Abstract

The Morroa aquifer located in Sucre state (northern Colombia) represents the exclusive source of water supply for nearly 500.000 people, including the capital of the state Sincelejo. Although multiple studies have been performed in this area, and a considerable amount of data including piezometric levels, stratigraphy at wells, and pumping tests has been collected; this information is in general fuzzy, heterogeneous and incomplete. The uncertainty in this information affects any quantification of the response of the aquifer. Therefore a methodology able to account for all of the available data and integrate it in a comprehensive conceptual model represents the starting point of our investigation. The uncertainty is accounted for by generating multiple realizations of the aquifer, so that these realizations honor statistical properties of the data. To generate the realizations, two different methods were employed: (1) the well-known Sequential Indicator method (SISIM) which is a semi-variogram based geostatistic method; and (2) the multiple-point geostatistics algorithm SNESIM, based on the concept of training images that represents the database of geological patterns, from which multiple-point statistics are borrowed. Results of the geostatistics simulations show the great ability of MPS to reproduce complex curve heterogeneities. Flow and transport simulations are performed using two different conceptual models of the Morroa aquifer considering heterogeneities. Steady-state flow and conservative contaminant were assumed. Results show a considerable influence of heterogeneity and the geostatistic method used to generate the conceptual model, i.e. two-points or multiple-point geostatistics. In particular, large differences on the aquifer response distribution were observed that may have an important effect on the design of mid- and large term water management policies regarding both quantity and quality at the Morroa aquifer, as well as on the design of remediation techniques.

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