Uncertainty Analysis of a Groundwater Flow Model in East‐Central Florida. Issue 3 (12th July 2014)

• Record Type: Journal Article
• Authors: Sepúlveda, Nicasio; Doherty, John
• Is Part Of: Ground water. Volume 53:Issue 3(2015:May/Jun.)
• Page Start: 464
• Page End: 474
• Publication Date: 2014-07-12
• Subjects: Groundwater -- Periodicals; Wells -- Periodicals; Eau souterraine -- Périodiques; Puits -- Périodiques; Grondwater; Eau souterraine; Puits; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 551.49
• DOI: 10.1111/gwat.12232
• Languages: English
• ISSNs: 0017-467X

Abstract

<abstract abstract-type="main" id="gwat12232-abs-0001"> <title>Abstract</title> <p id="gwat12232-para-0001">A groundwater flow model for east‐central Florida has been developed to help water‐resource managers assess the impact of increased groundwater withdrawals from the Floridan aquifer system on heads and spring flows originating from the Upper Floridan Aquifer. The model provides a probabilistic description of predictions of interest to water‐resource managers, given the uncertainty associated with system heterogeneity, the large number of input parameters, and a nonunique groundwater flow solution. The uncertainty associated with these predictions can then be considered in decisions with which the model has been designed to assist. The "Null Space Monte Carlo" method is a stochastic probabilistic approach used to generate a suite of several hundred parameter field realizations, each maintaining the model in a calibrated state, and each considered to be hydrogeologically plausible. The results presented herein indicate that the model's capacity to predict changes in heads or spring flows that originate from increased groundwater withdrawals is considerably greater than its capacity to predict the absolute magnitudes of heads or spring flows. Furthermore, the capacity of the model to make predictions that are similar in location and in type to those in the calibration dataset exceeds its capacity to make predictions of different types at different locations. The quantification of these outcomes allows defensible use of the modeling process in support of future water‐resources decisions. The model allows the decision‐making process to recognize the uncertainties, and the spatial or temporal variability of uncertainties that are associated with predictions of future system behavior in a complex hydrogeological context.</p> </abstract>