GIS-Based Model Parameter Enhancement for Urban Water Utility Networks

Péter Orgoványi, T. Karches
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Abstract

Water utilities are like arteries for the urban environment and, in order to satisfy water demand, extensive design and operation work applying modeling tools is required. An effective tool can be operated but only if the input, such as real-world consumption data, is built into the system. This study aims to present a GIS-based technique to align the consumption data to a simplified network topology. This study investigates four distinct methods, revealing noteworthy outcomes. The geocoding of consumption locations facilitates their seamless integration with model nodes through geospatial methods. Additionally, effective water consumption allocation is achieved by delineating influence ranges around each node. When comparing the zoning based on the street approach and the arithmetic average with the benchmark manual range of influence approach, substantial errors appear of approximately 190% and 230%, respectively. Addressing the impracticality of the manual method, especially for larger networks, this study advocates for the use of Thiessen polygons to delineate influence areas. In conclusion, this study presents a holistic approach to aligning consumption data with simplified network topologies for enhanced water utility modeling.
基于地理信息系统的城市供水网络模型参数改进
供水设施就像城市环境的动脉,为了满足用水需求,需要应用建模工具进行大量的设计和运行工作。有效的工具可以运行,但前提是系统中必须包含输入数据,如真实世界的用水数据。本研究旨在提出一种基于 GIS 的技术,将消耗数据与简化的网络拓扑结构相匹配。本研究调查了四种不同的方法,揭示了值得注意的结果。通过地理空间方法对用水地点进行地理编码,有助于将其与模型节点无缝集成。此外,通过划定每个节点周围的影响范围,可以实现有效的用水分配。将基于街道法和算术平均法的分区与基准人工影响范围法进行比较时,出现了巨大的误差,误差率分别约为 190% 和 230%。考虑到人工方法的不实用性,尤其是对于大型网络而言,本研究主张使用 Thiessen 多边形来划分影响范围。总之,本研究提出了一种将消耗数据与简化网络拓扑结构相结合的整体方法,以增强水务建模的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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