Author Archives: tonyladson

About tonyladson

I work as a hydrologist. I'm a director of a specialist consulting company, Moroka Pty Ltd and have teaching and research appointments at Monash University, the University of Melbourne and Victorian University

Assessing the impact of blockage as part of flood modelling

Australian Rainfall and Runoff 2016 provides guidance on assessing the impact of blockage of culverts and bridges as part of flood modelling. Details are in Book 6 Chapter 6.

The need to assess blockage represents a change to hydraulic modelling practice.  In the past, industry-wide guidance was lacking and the effect of blockage was often not considered.    The new guidelines provide a standard procedure but, as yet, there is limited experience in their application.  Part of the process is to complete a blockage assessment form which is linked from ARR.  Unfortunately the link no longer works but the form is on the internet here.

The guidelines are being incorporated into hydraulic modelling software with a recent paper outlining the procedures that have been included in TUFLOW and an assessment of how they have performed in three case studies of recent flood modelling projects (Ollett, et al., 2017).

It is likely that future flood modelling briefs will require assessment of blockage so flood consultants will need to learn about, and be able to apply, the procedures and explain the significance of results to clients.  Some resources are listed blow.

Large floating debris collection.

Large floating debris collection. Chalmers St Wollongong after the Aug 1998 flood (Forbes, Rigby 1999) (Source: ARR Project 11 Stage 1 report, p. 14)


Blockage Assessment Form

References – articles

Ollett, P., Syme, B. and Ryan, P. (2017) Australian Rainfall and Runoff guidance on blockage of hydraulic structures: numerical implementation and three case studies.  Journal of Hydrology (NZ) 56(2) 109-122. (link)

Ollett, P. and Syme, B. (2016) ARR blockage: numerical implementation and three case studies.  37th Hydrology and Water Resources Symposium 2016: Water, Infrastructure and the Environment. Queenstown, NZ. pp. 346-359 (link)

Ribgy, E. and Weeks, W. (2015) Evolving an Australian design procedure for structure blockages.  36th Hydrology and Water Resources Symposium: The art and science of water. Hobart, Tas. pp. 154-161. (link)

Suitability of ARR guidelines as an alternative blockage policy for Wollongong. 36th Hydrology and Water Resources Symposium: The art and science of water. Hobart, Tas. pp. 370-377. (link)

References – ARR2016 project reports

Project 11 Draft Blockage Guidelines (2015)

Project 11 (Blockage of Hydraulic Structures) Stage 2 Report (2013) (link at

Project 11 (Blockage of Hydraulic Structures) Stage 1 Report (2009) link at

TQmean, a measure of the impact of urbanisation on flow

Urban development has a profound impact on flow and hydrologic indicators have been proposed to highlight the changes as suburbs spread over a catchment, increasing impermeable area.  A commonly used measure of impact is TQmean– the proportion of time that flow in each year is greater than mean flow for that year.  This decreases with urbanisation, and has been shown to be linked to ecological condition of a stream (Booth et al., 2004).
As an example, consider two neighbouring streams in eastern Melbourne: Brushy Creek which flows through the suburb of Croydon, with a catchment that is 28% impervious, and Olinda Creek with a catchment that is mainly forested and which is 5% impervious.
Often, the value of TQmean is calculated and then averaged for several years. Using this approach, The TQmean for Brushy Creek, is 0.21, with the less urbanised Olinda Creek, having a value of 0.37 (for the period 1988 to 2016). Using the relationships in Booth et al. (2004) this suggests Olinda Creek would be predicted to have ‘good’ biological condition, while Brushy Creek would be predicted to be ‘very poor’.

Calculating a single value of TQmean is instructive but the temporal distribution of the time of the year when flows exceed the mean is also altered by urbanisation. Using TQmean as the metric, urbanisation results in high flows occurring more often, but for shorter periods, that are dispersed throughout the year. Comparing the plots of Olinda Creek and Brushy Creek in  (figure), higher flows (flows above the mean), are clustered in the winter (June to August) for Olinda Creek. There is more winter runoff because the Olinda Creek catchment wets up owing to the higher rainfall, and reduced evaporation that occur seasonally in this area. For Brushy Creek, with the same climate, short bursts of high flow occur throughout the whole year. This can be attributed to runoff from impervious surfaces which will occur anytime there is rain.



Figure 1:  Periods of flow above and below the mean flow for (A) Olinda Ck and (B) Brushy Ck

A key issue revealed by this analysis is the changed seasonality of high flow which is a result of urbanisation. This is just one of the many changes in flow regime caused by urbanisation that leads to poor stream condition (Burns et al. 2014).

Code to plot these graphs is available as a gist.


Graphing a long flow series

A long series of flows can be challenging to show graphically without squeezing the data so much that all the useful information is lost (Figure 1).  Two approaches are shown here.  First, a ‘cut-and-stack’ plot, which takes a long graph and cuts it into segments equal to the width of a page.  These segments are stacked on top of each other, stretching out the x-axis (Figure 2).  The figure shows the flows for each decade of the ~ 50 years of data for the Broken River at Caseys Weir (Gauge 404216).

An alternative is a trellis or facet plot (Figure 3).  Here, the flow in each year is plotted as a separate graph.  If the y-axis scale is held constant across all years, the overall temporal variation is highlighted and the very dry years stand out (for example 2006-2009).

If the scales are varied for each year the seasonal flow patterns are emphasised (Figure 4).  The transfers from upstreams dams standout with the rectangular hydrographs in 1977, 1982, 1983 and the summer of 1983-84.


Figure 1: Broken River at Caseys Weir (404216) 31 March 1972 to 19 April 2017


Figure 2: Cut-and-stack plot of the mean daily flow for the Broken River at Caseys Weir (flow data is the same as shown in Figure 1)


Figure 3: Facet plot of the mean daily flow for the Broken River at Caseys Weir.  Flow data is the same as shown in Figure 1; y-axis scaling is held contant


Figure 4: Same as Figure 3 except that y-axis scaling varies between years


Figure 5: Broken River at Caseys Weir (20 Mar 2017)

Data for gauge 404216 was obtained from the Victorian Water Measurement Information System (WMIS).

R code to produce the graphs in this blog is available as gists (here for the cut-and-stack plot; and here for the facet plots).

Better line graphs for hydrologic data

Line graphs are commonly used for comparisons of hydrologic data but they can become difficult to interpret if there are too many lines; the derogatory term is spaghetti graphs.  In my work reviewing flood studies I’ve seen some spaghetti.

The example below highlights common issues with these types of figures. It is difficult to unambiguously determine how the lines relate to the legend because the colours are not distinct and the lines overlap. Also, in this case the x-axis scaling is not meaningful.  The same distance on the graph represents different time periods: 3 hours between the first 2 tick marks (9 to 12) and 24 hours between the final 2 tick marks (48 to 72).

Line graph-1

Figure 1: Line graph – spaghetti version

An improved version is shown in Figure 2. Colours are distinct, lines are labelled directly, (rather than using a legend), the x-axis scaling is consistent, using a thousands separator makes it easier to read the y-axis values. Both ends of a line can be labelled where this contributes to clarity. A grey background can help make it easier to see the data and allows the use of unintrusive pale gridlines.

Ling graph-2

Figure 2: Line graph – improved version

Some may prefer the minimalist version shown in Figure 3.  This attempts to maximise the information to ink ratio by reducing “chart junk” – those parts of a chart that don’t contribute to understanding (Tufte, 1983).

Line graph-4

Figure 3: Line graph – minimalist version

Code to reproduce these figures is available as a gist.



Cleveland, W. S. (1993) Visualizing Data.  Hobart Press.

Tufte, E. R. (1983) The visual display of quantitative information.  Graphics Press.  Cheshire, CT, USA.

Better flood frequency plots from Flike – II

I’ve previously written about improving the flood frequency plots from Flike.   This is an update to that earlier post.

Using Flike version 5.0.300.0 I’ve fitted a Log Pearson III distribution to the annual series for the Tyers River at Browns (226007) using data from 1963 to 2007.  The graph produced by Flike is shown in Figure 1.  This graph is fine to show the quality of the fit but it would be nice to polish it for incorporation into a report.  A csv file of the flow data input to Flike is is available here; the Flike .fld file is here.


Figure 1: Flike plot – flood frequency curve for the Tyers River at Browns (226007) (1963-2007).  Log Pearson III probability model

The data used to create the plot can be downloaded into a csv file by clicking the ‘Save’ button below the plot (the file associated with this graph is available here).  There are three parts to the resulting file:

  1. the data points – deviates and gauged values
  2. points specifying the expected parameter quantiles and confidence limits
  3. points specifying the expected probability quantiles.

These can be read into Excel, or a graphics program, and plotted.   An example is shown in Figure 2.

A key enhancement in this figure, compared to the standard Flike plot, is that the y-axis tick marks are labelled with the flow values rather than logs. The log transformation has been retained, just the labelling has been changed. The x-axis tick mark labels are similar. The deviate values are plotted but are labelled using the ‘1 in Y’ format.

Although it takes some time to construct and label a plot, much of the work can be repeatedly re-used in future reports. If you are doing a lot of flood frequency analysis, its worth setting up a template.


I’ve used the ggplot2 package in R to produce this plot.  Details are available via this gist.

Red Books

I wrote a previous post about the on-line availability of the ‘Blue Books’, a key resource for Victorian Hydrologists which contain stream gauge information to 1987.   Now the ‘Red Books’ are also available, which include stream gauge information to 1982.  There are some additional gauges in the Red Books so its good to check both sources if you are looking for stream data.

The four volumes can be accessed via these links:

Red Books

Australian Rainfall and Runoff Workshops

A brief post to highlight the three ARR2016 workshops coming up in Melbourne:

As I learn things about ARR2016 I’m adding pages here.