In recent years, the continued technological advances have led to the spread of low-cost sensors and devices supporting crowdsourcing as a way to obtain observations of hydrological variables in a more distributed way than the classic static physical sensors. The main advantage of using these type of sensors is that they can be used not only by technicians but also by regular citizens. However, due to their relatively low reliability and varying accuracy in time and space, crowdsourced observations have not been widely integrated in hydrological and/or hydraulic models for flood forecasting applications. Instead, they have generally been used to validate model results against observations, in post-event analyses.
This research aims to investigate the benefits of assimilating the crowdsourced observations, coming from a distributed network of heterogeneous physical and social (static and dynamic) sensors, within hydrological and hydraulic models, in order to improve flood forecasting. The results of this study demonstrate that crowdsourced observations can significantly improve flood prediction if properly integrated in hydrological and hydraulic models. This study provides technological support to citizen observatories of water, in which citizens not only can play an active role in information capturing, evaluation and communication, leading to improved model forecasts and better flood management.
1.4 Research objectives
1.5 Outline of the thesis
2 Case studies and models
2.2 Case 1 - Brue Catchment (UK)
2.3 Case 2 - Bacchiglione Catchment (Italy)
2.4 Case 3 - Trinity and Sabine Rivers (USA)
2.5 Case 4 - Synthetic river reach
3 Data assimilation methods
3.2 Direct insertion
3.3 Nudging scheme
3.4 Kalman Filter
3.5 Ensemble Kalman Filter
3.6 Asynchronous Ensemble Kalman Filter
4 Assimilation of synchronous data in hydrological models
4.3 Experimental setup
4.4 Results and discussion
5 Assimilation of asynchronous data in hydrological models
5.3 Experimental setup
5.4 Results and discussion
6 Assimilation of synchronous data in hydraulic models
6.3 Experimental setup
6.4 Results and discussions
7 Assimilation of synchronous data in a cascade of models
7.3 Experimental setup
7.4 Results and discussion
8 Conclusions and recommendations
8.2 Research outcomes
8.3 Limitations and recommendations
IHE Delft PhD programme leads to a deepening of a field of specialisation. PhD fellows do scientific research, often with conclusions that directly influence their region. At IHE Delft, PhD researchers from around the world participate in problem-focused and solution-oriented research on development issues, resulting in an inspiring research environment. PhD fellows work together with other researchers from many countries dealing with topics related to water and the environment.
PhD research is often carried out in the ‘sandwich’ model. Preparation and final reporting – the first and last portion of the programme – are carried out in Delft, while actual research is done in the fellow’s home country, under co-supervision of a local institute. Regular contacts with the promotor are maintained through visits and long-distance communication. This enables researchers to employ solutions directly to problems in their geographical region.
IHE Delft PhD degrees are awarded jointly with a university. The degrees are highly valued and fully recognised in all parts of the world.