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Possibilities of continuous discharge measurements under extreme situations, using Radar and Numerical models

1205476-000 © Deltares, 2012, A

Bob Paap Guido Rutten Henk Verheij

Title Possibilities of continuous discharge measurements under extreme situations, using Radar and Numerical models Client Rijkswaterstaat Data-ICT-Dienst

Project 1205476-000

Reference 1205476-000-BGS-0011

Pages 87

Keywords Rivers, Discharge, Extreme conditions, Radar, Numerical models Summary This report assesses the feasibility of continuously measuring river discharge under extreme conditions using radar-based instruments and physics-based numerical models. The extreme river discharge conditions are defined as water levels, for which existing measurement techniques can only provide limited data (low and high discharge events and areas with tidal influence). Radar techniques have a high potential for providing valuable discharge information under extreme river discharge conditions. Several radar systems that are relevant for river discharge measurements were assessed based on performance criteria. Three systems, the CODAR Riversonde radar (UHF band), Sommer (K band) and Mutronics (K band) radar are especially designed to determine river discharge. It is recommended that these systems are tested in a pilot project at a location where high discharge events result in submerged floodplains. 3D physics-based numerical models that simulate discharge can be used for improved discharge determination from stage and current velocity data, especially for extreme water levels where existing stage/velocity- discharge relationships have a high uncertainty. Five models are reviewed: CCHE3D, Delft3D, MIKE, TELEMAC and WAQUA/TRIWAQ. These models allow for simulations of stage/velocity- discharge relationships representative for extreme conditions, which can be used for real-time discharge estimation. All presented models are available and suitable. This report shows that use of radar current velocity measurements and numerical models can improve stage/velocity- discharge relationships and yield better discharge data for extreme conditions. It is recommended that a pilot project using these techniques is realized in a “proeftuin” concept in which government (Rijkswaterstaat), companies and research institutes (e.g. Universities, Alterra, Deltares) collaborate. Samenvatting Dit rapport beschouwt de mogelijkheden van continu debiet metingen in extreme situaties, gebruik makend van radar metingen en fysisch gebaseerde modellen. Extreme situaties zijn die situaties in welke de huidige meettechnieken slechts beperkt functioneren (hoge en lage afvoeren, gebieden met getijde invloeden). Radar technieken hebben de potentie om ook in extreme situaties debieten te kunnen meten. Dit rapport beschouwt meerdere radar systemen op hun geschiktheid voor het meten van debieten op rivieren. Drie van deze systemen, de CODAR Riversonde radar (UHF band), Sommer (K band) en Mutronics (K band) zijn specifiek voor dit doel ontworpen. Voorgesteld wordt om deze systemen te testen op een locatie waar hoge afvoeren resulteren in overstromende uiterwaarden.

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Contents

1 Concept 1 1.1 Introduction 1 1.2 Integrated approach using radar and numerical models 2 1.3 Scope 2 1.4 Outline of this report 3

2 Short introduction to river discharge 5 2.1 Terminology used in discharge determination 5 2.2 Basics of river discharge determination 6

2.2.1 Stage/velocity- discharge relationships 7 2.2.2 Restrictions related to extreme conditions 9

3 Application of radar for river discharge determination 13 3.1 Introduction 13 3.2 Expected performance of radars in extreme conditions 14 3.3 High frequency radar: WERA and Seasonde 14 3.4 Ultra-high frequency radar: CODAR Riversonde 18 3.5 Nautical X band radar coupled to software 19 3.6 K band radar: Flo-Dar, Sommer and Mutronics 21 3.7 General applicability of radar systems 25

3.7.1 General restrictions 25 3.7.2 Possible requirement of radio- and building permits 28 3.7.3 Validation of radar for current velocity measurements on rivers 29

4 Numerical models for discharge simulation 31 4.1 Introduction 31 4.2 Implementation of numerical modeling for extreme conditions 31 4.3 Numerical modeling of rivers 32

4.3.1 Future of 3D numerical modeling 33 4.3.2 3D physics-based, continuous real-time modeling of integral river systems 33

4.4 Background 33 4.4.1 Computational fluid dynamics 33 4.4.2 CFD in river engineering 34 4.4.3 Accuracy versus computational time 34

4.5 Numerical modeling for river flow pattern analysis 35 4.5.1 3D numerical modeling for the improvement of stage/velocity- discharge models

35 4.5.2 Scientific reference studies 36 4.5.3 Example of application 38 4.5.4 Choice of measurement location 39 4.5.5 Uncertainty and validation 39

4.6 Evaluation of models 40 4.6.1 Criteria for the choice of modeling package 40 4.6.2 1: Basic technical requirements 40 4.6.3 Additional technical specifications 41 4.6.4 Implementation 41

4.7 Available models 42

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Possibilities of continuous discharge measurements under extreme situations,using Radar and Numerical models

4.8 Choice of modeling package 44

5 Synthesis and implementation in a pilot project 47 5.1 Key aspects for synthesis and implementation 47

5.1.1 Considerations for using radar data 47 5.1.2 Temporal and spatial aspects of combining model- and measurements 48 5.1.3 Quantification of uncertainty in discharge determination 49

5.2 Pilot Project 49 5.3 Long-term implementation 51

6 Conclusions 53

7 References 55

Appendices

A Theory of radar A-1 A.1 Introduction A-1 A.2 Classification of electromagnetic frequencies A-2 A.3 Polarization of electromagnetic waves A-2 A.4 Modulation technique A-3 A.5 Resolution of radar A-5 A.6 Accuracy of radar A-5 A.7 Coherent- and incoherent radar A-6 A.8 Current velocity determination from radar measurements A-6

B Wave heights on rivers and canals B-1

C Technical specifications of HF band radar systems: WERA and Seasonde C-1 C.1 WERA C-1 C.2 Seasonde C-4

D Technical specifications of Riversonde Radar D-1

E Technical specifications of nautical X band radar coupled to software E-1

F Technical specifications of K band radars: Flo-Dar, Sommer and Mutronics F-1

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1 Concept

1.1 Introduction The ability to continuously and accurately acquire river discharge data under all conditions is becoming increasingly important for Rijkswaterstaat. At present extreme discharge conditions are not measured optimally, since the acquisition of reliable discharge data is restricted to a limited range of regular discharge conditions. While the demand for reliable discharge information is especially high during a drought or floods (overbank), that are associated with low and high discharge events, respectively. This discharge information is required by decision- and policy makers, who are responsible for safety against flooding, distribution of water resources and for directing traffic in the river channels during a drought. Apart from low and high water levels, extreme conditions also include areas with tidal influence, where river currents interact with tidal currents, making discharge measurements very complex. Currently, continuous discharge information has a frequency between once every 10 minutes and once a day, at specific locations along rivers and canals in the Netherlands. Discharge is derived from measurements of water level and/or current velocity using stage/velocity- discharge relationships. These continuous measurement systems have been optimized for regular discharge conditions. In extreme conditions, discharge information can only be derived from incidental measurements (for example with a vessel-mounted ADCP during overbank flooding events). Carrying out these incidental measurements during extreme conditions can be difficult due to the river conditions and the availability of suitable vessels and equipment, thus yielding only intermitted data sequences. As a result, stage/velocity- discharge relationships are often not representative for extreme conditions as they are composed using data acquired under regular flow conditions. This results in decreased accuracy and increased uncertainty for discharge determination under extreme discharge conditions. To discuss the possibilities of improving discharge measurements under extreme conditions a brainstorm session with experts and users of discharge information was organized by Deltares on behalf of Rijkswaterstaat, on October 26th, 2011. This report addresses one of the principal results of the brainstorm session, which is the potential of obtaining new and more accurate discharge data by simultaneous use of radar technique and numerical models in addition to conventional measurement techniques. During this session, it was recognized that innovative approaches could offer a solution to continuously and accurately provide discharge information over the entire range. The participants of the brainstorm session concluded that radar techniques could be attractive for both instantaneous- and permanent discharge measurements on inland water during regular and extreme discharge events. Radar techniques have the advantage of allowing measurements during high discharge events without the requirement of a vessel, and without restrictions regarding river accessibility. Several radar systems exist that can be used for continuous discharge measurements including extreme conditions. Additionally, it was concluded during the brainstorm session, that 3D physics-based numerical models for discharge simulation could help improve discharge determination in extreme conditions. Numerical models allow for simulation of stage/velocity- discharge relationships representative for extreme conditions, which can be used for discharge

Possibilities of continuous discharge measurements under extreme situations,

using Radar and Numerical models

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estimation. Numerical models have no dependency on existing stage/velocity- discharge relationships as they use theoretical (non-regressive) physical formulations for flow to calculate discharge. As such, the uncertainty of discharge information for extreme events is smaller using numerical models than for existing stage/velocity- discharge relationships. Furthermore, once a physics-based numerical model is implemented and validated, it can be applied to different settings, giving an insight into the discharge conditions during extreme events. However, the computational effort required by these models can be considerable. Real-time modeling of discharge with numerical models has therefore not been implemented, yet. However, considering current developments of hardware and software, it is expected that this might be possible within the near future. Since, this is a medium to long-term development it falls outside the scope of this report.

1.2 Integrated approach using radar and numerical models Several radar systems exist with potential to be implemented for continuous discharge determination in extreme situations by measuring current velocities at the water surface. The radars considered most favorable for this purpose are the UHF CODAR Riversonde, the K band Sommer and K band Mutronics radar. To obtain accurate discharge information from radar measurements, a transformation of the radar data, current velocities at the water surface, to a vertical velocity profiles along the river cross-section is required. Although available stage/velocity- discharge relationships could be used, for extreme conditions these relationships are not sufficient. Therefore, it is suggested that they should be replaced by velocity- discharge relationships derived from model simulations. Newly obtained relationships from numerical models should be validated for regular discharge conditions by comparing them to existing stage/velocity relationships and for extreme situations model data can be compared with incidental vessel-mounted ADCP measurements. After validation, the new stage/velocity-discharge relationship can be implemented. Hence it is recommended that for extreme river conditions radar data and physics-based numerical models are combined to determine continuous discharge information.

1.3 Scope Rijkswaterstaat has requested Deltares to assess the possibilities for continuous discharge determination on rivers under extreme conditions using:

(i) Radar techniques to measure discharge; (ii) 3D numerical models in combination with measurement techniques, to improve

discharge determination. The following aspects are addressed:

Radar techniques for measuring discharge o Theoretical description of existing radar techniques; physical background,

radar signal characteristics, transmission technique, determination of current velocity, resolution and accuracy

o Practical description of existing radar systems; hardware, software, data accuracy and limitations

o Existing case studies and user experience o General applicability of existing radar systems o Additional research required for implementation

3D physics-based numerical models for discharge simulation o Theoretical description of existing models; accuracy o Practical description of existing models o Calibration and validation of models

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o Existing case studies and user experience o General applicability of existing models o Additional research required for implementation

Based on the assessment, the use of radar and numerical models are integrated in a synthesis, with a focus on

Proposal for the combined use of radar, models and traditional measurement techniques in a pilot project;

Criteria for selecting a pilot location; Definition of the requirements for the applicability of methods for continuous discharge

determination in extreme condition.

1.4 Outline of this report Chapter 2 gives an overview of discharge information for regular and extreme discharge conditions including definitions. Chapter 3 describes the applicability of available radar systems and addresses case studies and user experience. Chapter 4 presents the characteristics and applicability of 3D physics-based numerical models. In chapter 5, considerations and recommendations are discussed for implementation of radar and models in a pilot project. In chapter 6 the conclusions are presented. Appendix A presents an overview of the theoretical background of radar relevant for determining discharge from current velocity measurements. Appendix B gives a brief description of dimensional characteristics of surface water waves that can be expected at rivers. Appendices C, D E and F provide the technical specifications of considered radar systems.

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2 Short introduction to river discharge

2.1 Terminology used in discharge determination The following terminology is used throughout this report and explained here for the convenience of the reader. The terminologies that are listed without a reference are phrased by the authors. Flow The volume of water through a given cross-section over a given period of time. Current velocity Velocity of a steady flow. Discharge Discharge is the volumetric flow rate of water and sediment through a given cross-sectional area. Stage The water level referenced to an (inter)-national datum. Discharge measurements Determination of discharge using measurements of stage, current velocity and bottom profile converted into discharge using predetermined relationships. Incidental discharge measurements Discharge measurement on a specific location during a limited period with a maximum measuring frequency restricted to a few times a month (Stowa, 2009). Continuous discharge information Discharge measurement over longer period during which discharge data are acquired with a fixed time-interval, for example at a frequency of once every 10 minutes or once every day. Rijkswaterstaat defines a measurement frequency for continuous discharge measurements of once every 10 minutes. During such a period of 10 minutes a discharge value is obtained, derived from an average of the current velocity/water level values measured during that time period. (Stowa, 2009). Regular water levels Regular water levels are non-extreme water levels, i.e. no flow over floodplains and no extremely low water levels for which current measuring techniques are less suitable. Extremely low water level Extremely low water level is recognized as a condition during low discharge, when water level is below a threshold value, causing bottom roughness to become a dominating parameter for total discharge. This threshold value is dependent on various parameters such as the current velocity and the river bed gradient. This condition is characterized by low current velocities. Use of existing Q(h,v) relationships results in decreased accuracy of discharge measurement data.



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Extremely high water level Extremely high water level is the condition when the floodplain (uiterwaarde) is submerged. Areas with tidal influence Inland area near the coast where river currents interact with tidal currents, making discharge measurements more complex compared to regular situations. Stage/velocity- discharge relationship (Q(h,v)) Empirical relationship between stage and discharge (Q(h), or between stage, velocity and discharge (Q(h,v)). Q(f) relationship Empirical relationship between stage/velocity and discharge including the effects of hysteresis and bottom subsidence. Acoustic Discharge Measurement (ADM) ADM performs measurements of both current velocity and stage in order to continuously determine discharge. Discharge is determined from stage and current velocity using a Q(h,v) relationship. An ADM measures the current velocity at a fixed height in the river, by calculating the travel time difference of two acoustic signals transmitted in upstream and downstream direction (Stowa, 2009). Horizontal Acoustic Doppler Current Profiler (HADCP) HADCP performs measurements of both current velocity and stage in order to continuously determine discharge. Discharge is determined from stage and current velocity using a Q(h,v) relationship. An HADCP measures the current velocity at a fixed height by from the Doppler frequency shift of a transmitted acoustic signal that reflects upon suspended particles present in the water column (Stowa, 2009). Vessel-mounted Acoustic Doppler Current Profiler (vessel-mounted ADCP) Vessel-mounted ADCP is operated on a vessel and used to perform simultaneous measurements of both water depth and current velocity (along the vertical) to determine discharge incidentally. Vessel-mounted ADCP allows densely sampled measurements of major parts of the river cross-section (Stowa, 2009).

2.2 Basics of river discharge determination Determination of river discharge consists of measurements of water level and/or velocity, combined with a relationship that is used to compute the discharge. Rijkswaterstaat mainly uses two approaches for continuously obtaining discharge information: 1. Stage/velocity measurements and Q(h,v) relationships. This approach is conducted using ADM (STOWA, 2009, paragraph 6.3) or HADCP (Stowa, 2009, paragraph 6.4). 2. Stage measurements and Q(h) relationships (STOWA, 2009, paragraph 6.5). This approach is used when continuous current velocity measurements can not help to improve the discharge information, due to river conditions. Determination of discharge in extreme conditions is less reliable, because of limitations of regression-based relationships (i.e. currently used stage/velocity-discharge relationships) and limited implementation of continuous measuring systems.

I. Limitations of regression-type relationships

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Regression-type relationships are less suitable for discharge determination for extreme conditions, as they are typically based on data obtained under regular flow conditions. Therefore, extrapolation of regression-type relationships towards extreme conditions induces increased uncertainty in discharge determination (Stowa, 2009).

II. Limited performance of continuous measuring systems

Continuous measuring systems (i.e. HADCP, ADM) are often placed at a fixed height in the river, representative to accurately measure only under regular conditions. During extremely low water levels, the water level may simply fall below the level of the measurement system (i.e. HADCP or ADM), not allowing execution of measurements. During extremely high water levels with submerged outer banks, measurements from these systems are only representative for the main river cross-section and not for the submerged outer banks, complicating discharge determination. Therefore, under extreme conditions accurate measurements can only be performed incidentally, often with a vessel-mounted ADCP.

2.2.1 Stage/velocity- discharge relationships The discharge is determined from a continuously measured water level and/or current velocity using a stage/velocity- discharge relationship. The principal element of stage/velocity- discharge relationships is the definition of the velocity distribution across a river cross-section. The current velocity distribution along a vertical is determined from current velocity measurements at one or more points along the vertical. Figure 2.1 shows an example of the velocity distribution along a vertical in a river. These velocity profiles are based on regression curves often defined by simplified logarithmic relationships.

Figure 2.1. Example of a velocity distribution in a vertical. Here a and y represent arbitrary chosen distances from

the bottom, with flow velocities va and vy respectively. The mean velocity in the vertical is found at a distance from the bottom of approximately 0.4d, where d is the total depth. From Boiten (2000).

The measurement data used to define stage/velocity- discharge relationships are mainly obtained with the velocity area method. The velocity area method determines the discharge through a river cross section from incidental stage and current velocity measurements. This method is illustrated in Figure 2.2. The cross section is divided in multiple areas Ai representative to account for river depth variations along the cross section. Within each surface section Ai the velocity distribution along a vertical is measured.



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The discharge Qi through area Ai is found by: i i iQ AV with Vi being the average of the vertical current profile

The total discharge Q along the river cross-section is obtained by summing this product for the entire cross section (see Figure 2.2)

i iQ AV The stage/velocity- discharge relationship is found by determining the discharge with the velocity area method for a range of stages.

Figure 2.2. Illustration of the standard velocity area method. The total discharge along a cross section is derived by

summing the product of current velocity vi with flow surface for different verticals Ai. From Hartong and Termes (2009).

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Figure 2.3. Stage-discharge relationship at Borgharen, for 1993, 1995 and 2002. From Rijkswaterstaat. Figure 2.3 shows an example of a stage-discharge relationship of the Meuse at Borgharen, determined for 1993, 1995 and 2002. Stage/velocity- discharge relationships do not consider the effect of hysteresis, which can be caused by rising or falling water levels, where these relationships behave different than for a static water level. Furthermore, the effect of morphodynamics on discharge estimations is neglected in stage/velocity- discharge relationships. Modern Q(f) (function) relations already incorporate the effects of hysteresis and morphodynamics in the discharge estimation (STOWA 2009).

2.2.2 Restrictions related to extreme conditions For more extreme water levels, stage/velocity- discharge relationships have an inherent increased uncertainty. This means that because of the limited number of calibration measurements available for extreme values, these relationships need to be extrapolated. Figure 2.4. illustrates extrapolation of stage versus cross sectional area (Left: hA relationship) and stage versus measured current velocity (Right: hv relationship). Based on the measured stage h and the relation Q = v × A, the average velocity and area of the cross-section A can be plotted versus stage h. The curve hA is fitted through the measurement points and extrapolated outside of the measured range. Extrapolation of the h-v curve is performed by using Manning’s equation. The discharge corresponding to the extrapolated stage he is obtained with the relation Qe=vexAe. This is done for different stages in order to estimate the stage- discharge relation outside of the measured discharge range (Stowa, 2009). However, extreme discharge conditions can cause a significant change in the velocity distribution profile along a river cross-section and in the hA curve due to bottom changes, complicating extrapolation of the relationship.



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Figure 2.4 Representations of extrapolated hA and hv relationships. Left: cross-section surface (A) vs. stage (h). Right: Average velocity (v) vs stage (h). hmax denotes the maximum measured water level, the dashed lines are extrapolations of the curve. The extrapolated value is annotated with he. From STOWA (2009). The limitations of extrapolated stage/velocity- discharge relationships (Figure 2.4) can best be illustrated for extreme high water levels, when the river can partly cover the flood plain The velocity profiles along the flood plain will have different characteristics than the velocity profiles in the main channel. This is due to the different roughnesses, and the flow mechanisms associated with overbank flow in a two-stage channel (Figure 2.5). The upper right corner of this Figure shows an example of a vertically averaged velocity distribution along the cross-section. The shear layer indicated in this picture is characterized by local secondary flows in the main river channel. Due to these secondary flows, a horizontal velocity measurement in the main river channel may be less representative. Thus, for this case, the major uncertainty in using extrapolated stage/velocity- discharge relationships will be caused by cross-shore variation in the velocity profile. The uncertainty of existing stage/velocity- discharge relationships for the case of extremely high water levels might increase further as the limited number of calibration measurements for this situation may not suffice for changing geometry or vegetation characteristics. An example of the changing river geometry are the “Ruimte voor de Rivieren” projects, where groynes are lowered and floodplains altered. Calibration measurements prior to the geometry change may thus not be representative of the new condition.

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Figure 2.5 Flow mechanisms associated with straight overbank flow in a two stage channel

(Shiono and Knight, 1991). A problem encountered for extreme low water levels is related to the minimum water level under which measurement systems can obtain accurate stage or current velocity data. When the water level becomes smaller than the minimum water level this results in unreliable discharge information. Additionally, the presence of vegetation results in more complicated flow patterns for low water levels compared to regular conditions, which can not be included in empirical stage/velocity- discharge relationships. Areas with tidal influence are characterized by stratified flow, resulting in varying flow patterns (both temporally and spatially), which can not be accurately represented by stage/velocity- discharge relationships. Additionally these areas typically have a very large spatial extent, under which the possibilities for implementation of continuous measurement systems are limited. Therefore, discharge information at areas with tidal influence is only obtained by performing incidental measurements (vessel-mounted ADCP).



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The major limitations and uncertainties in empirical relationships are thus related to:

Extreme conditions: Water levels or velocities that occur only rarely yield less reliable results. For this reason, determination of hydraulic boundary conditions is already done with physics-based modeling (i.e. WAQUA/TRIWAQ).

Adaptation to changing geometries: The influence of variable geometries (for instance lowering of groynes) can only be observed after new calibration is performed.

Stratified flow in areas with tidal influence.

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3 Application of radar for river discharge determination

3.1 Introduction This Chapter presents a brief review of radar systems relevant for continuous discharge measurements. Radar systems measure current velocity at the water surface. This current velocity can be translated in discharge information using stage/velocity- discharge relationships. The expected performance of radar systems is summarized in Section 3.2. Sections 3.3-3.6 present background information of these radar systems being classified by their operating frequency, as shown in Table 3.1. Based on this information radar systems are compared in Section 3.7.

Table 3.1. Overview of the considered radar systems. Radar System Frequency specification Description WERA CODAR Seasonde

HF band radar

Regional coastal system

Section 3.3

CODAR Riversonde UHF band radar

Local river system

Section 3.4

WAMOS/SeaDarQ Nautical X band radar

Regional coastal system

Section 3.5

Flo-Dar Sommer

Mutronics

K band radar Local river system Section 3.6

The theoretical background of radar properties and terminology relevant for radar performance is described in Appendix A, comprising of:

Classification of electromagnetic frequencies; Polarization of electromagnetic waves; Modulation technique; Geometry, resolution and accuracy of radar; Coherent- and incoherent radar; Current velocity determination from coherent and incoherent radar measurements.

An important condition for applicability of radar systems often is the presence of surface water waves. Therefore, appendix B gives a brief description of dimensional characteristics of surface water waves that can be expected at rivers. Appendices C, D, E and F provide descriptions related to geometrical, signal- and data characteristics of HF band-, UHF band-, X band- and K band radar systems, respectively. These appendices also contain technical information of radar systems presented in tables, including specifications of the radar properties covered in appendix A.



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3.2 Expected performance of radars in extreme conditions Based on the results presented in the paragraphs below, the expected performance of considered radars under extreme discharge conditions are summarized in Table 3.2, which is based on technical specifications of the systems (Table 3.3 and Appendices C, D, E and F) and existing validation studies. The UHF band Riversonde radar is considered to be applicable for river current measurements under regular flow conditions, high water level and areas with tidal influence (various publications by C. Teague). Stage measurements should be performed simultaneously with the Riversonde to obtain discharge information. The K band radar provided by Sommer offers good possibilities to measure under extreme low water levels, and possibly during extreme high water levels and in areas with tidal influence. On the contrary, the K band radar of Flo-Dar is tailored for small-scale confined flow systems, its performance is expected to be limited. Based on the specifications of nautical X band radar and HF band radar (WERA and Seasonde), these systems are not expected to be suitable for river discharge measurements in general, when considering aspects such as restrictions of surface wave dimensions, acquired range resolution, and antenna sizes. Further research and testing is required for the HF band and nautical X band radar to assess their applicability for the purpose of river current measurements. Table 3.2 Expected performance of radar systems for extreme conditions.

Expected performance

High water level (submerged floodplain

Low water level Areas with tidal influence

HF band radar (CODAR Seasonde and WERA)

Limited, not proven. Limited, not proven Limited, not proven

UHF band radar (CODAR Riversonde)

Good, proven Limited/moderate, not proven Good, proven

X band radar coupled to software (WAMOS and SeaDarQ software)

Moderate, not proven Limited, not proven Limited, not proven

K band radar -Sommer

Moderate, not proven Good, proven Moderate, not proven

K band Flo-Dar Limited, not proven Good, proven Limited, not proven

K band Mutronics Moderate, not proven Good, not proven Moderate, not proven

3.3 High frequency radar: WERA and Seasonde Application Two well-known HF band radar systems designed for mapping ocean surface currents are the CODAR Seasonde (Coastal Ocean Dynamics Application Radar - Seasonde) and the WERA radar (Wellen radar), shown in Figure 3.1 and 3.2, respectively. They are shore based radar systems, designed to monitor ocean surface currents and waves. Both systems use the resonance of Bragg waves to derive current velocity information (see Appendix A for explanation on Bragg waves). A single radar station only provides radial current information. Therefore two radar stations are required to allow determination of the full 2D current field, both for WERA and the Seasonde. The spacing between two radar stations is typically more than 6 km, but is dependent on the operating range and differs for WERA and Seasonde.

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The major difference between the Seasonde and WERA, is that the Seasonde is a direction finding system and WERA is a phased-array system. When measuring with a direction finding system, phase differences are measured at each frequency in the backscattered signal at each antenna. (Wyatt, 2005). The SeaSonde employs the MUltiple SIgnal Classification (MUSIC; Schmidt, 1986) algorithm to maximize the signal to noise ratio and then performs a search function to determine the direction of arrival of the signal (Toh, 2005). With the phased array system, phase differences are added to the signal at each antenna of the array in the post-processing phase. In this way phase differences at the different antennas are used to effectively look in all directions at the same time. Compared to WERA, the main disadvantage of the Seasonde is that the used direction finding method requires a long measurement period of about 1 hour. This can be a problem in situations when there is a rapid variation in currents, resulting in less accurate determination of surface currents compared to WERA. The advantage of the Seasonde over WERA on the other hand is that it is much more compact (see Figure 3.1 and Figure 3.2). The Seasonde consists of a single transmitter and receiver antenna (Figure 3.2) opposed to WERA that requires a separate transmitter and receiver array, the latter composed of up to 16 receive antenna elements (Figure 3.1, center). The size of WERA can be reduced to a small receiver 4-square antenna configuration, which is sufficient when only measuring current velocity (Figure 3.2). This relatively compact configuration could be attractive for the purpose of current measurements on rivers, although it has not been tested under these conditions yet (and still two radar stations are required).



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Figure 3.1 Examples of WERA transmit- and receive arrays. Top: Rectangular transmit array consisting of 4

elements. Middle: Linear receive antenna array consisting of 16 elements. This configuration is used to measure the full 2D wave spectrum (both current and wave information). Bottom: Alternative compact square receiver configuration consisting of 4 antennas of WERA. This configuration is used to measure current information only. From http://ifmaxp1.ifm.uni-hamburg.de/WERA_Guide/WERA_Guide.shtml.

Rectangular transmit array

Linear receive array

Square receive array

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Figure 3.2 Left: Transmit antenna of the CODAR Seasonde Right: Mast with receiver antenna of CODAR

Seasonde that can also be used as a combined transmit-receive antenna. The CODAR Seasonde is used to measure surface current information only. From http://www.codar.com/SeaSonde_gen_specs.shtml

Field experiments and operational sites A significant number of published studies exist (~30), describing the application of WERA in different settings and for various purposes. The left side of Figure 3.3 shows an example in which surface currents are measured by WERA radar near Rotterdam. The CODAR Seasonde is operational at numerous locations worldwide and over 100 Seasonde systems have been sold. Most of the Northern American coast is covered with data obtained by the Seasonde, including several estuaries. The right side of Figure 3.3 shows an example of the result of surface current measurements obtained with the Seasonde in the Gulf of Farallones, California (Cough et al., 2010).

Figure 3.3 Left: Results of surface currents measured by WERA in front of Rotterdam harbour (Gurgel et al.,

1999). Right: Results of surface currents measured by the CODAR Seasonde in the Gulf of Farallones, California (Cough et al., 2010).



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3.4 Ultra-high frequency radar: CODAR Riversonde Application The Codar Riversonde is a UHF band variant of the CODAR Seasonde specifically designed for the purpose of river current measurements (see Figure 3.4). The Riversonde transmits a coherent gated FMCW signal and uses scattering information of Bragg resonant waves to measure current information, similar to Seasonde and WERA. To allow determination of the full 2D current field (both velocity and direction) two Riversonde stations are required, being typically spaced 100-150 m (Teague, 2008). In order to determine discharge, separate stage measurements are required to be performed simultaneously with the Riversonde measurements, since Riversonde only measures current velocity. The Riversonde is a compact system that can be relatively easily placed on a mast at the side of a river. According to the technical specifications, a maximum distance of 20 m to the river side is recommended to be used and a measuring range of 300 m can be attained. However it has been demonstrated to be able to perform well even when positioned 140 m distance from the river side, and providing measuring out to 1400 m range from the radar (Teague et al., 2011). Given this, the obtained measuring range is expected to be sufficient for wide river systems, including (submerged) flood plains. Riversonde measurements are restricted to a minimum water depth of 0.15 m. Water waves of 0.35 m wavelength are required to allow resonance of Bragg waves, which can be created by sufficient wind speed (> 0.73 m/s), or turbulence caused mainly by bottom roughness (Riversonde manual, 2008; Teague, 2008).

Figure 3.4 Left: CODAR Riversonde consists of a three-yagi antenna composed of a central transmitting element,

and two receiving side elements. Right: The enclosure of the Riversonde, allowing generation, transmission and reception of the radar signal. From Riversonde manual (2008)

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Field experiments and operational sites In a recent study performed by Teague et al. (2008), two Riversondes were used simultaneously to measure 2D flow patterns in the Sacramento-San Joaquin River Delta system. Figure 3.5 shows an example of flow vectors obtained with the two Riversondes. Flow vectors were compared to vessel-mounted ADCP measurement at two different locations for data validation (see Figure 3.5). Additionally the wind speed was measured, because of the strong dependence of the Riversonde data quality on this parameter. The results showed that for the first location at Walnut Grove (Figure 3.6, left) data of moderate quality were collected, due to unfavorable weather conditions (low wind speeds). For the second location at Threemile Slough (Figure 3.6, right) measuring conditions were more favorable, with wind speeds of 2.0 m/s, showing good data quality and consistency between Riversonde and vessel-mounted ADCP results. The number of operational Riversonde sites could not be verified. At least there is one site in China where the Riversonde is currently operational.

Figure 3.5 Results of current velocity measurements in the Sacramento-San Joaquin River Delta system, in which

Riversonde measurements (red flow vectors) were compared to vessel-mounted ADCP measurements (blue flow vectors) at two different locations (Left: Walnut Grove; Right Threemile Slough)). From Teague et al (2008).

3.5 Nautical X band radar coupled to software Application Nautical X band radars are installed worldwide and have potential to be used to provide information of ocean current velocity, when coupled to dedicated processing software. The software packages WAMOS and SeaDarQ are both capable of extracting current and wave information from nautical X band radar. Information on the sea-state is derived from measured data by analyzing radar time series within specific software. Figure 3.6 shows an example of nautical X band radar placed on a lighthouse. Surface water waves are required to be present with a minimum wave height and wave length of 0.5 m and 15 m, respectively (communication with Nortek on November 23rd 2011). The radar signal should be vertically polarized (see Appendix A for explanation on polarization effects). The original raw radar data are required to allow determination of current velocity,



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and to prevent data loss due to anti-clutter filters. Measurements are restricted to a minimum water depth of approximately 5 m. For shallower water, additional information on the water depth is required to calculate the intermediate- or shallow water phase velocity that is required to determine the current velocity (eq. 8).

Figure 3.6 Placement of nautical X band radar on a lighthouse. Field experiments and operational sites WAMOS is used in several studies to provide information on the sea conditions. Case studies show that SeaDarQ software can be used to successfully map oil spills and to distinguish the border of freshwater and seawater. The left side of Figure 3.7 shows results of measurements at the Westerschelde processed by SeaDarQ. At this location measurements were complicated due to a lack of surface waves with suitable wave lengths for current determination, and current velocities could not be derived. Nevertheless, data on the Westerschelde did allow establishment of current directions. The right side of Figure 3.7 shows an example of a radar image visualized by WAMOS. WAMOS is the market leader, with more than 30 operational sites worldwide to map ocean current velocity. SeaDarQ currently has operational sites in Rotterdam and Ameland.

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Figure 3.7 Left: Results of the Westerschelde, where nautical X band radar was analyzed with SeaDarQ showing

the presence of a vortex (provided by Nortek, November 2011). Right: Example of a radar image visualized by WAMOS software. The color is a measure for the intensity of the scattered wave.

3.6 K band radar: Flo-Dar, Sommer and Mutronics Application Three K band radar systems are considered, designed to measure current velocities at a spot at the water surface. These are the Flo-Dar, Sommer (RG30/RQ30) and Mutronics (MU2720) systems, manufactured by the companies Marsh-McBirney, Sommer and Mutronics, respectively (Figures 3.8 and 3.9 and 3.10). All three systems operate in the K band, which is a specific frequency band within the EHF frequency range (see Figure A.2).

1. The radar measures both water level and current velocity and is specifically developed to measure current velocity in confined flow conditions, such as sewers. For the determination of water levels, also Ultrasound measurements are used (see Figure 3.8).

2. Sommer provides two types of K band radars; the RQ-30 and RG-30. The RQ-30 provides information on both current velocity and water level at a point at the water surface, whereas the RG-30 system only measures flow velocity.

3. The Mutronics radar only measures current velocity. The hardware design of Mutronics differs slightly as it is made to be stationed temporarily. It consists of an antenna being placed on a tripod, making it a mobile system (see Figure 3.10). It is operated with an android-based tablet. Increased effort is required to protect it from vandalism, if being installed on a permanent basis.



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Figure 3.8 Left: Flo-Dar system. Right: Overview of placement of Flo-Dar to measure flow velocity and water level.

Figure 3.9 Sommer RQ-30 radar.

Figure 3.10 Mutronics radar.

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Field experiments and operational sites In the Netherlands, the Flo-Dar has been used by Waterboard Rijn en IJssel for current measurements on a small confined canal with filtered sewage water. The Sommer radar is currently operational at several locations worldwide. At the river Rhine in Austria (Vorarlberg), the RQ-24 radar of Sommer is currently operational for river flow measurements. Figure 3.11 shows two applications of the Sommer system. At the left side it is placed on a bridge and the right side shows an example where it is being placed on a cable, spanned over a river. Figure 3.12 shows results of flow velocity and stage measurements during the flood of the Rhine in August 2005 at Vorarlberg, Austria. There are no studies known to the authors demonstrating performance of the Mutronics radar on rivers. Currently, 12 Mutronics systems are active in South-Korea and an additional 20 systems will be installed in 2012 (personal communication with Mutronics in March 2012).

Figure 3.11 Placement of the Sommer system at a bridge (left) and on a cable spanned over a river (right). From

Sommer manual.



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Figure 3.12 Flow velocity (blue) and stage (red) measured with the Sommer RQ-30 during the flood of 2005 in the

River Rhine at Vorarlberg, Austria (adapted from: www.sommer.at).

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3.7 General applicability of radar systems Based on the assessment of radar systems (sections 3.3-3.6), this section addresses their general applicability for the purpose of river discharge determination from current velocity measurements. The criteria to compare and evaluate radar are:

1. General restrictions; Critical parameters to allow current velocity measurements, such as dimensions

of surface water waves, surface roughness, water depths and wind speed; Data- accuracy and resolution; Weather conditions; Antenna dimensions, transmit power and measurement time.

2. Possible requirement of radio- and building permits; 3. Validation studies.

3.7.1 General restrictions The general restrictions for applicability of radar systems for continuous river discharge measurements are summarized in Table 3.3 for each radar system. Critical parameters to allow current velocity measurements Table 3.3 shows that application of the WERA and Seasonde both rely on the presence of large-scale surface water waves. Surface waves of this size generally do not occur naturally under extremely low and regular discharge conditions, although they can incidentally be generated by passing ships (See Appendix B, Table B.1 Surface wave characteristics on inland water). Only under extreme high water level with sufficient wind speed these surface waves can occur naturally. The applicability of the Riversonde requires the presence of surface waves of 0.35 m wave length, such that Bragg wave resonance occurs. This criterium is expected to be satisfied during regular and extremely high water levels, provided there is sufficient wind speed. For extremely low water levels this will be more problematic, also taking into account the minimum required water depth of 0.15 m. A threshold value for minimum wave height could not be found from literature for the Riversonde. Two Riversondes are required to measure both current velocity and current direction. Two CODAR Riversondes are required to measure both current velocity and current direction. Separate stage measurements are required to be performed simultaneously with the Riversonde measurements to determine discharge, as the Riversonde only measures surface current velocity. Application of nautical X band radar coupled to software is restricted to large scale surface waves, of 15 m wavelength. Such surface waves are only expected to occur incidentally on inland water, during high water levels/sufficient wind speed or due to passing ships. A second restriction is that measurements are restricted to a minimum water depth of approximately 5 m. For shallower water, additional information on the water depth is required to calculate the intermediate- or shallow water phase velocity that is required to determine the current velocity. Additionally, to extract current velocity information from X band radar data a vertically polarized signal is required, possibly not always available for all nautical X band radar (see Appendix A for explanation of polarization). Implementation of K band radars is restricted to sufficient surface roughness.



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Finally, it should be mentioned that in general, the occurrence and interference of various wave types might result in unwanted bias in the measured current velocities and directions for the considered radar systems. Further research is required to address the impact of this effect on the obtained data, and recommended to take into account in a pilot project. Data- accuracy and resolution The accuracy of current velocity measurement of the considered radar systems is listed in Table 3.3, which is obtained from literature and product sheets. In addition, the range resolution and angular resolution for radar systems is given. Range- and angular resolution are not applicable for the K band radar systems as the data measured with these systems is representative for one single spot at the water surface only, in contrast to the other considered radar systems (WERA, SeaSonde, Riversonde, Nautical Xband radar) that obtain multiple data points distributed along an area the water surface. Comparing accuracy values of the considered radar systems is not a straightforward exercise, as they are expressed in different physical units by the respective manufacturers. However, values of accuracies, range- and angular resolution of WERA and Seasonde are comparable, both having a range resolution too coarse for river dimensions (Table 3.3). In addition, Flo-Dar, Sommer and Mutronics show comparable values for accuracies, but it is not clear from the information provided by the manufacturers whether the accuracy percentages are related to the reading or to the maximum measuring range. Weather conditions Application of radar current velocity measurements relies on the existence of specific surface waves (to allow Bragg wave resonance) and/or sufficient surface roughness. Both are dependent on wind speed. Therefore, wind speed is recommended to be measured with anemometers during radar measurements, which will help in performing successful data analysis. Wind can also affect currents near the water surface. A correction can be made for this effect by measuring the wind vector during the radar measurements (Plant et al., 2005). From the considered radar systems, only the performance of K band radars is known to be limited by heavy rain or fog. This results in a decrease in accuracy of measured current velocity for these systems (additional decrease in accuracy of measured value by ~5-6 cm/s for Sommer). Antenna dimensions, transmit power and measurement time Both WERA and the Seasonde require two stations to measure the full 2D current velocity field, which are typically spaced more than 6 km, both requiring an unblocked view towards the water. This requirement will be difficult to meet when measuring on inland waters in the Netherlands, due to presence of buildings and obstacles. The other radar systems are quite compact, although the placement height, and antenna orientations do vary. K band radars are the most compact systems. The K band radar of Sommer can also be placed on a cable spanned over the river. An interesting possibility is the placement of K band radar system next to a submerged flood plain, which has the potential to allow measurements under high discharge settings at selected points. A spatial limitation of radars are the lower and upper boundaries of the measurement range (Dmin and Dmax), which are listed in Table 3.3. Regarding the Riversonde, it should be mentioned that although a distance of 20 m to the river is recommended to be used, it is able to perform well even up to 140 m distance (Teague et al., 2011).

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The peak transmit powers of the considered radar- which are of relevance for radio permits – are listed in Table 3.3 and annotated with Pt. The HF radars have the highest peak transmit powers and the K band radars have the smallest peak transmit powers. The time required to perform one complete current velocity measurement at the surface is indicated in Table 3.2 and annotated with tm. The measurement time is of importance since it determines the frequency with which discharge measurements can be determined from surface current velocity measurements. Rijkswaterstaat defines the frequency required for continuous discharge measurements as once every 10 minutes. The only radar that does not meet this condition is the CODAR Seasonde. The measurement period of Mutronics could not be found, but is expected to be less than 10 minutes.

Table 3.3. Overview of general restrictions of radar systems to allow current measurements. Restrictions are only

listed when they are relevant for system performance for discharge measurement on inland water. Abbreviations: sw = wave length of surface wave, hsw, = wave height of surface wave , zmin.=minimum water level, Vwind =minimum wind speeds, Avel =accuracy of velocity measurement, Rrange=range resolution, Rang=angular resolution, Vmin= minimum water velocity, Vmax=maximum current velocity, n.s.=not specified, Dmin=lower boundary of the measurement range, Dmax= upper boundary of the measurement range, Pt= Peak transmit power, tm=measurement time for current velocity,.

Radar system Critical parameters to allow velocity measurements

Accuracy and resolution

Weather conditions

Antenna dimensions, transmit power and measurement time

WERA (HF band)

sw=5 m (at 30 MHz) -zmin>1 m -Vmin=n.s. -Vmax=n.s.

-Avel=0.05-0.10 m/s -Rrange=250 m at 30 MHz -Rang=1 -5

-Sufficient wind speed required

-Large size, two stations required, each consisting of Tx and Rx antenna array. -Dmin= not specified -Dmax= 300 km. -Pt=30 W -tm~10 minutes

Seasonde (HF band)

sw=5 m (at 30 MHz) -zmin> 1 m -Vmin= n.s. -Vmax= n.s.

-Avel< 0.07 m/sec -Rrange=200-500 m at 30 MHz operating frequency -Rang=1 -5


-Moderate size; two stations required, consisting of Tx and Rx antenna -Dmin= not specified Dmax=220 km -Pt=80 W -tm~60 minutes



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Radar system Critical

parameters to allow velocity measurements

Accuracy and resolution

Weather conditions

Antenna dimensions, transmit power and measurement time

Riversonde (UHF band)

-Surface roughness

sw=0.35 m (at 435 MHz) -zmin>0.15 m -Vmin= 0.025 m/s. -Vmax= 4 m/s

-Avel=5% of maximum value -Rrange ~ 5-15 m -Rang=1

-Sufficient wind speed required (> 0.73 m/s)

-Compact -Pt=1 W -Dmin=3 m -Dmax=20 m -tm~5 minutes

Nautical X band radar coupled to WAMOS or SeaDarQ

sw=15 m -hsw=0.5 m -zmin=5m -VV polarization -Vmin=n.s. -Vmax= n.s.

-Avel=+/-0.1m/s -Rrange=3.75 -7 m -Rang=1


-Compact -Dmin=100 m Dmax=3500 m -Pt>25 kW -tm~1.5 minutes

Sommer (K band)

-Surface roughness -Vmin =0.3 m/sec -Vmax=15 m/s

-Avel=+/-0,5%

-Sufficient wind speed required -Effect of rain/fog

-Compact -Dmin=0.5 m -Dmax = 35 m -Pt=400 mW -tm~4 minutes

Flo-Dar (K band) -Surface roughness -Vmin= 0.23m/s -Vmax = 6.10 m/s

-Avel=+/-0.5%


-Compact -Dmin=0 m -Dmax=6 m -Pt<10 mW -tm~1 minute.

Mutronics (K band)

-Surface roughness -Vmin= 0.03 m/s -Vmax = 20 m/s

-Avel~+/-3% up to +/-10% (dependent on current velocity)


-Compact -Dmin=n.s. -Dmax=100 m -Pt=n.s. -tm=not specified

3.7.2 Possible requirement of radio- and building permits The technical specifications relevant for radio- and building permits are provided in appendices C, D, E and F for HF band-, UHF band-, nautical X band-, and K band radar respectively. It is currently not clear for all systems if a radio- or building permit is required to allow implementation in The Netherlands. For operation of the WERA- and Codar Seasonde radar, a radio permit is probably required. Both WERA and Seasonde will require a building permit, as it concerns a (semi)-permanent installation (~months) and both radars require two stations spaced > 6 km. The Seasonde is relatively compact. The space required to install WERA, can be limited to a compact square receiver antenna consisting of 4 antennas to measure only surface currents.

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The UHF Codar Riversonde might require a radio permit. A relatively small amount of space is required for its placement, although building permits are probably required to place the antenna at a height between ~3 to 15 m. For the application of nautical X band radar coupled to software it is very attractive to use systems already operational near river sites, for which radio/building permits are already arranged. For installation of a new nautical X band radar radio/building permits are probably required (2.5 m length antenna at a minimum height of 15 m). The K band radar systems probably do not require a radio permit. Building permits are probably relatively easy to arrange for compact sized K band radars. For all radar systems measures are required to protect them from vandalism.

3.7.3 Validation of radar for current velocity measurements on rivers There are no studies known to the authors that demonstrate performance of WERA and CODAR Seasonde on rivers. Existing studies generally are related to measurements of the ocean state. A significant number of studies are performed with the Codar Riversonde in different settings and countries (various publications by C. Teague and J. Costa). Existing studies also demonstrate successful performance of the Riversonde for current measurements in areas with tidal influence (Styles, 2007). The most favorable approach seems to be the combined use of the Riversonde with vessel-mounted ADCP to optimize data validation of the Riversonde data (Teague et al, 2008). The Riversonde has not been used for river current measurements in the Netherlands yet. There are no existing studies showing successful performance of WAMOS or SeaDarQ coupled to nautical X band radar on rivers. Because of the large amount of nautical X band radars already operational near rivers worldwide and the required need of river current information, published results would already be expected if this system/software combination would have potential for the purpose of river current measurements. Within the Netherlands, the Waterboard Rijn en IJssel has experience with Flo-Dar measurements on filtered wastewater in a small confined canal and a small stream. The Sommer system is used in various countries for the purpose of discharge determination from current velocity measurements on rivers. Finally, a relevant and interesting study is presented by the USGS (Costa et al., 2006), showing results of a comparison between performances of different radar systems for a period of 4 weeks, including continuous wave microwave radar, UHF Doppler radar, a pulsed Doppler microwave radar, and a ground penetrating radar. They conclude that non-contact radar methods of flow measurement appear to be as accurate as conventional methods. Furthermore they state that radar measurements are suited to obtain data when standard contact methods are dangerous or cannot be applied, and provide insight into flow dynamics which is not available from detailed stage records alone.

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4 Numerical models for discharge simulation

4.1 Introduction The purpose of this chapter is to investigate the possibilities to improve real-time, continuous discharge determination of rivers using 3D, physics-based numerical models, for extreme events. Numerical models could offer potential to merge data from different measurement techniques (i.e. both in horizontal and vertical plane). For instance, HADCP data of current velocity measured inside the water body can be coupled to surface measured current velocity from radar. Table 4.1 gives an overview of models that were considered for an assessment in this report. The results are presented in Section 4.2, summarizing the feasibility of implementation of physics-based numerical models for extreme conditions. The general purpose of numerical modeling of rivers is discussed in section 4.3. The background of numerical models is discussed in section 4.4. Section 4.5 elaborates upon the different possibilities of numerical modeling, both on the short term as on the long term. Section 4.6 presents criteria for the selection of a numerical model. Section 4.7 presents a shortlist of eligible models. A discussion on the choice of the modeling package is given in section 4.8. Table 4.1. Overview of models discussed in section 4.5. Name Developer Application CCHE3D

University of Mississippi

Mainly in USA; focus on influence of obstacles on river flow

Delft3D

Deltares/TU Delft Global; both river and coastal engineering

MIKE3

DHI Global; both river and coastal engineering

TELEMAC

European consortium

Global; both river and coastal engineering

WAQUA/ TRIWAQ

Svašek & Rijkswaterstaat

Operational support model

4.2 Implementation of numerical modeling for extreme conditions This chapter focused on the possibilities of improving real-time, continuous discharge determination of rivers using 3D, physics-based numerical models, particularly for extreme cases. For each extreme condition, different key phenomena play a dominant role, which is shown in the overview in Table 4.2. Turbulence and flow over/along obstacles are key phenomena for extreme high water levels. For extreme low water levels, the bottom roughness plays an important role. For areas with tidal influence, mixing between flow layers is an important phenomenon that increases complexity.



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Table 4.2 Key phenomena for numerical modeling of extreme conditions and feasibility for implementation in pilot study

Discharge condition

Extreme high water level

Extreme low water level

Areas with tidal influence

Key phenomena

Turbulence Flow over/along obstacles

Bottom roughness Mixing between flow layers; Morphodynamics; Vegetation

Feasibility Feasible for pilot study Feasible for pilot study Further study required The cases of extreme high and extreme low water levels are most suitable for a pilot study given their relatively low complexity and the suitability to combine models with a variety of measuring techniques. Modeling of areas with tidal influence is more complex and could be, upon successful completion of the pilot, subject of a future study. In Table 4.3 a summary is presented of numerical models that are described in this report. Table 4.3. Overview of important characteristics of the considered numerical models. *FE = Finite Element, FV =

Finite Volume. See paragraph 4.6.3. for an explanation. Model Agreement with basic

technical requirements

Additional technical specifications*

Availability of user expertise

CCHE3D FE/FV, non-open source

USA (University of Mississippi)

Delft3D FV, open source The Netherlands (TU Delft, Deltares and other institutes)

MIKE3

FV, commercial Denmark (DHI)

TELEMAC

FE, open source France (EDF)

WAQUA/TRIWAQ

Yes

FV, in-house Rijkswaterstaat

The Netherlands (Rijkswaterstaat)

4.3 Numerical modeling of rivers Numerical modeling of rivers can be applied to estimate river characteristics for locations and/or conditions for which no measured information is available. In the simplest form, a numerical model can for instance calculate or “predict” the redistribution of water in a bifurcating channel when only the discharge upstream is known (measured). For physics-based numerical models, the actual calculation is based on knowledge of physical processes, i.e. mathematical representations of fluid dynamics. These are differential equations that cannot be solved analytically, and are thus approximated numerically. The numerical model furthermore requires a numerical schematization of the area to modeled, i.e. the river(bed) geometry, bottom roughness, obstacles present (dams, etc.). Currently, Rijkswaterstaat uses the 2D WAQUA numerical model, which can cover large areas (i.e. the Rhine-Meuse system). By defining hydraulic boundary conditions at certain locations where measured information is available, estimations can be made of for instance expected water levels (in cases of extreme high water) or distribution of discharge (in case of

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water scarcity). The 2D WAQUA model uses a depth-averaged approach, which gives a representative output but ignores some processes that have a 3-dimensional nature (see paragraph 2.2.2.)

4.3.1 Future of 3D numerical modeling The future of 3D numerical modeling in river engineering can be considered twofold. 1 There is a long-term perspective to perform high-detail 3D physics-based modeling of

integral river systems (e.g. the Rhine-Meuse system) on a continuous, real-time basis. Depending on the desired accuracy of the outcome, this type of modeling could be feasible when high computational power (computer cluster) is available. Rather than improving discharge determination at a single measurement location through knowledge of flow characteristics, this type of modeling can be used to correlate multiple discharge input data at different locations. Chapter 4.4.3 briefly discusses this topic.

2 A similar model could be applied locally (few kilometers river length) to analyze the flow

patterns in rivers experiencing hydrological extremes, with the goal of improving the accuracy of discharge determination from measured water level and velocity. This is feasible with a current-day desktop PC and is the topic of this study.

4.3.2 3D physics-based, continuous real-time modeling of integral river systems Modeling of integral river systems such as the Rhine-Meuse system is currently performed using 2D models, such as WAQUA. 3D models can provide greater accuracy, and thus a long-term goal would be to perform 3D continuous modeling of a river system. Rijkswaterstaat already has a 3D model available (TRIWAQ), used on ad-hoc basis (e.g. for the determination of water levels for a hypothetical maximum discharge). However, the computational effort associated with 3D modeling is much higher than for 2D, which makes continuous real-time modeling at present only possible when substantial computational power is available. It is important to establish that every model will always require data input. For the modeling of integral river systems, data input is provided by the available measurement stations. This type of numerical modeling makes it possible to correlate the input from different stations and as such to infer statements on the accuracy of the data input. In example: at measurement location A flooding of the overbank occurs and the measurement is deemed inaccurate, but at upstream measurement locations B and C in two tributary rivers, normal flow occurs. The combination of measurements B and C and the modeling of flow in this part of the river can be used to check the accuracy of measurement at location A. Moreover, the model can be used to reduce the input (number of measurement stations) and to provide more flexibility as to the type and location of origin of the input data (alternative measuring instruments and relocation of measurement stations).

4.4 Background

4.4.1 Computational fluid dynamics The numerical models discussed in this topic are all examples of Computational Fluid Dynamics (CFD), a very important topic of science with a broad range of applications in engineering, medical science and others. For computational hydrodynamic models, the basis is formed by the Navier-Stokes equations. These equations, derived from Newton’s laws of motion, describe the action of force applied to a fluid, i.e. the resulting changes in flow. Apart



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from this conservation of momentum (Newton’s second law), computational hydrodynamic models also apply the principle of mass and energy continuity. Numerical models for CFD can be categorized in general purpose and specific purpose models. A general purpose model, such as Flow3D or ANSYS Fluent, is designed to deal with a range of specific applications. While add-on modules exist for specific applications, these general purpose models are not tailored for the required level of accuracy and can have lower computational efficiency than specific purpose models.

4.4.2 CFD in river engineering For the application of CFD in river engineering, a number of aspects of numerical models are important. First of all, the model should be tailored for free surface flows. A free surface flow exists when there is a boundary between a liquid and a gas with a large difference in density (i.e. the river water and air). Thus, a scheme needs to be developed to describe the shape and location of the surface. In addition, an algorithm is required to evolve the shape and location with time, and free-surface boundary conditions must be applied at the surface. Hydrodynamic numerical models are often simplified for the specific properties of the ocean or the river environment. The resulting equations are the shallow water equations, so called since the scale of features in the horizontal is much greater than in the vertical. Oceans and estuaries are much larger in length and width than they are in depth, and motions in them are predominantly horizontal (e.g. tides and currents). The shallow water equations allow for more efficient numerical solution of flow in this environment. Turbulence is another important topic in the field of CFD. When turbulence is present, it usually dominates all other flow phenomena and results in increased energy dissipation, mixing, heat transfer, and drag. Deterministic solutions of the non-linear fluid mechanics equations exist, but science has not advanced far enough for it to be used in engineering practice. A technique called direct numerical simulation can be applied to find “closure” in turbulence problems, but will not be possible for real world engineering problems in the coming decades due to enormous computational effort and data production (Yokokawa et al, 2002). Instead, refuge must be sought in engineering solutions. These include Reynolds-Averaged Navier-Stokes (RANS) models, Large Eddy Simulations (LES) and a large number of variations or hybrid forms. Research on this topic is making fast advances, while the readily available engineering solutions are being validated in physical modeling or case studies. A final important aspect of CFD in river engineering is the coupling between hydrodynamic- and morphodynamic processes. This coupling is highly important for the adequate modeling of interactions between sediment and river flow. An example is the occurrence of moving sand dunes on river bottoms. These dunes can have an important effect on the flow characteristics of a river, and should thus be incorporated in the numerical model.

4.4.3 Accuracy versus computational time Computational time is an important aspect of numerical modeling. This report aims at continuous, real-time modeling of river systems. “Continuous” means that high-frequency measurements are made “Real-time” means that the time required for the numerical model to perform its calculations (and for instance determine discharge) is below a certain threshold value. In the strict sense, real-time means that the computational time is equal to or less than

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real time. However, simulations with calculation time in the order of minutes might also be considered acceptable for monitoring of rivers, as Rijkswaterstaat requires discharge to be measured at 10 minute intervals. The possibility of real-time 3D modeling thus depends on four factors, discussed below:

(i) required accuracy of the model; (ii) computational efficiency of the model; (iii) available computational power and (iv) size of the model.

ad (i) The computational time required for one simulation run is highly dependent on the physical processes that are taken into account in the model. In general, the more processes are taken into account, the more accurate the outcomes are. In other words, computational effort increases with the required level of accuracy. Basic numerical models take only elementary processes into account and could, with the current availability of computing power, be capable of performing “real-time” calculations. However, for extreme conditions, more complex phenomena may dominate the river flow. An example is turbulence associated with riverbank overflow (Figure 2.5) or flow through a river bed in case of extreme low waters. In order to be able to accurately model these phenomena, more advanced processes need to be incorporated in the model, resulting in larger computational effort. ad (ii) The nature of the numerical model (finite element or finite difference) and the architecture of the software largely determine the computational efficiency of the model. Models with older origins might be less efficient that recently developed models, as the latter are specifically designed for the specifications of modern computer systems. A key example of this is the possibility of parallel processing. ad (iii) Computational systems range from desktop PCs to state of the art computer clusters such as the BlueGene/P cluster at the Rijksuniversiteit Groningen. Apart from the computing power, the availability or uptime of the system is very important, which can be increased by making the system redundant. ad (iv) The size of the model (ranging from a few kilometers river length or entire catchment areas), the size of the numerical grid and the number of input parameters affect the total computational effort required. While a small-sized model (few kilometers river length) could be run on a desktop PC, larger models require more computational power.

4.5 Numerical modeling for river flow pattern analysis

4.5.1 3D numerical modeling for the improvement of stage/velocity- discharge models Following the previous paragraphs, high-detail 3D numerical modeling should, at this point, primarily be regarded as a way to gain insight into the uncertainties that exist with the present determination of discharges, to quantify these and to aid the improvement of discharge determination from measured water stage and / or velocity. Accurate discharge determination is a vital aspect of river monitoring. While numerical modeling of integral river systems (see chapter 4.3.2) gain accuracy, the quality of the results is and will remain largely dependent on the quality or accuracy of the input data. As discussed in Chapter 2, a “discharge measurement” is actually a measurement of water velocity and/or



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water level, combined with a stage/velocity– discharge relationship to determine the discharge. The nature of this stage/velocity- discharge relationship is to a large extent empirical. For rare events, no or limited calibration data is available. The flow patterns for these cases might differ substantially from the “regular river condition”, yielding discharges different from those expected by simply extrapolating the empirical stage/- discharge relationship. Flow patterns are also sensitive to adjustments in river geometry. As such, the empirical relationship should be re-calibrated after changes have been made to for instance groynes. An analysis of these flow patterns is thus key to the determination of uncertainty and subsequently the improvement of the accuracy of stage/velocity- discharge relationships. By using advanced 3D numerical modeling, a range of scenarios can be simulated and the effects on river flow patterns analyzed. As mentioned in chapter 4.4.3, real-time calculations that can capture the complexity of the river system require large computational effort. Instead and more efficiently at this stage, a higher-complexity model could be used and simulation runs be performed for a number of scenarios. Examples of possible scenarios could thus be to simulate extreme high water levels with water running over floodplains while changing the geometry of obstacles (e.g. groynes). For low water levels, the impact of changes in bottom roughness could be investigated. Once these simulations for different scenarios have been calculated, they can subsequently be used to improve stage/velocity-discharge determination for extreme conditions. An example is given in paragraph 4.5.3. In a broader perspective, of the analysis of river flow with numerical models will have a number of benefits, listed below.

(i) Quantification of the uncertainties in currently used stage/velocity-discharge relationships;

(ii) Improvement of stage/velocity- discharge relationships for extreme conditions.

(iii) Analysis of optimum locations for current velocity measurements, both in the horizontal plane as in the vertical plane. This allows combining data results of different measurement techniques. An example is coupling of HADCP measurement results to surface measured current velocity from radar for discharge determination;

(iv) Flexibility of a stage/velocity- discharge relationship to changes in the river geometry. This means that a stage-velocity relationship can easily be adapted when changes to the geometry of the river have been made that affect local flow patterns.

4.5.2 Scientific reference studies Several studies have been carried out using 3D numerical (CFD) models to analyze flows in rivers. However, most of these studies either address flows through small rivers (e.g. Wilson et al., 2003), the specific impact of vegetation or river geometry on flow structures (e.g. Stoesser et al., 2003), or the impact of structures on river flow (e.g. Kilanehei et al., 2011).

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Figure 4.1 Measured (a) versus calculated (b) velocity profiles from Nihei and Kimizu (2009). Nihei and Kimizu (2009) used a combination of HADCP and 3D numerical modeling for the determination of discharge. They aimed at using a physics-based model for real-time determination of discharge from HADCP measurements. Their model yielded accurate results for average flow in the main river channel. However, the simplified model that they used showed little predictive value for flow near the riverbanks. The authors state that this could be improved by adopting a more accurate turbulence model for horizontal eddy viscosity.



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Figure 4.2 Observed and modeled streamwise velocities in a river cross-section at the measuring height of an

HADCP from Nihei and Kimizu (2009). The continuous line indicates the modeled velocity profile. Note the inaccuracy of the modeled results near the riverbanks.

The conclusion reached by Nihei and Kimizu (2009) points in the direction that higher-detailed modeling is inevitable when simulating extreme river flows, e.g. the turbulence caused by flow over riverbanks or over/along obstacles. Incorporating these phenomena will substantially increase the computational time.

4.5.3 Example of application In this section, an example of application is given. A numerical modeling study is performed in order to improve the stage/velocity- discharge model for a certain measurement location where riverbank flooding occurs under extreme high water levels. We assume pilot location X with already installed HADCP measurement system and a readily available and up-to-date schematization. For 1 km of river length, a high-density numerical grid is built. Hydraulic boundary conditions for the upstream and downstream boundary are initially estimated. Next, calibration is performed by running a simulation for regular flow conditions and comparing the water velocities as simulated by the model with those measured by the HADCP and those measured by incidental vessel-mounted ADCP measurements. The hydraulic boundary conditions are adjusted to calibrate the model and simulations are run until the model results approximate those measured in reality. Once calibrated for regular flow conditions, the model is run for a number of scenarios by changing the upstream and downstream hydraulic boundary conditions; thus in essence for a range of possible flow conditions. As such, flooding of the riverbanks can be simulated. Within the modeling software, a fictive HADCP line can be defined, yielding simulated velocity measurements. The final result of these simulation runs is thus a range of discrete simulated discharges with associated simulated velocity measurements; factually a stage/velocity- discharge relationship. This simplified example could be carried out in similar manner for simulating the influence of for instance extreme low waters or geometry alterations. An added benefit of this type of modeling is its highly visual character. Users of the discharge monitoring system can be

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presented with (3D) images of water velocities in the river section. As such, users will gain a more detailed insight in the flow patterns of the river.

4.5.4 Choice of measurement location Numerical models can be used for determination of optimized locations for stage and current velocity measurements. Modeling results of flow patterns can be used to identify locations along the river that are characterized by flow behavior being representative for a river transect. Measuring at these optimized locations can contribute to more accurate stage and current velocity information under a large range of discharge scenarios, in turn yielding improved discharge information. However, the following aspects should be considered when planning new measurement locations:

The physical access towards the river, e.g. possible obstruction by obstacles; (Near)-future changes in river geometry resulting from policy measures should be

considered, as this will affect flow behavior at the selected location; When changing the location of an existing measurements station the existing data

time-series at the former measurement location is finished. This will result in restrictions when determine discharge time-trends at that location.

4.5.5 Uncertainty and validation As with any (numerical) modeling study, the outcome should be treated with great care and should be judged by an expert user. Proper choice of modeling parameters is vital for the accuracy of results. To assess the influence of modeling parameters, sensitivity analyses can be performed. Uncertainty of numerical CFD models is a topic of research by itself. The uncertainty in the outcome of the numerical simulation can be decomposed into three categories: (i) uncertainty in the input data (the schematization), (ii) uncertainty resulting from assumptions in equations underlying the numerical model (physics-based formulae) and (iii) uncertainty in the numerical solution. Quantification of these uncertainties can be performed through verification and validation. Verification is defined as “a process for assessing numerical uncertainty USN and, when conditions permit, estimating the sign and magnitude of the numerical error *SN itself and the uncertainty USCN in that error estimate” (Stern et al., 1999) or “The process of determining that a model implementation accurately represents the developer’s conceptual description of the model and the solution to the model” (AIAA, 1988) Validation is defined as “a process for assessing modeling uncertainty USM by using benchmark experimental data and, when conditions permit, estimating the sign and magnitude of the modeling error SM itself.” (Stern et al., 1999) or “The process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model”. (AIAA, 1988) Verification addresses the third category of uncertainty, while validation concerns the combined uncertainty of all three categories. Validation thus adds the specific uncertainties of



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the problem under study; i.e. the physics-based formulae involved and the input data. As a consequence, validation is usually performed for a range of possible problems, such as standard laminar flow, turbulent flow, flow over/along obstacles, etc. For the purpose discussed in this report, the influence of bottom roughness, modeling of flow over/along obstacles and the modeling of turbulence are key phenomena that require attention. For these phenomena, multiple (semi-empirical) formulae and modeling strategies exist, for which the choice will be based upon the expertise and experience of the user. Validation can be performed by comparing simulated results with (notably vessel-mounted ADCP) velocity measurements and quantifying the differences. These measurements in turn have their own uncertainties, which should be taken into account during validation.

4.6 Evaluation of models

4.6.1 Criteria for the choice of modeling package Providing a comparison of available numerical models is a complex task, given the different character of models, the influence of user input on the final result and the research status of specific modules. The following factors can be distinguished in the choice of modeling package: 1. Agreement with basic technical requirements 2. Additional technical specifications that increase the accuracy 3. Implementation, operation (GUI) and user training required These factors will be discussed in the following paragraphs.

4.6.2 1: Basic technical requirements In order to make a shortlist of eligible models, a number of basic technical requirements can be set. Langendoen (2001) provided an overview of available models, and listed the technical requirements. At that time, the models considered were 2DH (depth-averaged). From the formulated requirements, those most relevant for the purposes discussed here are listed below: Accurate simulation of depth-averaged or fully 3D flow.

– Capability to simulate subcritical flow, supercritical flow, and transition from one state to the other.

– Wetting and drying of parts of the domain, for example when point bars or groins become submerged or protrude the water surface.

– Suitable solution method. – The model should provide current velocity data that can be linked to the

measurement data (e.g. radar measurements of surface current velocity). Accurate simulation of depth-averaged or fully 3D sediment transport by distinguishing

bed load and suspended load transport by size class. Appropriate coupling of flow, sediment transport, and changes in channel form. Parameterization of vertical profiles of horizontal flow components and sediment

concentration. Capability to accurately schematize the physical domain including structures. Efficient solution method to simulate large time periods. Ability to cope with unsteady boundary conditions.

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In addition to these basic requirements set by Langendoen (2001), also the possibility for (future) nesting in larger-scale models should be considered.

4.6.3 Additional technical specifications A number of models will meet the basic technical requirements discussed in paragraph 4.6.2. In this paragraph, a number of additional technical specifications are discussed that either increase the possibilities and in consequence the accuracy of the model (but at the same time the complexity and simulation run time) or have an effect on the efficiency of the numerical solver. 2D Depth-averaged versus fully 3D models 2D models with vertical (depth) averaging (termed 2DH) apply an integration over the depth of the channel, while fully 3D models incorporate specific processes that cannot be modeled using depth-averaging. 2DH models apply parameterization to account for these processes. Lane et al (1999) stated that 3D models have a higher predictive ability, particularly if the 2D model is not corrected for the effects on flow structure of secondary circulation. It should be noted that fully 3D modeling heavily increases the computational effort required, and the computational time required for such a simulation can be considerable. Finite element versus finite volume A classical distinction can be made between finite element packages and finite difference/volume packages. Finite element (FE) packages have a superior ability to deal with a solution domain having a complex geometry by using unstructured grids. However, FE solution methods for strongly coupled and non-linear equations tend to be computationally intensive (Ranade, 2002). Finite Volume (FV) packages have faster algorithms but do not (yet) have the support for unstructured grids, which means that they are limited to curvilinear grids. These grids cannot as easily be locally refined as unstructured grids. However, ongoing research is in developing hybrid forms of structured and unstructured grids. As such, FV packages will have similar capability for complex geometries as FE packages. Morphodynamic coupling The coupling between morphodynamic (sediment transport) and hydrodynamic processes is largely empirical-based, i.e. it uses empirical formulae. A coupling is vital to simulate sediment transport and deposition processes. Specifically for rivers, the coupling is necessary for simulating more advanced water-bottom interactions, such as river dune development. Modeling flow over/along obstacles An important aspect of numerical modeling in river engineering is the appropriate modeling of flow over or along obstacles, e.g. groynes. Different methods of simulating obstacles are used to compare the performance of these modeling strategies is beyond the scope of this document.

4.6.4 Implementation Depending on the character of possible studies using numerical models, the choice of model package will also be influenced by implementation issues. A pilot study could be carried out by or in tight collaboration with the supplier of the model, while for longer term use in-house expertise might be preferred. Any numerical modeling study requires a thorough understanding by the user of the software used and of the choices made. Examples are the choice of grid dimensions, boundary conditions and turbulence model. As such, the accuracy of the method will be heavily influenced by the specific model expertise of the user.



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Thus, for possible future in-house use of numerical modeling for the purpose discussed here, the ease of implementation, the required initial user training and the support required during operation are important, both in terms of costs as well as quality of the produced results.

4.7 Available models Table 4.1 gives an overview of some of the major modeling packages available that match the requirements for this purpose. The list presented here is not exhaustive, however, the models listed here are the most widely used and accepted models. In the following paragraphs, the listed models are described in more detail. Furthermore, references are made to validation studies relevant to the purpose discussed in this report. The WAQUA/TRIWAQ software is listed separately, because it does not possess a coupling between hydrodynamics and morphodynamics. However, a significant user experience exists since the package is the in-house software for Rijkswaterstaat and thus it will be discussed as a special case. It should be noted that apart from these “market-ready” numerical packages, most universities develop their own numerical modeling software. TU Delft has developed some widely acknowledged software (SWASH and SWAN), partly incorporated in other packages. These models could be tailor-made for the specifications of this project. CCHE3D1

Figure 4.3 Simulation of the Mississippi river flow velocities using CCHE3D. Source:

http://www.ncche.olemiss.edu/sites/default/files/files/docs/cche3d/applications.pdf.

1. http://www.ncche.olemiss.edu/cche3d

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CCHE3D is a freely available, non-open source 3D FE/FV model developed by the University of Mississippi. Primary applications are river engineering projects in the USA, specifically on the influence of obstacles on river flow. Figure 4.3 shows an example of simulation of river flow velocities in the Mississippi using CCHE3D Delft3D2 Delft3D is the modeling suite developed by the Technical University of Delft and research institute Deltares, the Netherlands. It is an open-source 2D/3D FV package that has a wide range of applications. Delft3D is an integrated modeling suite, which simulates 2D or 3D flow, sediment transport and morphology, waves, water quality and ecology and is capable of handling the interactions between these processes. Figure 4.4 shows results of river flow patterns modeled in Delft3D, visualized in Google Earth.

Figure 4.4 Results from Delft3D modeling presented in Google Earth MIKE3 The MIKE models are developed by the DHI group, an independent international research and consultancy group. MIKE is a 3D FV model, providing an array of computational methods for steady and unsteady flow in branched and looped channel networks, and flood plains.

2. http://www.deltaressystems.com/hydro/product/621497/delft3d-suite

3. http://www.mikebydhi.com



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TELEMAC4 TELEMAC is an open-source 3D FE package, originally developed by Electricité de France (EDF), now supported and developed by a consortium of European partners. TELEMAC therefore has a wide support base, particularly in Europe.

Figure 4.5 Maximum flow in the Isle River valley with TELEMAC. Source:

http://www.opentelemac.org/images/Publications/a89.pdf WAQUA/TRIWAQ WAQUA (2D) and TRIWAQ (3D) form part of the SIMONA hydraulic modeling package, which is the in-house software for Rijkswaterstaat. These packages are now specifically used to determine hydraulic boundary conditions.

4.8 Choice of modeling package In this paragraph, the models are discussed for the factors mentioned in paragraph 4.6.1. Table 4.2 shows an overview of important characteristics of the considered numerical models.

1. Agreement with basic technical requirements All models mentioned in the previous paragraphs meet the basic technical requirements. 2. Additional technical specifications that increase the accuracy

The main theoretical difference is between the FV packages (Delft3D, MIKE, WAQUA/TRIWAQ) which have more efficient algorithms, but have a less flexible (structured) grid. CCHE3 and TELEMAC are computationally much more expensive, but have the advantage of having an unstructured grid, which allows for more detailed

4. http://www.opentelemac.org/

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modeling in specific areas. An example of possibly increased accuracy is the modeling of flow over obstacles (e.g. groynes). 3. Ease of implementation, operation (GUI) and user training required

The ease of implementation cannot be judged from the given overview. All models have a graphical user interface (GUI), of which the quality is subjective to the user. However, for this specific use, a significant higher user experience will exist at Rijkswaterstaat for WAQUA/TRIWAQ, thus limiting the user training required.

Delft3D and TELEMAC are open-source freeware, which will limit the costs. WAQUA/TRIWAQ is in-house software and will thus overall require less effort However, all models will have costs of implementation (hardware, training) and operational management. To gain more insight into these costs, a more detailed specification of work is required.

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5 Synthesis and implementation in a pilot project

Chapters 3 and 4 show that improving current velocity measurements using radar techniques and numerical models to improve stage/velocity- discharge relationships will yield better discharge data for extreme conditions, including low and high discharge events. However synthesis of methods, including conventional-, radar techniques and numerical model, is considered to biggest gain to improve quality and quantity of discharge data. Several key aspects and phenomena are expected to be important for data synthesis, which are discussed in more detail in section 5.1. In section 5.2 a pilot study is proposed, to test and validate the combination of radar and numerical modeling techniques and include considerations and general guidelines for a pilot project. A detailed work plan including cost estimates are outside the scope of this report and should be made before planning any field activities.

5.1 Key aspects for synthesis and implementation Radar data of current velocity at the water surface are defined by a pixel in 2D (x and y direction only) at the water surface. Using numerical models, data from these 2D pixels can be used to calculate the current velocity of a water body in 3D. Although this is currently not possible to calculate in real time, using predefined correlations could convert real time radar data into discharge data. Do note that in order to properly calculate the current velocity in the water body it is necessary to also continuously obtain stage data, wind speed and disturbances of surface waves. The result is a model cell -a 3D cell (x, y and z). Using vertically stacked model cells a vertical velocity profile representative for a specific location of finite xyz- dimensions can be built. Similarly traditional current velocity measurements inside the river water body (e.g. ADM and HADCP) can be used to specify average current velocities within cells. This allows for comparison of cells of different datatypes. Big advantage is that by averaging different datatypes (e.g. ADM, HADCP, radar and model) (un)certainties can be quantified.

5.1.1 Considerations for using radar data The major difference between radar measurements and conventional current velocity measurement techniques is that radar measures current velocity at a confined area at- or very near to the surface, whereas traditional measurement techniques (HADCP and ADM) measure inside the water body and yield data at a given height. Radar systems recognized most favorable are the UHF Riversonde radar and the K band radar systems. Important considerations for using surface current velocity data obtained with these systems are summarized:

UHF Riversonde radar o Measures spatial and temporal surface current velocity variation at a

significant area of the water surface o Coupling between Riversonde data and conventional data is feasible

based on this assessment. This system can measure over the entire river width (also under extreme high discharge conditions), and is therefore expected to provide data at the same scale as existing measurement techniques do.



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o Two Riversondes are required to measure simultaneously to reconstruct the 2D current velocity field. In practice the situation can occur that for a relatively short time window, data is measured with one Riversonde only (e.g. due to system failure of the other system).

o Additionally, stage measurements need to be performed simultaneously with the Riversonde measurements.

o A limitation of the Riversonde is the minimum water depth of 0.15 m that is relevant for extreme low discharge with low water levels or in extreme high discharge conditions along shallow parts of flooded banks. However, flow velocities in these parts will be rather low.

K band radar

o Measures temporal surface current velocity variation at a single spot at the water surface.

o Approach for coupling of K band radar data to conventional data will differ from the approach used for the Riversonde data, due to the scale differences between the data types. The K band data only provides point data, being representative only for a confined area (spot) at the river surface.

o For average and broad rivers, several K band systems are required to measure at various points along the river cross section to accurately reconstruct the flow patterns along the river. This approach is successfully illustrated in Plant (2005), yielding mean velocities that are nearly as accurate as those obtained from conventional measurements.

Radar measurements of surface current velocity can be distorted by factors such as wind, rain, fog and interference of various surface waves (generated by ships, wind and turbulence). Near-surface effects of wind on current patterns can complicate reconstruction of an accurate velocity profile (also see Figure 2.1). A correction can be made by simultaneously measuring the wind during radar measurements. Comparison to conventional measurement results is required to assess if data quality is acceptable after correcting for wind drift correction. It is essential to perform both vessel-mounted ADCP measurements and stage measurements simultaneously with radar measurements during initial implementation of radar (at least during a pilot project). With this accurate velocity profiles are independently obtained that can be used for quality control of discharge information obtained from radar- and model results.

5.1.2 Temporal and spatial aspects of combining model- and measurements The time interval at which the discharge is calculated from models and radar measurements should be restricted to 10 minutes. In practice, this is not expected to be a limitation with respect to computational power, as the model simulations of velocity profiles at different model cells, will be calculated prior to implementation. The defined size of model cells can be flexibly adjusted and tuned to the size of a measurement cell of a certain instrument (e.g. radar-, HADCP- or ADM cell). The size of measurement cells relies on the resolution of the data obtained with a given instrument. Therefore, direct coupling between measurement cells of different data types is not expected to be possible, without the use of model cells.

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5.1.3 Quantification of uncertainty in discharge determination When multiple datasets are used to determine river discharge, the uncertainty is composed of the uncertainties that are present within the individual datasets (e.g. radar- ADM, HADCP, vessel-mounted ADCP) and the uncertainties related to the models. Uncertainties related to individual measurement techniques should be carefully understood and quantified. Currently a better understanding is required of the uncertainties related to the analysis of radar measurements.

5.2 Pilot Project In the pilot study a phased approach is proposed in which radar technique(s), numerical model(s) and traditional measurement techniques are combined to test and demonstrate their performance for continuous measurements both in regular and extreme discharge conditions. Such an integrated approach is expected to improve the accuracy of discharge determination and to allow quantification of the accuracies obtained with the individual techniques by comparing the outcomes of the measured datasets. The pilot study should aim at the case of extreme high water levels. The case of extreme low water levels inherently means that less data will be available because the water level will be below the measurement line of a HADCP or ADM instrument. Although in spite of that, the case of extreme low water levels might also be suitable for a pilot study, the chance of both extreme high- and low water levels occurring within a limited timeframe is low. Setting up a pilot study to cover both extreme cases would thus require a very long measurement timeframe. The third case, discharge in areas with tidal influence, is considerably more complicated than the other two cases as the phenomena that occur are highly complex and the availability of data is usually low. The cases of extreme low water levels and discharge in areas with tidal influence can be addressed at a later stage. Important considerations for the choice of specific radar systems and numerical model(s) to be tested in a pilot are described in sections 3.7, 4.6 and 4.8, respectively. Preferably, both a K band radar (Sommer and possibly Mutronics) and the UHF band Riversonde radar are tested within the pilot, together with at least two different numerical models. Two CODAR Riversondes are required to measure both current velocity and current direction. Separate stage measurements are required to be performed simultaneously with the Riversonde measurements to determine discharge, as the Riversonde only measures current velocity. Additionally, wind speed and direction should be measured. Although the models under consideration are state-of-the-art in research, no specific additional research (e.g. programmatic effort) will be necessary to implement these models. For most rivers in the Netherlands, modeling studies have already been made, and as such the river schematization (including summer/winter bed decomposition, bed roughnesses, obstacles, etc.) and basic modeling parameters will be available. This will substantially reduce the effort needed to initiate the modeling activities in the pilot project. However, the required effort will depend on whether the existing model schematizations meet the required level of detail in the grid and output rate, and whether changes have occurred in the river bed after the model was constructed (natural or artificial). For a pilot project with the Delft3D modeling suite, the preparation of a model for a pilot study is estimated to cost roughly 2 to 4 man weeks. Important considerations for choosing a measurement location are carefully described in section 4 of the STOWA report (chapter 4). Additionally the following criteria are of importance when choosing pilot location X:



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The test period and the pilot location are chosen such that there is a high chance of occurrence of extremely high discharge conditions. A minimum measurement duration of 3 months is recommended to achieve this.

Continuous discharge measurements are already performed (by ADM and/or HADCP) and stage/velocity- discharge relationships are well defined for the location under regular discharge conditions. This allows validation of radar and numerical models under this condition.

Schematization of the entire river bed cross-section, including outer banks should be well known to constrain boundary conditions of the numerical model.

The pilot location should provide enough possibilities to test the effect of height and distance between radar instrument and water surface. Furthermore, the effect of the orientation of the radar (e.g. directed upstream on bridge or cross-stream along sides) is important to be tested. Especially for K band radar instruments, the possibilities of performing accurate measurements by orienting the antenna perpendicular to the stream flow direction requires testing in the pilot.

Objectives defined for regular discharge condition at pilot location X:

1. Numerical models: a. Simulation of stage/velocity- discharge relationships using numerical

model(s). b. Validation of discharge simulation calculated by numerical models. This can

be achieved by comparing simulated stage/velocity- discharge relationships generated by numerical model(s) to existing stage/velocity discharge relationships and measured data (ADM, Vessel-mounted ADCP and/or HADCP measurements).

2. Radar: a. Determine discharge from radar measurements of surface current velocities

by using existing stage/velocity- discharge relationships. Preferably, both UHF band CODAR Riversonde radar and K band radar (Sommer and possibly Mutronics) are tested in the pilot. Radar measurement results can be validated and accuracies quantified, by separately determining discharge from additional measurements (ADM, Vessel-mounted ADCP and/or HADCP measurements) and comparing the outcomes the discharge results obtained by radar

b. Assess whether radar measurements can be used to provide discharge information on a continuous basis (every 10 minutes) under regular discharge conditions;

c. The effect of the following factors on radar measurements should be carefully examined:

I. Height, distance and orientation of radar instrument with respect to the water surface.

II. Weather conditions (e.g. dependency on wind, rain and fog). These factors are simultaneously measured using a weather station and wind speed and direction meter,

III. Surface wave dimensions and surface roughness and their dependency on weather conditions and ship waves,

IV. Surface wave interference patterns between wind waves, ship waves and waves resulting from turbulence.

3. Validate the combined performance of radar and numerical models Assess the possibility of real-time coupling of radar velocity measurements to existing and simulated stage/velocity- discharge relationships.

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Objectives defined for extreme high discharge condition with submerged floodplains at pilot location X:

1. Numerical models: a. Simulation of stage/velocity- discharge relationships using numerical

model(s); b. Validation of discharge simulation calculated by numerical models, by

comparing the simulated results to separate incidental discharge measurements that are simultaneously obtained with vessel-mounted ADCP;

c. Assess whether numerical models allow accurate and continuous discharge simulations under extreme high discharge conditions.

2. Radar: a. Determine discharge from radar measurements of surface current velocities

using the stage/velocity- discharge relationships simulated by numerical models.

b. Validate performance and quantify accuracy of radar measurements by comparing the measurement results to separate incidental discharge measurements obtained simultaneously with vessel-mounted ADCP.

c. Assess whether radar measurements allow discharge measurements under extreme high discharge conditions on a continuous basis (every 10 minutes).

Finally, from the outcomes of the pilot study, a guiding document can be developed for the roll-out of simultaneous use of radar, models and traditional discharge measurement techniques for a large number of measuring stations.

5.3 Long-term implementation Based on the outcomes of the pilot, the most promising radar technique(s) and the stage/velocity- discharge relationships simulated by numerical models can be adapted for a large number of measuring stations in the Netherlands. Real-time computations with numerical models and live input data should be considered if simulation runtimes turn out to be acceptable (given expected near-future development in computer power).

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6 Conclusions

This report assesses the feasibility of using radar for measuring current velocity and using 3D numerical models to improve the continuous determination of discharge from measured water level and/or current velocity. A review of radar systems and numerical modeling and their combined use is presented in this report. Furthermore, technical requirements and selection criteria are used to compare and evaluate radar systems and numerical models. The most important conclusions for radar techniques and numerical models are: Radar

Seven radar instruments are presented for the purpose of obtaining current velocity measurements on rivers. These radar systems potentially offer valuable information under extreme river conditions. The radar instruments are compared and their expected performances, based on relevant criteria defined by RWS and Deltares, are discussed.

Three radar systems are recommended to test further. Not coincidently, these systems are currently used to obtain current velocity measurement on rivers - the CODAR Riversonde (UHF band)-, Sommer (K band) radar and Mutronics (K band) radar. These systems are recommended to test in a pilot project establish their suitability for continuous discharge measurements in extreme conditions.

Both nautical X band radar coupled to software (WAMOS and SeaDarQ) and HF band radar systems (WERA and Seasonde) are currently applied only for ocean current measurements. These systems are in general not expected to be applicable for the purpose of river discharge measurements.

The performance of radar measurements relies on the presence of surface water waves and/or surface roughness that can be generated by different factors, such as wind, turbulence and ships or their combined effect.

Numerical models Numerical models can be used to compute flow patterns, vertical velocity profiles and

new stage/velocity- discharge relationships for a short stretch of river, for regular and extreme discharge conditions.

Five models are pre-selected for this purpose: CCHE3D, Delft3D, MIKE, TELEMAC and WAQUA/TRIWAQ. Criteria for the choice of modeling package are discussed.

Numerical models can help in quantifying uncertainties of discharge determined by stage and current velocity measurements.

It is recommended to implement a model at a location where conventional discharge measurements are performed and river schematization is available.

Real-time modeling of discharge with live-input data is expected to be possible in the near future, given current developments in software and hardware. This could be the next target after the currently proposed pilot project.



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Synthesis of radar and numerical models Review of available information shows that discharge can be determined continuously

in extreme conditions by coupling current velocity measured at the water surface with radar, to new stage/velocity- discharge relationships simulated by numerical models. However, validation of these techniques for Dutch settings is necessary before it can be operational.

Synthesis of radar and numerical models should also include traditional methods, i.e. with ADM, HADCP and vessel-mounted ADCP. This should be included in the proposed pilot project, in which the performance of numerical models and radar are evaluated.

It is recommended that a pilot project is conducted on a test site in which government, universities, research institutes and companies collaborate.

In summary, there is a high potential for improvement of continuous determination of discharge in extreme conditions. The combination of multiple techniques (conventional techniques, radar, numerical modeling) should be applied in a pilot study to obtain a quantitative insight into the possible advantages for the water information system.

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7 References

Articles AIAA, 1998, Guide for the Verification and Validation of Computational Fluid Dynamics Simulations, G-077-1998 Barrick, D.E., Headrick, J.M., Bogle, R.W., and Crombie, D.D., 1974, Sea backscatter at HF: Interpretation and utilization of the echo, Proc. IEEE, 62, 673. Boiten, W., 2000, Hydrometry, Published by Balkema, Rotterdam Borge, J.C.N, Rodriguez, G.R., Hessner, K., Gonzalez, P.,I., 2004, Inversion of marine Radar images for surface wave analysis, Journal of Atmospheric and Oceanic Technology, volume 21, pp. 1291-1300 Costa, J.E., R.T. Cheng, F.P., Haeni, N., Melcher, K.R. Spicer, E., Hayes, W., Plant, K., Hayes, C., Teague, and Barrick, D., 2006, Use of Radars to monitor stream discharge by noncontact methods, Water Resour. Res., 42, W07422, doi:10.1029/2005WR004430 Cheng, R.T., Costa, J.E., Haeni, F.P., Melcher, N.B., and Thurman, E.M., 2002, In search of technologies for monitoring river discharge, in Younos, Tamin, ed., Advances in Water Monitoring Research, Water Resources Publication, p. 203-219. CODAR Ocean Sensors, Ltd., 2008, RiverSonde™ Non-Contact River Monitor, Model 100 Documentation Gurgel, G. Antoischki, Essen, H.H., Schlick, T., 1999, Wellen Radar (WERA), a new ground-wave based HF Radar for ocean remote sensing,.Coastal Engineering, VOL 37, NOS. 3-4, ISSN 0378-3839, pp. 219-234 Helzel T., M. Kniephoff, L. Petersen, 2006, WERA: Remote Ocean Sensing for Current, Wave and Wind Direction, US/EU Baltic

Kilanehei, F., Naeeni, S.T.O. and Nami, M.M., 2011, Coupling of 2DH-3D Hydrodynamic Numerical Models for Simulating Flow Around River Hydraulic Structures. World Applied Sciences Journal 15 (1): 63-77, 2011

Kingsley, s. and Quegan, S., 1999, Understanding Radar systems, ISBN: 1-891121-05-7978-1-891121-05-0 Lane, S.N., Bradbrook, K.F., Richards, K.S., Biron, P.A., Roy, A.G., 1999, The application of computational fluid dynamics to natural river channels: three-dimensional versus two-dimensional approaches. Geomorphology, vol. 29, issues 1-2, pp1-20 Langendoen, E.J., 2001, Evaluation of the Effectiveness of Selected Computer Models of Depth-Averaged Free Surface Flow and Sediment Transport to Predict the Effects of Hydraulic Structures on River Morphology. US Department of Agriculture / National Sedimentation Laboratory, Mississippi (USA).



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Nihei, Y and Kimizu, A., 2008, A new monitoring system for river discharge with horizontal acoustic Doppler current profiler measurements and river flow simulation. Water Resources Research, vol. 44, doi:10.1029/2008WR006970 Plant, W. J., W. C. Keller, and K. Hayes, 2005a, Measurement of river surface currents with coherent microwave systems, IEEE Trans. Geosci. Remote Sens., 43, 1242– 1257. Ranade, V.V., 2002, Computational flow modeling for chemical reactor engineering. Academic Press, London RIKZ, 2003, Evaluatie Landelijke Fysische Monitoring, bijlage bij Weten Wat We Meten. RIKZ, Den Haag. SeaDarQ brochure, 2011 Shiono, K. and Knight, D.W., 1991, ‘‘Turbulent open channel flows with variable depth across the channel’’, Journal of Fluid Mechanics, Vol. 222, pp 617-646 (vol. 231, October, p 693). Sommer Discharge measurement system, User manual RQ-30, October 2011

Spain, P., Barrick, D., Teague, C., 2006, Remote sampling of river discharge using Radar and sonar: combining RiverSonde Radar and Channel Master ADCP provides a new angle to an old measurement problem, Sea Technology, vol. 47, no. 2, pp. 35-44.

Stern, F., Wilson, R.V., Coleman, H.W., Paterson, E.G., 1999, Verification and validation of CFD studies. Iowa Institute of Hydraulic Research Report No. 407

Stoesser, T., Wilson, C. A. M. E., Bates, P. D. and Dittric, A., 2003, Application of a 3D numerical model to a river with vegetated floodplains. Journal of Hydroinformatics, 05.2, 2003

Hartong, H. Termes, P., 2009, Handboek debietmeten in open waterlopen, STOWA 2009-41

Styles, R., Teague, C.C., 2007, Evaluation of a UHF Radar Surface Current Mapping System in an Intertidal Salt Marsh, J. Atmos. Oceanic Technol., vol. 24, pp. 2120-2127. DOI: 10.1175/2007JTECHO538.1. Teague C.C., D. E. Barrick, P. Lilleboe, R. T. Cheng, 2004, UHF RiverSonde Observations of Cowlitz River Flow Velocity at Castle Rock, Washington, IEEE. Teague, C.C. Barrick, D.E. Lilleboe, P.M. Roarty, H. Holden, D. Goldinger, D., 2011, Extended-range Riversonde operation on the Hudson river, Current, waves and turbulence measurements,.pp. 78-80, Monterey, Canada Toh, K., Y., D., 2005, Evaluation of surface current mapping performance by Seasonde High Frequency radar through simulations, Thesis, Naval Postgraduate School, Monterey WAMOS brochure, 2011

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Wilson, C.A.M.E., Boxall, J.B., Guymer and I., Olsen, N.R.B., 2003, Validation of a Three-Dimensional Numerical Code in the Simulation of Pseudo-Natural Meandering Flows. J. Hydraul. Eng. 129, 758 (2003); doi:10.1061/(ASCE)0733-9429(2003)129:10(758)

Wyatt, L.R., 2005, HF radar for coastal monitoring – a comparison of methods and measurements. Presented at Oceans 2005, Brest, France, June 20-23, 2005 Yokokawa, M., Itakura, K., Uno, A., Ishihara, T., and Kaneda, Y., 2002, "16.4-TFlops Direct Numerical Simulation of Turbulence by a Fourier Spectral Method on the Earth Simulator", Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, Baltimore MD. Websites: 1http://www.ncche.olemiss.edu/cche3d 2http://www.deltaressystems.com/hydro/product/621497/delft3d-suite 3http://www.mikebydhi.com 4http://www.opentelemac.org

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Possibilities of discharge measurements under extreme situations, using Radar and Numerical models

A-1

A Theory of radar

A.1 Introduction The term radar is short of “RAdio Detection And Ranging”. The principle of radar consists of the transmission and reception of electromagnetic waves by using antennas. The radar steers the transmitted signal over a certain angle in order to cover an area. The transmitted signal will scatter off a target that it encounters, and a small amount of energy is scattered back to the radar, where it is subsequently amplified, processed and visualized. A radar signal can be physically described by the properties of a wave. The velocity of a wave is related to its wave length and frequency by c f [1] Where c is the velocity of light in air (3x108 ms-1), f the frequency (s-1) and the wave length (m). The distance from the transmitter antenna to a target from which a radar wave is scattered, is defined by the range (R):

/ 2dR c [2]

Where d is the time delay between the time of signal transmission and of reception of a scattered signal. Figure A.1 illustrates the basic principle of radar. Important properties that characterize radar systems are the:

Frequency Polarization Modulation Geometrical resolution (range resolution and azimuthal resolution) Accuracy of the data Coherency of radar signal Approach for velocity determination

These properties will be addressed in the following sections.

Figure A.1 Basic principle of radar.

Possibilities discharge measurements under extreme situations,


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A-2

A.2 Classification of electromagnetic frequencies A classification of radar systems based on the frequency content of electromagnetic waves is shown in Figure A.2. The range of frequencies usable for radar purposes lies within 3 MHz to 300 GHz, within which the following ranges are identified (see Figure A.2):

high frequency (HF), very high frequency (VHF), ultra high frequency (UHF), super high frequency (SHF) and extremely high frequency (EHF).

Furthermore, different frequency-band names are defined by the NATO-system, and some additional frequency-bands were defined during the Second World War for military purposes. In addition to the classification scheme, the term microwave radar is often used to define the frequency band from 1-100 GHz.

Figure A.2 Overview of the classification of electromagnetic waves, based on frequency content (From Kingsley

and Quegan, 1999).

A.3 Polarization of electromagnetic waves The radiation field of an antenna is composed of electric and magnetic lines of field strength. These electric- and magnetic lines of field strength are always at right angles to each other. The polarization of electromagnetic waves is determined by the electric field, and a distinction is made between polarization of the transmitted and received electromagnetic wave. Radars can transmit horizontal (H) or vertical (V) electric-field vectors, and receive either horizontal or vertical return signals, resulting in several transmit/receive polarization combinations. This is illustrated in Figure A.3, showing respectively vertical transmit/vertical receive (VV), horizontal transmit/horizontal receive (HH) and vertical transmit/horizontal receive polarization (VH). VV polarization is the preferred configuration when studying waves on the water surface, because electromagnetic waves are more sensitive to water waves in the vertical plane compared to the horizontal plane. HH polarization is the preferred configuration for ship

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A-3

detection. VH or HV polarization is used for detecting ship superstructures and various ice formations.

Figure A.3. Illustration of different types of polarization of transmitted and received electromagnetic waves. From

left to right VV, HH and VH polarization. From http://envisat.esa.int/handbooks/asar/CNTR1-1-5.htm#eph.asar.ug.choos.specfeat.dupol.

A.4 Modulation technique Two types of modulation techniques are generally considered in radar: pulse- and continuous wave (CW) radar. The differences between these modulation techniques are illustrated in Figure A.4. A pulse radar transmits a short pulsed signal and waits until the signal returns, such that the radar either transmits or receives (Figure A.4). Pulse radar requires a pulse length that is proportional to the range (e.g. long pulse for long range). Continuous wave (CW) radars continuously transmit electromagnetic radiation, as opposed to pulsed radar systems (see Figure A.4). This implies that they transmit and receive at the same time. A CW radar cannot measure range because there is no basis for the measurement of the time delay. CW radar allows measurement of the Doppler shift to determine the speed of a target. The Doppler shift is the change in frequency of a radar signal measured along the beam direction, that results from the motion of the target on which the signal scatters (Kingsley and Quegan, 1999). A distinction can be made between CW radars with and without frequency modulation, the latter referred to as FMCW radar. An intermediate form between pulse and CW radar exists, termed gated FMCW, that is introduced by CODAR. FMCW radar continuously transmits a signal, but additionally varies the frequency of the signal (Figure A.4). With this, the range of a target can also be determined in addition to the Doppler shift velocity measurement. The range is determined from the time delay between transmission and reception that is expressed by a frequency-shift in returned signal. A FMCW radar requires a bandwidth that is proportional to the range (e.g. large bandwidth for long range). Considering FMCW radar, the difference between the transmitted and received frequency are smaller for short ranges compared to long ranges and therefore less bandwidth is required (Kingsley and Quegan, 1999;5).

5. http://www.navigate-us.com/files/uploads/file/Review_5_Radar-1-1.pdf



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Figure A.4. Illustration of different types of modulation techniques; pulse radar, CW radar and FMCW radar.

Adapted from www.navigate-us.com and www.fas.org.

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A-5

A.5 Resolution of radar A distinction between range resolution, azimuthal resolution and angular resolution can be made. The range resolution defines the minimum distance in the range direction that two objects need to be separated to allow distinction by radar. With pulse radar, objects are distinguishable if the time duration between reflections from two objects is greater than the pulse length ( ). If the time duration between the echoes is smaller than , the objects will merge, and can not be distinguished. The range resolution of pulse radar is defined by

/ 2R c (m) [3] FMCW radar systems do not have a lower theoretical limit for range resolution. In practice their range resolution is limited by engineering implementation6. The azimuthal resolution is determined by the horizontal beam width of a beam and the distance from the point of scattering towards the antenna. Figure A.5 shows the geometry associated with definition of beam width and azimuthal resolution. The beam width is given by:

D (radians) [4]

Here D is the horizontal aperture of the antenna. The azimuthal resolution ( L) is defined by: RL

D (m) [5]

Where R is the distance to the antenna, as shown in Figure A.5. The angular resolution is defined as the minimum angular separation at which two targets can be separated when they are at the same range.

Figure A.5 Geometrical definitions of beam width and azimuth resolution L. See main text for further

explanation.

A.6 Accuracy of radar The range accuracy is defined as the degree to which the measured range agrees with the true range. This accuracy is dependent on:

Range resolution; Signal to noise ratio of the returned signal; The accuracy of the approach used to measure the range; The quality of the electrical components; Additional aspects, such as internal temperature stabilization to guarantee accuracy

at all times.

6. http://www.navigate-us.com/files/uploads/file/Review_5_Radar-1-1.pdf



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A.7 Coherent- and incoherent radar Coherency is a measure to which the phase of the transmitted radar signal is controlled by the radar. A distinction can be made between the coherency within an individual pulse and the coherency from pulse to pulse. The coherency within an individual pulse is defined as the degree to which the phase of the carrier wave of a pulse is stable and to which extent the phase evolves linearly with time. This type of phase-coherency is important to allow measurement of the Doppler shift of the returned signal. Determination of Doppler-shift from an individual pulse is possible, provided there is sufficient phase coherency within the pulse, and the length of the signals long enough. Radar systems are termed coherent from pulse to pulse, when the starting phase of the signal is controlled. To come to the starting phase of the next pulse, a coherent system determines how the end phase of the previous pulse would have theoretically evolved in between the two pulses. This is also referred to as “phase-locked”. Radars that have coherency from pulse to pulse allow determination of the Doppler shift of a combined set of successive radar measurements for a specific range cell. In addition, these radars can be used to measure the development of the phase of the received signal from successive received signals. For radar systems transmitting pulses that are incoherent from pulse to pulse, each pulse starts with a random pulse and is not phase locked.

A.8 Current velocity determination from radar measurements Two approaches exist for extracting current velocity information from radar measurements:

1. Analysis of time series of radar images to detect changes in image shapes based on the echo intensity only. This is suitable for pulse radars, that have limited phase coherency within a pulse, and lack coherency from pulse to pulse;

2. Determination by analysis of Doppler power spectrum. This is restricted to radars with sufficient phase-coherency within a pulse.

An important relation that is used to derive current velocities from radar data is the water wave dispersion relation, which is described in this section before further addressing the two approaches for current velocity determination. Dispersion implies that in an undisturbed situation (absence of currents), a surface/gravity wave with a given wave length travels at a specific phase velocity. Three dispersion relations exist to describe surface waves for deep, intermediate and shallow water, respectively (Lighthill, 1978). Deep water is defined for water depths h>0.5 , where h is the water depth. The deep water phase velocity is given by:

2deepgc [6]

Where g is the gravitational constant. Intermediate water is defined for depths 0.05 <h<0.5 , where the phase velocity is given by:

int2tanh( )

2g hc [7]

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Shallow water is defined for water depths h<0.05 , where the phase velocity is given by:

shallowc gh [8] Equation 6 shows that calculation of the deep-water phase velocity does not require information on the water depth h. For determination of the intermediate- and shallow water phase velocity, information on water depth is required (equations 7 and 8). The observed surface wave velocity (including the effect of currents) results from the combined effect of the phase velocity and the current. By subtracting the phase velocity from the observed surface wave velocity, the underlying current is found. Current velocity determination from Fourier analysis of radar image time series The observed surface wave velocity can be found using Fourier analysis of a to time series of (incoherent) radar images, on displacement of surface wave (crests and troughs) as a function of time. By subsequently subtracting the phase velocity found from the dispersion relation of surface waves (eq. 6-8) from the observed surface wave velocity, the underlying current velocity is found. This analysis is done in the Fourier spectrum by applying a 3D Fourier transformation to the radar image time series. Figure A.6 shows an example of time series of radar images is shown. Surface waves are required to be of sufficient size (wavelength and waveheight) in order to be distinguished on a single radar image. Also, surface waves should exist long enough to be recognized within successive radar images of a time series. A single radar system is sufficient to measure both current- velocity and direction.

Figure A.6. Illustration of a time series of incoherent radar images acquired with nautical X band radar. The surface

wave velocity is found from time series analysis of motion of peaks and troughs of surface waves. Current velocity is found by subtracting the surface wave velocity from the phase velocity. From Borge et al. (2004).

Current velocity determination by analysis of Doppler power spectrum For radar systems that have sufficient phase-coherency within a pulse, the observed surface wave velocity can be determined by analyzing the Doppler power spectrum of the received radar signal. An example of the Doppler power spectrum is shown in Figure A.7. This Figure



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A-8

shows the relative power of the frequency content, with the frequency being normalized by the centre frequency (f/fwo). The Doppler shifted signal is expressed by peaks in the Doppler power spectrum (see Figure A.7). These peaks will be spaced symmetrical around f/fwo=0, if there is an absence of underlying currents. In this case the corresponding velocity equals the phase velocity. Doppler shifted signals will be shifted up or down in frequency in the Doppler power spectrum, due to the presence of underlying currents. This is the case in the example of Figure A.7. Therefore the surface wave velocity of moving water, is found from the frequency of the Doppler shifted signal. The current velocity is found by subtracting the phase velocity from the surface wave velocity of moving water. The peaks in the Doppler power spectrum are also referred to as Bragg lines as they result from resonance of Bragg waves. Bragg waves provide a valuable source of information for current velocity determination. Bragg resonance describes the strong resonance effect that results from the interference of radar waves with surface waves defined by:

0.5water Radar . [9] For this specific wave length, the reflected radar waves add coherently resulting in a strong echo, expressed by Bragg lines in the measured Doppler power spectrum (Figure A.7). The optimal radar frequency for detecting Bragg waves can be found using equation [9]. Usually the water surface waves required for Bragg resonance are generated by wind speeds exceeding the phase velocity of the waves, or by surface turbulence caused mainly by bottom roughness. Bragg lines of different orders exist which is shown in Figure A.7 (indicated by first order- and higher order sea echoes). Bragg lines of the first and second order, respectively provide current- and wave information. For the purpose of obtaining discharge information on rivers from current velocities, analysis of first order Bragg peaks is sufficient. From second order Bragg lines, wave information such as significant wave height can be derived, which is useful for analysis of ocean waves.

Figure A.7 Doppler power spectrum showing the relative spectral amplitude against normalized Doppler frequency

(f/fwo).Deviations in symmetry of the first order peaks around f/fwo=0, reflect the effect of the underlying current velocity. This deviation is indicated by (from Barrick et al., 1974).

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B Wave heights on rivers and canals

The performance of radar systems on water depends on the presence of surface waves with a specific wavelength and height, as shown in the previous paragraph. This section provides a brief overview on the dimensional range of surface waves that can be expected on rivers in the Netherlands. Waves can be generated by either wind or ships, or water current. Waves generated by wind on rivers result in a water level fluctuation that depends on direction and endurance of wind, the fetch and the water depth. Under regular flow conditions, when river flood banks are not submerged, the fetch is small and wave heights are less than 0.20 m. During high water levels and sufficient wind speed, the fetch and the wave height will increase. When the wind is parallel to the stream direction the fetch will reach its maximum value. This can result in relevant wave heights, with a maximum of 1 m, but usually wave heights are less. In the design of levee defense, maximum wave heights in the order of 0.5 to 0.8 m are assumed. An example of waves generated by ships is given in Figure B.1. Wave components generated by a ship sailing with a constant speed consist of:

Primary waves, consisting of a front wave, water level depression, stern wave and return current;

Secondary waves; Propeller jet.

These waves occur both on a prismatic canal without a natural current, as on a river with a natural current and a shore with groynes and groyne fields, longitudinal dams, and a mobile river bed. The effects of the propeller jet are neglected here. In addition, a constant speed of ships is assumed, although it is known that speed variations from a ship do induce additional waves and currents.



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Figure B1. Example of ship waves along the Rhine. From: Google Earth. The primary wave system depends on the sailing speed, the ratio of the cross-sectional area of a ship with respect to the cross-section of the river, and the distance towards the banks. The primary wave is characterized by a lowering of the water level next to the ship, ranging from 0.2 to 1.0 m. The wave length of the primary wave equals the ship’s length. The speed of the waves is determined by the speed of the ship. Secondary ship waves are wave trains emitted at the bow and stern of the ship. These wave trains propagate at an angle towards the banks of the river. The heights of secondary ship waves are determined by the sailing speed and the dimensions of the ship. For conventional ships, associated wave heights can reach values up to 0.5 m, but for fast sailing vessels (service vessels, unloaded cargo ships, tugs) secondary waves can reach heights of even 1.0 m. Secondary waves are deep water waves. A characteristic property of secondary waves is that the wave height hardly decreases between ship and bank. Additionally, there is interference between ship waves and the natural current. Depending on the propagation direction of the waves relative to the current direction, the steepness will increase or decrease. Encountering and overtaking of ships may result in merging of interference peaks of the individual ships. During extreme high discharges, ship traffic might be forbidden and, subsequently, no ship waves are present. During low discharges, ships will continuously disturb the existing wind waves and the natural current pattern at the water surface. Also during low discharges, ship traffic might be forbidden. Table B.1 summarizes characteristic values for heights, lengths, and periods of waves generated by wind and ships on rivers and canals.

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Table B.1 Surface wave characteristic generated by wind and ships on inland water in the Netherlands. Type Wave height [m] Wave length [m] Wave period [s]

Wind waves (average water

levels)

< 0.2 < 4 < 1.5

Wind wave (high water levels)

0.2 - 1.0 m 4 - 20 1.5 - 3.5

Primary ship wave 0.2 – 1.0 30 - 150 5 - 50 Secondary ship wave 0.3 - 1.0 3 - 15 1.5 - 3

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C Technical specifications of HF band radar systems: WERA and Seasonde

C.1 WERA Geometrical characteristics The configuration of a WERA station consists of a separated location for transmitter and receiver antennas, illustrated in Figure C.1. WERA can measure the full-wave spectrum using a square transmitter array and a linear receiver array (Figure C.1). If only information on currents is required to be measured, the use of a square transmitter antenna configuration combined with a small square receiver antenna configuration is sufficient. Two WERA stations are required to measure the full 2D current field, including both transmitter antennas and a receiver antenna array. The recommended distance between the WERA stations is dependent on operating frequency (e.g. 15 km when operating at 28 MHz). Also, the antenna height and spacing need to be tailored for the working frequency of the radar.

Figure C1. An example of a WERA station. The recommended configuration of the transmitter antenna array is shown in Figure C2. It consists of a rectangular 4-element antenna array (see Figure C2.). The spacing between the elements needs to be adapted to the wavelength of the transmitted beam, in order to form an optimum beam pattern. The dimensions of the transmitter antenna array are approximately 5.4 x 1.6 m, when operating at 28 MHz (corresponding to = 10.8 m). Because the transmit antenna array transmits predominantly in seaward direction, the amount of radiation towards the mainland is reduced.



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Figure C2. Overview of geometry of transmitter antenna array of WERA. The grey squares represent the four

elements of the transmitter antenna array. From http://ifmaxp1.ifm.uni-hamburg.de/WERA_Guide/WERA_Guide.shtml. The configuration of the receive antennas is flexible and the number of antennas can be varied from 4 to 16 antennas, depending on the desired azimuthal resolution and the physical parameters to be measured. The recommended spacing between elements of the receive array is defined by the wavelength of the transmitted beam. A linear receive array consisting of 16-elements (phased array) is required to measure the full-wave spectrum (e.g. significant waveheight and wave directional spectra). A 12-element linear array can also be used for this purpose, but gives some coarser azimuthal resolution. The linear receive antenna array needs to be stationed parallel to the coastline, such that sea returns from the beam created by the transmitter array can be measured under multiple narrow angle bundles simultaneously. The field of view of a 16 element linear receive array is +/- 60° (see Figure C1). This should be taken into account when orienting two WERA sites, to allow sufficient data-overlap. A square 4-element receive array in combination with a 4-element transmit array can be used when only current information needs to be measured. The diagonal spacing of a 4-element receive array varies from 5 to 19 m, depending on the operating frequency. In order to ensure sufficient isolation on the direct path from transmitter to receiver array, a minimum distance of 100 m is required between the transmit and receive antennas . Pulse and data- characteristics WERA transmits a FMCW chirp signal, the phase of the transmitted signal being coherent both within the sweep and from sweep to sweep. WERA operates at frequencies between 6 and 30 MHz. When operating at 30 MHz, the range resolution and the range are approximately 0.25 km and 45 km, respectively. At this frequency, the corresponding wave length is 10 m, and Bragg resonance will occur with surface waves of 5 m wave length. The accuracy of velocity determination by analyzing WERA data is approximately 5-10 cm/s (Gurgel et al., 1999). WERA continuously transmits with a power of 30 W.

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Technical specifications WERA Manufacturer HELZEL Messtechnik GmbH

Representative in the Netherlands No

Type WERA

Frequency band(s) 29.85 MHz, 27.65 MHz, 16.045 MHz and 12.50 MHz

Bandwidth 50 kHz, 125 kHz and 500 kHz

Frequency modulation FMCW

Phase coherency within sweep Yes

Phase coherency from pulse to sweep Yes

Signal length 0.26 s (chirp)

Polarization Vertical (VV)

Transmitter orientation Perpendicular to shore

Duration of deployment (Semi) permanent

Type of configuration Separate transmitter and receiver antennas.

Receiver antenna array length 4-element receive antenna square array: 5 m (30 MHz)

16-element receive antenna linear array: < 55 m (30 MHz)

Distance between transmitting antenna and receiving antenna Minimum 100 m

Total antenna elevation Dependent on working frequency, 2.7 m above ground plane for 28 MHz

Minimum/maximum distance between radar and water surface As close as possible to the sea.

Dimension Long receiver antenna array, total length 170-550 m for 1 WERA-station

Transmit power 30 W continuously

Power supply Power cable of (115/230 V, 3*2.5 mm²) is required for operation of the power amplifier.

Range resolution 250 m at 30 MHz

Angular resolution Not specified

Accuracy velocity measurement ~5-10 cm/sec

Resolution velocity measurement Not applicable

Accuracy depth measurement Not applicable

Measurement duration ~10 minutes



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C.2 Seasonde Geometrical characteristics The CODAR Seasonde consists of a transmitter and receiver antenna. When operating at frequencies exceeding 24 MHz, the antennas can be placed on a single mast. Two separated radar stations are required for creating 2D surface current maps of direction and velocity. These should be spaced at a distance of 40-60% of the radar's offshore range. For a working frequency of 27 MHz, with an approximate range of 15 km, the radar spacing should thus be ~6-9 km. The total antenna elevation of the Seasonde (mast and whip) should be adapted towards the operating frequency, and ranges between 5.5 to 11 m. Pulse- and data characteristics Similar to WERA, the CODAR Seasonde transmits a gated FMCW chirp signal. The major difference between them being that WERA is a phased-array system, whereas CODAR Seasonde is a direction-finding system (see section 3.3 for further discussion on differences). The phase of the transmitted signal is coherent both within an individual pulse and from pulse to pulse. The Seasonde can be operated at three specified frequency modes termed standard (11.5-14 MHz or 24-27 MHz), Hi-Res (24-27 MHz or 40-45 MH), or Long-range (4.3-5.4 MHz). At the Hi-Res frequency mode, the range resolution and the range are approximately 0.2-0.5 km and 15-30 km, respectively. The accuracy of the Seasonde is < 7 cm/sec of the total current velocity (Seasonde Brochure 2011). The peak- and average power output of the Seasonde are respectively 80 W and 40 W.

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Technical specifications CODAR Seasonde Manufacturer CODAR

Representative in the Netherlands Aquavision

Type Seasonde

Frequency band(s) 4.3-5.4 MHz, 11.5-14 MHz, 24-27 MHz, 40-45 MHz

Bandwidth 25 kHz, 50 kHz, 75 kHz, 150 kHz

Frequency modulation Gated FMCW

Phase coherency within pulse Yes

Phase coherency from pulse to pulse Yes

Signal length Not applicable


Transmitter orientation Perpendicular to shore

Duration of deployment (Semi) permanent

Type of configuration Separate transmitter and receiver antennas.

Receiver antenna array length Not applicable

Distance between transmitter and first receiver Not applicable

Total antenna elevation Dependent on working frequency ~5.5 m to 11 m, For high frequency mode 7 m (combined Tx and Rx on single mast)

Minimum/maximum distance between radar and water surface As close as possible to the sea.

Dimension Transmit antenna: 4.8-9 m, Receive antenna 7 m

Transmit power Peak: 80 W, Average: 40W

Power supply 120VAC or 220VAC, 50-60 Hz

Range resolution 0.2-0.5 km, 0.5-3 km, or 3-12 km

Angular resolution 1-5

Accuracy velocity measurement <7 cm/s of the total current velocity


Accuracy depth measurement Not applicable


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D Technical specifications of Riversonde Radar

Geometrical characteristics Figure B1 illustrates the spatial restrictions and required placement conditions for the Riversonde. To allow determination of the full 2D current field (both velocity and direction) two Riversonde stations are required, being typically spaced 100-150 m (Teague, 2008). The Riversonde antenna needs to be placed on top of a mast and the system’s electronic enclosure attached to the mast. For optimal system performance, the antenna is positioned within 20 m of the water edge at a height ranging between 3 to 15 m (Riversonde manual, 2008). The central antenna element transmits the signal, and is pointed approximately perpendicular to the main water flow direction. The river width may vary between 10 to 300 m to allow good measurements. However, recent experiments on the Hudson river showed that these upper limits of the distance and height with respect to the river are conservative values. During this experiment, good results were obtained, with the Riversonde placed at a distance of 140 m from the river attaining usable information up to 1400 m distance from Riversonde (Teague et al., 2011). In this case study the antenna was placed approximately 40 m above the river surface.

Figure D1 Left: Overview of the detection limits of the Riversonde. Right: Overview of the required placement

criteria of the Riversonde. From Riversonde manual (2008). Pulse- and data characteristics The Riversonde transmits a gated FMCW chirp signal with an operating frequency range between 300 and 450 MHz, and requires a minimum bandwidth of 5 MHz. The opening angle is 90 degrees. The phase of the transmitted signal is coherent both within the pulse and from pulse to pulse Alternatively a system operating at a frequency range near 350 MHz can be chosen. Within this range, a band can be selected with a bandwidth varying between 10-30 MHz, corresponding to a pulse length of 0.1 s to 0.033 s, respectively. Predominant Bragg scattering occurs at a wave length of surface waves of 0.35 m (one half of the radar wave length) having a phase velocity of approximately 0.73 m/s (Teague et al., 2008). These waves usually are generated at a wind speed of at least the phase velocity, or by surface turbulence caused mainly by bottom roughness.



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The collected data are processed such that measured data points are spatially separated by in angle and 5 m in range. This results in a minimum cell size of ~5x5 m for each flow

vector. The accuracy of current velocity determination is 5% of the maximum measured velocity for the normal situation in which the Riversonde is placed at the riverbank and directed perpendicular to the main river flow direction. It should be mentioned that by directing the Riversonde upstream, the observed Bragg resonance effect might be stronger, possibly yielding increased accuracies in current velocity measurements. This aspect should be addressed in future research. The resolution of the measured flow velocity is 2.5 cm/second (Spain et al., 2006).The average and peak power of the transmitted pulse is 0.5 and 1 W, respectively (Riversonde manual, 2008). The measurement of current velocity by the Riversonde is restricted to a range from 0.025 to 4 m/s. Existing radio signals can be distorted by signal transmission of the Riversonde, but according to CODAR this distorting effect vanishes at distances larger than 2 km with respect to the Riversonde. Technical specifications Riversonde Manufacturer Codar

Representative in the Netherlands Aquavision

Type Riversonde

Frequency band(s) 420-450 MHz, optional 350 MHz

Bandwidth 10-30 MHz

Frequency modulation Gated FMCW


Phase coherency from pulse to pulse Yes

Signal length 0.1 s to 0.033 s


Transmitter orientation Perpendicular to riverbank

Duration of deployment Temporarily in pilot area.

Type of configuration

Riversonde consists of Tx-Rx antenna, with 3-yagi elements Two Riversondes are required to measure current direction, spaced 100-150 m.



Total antenna elevation 3-15 m (above water level)

Minimum/maximum distance between radar and water surface Minimum 3 m, maximum 20 m. Unobstructed view towards river > ±45º

Dimension Antenna size: ~1x1 m, transceiver/processing unit: ~0,6 m x 0,5 m x 0.4 m

Transmit power Peak 1 W, Average 0.5 W

Range resolution 5 m at 30 MHz bandwidth, 15 m at 10 MHz bandwidth

Azimuthal resolution Not specified

Power supply 120VAC or 220VAC, 50-60 Hz, ~ 100W required

Accuracy velocity measurement ~5% of maximum velocity bin

Resolution velocity measurement 2.5 cm/s

Accuracy water level measurement Not applicable


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E Technical specifications of nautical X band radar coupled to software

Geometrical characteristics Placement of a nautical X band radar is quite flexible, which can be either on a ship or on land. The antenna of a nautical X band radar should be placed at a minimum height of 15 m above water level. A minimum antenna length of 2.5 m is recommended to allow current velocity determination. Pulse- and data characteristics A nautical X band radar is a pulse radar and transmits at a frequency range of 8-12 GHz. The phase of the transmitted signal is coherent within the pulse, but incoherent from pulse to pulse. WAMOS and SeaDarQ describe recommended hardware settings for X band radar in order to obtain data of optimal quality. For proper system performance, a vertically polarized signal is required with a pulse length of 50 ns, 250 ns or 1 s. A 50 ns pulse provides a range resolution of 7.5 m. The current velocity is obtained from Fourier analysis of radar time series (see Appendix A8 for further explanation). The antenna rotation speed should be set to 48 RPM. The accuracies of current velocities and directions prescribed by SeaDarQ are higher than those defined by WAMOS. The accuracy of surface current velocity and current direction determined by SeaDarQ are +/- 0.1 m/s and 5 to 10 , respectively (SeaDarQ brochure). Accuracy of current speed and current directions determined with WAMOS, respectively are +/- 0.2 m/s and +/- 2 . The recommended peak power of the radar pulse is 25 kW or more. The average power is approximately 1.2 W. (WAMOS brochure, 2011). As the technical specifications of SeaDarQ and WAMOS are reasonably comparable, only the technical specifications of nautical X band radar coupled to SeaDarQ software are included in the following table.



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Technical specifications SeaDarQ software coupled to nautical X band radar

Manufacturer Nortek

Representative in the Netherlands Nortek

Type SeaDarQ software

Frequency band(s) 8-12 GHz

Bandwidth 1, 4 or 20 MHz

Frequency modulation Not applicable


Phase coherency from pulse to pulse No

Signal length 50 ns, 250 ns or 1 s


Transmitter orientation Not applicable. Recommended rotation speed 48 RPM


Type of configuration Single unit



Total antenna elevation Minimum 15 m

Antenna length Minimum of 2.4 m

Minimum/maximum distance between Radar and water level Minimum 15 m height

Dimension Antenna length 2.5 m or longer

Transmit power Transmitted: 25 kW or more (peak power), 1.2 W (average power)

Range resolution 3.75 m at 50 ns

Azimuthal resolution Not specified

Power supply Not specified

Accuracy velocity measurement +/- 10 cm/s

Resolution velocity measurement 10 cm/s

Accuracy water level measurement (if measured) Not applicable

Depth of velocity measurement below water surface

Measurement duration 11/2 minute

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F Technical specifications of K band radars: Flo-Dar, Sommer and Mutronics

Geometrical characteristics The three K band radar systems considered here - Flo-Dar, Sommer and Mutronics- are recommended to be placed in an upstream direction on a bridge or placed along a cable spanned over the river. The systems are not limited by a minimum water depth. The three systems all have a compact size, with the following dimensions:

Flo-Dar system, approximately 0.40 m x 0.16 m x 0.42 m; Sommer (RQ-30), approximately 0.33 m x 0.22 m x 0.13 m; Mutronics (MU2720), approximately 0.25 m x 0.25 m x 0.05 m.

Pulse- and data characteristics General The Flo-Dar, Sommer and Mutronics radars operate in the K band at 24 GHz, all transmitting a CW signal. The phase of the transmitted signal is coherent within the pulse, but incoherent from pulse to pulse. The radar transmits a signal at a defined angle at a spot of the water surface, which is reflected by disturbances on the water surface. The frequency content of the reflected signal is Doppler shifted by an amount directly proportional to the speed of the moving surface. The current velocity is found from Bragg scattering of centimeter-length surface waves, such that two Bragg lines are produced in the Doppler spectrum of the backscattered signal. The systems only measure the sign of flow direction, i.e. positive or negative. Flo-Dar, Sommer and Mutronics show comparable values for accuracies of current velocities, but it is not clear from the information provided by the manufacturers whether the accuracy percentages are expressed with respect to the reading or to the maximum measuring range. Flo-Dar The accuracy of the current velocity measurement with Flo-Dar is +/- 0.5%, with a measurement range of 0.2 to +/- 6 m/s. The accuracy of the calculated average current velocity, after correction, is typically between 2% to 5% (Flo-Dar brochure). The water level is determined by a separate 26 GHz pulse that is vertically transmitted and reflected on the water level. The water level is derived from the travel time elapsed by the pulse. The accuracy of the water level measurement is 1% +/- 2.5 cm. The maximum acceptable difference in water level for a certain measurement location is ~5 m. The peak power of the system is < 10 mW. Sommer The accuracy of the current velocity value measured with Sommer RQ-30 and RG-30 is +/- 1% with a measuring range of 0.15 to 15 m/s. The effect of fog on current velocity values is approximately 0.05-0.06 m/s (personal communication with Sommer, November 2011).The transmitted power for the radar signal used for flow velocity measurement is 400 mW (constant). The power consumption of the system during active measurements is 2.2 W. Power consumption reduces to 0.012 W in between measurements. The beam angle of the



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system is 12 . For example, this yields a measurement surface on the water ranging from 1.2 to 2.4 m when increasing height from 4 m to 8 m. Mutronics The accuracy of current velocity measured with Mutronics radar is +/-0.5%. The available information of Mutronics is rather limited, and additional information regarding pulse- and data characteristics should be requested at the manufacturer if desired.

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Technical specifications Flo-Dar Manufacturer Marsh-McBirney (VS)

Representative in the Netherlands Ten Kate-Kool

Type Flo-Dar 4000 (4000-SR en 4000-LR)

Frequency band(s) 24.075-24.175 GHz

Bandwidth Not applicable

Frequency modulation CW



Signal length 8 s


Transmitter orientation Directed upstream





Total antenna elevation 0.01-6 m (Model 4000-LR)

Dimension 17.5 cm x 42.3 cm x 29.7 cm, 4.8 kg

Transmit power Transmitted: 128 dbuV (average) at 3 m distance, <10mW

Range resolution Not applicable

Azimuthal resolution Not applicable

Power supply Supply voltage 100/230 VAC, 12VDC, 24 VDC, max. 30W

Accuracy velocity measurement +/-0.5%,+/-0.03m/s


Accuracy water level measurement (if measured) 1%

Minimum/maximum distance between Radar and water level 0.01-1.5 m (Model 4000-SR), extendable to 0.01-6 m (Model 4000-LR)

Measurement duration 1 minute



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Technical specifications Sommer Manufacturer Sommer (Austria)

Representative in the Netherlands RQ-30/RG-30

Type 24 GHz

Frequency band(s) Not specified





Signal length Burst of pulses over a long period of 5 s to 240 s. Individual pulse length not known.

Transmitter orientation Directed upstream



Total antenna elevation 0.5-35 m

Minimum/maximum distance between radar and water level 0.5-35 m

Dimension 33 cm x 22 cm x 13.4 cm

Transmit power Transmitted: 400 mW (constant during the measurement time).



Power supply Supply voltage: 220/230 VAC or autonomous (solar panel + battery)

Accuracy velocity measurement +/-0.5%

Resolution velocity measurement 0.001 m/s

Accuracy water level measurement (if measured) +/- 2 mm, with at least +/-0.02m/s

Measurement duration ~ 4 minutes

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Technical specifications Mutronics Manufacturer Mutronics (South-Korea)

Representative in the Netherlands No

Type 24 GHz

Frequency band(s) Not specified





Signal length Not specified

Transmitter orientation Preferred directed upstream



Total antenna elevation Not specified

Minimum/maximum distance between radar and water level Minimum distance not specified, maximum distance 100 m

Dimension 24.8 cm x 24.6 cm x .5.4 cm

Transmit power 79 mW



Power supply 110-240 VAC 50-60 Hz

Accuracy velocity measurement ~+/-3% up to +/-10% (dependent on current velocity)

Resolution velocity measurement Not specified

Accuracy water level measurement (if measured) Not specified

Measurement duration Not specified

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