003... 99

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FIGURE 85. SHIFTED CURVE OF ORTHO-PHOSPHATE CONCENTRATION, 5-6 OF NOVEMBER

2003 101

FIGURE 86. PH THE 21-22 OF AUGUST AT STATION 3... 103

FIGURE 87. PH THE 5-6 OF NOVEMBER AT STATION 3... 103

FIGURE 88. TOTAL ALKALINITY THE 21-22 OF AUGUST 2003... 104

FIGURE 89. TOTAL ALKALINITY THE 5-6 OF NOVEMBER 2003... 105

FIGURE 90. LONGITUDINAL ALKALINITY PROFILE IN THE EVENING THE 21 OF AUGUST AND IN THE MORNING THE 22 OF AUGUST... 105

FIGURE 91. THE SUSPENDED PARTICULATE MATTER AT STATION 3 AND 4 THE 21-22 OF AUGUST 2003 WITH STANDARD DEVIATION INDICATED... 106 FIGURE 92. THE SUSPENDED PARTICULATE MATTER AT STATION 3, AT THE MIDDLE STATION

AND AT STATION 4 THE 5-6 OF NOVEMBER 2003 WITH STANDARD DEVIATION INDICATED

107

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1 Introduction

Eutrophication is the result of high nutrient input into aquatic ecosystems. It is characterized by a massive biomass production due to the photosynthetic activity of the primary producers.

Eutrophication can lead to toxic algal bloom, reduced biodiversity and the occurrence of anoxic conditions associated with the degradation of the dead biomass. Reducing the high nutrient loading requires controlling point and diffusing sources, especially by wastewater treatment. In this way, the primary production is limited and anoxic conditions prevented, on a long term leading to a higher biodiversity.

In the aquatic environment, primary producers may consist of phytoplankton, such as algae, occurring mainly in the water column and of higher aquatic plants, the so-called macrophytes, which grow in the shallowest parts of the water stream. The phytoplankton is small enough to remain in the water column and is therefore transported with the current, whereas the dominant macrophyte species in streams are rooted in the sediment [23].

The issues of macrophyte management

Aquatic plants such as macrophytes are a necessary component of a healthy ecosystem.

Macrophytes provide food, protective cover and spawning areas for fish, habitat for insects and snails, and food and nesting material for waterfowl. Rooted plants also help stabilizing the river bottom. Aquatic plants near riverbanks protect against erosion by calming waves and stabilizing shoreline soils. All aquatic plants provide oxygen and organic matter to other river organisms. In addition, macrophytes play a role in the nutrient retention- not only as the result of nutrient uptake for biomass growth, but also by increasing the sedimentation rate [21].

Their development can therefore be a way to control the nutrient concentration in rivers.

However, an excessive growth of plants can have a negative effect on the river organisms, ecology and human use. Massive development of macrophytes may decrease the amenity value of the watercourses by limiting or preventing leisure activities such as swimming, rowing and fishing. In the Flemish region, one of the main concerns related to excessive macrophyte growth is the increased risk of flooding due to a rise in water level [26].

This flooding problem is an important issue in the Flemish region due to a number of reasons.

A large number of rivers have been affected by the consequences of urbanization and other changes in land use. In particular, river straightening has been largely applied for the purpose of rapid water withdrawal, presumably an effective way to control flooding. By doing so, the problem has actually been displaced downstream, where the risk of flooding has become higher due to the decreased damping of the upstream river system. In addition, the decrease in wetland surface area, as a result of agricultural expansion, contributes also to an enhanced risk of flooding, as wetlands act as damping zones for flood waves [26]. Finally, it is feared that climate change might result in more extreme weather conditions, causing heavy storms and rainfalls that can result in extreme flooding events. All these factors make the issue of flood control more and more critical. Up to now, the response to the problem has mainly consisted

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both the water column and the sediments and the sediments act as a reserve of nutrients, it is not easy to deduce the relationship between the macrophyte abundance and the reduction in nutrient concentration in the water column. The uptake and release path and rate of nutrient uptake and release by the macrophytes has to be further investigated [8] to quantify the macrophyte impact on the reduction of nutrients in the outgoing water.

The question is thus how macrophyte management should be accomplished in an economic way to the satisfaction of all interest groups, taking into account the risk of flooding, the reduction of the eutrophication problem, the leisure activities, and the conservation of an ecosystem of high biodiversity. To achieve these objectives, alternative actions are possible, such as partial removal, introduction of trees on the riverbanks to decrease the sunlight available to macrophytes and hence limit their growth.

The problematic in the Scheldt estuary and its tributaries

The Scheldt river course has a length of 335 km. It flows from Saint-Quentin in France to the North Sea near Vlissingen in the Netherlands. The Scheldt catchment is highly populated with about 10.5 million people living in the area. The largest cities are Antwerp, Gent, Brussels and Lille in France [25].

The human activity within the drainage area is one of the main contribution to the very high nutrient load into the Scheldt basin, but there is also a retention or elimination of nutrients within the river basin. About 50 % of the nitrogen input to the Scheldt basin is removed, mainly by denitrification. The same amount of phosphorus is removed, likely due to sedimentation before reaching the North Sea. The Scheldt basin has also a very high input of organic matter, resulting in intense oxygen consumption due to heterotrophic respiration [23].

During the last ten years, considerable efforts have been made in the implementation of primary and secondary treatment in an increasing number of wastewater treatment plants (WTP). The result has been an improvement of the water quality with respect to organic matter and suspended solids in most tributaries of the Scheldt. However, the nutrient load (i.e.

nitrogen and phosphorous) originating from WTP effluents and from diffuse (mostly agricultural) sources remains important. This has led to an enhanced primary production of macrophytes in the headwaters. As a consequence, a large quantity of organic matter is internally produced in the tributaries of the Scheldt basin.

The Manudyn-study

The Manudyn study, extending over three years, aims at investigating the role of macrophytes in the retention and transformation of nutrients in the upper catchment of the Scheldt basin, looking at the Nete sub-basin as a test catchment.

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• to design a good management of the Scheldt basin on a long term, taking into account criteria such as amenity value, nutrient retention, biodiversity, ecological quality criteria and flood management.

The project is designed to combine field studies at a test river site with laboratory experiments. It includes the study of the temporal biomass development of macrophytes over the full growth season. Nutrient retention by macrophytes and nutrient delivery by the sediments will be investigated by flume experiments under controlled conditions, taking into account parameters such as the stream velocity and macrophyte abundance. The nutrient uptake by macrophytes is evaluated by in situ nutrient mass balance studies, comparing the nutrient situation with and without macrophytes. Further details about the study can be found at the following URL: http://www.belspo.be/belspo/fedra/proj.asp?l=en&COD=EV/33#descr The overall project will result in a descriptive model, in a first step only including a smaller tributary (the Aa river), but extending to include the entire Nete basin at the end of the study.

After validation, the model should be used for predictive purposes, to help selecting among management options in the Nete basin, especially regarding the management of macrophytes.

Participating in the project are researchers from the Universiteit Antwerpen (UA), the Vrije Universiteit Brussel (VUB) and the Université Libre de Bruxelles (ULB). The ULB partner is mainly contributing with the modeling tool, but is also participating in the field and laboratory studies.

This study

My task within the project, in the frame of the ULB part, is to contribute to the set up of a one-dimensional water-quality model for a small river reach, a tributary to the Kleine Nete River, using an existing modeling tool (Mike 11 software from DHI, Denmark). The model includes hydraulic and transport parameters as well as biological parameters and processes and will be used to test the validity of the chosen process formulations and rates.

The hydraulic and transport modeling part consists of estimating the roughness and dispersion coefficient for the river reach. For the biogeochemical part of the model, a process-modeling tool integrated in the MIKE software is used, where the user chooses which processes to include and where he formulates his own rate equations. This method was chosen since the already existing water-quality simulation tool (eutrophication editor) has a limited modeling capacity for the macrophyte influence on the nutrient dynamics in the system, which is the main concern of the project. Choosing the convenient processes, constants and rates is thus necessary to construct the biogeochemical model. The model will later on be extended to include the Kleine Nete basin.

In the following text subjects will be treated in the following order:

• Description of the modeling site, where historical and recent data are analyses to have

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2 Description of the Nete and the Aa river

system

2.1 The Nete basin

The basin of the Nete is one of 11 river catchment of the Flemish region, and belongs to the northern part of the Scheldt basin. The Flemish region is situated in the north-western part of Belgium. The Nete river consists of two sub-basins: the Kleine Nete and the Grote Nete. The Nete basin is limited by the basin of the Meuse in the north and east, the basin of the Demer in the south and the basin of the Beneden Scheldt (lower Scheldt) river in the west. Total surface area of the catchment is 1673 km2 and the population living in the catchment area consist of about 600.000 people. The main cities are Turnhout, Herentals, Lier and Geel [12].

Figure 1. Map of the three catchment areas [12]

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Figure 2. Map of the most important running water and channels of the Nete area [12]

The main part of the watercourses of the Nete basin are in general lowland watercourses and the soil has a silty to sandy character. The Nete basin is in fact a part of the low plain of the Kempen-area, where the topography is rather flat. The rivers in the Nete basin are not very deep and have a small slope and a limited velocity, which give them a strong meandering character already in the upstream zone, i.e. from the beginning of the river system. A small part of the eastern Nete basin is included in the Kempen plateau, which has a higher topography than the rest of the Kempen area since it is situated close to the Ardennes, the hills in the southeast of Belgium. In the Kempen plateau the Grote Nete together with a number of tributaries have their source, all flowing along a gentle slope down to the Kempisch lowplain.

The Kempen plateau is covered with a thick layer of gravel covered with sand and the vegetation consist predominantly of forest and the cross-leaved heather [12].

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Figure 3. Map of the Kempisch lowplain and the Kempisch plateau respectively [12]

The watercourses of the Nete have almost no real point sources. In both the Kleine and the Grote Nete more than 60 percent of the total flow is coming from the vadose zone (the part of the underground water that is not the groundwater). Fed through a network of ditches (artificial ditches, made to drain the water from the agricultural zone) the runoff water is gathered principally from the precipitation/rainwater and seeping water. The temporary high flow is thus not due to the groundwater delivery, but to precipitation. Successive peak flow, due to precipitation, can superpose and the water level stays hence high for a long time.

During long dry periods however the upstream rivers and the smaller rivers can dry out [12].

The mean yearly discharge of the Grote Nete in the city of Hulshout is 5.2 m3/s. There are considerable deviations in the discharge at the daily or even hourly time-scale. A large part of the Nete basin has to deal with exceeding water flow. The main origin is of course high precipitation, which is reinforced by the fact that the soil nowadays has a decreased infiltration rate. The decreased infiltration rate is due to a modified soil usage and that an increased amount of the soil surface has been transformed into a hardened constructed

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• Type 2: Larger river with a water width of 6-9 meter. On the contrary to type 1, these rivers goes seldom dry.

• Type 3: has a mean width of 15 meters and depth greater than 1 m. The Grote and the Kleine Nete belongs to this category and they join each other to form the so-called Beneden-Nete (Lower-Nete).

• Type 4: is the tidal zone of the Nete rivers with a mean width between 35-60 m and a water depth up to 3 m. The Kleine Nete is affected by the tide up to the city of Grobbendonk and the Grote Nete is affected up to the city of Itegem [12].

The water, not perturbed by human activity, is strongly influenced by the valley. The water is generally quite acid and relatively poor in mineral content. However some rivers are influenced by deeper groundwater or by canal water from the river Meuse, which causes an increase in the mineral content. The water quality of the Nete basin is relatively good in comparison with other part of the Flemish region (Vlanders) as wastewater treatment plants have been constructed rather early in connection to the Nete basin. The first one in Turnhout started in 1958, in 1980 19 treatment plants were operational in connection to the Nete basin and in 2000 the number of treatment plants was increased to 29.

Aerial photos together with historical maps illustrate in a good way how human influence on the river system causes large perturbation of the natural relationship between the river and its valley.

Figure 4. Cattle Dike at Turnhout, year 1865 and Cattle Dike at Turnhout, year 1990 respectively [12]

The land use has led to a decrease/disappearance of the meandering by straightening of the river system. The reinforcement and/or the construction of dikes that were performed in order to increase the level of protection against flooding, makes it more difficult for the tributaries to flow into the main river and it increases the danger of flooding downstream. The risk of flooding in the tributary rivers increases also due to construction of the sluices and dams. The issue of flood protection and flood control is in other words an important problem in these lowlands. To avoid flooding there is therefore a need for a new infrastructure such as

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2.2 The test river-reach

2.2.1 Hydrological description

The Aa-river is one of the main tributaries to the Kleine Nete-river. The Aa-river is of the morphological type 2, which means that the maximum water depth is about 1 m at normal flow conditions with a mean annual flow of 2 m3/s and an average river width of about 10 m [23]. The Aa-river is an example of a river where macrophyte mowing is performed in the early summer (May, June) and, in the case of continuous massive macrophyte development, a second time in the late summer (August, September). In the entire Aa-river the macrophytes are mowed, except within the small test river-reach of the Aa-river chosen for the modeling purposes. In this small river reach the macrophytes are left untouched in order to keep a natural river system for macrophyte research purposes.

The experimental river reach of interest used for model purposes is only a small part, 1.4 km long, of the Aa-river and has one weir at the beginning and one at the end, so called overflow structures (see Figure 5)

Figure 5. The overflow structure that is situated in the beginning and the end of the test river reach

River bed

P

h

1

θ

The main purpose of the weir is to regulate the upstream water level. This means that the weir height is not fixed, but adjusts to keep the upstream water level constant. At the weirs, which serve as measuring stations, historical and recent data of the water level for both stations and values for a calculated discharge after the downstream weir are available. The data were handed over to us by Mr. Emmanuel Cornet at the Ministry of the Flemish community Hydrological research and Information Center [34].

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Station 3

Station 4

Figure 6. Scanned map of the test river reach with its near environment

2.2.2 Biochemical description

The following discussion is based on the data from the Internet site of the Flemish Environmental Agency (VMM: Vlaamse Milleumaatschappij meetnet) www.vmm2.be [31].

The parameters used to assess the water quality in the system are

• The biological oxygen demand (BOD,

• The chemical oxygen demand (COD),

• The oxygen concentration, and

• The nutrient concentrations in the form of nitrate, ammonium and ortho-phosphate.

The biochemical oxygen demand (BOD), which is a measure of the amount of oxygen respired by aerobic microorganisms, is an estimation of the total amount of biodegradable organic matter in a sample. The chemical oxygen demand (COD) also includes the oxygen demand arising from the oxidation of slowly degradable and refractory organic matter. High organic load in untreated wastewater coming from treatment plants, industrial effluents and agricultural run-off, leads to high BOD and COD values and therefore a consumption of the

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COD less than 30 mg O2 per liter, which are almost always reached in the beginning of 2000 and later.

Biochemical oxygen demand over the years; yearly mean value and all available data

0 5 10 15 20 25 30

04/89 04/90 04/91 04/92 04/93 04/94 04/95 04/96 04/97 04/98 04/99 04/00 04/01 04/02 04/03 Date

[mgO2/L]

BOD yearly mean value BOD All data

Figure 7. Historical data for the biological oxygen demand in the river reach

Chemical oxygen demand over the years; yearly mean value and all available data

20 40 60 80 100 120

[mgO2/L]

COD yearly mean value COD all data

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survive for long periods at concentrations below 3 mg/L. The oxygen levels are according to the historical data in general above the level of 5 of milligrams per liter. Keeping in mind that a sudden decrease in oxygen for a short period can cause a massive fish depletion, it is not relevant to speak of a mean yearly value of the oxygen concentration. There are some measured values between 2-3 mg O2/L that could mean that a sudden fish depletion has taken place, but more frequent oxygen concentration measurements are needed to account for this effect. The few measurements made for the oxygen concentration is only sufficient to give an indication of an increased average oxygen concentration with time from the early 90's.

Dissolved oxygen over the years; yearly mean value and all available data

0 2 4 6 8 10 12 14 16 18

04/89 04/90 04/91 04/92 04/93 04/94 04/95 04/96 04/97 04/98 04/99 04/00 04/01 04/02 04/03 Date

[mgO2/L]

DO yearly mean value DO all data

Figure 9. Historical data for the dissolved oxygen concetration in the river reach

The soluble reactive nitrogen available to plants is in the form of NH4+ and NO3-. There is a remarkable reduction of ammonium from 1990 to 2004 whereas there is an increase in the nitrate concentration with time. The total nitrogen decreases with time, which can be seen in Figure 12. The considerable decrease of ammonium, and thus the total nitrogen, from the beginning of the nineties until now is with high probability due to the implementation of waste water treatment, not only treating the loads of organic carbon, but also eliminating a large part of the nutrients.

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Nitrate over the years; yearly mean value and all available data

0 1 2 3 4 5 6 7 8 9 10

04/89 04/90 04/91 04/92 04/93 04/94 04/95 04/96 04/97 04/98 04/99 04/00 04/01 04/02 04/03 Date

[mgN/L]

NO3- yearly mean value NO3- all data

Figure 10. Historical data for the nitrate concentrations in the river reach

Ammonium concentration over the years; yearly mean value and all available data

5 10 15 20 25 30 35 40

[mgN/L]

NH4+ yearly mean value NH4+ all data

(21)

Yearly mean value for the inorganic nitrogen available to plants

2 3 4 5 6 7 8 9 10 11 12

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Year

[mgN/L]

NO3- plus NH4+ yearly mean value

Figure 12. Historical data for the inorganic nitrogen concentration in the river reach

The soluble reactive phosphorus (PO43-) is the phosphorus available to plants. The total amount of phosphorus (Ptot) includes the amount of phosphorus in solution (reactive), in non- available particulate form (in general a small percentage of the total phosphorus) and, earlier, the polyphosphate which was a constituent of most washing powders. The total phosphorus (Figure 14) decreased rapidly in the beginning of the nineties, in all probability due to the ban of polyphosphate in washing powder. The norm of total phosphorus is a concentration lower than 1 mgP/L, which has almost always been reached the last year. The ortho-phosphate (Figure 13) decreases continuously until recently, ending up at a fairly low concentration from the end of the nineties, which is conform to the norms of less than 0.3 mgP/L.

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Ortho-phosphate concentration over the years; yearly mean value and all available data

0 0.2 0.4 0.6 0.8 1 1.2

04/89 04/90 04/91 04/92 04/93 04/94 04/95 04/96 04/97 04/98 04/99 04/00 04/01 04/02 04/03 Date

[mgP/L]

P-ortho yearly mean value P-ortho all data

Figure 13. Historical data for the ortho-phosphate concentration in the river reach

Total phosphorus concentration over the years; yearly mean value and all available data

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

04/89 04/90 04/91 04/92 04/93 04/94 04/95 04/96 04/97 04/98 04/99 04/00 04/01 04/02 04/03 Date

[mgP/L]

P tot yearly mean value Ptot all data

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reach is with high prospect due to the nutrient elimination in the treatment plants and to an increased number of people that has been connected to the wastewater treatment plant in the city of Turnhout and Oud-Turnhout [31].

2.2.2.1 The primary producers

Macrophytes, which are the principal primary producers in most river streams, are multicellular autotroph organisms (plants) whereas phytoplankton are microscopic one-celled organisms floating in colonies and periphyton are autotrophs growing on stones (epilithon), soft surfaces (epipelon) and on plants (epiphyton). Epiphyton grow on macrophytes and can be harmful to host plant survival. Phytoplanktons are eaten by zooplankton (microscopic animals) and by small fish. Most of the zooplankton species have phytoplankton as their primary source. The zooplanktons are in turn eaten by fish or other higher aquatic organisms.

The effect of grazing, that is the feeding on the macrophytes by aquatic organisms, on the macrophyte growth in a river can be considered as negligible since there in running waters exist few invertebrates that can graze on living aquatic macrophytes. Mostly the invertebrates feed on the dead macrophytes and not on the living material [29][32].

Phytoplanktons are most abundant where there is an adequate supply of nutrients and they are specially adapted to staying near the water surface to obtain enough light for photosynthesis.

Phytoplankton dominance usually is the case for rivers with an increased water depth and when water velocity and turbulence are low enough to prevent washout of the phytoplankton colonies [2]. The Aa river reach is a river with a small water depth which favors macrophyte over phytoplankton growth. The main autotrophic organisms living in the river reach is therefore the macrophyte but there are also some phytoplankton and periphyton communities.

Macrophytes

The following information is based on a macrophyte inventory (made once a month by Sofie van Belleghem at the University of Antwerp) upstream, in the middle and downstream of the river reach. Maximum overall biomass 2003 is found in May until September. The maximum peak of total macrophyte dry weight in 2003 occurred in June with a peak of almost 100 g dry weight per square meter. This can be compared to a total biomass that was only about 10 g dry weight per square meter in October.

May-November 2003 Macrophyte dry weight

40 50 60 70 80 90 100

Dry weight [g/m2]

(24)

Figure 15. Macrophyte biomass evolution in the river reach for 2003

The dominant macrophyte species in streams are rooted in the sediment and in the Aa-river the main part of the macrophyte species are rooted submerged [23]. The most abundant species growing during the spring, summer and autumn were Potamogeton Pectinatus, Sparganium emersum, Sagittaria sagittifolia, Potamogeton Natans, Ceratophyllum demersum, Rorippa Amphibia and Elodea Canadensis.

In the spring and early summer the dominant species was Potamogeton Pectinatus, which is a submerged plant having long, narrow underwater leaves, and which tolerates a wide range of conditions including brackish, alkaline or nutrient rich water (Figure 17). This plant was gradually replaced by other species during June and July such as by Sparganium Emersum (Figure 18), which has its biomass peak in July. Sparganium Emersum is growing in

watercourses of moderate to high nutrient status. Sparganium Emersum can grow up to 1 m deep and is not easily uprooted by fast flowing water. The leaves may become emergent in shallower water. The species is very sensible to shading and even a slight increase in the amount of shade will lead to the loss of the species. This can be seen on the results as Sparganium Emersum disappears rapidly after having its peak biomass in the beginning of July

Evolution of the plant species during the season 2003

0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040

mei juni juli augustus september oktober november

Month Dry weight (kg/m²)

P. pectinatus Callitriche sp.

C. demersum E. canadensis P. natans S. sagittifolia S. emersum

Figure 16. Evolution of the plant species during the season 2003

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Figure 17. Potamogeton Pectinatus Figure 18. Sparganium Emersum

Sagittaria Sagittifolia is the dominant plant between July and September and the maximum biomass is found in the beginning of august. Sagittaria Sagittifolia, Figure 19, is easy to recognize on the white flowers and arrow-formed leaves, which can be submerged, floating and emergent. Sagittaria Sagittifolia often grows in shallow eutrophic water. The macrophyte having its peak biomass the latest, i.e. in the beginning of September, is the Ceratophyllum Demersum (Figure 20). This is a submerged rootless plant tolerant to hard water and low light levels. It tends to form dense colonies in nutrient rich water, either anchored in the mud or floating freely close to the surface. The fact that it is tolerant to low light levels is perhaps the explanation of its late biomass peak, as it out-concurs other plants which are more sensible to low light conditions in the late summer/early autumn [33].

Figure 19. Sagittaria Sagittifolia Figure 20. Ceratophyllum Demersum

2.2.2.2 Fish

During a 24-hours experiment in August 2003, a fish inventory was made within a part of the river reach. The most common species found in the river reach were in the order Prussian carp (tolerant species), Gudgeon, Rudd (typical in vegetated areas), Tench (typical in vegetated areas) and the Eel (tolerant species) with a mass in gram per hectar of about 3430, 1260, 780, 550 and 240 respectively. The total fish biomass was about 6.7 kg per hectare for the 419 fishes. This would mean that the total fish biomass within the test river reach is about 11.3 kg, with a mean width of the river reach taken as12 m.

Fish Species Density [kg/hectare]

Prussian carp 3.43

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3 The hydrodynamics of the river system

The hydrodynamic characterization of the river reach requires a well-defined bathymetry, together with the water discharge, the corresponding water levels and the resistance to flow.

The resistance to flow, the so-called bed resistance, is the parameter that has to be estimated through model calibration and data evaluation. The Manning coefficient is used to describe the bed resistance and is a coefficient of roughness, which defines the flow resistance of a unit of bed surface. The resistance is a function of particle size, bed shape, constructional bed forms, channel roughness, irregularity of the channel cross-section, sedimentation, vegetation and other physical factors [4].

For the estimation of the bed resistance of the river reach, two sets of simulation data are available

1) Historical data of discharge at the downstream station and the corresponding water levels at both downstream and upstream stations, and

2) Water elevation data from artificial wave experiments performed in the river reach by K. Bal in 2000 and 2001, where the bed resistance can be estimated by the wave damping through the system [3]

3.1 Evaluation of hydrodynamic data 3.1.1 Data used in the hydrodynamic simulation

3.1.1.1 Discharge and water levels

The river reach is delimited by two weirs, which also serve as measuring stations, situated upstream and downstream of the river reach. The upstream station is called station 3, and the downstream station is called station 4 (Figure 22).

The weirs are of the type “overshot gate” and designed to maintain an almost constant water level upstream of these weirs, regardless of the discharge. This is done by automatically adjusting the gate angle θ of the weir (Figure 21).

θ h1

P

WL

(27)

(1) Q = Ca*Ce*Le*h11.5

where,

a is the correction factor for the angle of the gate

e is the effective discharge coefficient for a vertical weir,

eis the effective crest length L is the water level

is the weir level

nfortunately several factors make the weir head/discharge relationship at the downstream

ince the problem with the measurement of the weir head has not yet been solved, the

Figure 22 s along the river reach

herefore a correction is undertaken by measuring the velocity profile with a current meter a C

C L W P U

weir hard to obtain. First of all, the gate angle is not monitored, so that the elevation of the weir crest P is not known. Therefore, the water head h1 cannot be obtained by the level difference, h1 = WL - P between the weir level P and the total water level WL. Secondly, the head h1 is small (in the order of 5-10 cm), and hence difficult to measure with precision. This means that even if it would be possible to measure the head, it is not sure that the precision would be good enough to give a reliable discharge/head relationship. Lastly, an accumulation of debris in front of the gate is rare, leading to a large and erratic fluctuation of the water level / water flow relationship.

S

alternative is to use a water level/discharge relationship just after the weir at station 4. The water level is measured downstream of station 3, (H3DS*) and upstream (H4US*) and downstream (H4DS) of station 4). The water level H4DS (Figure 22) is converted into Q4DS by a H/Q relationship. One problem with this approach is that the H/Q relationship is influenced by the presence of macrophytes downstream of the river reach, whose presence will cause an elevation of the water level where H4DS is measured.

St 3

St 4

H4US H4DS

H3DS

Length of the test river reach L = 1400 m

. The placement of the measurement point

T

couple of times per years. The measurement of the velocity profiles is not undertaken frequent

(28)

Due to the fact that field measurements have to be performed to validate the correlation, the

(2) Q4DS = 18.65*QTurnhout0.7716

historical data of Q4DS is only available with a one-year delay. To obtain the discharge after station 4 for the year 2003, Inge Folmer at ULB therefore established a correlation between historical data for the measured discharge in Turnhout, a measuring station situated about 15 kilometers upstream of the river reach, and historical data for the calculated discharge after station 4. As can be seen in Figure 24, this correlation allows reproducing fairly well the historical data obtained for 2001. The correlation can in other words be used to estimate the discharge at station 4 using the following equation obtained from Figure 23:

Correlation for the discharge between station 4 and Turnhout for discharges at station 4 below 7000 L/s in the period 1/1/98 - 31/12/01

y = 18.65x0.7716 R2 = 0.8773

0 1000 2000 3000 4000 5000 6000 7000 8000

0 500 1000 1500 2000 2500 3000

Discharge in Turnhout [L/s]

Discharge at st. 4 [L/s]

Figure 23. Correlation for the discharge between station 4 and Turnhout

(29)

Comparision of the discharge obtained from the Q/H relationship and the discharge obtained from the correlation equation

0 2000 4000 6000 8000 10000 12000 14000 16000

01/01/01 02/03/01 01/05/01 30/06/01 29/08/01 28/10/01 27/12/01 Date

Discharge [L/s]

Q/H relationship Correlation

Figure 24. Comparison of the discharge obtained from the Q/H relation and the discharge obtained from the correlation equation

The historical data of the measured water levels at station 3 and 4 and the calculated discharge after station 4 are available from the Ministry of the Flemish community [35].

3.1.1.2 The artificial wave data

Wave experiments were performed in the river reach in September and November 2000 and in March 2001 by K. Bal at the University of Antwerp to estimate the riverbed resistance [3].

The experimental set-up consisted of a pressure sensor, a so-called diver, used to measure the height of the overlaying water column. Five divers were placed on five poles along the river reach, according to the map, Figure 25:

(30)

lim

Pole 5 Pole 3

Pole 4 Pole 2

Direction of flow

Pole 1

Scale:

0 200 400 m

Figure 25. The position of the measuring poles along the river reach

To create a wave the weir at station 3 was raised, accumulating water in the upstream reach.

When lowering the weir, the accumulated water mass created a wave propagating in the river system. At the five poles the water level above the diver was recorded once per second. By comparing the wave amplitude at different distances from station 3, the damping of the wave due to the bed resistance could be followed along the river reach. The water level at the measuring stations as a function of time for the wave experiment on the 1st of November 2000 can be seen in Figure 26. Normally, the system for the automatic adjustment of the downstream weir to keep the upstream water level constant was turned off during the experiment, to avoid sudden change in water level due to a changing weir level.

(31)

1 of November 2000 : Water level during steady-state and during wave experiment with the distance from station 3

9,7 9,8 9,9 10 10,1 10,2 10,3 10,4

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500

Elapsed time from the generation of the first wave [s]

Water level [m]

1400 m 1250 m 910 m 320 m

Figure 26. The water level with the distance from the upstream station, station 3

The travel-time between the measuring stations can be used to calculate the mean depth

(3)

between the measuring poles through the formula for the velocity of a propagating wave:

where

is the longitudinal velocity of the wave [m/s]

d g v= ×

v

d is the depth [m]

g is the gravitational acceleration [m/s2]

(32)

1 of November 2000

Wave amplitude with the distance from station 3

0 2 4 6 8 10 12 14 16 18 20

3800 4000 4200 4400 4600 4800 5000 5200 5400 5600

Elapsed time from the generation of the first wave [s]

Wave amplitude [cm]

1400 m 1250 m 910 m 320 m 10 m

Figure 27. The wave elevation at various distances from the upstream station (station 3)

The main problem with the experiment was that the poles had moved from one experiment to another, which means that it was only possible to measure the water level profile for the 1st of November.

Another problem with the experiment was the back wave that overlapped the waves at the two poles closest to the downstream station, station 4. Since a number of waves were generated without obtaining an equilibrium situation between the waves, it is not easy to understand the hydrodynamics of the river system during the wave experiment. Furthermore, the automatic adjustment of the weir level was probably still working during the wave experiment the 1st of November, resulting in an accumulation of water in the river system.

3.1.2 Macrophyte influence on the water velocity

Open channel flow is often laminar or near-laminar and the highest velocity is located in the center of the flow channel, slightly below the water surface (see Figure 28

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Figure 28. Typical flow profile in an open channel [4]

The velocity as a function of the depth was measured on the 21 of August and on the 5 of November 2003 during the 24-h experiment. This was done upstream (station 3), at a middle point and downstream (station 4). The measurement was made along the banks and in the center of the section. Each velocity profile is made up by 3 points; one point measured 5 cm from the bottom, one at mid-depth and one point 5 cm from the surface. The water velocity should increase with the distance from the bottom and with the distance from the banks.

5 cm

5 cm

5 cm

5 cm Center

Left bank Right bank

Figure 29. The principle for the velocity profile measurement in August and November 2003

This is not the general pattern for the measured velocity profiles in August, which the following figure is a good example of:

(34)

Velocity as a function of water depth for station 3

0

10

20

30

40

50

60

70

80

90

100

-0.01 0.00 0.01 0.02 0.03 0.04 0.05 0.06

Velocity [m/s]

Water depth [cm]

Left bank Center Right bank

Figure 30. Velocity profile at station 3 in August 2003

5-6 of November 2003

Velocity profile 50 m downstream of station 3

0

10

20

30

40

0 0,05 0,1 0,15 0,2 0,25 0,3

Velocity [m/s]

Depth [cm]

left bank center right bank

(35)

Distribution of macrophyte mass across the section at station 3

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0

May June July August September October November

Month kgWW/m2

Right bank Middle Left bank

Figure 32. The distribution of macrophyte wet weight within the section at station 3

One explanation of the irregular velocity profiles in August is certainly the influence of macrophytes. In a study in the river Spree in Germany the macrophyte stands of among others S. Sagittifolia and P. Pectinatus considerably lowered the water velocity within and downstream of the macrophyte stands [21]. For example, the highest water velocities at station 3 during the 24-hours experiment in August is not found in the center of the section, as expected, but at the right bank of the river (see Figure 30). The measured macrophyte distribution at station 3 in August (Figure 32) also shows that there is abundant macrophyte growth in the center of the section, which could be an explanation for the lower velocity in the center.

The macrophyte biomass at station 4 is lower than at the middle station and station 3 in August and the fact that the mean velocity is highest at station 4 confirms the relation between a lower velocity and the higher macrophyte abundance.

The velocity profiles for the 5-6 of November show a normal relationship between the distance from the bottom and the increase in velocity. In November, the velocities are in the order of 3-5 times higher than in August and there are almost no macrophytes present.

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Wet weight of macrophytes per square meter

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

May June July August September October November

Month [kgWW/m2]

Station 4 Middle Station 3

Figure 33. Wet weight of macrophytes per square meter in 2003 at station 3, at the middle station and at station 4

Mean velocity Station 3 0,023 Middle station 0,021 Station 4 0,027

Table 2. Mean velocity 21 of August 2003

Mean velocity [m/s]

Station 3 0,125 Middle station 0,081 Station 4 0,077

Table 3. Mean velocity 5 of November 2003

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flood risk analysis and mapping

design of flood alleviation systems

real-time flood forecasting

hydraulic analysis/design of structures including bridges

drainage and irrigation studies

optimization of river and reservoir operations

dam break analysis

water quality issues

integrated groundwater and surface water analysis

The model we are about to develop belongs to the category of water quality issues. The one- dimensional model, Mike 11, is used to simulate the hydrodynamics, the advection-dispersion (transport) properties of the river reach as well as the geochemical processes taking place in the water column and in the sediments. The finished integrated model will be used to model the macrophyte growth in combination with the nutrient uptake and release in the river reach.

The temporal and longitudinal variation of the discharge and water level is obtained through the hydrodynamic simulation, which will be treated in the following chapter. The non-linear equation of open channel flow (the Saint-Venant equation) is solved numerically in time and space for specified boundary and initial conditions. The hydrodynamic output is needed as input for the advective-dispersive transport simulation and the geochemical simulation, the so called water-quality simulation [17].

3.2.1 Bathymetry

The geographical definition of the river area is made in the network editor. The first that has to be done is to digitize a map of the river area. A high-resolution scanned map of the Aa- river and the near environments is imported as a bitmap background into the Mike 11 network editor. The position of the river area within the UTM (Universal Transverse Mercator) grid used in Mike 11 is done by inserting the UTM coordinates of three selected points on the background map to serve as reference points.

Thereafter the river reach has to be defined on the map. This is done by adding points on the background map along the river reach, where the cross-sections are to be inserted, the first point being chainage zero. The chainage is the distance from the first defined point and by definition the positive direction of the flow is the direction of increasing chainage.

The topography of the river reach is obtained through the insertion of cross-sections, which is done in the cross-section editor. The cross-sections are specified by x-z-coordinates, where x is the transverse distance from the left bank top and z is the corresponding bed elevation [17].

30 cross-sections were available from the Division of the Hydraulic Laboratory and Hydrological research at the Ministry of the Flemish community [35] to describe the topography of the 1400 m long river reach.

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Cross-sections from the downstream station up to the middle of the river

8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0

20 22 24 26 28 30 32 34 36 38 40 42 44

Distance from the left leave bank [m]

Bank elevation [m]

Figure 34. Cross-sections of the downstream part of the river reach

These cross-sectional raw data are automatically processed to calculate the hydraulic parameters needed in the hydrodynamic calculations, i.e. the cross-sectional area, hydraulic radius and flow width are calculated for different water elevations.

The computational grid alternates discharge (Q) and water level (H) points, where results for the discharge and water level will be available in the result file. The Q-points are placed midway between neighbouring H-point and at structures while H-points are located at cross- sections. The minimum number of grid points is therefore dependent on the number of inserted cross-sections [17].

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Q-point ∆x

Direction of flow

H-point

Figure 35. The placement of the result grid along the river reach

3.2.2 The Saint Venant Equations

Mike 11 HD-editor solves the vertically integrated equations of conservation of volume and momentum based on the following assumptions:

• The water is incompressible and homogenous, i.e. the density variation is negligible

• The bottom slope is small, which means that the cosine of the angle it makes with the horizontal is taken as 1

• The wave lengths are large compared to the water depth, which ensures that the flow everywhere can be regarded as having a direction parallel to the bottom; i.e. vertical accelerations are neglected and hydrostatic pressure variation along the vertical assumed.

• The flow is sub critical, which means that the flow velocity is lower than the velocity of a wave propagating on the surface

The Saint Venant equations are the following:

Conservation of volume:

(4) q

t A x

Q =

∂ + ∂

where,

x the chainage (distance from the beginning of the river system)

References

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