Importance of fire flows to calibrate water distribution models

Over the years, I have found several engineering projects and journal articles in the topic of modeling water distribution networks. One common mistake that I found in most of them is that they "calibrate" the model (pipe roughness) considering only normal flow conditions instead of high demand conditions such as fire flow tests. Actually, it is not possible to calibrate a model without considering high demand conditions. 

There are several water distribution models such as EPANET, InfoWater, WaterGEMS, Mike Urban and others. It is important to remember that water distribution models are based on physical processes and they simulate the network by solving a matrix system based on:

  • Conservation of mass in every node
  • Conservation of energy in every pipe
In the conservation of mass we have 3 variables:

  • Flow. This is a known value. Is a boundary condition.
  • Area. This value is calculated based on pipe size (known value)
  • Velocity. This is a function of flow (known value) and pipe size (known value)

In the conservation of energy we have 4 variables:

  • Pressure. This is the value to be calculated
  • Velocity. This is a function of flow (known value) and pipe size (known value)
  • Elevation. This is a known value
  • Head losses. This is a calculated based on the Hazen-WIlliams equation, which is a function of flow (known value), pipe size (known value) and pipe roughness (to be calibrated)
Thus, we have 2 unknown values: pressure and pipe roughness. By assuming a proper pipe roughness we can calculate the pressure. This process of assuming the proper roughness is the calibration of the model. 

Head losses are calculated based on the Hazen Williams equation. Hazen Williams equation relates the friction head loss as power function of the flow. Thus, it becomes more sensitive to higher flows (you can solve the Hazen-Williams equation online). Let’s show one simple example.

Let’s assume a 1 km pipe reach of a 250 mm pipe, and considering different roughness values from 130 (new pipe) to 70 (pipe in a very bad condition). The head loss can be calculated online with this tool. Let’s find the pressure drop for different flows between 1500 cmd and 5450 cmd. 1500 cdm and 5450 cdm were the considered flows because:

  • Assuming a 300 l/hab day, 1500 cmd would be enough to supply water to a 5000 habitants zone
  • 5450 cmd is equivalent to a standard fire demand (1000 gpm)

As we can see, considering a 1500 cmd water flow would led to accept a wide range of roughness values. We could assume any roughness value between 70 to 130, and pressure differences would be 1.3 m (about 1.9 psi). On the other hand, those roughness values (between 70 to 130) with fire flow demand produces a 14.5 m pressure difference (about 20.5 psi). Thus, high flows such as fire flow really show the sensitivity of the pipe to roughness. 

Suggestions to calibrate water distribution models
My suggestions for calibrating water distribution models are:

  • Use normal conditions data to verify connectivity issues only. Do not use it to verify roughness. 
  • If you want to calibrate the model, then perform fire flow tests or collect data during high demand equivalent or greater than 1000 gpm.
  • If is not possible to collect high flow data, do not say that your model is calibrated (because it is not). In this case perform a sensitivity analysis.

Hidroituango dam fail emergency

A dam fail does not necessarily mean a total collapse of the dam. A dam fail refers to any unexpected or uncontrolled water flow. Therefore, the recent emergency at the Hidroituango dam in Colombia could be referred as a dam fail.

Last month Colombia faced one of its worse dam fails in history in the Hidroituango hydropower dam construction. Hidroituango hydropower dam is supposed to be the most important hydropower project in Colombia. With a 220 m high dam and 8 turbines it will have an installed capacity of 2 400 MW. Last month, some landslides locked some water detour tunnels, thus creating an unexpected fill and unexpected water flows. In order to safe the dam, it was necessary to sacrifice the machines room by using it as an emergency spillway.

In this post we present a time frame summary of this event. 
  • April 28th. Water detour tunnel gets locked due to internal landslide
  • April 30th. Water naturally unlocks the tunnel
  • May 1st. Another water detour tunnel gets locked due to internal landslide. Water begins to accumulate and to fill the reservoir
  • May 4th. Water fills about 50% of reservoir capacity.
  • May 10th. It is decided to use the machines room as bypass. Machines room gets flooded.
  • May 12th. River flow downstream increases. Some towns are flooded and some bridges collapse
  • May 16th. Emergency is declared. Several towns and thousands of people are evacuated. One filtration is reported; there is possibility for a dam break. Emergency works continue.
  • May 19th. Dam works reach level 405 masl (target level to use the cofferdam is 410 masl). Although there is hope for reaching the target, rains are forecasted.
The video and the infographic shows a time frame of this event
Infographic of Hidroituango dam crisis 2018


New HEC-RAS v 5.0.4


A new version of HEC-RAS was released; HEC-RAS 5.0.4. The first question to HEC-RAS user's is What are the main improvements of this version?
Actually, there are several improvements. Moreover, considering the software versioning standards, I think it would have been better to call it version 5.1. I will not go into the detail of all the improvements (the release notes is a 19 pages document), but I will summarize the most important ones.

       Computational speed. Computational speed is crucial in selecting a 2D model. I remember my first experience with HEC-RAS 5 beta took several days to perform a simulation; that same simulation took just about 2 hours using other models. Fortunately, HEC-RAS has been improving its computational speed. This new version has a fully parallelized engine that doubles the computational speed. If your previous simulation required X hours, with this new version it will only require 0.5 X hours.
       Ras Mapper tools. This one is a major improvement. Previous version still required ArcGIS and GeoRAS for preparing geometric data, especially for 1D cross sections and 1D profiles. This new version includes full GIS geometric processing capabilities. This video shows the creation of a 1D river geometry with the new Ras Mapper.
       2D nested mesh. Previous version performed 2D simulations on a nearly regular non staggered grid. That means the 2D DX was the same for all the grid. The new version allows to refine the grid at specific locations. Hence, a coarse grid can be used for big floodplains, while a more refined grid can be used for particular areas requiring more detail.
       More sediment options. New linear scaling factors and granulometry options are available
       64 bit processor. Most users may not be deep into computer science and may neglect the importance of this improvement. Let me tell you that this is an important improvement with BIG benefits. It allows working with bigger data files and faster processing. You will easily realize this benefits when working with the 2D; you will see how the mouse movements and the clicks are faster and your work is more comfortable.

Image 1. Print screen from the video showing 1D creation with the new RasMapper

Nevertheless, there is one disadvantage that you have to consider before using this new version. Although this 5.0.4 version is compatible with previous versions, previous version are not compatible with models saved under 5.0.4 version.

As I you can see, this new version is not limited just to fixing bugs. It has important add-ons and improvements. Therefore, considering the software versioning standards, I consider that it could have been  more appropriate to call it version 5.1.