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Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

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Stochastic hydrogeology: what professionals really need?

Philippe Renard¹

¹Centre of Hydrogeology, University of Neuchâtel, 11 Rue Emile Argand, CP 158, CH-2000 Neuchâtel, Switzerland. philippe.renard@unine.ch

|September 1, 2007

Summary

Geostatistics significantly impacts quantitative hydrogeology, yet a gap exists between academic use and routine application. Bridging this requires regulatory buy-in, market emphasis, and accessible tools for broader adoption.

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Area of Science:

Hydrogeology
Geostatistics

Background:

Quantitative hydrogeology has a long history, with geostatistics emerging as a powerful tool.
Geostatistics is routinely used for parameter interpolation and uncertainty forecasting in hydrogeology.
Academic research extensively employs geostatistics for studying physical processes in heterogeneous aquifers.

Purpose of the Study:

To highlight the gap between academic and routine geostatistical applications in hydrogeology.
To identify barriers hindering wider adoption of geostatistics in hydrogeology.
To propose strategies for bridging the gap and increasing geostatistical implementation.

Main Methods:

Review of current geostatistical practices in hydrogeology.
Analysis of factors contributing to the gap (market, technical, misconceptions).
Identification of necessary actions for broader adoption.

Main Results:

A significant gap persists between academic research and practical application of geostatistics in hydrogeology.
Barriers include market factors, lack of accessible software, and prevailing misconceptions.
Successful integration requires regulatory acceptance, market demonstration, theoretical relevance, and infrastructure development.

Conclusions:

Addressing the gap requires a multi-faceted approach involving regulators, industry, and academia.
Enhanced accessibility to software, data, and computing power is crucial.
Overcoming misconceptions and demonstrating economic value will drive wider geostatistical adoption in hydrogeology.