Regionalization of groundwater residence time using metamodeling

Water Resources Research
By:  and 

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Abstract

Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to degradation. A novel combination of numerical modeling and statistical methods allows estimation of regional RTDs with unprecedented speed. In this method, particle RTDs are generated in 30 type locales in the northeastern glaciated U.S using automated generalized finite-difference groundwater flow and advective transport models. Targets for statistical learning were created from particle RTDs by fitting Weibull, gamma, and inverse Gaussian distributions. Whole-basin flux-weighted RTDs were well fit by one-component Weibull distributions. Flux-weighted RTDs at stressed receptors such as wells often produced more complicated RTDs that required a two-component mixture to fit. A Multitask Lasso regression was trained on the parametric RTDs using hydrogeographic features of the modeled areas as explanatory features. In this way, RTDs are regionalized using mappable physical features such as recharge and aquifer volume. The shape, location, and scale parameters of the parametric RTDs are strongly related to the mean exponential age. The shape parameter of the distribution, which controls deviation from exponential, is additionally a function of aquifer heterogeneity and hydrologic features. Regionalized RTDs provide useful metrics with respect to groundwater lag times and solute loading to streams. The lag time between input and output contained in the RTD is critical to understanding the relation between the land surface and human and ecological receptors.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Regionalization of groundwater residence time using metamodeling
Series title Water Resources Research
DOI 10.1029/2017WR021531
Volume 54
Issue 9
Year Published 2019
Language English
Publisher Wiley
Contributing office(s) WMA - Earth System Processes Division
Description 17 p.
First page 6357
Last page 6373