Groundwater Recharge Rate and Zone Structure Estimation Using PSOLVER Algorithm

Abstract

The quantification of groundwater recharge is an important but challenging task in groundwater flow modeling because recharge varies spatially and temporally. The goal of this study is to present an innovative methodology to estimate groundwater recharge rates and zone structures for regional groundwater flow models. Here, the unknown recharge field is partitioned into a number of zones using Voronoi Tessellation (VT). The identified zone structure with the recharge rates is associated through a simulation-optimization model that couples MODFLOW-2000 and the hybrid PSOLVER optimization algorithm. Applicability of this procedure is tested on a previously developed groundwater flow model of the Tahtalı Watershed. Successive zone structure solutions are obtained in an additive manner and penalty functions are used in the procedure to obtain realistic and plausible solutions. One of these functions constrains the optimization by forcing the sum of recharge rates for the grid cells that coincide with the Tahtalı Watershed area to be equal to the areal recharge rate determined in the previous modeling by a separate precipitation-runoff model. As a result, a six-zone structure is selected as the best zone structure that represents the areal recharge distribution. Comparison to results of a previous model for the same study area reveals that the proposed procedure significantly improves model performance with respect to calibration statistics. The proposed identification procedure can be thought of as an effective way to determine the recharge zone structure for groundwater flow models, in particular for situations where tangible information about groundwater recharge distribution does not exist.

Comparison between MODFLOW Groundwater Modeling with Traditional and Distributed Recharge

“…One of the most relevant elements in groundwater modeling is the representation of recharge as an input component to the subsurface model because it varies spatially and temporally [13][14][15][16]. Changes in land use significantly alter recharge patterns associated with the hydrological cycle [17] and are linked to population increase [2].…”