Integration of spatio-temporal recharge assessment in groundwater model applied to semi-arid environment
|Graduate student||Alain Francés|
|Promotors||To be appointed|
|Co-promotors||Dr. M.W. Lubczynski|
|Timeline||March 2008 - March 2011|
|Sources of funding||FCT (Portuguese Science Foundation)|
Numerical flow models are nowadays a powerful tool for groundwater management. They allow to predict dynamic responses of the aquifers in reaction to various groundwater abstraction scenarios and climatic or land use changes. A reliable groundwater model requires both an accurate physical representation of an aquifer system and appropriate boundary conditions. While parameters like hydraulic conductivity (K) and storativity (S) are spatially dependent and time invariant, groundwater fluxes such as recharge (R), evapotranspiration from groundwater (ETg) and groundwater inflow/outflow (Qgw) can vary in both space and time. Multiplicity of combinations between parameters and fluxes leads to a non-uniqueness of model solutions which limits their reliability and forecasting capability.
In this PhD study, I propose to implement a methodology to reduce the number of solutions of the groundwater models based on the coupling and the transient resolution of: (1) a distributed conceptual unsaturated zone model, (2) a three-dimensional groundwater flow model and (3) a three-dimensional groundwater solute transport model.
The specific tasks are:
- intensive meteorological and hydrogeological data acquisition through monitoring stations equipped with Automatic Data Acquisition System (ADAS;
- design and implementation of a GIS-based Relational Data Base Management System (GIS-RDBMS) for efficient storage and management of meteorological and hydrogeological data;
- hydrogeophysics-based data acquisition schemes to improve the parameterization of the unsaturated/saturated reservoirs;
- development of data integration techniques to incorporate the parameters in the unsaturated/saturated models;
- development and implementation of a distributed conceptual water balance model of the unsaturated zone to compute recharge;
- dynamic coupling and calibration of the distributed recharge model with groundwater numerical flow and solute transport model using PEST.
Besides the improvement of groundwater model reliability, the coupling approach of both unsaturated/saturated models also allows to take into account the partitioning of fluxes into unsaturated/saturated zones. This is particularly important in dry water limited environment (WLE) where the ETg component plays a significant role in the water balance and is generally underestimated in groundwater modelling and resources management.
The methodology will be tested in semi-arid and arid catchments in Portugal, Spain and Botswana.
Pictures data acquisition and integration (monitoring)
|Micrometeorological ADAS (Left: COTR, Portugal; right: Sardon, Spain)|
|Depth-wise soil moisture monitoring (Pisoes, Portugal).|
|Soil moisture profile s (4) installation in a transect perpendicular to a Quercus ilex.|
Pictures data acquisition and integration (Hydrogeophysics)
|EM-31 instrument (Pisoes, Portugal)|
|Apparent electrical conductivity (ECa) and drilling locations plotted on QuickBird image |
(natural colour). Higher values of ECa are related to higher thickness of clayey topsoil in the
depressed drainage area of the catchment (measurements with EM31 device on the ground in
vertical position) (Pisoes, Portugal)
|Tracer test monitored with ERT (Sardon, Spain) to derive solute transport parameter.|
|ERT profile: blue colour indicate saturated zone, dark blue indicate the NaCl plume.|
Pictures data acquisition and integration (Sampling)
|Drilling operation with percussion hammer Cobra for depth-wise sampling (Pisoes, Portugal).|
|Core obtained by drilling (thickness and soil moisture measurements and sampling for further |
|Drilling operation with percussion hammer Cobra for piezometer construction (Sardon, Spain).|
|DGPS survey (piezometer levelling) and water sampling (laboratory analysis).|
Pictures data acquisition and integration (remote sensing data integration)
|Soil classification in clay (light pink) and calcrete (grey) + other land covers.|
|Profiles of soil electrical conductivity obtained using EM31 apparent conductivity |
(depth of 6 meters) (Pisoes, Portugal).
|Topsoil thickness map obtained by integration of EM31 geophysical measurements, remote |
sensing classification and geostatistical interpolation.
Picture data acquisition and integration (distributed recharge model)
|Recharge assessment using distributed conceptual model (Pisoes, Portugal)|
Picture data acquisition and integration (groundwater models)
|Hydraulic heads of the steady state flow model (left) and chloride concentrations of solute |
transport model (right) (Sardon, Spain).