Transient Recharge Estimability Through Field-Scale Groundwater Model Calibration.

Area of Science:

• Hydrogeology
• Environmental Modeling

Background:

• Groundwater model calibration for recharge estimation faces non-uniqueness issues with aquifer parameters.
• Steady-state models require extensive data for spatially distributed recharge estimation.
• The impact of transient model calibration on temporal recharge variability is not well understood for practical applications.

Purpose of the Study:

• To investigate the estimability of time-varying groundwater recharge through transient model calibration.
• To assess the influence of hydraulic parameter constraints, data availability, and temporal resolution on recharge estimation.
• To determine the practicality of estimating temporal recharge variability in field-scale aquifer settings.

Main Methods:

• Utilized a synthetic reality based on a field-scale, highly parameterized groundwater model.
• Systematically varied constraints on hydraulic conductivity (K) and specific yield (Sy).
• Evaluated the impact of the number of water-level calibration targets and temporal resolution on recharge estimation using identifiability statistics.

Main Results:

• Reasonable monthly recharge estimates ( <30% RMSE) necessitate substantial transient water-level data and known spatial distribution of K.
• Jointly estimating recharge, Sy, and K significantly hinders the accurate inference of recharge and hydraulic parameters.
• The study highlights the sensitivity of recharge estimation to parameter uncertainty and data limitations.

Conclusions:

• Estimating temporal recharge variability via model calibration may be impractical for real-world groundwater management.
• Careful consideration of data requirements and parameter identifiability is crucial for reliable groundwater modeling.
• Future research should focus on advanced techniques to overcome non-uniqueness challenges in recharge estimation.