GRADE. Nienke Kramer Hessel Winsemius Otto de Keizer Deltares, 2010

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1 GRADE 2009

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3 GRADE 2009 Nienke Kramer Hessel Winsemius Otto de Keizer Deltares, 2010

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5 Title GRADE Client Waterdienst Project Reference VEB-0002 Pages 84 Keywords Generator of Rainfall And Discharge Extremes, Extreme value analysis, hydrological modelling Summary The project GRADE is carried out for RWS Waterdienst in Lelystad. GRADE (Generator of Rainfall and Discharge Extremes) is a new methodology to provide a better physical basis for the estimation of the design discharge of the main Dutch rivers compared to the present method based on frequency analysis of extreme discharge values. GRADE can also be used for the determination of the shape of the design hydrograph, important for the duration of the stress on the river dikes, for the assessment of the impact of scenarios, such as climate change or major changes in the river geometry, as well as for the impact of measures on the design discharge hydrograph on the Rhine and Meuse river in the Netherlands This report describes investigations and developments to the GRADE instrument for the Meuse and Rhine rivers performed in Rhine The new HBV calibration from SMHI, which has been commissioned by BfG in cooperation with Rijkswaterstaat Waterdienst, has been compared to the version currently used in GRADE-Rhine. The comparison shows that the new calibration results in a large over-estimation of peak flows, which does not make it suitable for application in GRADE. This can be explained by the fact that this calibration has been focused in particular on low flows, whereas the previous calibration was focused on peak flows. Meuse The development of GRADE-Meuse is further advanced than GRADE-Rhine and sufficient confidence is obtained now in the GRADE-Meuse instrument for application in the project Wettelijk Toets instrumentarium (WTI) in pre-operational mode (Dutch: schaduwdraaien ) for the determination of the Hydraulic Boundary conditions (HBC). This is evident from the results of various studies carried out in 2009 and which are summarized in this report. These include the study of the newly derived parameter sets with the GLUE methodology that result in a better performance given all criteria. Furthermore, the potential for future improvements in the hydrological component of the instrument is demonstrated. Finally, the effect of new, improved model structures (with respect to HBV) on the trade-off between several hydrograph behaviours (volume, hydrograph shape, and wave irregularity) has been investigated. An investigation of the wave patterns produced with the new parameter set of HBV for the Meuse shows that with this new set much more realistic patterns can be simulated than with the original (Van Deursen) parameter set. This is a major improvement over the original results that were available before in the year 2008 and also opens the way to start using GRADE directly for the derivation of the wave patterns belonging to the design discharges instead of relying on an upscaling of historical wave patterns as has been the case until now. The main conclusion on GRADE-Meuse is that the significant improvements of GRADE- Meuse, since introduction of the GLUE parameter sets, give enough confidence to include GRADE-Meuse pre-operationally in WTI.

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7 Contents 1 Introduction Background GRADE 2007 & 2008 project GRADE 2009 project Report outline 6 2 GRADE for the Rhine basin Introduction Hydrological modelling New HBV-calibration (2009) Hydraulic modelling 16 3 Hindcast with the HBV model for the Meuse river Parameter sets Comparison between HBV old and new for Monsin Volume Peaks Wave pattern Performance of the HBV parameter sets at Borgharen with and without SOBEK Peaks Wave pattern Performance of the parameter sets at Maaseik with SOBEK Performance of the parameter sets at Lith Conclusions 30 4 Comparison hourly and daily timesteps Input Analysis Conclusion 37 5 Influence of weirs upstream of Borgharen on the discharge Introduction Weirs in the river Meuse SOBEK Effect of the weirs in the SOBEK model Adaptations Difference in maximum waterlevel and discharge Timing of the peaks Borgharen Timing of the peaks locations up- and downstream of Borgharen Conclusions 51 6 Investigation of hydrological behaviour of GRADE-Meuse instrument Introduction of criterion for hydrograph irregularity Reproduction of autocorrelation by HBV at Borgharen Model experiments Discussion Outlook 60 GRADE i

8 6.6 Recommendations 61 7 Conclusions GRADE-Rhine GRADE-Meuse 63 8 Recommendations GRADE in WTI context GRADE-Rhine GRADE-Meuse Assessment wave pattern 70 9 References 71 Appendices A Appendix GRADE model A-1 A.1 FEWS system A-1 A.2 SOBEK river Meuse model A-3 A.2.1 Differences between FEWS-GRADE and FEWS operational system A-4 A.2.2 New developments A-5 A.3 HBV model A-5 B Appendix Hourly versus daily HBV model results B-1 B.1 Chaufontaine B-1 B.2 Chooz B-2 B.3 Gendron B-3 B.4 Martinrive B-5 B.5 Membre pont B-6 B.6 Salzinne B-7 B.7 Tabreux B-8 B.8 Treignes B-9 ii GRADE

9 1 Introduction 1.1 Background In the Netherlands, the flood protection situation must be evaluated every 5 years, which includes the evaluation of the Hydraulic Boundary Conditions (HBC) along the Meuse and Rhine branches. For the determination of the HBC, use is made of the 1250-year design discharge at Lobith and Borgharen. The next determination of the HBC in 2011 is carried out in the project Wettelijk Toets Instrumentarium (WTI). The current estimation of the 1250-year design discharges from statistical analyses of the measured peak discharges faces various problems. The estimation of the 1250-year discharge event from statistical information in a discharge record of about 100 years involves a strong extrapolation, and is therefore hampered by a large uncertainty (Figure 1.1). Q Q 100 years Extrapolation Q 1250 years T 1250 Figure 1.1 Present method for the determination of design discharges In 1996 Rijkswaterstaat RIZA, KNMI and WL Delft Hydraulics started to work together on a new methodology to provide a better physical basis for the estimation of the design discharge of the main Dutch rivers. The new methodology is a combination of various components (Figure 1.2). The first component of this new methodology is a stochastic multivariate weather generator, which generates long synthetic simultaneous records of daily rainfall (P) and temperature (T) records (up to 20,000 years). Evaporation (E) series are derived from the temperature series. The second component consists of hydrological and hydraulic models, which transform the generated rainfall and temperature records into discharge series. Altogether, this new methodology is indicated as GRADE: Generator of Rainfall And Discharge Extremes. GRADE 1 of 84

10 Q P,T,E 66 years rainfall generator P,T,E years HBV Q SOBEK years Q years T 1250 Figure 1.2 Overview of the GRADE instrument Advantages of the GRADE methodology are that: long discharge records can be simulated, meteorological conditions and basin characteristics can be taken into account, the shape and duration of the flood can be analysed, the method can iteratively be improved and uncertainties can be reduced on the basis of new knowledge, the method can potentially assess the effects of future development like climate change and upstream interventions such as retention basins and dike relocations. As mentioned in this paragraph for the determination of the HBC s there is a potential role for GRADE on the following three parts: 1. determination of the design discharge line; 2. determination of shape of the hydrograph; and 3. determination of the hydrograph of the waterlevels. The GRADE instrument is now in the experimental phase. The ambition is to use the instrument for the river Meuse semi-operationally for the determination of the HBC This means that GRADE will be used parallel to the original method and the GRADE results will not be used yet for the final determination of the HBC s. When the model gives sufficient and reliable results, the model is a serious candidate to be used in the operational phase for the period after The criteria that will be applied to decide whether the instrument is reliable will need to be defined as part of the pre-operational application. This will need to be done in close cooperation with the Expertise Netwerk Waterkering (ENW), which carries out the quality control of the WTI programme. For the determination of the proposed improvements to the WTI instruments the following basic principles are used: acceptation by managers of the dikes and policy makers; reproducibility; reliability; consistence; user friendliness (applicable, no too laborious, good instructions and helpdesk); production of the results on time; continuity in the HBC s; uniformity of the models. 2 of 84 GRADE

11 For the GRADE model it is important to guaranty the continuity of the HBC. In the second place, it is important to have a good overview of the reliability of the model in order to approve the system by the managers of the dikes and policy makers. 1.2 GRADE 2007 & 2008 project The current GRADE 2009 project is the continuation of the former GRADE project, which was carried out in the period and completed was with a workshop in December The GRADE 2007 and 2008 project consisted of three parts: 1. configuration of GRADE-Rhine and GRADE-Meuse in Delft-FEWS; 2. analysis of performance of the GRADE-Meuse instrument by: a. analysis of the shape and duration of the extreme flood hydrograph; b. qualification of the uncertainties in the GRADE instrument. 3. improvement of the GRADE-Meuse model by selection of new parameter sets for the HBV model using a GLUE analysis. The main findings of the analysis of the performance of the GRADE-Meuse model were: 1. The original (Van Deursen) parameter set of the HBV model underestimates the peak discharges for the river Meuse. 2. The volume of the wave pattern is significantly larger than the measured wave pattern 3. The observed wave pattern is much more irregular than the form of the simulated peaks. In Figure 1.2 the observed flood wave patterns are shown. The pattern is irregular and most waves have multiple peaks. Figure 1.3 shows the simulated flood wave patterns using the GRADE instrument. All flood waves are smooth and have one single peak. Figure 1.3 Measurements of historical peak discharges of the river Meuse at Borgharen (Roelevink, 2008) GRADE 3 of 84

12 Figure 1.4 Generated wave patterns using the GRADE instrument in 2008 with the Van Deursen parameterset. (Roelevink, 2008, HKV) 1 Possible explanations for the difference in volume were identified: 1. The parameter set (Van Deursen, 2004) of the hydrological model is not applicable for peak flows; the simulated peak discharges are too low and too smooth. Consequently the selection method of Roelevink (2008) causes too large volume of the wave, 2. It is difficult to simulate the discharge at the location Borgharen. This is caused by the presence of the weir upstream of the gauging station and many extractions and inflow points in the surrounding of this location (Figure 1.5) (Weir operation and abstractions are not taken into account in the hydrological model). Possible explanations for the smooth pattern of the simulated wave at Borgharen were also identified: 1. The geological situation at the location Borgharen (see point 2 in upper section) 2. The daily time step used in the hydrological model. It is known that in tributaries such as the Ourthe and other small tributaries, the flow is generated by processes that occur at a smaller time scale than a day. This may compromise the ability of the hydrological models to capture the real flow processes during extremes, 3. Effects of the weirs at the Belgian part of the river Meuse, 4. Imperfection of the rainfall generator, mainly the spatial patterns of the discharge events. 1 For this figure, only peak waves having a discharge of (m 3 /s) have been selected. The discharges are based on 10 synthetic meteorological series of each 3000 years. For the translation of rainfall to discharge the HBV model, including the Van Deursen parameter set, were used. 4 of 84 GRADE

13 Grensmaas Measurement point Borgharen Julianakanaal sluis Zuid Willemsvaart stuw Borgharen Figure 1.5: location Borgharen Maastricht 1.3 GRADE 2009 project In the GRADE project, the focus has been on the Meuse basin. In 2009 the research on GRADE for the Rhine has been resumed. The rainfall-runoff part of the modelling chain has been analysed, in particular with regard to the performance of the new HBV calibration for the Rhine published early 2009 (Berglöv et al., 2009). A general overview of the modelling chain for the Rhine is also given. In GRADE 2009 fundamental research for the Meuse has primarily concentrated on the issues brought forward during the 2008 GRADE workshop and has therefore focussed on the evaluation of the performance of the status quo of GRADE compared to the presented GRADE-Meuse version in 2008 (using the Van Deursen parameter set). A second topic was the testing of certain sensitivities within the hydraulic part of the model such as the impact of weirs and their operation on flood hydrographs and the use of the SOBEK hydraulic model in general. Furthermore, one of the advantages of GRADE is that (unlike statistics based extreme value distributions) it can be further developed by incorporating the knowledge of the hydrological and hydraulic characteristics of extreme events and reduce the uncertainty in the estimation of design discharges. Therefore, investigations into future developments of the hydrology within GRADE have been undertaken in 2009, which have resulted in a number of recommendations for future research and a framework, which can be used to test possible improvements. The results of these investigations are summarized in this Report. GRADE 5 of 84

14 1.4 Report outline In detail, investigations have been performed on: 1. GRADE for the Rhine basin, which includes: a. performance of the new HBV calibration for the Rhine published early b. general overview of the modelling chain for the Rhine. This part is described in Chapter GRADE for the Meuse basin, which includes: a) Hindcast using the HBV model. This hindcast describes the improvements in performance of the HBV model by introduction of the GLUE parameter set. A thorough comparison has been performed between the Van Deursen and the GLUE parameter sets, based on criteria that are deemed important for operational use of the GRADE instrument (i.e. flood peaks, flood volumes and flood wave shape). In this hindcast also the impact of the choice of the location and the use of Sobek is analysed. This assessment is presented in Chapter 3. b) Analysis to investigate the sensitivity of the timestep of the HBV model. In this analysis the difference between the original simulated daily and simulated hourly flood wave patterns (using the same parameter set, calibrated on daily basis) is investigated. The findings are presented in Chapter 4. c) Analysis of the sensitivity of the discharge to weir operations (Chapter 5). 3. Investigation of hydrological behaviour of the HBV model and possible future improvements of the hydrological model by enhanced process understanding. a. Introduction of a new criterion for assessing the model s capability to reproduce flood wave irregularity b. Assessment of possible irregularities in the performance of the HBV model. c. Testing of process-based improvements of the hydrological model, based on the aforementioned criteria. This part is described in Chapter 6. The conclusions and recommendations formulated on basis of the results form this study are given in respectively Chapter 7 en 8. In these two Chapters the results of the external study by HKV (Barneveld and Van den Berg, 2010) towards the impact of the new HBV hydrological model calibration on the wave pattern produced by GRADE have been incorporated. For details on this study, reference is made to the original report. 6 of 84 GRADE

15 2 GRADE for the Rhine basin Both the international Rhine and Meuse river basins are of major importance for the Netherlands. For the Rhine the design discharge at Lobith, near the German border, is taken as a reference for the Dutch hydraulic boundary conditions (e.g. Diermanse, 2004). The development of GRADE has been initiated both for the Rhine and Meuse basins. Considering the much smaller size of the Meuse basin, GRADE-Meuse has been put on a faster track during last years, which has resulted in a new calibration parameter set for the HBV model and some improvements on the hydrological modelling side. Although GRADE- Rhine is being constructed based on existing modelling tools for the Rhine basin, it has not been documented neither validated yet as a whole. The objective of the GRADE 2009 Rhine study is to analyse the new calibration of the HBV model for the Rhine basin. Besides, as current knowledge on the hydrological toolbox used in GRADE-Rhine is rather fragmented, also an overview on the status of the whole hydrological modelling chain is provided 2.1 Introduction GRADE, Generator of Rainfall And Discharge Extremes, has been developed to estimate low probability (high) flows. It is a combination of a stochastic weather generator, which creates synthetic time series based on historical precipitation and temperature, and a hydrological / hydraulic model to facilitate the estimation of low probability discharges (Figure 2.1). Figure 2.1 Schema of GRADE GRADE is a collaborative initiative between KNMI, Deltares and Rijkswaterstaat. KNMI is has developed the Rainfall Generator and Deltares the hydrological modelling phase. Here we will focus on the hydrological modelling toolbox that is being developed for the Rhine basin. This hydrological modelling toolbox is implemented in FEWS, which is an operational system particular useful for the coupling of different types of models and data management. Current applications include FEWS-NL which is used in operational flood forecasting for the Netherlands, as well as applications for flood and drought forecasting in other countries of Europe and the rest of the world. Figure 2.2 presents the different modelling steps used in GRADE-Rhine for the estimation of low probability discharge extremes. The synthetic climate series, with a daily time step and in GRADE 7 of 84

16 general between and years long, are used as input for the hydrological model HBV that calculates a discharge series of the same length. The (relatively fast) Muskingum model is run to emulate the flow routing, the results being used to identify periods with maxima that require more precise flood routing. Then the selected flood waves are recalculated with the SYNHP routing module for the Rhine upstream from Maxau, and the hydrodynamic SOBEK model for the lower Rhine stretch starting off from Maxau. Subsequently statistical analyses and/or the calculation of low probability return flows (e.g. for a 1250 year return period) can be made for the location of Lobith. Figure 2.2 GRADE modelling steps (Rhine basin) The historical climate series for the Rhine that is used is the CHR-climate data set (Hydrological Commission of the Rhine). This data set contains areal precipitation and temperature of the 134 HBV subbasins. In the following subchapters the hydrological and the hydraulic modelling steps respectively will be described in more detail. Information on the configuration of FEWS-GRADE can be found in Patzke (2007). 2.2 Hydrological modelling The first step in the modelling chain within FEWS consists of the HBV-model. HBV is a conceptual rainfall runoff model that has been developed in the early 1970 s by SMHI, Sweden. The simple structure of the model makes it attractive for discharge calculations based on meteorological data at river basin level (see Figure 2.3). In 1996 an enhanced version of HBV has been published (Lindström et. al., 1997), which is currently used by Deltares and BfG (Bundesanstal für Gewässerkunde, Germany). 8 of 84 GRADE

17 Figure 2.3 Schematic presentation of the HBV-model. Different phases in the development of the HBV-Rhine model have taken place leading to the version that is currently used (Eberle et al., 2005). This year a new calibration by SMHI has become available, see Table 2.1. Table 2.1 HBV-Rhine versions I Daily models for major tributaries Mülders et al. [1999] II Hourly model for the Rhine basin between Maxau and Lobith (daily model between Basel and Maxau) Eberle et al. [2001] III Daily model for the entire Rhine basin upstream of Lobith Eberle et al. [2005] IV Hourly model for the Rhine basin Berglöv et al. [2009] The Rhine basin upstream from Lobith has been divided into 134 subbasins and some additional ones with surface area of zero that are only used for flow routing purposes. Each subbasin consists of an HBV model as shown in Figure 2.4 and the resulting flows are routed downstream between the sub basins. GRADE 9 of 84

18 Figure 2.4 Subbasins in the HBV Rhine model. Red dots mark the main gauging stations (Berglöv et al., 2009) 2.3 New HBV-calibration (2009) In several test runs of the forecasting systems it was found that the previous HBV model has, in certain ranges, significant shortcomings, with the consequence that predictions of mean and low-flow conditions require manual corrections (Berglöv et al., 2009). Therefore, in 2009 a new HBV-calibration was published by SMHI that was commissioned by the German BfG. As a basis for this calibration Weerts et al. (2008) developed a new interpolation method of precipitation and temperature. Although the objective of the calibration was to improve model performance for mean and low-flow predictions, it was agreed that this should not affect the performance for simulation of peak discharges 2. 2 Personal communication with Erik Sprokkereef (RWS-Waterdienst) and Albrecht Weerts (Deltares) 10 of 84 GRADE

19 As it was hard to match flood peaks in summer and winter with the same parameter sets, a contributed area approach was applied. Normally, the recession curve of an observed discharge wave is less steep when the basin is wet (in winter) than when it is dry (in summer). This is because in dry circumstances a smaller part of the basin actively contributes to discharge generation. In order to include this effect in the modelling, the contributed area approach was applied in which the areal wetness in the soil routine (SM/fc) is used, letting it represent the contributing area. The percolation parameter PERC (between first and second HBV reservoir) is multiplied with this areal wetness, and the outflow Q 0 is divided by this factor (see Figure 2.5). Figure 2.5 Principal behaviour of the response routine when the contributing area approach is used (Berglöv et al., 2009) To evaluate the new calibration for its possible application in GRADE-Rhine, a comparison was made between the two HBV-versions. This has been done using the historical CHR data set. As the new calibration is based on hourly values and the current calibration on daily values, different approaches have been used to make them comparable; the first one being to transfer the new hourly calibration to a daily one using the same approach as in Eberle et al. (2005). In the following description the currently used HBV calibration is named HBV-2005 and the new one HBV Figure 2.6 shows a comparison between observed and modelled discharges at Lobith for the flood peak of HBV-2005 slightly overestimates the peak discharge at Lobith, but the HBV-2009 overestimates this value very strongly. GRADE 11 of 84

20 Q (m³/s) Q_m Q_HBV Q_HBV_new mrt 07 mrt 17 mrt 27 apr 06 apr 16 Date Figure 2.6 Flood wave at Lobith for March 1988, comparing both HBV-calibrations with the observed discharge values (new HBV calibration has been adapted to daily values). Figure 2.7 Flood wave 1995 at Lobith, calculated with both HBV models and compared to measured values (for both calibrations hourly models have been used) 12 of 84 GRADE

21 In order to make sure that this difference is not caused by the conversion from the hourly to the daily model of the new calibration set, also the hourly version of the current HBV-model has been compared to the new calibration (see Figure 2.7). Finally Figure 2.8 shows the 2003 flood wave as taken from the extended calibration report of SMHI. Also here the overestimation of the flood waves can easily be confirmed visually. Figure 2.8 Flood wave 2003 at Lobith according to Berglöv et al. (2009). Note that the discharge at Maxau has been excluded. Table 2.2 presents the average discharge over the period as calculated by each model calibration at different location in the Rhine basin. For Lobith also the average observed flow has been included. Here also an overestimation of the discharge is shown for the new calibration, in particular for the Neckar (Rockenau) and Main (Raunheim). Table 2.2 Average discharge in m 3 /s of period and systematic relative difference between calibrations Lobith Cochem Rockenau Raunheim Maxau HBV HBV Observed 2299 Relative difference between HBVcalibrations 17% 17% 33% 50% 5% Now the question is what could cause this very significant overestimation of peak discharges while average and low discharges are calculated sufficiently well. Different reasons can be thought of, each of which will be analysed in the following paragraphs: 1. Calibration and validation periods 2. Calibration data and interpolation technique applied GRADE 13 of 84

22 3. Performance criteria used during calibration 4. Flow routing Calibration and validation periods The calibration periods used in the current HBV-2005 version and for different parts of the Rhine basin are presented in Table 2.3. Table 2.3 Basics for the calibration of different model parts of HBV-2005 (Eberle et. al., 2005) For HBV-2009, the period from November 2000 until October 2007 has been used for calibration and the period from November 1996 until October 2000 for validation (Berglöv et al., 2009). For some sub-catchments with incomplete time series of recorded discharge, the periods had to be shortened. Note that HBV-2009 has been calibrated on hourly values. Comparing the calibration periods of the HBV-2009 with those of HBV-2005 it becomes evident that these periods are different and do not overlap. During the (shorter) calibration period of HBV-2009 only one major flood wave was included in the calibration period (in 2003) and even this one was much smaller than the 1993 and 1995 peak discharges. This makes it particularly difficult to produce a new parameter set that reproduces faithfully the (extreme) flood waves that will need to be simulated with the GRADE-Rhine instrument. Discharge data and interpolation technique used for calibration We will focus here on the precipitation data, as for the lower part of the Rhine basin differences in peak flows are mainly defined by this input. As explained by Eberle et al. (2005), for HBV-2005, precipitation data for the German part of the Rhine basin are calculated out of REGNIE grid data provided by the German Meteorological Service (DWD). From these data, daily areal precipitation values are calculated by computing the arithmetic mean of the grid values within a subbasin. For the River Moselle basin and the Swiss part of the basin, a different approach was chosen. 14 of 84 GRADE

23 The calibration data used for HBV-2009 are based on a new interpolation technique developed by Weerts et. al. (2008). As for operational purposes, a limited amount of operational weather stations is available, using the areal precipitation results in unsatisfactory results with HBV The new interpolation technique is based on the intention to approach the REGNIE data as much as possible within the operational systems FEWS-NL and DE. One can conclude that although different calibration data have been used, the very large differences between both calibrations during peak flows cannot be explained by differences in the interpolation as the new interpolation intends to approach the REGNIE data as closely as possible. Performance criteria The choice of criteria for defining the quality of simulations depends on the questions the model should help answering. The criteria can be optimised applying predefined objective functions. For HBV-2005 a calibration of all parts of the HBV model was done to obtain a good overall simulation of the discharge dynamics with some emphasis on the simulation of flood events (Eberle et. al., 2005). The simulation of low flows was not of special interest at the time of calibration. In addition to comparing hydrographs of computed and observed runoff visually, three quality criteria that are implemented in the modelling software were used during calibration: the explained variance according to Nash-Sutcliffe the relative accumulated difference between observed and computed discharge the relative peak error Results for gauging stations at the main river are presented in Table 2.4: Table 2.4 Simulation results from HBV-2005 (Eberle et. al., 2005) For HBV-2009 the calibration criterion was (Berglöv et al., 2009): crit = 0.5 R R 2 log Relaccdif Where: R 2 R 2 log Relaccdif efficiency criterion according to Nash-Sutcliffe as R 2, but using the logarithmic discharge values (gives more weight to low flows) the accumulated difference between simulated and observed discharge. GRADE 15 of 84

24 Also, but separately, the peak err criterion was evaluated; it is based on one value per full year (i.e. 6 values for the calibration period and 4 for the verification period). The results for those criteria are shown in Table 2.5. Table 2.5 Results for the calibration and validation for HBV-2009 (Berglöv et al., 2009) When we only have a look at the peak error at each location, it is easy to see that these are much higher in the new HBV calibration. Note that also the other statistics for the main river are better for HBV-2005, although the R 2 log, an important (low flow) criterion in HBV-2009, cannot be compared. Flow routing In HBV-2005 flow routing has been adjusted as simulated flows during peak discharges were much too high. The option of simulating several branches has been used to model routing during flood. As soon as a certain threshold discharge is exceeded, water starts to run through another branch, usually flowing slower and a certain percentage even getting lost (branches flowing to nowhere) (Eberle et. al., 2005). In a memo that came with the HBV-2009 calibration the following statement is found: In the original HBV Rhine set-up the branch option was used to remove and delay water in some of the sub-basins along the Rhine. The reason was assumed to be a decrease in observed discharge values from upstream to downstream stations at high flows. This option was not used in the current set-up as the results seemed acceptable also without it. Apparently, flow routing has a critical influence on the discharge peaks. Normally SYNHP and SOBEK are used for the flow routing, skipping the routing within HBV. However, when only HBV is used, as is the case here, its impact on peak discharges is very relevant. 2.4 Hydraulic modelling As SOBEK has a large calculation time for long time series, the periods with high discharges are selected from the discharge series from HBV. As explained before this is done using a certain threshold on the HBV discharges corrected with the Muskingum flow routing utility. In this way for each tributary a time series is created for each flood wave, which is used as input for SYNHP and SOBEK. 16 of 84 GRADE

25 For the area upstream of Maxau (see Figure 4) a SOBEK schematization does not exist yet. For this part of the basin the SYNHP model, administered by the German state Baden Würtenberg, is applied. This model describes the routing of the flood wave through a series of linear reservoirs. A number of configurations exist, being the situation of this reach before (1997) and after initiation of the major river training works in the last century. In GRADE- Rhine the model is run for the situation of 1997 (Patzke, 2007). The area downstream from Maxau is modelled with SOBEK. Also different versions of the SOBEK model do exist. Details regarding the different versions have not been analysed yet. Using the HBV-output directly as input for the SYNHP and SOBEK models resulted in a significant over-estimation of the flood peaks. To correct for this, correction factors have been introduced (Buiteveld, 2004). Globally, discharge values have been diminished by 5% and the contribution of in-between-catchments has been set to zero. Two possible explanations for the use of these correction factors include (1) not taking into account the effect of groundwater and (2) backwater effects at the tributaries by the models. The last explanation might be important as SOBEK simulates only the main river stretch of the Rhine and does not include the tributaries. Note that in the current development version of FEWS-GRADE, the factor for Maxau (earlier set at 0.9) has been left out for an unknown reason. It is important to stress that the corrections factors are only valid during periods of high discharge, so the SOBEK-model within FEWS-GRADE can only be used for the calculation of flood waves. Considering the large influence of these factors on the final results of GRADE we suggest to re-evaluate their values regularly due to possible effects of differences in HBV, SYNHP or SOBEK versions. GRADE 17 of 84

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27 3 Hindcast with the HBV model for the Meuse river In this chapter, a hindcast is made for the period 1968 to 1998 using the HBV model of the Meuse river. This hindcast describes the improvements in performance of the HBV model by introduction of the GLUE parameterset as defined in the GRADE 2008 project. In this hindcast the performance of the different parameter sets are analysed for different locations: Monsin (paragraph 3.2) Borgharen (paragraph 3.3) Maaseik (paragraph 3.4) Lith (paragraph 3.5) For the simulations at Monsin and Borgharen only the HBV model is used. For Borgharen, Maaseik and Lith use is made of the Sobek model. 3.1 Parameter sets During GRADE , Deltares has worked on the optimalisation of the parameter sets in the HBV model. A GLUE method was used and new (for the lateral inflows) and longer discharge series are used for the optimalisation of the parameter sets. The results are reported in Kramer et al (2008) and Kramer and Schroevers (2008). In this chapter the HBV Meuse model with the Van Deursen parameter set (2004) is indicated as HBV old. The parameter sets as selected in Kramer en Schroevers (2008) is indicated as HBV new. The GLUE analysis produces a large number of possible parameter sets. Out of these sets five final sets were selected, which are indicated as HBV5%, HBV25%, HBV50%, HBV75%, HBV95%. For more details reference is made to Kramer and Schroevers (2008). 3.2 Comparison between HBV old and new for Monsin The discharges simulated with the HBV model are compared with the measurements at the station Monsin instead of Borgharen, because this location is not influenced by upstream weir operations or abstractions. To define the discharge at Borgharen the simulated HBV results for Monsin are reduced with the discharge of the lateral inflow of the Jeker. The (synthetic) observed series of Monsin is calculated as the observations of Borgharen minus the extractions of the branches between Liège and Borgharen (Albertkanaal / Zuid-Willemsvaart / Julianakanaal) Volume In Figure 3.1 the discharge regimes for the observations and the simulations at Monsin are given. All models slightly overestimate the discharges in spring and underestimate the discharges in autumn. A possible explanation is that the under- and over estimation is caused by the crude monthly potential evaporation numbers used. It could be that in spring, the potential evapotranspiration is estimated too low, which leads to too wet soils and too high discharges in the model. GRADE 19 of 84

28 This absolute error is specified in more detail in Figure 3.2. The highest errors are found for the old model. The relative volume error is calculated by the following formula: n AVE ( Q Q ) i 1 m o where Q i n o m discharge (m 3 /s) the time step [d] the total number of time steps [d] observed modelled 550 Discharge regime discharge (m3/s) Measured HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% jan feb mar apr may jun jul aug sep oct nov dec Figure 3.1 Discharge regime (monthly) 20 of 84 GRADE

29 60.0 Monsin old volume error (m3/s) jan feb mar apr may jun jul aug sep oct nov dec 5% 25% 50% 75% 95% Figure 3.2 Absolute volume error per month, the volume error is determined by comparing the simulated discharges at the Meuse-Monsin station of the period with the measurements Peaks In Table 3.1 the averaged yearly maxima for the years 1968 to 1998 are given. In this table two methods are use to calculate the yearly maxima. In the first column, the yearly simulated maxima are given at the day that the yearly maxima were observed. In the second column, the yearly maximum is the discharge of the real yearly maxima (timing of the peaks is not taken into account). For both comparisons, it can be concluded that the new parameter sets perform better in terms of peak simulations than the old HBV parameter set. Table 3.1 Averaged yearly maxima for the period Yearly day-maxima Yearly maxima-day at t= t peak measured (m 3 deviation /s) (m 3 deviation /s) (%) (%) Measurements HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% In Figure 3.3 the yearly maxima are plotted for every year. The figure shows that only for the highest peaks 1993 and 1995 the simulated discharges are higher than the measured discharges. For less extreme situations, the measured discharge (square) is generally situated in between the peaks simulated by the new parameter sets. Furthermore, it can clearly be seen that the old HBV model underestimates the peak flows. Note that the variable performance of the models is also caused by the limited amount of rainfall data available for the simulations. GRADE 21 of 84

30 Monsin discharge (m3/s) old 5% 25% 50% 75% 95% Measured (year) Figure 3.3 Yearly maximum discharge for the river Meuse at Monsin. In Figure 3.4, Figure 3.5 and Figure 3.6 the measured and simulated discharges are given for three extreme situations. In both flood situations, the simulated discharges of the new HBV models overestimate the peak discharges. Especially for the simulation with the new HBV model, the peaks of the simulated discharges are earlier (mostly 1 day) than the measured peaks. Based on a visual comparison the new parameters already give more irregularly shaped hydrographs. However, it cannot be concluded that the new HBV models simulate the extreme flood periods (1993 and 1995) and the extreme low flows (1976) better than the old HBV simulations. December 1993 m3/s Measured HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% /12/93 20/12/93 25/12/93 30/12/93 04/01/94 09/01/94 Figure 3.4 The highest measured peak discharge in de river Meuse at Monsin occurred in December of 84 GRADE

31 Measured HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% January m3/s /01/95 20/01/95 25/01/95 30/01/95 04/02/95 09/02/95 14/02/95 Figure The second highest measured peak discharge in the river Meuse at Monsin occurred in December Low Flow 1976 m3/s Measured HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% /03/76 20/03/76 04/04/76 19/04/76 04/05/76 19/05/76 03/06/76 18/06/76 03/07/76 18/07/76 02/08/76 17/08/76 01/09/76 16/09/76 01/10/76 16/10/76 31/10/76 Figure 3.6 An extreme low flow period in the river Meuse was in the summer of In the figure the measured and simulated discharges for the river Meuse at Monsin are plotted. GRADE 23 of 84

32 3.2.3 Wave pattern For the determination of the volume of the wave pattern, the 10-day volume of peak events has been calculated. The 10-days volume is important because the longer flood waves that produce several days of flood conditions along the dikes in the lower Meuse river reach in the Netherlands, put a severe stress on the dike systems. In this table, two methods are used to calculate the average of 10 contentious days around the yearly maxima over the period 1969 to 1998 (Yearly-maxima-10-days). In the first column, the simulated yearly-maxima-10-days are chosen at the same dates as observed days. In the second column the yearly-maximum- 10 days is chosen at 10 days around the date of the yearly maxima (timing of the peaks is not taken into account). When comparing the 10-daily volume the old HBV model performs much better than the new HBV models (Table 3.2). The new models produce a higher 10-days volume (4-12 %) than the measured 10-days volume. Table 3.2 Averaged of 10-days discharge along the peaks of the yearly maxima for the period Yearly-maxima 10-days at t= t peak measured (m 3 Deviation /s) (%) Yearly-maxima 10-days (m 3 /s) Deviation (%) Measurements* HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% *The comparison is made for the following years: , 1973, , 1982, 1984, 1986, 1987, 1990, , 1997, Performance of the HBV parameter sets at Borgharen with and without SOBEK Borgharen is a difficult measurement location and it is not easy to simulate the discharge here. This is caused by the presence of the weir upstream and the river diversions and confluences upstream of Borgharen. HBV is strictly a hydrological model and is therefore not able to take into account hydraulic effects such as the river geometry and weirs. By coupling the SOBEK model to the HBV model it is possible to take into account these weirs and river geometry. In Appendix A.2 information is given about the construction of the SOBEK model. In this paragraph the difference between the performance of HBV with the different parameter sets with and without the SOBEK model for the location Borgharen is analysed. 3 The comparisons could not be made for the full period ( ) because of the use of SOBEK. Because SOBEK has a long run time. Therefore, 10 days before and 10 days after the yearly maxima have been simulated. As there were not enough data available to carry out the comparison for all years, the analysis could only be carried out when: 1. the peaks of the yearly maximum are the same peak as the maximum of the hydrological year. 2. the measured yearly maximum discharge falls inside the same peak period as all simulated yearly maxima. 24 of 84 GRADE

33 3.3.1 Peaks In Table 3.3 and Table 3.4 the yearly maxima and the 10-days-yearly maxima are given for the simulations with only the HBV model and those with the SOBEK model included for the hydraulic routing. In this table the method is used that the yearly simulated maxima are given at the day of the real yearly maxima (timing of the peaks is not taken into account). The following conclusions can be drawn: The SOBEK model gives lower peak values than the HBV model. Due to the lower peak values also the volume of the wave decreases The performance of the new parameter sets improves when using the SOBEK model in comparison with the single HBV model The old parameter set performs better for the single HBV run (without SOBEK) than with SOBEK For the new parameter sets HBV5% and HBV25%, the performance of the yearly maxima is lower when taking into account SOBEK For the new parameter sets HBV50%, 75% and 95% the performance of the yearly maxima improves when taking into account SOBEK. Table 3.3 Borgharen HBV ( ). Yearly maxima Yearly 10 days-maxima (m 3 deviation /s) (m 3 deviation /s) (%) (%) Measurements* HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% Table 3.4 Borgharen SOBEK ( ). Yearly maxima Yearly 10 days-maxima (m 3 deviation /s) (m 3 deviation /s) (%) (%) Measurements* HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% *The comparison is made for the following years: , 1973, , 1982, 1984, 1986, 1987, 1990, , 1997, The comparisons could not be made for the full period ( ) because of the use of SOBEK. Because SOBEK has a long run time. Therefore, 10 days before and 10 days after the yearly maxima have been simulated. As there were not enough data available to carry out the comparison for all years, the analysis could only be carried out when: 1 the peaks of the yearly maximum are the same peak as the maximum of the hydrological year. 2 the measured yearly maximum discharge falls inside the same peak period as all simulated yearly maxima. GRADE 25 of 84

34 3.3.2 Wave pattern The wave pattern of the peak events is important to determine the standard wave pattern. The figures below give the simulated wave pattern for several flood periods. For the simulation shown in Figure 3.8 the old parameter set has been used. Figure 3.9 gives the wave patterns using the GLUE 50% parameter set (HBV 50%). Based on visual comparison the wave pattern generated with the 50% parameter sets is smaller than the pattern based on the old parameter sets. Despite of the smaller wave pattern the volume of the 50% wave is still larger for the 50% set (see previous paragraphs), which is caused by the higher peak waves. In Figure 3.10 the peaks of the simulations including the HBV50% and SOBEK are plotted. The shape of the peaks are comparable to the HBV50% peaks, however the height of the peaks is higher for the single HBV50% run than for the run which includes SOBEK discharge (m3/s) time (days) Figure 3.7 Measured peak discharge river Meuse at Borgharen using daily timestep. In the figure the timescale is shifted to let all peaks coincide. 26 of 84 GRADE

35 3500 discharge (m3/s) time (days) Figure 3.8 Old parameter set. Simulated discharge river Meuse at Borgharen using daily timestep. For the simulation the old parameter set has been used. In the figure the shifting of the peaks is equal to the shift of the measured data (Figure 3.8) discharge (m3/s) time (days) Figure 3.9 HBV50% parameter set. Simulated peak discharge river Meuse at Borgharen using daily timestep. For the simulation the 50% parameter set has been used. In the figure the shifting of the peaks is equal to the shift of the measured data (Figure 3.8). GRADE 27 of 84

36 3500 discharge (m3/s) time (days) Figure 3.10 HBV50% parameter set + SOBEK. Simulated peak discharge river Meuse at Borgharen using daily timestep. For the simulation in HBV the 50% parameter set has been used. In the figure the shifting of the peaks is equal to the shift of the measured data (Figure 3.8). 3.4 Performance of the parameter sets at Maaseik with SOBEK In this paragraph the performance of HBV at downstream location Maaseik is analysed. As the HBV model only simulates discharges upstream of Borgharen, the SOBEK model is used to simulate the discharges at Maaseik. In Table 3.5. the yearly maxima and the 10-days-yearly maxima are given. In this table the method is used that the yearly simulated maxima are given at the day of the real yearly maxima (timing of the peaks is not taken into account). It can be concluded that generally the new parameter sets perform better than the old parameter set. For the yearly maxima and the 10-days maxima the parameter sets between HBV5% and HBV50% perform best. In Figure 3.11 the yearly maxima are plotted against the accompanying year. It is not possible to draw any conclusions regarding the performance of the parameter sets. 28 of 84 GRADE

37 Table 3.5 Maaseik SOBEK Yearly maxima-day Yearly-maxima 10-days (m 3 deviation /s) (%) (m 3 /s) (m 3 /s) Measurements* HBV old HBV 5% HBV 25% HBV 50% HBV 75% HBV 95% *The Waterloopkundig Laboratorium of Vlaanderen kindly provided the discharge data of 1979 tot Because of limited SOBEK data the analysis is based on a limited number of years (1982, 1984, 1986, 1987, 1990, 1991, , ) Maaseik discharge (m3/s) old 5% 25% 50% 75% 95% Measured (year) Figure 3.11 Yearly maximum discharge for the river Meuse at Maaseik. 3.5 Performance of the parameter sets at Lith In this paragraph the performance of HBV at downstream location Lith is analysed. As the HBV model does only simulates discharges upstream of Borgharen, the SOBEK model is used to simulate the discharges at Lith. Dienst Limburg of RWS kindly provided the discharge data at Lith of 1968 tot However, the Q-H relation is considered unreliable for high discharges. In Table 3.6 the yearly maxima and the 10-days-yearly maxima are given. In this table the method is used that the yearly simulated maxima are given at the day of the real yearly maxima (timing of the peaks is not taken into account). It can be concluded that generally the new parameter sets perform better than the old parameter set. GRADE 29 of 84