SMART Seminar Series: Development and comparison of two interaction indices between extractive activity and groundwater resources

Development and comparison of two interaction indices betweenextractive activity and groundwater resources

J. Barthélemy, T. Carletti, L. Collier, V. Hallet, M. Moriamé, A. Sartenaer

SMART (University of Wollongong, Australia)

NAXYS (University of Namur, Belgium)

July 2015 - Wollongong

Barthélemy et al. (SMART - NAXYS) Interaction indices July 2015 1 / 19

Outline

1 Introduction and motivation

2 Interaction index and parameters

3 Discrete choice-based Logit indicator

4 Neural network-based indicator

5 Application

6 Conclusions


Introduction and motivation

Underground resources: water and rock

Population density and environmental pressures⇓

Limited lateral quarry extension⇓

Excavate deeper⇓

Aquifer level reached⇓

Pumping systems to depress the water table⇓

Need to assess the environmental impact⇓

Interaction index

The Neufvilles quarry (Belgium)

Maximal dewatering flow of2.000.000 m3/year

Water table dropped from 70mdown to 25m.


Quarries and groundwater in Wallonia (Belgium)

Area: 16,844 km2

Population: 3 585 214 (210/km2)

Quarries: 160 sites, 73 × 106 T/year

Groundwater: 380.4 × 106 m3/year


Interaction index

Interaction index (Dauphiné and Provitolo, 2003)

I = f (Quarry , Groundwater)

Interaction index Feasibility studylow hydrogeology characterization

medium low + piezometric monitoringhigh medium + steady state (static) mathematical model

very high high + transient state (dynamic) mathematical model


Quarry Parameters: Hazard

Geological contextG1 completely isolated by other formations with low permeabilityG2 limited extension and partly compartmentalizedG3 local extensionG4 regional extension

Hydrogeological contextH1 aquiclude formationH2 aquitard formationH3 aquifer formationH4 carbonate aquifer formation

Piezometric context: altimetric level of the quarry floorZ1 higher than the piezometric level of the water tableZ2 lower than the piezometric level of the water table but higher than the river thalweg

which is the regional base levelZ3 lower than the piezometric level of the water table and the altimetric level of the

river thalweg which is the regional base levelZ4 lower than the piezometric level of the water table and the altimetric level of the

river thalweg which is not the regional level any more (the river is perched)


Quarry Parameters: HazardPiezometric context


Groundwater Parameters: Vulnerability

Relative position of the quarry and the water catchments

C1 outside the drainage zone of a catchmentC2 in the drainage zone of a catchmentC3 in the distant prevention area of a catchment (50 days of delay in case of aquifer

contamination)C4 in the close prevention area of a catchment (24 hours of delay in case of aquifer

contamination)Production of the catchments

T1 lower than 2 m3/hT2 between 2 and 10 m3/hT3 between 10 and 30 m3/hT4 greater than 30 m3/h

Potential quality of the catchmentsL1 poor qualityL2 water potabilisable with minor treatmentL3 good quality waterL4 water of exceptional quality (mineral water)


Dataset: Physically feasible combination of the quarry parameters with I

Id Interaction index H Z G C T L1 low 1 1 1 1 1 12 low 1 1 1 2 1 13 low 1 1 1 3 1 1...

......

......

......

...1511 medium 4 3 2 1 1 11512 medium 4 3 2 2 1 11513 medium 4 3 2 3 1 1

..

....

..

....

..

....

..

....

2198 high 4 1 1 3 2 42199 high 4 1 1 4 2 42200 high 4 1 1 3 3 2

......

......

......

......

3325 very high 4 4 4 2 4 43326 very high 4 4 4 3 4 43327 very high 4 4 4 4 4 4


First Index: Logit-based approach

Logit discrete choice model

Probability that entity n selects alternative i associated with utility Uin

Uin = Vin (observable) + ǫin (hidden)

Pin = P(Uin > Ujn) = P(ǫjn − ǫin < Vin − Vjn, ∀ j 6= i)

ǫin independent and F (ǫin) = e−e−ǫin

⇒ Pin =eVin

∑

k eVkn


Logit-based index

Model

Vl = 0

Vm = βm +4

∑

k=1

(

βmg,kGk + βm

h,kHk + βmz,kZk + βm

c,kCk + βmt,kTk + βm

l,kLk

)

Vh = βh +4

∑

k=1

(

βhg,kGk + βh

h,kHk + βhz,kZk + βh

c,kCk + βht,kTk + βh

l,kLk

)

Vv = βv +4

∑

k=1

(

βvg,kGk + βv

h,kHk + βvz,kZk + βv

c,kCk + βvt,kTk + βv

l,kLk

)

Summary statistics (BIOGEME)Number of estimated parameters 48Number of observations 3327Null log-likelihood L(0) -4612.201

Final log-likelihood L(β̂) -1754.804ρ2 0.620ρ̄2 0.609Diagnostic Convergence reachedVariance-covariance from analytical Hessian


Logit-based Index: Estimated parameters (BIOGEME)

k β̂ig,k

β̂ih,k

β̂iz,k

β̂ic,k

β̂it,k

β̂il,k β̂i

Vm

1 0.00 0.00 0.00 0.00 0.00 0.00

-9.422 -0.38 0.00 2.21 3.26 0.45 4.083 -0.39 2.97 4.65 5.35 1.69 4.644 -0.44 2.97 4.59 5.34 4.50 4.78

Vh

1 0.00 0.78 -5.35 -6.92 -3.57 -7.20

-1.972 0.00 0.00 0.00 0.00 0.00 0.003 0.00 5.11 3.88 4.99 2.97 1.914 0.00 5.11 3.84 5.35 6.47 3.24

Vv

1 0.00 -7.36 -16.90 -23.50 -13.00 -13.90

24.202 0.00 -8.96 -7.69 -8.48 -6.16 -3.663 0.00 0.00 0.00 0.00 0.00 0.004 0.00 0.00 0.00 0.78 2.53 3.30


Second Index: Artificial neural network-based approach

Decision rule

I = arg max

l,m,h,v

{Ol ,Om,Oh,Ov}

Logistic activation function

f (Hi ) = max

{

0,1

e−∑

k wki Ik− θi

}


Feed-forward neural network: Choosing the right design

Proportion of correct prediction with respect to the number of nodes in the hidden layer

⇒ 7 nodes in the hidden layer (92.19% of correct predictions)

Training: R neuralnet package, 75% training, 25% validation


Application on the Boverie quarry and the Tridaine spring (Lhoist Group)

G2,H4,Z1,C4,T4,L3

Tridaine Spring

Provide water to Rochefort andSaint-Remy’s abbey (beer!)

Boverie quarry

High purity limestone ($$$)

Google Earth


Application on the Boverie quarry and the Tridaine spring (Lhoist Group)Current situation

G2,H4,Z1,C4,T4,L3

Logit:Pl ≤ 0.01%, Pm = 1.50%, Ph = 66.4%, Pv = 32.1%

⇒ high level of interaction likely, but very high must no be ruled out!

ANN:Ol = 0.002, Om = 0.001, Oh = 0.037, Ov = 0.960

⇒ very high level of interaction.

Recommendation

Complete mathematical hydrodynamic and geographic modelling!(Dassargues et al., 2012)


Application on the Boverie quarry and the Tridaine spring (Lhoist Group)Deepening the quarry

Altimetric levels

current: 220 m groundwater: 215.5 m planned: 160 m

Z1 ⇒ Z4

Logit:Pl ≤ 0.01%, Pm ≤ 0.01%, Ph ≤ 0.01%, Pv = 99.9%


ANN:Ol = 0.002, Om = 0.001, Oh = 0.035, Ov = 0.962


Recommendation

Same as previously!


Conclusion and future work

2 interaction indices between extractive activity and groundwater resources

AAN and Logit-based indices

Depenging on I , operator will conduct an appropriate feasibility study

Satisfactory results and successfully applied on one quarry

Accuracy: ANN > Logit

ANN and Logit complementary:→ Logit is probabilistic→ ANN is a deterministic black box

Future work

Extension to other type of mining activities

Testing alternative ANN designs, decision trees, discrete choice models,...


Thank you for your attention! And...


Education

SMART Seminar Series: Development and comparison of two interaction indices between extractive activity and groundwater resources