session 4 metrology and data transmission
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9th Conference on Limestone Hydrogeology in Besançon 9ième Colloque d'Hydrogéologie en Pays Calcaire à Besançon. Session 4 Metrology and data transmission “Artificial neural network for karst aquifer sustainable management” Marc Lambert Manager of Syndicat des Eaux du Vivier. - PowerPoint PPT PresentationTRANSCRIPT
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9th Conference on Limestone Hydrogeology in Besançon
9ième Colloque d'Hydrogéologie en Pays
Calcaire à BesançonSession 4
Metrology and data transmission
“Artificial neural network for karst aquifer sustainable
management”
Marc Lambert
Manager of Syndicat des Eaux du Vivier
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The Syndicat des Eaux du Vivier« SEV » in a few figures
– 5 municipalities including the city of Niort
– about 100.000 people depending on the Vivier karstic spring
– 650 km water networks, 36000 compteurs, 5 main water resources
– 60 agents, in public management– Hospitals, industry with SEVESO sites,
schools…)
9th Conference on Limestone Hydrogeology in Besançon
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What are the mains problems?– Agricultural area with intensive
production– Competition with water supply– Limited and fragile underground
resources, with 2 observed karstic collapses in Vivier spring
– Quality problems due to nitrates and pesticides
9th Conference on Limestone Hydrogeology in Besançon
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Our main purposes about quantity
– Securize water supply on our area– Understand and anticipate needs
(peaks, periodicity)– Understand and modelize water
resources (rain effect, cycles, pumping effects…)
– Criterion:
« water resources always > peak needs »
9th Conference on Limestone Hydrogeology in Besançon
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Geological context9th Conference on Limestone Hydrogeology in Besançon
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Geological context (AB cut)9th Conference on Limestone Hydrogeology in Besançon
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Vivier karst observed behaviour
9th Conference on Limestone Hydrogeology in Besançon
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Effects of pumpings forirrigation and water supply
9th Conference on Limestone Hydrogeology in Besançon
IMPACT DES PRELEVEMENTS AGRICOLES SUR LA RESSOURCE DE NIORT
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
oct-01 avr-02 oct-02 avr-03 oct-03 avr-04 oct-04
SEMESTRES SECS / DE RECHARGE
Dé
bit
So
urc
e (
m3
/s)
/Niv
Pu
its
(-m
)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
PR
EL
EV
EM
EN
TS
(A
EP
/AG
RI)
m3
/s
canal
rabattement dans lepuits du Vivier (m)
besoin Niort (V+G)(m3/s moyensmensuels)
Irrigation (m3/smoyens mensuels)données estiméespour secteur 13
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Methodology followed– 1 : Data collecting, selecting…and mining
(ACP, geostatistics, wavelets…)– 2 : Modelling with different techniques
(lumped modelling of rainfall – runoff and rainfall aquifer level, inverse modelling using fourier analysis, neural networks…)
– 3: Forecasting with rainfall simulation– 4: Managing resources…ie how to keep
« water resources always > peak needs »
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Rainfall data analysis9th Conference on Limestone Hydrogeology in Besançon
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Inverse modelling (TEMPO BRGM)
9th Conference on Limestone Hydrogeology in Besançon
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Inverse modelling (TEMPO BRGM)
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Hydrological modelling (GARDENIA BRGM)
9th Conference on Limestone Hydrogeology in Besançon
RUMAX déficit maximal du sol
RUIPER Hauteur d'équiRuissellement Percolation
THG Temps ½ percolation
Percolation(RECHARGE de la nappe)
PLUIE EFFICACE
Q = SURF * EC + Qo NP = G / S + NB
Écoulement total(DEBIT du cours d'eau)
Niveau Piézom. NPDébit Q
PLUIE ETP
Surface du bassin versant
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Hydrological modelling (GARDENIA BRGM)
9th Conference on Limestone Hydrogeology in Besançon
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Artificial neural network modelling (Neuro one Netral)
9th Conference on Limestone Hydrogeology in Besançon
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9th Conference on Limestone Hydrogeology in Besançon
Artificial neural network modelling
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9th Conference on Limestone Hydrogeology in Besançon
Example of use of this model:Crisis anticipation and management
CROISEMENT ENTRE RESSOURCES DISPONIBLES ET BESOINS - ETIAGE 2005
0
10000
20000
30000
40000
50000
60000
70000
80000
01/01/05 01/07/05 01/01/06
vo
lum
es
en
m3
/j
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
rab
att
eme
nt
(<0
) et
plu
ie (>
0)
en
m
Ress.princ.V+GI+GIII+Canal(m3/j)
Consommationm3/j
Secoursnécessaire m3/j
pluies (m)
rabattementVivier (m)
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9th Conference on Limestone Hydrogeology in Besançon
Conclusion: advantages of ANN tools
– After choosing a good model, easy qnalytical formulation under Excel…
– « Intelligent » black box, but to use under constraints (learning sets must include extrem years)
– Easy to use for simulations (pumpings for irrigation or water supply, climate…)
– Easy to use for sensitivity analysis