High-resolution topography data (lidar) are being collected over increasingly larger geographic areas. These data contain an immense amount of information regarding the topography of bare-earth and vegetated surfaces. Repeat lidar data (collected at multiple times for the same location) enables extraction of an unprecedented level of detailed information about landscape form and function and provides an opportunity to quantify volumetric change and identify hot spots of erosion and deposition. However, significant technological and scientific challenges remain in the analysis of repeat lidar data over enormous areas (>1000 square kilometers), not the least of which involves robust quantification of uncertainty. Excessive sedimentation has been documented in the Minnesota River and many reaches of the mainstem and tributaries are listed as impaired for turbidity and eutrophication under the Clean Water Act of 1972. The Blue Earth River and its tributaries (Greater Blue Earth basin) have been identified as one of the main sources of sediment to the Minnesota River. Much of the Greater Blue Earth basin is located in Blue Earth County (1,982 square kilometers) where airborne lidar data were collected in 2005 and 2012, with average bare-earth point densities of 1 point per square meter and closer to 2 points per square meter, respectively. One of the largest floods on record (100-year recurrence interval) occurred in September 2010. A sediment budget for the Greater Blue Earth basin is being developed to inform strategies to reduce current sediment loads and better predict how the basin may respond to changing climate and management practices. Here we evaluate the geomorphic changes that occurred between 2005 and 2012 to identify hotspots of erosion and deposition, and to quantify some of the terms in the sediment budget. To make meaningful interpretations of the differences between the 2005 and 2012 lidar digital elevation models (DEMs), total uncertainty must be accounted for between and within DEMs. We identified, quantified, and corrected for a systematic vertical bias of 6 cm between the two DEMs. We compared elevation differences using the control points used to ground-truth and from points digitized in areas outside channels where we did not expect geomorphic change over time. Digitized points were stratified by geography and flight lines to determine if the bias was spatially distributed. To evaluate horizontal bias, we digitized points at the corners of buildings throughout each DEM. For each set of points, we compared the direction and magnitude of differences and did not detect a systematic horizontal bias. A new uncertainty model was developed and applied to each DEM that accounts for uncertainty due to vegetation interference and topographic complexity relative to sampling. These uncertainty models were propagated into the change detection estimates to establish a probabilistically thresholded estimate of elevation change and estimates of volume eroded or deposited. Results will be presented of the spatial patterns of net erosion and deposition and their contribution to the overall sediment budget being developed.
Available at: http://works.bepress.com/joseph_wheaton/79/