September 9, 2015 1 Today’s topics Distributed modelling 08:45 – 09:30 Distributed catchment...
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Transcript of September 9, 2015 1 Today’s topics Distributed modelling 08:45 – 09:30 Distributed catchment...
![Page 1: September 9, 2015 1 Today’s topics Distributed modelling 08:45 – 09:30 Distributed catchment modelling 09:45 – 10:30 Choices in degree of distribution.](https://reader035.fdocuments.net/reader035/viewer/2022070407/56649e2a5503460f94b17d14/html5/thumbnails/1.jpg)
April 21, 2023
1
Today’s topicsDistributed modelling
08:45 – 09:30 Distributed catchment modelling
09:45 – 10:30 Choices in degree of distribution and data
Hope to give some relevant examples
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April 21, 2023 2
Choice of degree of distribution
How to choose the spatial representation of your model?
• Data availability (spatial distributed data?)• Which processes are you interested in?• Computational time
• Choose between lumped parameters or distributed parameters (equifinality)
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April 21, 2023 3
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April 21, 2023 4
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April 21, 2023 5
Equifinality
• How can you justify a lot more parameters??
0.79
0.8
0.81
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200 220 240 260 280 300
FC [mm]N
S c
oef
fici
ent [-] m
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0 0.2 0.4 0.6 0.8 1
Perc [mm]
NS
coef
fici
ent [-] m
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April 21, 2023 6
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April 21, 2023 7
Other data sources
Eobs
CR(FC)Pn
EsimConstraining on
evaporationConstraining on
evaporation
IP
T(FC,L)Pn
FCR
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April 21, 2023 8
Methodology
HighlandsForested
Dambos (wetlands)Riverine
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April 21, 2023 9
Results
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April 21, 2023 10
Application e.g. flood forecasting
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April 21, 2023 11
Example of distributed responses
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April 21, 2023 12
Application e.g. flood forecasting
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April 21, 2023 13
Data sources
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April 21, 2023 14
Introduction
• History: from point to grid geo-statistical interpolation, e.g.• Thiessen polygons (nearest neighbour)• Kriging (co-variance matrix approach)• Inverse distance weighted• See also: lecture notes hydrological
measurements• General problem: by interpolating, you loose
(local) extremes
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April 21, 2023 15
Introduction
• Now:• Remote sensors on satellites provide new data:• …to help estimating parameters e.g…
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April 21, 2023 16
Elevation
• Slopes• Drain direction• Catchment delineation• Wetland and lake identification
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April 21, 2023 17
Land cover
• Root zone depth• Hydrotope
delineation• Estimate of
interception capacity
• Often, links are made with extensive lookup tables (e.g. SWAT, SOBEK RR)
Interception
Uns
atur
ated
zon
eG
roun
dwat
er
Rainfall Radiation, humidity /etc.
Base flow
(Sub)surface flowTranspiration
(Sub)surface flow
1-αα
Base flow
Transpiration
RainfallRadiation, humidity /etc.
Interception
Flux
State
PercolationPercolation
Perception Model structure
River discharge
Interception
Uns
atur
ated
zon
eG
roun
dwat
er
Rainfall Radiation, humidity /etc.
Base flow
(Sub)surface flowTranspiration
(Sub)surface flow
1-αα
Base flow
Transpiration
RainfallRadiation, humidity /etc.
Interception
Flux
State
PercolationPercolation
Perception Model structure
River discharge
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Distributed model ‘wflow’
• Uses terrain analysis (derivation of flow direction, slopes, streams)
• Uses lookup tables to link model parameters with soil types, land cover classes
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04/21/23 19
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• Remote sensors on satellites provide new data:• …to help estimating parameters e.g…• …to help estimating temporally and spatially
distributed data e.g…
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April 21, 2023 21
Rainfall
• Generally based on a combination of information from different sensors
• Many rainfall products available• Tropical Rainfall Measuring Mission (TRMM,
~25x25 km, 3-hourly)• GSMaP (~10x10 km, 1-hourly)• FEWS RFE 2.0 (10x10 km, daily)• PERSIANN CCS (4x4 km, 30-min!!)
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Validation and bias-correction is often required!!!
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April 21, 2023 25
Energy budgets
• E.g. incoming solar radiation at the land surface• Provides a strong indicator for the
evaporative potential• For Europe and Africa, LSA SAF products (see
http://landsaf.meteo.pt)
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April 21, 2023 26
Energy budgets
1n solar long longR R R R
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April 21, 2023 27
Summarizing: application of remote sensing
• Provide input (e.g. rainfall, (potential) evaporation)
• May be used to constrain model structures and parameters
• Mitigating the ‘equifinality problem’ by incorporating the spatially distributed data in a performance criterium