Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway
Cloudbursts and extreme rainstorms pose a growing threat to urban areas. Accurate rainfall data is essential for predicting inundations and urban flooding. Private weather stations are becoming increasingly common, and their spatial distribution roughly follows population density. This makes them a...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Journal of Hydrology X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S258991552400021X |
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| author | Kay Khaing Kyaw Emma Baietti Cristian Lussana Valerio Luzzi Paolo Mazzoli Stefano Bagli Attilio Castellarin |
| author_facet | Kay Khaing Kyaw Emma Baietti Cristian Lussana Valerio Luzzi Paolo Mazzoli Stefano Bagli Attilio Castellarin |
| author_sort | Kay Khaing Kyaw |
| collection | DOAJ |
| description | Cloudbursts and extreme rainstorms pose a growing threat to urban areas. Accurate rainfall data is essential for predicting inundations and urban flooding. Private weather stations are becoming increasingly common, and their spatial distribution roughly follows population density. This makes them a valuable source of crowdsourced data for high-resolution rainfall fields in urban areas. We evaluated the performance of private rain gauges in two recent pluvial flood events in Oslo. We also explored the potential use of private rain gauge data in inundation models. Our results indicate that private sensors have excellent rain detection capabilities, but they tend to underestimate the reference value on average by approximately 25%. However, bias-corrected crowdsourced rainfall data can produce significantly more accurate inundation maps than those generated from official rain gauges, if compared with maps resulting from bias-corrected weather radar. Overall, our study highlights the potential of utilizing crowdsourced rainfall data from private sensors for accurately representing pluvial flooding in urban areas. These findings have significant implications for improving flood prediction and mitigation strategies in vulnerable urban settings. |
| format | Article |
| id | doaj-art-c918f8a012694f6b9c3d5b0494bf254f |
| institution | Kabale University |
| issn | 2589-9155 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology X |
| spelling | doaj-art-c918f8a012694f6b9c3d5b0494bf254f2024-11-23T06:31:32ZengElsevierJournal of Hydrology X2589-91552024-12-0125100191Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, NorwayKay Khaing Kyaw0Emma Baietti1Cristian Lussana2Valerio Luzzi3Paolo Mazzoli4Stefano Bagli5Attilio Castellarin6Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, Italy; Corresponding author.Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, ItalyNorwegian Meteorological Institute, Oslo, NorwayGECOsistema Srl, 47923 Rimini, ItalyGECOsistema Srl, 47923 Rimini, ItalyGECOsistema Srl, 47923 Rimini, ItalyDepartment of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, ItalyCloudbursts and extreme rainstorms pose a growing threat to urban areas. Accurate rainfall data is essential for predicting inundations and urban flooding. Private weather stations are becoming increasingly common, and their spatial distribution roughly follows population density. This makes them a valuable source of crowdsourced data for high-resolution rainfall fields in urban areas. We evaluated the performance of private rain gauges in two recent pluvial flood events in Oslo. We also explored the potential use of private rain gauge data in inundation models. Our results indicate that private sensors have excellent rain detection capabilities, but they tend to underestimate the reference value on average by approximately 25%. However, bias-corrected crowdsourced rainfall data can produce significantly more accurate inundation maps than those generated from official rain gauges, if compared with maps resulting from bias-corrected weather radar. Overall, our study highlights the potential of utilizing crowdsourced rainfall data from private sensors for accurately representing pluvial flooding in urban areas. These findings have significant implications for improving flood prediction and mitigation strategies in vulnerable urban settings.http://www.sciencedirect.com/science/article/pii/S258991552400021XCrowdsourcingInundation modelsOfficial rain gaugesPluvial floodingPrivate sensorsWeather radar |
| spellingShingle | Kay Khaing Kyaw Emma Baietti Cristian Lussana Valerio Luzzi Paolo Mazzoli Stefano Bagli Attilio Castellarin Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway Journal of Hydrology X Crowdsourcing Inundation models Official rain gauges Pluvial flooding Private sensors Weather radar |
| title | Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway |
| title_full | Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway |
| title_fullStr | Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway |
| title_full_unstemmed | Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway |
| title_short | Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway |
| title_sort | private sensors and crowdsourced rainfall data accuracy and potential for modelling pluvial flooding in urban areas of oslo norway |
| topic | Crowdsourcing Inundation models Official rain gauges Pluvial flooding Private sensors Weather radar |
| url | http://www.sciencedirect.com/science/article/pii/S258991552400021X |
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