6 Model development. 6.1 Introduction. 6.2 The hydrological model

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1 6 Model development 6.1 Introduction The intention of this project was to create a model that would use rainfall as an input and predict inundation areas and extents on a daily basis, in map form, that would be easy to understand by managers and specialists from other disciplines involved with the Nylsvlei floodplain. Stewart Scott Consulting Engineers developed the hydrological model that transformed rainfall in the catchments of the floodplain to flows at the floodplain margin on a daily time step. The CWE developed the hydraulic model that transformed these inflows into inundation areas and depths on the floodplain and flows further down the floodplain. The development of these models is discussed in this chapter. 6.2 The hydrological model A hydrological model of the Nylsvlei floodplain catchments was developed by Stewart Scott Consulting Engineers to convert rainfall into runoff at the floodplain margin, to be fed into the hydraulic model. The hydrological modelling was achieved using Stewart Scott s in-house programs WRSM2000 and DAYFLOW (Pitman, 1998) and is described in a report entitled Hydrological Model Calibration, DWAF Report no. P WMA 01/A61/00/0403 (Pitman and Bailey, 2003; Bailey, 2003). The hydrological model is summarised briefly here, to give a broad view of the entire model. WRSM2000 can produce flows on a monthly time step and DAYFLOW can produce flows on a daily time step. DAYFLOW was used to provide the required daily flows for the hydraulic model, while WRSM2000 was used for the purposes of comparison and for broader planning of the Mogalakwena basin (Bailey, 2003). Flows were produced by the model at the various DWAF flow gauges in the catchments and calibrated on a station-by-station basis against patched flow data using historical peak flows as well as monthly and annual flows. Flows were modelled for ungauged catchments using extrapolated catchment data from adjacent calibrated catchments. Calibration was achieved using patched rainfall 123

2 data. Due to a sparse distribution of rain gauges in the catchments, gauges were selected to represent five extensive zones and monthly rainfall time series were calculated for each zone, and applied to each sub-catchment within these zones. Due to the limited areal extent of many storms in this area, a representative rain gauge was selected to represent rainfall for each zone. The limited areal extent of typical convective storms in the Nylsvlei catchments is shown in Figure 6.1. Evaporation records were used from six evaporation stations in the area. Figure 6.2 shows the positions of the rainfall, evaporation, geohydrological and flowgauging stations in the catchment and the location of the hydraulic study area of the floodplain. Figure 6.1: View north to the Waterberg foothills from Vogelfontein in the Nylsvley Reserve, showing the typical limited areal extent of convective storms in the Nylsvlei catchments. 124

3 Figure 6.2: Map of the Nylsvlei floodplain and catchments showing the positions of all evaporation, rainfall, geohydrological and flowgauging stations (after Pitman & Bailey, 2003). 125

4 An extensive basin study was conducted to determine historical water use. The hydrological model took into account historical growth of impoundments (all registered and unregistered dams with a surface area greater than m 2 were included), afforestation, urbanization and irrigation (water was abstracted from the rivers until their capacity for supply was depleted, then water was abstracted from the groundwater storage) developments in the catchments. The model was verified using a graphical comparison of observed and simulated ranked maximum daily flows and a comparison of observed and simulated frequencies of flows above each of a range of thresholds. Additional verification was achieved by simulating natural streamflows for the various sub-catchments of the Nyl River, estimating the long-term mean annual runoff (MAR) and comparing these MARs with the MARs obtained in the Mogalakwena Basin Study (Schultz, 1992) at various locations along the Nyl River. Bailey (2003) found the performance of both models (WRSM2000 and DAYFLOW) to be similar with respect to the simulation of annual flows but the daily model was superior in the generation of monthly flows. Bailey found the daily model s ability to simulate daily flows to be adequate. The modelled daily flows from these gauges were then routed downstream to the four entry points where the rivers enter the floodplain study area at the floodplain margin, taking into account the intervening catchment areas. Equation 7.1 for the Nyl River at Middelfontein shows the form of the routing equations. Patched historical flows were also routed to the floodplain entry points using these equations and were used in an application of the model (that also served as an additional verification) and for tributary inflows for the model calibration and verification (Middelfonteinspruit, De Wet Zyn Loop and Bad se Loop). Flows from the ungauged Eersbewoondspruit (Blindefontein) were modelled and output at the floodplain margin. Modelled historical, present day and virgin flow data were provided from 1973 to 2001 on a daily time step at each gauge site in the catchments and at the floodplain margin for the Nyl River and all five tributaries. 126

5 These modelled data series were used in the scenario modelling discussed in Chapters 7 and Introduction to the hydraulic model The choice of hydraulic modelling method and commercial package (if desired) was very important, as this would have a bearing on the accuracy of the model and ease of modelling. This is discussed in detail in Chapter 2. The setting up of the hydraulic model was carried out together with Birkhead, who set up the model for the Nylsvley Reserve and Vogelfontein Mosdene reaches and converted the DWAF continuous stage data to daily data. I set up the model for the Middelfontein reach under the supervision of Birkhead. The reaches are defined in Figure 1.4. This chapter is about the model set up and some of the general description of this is from Birkhead et al (2004). The Nylsvlei floodplain is a relatively flat floodplain with an ill-defined channel, and in the lower reaches no defined channel. Numerous man-made features modify the flow such as dams, levees, dikes, ditches and roads. It is generally accepted that a two-dimensional model would best describe flow (which is twodimensional) in this sort of environment. Thus, Birkhead (Birkhead et al, 2004) initially attempted to model the floodplain using a two-dimensional modelling package, Surfacewater Modelling System (SMS) marketed by Boss International ( the most advanced two-dimensional dynamic-flow software available. He successfully used SMS to develop a steady-state model for a portion of the Reserve area. However, he experienced difficulties with unsteady simulations that involved wetting and drying of boundary elements. Having assessed the SMS model of the Reserve area, the hydraulic modelling group at Boss International advised the alternative use of one-dimensional modelling through RiverCAD for simulating the flow behaviour of the Nyl River floodplain. 127

6 This resulted in the Nylsvlei floodplain being modelled in one-dimension using the following commercial programs: Quicksurf RiverCAD HEC-RAS, and HEC-DSSVue Quicksurf was used to draw the contour map of the Nylsvlei floodplain, using the LiDAR survey data. This program was purchased from Boss International ( and works within a CAD program called FelixCAD. Quicksurf converts surface mapping data such as point and/or break-line data into contours, grids (GRDs), triangulated irregular networks (TINs), and triangulated grids (TGRDs). A suite of tools allows the manipulation of surfaces into high quality maps. Quicksurf version 5.1 and FelixCAD version 2.1 were used in this project. RiverCAD was used as a pre and post processor to the hydraulic modelling software HEC-RAS. RiverCAD is an advanced graphical modelling environment, providing support for the US Army Corps of Engineers one-dimensional flowanalysis software HEC-RAS (Hydrological Engineering Centre - River Analysis System). RiverCAD was used to extract cross-sections from the contour map created in Quicksurf and was used to map floodplain inundation areas. A raster image module allows the loading of geo-referenced digital images (aerial photographs were used at Nylsvlei), in the background behind maps, which can be very useful for picking out features on the floodplain. HEC-RAS was used for the unsteady hydraulic modelling of the floodplain and is part of the next generation (NexGen) of hydrologic engineering software encompassing several aspects of hydrologic engineering, including rainfall-runoff analysis, river hydraulics, reservoir systems simulation, flood damage analysis, and real-time river forecasting for reservoir operation. It is an integrated system 128

7 of software, designed for interactive use in a multi-tasking environment. The system comprises a graphical user interface, separate hydraulic analysis components, data storage and management capabilities, graphics and reporting facilities. HEC-RAS version 3.1 performs unsteady flow simulations through a full network of open channels and data storage is accomplished using ASCII and binary files, as well as the HEC-DSS. Graphics includes plan plots of the river system schematic, cross-sections, longitudinal profiles, rating curves, hydrographs and other hydraulic variables, which may be passed to the Windows clipboard for use in other software (such as the preparation of figures for reports). The various graphical outputs may also be animated. The theory on which HEC-RAS is based is summarised in Chapter 2. HEC-RAS version 3.1 was used in combination with the HEC-DSSVue version in this study. This software is free-domain, and may be downloaded with supporting manuals (Adobe PDF format) from the US Army Corps of Engineers HEC web site at The Middelfontein reach is discussed in depth in this chapter, as this particular reach was set up and calibrated as part of this Masters project. Modelling of the other reaches (Nylsvley Reserve and Vogelfontein Mosdene Reaches) was done by Birkhead and is described in full by Birkhead et al (2004). 6.4 Drawing a contour map using Quicksurf Quicksurf was used to draw contour maps of each of the three modelled reaches of the Nylsvlei floodplain. Quicksurf uses surface memory storage, rather than a drawing database, to reduce the amount of memory required to manipulate data thereby providing fast execution of modelling operations. Quicksurf uses what are termed surfaces and FelixCAD what are termed layers. A surface is stored in CAD-controlled memory; the data in a surface cannot be viewed until it is drawn into a layer. If entities are drawn into a layer by the user, they cannot be operated upon by the Quicksurf functions until they are extracted to a surface. Surfaces are saved with.qsf file extensions, which save the data in binary format, and layers 129

8 are saved with.flx file extensions. This system is used as the binary.qsf files are a more efficient method of storing the surface data, and use the RAM memory of the computer more efficiently. The contour map of each reach of the floodplain was drawn as follows: 1. The LiDAR survey point data, in ASCII format, was imported into the results or dot surface within Quicksurf. These points cannot be seen as they exist merely in the memory of the program as a surface. These points were then drawn to a layer so that they could be seen (Figures 3.13 and 3.14). 2. A boundary was then drawn around the floodplain area being mapped. The boundary extended from the upstream side of the upstream road-crossing to the downstream side of the downstream road-crossing for each reach, and only as far up the sides of the valley as flooding would occur, i.e. to include only relevant data on the floodplain, due to the large amount of data available from the LiDAR survey. For example, there were approximately data points inside this boundary in the Middelfontein to Nylsvley Reserve (upstream) reach alone. The boundary was drawn on a separate layer as a 2D polyline, and subsequently saved as a boundary file. This boundary file was loaded first, followed by the LiDAR points, and this saved time by leaving out all the unneeded points. 3. A contour map was drawn to a new layer, with a 10cm contour interval based on a triangular irregular network, or TIN. A TIN consists of a series of triangles drawn linking every point with the points immediately around it and is the most accurate surface form that can be drawn, as it uses every data point in the surface available from the LiDAR survey. This TIN file was very large and so was cumbersome to manipulate on a computer. The highly accurate 10cm contour map based on the TIN was used to see features in the landscape, such as levees, roads, dams and depressions. A 130

9 contour map of the southern portion of the Nylsvley Reserve at 10cm contour intervals based on the TIN, is shown in Figure 6.3, with contours of different colours showing different ranges in height. Figure 6.3: Contour map at 10cm intervals for the upper portion of the Nylsvley Nature Reserve between GP2 (Deelkraal Road) and GP4. (after Birkhead et al, 2004) 4. A triangular grid, or TGRD, was drawn so that the grid points could be extracted from it and used to draw a contour map at a 20cm contour interval in an effort to reduce the amount of data and thereby make the data manipulation less cumbersome. A TGRD is a type of TIN where the surface is based on a special data set of points arranged on a regular grid, with a spacing defined by the user. It is very similar to a normal square grid, except that it has triangles in between which allows it to honour break lines exactly, where a normal grid cannot. A break line is a line that marks a sharp transition between two different slopes. These were used in the model to mark the edge of the channel. A normal grid can show a break line as a zig-zag pattern due to its grid shape, while the triangles in a TGRD allow each point on the break line to be honoured exactly. The TGRD is not as accurate as the TIN surface, as it uses points on a grid that 131

10 have been calculated using the denser LiDAR base data. The method used to calculate the vertical position of the TGRD points used second derivatives of the TIN surface, to create a TIN surface that was smooth between the TIN data points, so that the triangles between the TIN points weren t planes but rather were curved in shape allowing a smooth change in slope between each triangle. According to the Quicksurf manual, this is a satisfactory and generally accurate method. Originally a TGRD at grid spacings of 20m x 20m was drawn but this produced about grid points in the Middlefontein reach, which including all the other points in the program exceeded the maximum number of points allowed by the software. This problem was apparently due to be fixed in a newer version of Quicksurf, to be released late in A second TGRD was then drawn at a grid spacing of 25m x 25m with the number of points just less than the maximum allowed by the program. The resolution of the grid had to be sacrificed to a degree but it was not expected to be significant to the quality of the final product. The Nylsvley Nature Reserve reach modelled by Birkhead (Birkhead et al, 2004) used a TGRD spacing of 20m x 20m but the section downstream of the reserve at Mosdene was also modelled at a spacing of 25m x 25m. The points from this TGRD were then drawn to a new layer. 5. Other areas that had to be dealt with included areas of high relief that the TGRD would not describe adequately such as levees, roads, depressions, oxbow lakes and the Deelkraal Dam. At first, it was planned to trace lines on these features and then drape them onto the TIN and cut them into the TGRD in the same manner as was done for the channel (see points 6 to 8). Birkhead (Birkhead et al, 2004) found this very laborious, as it was time consuming for the computer and problems were also experienced with areas where two or more levees met at a T-junction as these are not easy to represent in the program. Tracing the levees along their highest points was also difficult and inaccurate, and led to errors. Birkhead devised a better way, where the LiDAR points in areas of high detail relief were inserted 132

11 into the TGRD to accurately reflect the terrain in these areas. This was done by drawing boundaries around all the high relief areas of interest onto a separate layer. These boundaries were then extracted to a boundary file and saved. The LiDAR points were drawn to the 25m x 25m grid point layer using the boundary file, so that the LiDAR points lay in the areas of high relief together with the few grid points in those areas. Figures 6.4 and 6.5 show the northern portion of the Nylsvley Reserve, with all the levee detail shown in the map and photograph. 6. The channel centreline was traced using the TIN contour map and the aerial photos to identify the channel position, onto a new layer as a 2D polyline, taking in all the meander details. This polyline was then smoothed using the smooth contours function to reflect the actual channel course. The channel centreline was draped onto the TIN, which changes the 2D polyline in x and y to a 3D polyline in x, y, and z, assuming the vertical level of the TIN directly beneath it. The vertical level in this case generally represented the water surface in the channel on the day the floodplain was surveyed. 7. The draped centreline of the channel was flattened producing a long section view of the channel water surface vertical alignment. The channel water surface vertical alignment followed a general downward trend as would be expected but with quite a lot of noise at a resolution below approximately 20cm in height. This can be attributed to three reasons: a. The channel is not flat but has pools, dips and peaks along its bed. b. The traced centreline of the channel was not always exactly along the centre of the channel, but followed the general path of the channel and at times deviated from the side of the channel near bends. c. The absolute accuracy of the LIDAR system is 15cm and so there would be some variation due to this. 133

12 Flow Nyl River Tree grove & bird hide Dykes Vogelfontein Road Gauge A6H037 Figure 6.4: Annotated contour map (20cm intervals) of the Nylsvley Nature Reserve upstream of the Vogelfontein Road, showing the artificial dikes (after Birkhead et al, 2004) Figure 6.5: Vogelfontein causeway, looking upstream into the Nylsvley Nature Reserve. The influence of artificial topographical features (dikes and road) on the hydraulic behaviour is noticeable. A bird-hide is located in the tree-grove upstream of the road (photo K. Rogers) (after Birkhead et al, 2004) 134

13 A line was drawn onto a new layer that took the average gradient of the long section profile of the water surface - a generalised long section. This line was then dropped by 1.5m to ensure that it was lower than the channel water surface at all times. The revised and deepened channel bed alignment was then applied to the channel centreline, changing the channel centreline from a 3D polyline with the z dimension determined by the draped line on the TIN, to a 3D polyline with the z dimension determined by the new bed alignment. This is artificial in that the channel is being modelled as deeper than it really is, but this was not expected to have a significant effect on the modelling results. 8. The channel was then cut into the surface with a defined cross-section (a 10 metre wide bed and 1:1 side slopes - a simplified but typical crosssection of the channel) along the channel centreline, removing all the points of the surface that fell within the channel area. This process took a long time, several hours was a normal duration. The new channel crosssection then consisted of four breaklines, the two daylight lines that represented the intersection of the channel sides with the surface and the two lines at the bottom of the channel that represented the change in slope between the channel bed and its sides. An artificial channel was cut into the DTM because the channel in the Nylsvlei floodplain is indistinct in places, has many pools and a varying gradient, and the accuracy of channel topographical points were in doubt as parts of the channel were inundated at the time of the LiDAR survey. Stability in the HEC-RAS unsteady model can be significantly improved by having a smooth long-section channel invert slope as opposed to a long-section with pools and riffles where super-critical flow can occur. The artificial channel changed the cross-sectional area and cross-sectional shape of the floodplain but this was accounted for in the calibration phase of the project where the Manning s resistances of the channel were adjusted. 135

14 Figure 6.6: Contour map at 20cm intervals for the upper portion of the Nylsvley Reserve, with every fifth contour shaded in black (i.e. at 1m intervals) (after Birkhead et al, 2004) 9. The points from the 25m x 25m grid and the denser random laser points for levees, dams, roads and depressions were extracted from the layer created in points 1 to 8 and saved to a new named surface. A new contour map was drawn with a 20cm contour interval using a TIN based on this new surface with the channel breaklines. This contour map was coloured with grey contours and every fifth contour was coloured white. The 20cm contour map of the southern portion of the Nylsvley Reserve is shown in Figure 6.6. Unnecessary contours were removed manually: there were many areas where there were small contour loops making the map harder to read. These contours were saved to another layer for use in RiverCAD, referred to as deleted contours from here on. 6.5 Positioning and extracting cross-sections using RiverCAD As explained earlier, RiverCAD was used as a pre and post processor program to HEC-RAS to position and extract cross-sections, measure reach (channel and 136

15 floodplain) distances between adjacent cross-sections, enter boundary conditions for steady-state hydraulic computations using HEC-RAS, and map floodplain inundation after simulations were completed. The procedure is as follows: 1. The contour map drawn in Quicksurf was opened in RiverCAD, together with the aerial photograph of the floodplain (a raster image), which was loaded in the background and geo-referenced by selecting the associated world coordinate file (Figure 6.7). The contour map overlying the aerial photograph makes identification of features easy and more accurate and is similar to an orthophoto. 2. Cross-sections were cut from downstream to upstream and were numbered in this order, as per the requirements of HEC-RAS. Cross-sections were cut in such a way that they were always perpendicular to the assumed flow direction through the floodplain and channel, which means that few of the cross-sections were straight and most consisted of numerous straight line segments. Figure 6.7 shows an area in the Nylsvley Reserve, near the bird hide at GP4, with the cross-sections in yellow. Figure 6.8 shows the same area looking upstream. Birkhead (Birkhead et al, 2004) notes however that inclusion of the large number of hydraulic controls on the floodplain is of great concern. Cross-sections were therefore positioned in places where there was an abrupt change in area at hydraulic controls such as levees, dikes, dams and roads that run perpendicular or close to perpendicular to the flow of the water on the floodplain, at stage monitoring locations, and after this at regular spaces in-between where necessary. The cross-sections at the dikes, levees, dams and roads were cut on the crest of these structures. Fifty-one cross-sections were cut on the Middelfontein reach for example. On this reach a cross-section was cut across the Deelkraal Dam wall, where water flows past the dam in a channel and only the initial flow from floods seems to get stored in the dam itself. In the Middelfontein reach, two cross-sections were also cut on tracks that cross the floodplain, one downstream and one upstream of the Deelkraal Dam 137

16 Chapter 6: Model development Figure 6.7: Position of cross-sections (yellow transects) downstream of Gauge Plate (GP) 4 in the Nylsvley Nature Reserve, superimposed on a background image of the floodplain and 20cm contour map. The Nyl River flows from the bottom to the top of the figure (after Birkhead et al, 2004) Figure 6.8: Photograph of the same area as in Figure 6.7, looking upstream towards Gauge Plate (GP) 4. A bird hide is located in the reed beds through which the Nyl River flows. (photo K. Rogers) (after Birkhead et al, 2004) 138

17 (Figure 6.9). Both these tracks cross the floodplain on small embankments and have culverts at the channel crossing. The upstream track culvert is very close to the DWAF stage gauge A6H002, where another cross-section was cut. Cross-sections were cut just upstream of the downstream roadcrossing and just downstream of the upstream road-crossing in each reach. Figure 6.9: Aerial view of the Deelkraal Dam, looking downstream, a channel runs past the dam to the bottom right of the photograph (photo K. Rogers) 3. Next, the two contour layers created in Quicksurf, the continuous and deleted layers, were used together to generate cross-section profiles automatically in RiverCAD 4. Flow lengths between cross-sections on the left and right overbank areas and in the channel were traced in RiverCAD and entered into the program. Manning s resistances can also be defined for each of these individual flow lengths. Bank stations define the boundary between the left overbank, 139

18 channel and right overbank flow areas. Defining the position of these bank stations can be useful in calibration of the model. 5. The model was roughly calibrated for steady flow conditions using the HEC-RAS module within RiverCAD. Various steady flows were input into the system and the stages output by the model for the upstream-most and downstream-most cross-sections in each reach and were checked against the stages as given by the rating curves at these cross-sections. Calibration was achieved by adjusting the values of the Manning s resistance at these two cross-sections on each reach. A Manning s resistance of 12 in the channel and 2 on the floodplain at the N1 (A6H039) and Manning s resistance of 2 in the channel and 0.2 on the floodplain at the Nylsvley Bridge (GP2) in the Middelfontein reach was used, for example. These very high flow resistance values are due to channel and floodplain vegetation, the artificially deep channel cut into the floodplain surface in the model (explained in section 6.4), and channel and floodplain topography (such as the numerous levees and dikes) which are not fully accounted for in a one-dimensional model. 6.6 Unsteady hydraulic modelling using HEC-RAS The hydraulic modelling was carried out using the stand-alone program HEC- RAS, reviewed in more detail in Chapter 2. Calibration of the model using HEC- RAS is described later. HEC-RAS is a one-dimensional modelling package, which assumes the flow direction to be in only one direction downstream. Birkhead (Birkhead et al, 2004) maintains that this is not unreasonable for the Nylsvlei floodplain as the lateral flow gradient will be near-horizontal except with the initial overtopping of stream banks and levees when laterally spreading flows inundate local depressions in the landscape. The longitudinal water surface slope of the Nylsvlei floodplain is reasonably steep for a wetland ( , and for the upper, Reserve and lower study areas, respectively) and is likely to exceed lateral water surface slopes under most flow conditions. Figure

19 shows a typical view of the floodplain in the Nylsvley Reserve, the channel is very clear in this view. The cross-section and flow length between cross-section data were imported from RiverCAD as geometric data. Boundary conditions in the form of an inflow hydrograph at the upstream end and rating curve at the downstream end of each reach were input. The inflow hydrograph and downstream rating curve were imported into HEC-RAS from HEC-DSS, the viewing program used for all the HEC programs. The inflow hydrographs for calibration and verification were created using CWE or DWAF measured stage data at the inflow point to each reach (gauges A6H039 for Middelfontein, GP2 for the Nylsvley Reserve, A6H037 or GP7 for Mosdene), fed through a rating curve derived from measured stage and flow data by the CWE as discussed in Chapter 3. The inflow hydrographs for the application of the model were obtained from patched stage records measured at the DWAF gauges in the catchments converted to flows and routed to the respective inflow points. Flows were supplied by Stewart Scott International obtained from the hydrological model for the scenario modelling. The downstream rating curve was derived by the CWE from measured stage and flow data, also discussed in chapter 3 (Figures 3.5 to 3.8). Tributary inflows were entered as boundary conditions in the form of lateral inflow hydrographs. The flow data for tributaries were provided by Stewart Scott International from measured flows at gauges in the catchments routed to the floodplain or as modelled flows for ungauged catchments (in particular the Eersbewoondspruit). The two tributaries flowing into the Middelfontein section of the floodplain for example, were the Middelfonteinspruit (with DWAF flow gauge A6H020 along its reach) that enters the floodplain about 1.5kms downstream of the N1 between cross-sections 47 and 46, and the De Wet Zyn Loop (referred to by Birkhead et al (2004) as the De Wet Spruit) with DWAF flow gauge A6H021, which enters the floodplain about 500m upstream of the Nylsvley Bridge (GP2), 141

20 between cross-sections 2 and 3. Flow-time series files were created using HEC- DSS and linked to the model using the Unsteady Flow Data window in HEC- RAS. An artificial minimum inflow of 0.1 m 3 /s was defined, and any inflow below this rate was set to this rate using a spreadsheet. This was done to maintain numerical stability, as very low or zero flows cause modelling instability. A flow of 0.1 m 3 /s occurs within the channel so flows smaller than this are not significant to inundation. There is a facility in HEC-RAS to set a minimum flow to maintain model stability, but in version used here, this option did not work. It was found to work in later versions of HEC-RAS however, obviating the need to impose a minimum flow using a spreadsheet. Initial conditions have to also be defined - an initial flow of 0.1 m 3 /s was input corresponding to the minimum inflow defined in the inflow hydrograph at A6H039. HEC-RAS has a very useful facility that allows variable time steps, speeding up run times of the model. A large time step can be defined for a run and when the model encounters a sudden change in flow, the time step can be cut in half repeatedly until the flow increase per time step is smaller than a user-defined value. The Middelfontein reach of the model was run at half-hour time steps; when inflows at the N1 increased by more than 0.03m 3 /s per time step, time step cutting was introduced and the time step could be sliced up to 11 times. The maximum increase in inflow that triggered time step cutting was determined by trial and error. An initial stability issue was the spacing of cross-sections, which were generally too far apart. New cross-sections can be interpolated between existing crosssections in HEC-RAS to improve numerical stability. Levees, weirs and ineffective flow areas can also be incorporated into the model. Ineffective flow areas are areas where water is ponded but not flowing, such as areas behind levees and dam walls. 142

21 Rainfall, evapotranspiration and ponding and infiltration losses were converted to average daily flows in m 3 /s, found from a daily flow volume using methods described later. It was attempted to include the evapotranspiration, infiltration, and ponding losses in HEC-RAS as a uniform lateral inflow. This allows additions or subtractions of flow to be distributed uniformly to every cross-section in the model. Unfortunately, Birkhead (Birkhead et al, 2004) found that subtracting losses as uniform lateral inflows caused model instability - only rainfall could be added in this manner. It was then attempted to take account of losses due to evapotranspiration and infiltration and ponding, by subtracting these from the Nyl River inflow file before the model was run. Inaccuracies due to this simplification are largest at the inflow and reduce with distance downstream and also increase with longer reach lengths. This produced unacceptable results for the upper portions of the modelled floodplains, and an alternative means of incorporating losses was sought. HEC-RAS allows for the extraction of flows using pump stations. Pump operation (on/off) may be linked to stage levels and an efficiency curve (headflow relationship) specified. Using this facility, a number of pumps were specified along the length of the floodplain to extract losses. The efficiency curves were determined by correlating estimated daily losses with stage levels, and hence pumping head. In this way, flows are more realistically reduced with distance downstream. Three pumps were used in the Middelfontein reach, at crosssections 15, 25 and 35. In order to maintain stability with three pumps in the system, all interpolated cross-sections at a maximum of 100m intervals were deleted and reinterpolated at a maximum of 400m intervals. All time series and stage-discharge data were input and output through HEC-DSS (HEC Data Storage System). This included all boundary input data, output data and observed data for calibration. Large fields of data could be cut and pasted to or from a spreadsheet to HEC-DSS, where the data files and paths could be linked to the model. HEC-DSS is also designed to graph and tabulate hydraulics data and comparing hydrographs was very easy and efficient. 143

22 The three modelled sections were linked by making the outflow file of an upstream reach the inflow file to a downstream reach. 6.7 Predicting inundation surface areas Losses due to evapotranspiration, infiltration, ponding and the addition of rainfall were included in the model, as explained previously. Evapotranspiration, infiltration and rainfall are generally measured as a depth and an inundated area is therefore required to account for these. Birkhead (Birkhead et al, 2004) found that inflow and inundated area were well correlated for the Nylsvlei floodplain. A regression of daily inflows and inundated areas was conducted for each reach (see Figure 6.10 for the Middelfontein reach and equations 6.1 to 6.3). The regressions were conducted over the hydrological year 1 October 1999 to 30 September 2000 (Birkhead et al, 2004), a part of the verification period. Inundated areas could be determined from the inflow relatively accurately using this inflow area relationship, negating the need for an iterative area and loss determination method. Top widths of the inundated areas at each cross-section; reach lengths and inflows were output in tabular form by HEC-RAS. The average of the right and left overbank reach lengths were used to find a reach length between each crosssection in the Middelfontein reach, in an attempt to exclude unrealistic reach lengths due to channel meanders. The longitudinal distance that would be used to calculate the inundated area around each cross-section was found by taking half of the downstream reach length for the cross-section in question and adding it to half the reach length of the cross-section upstream. The tops widths and longitudinal lengths were fed through a program written by Birkhead (Birkhead et al, 2004), which multiplied the top width by the reach length for each cross-section to find the inundated area. The inundated areas of all cross-sections on each day were summed to find a total inundated area for each day. 144

23 For flows less than or equal to 0.1m 3 /s, the inundated area was set to zero, and the regression line was forced through this point. About 15 points in the Middelfontein reach regression showed small inundation areas corresponding to high inflows and were ignored in the analysis as these were thought to have occurred when the floodplain was beginning to inundate with high rates of inflow and small inundation areas, while the flood peak was travelling through the reach. The modelled relationships therefore overestimate inundated surface area during initial flooding (Birkhead et al, 2004) Inundated area (km 2 ) Flow (m 3 /s) Figure 6.10: Measured inflows from the DWAF stage plate A6H039 for the 1999/2000 hydrological year, plotted against inundated area in the Middelfontein reach together with the best fit regression line The goodness of fit was acceptable for the Middelfontein reach, with an R 2 of The regression equation for the Middelfontein reach is given below: A = I I I (0 < I <16.0) A = 12.9 (I 16.0) (6.1) 145

24 where A is the surface area of inundated floodplain (km 2 ), and I is the inflow from the Nyl River (m 3 /s). According to equations 6.1 and 6.2, inundation area increases at a steadily decreasing rate with increasing inflow, with the simplification of a constant limiting value. The topography does not suggest that the inundation area reaches a constant limiting value above certain flows, but inundation areas greater than the limiting value represent very large flows that occur infrequently. The equations developed by Birkhead (Birkhead et al, 2004) for the Nylsvley Reserve and Nylsvley Reserve to Mosdene sections are given below: Nylsvley Reserve A = 2.513I (0 < I < 20.1) A = 13.2 (I 20.1) (6.2) Nylsvley Reserve to Mosdene A = I (6.3) 6.8 Water balance of the Nyl River floodplain A water balance for the floodplain was used to quantify the contributions of inflows (I) (stream flow and rainfall) and outflows (O) (stream flow, evapotranspiration, infiltration and ponding), and was also used to develop an empirical relationship for the losses arising from infiltration and ponding, which are difficult to measure. A water balance equation for the Nylsvlei floodplain can be given as: Nyl River inflows + tributary inflows + rainfall on inundated areas Nyl River outflows evapotranspiration infiltration ponding = 0 (6.4) 146

25 Data were available for all the terms in this equation except infiltration and ponding losses. Infiltration is difficult to measure and as discussed in Chapter 5 is thought to be a relatively small loss. Quantifying ponding losses would have been difficult and Birkhead therefore decided to solve for a lumped term consisting of infiltration and ponding losses. The daily evapotranspiration losses were found by multiplying the daily evapotranspiration depth (mm) by the inundated area for the same day, determined from the inflow to the reach. Rainfall addition to the inundated areas of the floodplain was determined in a similar way. Rainfall data from the Nylsvley weather station were used in this model (gauge shown in Figure1.3 and 6.2). It was decided to use these rainfall data instead of the Nylstroom gauge rainfall data due to the proximity of this reach to the Nylsvley Reserve. The rainfall data for Nylsvley were compared to that of Nylstroom by Morgan (1996) and found generally to have similar rainfall depths on the same days, despite the limited areal extent of many storms in this area. A water balance was conducted for each year when there were flow data available, for all three reaches, this was for the 1998/1999 and 1999/2000 hydrological years in the Middelfontein reach (Table 6.1). Daily inflow volumes from the Nyl River and tributaries together with daily rainfall (found by the method described earlier and given as a daily averaged inflow) were cumulatively summed over each year and measured daily outflows and evapotranspiration losses for each year were cumulatively summed and subtracted. This was done cumulatively to avoid the influence of unsteady flow effects (Birkhead et al, 2004). Thus, the water balance yielded the missing term in the equation - losses due to infiltration and ponding of floodwaters. The water balance turned out to be positive in the Nylsvley Reserve (which had data available for a water balance for six years /1996 to 2000/2001, the last four years yielding positive loss volumes). The other reaches yielded negative water balances throughout and were negative even before evapotranspiration and rainfall were included inferring that inflows were underestimated and/or outflows overestimated (Birkhead et al, 147

26 2004). Results for the Nylsvley Reserve reach were therefore used for the other two sections. These negative losses were possibly due to: incomplete and discontinuous stage records the coarse resolution of stage data collection on the Nyl River - CWE gauges were generally only read every five days, data for the missing days were interpolated. This means that flood peaks may have been missed. inaccuracies in modelled inflows on ungauged tributaries inaccuracies in extrapolated inflows on tributaries with DWAF gauges further upstream, which took into account the intervening catchment areas and flow distances (for instance the Middelfontein and De Wet Zyn Loop DWAF gauges were 3km and 7km respectively from the floodplain margin on the Middelfontein reach). These flows were also patched for periods where flow data was missing. inaccuracies in the rating curves inaccuracies in rainfall depth, evapotranspiration rates and inundated areas on the Middelfontein reach, certain peak outflows at GP2 could not be matched if all the inflow peaks from tributaries and the Nyl River were summed for the same flood. For example in February 2000 a flood peak of 45 m 3 /s passed out of the floodplain yet the maximum combined peak inflow was only 20 m 3 /s. This situation occurred again in March and April of Birkhead et al (2004) state for the last four years of the water balance exercise in the Nylsvley Reserve reach, losses to infiltration and ponding (I 0) were between 3.3 x 10 6 and 10.7 x 10 6 m 3, significantly higher than losses to evapotranspiration which ranged from 0.8 x 10 6 to 2.8 x 10 6 m 3. Most of these losses are probably due to ponding followed by subsequent evaporation as infiltration was found to be very low on the floodplain (Chapter 5). They concluded that a method for predicting these losses was required, and given the limited data and uncertainties in the water balance, the use of a simple empirical equation was appropriate. The derivation of this equation is explained below. 148

27 Inundation areas were calculated cumulatively in a similar fashion using the inflow inundation area relationships over the course of each hydrological year. The cumulative infiltration and ponding losses and cumulative inundation areas gave four data points in the Nylsvley Reserve reach with sensible loss estimates (years 1997/1998 to 2000/2001) (Birkhead et al, 2004). A regression was conducted on these data and an equation of form y = ax b + c was derived where infiltration and ponding losses could be found on an annual cumulative basis, from annual cumulative inundation area (equation 6.5). L t = 0.472( A t ) (6.5) where L t is the cumulative loss (m 3 ), and A t is the cumulative surface inundation area (km 2 ) for the hydrological year, and t is time (days) (Birkhead et al, 2004). Losses were not correlated directly with inflow, since transferability of the loss function to other regions of the floodplain was required (Birkhead et al, 2004). This equation was used to calculate infiltration and ponding losses on a cumulative annual basis for every year, and in the other two reaches. Equation 6.5 cannot be applied to inundation area data on a daily basis since addition and exponentiation are not commutative operations (Birkhead et al, 2004). Daily values were therefore obtained from the difference between consecutive cumulative daily values (equation 6.6). L t = ( L t - L t-1 ) (6.6) where L t is the daily loss (m 3 ) due to infiltration and ponding, and t is time (days) (Birkhead et al, 2004). 149

28 Table 6.1: Water balance for the floodplain from Middelfontein to the Nylsvley Reserve (after Birkhead et al, 2004) Hydrological year Cumulative inundated area, ΣA (km 2 ) HEC- RAS Equation 6.1 Nyl River Inflows, I (10 6 m 3 ) Middelfonteinspruit De Wet Zyn Loop Rainfall Outflows, O (10 6 m 3 ) Nyl River ET I - O Balance (10 6 m 3 ) Loss Equation /1999* /2000* ET evapotranspiration, * - missing data Estimated total losses (including evapotranspiration) in the Middelfontein reach (Table 6.1) accounted for between 16% and 35% of the total inflows, in the Nylsvley Reserve for between 13% and 50% of the total inflows and in the Vogelfontein Mosdene reach between 26% and 100% (Birkhead et al, 2004). 6.9 Calibration of the model Calibration defines the process of adjusting certain parameters values to give modelled results that agree, as closely as possible, with measured values (Birkhead et al, 2004). The model was calibrated against observed stage and flow data from CWE and DWAF gauges along the floodplain. Details of the positions of these gauges are given in Figure 1.3, Figure 6.2 and Table 3.1; details of these gauges data sets are given in Table 3.2; their flow data series are given in Table 3.3 and their stage data series are shown in Figures 3.1 to 3.4. The calibration of the models is discussed with specific reference to the Middelfontein reach, due to this reach being modelled by the author. The calibrated flows and stages are shown in Figures 6.11 to In the case of the Middelfontein reach, calibration was conducted against observed data at the upstream and downstream ends: A6H039 (cross-section 51) and GP2 (cross-section 1) respectively and at the stage gauge at Deelkraal (A6H002, cross-section 20). The length of channel in this reach was 19.4km. Observed flow data (converted from observed stage data through a rating curve, Figure 3.5) for the DWAF stage plate A6H039 (cross-section 51) at the inflow point of the Nyl River to the study area, were available for the period 25 February 1998 to 9 May Consequently, the 1999/2000 hydrological year was chosen 150

29 for calibration as it had the greatest range in flows within this data set. The rest of this data set could then be used for verification of the model Initial attempts at calibration Calibration at the N1 (A6H039) was first attempted by adjusting the Manning s resistance of the floodplain and channel. The best calibration here was with a channel resistance of approximately 12 and a floodplain resistance of approximately 1.0. These fitted the low flows very well but the high flows had stage peaks much higher than desired, up to 1.5 metres higher than the observed stages for these peaks. When attempts were made to reduce these peaks, the base flows ended up being lower and the shape of the hydrograph was not influenced greatly. GP2, the downstream-most cross-section, relies on a rating curve and so to achieve a good match of observed and modelled stages and flows at this crosssection, the attenuation and travel time of flows had to be adjusted upstream. This was done by mainly adjusting the resistance of the upstream reach, which changes the floodwater velocity and depth. This in turn changes the storage in the reach. Storage is also influenced by impoundments and these were adjusted using ineffective flow areas and weirs. Resistance factors were applied to the resistance values, which varied the resistance of the floodplain according to the flow. This is realistic as a change in resistance with stage (which is related to flow) can be expected due to different vegetation growing at different elevations above the channel. The best results given by these resistance factors, using a constant resistance at each cross-section for channel and floodplain was a modelled stage hydrograph that was too low at the peaks and too high at the base flows, a sort of compromise solution. Unfortunately, even this was not satisfactory, being more than 20cm out for most of the year. It was possible to get the modelled hydrograph to match the peaks of the observed data but this meant that it completely overestimated the base flows. Another facility not used here, is a seasonal flow resistance adjustment table, where factors can be input for each month to account for growth in vegetation at certain times of the year. 151

30 In the Middelfontein reach, the effect of modelling weirs was assessed, with weirs positioned downstream of cross-sections 8 (a culvert for a farm track), 10 (the Deelkraal Dam), 20 (a culvert for a farm track crossing a few metres downstream of A6H002) and 47 (a long dike crossing the floodplain laterally). The inclusion of weirs was useful by improving the stability of the model and allowing an abrupt change in the Manning s resistance upstream and downstream. They raised the stage of base flows at places where there were observed data available, such as A6H002 (Deelkraal Dam) and A6H039 (N1) in the Middelfontein reach. This allowed the use of slightly more realistic resistance values for these crosssections. Large improvements in calibration were noted when weirs were used in conjunction with a change in resistance between channel and floodplain. Weir shapes such as a V notch that was varied in area and height were attempted. Bank stations were also moved into the floodplain, so that the effect of the channel resistance would be greater at higher flows. This was found to work reasonably well, and together with weirs that kept the model stable by regulating low stages, and experimenting with different floodplain and channel resistance combinations, a reasonably acceptable calibration was achieved. The modelled flood peaks in the Middelfontein reach were no greater than 20cm higher than the observed stages and the low flow stages were generally well correlated, being within one or two centimetres of the observed stages Final calibration It was eventually decided to remove all weirs from the model, and ineffective flow areas were defined behind some major levees shown on the contour map in RiverCAD. It was easier to calibrate the model once the ineffective flow areas were defined although they did cause instability when they were not defined as permanent i.e. they switched off when stages exceeded their defined heights. The ineffective flow areas were used in conjunction with moving the bank stations into or out of the floodplain where necessary, and adjusting the resistances along the floodplain. Ineffective flow areas were defined at the Deelkraal Dam to model the dam, and just downstream of the Nyl River and Middelfonteinspruit confluence along a levee that runs to the east and parallel to the channel. This 152

31 ineffective flow area affected stages upstream as far as the N1 (A6H039 crosssection 1) aiding calibration there. During the calibration process, it was discovered that there were observed data available at A6H002 since This data was discovered to be 600mm lower than the observed data set used for this stage plate, which only spanned the years 1998 to Calibration is a time-consuming business of trial and error and this caused more delays. In the end, the model was recalibrated with more realistic values of Manning s n, and far less ineffective flow areas than were required before Manning s resistances in the Middelfontein reach The final Manning s resistances for the Middelfontein reach are given in Table 6.2 and may appear very high for a wetland. This is due to the channel being artificially deeper in the model than it is in reality to account for the survey of the inundated channel (discussed previously), and man-made features such as levees, dikes and dams on the floodplain that are not accounted for completely in the model due to its one-dimensional form. Table 6.2: Manning s resistance values for the floodplain and channel in the Middelfontein reach, from the N1 (cross-section 51) to the Nylsvley Bridge (cross-section 1) Cross-section Stage plate Left overbank Channel Right overbank 51 A6H A6H GP

32 Bank stations were moved carefully to maintain stability, while the Manning s resistances were determined through trial and error. It was found that to achieve and maintain stability, the positions of the bank stations had to be gradually changed cross-section by cross-section, until the desired bank station position was achieved at the desired cross-section. During the calibration process it was found through trial and error that model stability was affected by a resistance less than 0.05, a resistance greater than 20, a large difference in resistance between channel and floodplain and a sudden upstream/downstream change in resistance Discussion of the calibration and verification of the model The calibration and verification of modelled against observed data are shown in Figures 6.11 to 6.13 for the Middelfontein reach. They are discussed together here as they make up one continuous data set from 25 February 1998 to 9 May 2001, representing the full available data set of observed inflows at A6H039 for the Middelfontein reach. The 1999/2000 hydrological year was chosen as the calibration period, as stated previously, and the rest of the data set was used for verification. Calibration and verification of the other reaches is discussed in detail by Birkhead et al (2004). Birkhead et al (2004) define verification as the process of comparing calibrated model predictions with measured data that have not been used in the calibration process, allowing an objective assessment of the predictive accuracy of the model. The Middelfontein reach was verified using the same inputs as for the calibration period: observed flow data at A6H039 (cross-section 51) and observed flow data routed to the floodplain from the DWAF gauges on gauged tributaries and the same hydrologically-modelled flow data for ungauged tributaries. These were compared to observed flow and stage data at stage plates on the floodplain: on the Middelfontein reach, these were A6H039 (cross-section 51), A6H002 (crosssection 20) and GP2 (cross-section 1). 154

33 At low flows on all three calibration cross-sections in the Middelfontein reach, the modelled stages were higher than the observed stages due to the minimum flow requirement for stability of 0.1 m 3 /s Plan: Verification River: Nyl River Reach: Mddlftn-Reserve RS: Legend Stage Obs Stage Obs Flow Stage (m) Flow (m3/s) Flow May Aug Nov Feb May Aug Nov Feb May Aug Nov Feb May Time Figure 6.11: Plot of modelled stage and discharge hydrographs, and measured values at Middelfontein (A6H039 cross-section 51) for the period 26/02/1998 to 09/05/2001 (after Birkhead et al, 2004). The N1 cross-section (A6H039, cross-section 51) was calibrated generally to within 10cm of the observed stage data and generally at worst to within 1 m 3 /s of the observed flow data although most flows were far better replicated throughout the calibration and verification period. Peaks were generally well replicated, an important part of the hydrograph for modelling flood inundation. The long-term wet season recessions were generally well replicated on this cross-section; even in September and October 2000 the difference between modelled and observed stages was never greater than 10cm. 155

34 Plan: Verification River: Nyl River Reach: Mddlftn-Reserve RS: 20 Legend Stage Obs Stage Stage (m) May Aug Nov Feb May Aug Nov Feb May Aug Nov Feb May Time Figure 6.12: Plot of modelled stage hydrographs and measured values at Deelkraal (A6H002 cross-section 20) for the period 26/02/1998 to 09/05/2001 (after Birkhead et al, 2004) The cross section at Deelkraal (A6H002, cross-section 20) (Figure 6.12) was calibrated against observed stage data only, due to the lack of observed flow data here. It was found to be extremely difficult to calibrate this cross-section, possibly due to the extrapolated inflows from the Middelfonteinspruit differing from the actual inflows. For example, the model could not reproduce a dip in observed stage at the end of June 2000; it produced a small peak in the modelled stages instead. Birkhead et al (2004) were surprised that the observed drop in stage levels during mid-winter 2000, by 0.5m, is not reflected at the outflow, although there are no data at GP2 in July for comparison. The model also produced three small floods in the autumn and winter of 1999, the stages of which appear to be overestimated. The long-term wet season recessions were generally well replicated except in May to September 2000 and March to May The amplitudes of dips between the flood peaks were too small in January 1999 and March 2000, although the flood peaks during the 1998/1999 wet season were overestimated. 156

35 Plan: Verification River: Nyl River Reach: Mddlftn-Reserve RS: 1 20 Legend Stage Stage (m) Flow (m3/s) Obs Stage Obs Flow Flow May Aug Nov Feb May Aug Nov Feb May Aug Nov Feb May Time Figure 6.13: Plot of modelled stage and discharge hydrographs, and measured values at the downstream boundary of the Middelfontein reach (GP2 cross-section 1) for the period 26/02/1998 to 09/05/2001 (after Birkhead et al, 2004) The cross-section at the downstream end (GP2, cross-section 1) (Figure 6.13) was calibrated against observed stage and flow data. The calibration at GP2 was reasonable (generally within 20cm of observed stage data and 1 m 3 /s of observed flow data) except for a few stage and flow peaks, which were impossible to match in the model as the inflows required to produce them did not exist. Using measured inflow data at A6H039, extrapolated inflow data for the tributaries (Middelfonteinspruit and De Wet Zyn Loop) and measured outflow data at GP2: in February 2000 the outflow peak was 45m 3 /s, whereas the sum of the peak inflows was only 20m 3 /s - a difference of 25 m 3 /s. This occurred again in March and April At stages below m, when the water is entirely in the channel, the modelled stages were slightly higher than the observed stages, but never by more than 10cm. Stages in the long-term wet season recessions were generally well replicated, being overestimated by no more than 10cm by the model. 157

36 For the calibration and verification period, the range of observed stage fluctuations at Deelkraal was approximately 2.1m, substantially higher than those observed at Middelfontein (0.65m), as the stages at Deelkraal are influenced by the culvert downstream of the Deelkraal gauge, the Deelkraal Dam further downstream (Figure 6.9) and the relatively narrow valley at this point (Figure 6.14). Observed stage fluctuations at GP2 during this period were 1.7m, influenced by the bridge structure and culverts immediately downstream of the gauge plate and reed bed further downstream of these structures. Figure 6.14: Aerial view of the Deelkraal gauge (A6H002) (top right) and the narrow channel and floodplain at this point. (K. Rogers) Errors between modelled and observed flow and stage data at the calibration cross-sections stem from: the rating curves that do not take into account extremely high flows due to the lack of rating data available for these high flows inaccuracies in modelled and routed tributary inflows inaccurate rainfall additions 158