Simulation of ground-water flow, surface-water flow, and a deep sewer tunnel system in the Menomonee Valley, Milwaukee, Wisconsin

Abstract

Numerical models were constructed for simulation of groundwater flow in the Menomonee Valley Brownfield, in Milwaukee, Wisconsin. An understanding of groundwater flow is necessary to develop an efficient program to sample ground water for contaminants. Models were constructed in a stepwise fashion, beginning with a regional, single-layer, analytic-element model (GFLOW code) that provided boundary conditions for a local, eight layer, finite-difference model (MODFLOW code) centered on the Menomonee Valley Brownfield. The primary source of ground water to the models is recharge over the model domains; primary sinks for ground water within the models are surface-water features and the Milwaukee Metropolitan Sewerage District Inline Storage System (ISS). Calibration targets were hydraulic heads, surfacewater fluxes, vertical gradients, and groundwater infiltration to the ISS. Simulation of groundwater flow by use of the MODFLOW model indicates that about 73 percent of recharge within the MODFLOW domain circulates to the ISS and 27 percent discharges to gaining surface-water bodies. In addition, infiltration to the ISS comes from the following sources: 36 percent from recharge within the model domain, 45 percent from lateral flow into the domain, 15 percent from Lake Michigan, and 4 percent from other surface-water bodies. Particle tracking reveals that the median traveltime from the recharge point to surface-water features is 8 years; the median time to the ISS is 255 years. The traveltimes to the ISS are least over the northern part of the valley, where dolomite is near the land surface. The distribution of traveltimes in the MODFLOW simulation is greatly influenced by the effective porosity values assigned to the various lithologies.

Tunnel Inflow Monitoring in Permeable Rocks Nearby Cannero River, Piedmont (Northern Italy)

“…This importance has already been demonstrated in numerical modeling studies of Dunning et al (2004), about the Menomonee Valley tunnel. The Authors try to explain two cases: in the first the tunnel does not interfere with the river ( Figure 1A), for the reason that it is located at a huge depth, in the second ( Figure 1B) where the tunnel causes a river drainage, which draws water.…”

“…3;2012 6. Conclusion Dunning et al, 2004 have shown as a river presence can influence the tunneling inflow behavior depending on its nearby aquifer location, such as river distance and impermeable bedrock depth. Consequently, the proper model for computation must take in account both river oscillations (Pinder et al, 1969) and bedrock depth respect to the tunnel base (Goode et al, 1987), in addition to the tunnel and aquifer properties.…”

“…For this reason it needs to propose a forecasting method in order to predict, in approximate way, the interference of a tunnel on the shallow aquifers. Kawecki (2000), Odeh and Babu (1993), Goode and Thambynayagam (1987), Dunning et al (2004) obtained analytical solutions for the transient state for horizontal drainage system similar to the tunnels but in an infinite domain without boundary conditions. Therefore, the relationships are not useful for direct application in reality.…”

Water Circulation in Rocks

“…It is well known that the excavation of tunnels has a relevant draining effect leading to a more or less generalized drawdown of the groundwater level, whose effects may be undesirable, such as the drying up of springs and/or wells (Gisotti and Pazzagli, 2001), qualitative changes of the groundwater (Civita et al, 2002), changes in the vegetations, changes in the slope stability (Picarelli et al, 2002), changes in the flow and quality of thermal waters and changes of the hydrogeological balance at the basin scale. In the last few years, many studies have been carried out that allowed to define more clearly the contribution that hydrogeology can provide to the different stages of tunnel projecting (Civita et al, 2002), in particular in relation to the problem of forecasting tunnel inflows (Goodman et al, 1965;Knutsson et al, 1996;Ribacchi et al, 2002;Anagnostou, 1995;Federico, 1984;Karlsrud, 2001;Loew, 2002;Molinero et al, 2002;Dunning et al, 2004) and to the impact on the hydrogeological conditions of the surrounding environment, in particular on the regime of springs, groundwater and superficial waters (Dematteis et al, 2001). In the last few years, many studies have been carried out that allowed to define more clearly the contribution that hydrogeology can provide to the different stages of tunnel projecting (Civita et al, 2002), in particular in relation to the problem of forecasting tunnel inflows (Goodman et al, 1965;Knutsson et al, 1996;Ribacchi et al, 2002;Anagnostou, 1995;Federico, 1984;Karlsrud, 2001;Loew, 2002;Molinero et al, 2002;Dunning et al, 2004) and to the impact on the hydrogeological conditions of the surrounding environment, in particular on the regime of springs, groundwater and superficial waters (Dematteis et al, 2001).…”

“…An estimate of tunnel inflows can be obtained using geomechanical classifications (Gates, 1997), through analytical formulations (Jacob and Lohman, 1952;Kawecki, 2000;Goodman et al, 1965) or the implementation of mathematic models (Dunning et al, 2004;Molinero et al, 2002), notwithstanding all the mistakes deriving from the uncertainty of the variables involved. Actually, it must be considered that the results obtained are highly conditioned by the hydraulic conductivity value, which depends on the fracturing degree and the stress degree, as well as on the hypothesis of isotropy and homogeneity that constitutes the basis of traditional formulations, which, therefore, are often inadequate to describe correctly the draining process in rock masses.…”