Factors Governing Sustainable Groundwater Pumping near a River

Abstract

The objective of this paper is to provide new insights into processes affecting riverbank filtration (RBF). We consider a system with an inflatable dam installed for enhancing water production from downstream collector wells. Using a numerical model, we investigate the impact of groundwater pumping and dam operation on the hydrodynamics in the aquifer and water production. We focus our study on two processes that potentially limit water production of an RBF system: the development of an unsaturated zone and riverbed clogging. We quantify river clogging by calibrating a time-dependent riverbed permeability function based on knowledge of pumping rate, river stage, and temperature. The dynamics of the estimated riverbed permeability reflects clogging and scouring mechanisms. Our results indicate that (1) riverbed permeability is the dominant factor affecting infiltration needed for sustainable RBF production; (2) dam operation can influence pumping efficiency and prevent the development of an unsaturated zone beneath the riverbed only under conditions of sufficient riverbed permeability; (3) slow river velocity, caused by dam raising during summer months, may lead to sedimentation and deposition of fine-grained material within the riverbed, which may clog the riverbed, limiting recharge to the collector wells and contributing to the development of an unsaturated zone beneath the riverbed; and (4) higher river flow velocities, caused by dam lowering during winter storms, scour the riverbed an thus increase its permeability. These insights can be used as the basis for developing sustainable water management of a RBF system. 2

Is high-resolution inverse characterization of heterogeneous river bed hydraulic conductivities needed and possible?

“…These interactions have a number of consequences on the hydrological, chemical and biological environment around streams. For example, the resulting exchange fluxes between these two compartments influence the regional water balance and groundwater flow (Woessner, 2000) and thus also affect the yield of management activities close to streams, such as river bank filtration (Zhang et al, 2011;Schubert, 2002). Additionally, the different chemical composition of river water and groundwater also has implications on chemical and ecological processes around streams (Brunke and Gonser, 1997;Sophocleous, 2002).…”

Recent advances in modeling of well hydraulics

“…Su et al [261] adopted the TOUGH2 to study the development of unsaturated region beneath a perennial river due to the pumping at two radial collector wells near the streams. Zhang et al [262] also used the TOUGH2 to investigate crucial factors such as riverbed permeability, dam operation and river velocity influencing aquifer recharge, maximum pumping capacity, and development of an unsaturated zone beneath the riverbed. Xu et al [266] developed a model based on Multi-Node Well package of MODFLOW to assess the effect of chemical clogging occurring around the caisson on the groundwater level.…”

“…In addition, numerical modeling can also be used for the design of collector wells or the determination of well field capacity. Several different numerical approaches were used for the simulation of flow induced by radial collector wells in the past; for example, finite difference method [260], finite element method [261,262], analytic element method [258,262,263], and boundary element method [264].…”

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

“…Moreover, it can control and interact with the simulator, should an individual forward run encounter convergence problems. To increase flexibility, iTOUGH2 supports the PEST protocol (Doherty, 2007;Finsterle and Zhang, 2011a), which links iTOUGH2's toolsets to external models. These external models can be pre-or postprocessors, or programs that are unrelated to the TOUGH suite of codes.…”

“…iTOUGH2 ; http://esd.lbl.gov/iTOUGH2) provides inverse modeling capabilities and (local and global) sensitivity and uncertainty propagation analyses for most TOUGH modules or any stand-alone simulation program (Finsterle and Zhang, 2011a). Such model-independent inverse modeling capabilities are also provided by other software packages, such as PEST (Doherty, 2010), UCODE (Poeter et al, 2014), and DAKOTA (Adams et al, 2016).…”