Ricker Method Well Sufficiency Analysis for Groundwater Monitoring
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Solution Overview
Problem
Current groundwater monitoring well systems rely on subjective professional judgment for modifying monitoring protocols, leading to inconsistent decisions and lack of empirical basis for determining when wells can be removed or sampling frequency reduced, resulting in inefficiencies and potential misinterpretation of plume stability.
Innovation Solution
The Ricker Method Well Sufficiency Analysis uses scientific and statistical methods to assess the sufficiency of monitoring well data by comparing plume area, concentration, and mass profiles under different sampling configurations, employing parameters like Mann-Kendall, linear regression, and correlation coefficients to determine if reducing the number of wells or sampling frequency affects plume stability evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If subjective professional judgment is used to modify monitoring protocols, then decision-making flexibility is maintained, but consistency and empirical basis of decisions deteriorate
Solution Approach 1:
The patent transforms subjective professional judgment into objective statistical parameters by calculating sufficiency metrics (e.g., Mann-Kendall trend statistics, correlation coefficients, regression analysis results) that quantitatively assess whether monitoring well data adequately characterizes plume stability. This parameter transformation enables consistent, empirical decision-making while preserving adaptability through automated evaluation of monitoring protocol modifications.
2Measurement precision
If more monitoring wells and sampling frequency are maintained, then plume stability evaluation accuracy is improved, but monitoring cost increases
Solution Approach 1:
The patent applies partial action by determining the minimum sufficient monitoring configuration through statistical sufficiency analysis. Instead of maintaining maximum monitoring intensity, the system identifies the optimal subset of wells and sampling frequency that provides adequate plume stability characterization, eliminating excessive monitoring costs while preserving evaluation accuracy through rigorous statistical criteria.
Solution Approach 2:
The system changes the parameter of monitoring intensity by using statistical sufficiency metrics to objectively determine the optimal balance between monitoring cost and evaluation accuracy. By calculating metrics such as the proportion of variance explained by monitoring data and statistical significance of plume stability trends, the system identifies cost-effective monitoring configurations that maintain sufficient measurement precision.
3Quantity of substance
If monitoring protocol is reduced, then cost is reduced, but reliability of plume stability assessment deteriorates
Solution Approach 1:
The patent implements feedback through iterative sufficiency analysis where the system evaluates whether reduced monitoring protocols maintain adequate assessment reliability. By continuously calculating statistical sufficiency metrics (e.g., trend significance, data adequacy ratios) and comparing them against predefined criteria, the system provides feedback on whether protocol reductions are acceptable, ensuring reliability is maintained while minimizing costs.
Data Source
AI summary
Disclosed are exemplified methods and systems that uses scientific and statistical basis to determine whether wells can be removed from a monitoring network and/or whether the frequency of well sampling can be reduced and/or whether the number of constituents being analyzed can be reduced. The exemplified method facilitates a more accurate and precise assessment of the sufficiency of the monitoring in decision making processes to modify the monitoring protocol of wells at a given contaminated site as well as to provide a defensible assessment and analysis that is empirical, graphical, and easy to understand.