Simple probabilistic and statistical risk calculations in an aquifer

Area of Science:

• Hydrogeology
• Environmental Science
• Statistical Modeling

Background:

• Groundwater resource assessment traditionally relies on point estimates, which often fail to capture inherent uncertainties in hydrogeological parameters.
• Variability and randomness in parameters like aquifer properties significantly impact the accuracy of groundwater storage and flow estimations.
• Existing methodologies may not adequately address the statistical nature of groundwater phenomena on a regional scale.

Purpose of the Study:

• To propose an objective methodology for assessing potential groundwater yield that incorporates uncertainty and randomness in hydrogeological parameters.
• To develop a systematic approach for selecting aquifer parameters to achieve reliable groundwater storage and subsurface flow estimates.
• To provide a framework for calculating probable interval estimates of groundwater resources, moving beyond conventional point estimates.

Main Methods:

• Utilizing statistical randomness to model regional groundwater phenomena.
• Employing a systematic approach for selecting key aquifer parameters.
• Applying a perturbation approach to calculate average specific groundwater capacity and subsurface flow rates.
• Generating probability distribution functions for aquifer storage and subsurface flow estimates.

Main Results:

• Demonstrated that cross-correlations between hydrogeologic variables can lead to under- or overestimation of model parameters.
• Obtained aquifer storage and subsurface flow estimates in the form of probability distribution functions.
• Confirmed that surface flow rates follow a log-normal distribution.
• Developed a methodology yielding probable interval estimates instead of single point estimates.

Conclusions:

• The proposed methodology offers a more objective and reliable assessment of potential groundwater yield by embracing parameter uncertainty.
• The use of probability distribution functions provides a more comprehensive understanding of groundwater storage and flow dynamics.
• This approach enables more accurate projections of future groundwater availability and subsurface flow rates.