Accurate Allocating the Water Demand to the Water Pipe Network Simulation model
The process of spatially allocate the water demand is a potential source of errors that should be considered when building the hydraulic simulation model. There are several methods for this purpose and each has limitations and advantages. In the case of existing accurate recording of coordinates for...
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Veröffentlicht in: | Āb va fāz̤ilāb : majallah-i ʻilmī, pizhūhishī pizhūhishī, 2019-11, Vol.30 (5), p.61-74 |
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Sprache: | eng |
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Zusammenfassung: | The process of spatially allocate the water demand is a potential source of errors that should be considered when building the hydraulic simulation model. There are several methods for this purpose and each has limitations and advantages. In the case of existing accurate recording of coordinates for water meters in GIS, there are several base demand automated allocation strategies for modeling the spatial distribution of water consumption in water networks. Where the spatial data for water meters are not available, conventional methods such as Thiessen and LDM (Length Dependent Method) can be used. And if this data is incomplete mixed practices can be used. This study proposed a mixed method named SAWDSL (Spatial Allocation of the Water Demand based on Data of Consumers) that divides the total consumption in subgroups related with corresponding water meters’ recorded. This method assigning the demand of each subgroup into the nearest pipe. The simulation results of WaterGEMS software using SAWDSL, Thiessen and LDM methods, after calibration, were compared to field measurements in zone I1 of Mashhad city. RMSE between observed and simulated pressure with the SAWDSL, Thiessen and LDM methods were determined to be 0.9, 2.3 and 1.4 respectively. That shows if the incomplete data of water meters would have existed and have enough time to use them, SAWDSL method is more accurate than others. Otherwise LDM method is more accurate than Thiessen method. |
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ISSN: | 1024-5936 2383-0905 |
DOI: | 10.22093/wwj.2018.127043.2666 |