Exploratory data analysis and clustering of multivariate spatial hydrogeological data by means of GEO3DSOM, a variant of Kohonen's Self-Organizing Map

International audienceThe use of unsupervised artificial neural network techniques like the self-organizing map (SOM) algorithm has proven to be a useful tool in exploratory data analysis and clustering of multivariate data sets. In this study a variant of the SOM-algorithm is proposed, the GEO3DSOM, capable of explicitly incorporating three-dimensional spatial knowledge into the algorithm. The performance of the GEO3DSOM is compared to the performance of the standard SOM in analyzing an artificial data set and a hydrochemical data set. The hydrochemical data set consists of 141 groundwater samples collected in two detritic, phreatic, Cenozoic aquifers in Central Belgium. The standard SOM proves to be more adequate in representing the structure of the data set and to explore relationships between variables. The GEO3DSOM on the other hand performs better in creating spatially coherent groups based on the data

Assessing the effects of spatial discretization on large-scale flow model performance and prediction uncertainty

Large-scale physically-based and spatially-distributed models (>100 km2) constitute useful tools for water management since they take explicitly into account the heterogeneity and the physical processes occurring in the subsurface for predicting the evolution of discharge and hydraulic heads for several predictive scenarios. However, such models are characterized by lengthy execution times. Therefore, modelers often coarsen spatial discretization of large-scale physically-based and spatially-distributed models for reducing the number of unknowns and the execution times. This study investigates the influence of such a coarsening of model grid on model performance and prediction uncertainty. The improvement of model performance obtained with an automatic calibration process is also investigated. The results obtained show that coarsening spatial discretization mainly influences the simulation of discharge due to a poor representation of surface water network and a smoothing of surface slopes that prevents from simulating properly surface water-groundwater interactions and runoff processes. Parameter sensitivities are not significantly influenced by grid coarsening and calibration can compensate, to some extent, for model errors induced by grid coarsening. The results also show that coarsening spatial discretization mainly influences the uncertainty on discharge predictions. However, model prediction uncertainties on discharge only increase significantly for very coarse spatial discretizations.Peer reviewe

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

Caractérisation isotopique des eaux du granite et de l’auréole métamorphique d’Oulmès (Maroc central)

Dans le bassin d’Oulmès sont exploitées et commercialisées par la société des Eaux Minérales d’Oulmès qui constitue le plus gros embouteilleur d’eaux minérales du Maroc :Sidi Ali Lala Haya. Le pluton granitique, d’âge hercynien, d’Oulmès est un granite à biotite et muscovite. Il présente une fracturation très marquée et un système filonien très développé. L’altération, très poussée, se manifeste par une arénitisation généralisée qui s’étend en profondeur. Le kaolin caractérise cette altération d’origine hydrothermale. L’eau de Lalla Haya émerge dans les granites à la faveur de fissures à une température de 42°C, il s’agit d’une eau carbo-gazeuse, bicarbonatée sodique. L’auréole métamorphique générée par ce granite englobe la formation des schistes en dalles, roches métapélitiques cambro-ordoviciennes homogènes. L’eau de Sidi Ali est faiblement minéralisée, elle aussi bicarbonatée sodique avec une pression partielle de CO2 non négligeable L’utilisation de l’outil isotopique a permis de préciser un certain nombre de points concernant la recharge et l’écoulement des eaux souterraines dans le bassin d’Oulmès. Les teneurs en 18O d’une vingtaine de sources situées autour du site et étagées entre 300 et 2000 m s’alignent suivant un gradient de -0,21 ‰ / 100 m. La zone de recharge commune des eaux du granite et des schistes en dalle se situe vers 1100/1300 m. De plus le rapport 18O/D pour ces deux types d’eau indique un appauvrissement en 18O de près de 1 ‰ dû à un échange avec le CO2 magmatique. Le temps de séjour moyen des eaux dans l’auréole métamorphique est de quelques dizaines d années (présence de 3H thermonucléaire) et, au moins, de plusieurs centaines d’années dans les eaux du massif granitique (absence de 3H thermonucléaire). De la remontée de CO2 magmatique, à 14C mort, il résulte que la teneur en 14C du carbone minéral dissous est quasiment nulle et qu’il vieillit, plus ou moins, les activités en 14C du carbone minéral dissous des eaux de l’auréole. En conclusion l’eau qui s’infiltre dans les fractures du massif granitique où elle se réchauffe suivant un gradient géothermique d’environ 40°C/km. Comme le géothermomètre Na/K indique une température de 165 °C, elle atteint une profondeur de l’ordre de 2 à 3 km. Elle s’est enrichie en CO2 magmatique et remonte par effet de gaz lift et donne naissance à Lalla Haya. Cette remontée ne se limite pas au seul massif granitique mais s’étend à l’auréole métamorphique en profitant des fractures du massif et des filons de quartz en provenance du batholite où elle se mélange, en proportions variables, aux eaux récentes qui se sont infiltrées directement sur les schistes en dalles. Ce sont ces fluides hydrothermaux qui ont donné naissance aux dépôts hydrothermaux autrefois exploités en mines (Sn)

Groundwater flow modelling in the central zone of Hanoi, Vietnam

On the basis of a review of the Quaternary sedimentary architecture in the area of Hanoi city (Vietnam), a numerical, deterministic and three-dimensional groundwater flow model has been built for a simulation between 1995 and 2004. The sedimentary architecture has been constructed on the basis of the data from 32 drillings covering the entire Quaternary sequence (but with little sedimentological detail), as well as hydrographical and hydrogeological data. Both steady- and transient-state conditions were tested. Results calculated by the model seem to indicate that the conceptual hypotheses adopted are reasonable for the modelled domain and period. The simulation allows for calculation of the regional groundwater flow trends. It is also used for assessing the relative importance of the various recharge sources of the shallow aquifer system in Hanoi, and for estimating the interactions between groundwater and the Red River

A framework for an optimised groundwater monitoring network and aggregated indicators

The implementation of the Water Framework Directive (EU 2000) requires a groundwater quality monitoring. It is used for characterisation of the 'good' chemical status of each groundwater body and for the restoration or protection purposes of those bodies already at 'good' status. Interpretative aspects are lying in the design of monitoring network and in the way of building global indicators. Attention is given here to the global chemical status of the groundwater bodies and to the role of diffuse pollution, much of which is brought via groundwater to surface water. Monitoring 'local' pollution associated with individual sites is not addressed. Groundwater bodies with different contrasted hydrogeology conditions, land use and topography have been considered to establish an approach for choosing an optimised monitoring network. Then, a quality assessment system has been developed and applied for qualifying the general status of each groundwater body. The use of non-dimensional indexes allows us to process with all kinds of chemical parameters in a normalised way and, by means of adequate aggregation rules, to qualify the general quality status of a groundwater body. The obtained diagnostic, even if not fully validated, is closely linked to the pragmatic objectives contained in the EU Water Directive