The three-dimensional alluvial aquifer reconstruction through deterministic method from well stratigraphical data is a well-known problem. The purpose of this study concerns the realization of a geostatistical stochastic model based on 1d Markov chains with the use of T-PROGS codes of GMS Aquaveo. This method allows to obtain the vertical transition probability of the alluvial deposits and propagate them to x-y plane through the application of Walther law. The Val di Cornia valley and San Vincenzo coastal plain constitute a unique multilayered coastal aquifer, which extends over an area of 170 square kilometers, in the southern coast of Tuscany (Italy), and it is the results of the erosional and depositional processes of the Cornia river. The better understanding of this aquifer is a crucial issue, due to its regional importance and for managing the increasing saltwater intrusion, which affects the area during the last 50 years. The model realization was initially based on 300 stratigraphic data logs coming from a water well database implemented by local authorities, subsequently integrated with HVSR data acquired for this work. The stratigraphic data were digitized and simplified in order to permit a better reconstruction. The control of the quality of the input data allowed to eliminate the stratigraphic logs that could be inconsistent with the surrounding ones, in order to avoid interpretation problems of the conceptual geological model. This filtering operation led, finally, to the selection of only 140 stratigraphic logs. The processing of this data allowed the reconstruction of the bottom of the model (the bedrock) and the realization of n-equiprobable simulations of the sedimentary hetereogeneity. The obtained geological model will allow the realization of further groundwater flow model of the Cornia Valley to be implemented in the next months.
Ricostruzione probabilistica 3D dell’acquifero alluvionale della Val di Cornia (Provincia di Livorno)
Febo, Simone
Writing – Original Draft Preparation
;De Filippis, GiovannaWriting – Review & Editing
;Rossetto, RudyWriting – Review & Editing
;
2018-01-01
Abstract
The three-dimensional alluvial aquifer reconstruction through deterministic method from well stratigraphical data is a well-known problem. The purpose of this study concerns the realization of a geostatistical stochastic model based on 1d Markov chains with the use of T-PROGS codes of GMS Aquaveo. This method allows to obtain the vertical transition probability of the alluvial deposits and propagate them to x-y plane through the application of Walther law. The Val di Cornia valley and San Vincenzo coastal plain constitute a unique multilayered coastal aquifer, which extends over an area of 170 square kilometers, in the southern coast of Tuscany (Italy), and it is the results of the erosional and depositional processes of the Cornia river. The better understanding of this aquifer is a crucial issue, due to its regional importance and for managing the increasing saltwater intrusion, which affects the area during the last 50 years. The model realization was initially based on 300 stratigraphic data logs coming from a water well database implemented by local authorities, subsequently integrated with HVSR data acquired for this work. The stratigraphic data were digitized and simplified in order to permit a better reconstruction. The control of the quality of the input data allowed to eliminate the stratigraphic logs that could be inconsistent with the surrounding ones, in order to avoid interpretation problems of the conceptual geological model. This filtering operation led, finally, to the selection of only 140 stratigraphic logs. The processing of this data allowed the reconstruction of the bottom of the model (the bedrock) and the realization of n-equiprobable simulations of the sedimentary hetereogeneity. The obtained geological model will allow the realization of further groundwater flow model of the Cornia Valley to be implemented in the next months.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.