Figure 1. Examples of heterogeneous permeability fields that have been developed using geostatistical methods to represent the subsurface of the Critical Zone. The first method, panel (A) shows a method that subdivides the domain into regions of low permeability saprolite and a high permeability, “discrete” fracture network. The second method, panel (B) shows a correlated random field generated using sequential Gaussian simulation, which is commonly used to represent heterogeneity in the subsurface but may not capture the sharp differences in permeability that would result from fracturing in a natural setting. Discrete fracture networks were found to result in a distinct hydrologic partitioning of water into mobile and immobile regions, which influenced both solute transport and weathering behavior in subsequent hydro-geochemical weathering simulations.

Figure 2. Sensitivity of weathering rates in a subsurface hydro-geochemical model of the Critical Zone to the different representations of heterogeneity shown in Figure 1. The model domain is an idealized subsurface transect of saprolite exposed to vertical infiltration of "fresh" water from the top boundary (z = 10 m) that reacts with minerals prior to leaving the system (z = 0 m). K-feldspar is uniformly distributed at 0 kyr, and the figure shows K-feldspar weathering rates after 300 kyr of simulation.  (A) Shows dissolution rates in the discrete fracture network and (B) shows rates in the correlated random permeability field. There exists strong heterogeneity-dependence in the spatial distribution and magnitude of weathering for both cases. The permeability field of (A) may better represent natural fracturing since it results in a reaction zone distributed along fracture pathways and causes the development of reactive corestones. Evidence of these phenomena have been observed in Critical Zone observatories and other subsurface studies.