57 Advances in River Science in the Intermountain West II

Thursday, 17 May 2018
10:20 AM - 12:05 PM
Coconino Room

CHASING CENTIMETERS: A CASE STUDY OF FINDING AND APPLYING AN APPROPRIATE UNCERTAINTY FOR MORPHOLOGICAL SEDIMENT BUDGETING IN A LARGE RIVER

Paper number: 57-5
Program: Theme Sessions
Time: 11:25 AM – 11:45 AM

Authors

Abstract

Sediment budgets are frequently used to understand the relationship between sediment transport and morphological change. Accurately quantifying the inputs, outputs, and storage of sediment in a dynamic system using a morphological mass balance approach is challenging at large scales and over long periods, which can lead to accumulations of large uncertainties in computed sediment volumes. Develop an understanding of the uncertainties associated with each component of the budget is therefore a crucial component of the budgeting process. In large rivers, sediment budgets based on measuring changes in channel topography are often accomplished by differencing Digital Elevation Models (DEMs) constructed from repeat surveys of the study reach. The uncertainty associated with each DEM is propagated through the budget calculations and determines the amount of detectable change. DEM uncertainty should contain components of both the raw measurement uncertainty and the uncertainty associated with the construction of the DEM.

We present examples of two different approaches to DEM uncertainty and their effects on the resultant sediment budget for a study reach of the Colorado River in Grand Canyon. One method uses the absolute difference between features that are assumed to not have changed between surveys, such as the tops of rocks which are termed here fiducial surfaces, and fuzzy inference system (FIS) modeling. The fiducial surface uncertainty estimate results in a scalar uncertainty for each data collection type that is applied to the entire DEM. Fuzzy inference is the process of mapping inputs (different sources of error) to outputs (volumetric uncertainty) using fuzzy logic. The FIS approach results in models of spatially distributed uncertainty (i.e. a unique uncertainty value per grid cell) that incorporates information derived from the DEM, such as surface roughness and slope.

Geological Society of America Abstracts with Programs. Vol. 50, No. 5

doi: 10.1130/abs/2018RM-314230

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