flow forecasting using deterministic updating of water levels in distributed hydrodynamic urban drainage models

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ID: 179202
2014
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Abstract
There is a growing requirement to generate more precise model simulations and forecasts of flows in urban drainage systems in both offline and online situations. Data assimilation tools are hence needed to make it possible to include system measurements in distributed, physically-based urban drainage models and reduce a number of unavoidable discrepancies between the model and reality. The latter can be achieved partly by inserting measured water levels from the sewer system into the model. This article describes how deterministic updating of model states in this manner affects a simulation, and then evaluates and documents the performance of this particular updating procedure for flow forecasting. A hypothetical case study and synthetic observations are used to illustrate how the Update method works and affects downstream nodes. A real case study in a 544 ha urban catchment furthermore shows that it is possible to improve the 20-min forecast of water levels in an updated node and the three-hour forecast of flow through a downstream node, compared to simulations without updating. Deterministic water level updating produces better forecasts when implemented in large networks with slow flow dynamics and with measurements from upstream basins that contribute significantly to the flow at the forecast location.
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hansen2014waterflow Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Lisbet Sneftrup Hansen;Morten Borup;Arne Møller;Peter Steen Mikkelsen
Journal Journal of food biochemistry
Year 2014
DOI
10.3390/w6082195
URL
http://www.mdpi.com/2073-4441/6/8/2195
Keywords
data assimilation urban drainage systemshydraulic engineeringwater supply for domestic and industrial purposes

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