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Estimating extreme river discharges in Europe through a Bayesian network
Dominik Paprotny
,
Oswaldo Morales Napoles
Hydraulic Structures and Flood Risk
Research output
:
Contribution to journal
›
Article
›
Scientific
›
peer-review
32
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Citations (Scopus)
122
Downloads (Pure)
Overview
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Research output
(1)
Datasets
(1)
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Dive into the research topics of 'Estimating extreme river discharges in Europe through a Bayesian network'. Together they form a unique fingerprint.
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Earth and Planetary Sciences
Estimating
100%
River Discharge
100%
Europe
100%
Model
100%
River
50%
Show
33%
Climate
33%
Climate Change
33%
Accuracy
33%
Information
33%
Covering
16%
Position (Location)
16%
Domain
16%
Region
16%
Flood
16%
Proving
16%
Land Use
16%
Hydrology Models
16%
Investigation
16%
Landscape
16%
Watershed
16%
Hazard
16%
Geographical Characteristics
16%
Variation
16%
Dependence
16%
Input
16%
Estimate
16%
Correlation
16%
Size
16%
Random Variable
16%
Approach
16%
Catchment
16%
Station
16%
Statistical Analysis
16%
Continent
16%
Sample
16%
Return Period
16%
INIS
europe
100%
rivers
100%
information
40%
accuracy
40%
climatic change
40%
modeling
40%
climates
40%
prediction
20%
hydraulics
20%
power
20%
coverings
20%
distribution
20%
variations
20%
hazards
20%
floods
20%
correlations
20%
randomness
20%
physics
20%
performance
20%
statistical models
20%
data
20%
size
20%
land use
20%
validation
20%
Engineering
River
100%
Models
80%
Climate Change
40%
Accuracy
40%
Physical Model
20%
Random Variable ξ
20%
Return Period
20%
Coverage
20%
Land Use
20%
Characteristics
20%
Statistical Model
20%
Performance
20%
Input Information
20%
Joint Distribution
20%
Computational Power
20%
Prediction
20%
Hydraulics
20%
Correlation
20%
Hazards
20%
Keyphrases
Extreme Discharge
100%
Dependency Structure
33%
Large-scale Hydrological Model
33%
Gauging Stations
33%
Conditional Correlation
33%
Extreme Distribution
33%
Discharge Prediction
33%
Catchment Area
33%
Dependent Random Variables
33%
Split-sample Tests
33%
River Gauge
33%
Annual Return
33%