Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Noise mapping of highly trafficked roads of the province of Bologna according to D.Lgs. 194/2005

The European Community has stressed the importance of achieving a common understanding to deal with the environmental noise through community actions of the Member States. This implies the use of harmonized indicators and specific information regarding the values of indicators, the exceedance of limits and the number of people and dwellings exposed to noise. The D.Lgs. 149/2005 in compliance with the European Directive 2002/49/EC defines methodologies, noise indicators and types of outputs required. In this dissertation the work done for the noise mapping of highly trafficked roads of the Province of Bologna will be reported. The study accounts for the environmental noise generated by the road infrastructure outside the urban agglomeration of Bologna. Roads characterized by an annual traffic greater than three millions of vehicles will be considered. The process of data collection and validation will be reported, as long as the implementation of the calculation method in the software and the procedure to create and calibrate the calculation model. Results will be provided as required by the legislation, in forms of maps and tables. Moreover results regarding each road section accounted will be combined to gain a general understanding of the situation of the overall studied area. Although the understanding of the noise levels and the number of people exposed is paramount, it is not sufficient to develop strategies of noise abatement interventions. Thus a further step will be addressed: the creation of priority maps as the basis of action plans for organizing and prioritizing solutions for noise reduction and abatement. Noise reduction measures are reported in a qualitative way in the annex and constitute a preliminary research.