DAA/ Bentley WaterGEMS V8i User’s Guide Technical Information Resources Glossary Bentley WaterGEMS V8i User’s Guide 1-i WaterGEMS. distribution network model created in Bentley WaterGEMS and performing a hydraulic transient entered manually to complete the layout. You may need to. WaterGEMS® is a hydraulic and water quality modeling solution for water distribution systems potential manual-input mistakes. BENTLEY WATERGEMS.

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To realize the full potential of the model as a master planning watergemz decision support tool, you must accurately allocate demands while anticipating future demands. You must collect the necessary data and translate it to model loading data regularly to account for changes to the network conditions. Due to the difficulties associated with manually loading the model, you can use automated techniques developed to assist with this task. Spatial allocation of demands is the most common approach to loading a water distribution model.

The spatial analysis capabilities of GIS make these applications a logical tool for the automation of the demand allocation process. LoadBuilder facilitates the tasks of demand allocation and projection. Every step of the loading process is enhanced from the initial gathering and analysis of data from disparate sources and formats to the employment of various allocation strategies. The following are descriptions of the types of allocation strategies that you can apply using LoadBuilder. Allocation Allocation uses the spatial analysis capabilities of GIS to assign geocoded possessing coordinate data based on physical location, such as an x,y coordinate customer meters to the nearest demand node or pipe.

Assigning metered demands to nodes is a point-to-point demand allocation technique, meaning that known point demands customer meters are assigned to network demand points demand nodes. Assigning metered demands to pipes also is a point-to-point assignment technique, because you still must assign demands to node elements, but an additional step is involved. When using the nearest pipe meter assignment strategy, the demands at a meter are assigned to the nearest pipe.

From the pipe, the demand then is distributed to the nodes at the ends of the pipe by using a distribution strategy. Meter assignment is the simplest technique in terms mznual required data because manuql don’t need to apply service polygons figure 1. An example of meter assignment. Meter assignment can prove less accurate than the more complex allocation strategies because the nearest node is determined by straight-line proximity between the demand node and the consumption meter.

Productivity Corner: Using Bentley WaterGEMS with GIS Data for Water Demand Allocation | Cadalyst

Piping routes are not considered, so the nearest demand isn’t necessarily the location from which the meter actually receives its flow.

In addition, you may not know the actual location of the manjal meter. The geographic location of the meter in the GIS is not necessarily the point from which water is taken from the system, but it may be the wahergems of the land parcel, the centroid of building footprint or a point along the frontage of the building. Ideally, you should place these meter points at the location maunal the tap, but you may only know the centroid of the building or land parcel for a customer account.

Billing Meter Aggregation Billing meter aggregation is the technique of assigning all meters within a service polygon to a specified demand node. Service polygons define the service area for each of the demand nodes figure 2.


Service polygons define the service area for each of the demand nodes.

Meter aggregation is a polygon-to-point allocation technique because the service areas are contained in a GIS polygon feature class, and the demand nodes are contained in a point feature class. The demands associated with the meters within each of the service area polygons is assigned to mannual respective demand node points.

Due to the need for service polygons, the initial setup for this approach is more involved than the meter assignment strategy — the trade-off is greater control over the assignment of meters to demand nodes.

Automated construction of the service polygons may not produce the desired results, so you may need to adjust the polygon boundaries manually, especially at the edges of the drawing. Distribution This strategy involves distributing lump-sum area water-use data among a number of service polygons service areas and, by extension, their associated bentey nodes.

The lump-sum area is a polygon for which the total lump-sum water use of all of the service areas and their demand nodes within it is known metered but the distribution of the total water benltey among the individual nodes is not. You can base the water-use data for these lump-sum areas on system meter data from pump stations, treatment plants or flow control valves, meter routes, pressure zones and TAZ traffic analysis zones.

The lump-sum area for which a flow is known must be a GIS polygon. There is one flow rate per polygon, and you cannot overlap open space between the polygons.

The known flow within the lump-sum area generally is divided among the service polygons within the area using one of two techniques — equal distribution or proportional distribution: The equal flow distribution option simply divides the known flow evenly between mnaual demand nodes.

The lump-sum area in this case is a polygon feature class that represents meter route areas. For each of these meter route polygons, the total flow is known.

Productivity Corner: Using Bentley WaterGEMS with GIS Data for Water Demand Allocation

The total flow is then equally divided among the demand nodes within each of the meter bentey polygons. The proportional distribution option by area or by population divides the lump-sum flow among the service polygons based upon one of two attributes of the service polygons — the area or the population. The greater the percentage of the lump-sum area or population that a service polygon contains, the greater the percentage of total flow assigned to that service polygon.

Each service polygon has an associated demand node, and the flow that is calculated for each service polygon is assigned to this demand node.

Bentley WaterGEMS V8i (SELECTseries 5)

This strategy requires the definition of lump-sum area or population polygons in the GIS, service polygons in the model and their related demand nodes. Sometimes you must use the flow distribution technique to assign unaccounted-for water wategrems nodes and when any method that uses customer metering data as opposed to system metering data is implemented.

In figure 3, the total demand in meter route A may be 55 gpm 3. Because meter route A has 11 nodes, the demand at each node would be 5 gpm 0.

Point Demand Assignment A point demand assignment technique is used to assign a demand directly to a demand node. This strategy primarily is a manual operation and is used to ebntley large generally industrial or commercial water users to the demand node that serves the consumer in question.


This technique is unnecessary if all demands satergems accounted for using one of the other allocation strategies. Estimation of Demands Using Land Use and Population Data Automated techniques also can assist in the estimation of demands using land use and population density data.

These techniques are similar to the flow distribution allocation methods, except mannual the type of base feature class that is used to intersect with the service feature class may contain information other than flow; for example, land use or population.

You can use this type mannual demand estimation in the projection of future demands; in this case, the demand allocation relies on a polygon feature class that contains data regarding expected future conditions. You can use various data types with this technique, including future land use, projected population or demand density in polygon form with the polygons based upon traffic analysis zones, census tracts, planning districts or other classifications.

Note that you can use these data sources to assign current demands; the difference between the two being the data that is contained within the source. If the data relates to projected values, you can use it for demand projections. Many of these data types do not include demand information, so waetrgems data conversion is required to translate the information contained in the future condition polygons into projected demand values.

This conversion entails translating the data contained within your data source to flow, which you then can apply using LoadBuilder.

After an appropriate conversion method is in place, the service feature class containing the service waergems and demand nodes is overlaid with the future condition polygon feature class. You can determine a projected demand for each of the service areas and assign the demand nodes manjal with each service polygon.

The conversion required will depend on the source data used. You may need to translate the data contained within the source — such as population, land area, etc. Depending on how the feature classes intersect, service areas may contain multiple demand types land uses that are added benltey applied to the demand node for that service polygon. In kanual easy-to-follow, friendly style, long-time Cadalyst contributing editor Lynn Allen guides you through a new feature or time-saving trick in every episode of her popular AutoCAD Video Tips.

All exclusively from Cadalyst! Follow Lynn on Twitter. Andres Gutierrez Automated techniques help you meet current demands and plan for the future. The consumption of water is the driving force behind the hydraulic dynamics occurring in water distribution systems.

When simulating these dynamics in your water distribution model, an accurate representation of system demands is as critical as a precise model watergfms the physical components of the model. Reproduction in whole or in part is prohibited. Please send any technical comments or questions to benrley webmaster. Entire site Article Author Event News. Do you use social media — such as Facebook or Twitter updates, YouTube videos, or discussion forums — for work-related purposes?