Keywords:
Flood forecasting.
;
Electronic books.
Type of Medium:
Online Resource
Pages:
1 online resource (275 pages)
Edition:
1st ed.
ISBN:
9781351652568
Series Statement:
IHE Delft PhD Thesis Series
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=4824709
DDC:
363.34930112
Language:
English
Note:
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Acknoledgments -- Summary -- Samenvatting -- Sommario -- Table of Contents -- 1: Introduction -- 1.1 Background -- 1.1.1 Flood Forecasting and Early Warning Systems -- 1.1.2 Hydrological and Hydrodynamic Modelling -- 1.1.3 Uncertainty in Hydrological and Hydrodynamic Modelling -- 1.1.4 Data Assimilation -- 1.1.5 Citizen Science -- 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) -- 2.2.1 Catchment Description -- 2.2.2 Model Description -- 2.3 Case 2 - Bacchiglione Catchment (italy) -- 2.3.1 Catchment Description -- 2.3.2 Model Description -- 2.4 Case 3 - Trinity and Sabine Rivers (usa) -- 2.4.1 Rivers Description -- 2.4.2 Model Description -- 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 -- 4.2.1 Assimilation of Intermittent Observations -- 4.2.2 Observation and Model Error -- 4.2.3 Generation of Synthetic Observations -- 4.3 Experimental Setup -- 4.3.1 Experiment 4.1: Streamflow Data from Static Physical (stph) Sensors -- 4.3.2 Experiment 4.2: Streamflow Data from Static Social (stsc) Sensors -- 4.3.3 Experiment 4.3: Intermittent Streamflow Data from Static Social (stsc) Sensors -- 4.3.4 Experiment 4.4: Heterogeneous Network of Static Physical (stph) and Static Social (stsc) Sensors -- 4.4 Results and Discussion -- 4.4.1 Experiment 4.1 -- 4.4.2 Experiment 4.2 -- 4.4.3 Experiment 4.3 -- 4.4.4 Experiment 4.4 -- 4.5 Conclusions.
,
5: Assimilation of Asynchronous Data in Hydrological Models -- 5.1 Introduction -- 5.2 Methodology -- 5.2.1 Assimilation of Asynchronous Observations -- 5.2.2 Observation and Model Error -- 5.2.3 Generation of Synthetic Observations -- 5.3 Experimental Setup -- 5.3.1 Experiment 5.1: Observations from a Single Static Social (stsc) Sensor -- 5.3.2 Experiments 5.2: Observations from Distributed Static Physical (stph) and Static Social (stsc) Sensors -- 5.4 Results and Discussion -- 5.4.1 Experiment 5.1 -- 5.4.2 Experiment 5.2 -- 5.5 Conclusions -- 6: Assimilation of Synchronous Data in Hydraulic Models -- 6.1 Introduction -- 6.2 Methodology -- 6.2.1 Data Assimilation Methods -- 6.2.2 Observation and Model Error -- 6.2.3 Streamflow Observations -- 6.3 Experimental Setup -- 6.3.1 Experiment 6.1: Effect of Different Da Methods -- 6.3.2 Experiment 6.2: Effect of Sensors Location on Kf Performances -- 6.4 Results and Discussions -- 6.4.1 Experiment 6.1 -- 6.4.2 Experiment 6.2 -- 6.5 Conclusions -- 7: Assimilation of Synchronous Data in a Cascade of Models -- 7.1 Introduction -- 7.2 Methodology -- 7.2.1 Data Assimilation Method -- 7.2.2 Observation and Model Error -- 7.2.3 Generation of Synthetic Observations -- 7.3 Experimental Setup -- 7.3.1 Experiment 7.1: Assimilation of Data from Static Physical (stph) Sensors -- 7.3.2 Experiment 7.2: Assimilation of Data from Static Social (stsc) Sensors -- 7.3.3 Experiment 7.3: Assimilation of Data from Dynamic Social (dysc) Sensors -- 7.3.4 Experiment 7.4: Realistic Scenarios of Engagements -- 7.4 Results and Discussion -- 7.4.1 Experiment 7.1 -- 7.4.2 Experiment 7.2 -- 7.4.3 Experiment 7.3 -- 7.4.4 Experiment 7.4 -- 7.5 Conclusions -- 8: Conclusions and Recommendations -- 8.1 Overview -- 8.2 Research Outcomes -- 8.3 Limitations and Recommendations -- References -- List of Acronyms -- List of Table -- List of Figures.
,
About the Author.
Permalink
