Abstract
Abstract. Several engineered facilities located on deep alluvial basins in southern Arizona, including flood retention structures (FRS) and a coal ash disposal facility, have been impacted by up to as much as 1.8 m of differential land subsidence and associated earth fissuring. Compressible basin alluvium depths are as deep as about 300 m, and historic groundwater level declines due to pumping range from 60 to more than 100 m at these facilities. Addressing earth fissure-inducing ground strain has required alluvium modulus characterization to support finite element modeling. The authors have developed Percolation Theory-based methodologies to use effective stress and generalized geo-material types to estimate alluvium modulus as a function of alluvium lithology, depth and groundwater level. Alluvial material modulus behavior may be characterized as high modulus gravel-dominated, low modulus sand-dominated, or very low modulus fines-dominated (silts and clays) alluvium. Applied at specific aquifer stress points, such as significant pumping wells, this parameter characterization and quantification facilitates subsidence magnitude modeling at its' sources. Modeled subsidence is then propagated over time across the basin from the source(s) using a time delay exponential decay function similar to the soil mechanics consolidation coefficient, only applied laterally. This approach has expanded subsidence modeling capabilities on scales of engineered facilities of less than 2 to more than 15 km.
Highlights
Subsidence has been analyzed at engineered facilities in Arizona for over two decades (Keaton et al, 1998; Rucker et al, 2008)
Connectivity of alluvium aquifer systems consisting of fines-dominated, sand-dominated or gravel-dominated units can be quantified through concepts of Percolation Theory (PT)
Percolating network permeable flow, and lack of a percolating network low resistivity pathway are demonstrated in the 2-D matrix example (Fig. 1a)
Summary
Subsidence has been analyzed at engineered facilities in Arizona for over two decades (Keaton et al, 1998; Rucker et al, 2008). Alluvium material classification included well logs (ranging from commonly poor-quality historical qualitative descriptions to high-quality quantitative borehole geophysical logging) and surface geophysical measurements (especially resistivity) to supplement published data (AMEC, 2009)
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