The use of discrete fracture network simulations in the design of horizontal hillslope drainage networks in fractured rock
Abstract Characteristics of fracture networks are explored in a discrete fracture network framework to provide design guidelines for horizontal drainage networks in fractured rock. Central to the study is defining how fracture attributes relate to fracture network structure and network-scale fluid flow, and in turn, how flow characteristics of fracture networks influence horizontal drain length and orientation. Multiple realizations of stochastic fracture networks, generated from both synthetic and field-specific data sets, serve as a basis for understanding physical fracture network structure and resultant global flow and for performing intersection analyses of hillslope drains with flowing fractures. Study results indicate that the logarithm of the standard deviation of fracture transmissivity, log( σ T ), is the single most important attribute for drainage network design, as higher values of log( σ T ) describe heterogeneous flow patterns where only a small portion of the network conducts a significant quantity of fluid. Thus recommended drain lengths for intersecting significantly conductive fractures increase with increases in log( σ T ). Fracture trace length, orientation, and density also play a role, albeit secondary to the distribution of transmissivity, in defining drain length as a function of drain orientation relative to the mean fracture set orientation. The spatially discontinuous nature of fracture networks and the wide range in transmissivity values found in natural fracture networks tend to produce high degrees of variability in computed intersection distances between drains and fractures conducting significant quantities of fluid. To account for this variability, a conservative approach is recommended where horizontal drain lengths along a pre-defined orientation are scaled by discrete fracture network computed intersection distances equal to the upper 95th confidence interval.