Assessment of data availability influence on integrated urban drainage modelling uncertainty

被引:42
|
作者
Freni, Gabriele [1 ]
Mannina, Giorgio [1 ]
Viviani, Gaspare [1 ]
机构
[1] Univ Palermo, Dipartimento Ingn Idraul & Applicaz Ambientali, I-90128 Palermo, Italy
关键词
Environmental modelling; Integrated urban drainage systems; Uncertainty analysis; Receiving water body; Model reliability assessment; WASTE-WATER SYSTEMS; REAL-TIME CONTROL; QUALITY PREDICTIONS; SURROGATE MODELS; DECISION-SUPPORT; GLUE METHODOLOGY; TREATMENT PLANTS; RIVER; MANAGEMENT; POLLUTION;
D O I
10.1016/j.envsoft.2009.03.007
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In urban water quality management, several models are connected and integrated for analysing the fate of pollutants from the sources in the urban catchment to the final recipient; classical problems connected with the selection and calibration of parameters are amplified by the complexity of the modelling approach increasing their uncertainty. The present paper aims at studying the influence of reductions in available data on the modelling response uncertainty with respect to the different integrated modelling outputs (both considering quantity and quality variables). At this scope, a parsimonious integrated home-made model has been used allowing for analysing the combinative effect of data availability regarding the different parts of the integrated urban drainage system; the uncertainty analysis approach has been applied to an experimental catchment in Bologna (Italy). The number of available data points has been fictitiously reduced obtaining data sets ranging between 25% and 100% of the actually measured data. For each of the data sets, uncertainty has been evaluated and its propagation from the upstream sub-model to the downstream ones has been assessed. The present study demonstrates that model calibration and modelling efficiency assessment may induce the operator to be excessively confident in the model results when available data are scarce. Quite the opposite is indeed true. that limited data availability increases modelling uncertainty. A conclusion of this article is that uncertainty analysis should always be conducted in order to effectively evaluate model reliability. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1171 / 1181
页数:11
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