DOI: 10.5194/hess-22-5243-2018
论文题名: Value of uncertain streamflow observations for hydrological modelling
作者: Etter S. ; Strobl B. ; Seibert J. ; Ilja Van Meerveld H.J.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2018
卷: 22, 期: 10 起始页码: 5243
结束页码: 5257
语种: 英语
Scopus关键词: Catchments
; Random errors
; Runoff
; Time series
; Error distributions
; Hydrological modelling
; Hydrological models
; Model calibration
; Standard deviation
; Streamflow measurements
; Temporal resolution
; Ungauged catchment
; Stream flow
英文摘要: Previous studies have shown that hydrological models can be parameterised using a limited number of streamflow measurements. Citizen science projects can collect such data for otherwise ungauged catchments but an important question is whether these observations are informative given that these streamflow estimates will be uncertain. We assess the value of inaccurate streamflow estimates for calibration of a simple bucket-type runoff model for six Swiss catchments. We pretended that only a few observations were available and that these were affected by different levels of inaccuracy. The level of inaccuracy was based on a log-normal error distribution that was fitted to streamflow estimates of 136 citizens for medium-sized streams. Two additional levels of inaccuracy, for which the standard deviation of the error distribution was divided by 2 and 4, were used as well. Based on these error distributions, random errors were added to the measured hourly streamflow data. New time series with different temporal resolutions were created from these synthetic streamflow time series. These included scenarios with one observation each week or month, as well as scenarios that are more realistic for crowdsourced data that generally have an irregular distribution of data points throughout the year, or focus on a particular season. The model was then calibrated for the six catchments using the synthetic time series for a dry, an average and a wet year. The performance of the calibrated models was evaluated based on the measured hourly streamflow time series. The results indicate that streamflow estimates from untrained citizens are not informative for model calibration. However, if the errors can be reduced, the estimates are informative and useful for model calibration. As expected, the model performance increased when the number of observations used for calibration increased. The model performance was also better when the observations were more evenly distributed throughout the year. This study indicates that uncertain streamflow estimates can be useful for model calibration but that the estimates by citizen scientists need to be improved by training or more advanced data filtering before they are useful for model calibration. © Author(s) 2018. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163173
Appears in Collections: 气候变化与战略
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作者单位: Etter, S., Department of Geography, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland; Strobl, B., Department of Geography, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland; Seibert, J., Department of Geography, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland, Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, P.O. Box 7050, Uppsala, 75007, Sweden; Ilja Van Meerveld, H.J., Department of Geography, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland
Recommended Citation:
Etter S.,Strobl B.,Seibert J.,et al. Value of uncertain streamflow observations for hydrological modelling[J]. Hydrology and Earth System Sciences,2018-01-01,22(10)