Innovyze

Using InfoNet to build InfoWorks CS hydraulic models

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Courtesy of Innovyze

Water utilities are now using MWH Soft’s InfoNet database and network management solution to monitor data, which has in turn enabled digital models of these networks to be created in a more efficient way.

Many countries are still developing modeling standards, and management tools are either basic or non-existent, so these challenges have to be faced when building models to ensure they are as accurate as possible.

The advantages of using InfoNet to build digital models, compared to the traditional option of importing data directly into InfoWorks CS, are being demonstrated in a project undertaken for the town of Drogheda in Ireland.

Drogheda is a town with 35,000 inhabitants, 35 miles north of Dublin on the east coast of Ireland. The river Boyne divides the town, so it has two essentially independent sewerage networks, north and south, which drain into a common pumping station. From there, flows are pumped to the wastewater treatment works to be treated.

As large developments were anticipated in some areas of the town, Drogheda Borough Council, assisted by Tobin Consulting Engineering, decided to define a master plan for the area that would enable the town to be developed without exacerbating the existing issues or creating further problems.

HR Wallingford (HRW) is working as a sub-consultant to Tobin to develop a model of the drainage systems. The work includes model build and verification activities, the assessment of existing and future system deficiencies, the development of improvement proposals and contributing to Tobin´s overall reporting. In addition, HRW is identifying the requirements for a short-term flow survey and is assessing the suitability of the flow data collected for use in model. Work started in the southern network and subsequently will carry on in the northern one.

Why InfoNet?

HR Wallingford used InfoNet to aid its modeling for the first time on this project because it was capable of importing data from a software solution called SUS25, which is commonly used in Ireland as a data collection tool for assets. SUS25 is a very simple software tool that writes a very long and complex text file that calls different libraries.

Initially, it was thought data from SUS25 could be directly exported into InfoWorks CS, but HR Wallingford’s preliminary testing revealed that the outcome was unsatisfactory as some data was lost, other data was not imported properly and therefore some tedious and repetitive adjustments were needed. The process was also not satisfactory because survey data would need to be imported several times (due to the northern and southern networks being surveyed independently and due to regular updates happening in the data). In addition, the fact that the exporting process was done without any direct control from HRW’s modellers was also perceived as a drawback. For optimal modeling, the company decided it required full access to the data without this preliminary screening, and looked for a way to import the data automatically.

The company was aware that many of Ireland’s local authorities used an early asset management solution called MapDrain, which converts SUS25 text files into MapInfo tables and Access databases.

MWH Soft had developed a methodology to convert MapDrain data into InfoNet some years previously, so HR Wallingford decided to utilize this combination of solutions to facilitate the automated data transfer from SUS25 that it required. It was found that files could be imported quickly and efficiently into InfoNet, allowing the data to be converted into InfoWorks CS to enable the modeling work to continue.

Drogheda case study

The original methodology was created for an early version of InfoNet (v.3.0). The current version at the time of this project was 10.0 and between both versions there had been significant changes in the structure and type of data stored. Consequently, HR Wallingford updated the importing process to make it more compatible with InfoNet10.0. For instance, in the previous methodology only the pipe diameter of the upstream manhole survey was used. However, as the consultancy wanted to utilize all of the available data, especially to fill gaps in the data in a sensible way, it modified the methodology to take advantage of the improvements in InfoNet version 10.0, which allows both upstream and downstream manhole survey values to be stored.

The only issue that the modelers encountered was in defining bends in pipes. In MapDrain, bend data is stored in a separate table, and if a pipe has several bends each one will have separate coordinates. To resolve this, the data required from this table was exported manually to Excel and an SQL query was used to create a .csv file that could be imported into InfoNet.

Advantages of InfoNet

InfoNet provided the useful ability to check discrepancies such as differing upstream and downstream pipe shape and size. Such errors are automatically identified by the solution through a simple query before the data is imported into InfoWorks.

InfoNet can also infer missing values – for instance, where it has not been possible to survey an asset. Traditionally, this would have resulted in the creation of a pipe with no values within the model. Another example would be pipes that have no upstream manhole survey data. These can be selected and a simple query will assign them their own downstream survey manhole data as pipe shape, pipe size and so on. Inferring data in InfoNet is more accurate than doing so in InfoWorks simply because there is more redundant information available.

Handling CCTV survey data

InfoNet also considerably improved the usage of CCTV survey data, which has always been theoretically useful but has been difficult to access and view in practice. One of the advantages is the visual improvement that GIS display of the CCTV survey data brings. It is also possible in InfoNet to automatically infer missing data in the network by cross-checking the CCTV and the asset survey data. This enables discrepancies or missing data across the entire network to be identified. The check is undertaken simply by creating a validation rule, which provides a list of all locations where the two datasets differ. Pipes can be sorted in various ways by creating queries to identify the required characteristics (such as material, diameter and shape). It is also possible to export the data into Excel and automatically identify discrepancies using VLookup.

InfoNet also enhances the way in which defect data from CCTV survey can be accessed. Finding survey defects by comparing hard copy data is a laborious process, but using InfoNet they can be identified quickly and easily. The main issue when handling survey defects is that initially it is not possible to determine how many defects there will be for each individual pipe. That makes this type of data more difficult to handle than, for example, typical pipe size data, where there will always be a maximum of two values (pipe size from the upstream and downstream manhole survey). For this reason, this kind of data is very difficult to manage and export, but with InfoNet it can be geographically displayed and even used to select pipes (for instance, to select all the pipes that have infiltration problems).

This is particularly useful when determining the network’s connectivity in relation to lateral pipes (pipes that connect into bigger conduits without manholes). These connexion points will be missed by the asset survey but should be identified in the CCTV survey. In this way it is possible to estimate the location of the connection point, also checking if the connection location is valid by comparing key data such as pipe diameters extracted from both the CCTV and asset survey. InfoNet can also be used to check across the whole network to determine whether asset survey discrepancies such as differing upstream and downstream pipe shape and size are genuine changes in diameter, as this should be included as a CCTV survey defect.

Conclusion

From the project perspective, the ease with which databases could be modified to enable import into InfoNet proved extremely valuable, especially because of the number of times that this importing exercise had to be undertaken (for two different catchments plus subsequent updates for each catchment).

InfoNet enables survey data loss to be minimized – traditionally, much data is lost without modelers realizing, or if they do realize, they are unable to rectify the situation. InfoNet improves the way in which data is assessed and assumed, simply because there is more information available than that which is strictly necessary to run a hydraulic model. InfoNet also enhances the way in which CCTV survey data is used.This depth of detail is invaluable in building and calibrating the model. HR Wallingford is now recommending the use of MWH Soft’s InfoNet on every modeling project. It is hoped that in future InfoNet will become even more model-build oriented.

This article is based on an original presentation by Juan Gutierrez Andres of HR Wallingford and Idris Nujjoo of MWH Soft to the MWH Soft User Conference in September 2009.

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