This document discusses coupling groundwater monitoring networks with regional scale flow models to manage groundwater resources in the Almádena-Odeáxere Aquifer in Portugal. A conceptual model of the aquifer was developed considering its geometry, water budget, boundary conditions, and hydraulic parameters. An initial model simulation using homogeneous parameters did not match observed data. Additional monitoring data allowed dividing the aquifer into zones and calibrating the model parameters, improving the fit between measured and simulated values. The calibrated model provides a basis for evaluating the aquifer's behavior under different scenarios and improving groundwater management.

1. Coupling Monitoring Networks and Regional Scale Flow Models for the Management of Groundwater Resources The Almádena-Odeáxere Aquifer Case Study (Algarve-Portugal) J. MARTINS & J. P. MONTEIRO Algarve University Geo-Systems Centre UALG/CVRM Marine and Environmental Sciences Faculty, Campus de Gambelas, 8005-139 Faro, Portugal [email_address]

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

3. 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

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

14. 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

15. Almeida et al (2000) Impermeable Formations

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

17. 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

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

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

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

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

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

28. 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

29. Good fit between measured and simulated values

30. T (m 2 /day)

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

32. 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

34. 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

35. 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

36. 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

37. Future Model Uses Reliability pays off:

39. cvrm.ualg.pt

40. Thank You