Rainfall Threshold Assessment Corresponding to the Maximum Allowable Turbidity for Source Water

  This study aims to assess the upstream rainfall thresholds corresponding to the maximum allowable turbidity of source water, using monitoring data and artificial neural network computation. The Taipei Water Source Domain was selected as the study area, and the upstream rainfall records were collec...

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Veröffentlicht in:Water environment research : a research publication of the Water Environment Federation. - 1998. - 88(2016), 12 vom: 01. Dez., Seite 2285-2291
1. Verfasser: Fan, Shu-Kai S (VerfasserIn)
Weitere Verfasser: Kuan, Wen-Hui, Fan, Chihhao, Chen, Chiu-Yang
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:Water environment research : a research publication of the Water Environment Federation
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:  This study aims to assess the upstream rainfall thresholds corresponding to the maximum allowable turbidity of source water, using monitoring data and artificial neural network computation. The Taipei Water Source Domain was selected as the study area, and the upstream rainfall records were collected for statistical analysis. Using analysis of variance (ANOVA), the cumulative rainfall records of one-day Ping-lin, two-day Ping-lin, two-day Tong-hou, one-day Guie-shan, and one-day Tai-ping (rainfall in the previous 24 or 48 hours at the named weather stations) were found to be the five most significant parameters for downstream turbidity development. An artificial neural network model was constructed to predict the downstream turbidity in the area investigated. The observed and model-calculated turbidity data were applied to assess the rainfall thresholds in the studied area. By setting preselected turbidity criteria, the upstream rainfall thresholds for these statistically determined rain gauge stations were calculated
Beschreibung:Date Completed 15.03.2017
Date Revised 11.10.2018
published: Print-Electronic
Citation Status MEDLINE
ISSN:1061-4303
DOI:10.2175/106143016X14504669768570