River flood prediction systems: towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis
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Format: | Abschlussarbeit Buch |
Sprache: | English |
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Karlsruhe
Inst. für Wasser und Gewässerentwicklung
2005
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Schriftenreihe: | Mitteilungen des Instituts für Wasser und Gewässerentwicklung - Bereich Wasserwirtschaft und Kulturtechnik - mit "Theodor-Rehbock-Wasserbaulaboratorium" der Universität Karlsruhe (TH)
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Beschreibung: | Zsfassung in dt. Sprache |
Beschreibung: | xi, 157 Seiten Illustrationen, Diagramme 21 cm |
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adam_text | INSTITUT FUR INV .-WR. WASSER UND GEWASSERENTWICKLUNG UNIVERSITAT
KARLSRUHE (TH) TECHNISCHE UNIVERSITAT DARMSTADT /JQ /^FT BIBLIOTHEK
WASSER UND UMWELT W PETERSENSTRATTE 13 D-64287 DARMSTADT TELEFON
06151/163659 FAX 06151/163758 RIVER FOOD PREDICTION SYSTEMS: TOWARDS
COMPLEMENTARY HYDRODYNAMIC, HYDROLOGICAL AND DATA DRIVEN MODELS WITH
UNCERTAINTY ANALYSIS RAJESH RAJ SHRESTHA HEFT 229 MITTEILUNGEN DES
INSTITUTS FIIR WASSER UND GEWASSERENTWICKLUNG - BEREICH WASSERWIRTSCHAFT
UND KULTURTECHNIK - MIT THEODOR-REHBOCK-WASSERBAULABORATORIUM DER
UNIVERSITAT KARLSRUHE (TH) HRSG.: PROF. DR.-LNG. DR. H. C. MULT. FRANZ
NESTMANN, ORDINARIUS 2005 CONTENTS CONTENTS ZUSAMMENFASSUNG J SUMMARY IV
ACKNOWLEDGEMENTS VII CONTENTS -^ VIII CHAPTER 1: BACKGROUND 1 1.1
INTRODUCTION 1 1.2 FLOOD RISK AND MANAGEMENT 2 1.3 FLOOD MODELLING AND
FORECASTING SYSTEMS 3 1.4 RIVER FLOOD PREDICTION SYSTEMS 5 1.5
UNCERTAINTIES IN RIVER FLOOD PREDICTION SYSTEMS 6 1.6 RESEARCH NEEDS 7
1.7 OBJECTIVES OF THE PRESENT RESEARCH 8 1.8 STRUCTURE OF THE THESIS 9
CHAPTER 2: HYDRODYNAMIC AND HYDROLOGICAL MODELS 10 2.1 PHYSICALLY BASED
HYDRODYNAMIC NUMERICAL MODELS ...10 2.1.1 SAINT VENANT EQUATIONS 11
2.1.2 ENERGY LOSS COEFFICIENT 13 2.1.3 DIMENSIONLESS NUMBERS 15 2.1.3.1
FROUDE NUMBER 15 2.1.3.2 REYNOLDS NUMBER 15 2.1.4 NUMERICAL SOLUTION OF
SAINT VENANT EQUATION 17 2.1.4.1 IMPLICIT FINITE DIFFERENCE SCHEME 17
2.1.4.2. STABILITY CRITERIA 19 2.1.5 STEADY FLOW SIMULATIONS 19 2.2
HYDROLOGICAL FLOW ROUTING MODELS 20 2.2.1 METHOD OF SOLUTION 22 2.2.2
STABILITY CRITERIA 23 2.3 REVIEW OF APPLICATIONS 23 2.3.1 FLOOD ROUTING
23 2.3.2 FLOODPLAIN MAPPING AND FLOOD RISK ASSESSMENT 24 VILI CONTENTS
CHAPTER 3: DATA DRIVEN MODELS: ARTIFICIAL NEURAL NETWORKS AND FUZZY
SYSTEMS 28 3.1 DATA DRIVEN MODELLING 28 3.2 ARTIFICIAL NEURAL NETWORKS
29 3.2.1 ACTIVATION FUNCTIONS 31 3.2.2 MULTILAYER PERCEPTRONS 32 3.2.3
DYNAMIC NEURAL NETWORKS 33 3.2.4 RADIAL BASIS FUNCTION NETWORKS 34 3.2.5
NEURAL NETWORK TRAINING 35 3.2.6 ANN MODEL CONSTRUCTION 36 3.2.6.1 DATA
SELECTION AND PRE-PROCESSING 37 3.2.6.2 DESIGN OF AN ANN MODEL 37
3.2.6.3 TRAINING, CROSS VALIDATION AND TESTING 38 3.3 FUZZY SYSTEMS 39
3.3.1 MEMBERSHIP FUNCTIONS 39 3.3.2 FUZZY NUMBERS 39 3.3.3 EXTENSION
PRINCIPLE 42 3.3.4 ALPHA LEVEL CUT 42 3.3.5 FUZZY RULES 43 3.3.6 FUZZY
RULE BASED MODEL 44 3.3.7 RULE CONSTRUCTION 45 3.3.8 ADAPTIVE NETWORK
BASED FUZZY INFERENCE SYSTEM 45 3.4 REVIEW OF APPLICATIONS 47 3.4.1 ANN
APPLICATIONS 48 3.4.2 FUZZY SYSTEMS APPLICATIONS 50 CHAPTER 4:
COMPLEMENTARY HYDRODYNAMIC, HYDROLOGICAL AND DATA DRIVEN MODELS 52 4.1
STUDY AREA : 52 4.2 AVAILABLE DATA 53 4.3 HYDRODYNAMIC NUMERIC MODEL 55
4.3.1 MODEL IMPLEMENTATION 56 4.3.2 RESULTS AND DISCUSSION 57 4.4
MUSKINGUM CUNGE HYDROLOGICAL MODEL 59 4.4.1 MODEL IMPLEMENTATION 60
4.4.2 RESULTS AND DISCUSSION 61 4.5 DATA DRIVEN MODELS 63 4.5.1 MODEL
IMPLEMENTATION 63 4.5.2 RESULTS AND DISCUSSION 64 4.6 DATA DRIVEN MODELS
BEYOND THE RANGE OF TRAINING DATASETS 67 IX CONTENTS 4.7 ASSESSMENT OF
MODELS FOR EXTREME FLOWS 71 4.8 ASSESSMENT OF MODEL CHOICES .74 4.8.1
DATA REQUIREMENT 74 4.8.2 PREDICTION CAPABILITY 75 4.8.3 EXTRAPOLATION
AND PREDICTION OF EXTREME EVENTS 76 4.8.4 MODEL DEVELOPMENT 76 4.9
CONCLUDING REMARKS 78 CHAPTER 5: COMBINED HYDRODYNAMIC AND NEURAL
NETWORK MODELS 79 5.1 STUDY AREA AND DATA 79 5.2 COMBINED HYDRODYNAMIC
AND INUNDATION MODELS .^ 81 5.3 UNSTEADY FLOW HYDRODYNAMIC MODEL 83
5.3.1 RESULTS AND DISCUSSION 84 54 UNCERTAINTIES IN THE 1993 DISCHARGE
87 5.5 ANN RIVER FLOW PREDICTION MODEL 88 5.5.1 MODEL IMPLEMENTATION 89
5.5.2 RESULTS AND DISCUSSION 90 5.5.2.1 PERFORMANCE OF THE ROCKENAU ANN
MODELS 90 5.5.2.2 PERFORMANCE OF THE SUB-REACH MODELS 91 5.5.2.3
COMBINED ANN SIMULATION MODEL 94 5.5.2.4 ANN MODELS FOR EXTREME FLOWS :
95 5.6 COMBINED HN-ANN MODEL 97 5.7 MUSKINGUM NETWORK MODEL 98 5.7.1
MODEL IMPLEMENTATION 99 5.7.2 RESULTS AND DISCUSSION 99 5.8 CONCLUDING
REMARKS 101 CHAPTER 6: UNCERTAINTY ANALYSIS OF THE STAGE DISCHARGE
RELATIONSHIP 103 6.1 STAGE DISCHARGE RELATIONSHIP 103 6.1.1
UNCERTAINTIES IN STAGE DISCHARGE RELATIONSHIP 104 6.1.2 METHODS OF
UNCERTAINTY ANALYSIS AND MANAGEMENT 105 6.2 UNCERTAINTY MANAGEMENT OF
STAGE DISCHARGE RELATIONSHIP USING ANNS 107 6.2.1 MODELLING NONLINEAR
STAGE DISCHARGE RELATIONSHIP 107 6.2.1.1 MODEL IMPLEMENTATION 108
6.2.1.2 RESULTS AND DISCUSSION : 109 6.2.2 MODELLING LOOPED RATING CURVE
111 6.2.2.1 MODEL IMPLEMENTATION : 111 6.2.2.2 RESULTS AND DISCUSSION
112 6.3 UNCERTAINTY ANALYSIS USING FUZZY REGRESSION*. 113 6.3.1 FUZZY
NONLINEAR REGRESSION MODEL 114 CONTENTS 6.3.2 FUZZY LINEAR REGRESSION
MODEL 115 6.3.3 FUZZY REGRESSION MODEL FITTING 116 6.3.4 RESULTS AND
DISCUSSION 117 6.4 UNCERTAINTY ANALYSIS IN WATER LEVEL SIMULATION 119
6.4.1 MODEL IMPLEMENTATION 120 6.4.2 RESULTS AND DISCUSSION 120 6.5
CONCLUDING REMARKS 123 CHAPTER 7: CONCLUSIONS AND PERSPECTIVES 125 7.1
CONCLUSIONS 125 7.1.1 MODEL STRENGTHS AND LIMITATIONS 125 7.1.2
COMPLEMENTARY MODELLING 127 7.1.3 UNCERTAINTY MANAGEMENT AND ANALYSIS
128 7.2 PERSPECTIVES FOR FUTURE RESEARCH 128 7.2.1 COMBINED DATA DRIVEN
AND MULTIDIMENSIONAL MODELS 129 7.2.2 INTEGRATED DATA DRIVEN AND
PHYSICALLY BASED MODELS 129 7.2.3 UNCERTAINTY ANALYSIS IN RIVER FLOOD
FORECASTING SYSTEMS 129 7.2.4 COMBINED FLOOD RISK AND UNCERTAINTY
ASSESSMENT 130 APPENDIX A: NEURAL NETWORK TRAINING ALGORITHMS 131 A.1
BACKPROPAGATION ALGORITHM 131 A.1.1 NETWORK ERRORS 132 A.1.2 ADJUSTMENT
OF WEIGHTS 132 A.2 FASTER TRAINING 134 A.2.1 NEWTON S METHOD 134 A.2.2
LEVENBERG-MARQUARDT METHOD 135 A.3 IMPROVING GENERALISATION 136 APPENDIX
B: ERROR MEASUREMENT 137 REFERENCES 138 LIST OF SYMBOLS 148 LIST OF
ACRONYMS 151 LIST OF TABLES 152 LIST OF FIGURES 153 XI
|
adam_txt |
INSTITUT FUR INV .-WR. WASSER UND GEWASSERENTWICKLUNG UNIVERSITAT
KARLSRUHE (TH) TECHNISCHE UNIVERSITAT DARMSTADT /JQ /^FT BIBLIOTHEK
WASSER UND UMWELT W PETERSENSTRATTE 13 D-64287 DARMSTADT TELEFON
06151/163659 FAX " 06151/163758 RIVER FOOD PREDICTION SYSTEMS: TOWARDS
COMPLEMENTARY HYDRODYNAMIC, HYDROLOGICAL AND DATA DRIVEN MODELS WITH
UNCERTAINTY ANALYSIS RAJESH RAJ SHRESTHA HEFT 229 MITTEILUNGEN DES
INSTITUTS FIIR WASSER UND GEWASSERENTWICKLUNG - BEREICH WASSERWIRTSCHAFT
UND KULTURTECHNIK - MIT "THEODOR-REHBOCK-WASSERBAULABORATORIUM" DER
UNIVERSITAT KARLSRUHE (TH) HRSG.: PROF. DR.-LNG. DR. H. C. MULT. FRANZ
NESTMANN, ORDINARIUS 2005 CONTENTS CONTENTS ZUSAMMENFASSUNG J SUMMARY IV
ACKNOWLEDGEMENTS VII CONTENTS -^ VIII CHAPTER 1: BACKGROUND 1 1.1
INTRODUCTION 1 1.2 FLOOD RISK AND MANAGEMENT 2 1.3 FLOOD MODELLING AND
FORECASTING SYSTEMS 3 1.4 RIVER FLOOD PREDICTION SYSTEMS 5 1.5
UNCERTAINTIES IN RIVER FLOOD PREDICTION SYSTEMS 6 1.6 RESEARCH NEEDS 7
1.7 OBJECTIVES OF THE PRESENT RESEARCH 8 1.8 STRUCTURE OF THE THESIS 9
CHAPTER 2: HYDRODYNAMIC AND HYDROLOGICAL MODELS 10 2.1 PHYSICALLY BASED
HYDRODYNAMIC NUMERICAL MODELS .10 2.1.1 SAINT VENANT EQUATIONS 11
2.1.2 ENERGY LOSS COEFFICIENT 13 2.1.3 DIMENSIONLESS NUMBERS 15 2.1.3.1
FROUDE NUMBER 15 2.1.3.2 REYNOLDS NUMBER 15 2.1.4 NUMERICAL SOLUTION OF
SAINT VENANT EQUATION 17 2.1.4.1 IMPLICIT FINITE DIFFERENCE SCHEME 17
2.1.4.2. STABILITY CRITERIA 19 2.1.5 STEADY FLOW SIMULATIONS 19 2.2
HYDROLOGICAL FLOW ROUTING MODELS 20 2.2.1 METHOD OF SOLUTION 22 2.2.2
STABILITY CRITERIA 23 2.3 REVIEW OF APPLICATIONS 23 2.3.1 FLOOD ROUTING
23 2.3.2 FLOODPLAIN MAPPING AND FLOOD RISK ASSESSMENT 24 VILI CONTENTS
CHAPTER 3: DATA DRIVEN MODELS: ARTIFICIAL NEURAL NETWORKS AND FUZZY
SYSTEMS 28 3.1 DATA DRIVEN MODELLING 28 3.2 ARTIFICIAL NEURAL NETWORKS
29 3.2.1 ACTIVATION FUNCTIONS 31 3.2.2 MULTILAYER PERCEPTRONS 32 3.2.3
DYNAMIC NEURAL NETWORKS 33 3.2.4 RADIAL BASIS FUNCTION NETWORKS 34 3.2.5
NEURAL NETWORK TRAINING 35 3.2.6 ANN MODEL CONSTRUCTION 36 3.2.6.1 DATA
SELECTION AND PRE-PROCESSING 37 3.2.6.2 DESIGN OF AN ANN MODEL 37
3.2.6.3 TRAINING, CROSS VALIDATION AND TESTING 38 3.3 FUZZY SYSTEMS 39
3.3.1 MEMBERSHIP FUNCTIONS 39 3.3.2 FUZZY NUMBERS 39 3.3.3 EXTENSION
PRINCIPLE 42 3.3.4 ALPHA LEVEL CUT 42 3.3.5 FUZZY RULES 43 3.3.6 FUZZY
RULE BASED MODEL 44 3.3.7 RULE CONSTRUCTION 45 3.3.8 ADAPTIVE NETWORK
BASED FUZZY INFERENCE SYSTEM 45 3.4 REVIEW OF APPLICATIONS 47 3.4.1 ANN
APPLICATIONS 48 3.4.2 FUZZY SYSTEMS APPLICATIONS 50 CHAPTER 4:
COMPLEMENTARY HYDRODYNAMIC, HYDROLOGICAL AND DATA DRIVEN MODELS 52 4.1
STUDY AREA : 52 4.2 AVAILABLE DATA 53 4.3 HYDRODYNAMIC NUMERIC MODEL 55
4.3.1 MODEL IMPLEMENTATION 56 4.3.2 RESULTS AND DISCUSSION 57 4.4
MUSKINGUM CUNGE HYDROLOGICAL MODEL 59 4.4.1 MODEL IMPLEMENTATION 60
4.4.2 RESULTS AND DISCUSSION 61 4.5 DATA DRIVEN MODELS 63 4.5.1 MODEL
IMPLEMENTATION 63 4.5.2 RESULTS AND DISCUSSION 64 4.6 DATA DRIVEN MODELS
BEYOND THE RANGE OF TRAINING DATASETS 67 IX CONTENTS 4.7 ASSESSMENT OF
MODELS FOR EXTREME FLOWS 71 4.8 ASSESSMENT OF MODEL CHOICES .74 4.8.1
DATA REQUIREMENT 74 4.8.2 PREDICTION CAPABILITY 75 4.8.3 EXTRAPOLATION
AND PREDICTION OF EXTREME EVENTS 76 4.8.4 MODEL DEVELOPMENT 76 4.9
CONCLUDING REMARKS 78 CHAPTER 5: COMBINED HYDRODYNAMIC AND NEURAL
NETWORK MODELS 79 5.1 STUDY AREA AND DATA 79 5.2 COMBINED HYDRODYNAMIC
AND INUNDATION MODELS .^ 81 5.3 UNSTEADY FLOW HYDRODYNAMIC MODEL 83
5.3.1 RESULTS AND DISCUSSION 84 54 UNCERTAINTIES IN THE 1993 DISCHARGE
87 5.5 ANN RIVER FLOW PREDICTION MODEL 88 5.5.1 MODEL IMPLEMENTATION 89
5.5.2 RESULTS AND DISCUSSION 90 5.5.2.1 PERFORMANCE OF THE ROCKENAU ANN
MODELS 90 5.5.2.2 PERFORMANCE OF THE SUB-REACH MODELS 91 5.5.2.3
COMBINED ANN SIMULATION MODEL 94 5.5.2.4 ANN MODELS FOR EXTREME FLOWS :
95 5.6 COMBINED HN-ANN MODEL 97 5.7 MUSKINGUM NETWORK MODEL 98 5.7.1
MODEL IMPLEMENTATION 99 5.7.2 RESULTS AND DISCUSSION 99 5.8 CONCLUDING
REMARKS 101 CHAPTER 6: UNCERTAINTY ANALYSIS OF THE STAGE DISCHARGE
RELATIONSHIP 103 6.1 STAGE DISCHARGE RELATIONSHIP 103 6.1.1
UNCERTAINTIES IN STAGE DISCHARGE RELATIONSHIP 104 6.1.2 METHODS OF
UNCERTAINTY ANALYSIS AND MANAGEMENT 105 6.2 UNCERTAINTY MANAGEMENT OF
STAGE DISCHARGE RELATIONSHIP USING ANNS 107 6.2.1 MODELLING NONLINEAR
STAGE DISCHARGE RELATIONSHIP 107 6.2.1.1 MODEL IMPLEMENTATION 108
6.2.1.2 RESULTS AND DISCUSSION : 109 6.2.2 MODELLING LOOPED RATING CURVE
111 6.2.2.1 MODEL IMPLEMENTATION : 111 6.2.2.2 RESULTS AND DISCUSSION
112 6.3 UNCERTAINTY ANALYSIS USING FUZZY REGRESSION*. 113 6.3.1 FUZZY
NONLINEAR REGRESSION MODEL 114 CONTENTS 6.3.2 FUZZY LINEAR REGRESSION
MODEL 115 6.3.3 FUZZY REGRESSION MODEL FITTING 116 6.3.4 RESULTS AND
DISCUSSION 117 6.4 UNCERTAINTY ANALYSIS IN WATER LEVEL SIMULATION 119
6.4.1 MODEL IMPLEMENTATION 120 6.4.2 RESULTS AND DISCUSSION 120 6.5
CONCLUDING REMARKS 123 CHAPTER 7: CONCLUSIONS AND PERSPECTIVES 125 7.1
CONCLUSIONS 125 7.1.1 MODEL STRENGTHS AND LIMITATIONS 125 7.1.2
COMPLEMENTARY MODELLING 127 7.1.3 UNCERTAINTY MANAGEMENT AND ANALYSIS
128 7.2 PERSPECTIVES FOR FUTURE RESEARCH 128 7.2.1 COMBINED DATA DRIVEN
AND MULTIDIMENSIONAL MODELS 129 7.2.2 INTEGRATED DATA DRIVEN AND
PHYSICALLY BASED MODELS 129 7.2.3 UNCERTAINTY ANALYSIS IN RIVER FLOOD
FORECASTING SYSTEMS 129 7.2.4 COMBINED FLOOD RISK AND UNCERTAINTY
ASSESSMENT 130 APPENDIX A: NEURAL NETWORK TRAINING ALGORITHMS 131 A.1
BACKPROPAGATION ALGORITHM 131 A.1.1 NETWORK ERRORS 132 A.1.2 ADJUSTMENT
OF WEIGHTS 132 A.2 FASTER TRAINING 134 A.2.1 NEWTON'S METHOD 134 A.2.2
LEVENBERG-MARQUARDT METHOD 135 A.3 IMPROVING GENERALISATION 136 APPENDIX
B: ERROR MEASUREMENT 137 REFERENCES 138 LIST OF SYMBOLS 148 LIST OF
ACRONYMS 151 LIST OF TABLES 152 LIST OF FIGURES 153 XI |
any_adam_object | 1 |
any_adam_object_boolean | 1 |
author | Shrestha, Rajesh Raj 1971- |
author_GND | (DE-588)130453145 |
author_facet | Shrestha, Rajesh Raj 1971- |
author_role | aut |
author_sort | Shrestha, Rajesh Raj 1971- |
author_variant | r r s rr rrs |
building | Verbundindex |
bvnumber | BV021583478 |
ctrlnum | (OCoLC)68181070 (DE-599)BVBBV021583478 |
discipline | Geologie / Paläontologie |
discipline_str_mv | Geologie / Paläontologie |
format | Thesis Book |
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genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
genre_facet | Hochschulschrift |
id | DE-604.BV021583478 |
illustrated | Illustrated |
index_date | 2024-07-02T14:42:18Z |
indexdate | 2024-07-09T20:39:12Z |
institution | BVB |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014799092 |
oclc_num | 68181070 |
open_access_boolean | |
owner | DE-M490 DE-706 DE-83 DE-634 |
owner_facet | DE-M490 DE-706 DE-83 DE-634 |
physical | xi, 157 Seiten Illustrationen, Diagramme 21 cm |
publishDate | 2005 |
publishDateSearch | 2005 |
publishDateSort | 2005 |
publisher | Inst. für Wasser und Gewässerentwicklung |
record_format | marc |
series | Mitteilungen des Instituts für Wasser und Gewässerentwicklung - Bereich Wasserwirtschaft und Kulturtechnik - mit "Theodor-Rehbock-Wasserbaulaboratorium" der Universität Karlsruhe (TH) |
series2 | Mitteilungen des Instituts für Wasser und Gewässerentwicklung - Bereich Wasserwirtschaft und Kulturtechnik - mit "Theodor-Rehbock-Wasserbaulaboratorium" der Universität Karlsruhe (TH) |
spelling | Shrestha, Rajesh Raj 1971- Verfasser (DE-588)130453145 aut River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis von Rajesh Raj Shrestha. [Institut für Wasser und Gewässerentwicklung, Universität Karlsruhe (TH)] Karlsruhe Inst. für Wasser und Gewässerentwicklung 2005 xi, 157 Seiten Illustrationen, Diagramme 21 cm txt rdacontent n rdamedia nc rdacarrier Mitteilungen des Instituts für Wasser und Gewässerentwicklung - Bereich Wasserwirtschaft und Kulturtechnik - mit "Theodor-Rehbock-Wasserbaulaboratorium" der Universität Karlsruhe (TH) 229 Zsfassung in dt. Sprache Dissertation Universität Karlsruhe 2005 Mathematisches Modell Flood forecasting Mathematical models Hydrodynamics Mathematical models Hydrologic models Computersimulation (DE-588)4148259-1 gnd rswk-swf Hochwasservorhersage (DE-588)4220751-4 gnd rswk-swf Hochwasser (DE-588)4025289-9 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Hochwasser (DE-588)4025289-9 s Computersimulation (DE-588)4148259-1 s DE-604 Hochwasservorhersage (DE-588)4220751-4 s Mitteilungen des Instituts für Wasser und Gewässerentwicklung - Bereich Wasserwirtschaft und Kulturtechnik - mit "Theodor-Rehbock-Wasserbaulaboratorium" der Universität Karlsruhe (TH) 229 (DE-604)BV035421218 229 HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014799092&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Shrestha, Rajesh Raj 1971- River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis Mitteilungen des Instituts für Wasser und Gewässerentwicklung - Bereich Wasserwirtschaft und Kulturtechnik - mit "Theodor-Rehbock-Wasserbaulaboratorium" der Universität Karlsruhe (TH) Mathematisches Modell Flood forecasting Mathematical models Hydrodynamics Mathematical models Hydrologic models Computersimulation (DE-588)4148259-1 gnd Hochwasservorhersage (DE-588)4220751-4 gnd Hochwasser (DE-588)4025289-9 gnd |
subject_GND | (DE-588)4148259-1 (DE-588)4220751-4 (DE-588)4025289-9 (DE-588)4113937-9 |
title | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis |
title_auth | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis |
title_exact_search | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis |
title_exact_search_txtP | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis |
title_full | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis von Rajesh Raj Shrestha. [Institut für Wasser und Gewässerentwicklung, Universität Karlsruhe (TH)] |
title_fullStr | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis von Rajesh Raj Shrestha. [Institut für Wasser und Gewässerentwicklung, Universität Karlsruhe (TH)] |
title_full_unstemmed | River flood prediction systems towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis von Rajesh Raj Shrestha. [Institut für Wasser und Gewässerentwicklung, Universität Karlsruhe (TH)] |
title_short | River flood prediction systems |
title_sort | river flood prediction systems towards complementary hydrodynamic hydrological and data driven models with uncertainty analysis |
title_sub | towards complementary hydrodynamic, hydrological and data driven models with uncertainty analysis |
topic | Mathematisches Modell Flood forecasting Mathematical models Hydrodynamics Mathematical models Hydrologic models Computersimulation (DE-588)4148259-1 gnd Hochwasservorhersage (DE-588)4220751-4 gnd Hochwasser (DE-588)4025289-9 gnd |
topic_facet | Mathematisches Modell Flood forecasting Mathematical models Hydrodynamics Mathematical models Hydrologic models Computersimulation Hochwasservorhersage Hochwasser Hochschulschrift |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014799092&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
volume_link | (DE-604)BV035421218 |
work_keys_str_mv | AT shrestharajeshraj riverfloodpredictionsystemstowardscomplementaryhydrodynamichydrologicalanddatadrivenmodelswithuncertaintyanalysis |