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Chapter 6: Model development

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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 Scotts 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

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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 flow-

gauging 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.

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Figure 6.2: Map of the Nylsvlei floodplain and catchments showing the

positions of all evaporation, rainfall, geohydrological and flow-

gauging stations (after Pitman & Bailey, 2003).

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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 10 000m2 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 models

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 anadditional 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.

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These modelled data series were used in the scenario modelling discussed in

Chapters 7 and 8.

6.3 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 two-

dimensional) 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

(www.bossintl.com) 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.

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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

(www.bossintl.com) 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 flow-

analysis 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

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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

1.0.08 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 www.hec.usace.army.mil.

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

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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 800 000 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 intervalbased 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

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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

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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

werent 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 96 000 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 2003. 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 theTGRD 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

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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 inx andy to a 3D polyline inx,y, andz, 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.

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Tree grove & bird hide

Flow

Nyl River

Dykes

Gauge A6H037

Vogelfontein Road

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)

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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 thezdimension determined by the

draped line on the TIN, to a 3D polyline with thezdimension 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 cross-

section 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 cross-

section 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 Mannings resistances of the channel were

adjusted.

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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

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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-sectionsat 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

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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)

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(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 road-

crossing 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.

Mannings resistances can also be defined for each of these individual

flow lengths. Bank stations define the boundary between the left overbank,

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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 Mannings

resistance at these two cross-sections on each reach. A Mannings

resistance of 12 in the channel and 2 on the floodplain at the N1 (A6H039)

and Mannings 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 (0.00098, 0.00052 and

0.000654 for the upper, Reserve and lower study areas, respectively) and is likely

to exceed lateral water surface slopes under most flow conditions. Figure 6.8

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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 thefloodplain 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),

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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 m3/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 m3/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 3.1.1 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 m3/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 0.03m3/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 cross-

sections 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.

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Rainfall, evapotranspiration and ponding and infiltration losses were converted to

average daily flows in m3/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 (head-

flow 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 cross-

sections 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.

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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 cross-

section 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.

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For flows less than or equal to 0.1m3/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).

0

2

4

6

8

10

12

14

16

0 5 10 15 20 25

Flow (m3/s)

Inundatedarea(km

2)

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 R2 of

0.966. The regression equation for the Middelfontein reach is given below:

A = 0.0033I3 - 0.1463I2 + 2.3162I - 0.2165 (0 < I

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whereA is the surface area of inundated floodplain (km2), andIis the inflow from

the Nyl River (m3/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 = 2.513I0.564 - 0.684 (0

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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 0590307 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 - 1995/1996 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,

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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 m3/s passed out of the floodplain yet the maximum combined peak

inflow was only 20 m3/s. This situation occurred again in March and April

of 2000.

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 (I0) were

between 3.3 x 106 and 10.7 x 106 m3, significantly higher than losses to

evapotranspiration which ranged from 0.8 x 106 to 2.8 x 106 m3. 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.

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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 formy = axb + c was derived where

infiltration and ponding losses could be found on an annual cumulative basis,

from annual cumulative inundation area (equation 6.5).

Lt= 0.472(At)0.453 (6.5)

where Lt is the cumulative loss (m3), and Atis the cumulative surface

inundation area (km2) for the hydrological year, and tis 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).

Lt= (Lt- Lt-1) (6.6)

whereLtis the daily loss (m3) due to infiltration and ponding, and tis time (days)

(Birkhead et al, 2004).

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Table 6.1: Water balance for the floodplain from Middelfontein to the

Nylsvley Reserve (after Birkhead et al, 2004)

Cumulative

inundated area,A

(km2)

Inflows,I(106 m3) Outflows, O

(10

6

m

3

)

Balance (106 m3)Hydrological

year

HEC-

RAS

Equation

6.1

Nyl

River

Middelfonteinspruit De

Wet

Zyn

Loop

Rainfall Nyl

River

ET I -

O

Loss

Equation

6.6

1998/1999* 230 13.4 2.7 1.6 0.7 18.7 1.0 -1.3 5.5

1999/2000* 1093 1116 70.4 11.4 6.3 3.0 98.0 2.9 -9.8 11.3

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 theVogelfontein 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 6.13.

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 2001. Consequently, the 1999/2000 hydrological year was chosen

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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.

6.9.1 Initial attempts at calibration

Calibration at the N1 (A6H039) was first attempted by adjusting the Mannings

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 cross-

section, 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.

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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 Mannings 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 cross-

sections. 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.

6.9.2 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

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ineffective flow area affected stages upstream as far as the N1 (A6H039 cross-

section 1) aiding calibration there.

During the calibration process, it was discovered that there were observed data

available at A6H002 since 1922. 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 2001. 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 Mannings n, and far less ineffective flow areas than were required

before.

6.9.3 Mannings resistances in the Middelfontein reach

The final Mannings 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: Mannings 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 A6H002 0.05 12 0.05

50 0.09 1 0.09

49 0.1 0.7 0.1

35 - 48 0.5 0.5 0.5

22 - 34 0.1 1 0.1

21 0.1 1.7 0.1

20 A6H002 0.1 1.7 0.1

19 0.1 1.7 0.1

16 - 18 0.1 1 0.1

15 0.1 0.7 0.1

2 - 14 0.1 0.1 0.1

1 GP2 0.1 0.1 0.1

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Bank stations were moved carefully to maintain stability, while the Mannings

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.

6.10 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 (cross-

section 20) and GP2 (cross-section 1).

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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 m3/s.

May Aug Nov Feb May Aug Nov Feb May Aug Nov Feb May1998 1999 2000 2001

1109.5

1109.6

1109.7

1109.8

1109.9

1110.0

1110.1

1110.2

0

5

10

15

20

25Plan: Verification River: Nyl River Reach: Mddlftn-Reserve RS: 51

Time

Stage(m)

Flow

(m3/s)

Legend

Stage

Obs Stage

Obs Flow

Flow

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 m3/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.

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1095.5

1096.0

1096.5

1097.0

1097.5

1098.0

1098.5Plan: Verification River: Nyl River Reach: Mddlftn-Reserve RS: 20

Time

Stage(m)

Legend

Stage

Obs Stage

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 crosssection 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 2001. 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.

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1090.2

1090.4

1090.6

1090.8

1091.0

1091.2

1091.4

1091.6

1091.8

0

5

10

15

20Plan: Verification River: Nyl River Reach: Mddlftn-Reserve RS: 1

Time

Stage(m)

Flow

(m3/s)

Legend

Stage

Obs Stage

Obs Flow

Flow


measured values at the downstream boundary of the

Middelfontein reach (GP2 cross-section 1) for the period


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 m3/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 45m3/s, whereas the sum of the peak

inflows was only 20m3

/s - a difference of 25 m3

/s. This occurred again in March

and April 2000. At stages below 1090.8m, 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.

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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

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inaccurate evapotranspiration, infiltration and ponding losses

inaccurate cross-sections cut in RiverCAD which do not always lie

perpendicular to the flow and thus present a different modelled cross-

section to reality

inaccurate representation of reach storage

6.11 Application of the model

The model was applied for the project, in a run from 1 October 1973 to 1 May

2001, using as inputs patched daily-observed flow gauge data from the DWAF

gauges in the catchments extrapolated to the floodplain margin, and modelled data

for ungauged catchments. The DWAF gauges in the catchments whose flow data

were extrapolated to the upstream end of the Middelfontein reach (A6H039) were

A6H006, A6H011, A6H018, A6H012 and A6H019 (Figure 1.3 and 6.2). This

means that this application run was also another verification run as the input data

were not strictly modelled hydrology data. Outflows from a reach were used as

inflows for the next reach downstream to create a model for the entire study area.

Observed data were only available at A6H039 after 1998 (Figure 6.15). The

highest stage recorded during the modelling period was 1110.473 in February

1976. Observed and modelled stage data were generally within 20cm, although

modelled stages overestimated observations at lower flows and the long-term wet

season recessions were also overestimated. This was due to the enforced

minimum flow of 0.1 m3/s for model stability and errors in the hydrological

modelled inflows.

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160

Mar Sep Mar Sep Mar Sep Mar Sep Mar 1997 1998 1999 2000 2001

1109.4

1109.6

1109.8

1110.0

1110.2

0

10

20

30

40

50Plan: Application River: Nyl River Reach: Mddlftn-Reserve RS: 51

Time

Stage(m)

Flow

(m3/s)

Legend

Stage

Obs Stage

Obs Flow

Flow


measured values at Middelfontein (A6H039) for the period


Apr Oct Apr Oct Apr Oct Apr Oct Apr Oct Apr1974 1975 1976 1977 1978 1979

1095.5

1096.0

1096.5

1097.0

1097.5

1098.0

1098.5Plan: Application River: Nyl River Reach: Mddlftn-Reserve RS: 20

Time

Stage(m)

Legend

Stage

Obs Stage


Deelkraal (A6H002) for the period 1973 to 1979 (after

Birkhead et al, 2004)

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161

1980 1981 1982 1983 1984 1985 19861095.5

1096.0

1096.5

1097.0

1097.5

1098.0


Time

Stage(m)

Legend

Stage

Obs Stage




1986 1987 1988 1989 1990 1991 19921095.5

1096.0

1096.5

1097.0

1097.5


Time

Stage(m)

Legend

Stage

Obs Stage




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162

Jan Jul Jan Jul Jan Jul Jan Jul Jan1997 1998 1999 2000 2001

1095.5

1096.0

1096.5

1097.0

1097.5

1098.0


Time

Stage(m)

Legend

Stage

Obs Stage


Deelkraal (A6H002) for the period 10/1997 to 04/2001 (after


Stages had been recorded at A6H002 (Deelkraal) since 1922, so apart from a few

gaps in observed data a comparison could be made for most of the modelled

period. The application results are shown in Figures 6.16 to 6.19. Large gaps in

the observed data occurred during 1986 and from 1992 to 1997. From 1973 to

1979, there was excellent correlation with the observed data, the modelled stages

generally being within 20cm and no more than 50cm from observed stages.

Agreement was also good from 1980 to 1986, generally better than 50cm in stage,

although some of the peak levels were not reflected in the observed record. From

1986 to 1992, the modelled stages were generally overestimated by half a metre

and up to 0.7m for 1990, but the maximum water levels were well replicated. The

shapes of the observed and modelled hydrographs were similar however.

Modelled stage levels from 1997 to 2001 overestimated measured stages by up to

50cm, but the peak levels were generally well replicated.

The stage levels given by the Deelkraal stage plate may not always be accurate.

The datum used to convert recordings to a common datum (m amsl) was from a

survey of the existing gauge plate, although there is a possibility that the stage

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163

plate has moved during its history and not been resurveyed. Birkhead et al(2004)

comment that the accuracy of this datum for the historic levels is uncertain, and

the absolute accuracy of these data cannot be assumed. Taking the uncertainty in

the gauge datum into account, the predicted and historic water levels agree well,

except for the period from the late eighties to the early nineties.

At GP2 (Figure 6.20), the modelled stages compared well with the observed

stages, except in 1996 during the wet season recession between April and October

where the modelled stages were overestimated by about 20cm to 25cm. A large

peak in stage during February 2000 was underestimated possibly due to errors in

the modelled inflows. The modelled peak in December 1996 was not confirmed

by observed data as the CWE employee who collected the data was on holiday.

Modelled flows generally compared well with the few observed flows.

Jan Jul Jan Jul Jan Jul Jan Jul Jan Jul Jan

1996 1997 1998 1999 2000 2001

1090.0

1090.5

1091.0

1091.5

1092.0

1092.5

0

20

40

60

80

100Plan: Application River: Nyl River Reach: Mddlftn-Reserve RS: 1

Time

Stage(m)

Flow

(m3/s)

Legend

Stage

Obs Stage

Obs Flow

Flow


measured values at GP2 in the Nylsvley Reserve for the period

01/1996 to 04/2001 (Birkhead et al, 2004)

Reasons for the model over-predicting stages and flows, especially during the wet

season recessions, are that the extrapolated gauge hydrology did not consider

potential losses in the intervening stream sections between the gauges and the

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164

floodplain. The Nylsvlei floodplain extends upstream of the N1 crossing at

Middelfontein, almost as far as Nylstroom and losses can be expected to occur

along this section too. Birkhead (Birkhead et al, 2004) compared the discharge

hydrographs at GP2 using three sources of flow data, from measured stages and

the rating function at GP2, from measured stage and the rating function at

Middelfontein together with extrapolated tributary inflows routed to GP2 and

from extrapolated flows from the catchments throughout. This is shown in Figure

6.21 and clearly shows the influence of losses, especially in the wet season

recession.

1996 1997 1998 1999 2000 20010

1

2

3

4

5

Figure 6.21: Discharge hydrographs at GP2 derived from (i) measured

stages and rating function (), (ii) hydraulic routing through

the upstream wetland using (a) measured flows at

Middelfontein and extrapolated tributary flows () and (b)

extrapolated flows throughout () (after Birkhead et al, 2004)

6.12 Summary

A hydrological rainfall-runoff model was developed by Stewart Scott Consulting

Engineers for the Nylsvlei floodplain catchments (using their programs

DAYFLOW and WRSM2000), which provided flows at the floodplain boundary

for different scenarios. The hydraulic model was set up using the commercial

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software programs Quicksurf, RiverCAD and HEC-RAS. Quicksurf was used to

create a 20cm contour interval topographical map of the floodplain using the

LiDAR survey data. RiverCAD was used as a pre and post processor program, to

cut cross-sections required for hydraulic modelling and for floodplain mapping of

inundation areas and extents using the 20cm contour map. A hydraulic model was

developed using HEC-RAS and was calibrated and verified using measured flows

at the inflow point to each reach, against observed flow and stage data. The model

was then applied to extrapolated flows from gauges in the catchments and

modelled flows from ungauged catchments, for the period 1973 to 2001. This

gave generally satisfactory simulations of stage and flow compared to observed

data. The next chapter is about the development of various catchment scenarios,

so that their effect on floodplain inundation using the model could be predicted.

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