DOI: 10.5194/hess-22-391-2018
Scopus记录号: 2-s2.0-85040714374
论文题名: Exploring the influence of citizen involvement on the assimilation of crowdsourced observations: A modelling study based on the 2013 flood event in the Bacchiglione catchment (Italy)
作者: Mazzoleni M ; , Juliette Cortes Arevalo V ; , Wehn U ; , Alfonso L ; , Norbiato D ; , Monego M ; , Ferri M ; , Solomatine D ; P
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2018
卷: 22, 期: 1 起始页码: 391
结束页码: 416
语种: 英语
Scopus关键词: Climate models
; Dynamics
; Flood control
; Floods
; Forecasting
; Heterogeneous networks
; Hydraulic models
; Hydrology
; Probability distributions
; Runoff
; Citizen involvement
; Extreme flood events
; Hydrological modeling
; Hydrological prediction
; Prediction validation
; Real time measurements
; Semi distributed hydrological models
; Spatial variability
; Catchments
英文摘要: To improve hydrological predictions, real-time measurements derived from traditional physical sensors are integrated within mathematic models. Recently, traditional sensors are being complemented with crowdsourced data (social sensors). Although measurements from social sensors can be low cost and more spatially distributed, other factors like spatial variability of citizen involvement, decreasing involvement over time, variable observations accuracy and feasibility for model assimilation play an important role in accurate flood predictions. Only a few studies have investigated the benefit of assimilating uncertain crowdsourced data in hydrological and hydraulic models. In this study, we investigate the usefulness of assimilating crowdsourced observations from a heterogeneous network of static physical, static social and dynamic social sensors. We assess improvements in the model prediction performance for different spatial-temporal scenarios of citizen involvement levels. To that end, we simulate an extreme flood event that occurred in the Bacchiglione catchment (Italy) in May 2013 using a semi-distributed hydrological model with the station at Ponte degli Angeli (Vicenza) as the prediction-validation point. A conceptual hydrological model is implemented by the Alto Adriatico Water Authority and it is used to estimate runoff from the different sub-catchments, while a hydraulic model is implemented to propagate the flow along the river reach. In both models, a Kalman filter is implemented to assimilate the crowdsourced observations. Synthetic crowdsourced observations are generated for either static social or dynamic social sensors because these measures were not available at the time of the study. We consider two sets of experiments: (i) assuming random probability of receiving crowdsourced observations and (ii) using theoretical scenarios of citizen motivations, and consequent involvement levels, based on population distribution. The results demonstrate the usefulness of integrating crowdsourced observations. First, the assimilation of crowdsourced observations located at upstream points of the Bacchiglione catchment ensure high model performance for high lead-time values, whereas observations at the outlet of the catchments provide good results for short lead times. Second, biased and inaccurate crowdsourced observations can significantly affect model results. Third, the theoretical scenario of citizens motivated by their feeling of belonging to a "community of friends" has the best effect in the model performance. However, flood prediction only improved when such small communities are located in the upstream portion of the Bacchiglione catchment. Finally, decreasing involvement over time leads to a reduction in model performance and consequently inaccurate flood forecasts. © Author(s) 2018. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79423
Appears in Collections: 气候变化事实与影响
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作者单位: Integrated Water Systems and Governance Department, IHE Delft Institute for Water Education, Delft, Netherlands; Water Engineering and Management, University of Twente, Enschede, Netherlands; Alto Adriatico Water Authority, Venice, Italy; Water Resources Management Department, Water Problems Institute, Russian Academy of Sciences, Moscow, Russian Federation; Water Resources Section, Delft University of Technology, Delft, Netherlands
Recommended Citation:
Mazzoleni M,, Juliette Cortes Arevalo V,, Wehn U,et al. Exploring the influence of citizen involvement on the assimilation of crowdsourced observations: A modelling study based on the 2013 flood event in the Bacchiglione catchment (Italy)[J]. Hydrology and Earth System Sciences,2018-01-01,22(1)