Automating Recession Curve Displacement Recharge Estimation
Brennan Smith1, Stuart Schwartz2
1Currently at Versar, Inc., 9200 Rumsey Road, Columbia, MD 21045.
Ground Water
|July 9, 2016
Summary
Automating groundwater recharge estimation using a new algorithm improves accuracy and efficiency. This method objectively estimates annual recharge, complementing other data-intensive techniques for better water resource management.
Area of Science:
- Hydrology
- Hydrogeology
- Water Resource Management
Background:
- Groundwater recharge estimation is crucial for sustainable water management but presents significant challenges.
- Existing methods vary in data needs and scale applicability, necessitating the use of multiple approaches.
- Recession curve displacement offers a first-order estimate but relies on subjective baseflow recession event selection.
Purpose of the Study:
- To develop and present a parametric algorithm for objective automation of recession curve displacement.
- To overcome the subjectivity and operator-dependency in current recession index estimation.
- To facilitate consistent and automated annual groundwater recharge estimation.
Main Methods:
- Development of a parametric algorithm to automate recession curve displacement.
- Objective parameterization and automation of baseflow recession event selection.
- Implementation within a hierarchical, multi-method approach for recharge estimation.
Main Results:
- The algorithm objectively automates the estimation of recession curve displacement.
- Reproduces regional groundwater recharge estimates with an average absolute error under 2%.
- Demonstrates consistency and full automation in annual recharge estimation.
Conclusions:
- The developed algorithm provides an objective and automated method for recharge estimation.
- Enhances the utility of recession curve displacement as part of a multi-method strategy.
- Complements rigorous, data-intensive techniques for improved groundwater resource management.
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