Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models

Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models

by Maurizio Mazzoleni

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Product Details

ISBN-13: 9781138035904
Publisher: Taylor & Francis
Publication date: 01/25/2017
Pages: 240
Product dimensions: 6.68(w) x 9.43(h) x (d)

About the Author

Maurizio Mazzoleni was born in Brescia in November 1986. Mr. Mazzoleni graduated from University of Brescia, in Brescia, Italy, in May 2011. During his university studies he continued to pursue his interest in the flood protection by moving to UNESCO-IHE with the support of a scholarship awarded by University of Brescia to carry out his Master Thesis. Afterwards, he cooperate for 1 year within the KULTURisk Project as research fellow of the University of Brescia. Currently, Mr. Mazzoleni is a PhD candidate at UNESCO-IHE Institute for Water Education under the Department of Integrated Water Systems and Governance, Delft, The Netherlands. His research interest include hydrologic and hydrodynamic modelling, in particular he dealt with issue related to flood forecasting, data assimilation, flood inundation mapping, flood risk and uncertainty analysis, flood defence systems design and reliability analysis, statistical hydrology.

Table of Contents

1 Introduction
1.1 Background
1.2 Motivation
1.3 Terminology
1.4 Research objectives
1.5 Outline of the thesis

2 Case studies and models
2.1 Introduction
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
3.1 Introduction
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
4.1 Introduction
4.2 Methodology
4.3 Experimental setup
4.4 Results and discussion
4.5 Conclusions

5 Assimilation of asynchronous data in hydrological models
5.1 Introduction
5.2 Methodology
5.3 Experimental setup
5.4 Results and discussion
5.5 Conclusions

6 Assimilation of synchronous data in hydraulic models
6.1 Introduction
6.2 Methodology
6.3 Experimental setup
6.4 Results and discussions
6.5 Conclusions

7 Assimilation of synchronous data in a cascade of models
7.1 Introduction
7.2 Methodology
7.3 Experimental setup
7.4 Results and discussion
7.5 Conclusions

8 Conclusions and recommendations
8.1 Overview
8.2 Research outcomes
8.3 Limitations and recommendations

References

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