Information about Coupling Monitoring Networks and Regional Scale Flow Models for the...

Automatic monitoring networks were settled to provide datasets for the calibration

and validation of regional flow models, as a strategy to complement data available in official

monitoring networks for the main regional aquifers in Algarve (Portugal). The Almádena-

Odeáxere aquifer system is presented as an example, where the comparative analysis of

variables representing “reality”, consisting of data obtained in these networks, was made

against values simulated with a finite element numeric model. This methodology contributed

for a better calibration and validation of the model, together with the design of effective

groundwater monitoring networks, at the regional scale.

and validation of regional flow models, as a strategy to complement data available in official

monitoring networks for the main regional aquifers in Algarve (Portugal). The Almádena-

Odeáxere aquifer system is presented as an example, where the comparative analysis of

variables representing “reality”, consisting of data obtained in these networks, was made

against values simulated with a finite element numeric model. This methodology contributed

for a better calibration and validation of the model, together with the design of effective

groundwater monitoring networks, at the regional scale.

Portugal Study Area Algarve Region Almádena-Odeáxere Aquifer System Area = 63,5 km 2 Karst Aquifer

Studied Aquifers - Project “ POCTI/AMB/57432/2004 ” Groundwater Flow Modelling and Optimisation of Groundwater Modelling Networks at the regional scale in Coastal Aquifers – The Algarve Study Algarve Region

Conceptual Model Geometry of the flow domain Water budget Definition of Boundary Conditions Temporal evolution and spatial distribution of state variables Hydraulic parameters

Geometry of the flow domain

Water budget

Definition of Boundary Conditions

Temporal evolution and spatial distribution of state variables

Hydraulic parameters

Conceptual Model Geometry of the flow domain Water budget Definition of Boundary Conditions Temporal evolution and spatial distribution of state variables Hydraulic parameters

Geometry of the flow domain

Water budget

Definition of Boundary Conditions

Temporal evolution and spatial distribution of state variables

Hydraulic parameters

Conceptual Model Precipitation / Recharge Geometry of the flow domain Water budget Definition of Boundary Conditions Temporal evolution and spatial distribution of state variables Hydraulic parameters

Geometry of the flow domain

Water budget

Definition of Boundary Conditions

Temporal evolution and spatial distribution of state variables

Hydraulic parameters

Conceptual Model Geometry of the flow domain Water budget Definition of Boundary Conditions Temporal evolution and spatial distribution of state variables Hydraulic parameters

Geometry of the flow domain

Water budget

Definition of Boundary Conditions

Temporal evolution and spatial distribution of state variables

Hydraulic parameters

Geometry of the flow domain Water budget Definition of Boundary Conditions Temporal evolution and spatial distribution of state variables Hydraulic parameters Conceptual Model Hydraulic Head

Geometry of the flow domain

Water budget

Definition of Boundary Conditions

Temporal evolution and spatial distribution of state variables

Hydraulic parameters

Conceptual Model Transmissivity Geometry of the flow domain Water budget Definition of Boundary Conditions Temporal evolution and spatial distribution of state variables Hydraulic parameters

Geometry of the flow domain

Water budget

Definition of Boundary Conditions

Temporal evolution and spatial distribution of state variables

Hydraulic parameters

Early Simulations Homogeneus T throughout the whole flow domain “ Croissant look”

Homogeneus T throughout the whole flow domain

“ Croissant look”

Hydraulic head analysis High degree of dependence between the terrain’s morphology and piezometric data Regional control of the flow pattern by conduits

Hydraulic head analysis Unexpected System Outputs High degree of dependence between the terrain’s morphology and piezometric data Regional control of the flow pattern by conduits

Almeida et al (2000) Impermeable Formations

Hydraulic head analysis Unexpected Outputs Insufficient data to provide a consistent estimate of the hydraulic behaviour of the aquifer

Hydraulic head analysis Unexpected Outputs Insufficient data to provide a consistent estimate of the hydraulic behaviour of the aquifer Need to obtain data at more points

Use of obtained data in the Model Finite Element Network Monteiro et al. (2005)

Introduction of additional “real” field data points for the model to converge Zones divided on the basis of the character of piezometric contours

M Inputs i Outputs o x describes the system’s configuration Modelling process o = M (x,p,i) Parameters (p)

M Inputs i Field Data q Parameters (p) x describes the system’s configuration The inverse problem p, i = M -1 (x,q)

M Inputs i Field Data q Parameters (p) The inverse problem p = M -1 (x,i,q) x describes the system’s configuration

Objective Function, Φ Corr. Coeficient, R 0,9 < 0,9967 Calibrated Model Gauss-Marquardt-Levenberg algorithm 5,12 4,56 5,93 v5.2 v5.1 v5

Good fit between measured and simulated values

T (m 2 /day)

Zones having smoother piezometric surfaces (Faster flow) T (m 2 /day) Porous media used “artificially”

Scale effect was observed, when comparing K values: Hydraulic Conductivity – variation with scale ( Assuming that the aquifer’s thickness, b, is 1000 m and K=T/b ) local scale values< regional scale values

Until the present work, the context of application of the AO flow model was merely the evaluation of the coherence between it’s results, existing conceptual models and historical field data. Model Outputs Borehole Scale Estimates Homogeneous distribution of parameters

Until the present work, the context of application of the AO flow model was merely the evaluation of the coherence between it’s results, existing conceptual models and historical field data. Distinguish the hydraulic behaviour of different statigraphic units Model Outputs Borehole Scale Estimates Homogeneous distribution of parameters

Until the present work, the context of application of the AO flow model was merely the evaluation of the coherence between it’s results, existing conceptual models and historical field data. First estimates of hydraulic parameters at the regional level (values ranged from 86 m 2 /day to 8158 m 2 /day Distinguish the hydraulic behaviour of different statigraphic units Model Outputs Borehole Scale Estimates Homogeneous distribution of parameters

Future Model Uses Reliability pays off:

Improved confidence on future simulations of spatial distribution and temporal evolution of state variables Basis for the development of different scenarios of the aquifer’s hydraulic behaviour by assuming different water withdrawal regimes or changes on climate conditions Future Model Uses Reliability pays off:

Improved confidence on future simulations of spatial distribution and temporal evolution of state variables

Basis for the development of different scenarios of the aquifer’s hydraulic behaviour by assuming different water withdrawal regimes or changes on climate conditions

cvrm.ualg.pt

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