Computer-simulation models of scoria cone degradation

Ž . Long-term erosional modifications of the relatively simple morphology of scoria ‘cinder’ cones are ideally suited for study by field and computer-simulation methods. A series of temporally-distinct cones in the San Francisco and Springerville volcanic fields of Arizona provides the foundation for documenting the degradational evolution of scoria cones in a semi-arid climate. Progressive changes due to erosion are illustrated by the systematic decrease with increasing age of Ž . various morphometric parameters, including scoria cone height, cone heightrwidth ratio H rW , crater depthrwidth co co ratio, and slope angle. For example, Holocene–latest Pleistocene cones in the San Francisco field have a mean H rW co co value of 0.178"0.041, a mean maximum slope angle of 29.7"4.28, and a mean average slope angle of 26.4"7.38, whereas the group of Pliocene cones have values of 0.077"0.024, 20.5"5.88, and 8.7"2.78, respectively. Comparative morphology of scoria cones is a potentially useful dating tool for mapping volcanic fields. In order to better understand the degradational modifications of these volcanic landforms, we have developed a numerical approach to simulate the surficial processes responsible for the erosion of a typical scoria cone. The simulation algorithm can apply either a linear diffusion-equation model or a model with a nonlinear transport law. Using a finite-difference formulation, the simulation operates upon a three-dimensional scoria cone input as a matrix of elevation values. Utilizing both field and model results, the correlation between changing H rW value, cone age, and computer time step was co co Ž . expressed graphically to derive comprehensive values of the transport or diffusion coefficient D for both volcanic fields. f For the San Francisco volcanic field, D had a calculated value of 21.4 mrkyr for the linear model and 5.3 mrkyr for the f nonlinear model, while for the Springerville volcanic field D had a calculated value of 24.4 mrkyr for the linear model f and 6.3 mrkyr for the nonlinear model. q 1998 Elsevier Science B.V. All rights reserved.