Measuring decadal vertical land-level changes from SRTM-C (2000) and TanDEM-X ( ∼ 2015) in the south-central Andes

Abstract

Abstract. In the arctic and high mountains it is common to measure vertical changes of ice sheets and glaciers via digital elevation model (DEM) differencing. This requires the signal of change to outweigh the noise associated with the datasets. Excluding large landslides, on the ice-free earth the land-level change is smaller in vertical magnitude and thus requires more accurate DEMs for differencing and identification of change. Previously, this has required meter to submeter data at small spatial scales. Following careful corrections, we are able to measure land-level changes in gravel-bed channels and steep hillslopes in the south-central Andes using the SRTM-C (collected in 2000) and the TanDEM-X (collected from 2010 to 2015) near-global 12–30 m DEMs. Long-standing errors in the SRTM-C are corrected using the TanDEM-X as a control surface and applying cosine-fit co-registration to remove ∼1/10 pixel (∼3 m) shifts, fast Fourier transform (FFT) and filtering to remove SRTM-C short- and long-wavelength stripes, and blocked shifting to remove remaining complex biases. The datasets are then differenced and outlier pixels are identified as a potential signal for the case of gravel-bed channels and hillslopes. We are able to identify signals of incision and aggradation (with magnitudes down to ∼3 m in the best case) in two >100 km river reaches, with increased geomorphic activity downstream of knickpoints. Anthropogenic gravel excavation and piling is prominently measured, with magnitudes exceeding ±5 m (up to >10 m for large piles). These values correspond to conservative average rates of 0.2 to >0.5 m yr−1 for vertical changes in gravel-bed rivers. For hillslopes, since we require stricter cutoffs for noise, we are only able to identify one major landslide in the study area with a deposit volume of 16±0.15×106 m3. Additional signals of change can be garnered from TanDEM-X auxiliary layers; however, these are more difficult to quantify. The methods presented can be extended to any region of the world with SRTM-C and TanDEM-X coverage where vertical land-level changes are of interest, with the caveat that remaining vertical uncertainties in primarily the SRTM-C limit detection in steep and complex topography.

Applications of SAR Interferometric Coherence Time Series: Spatiotemporal Dynamics of Geomorphic Transitions in the South‐Central Andes

“…The Quebrada del Toro in particular serves as a representative example of the climatic and topographic gradients found throughout the south‐central Andes (e.g., Bookhagen & Strecker, , ; Castino et al, , ; Purinton & Bookhagen, ; Tofelde et al, , ). The lower Quebrada del Toro is typified by a steep gorge with relatively high precipitation, moderate vegetation, and a steep hillslope gradient (Figure ).…”

“…The lower Quebrada del Toro is typified by a steep gorge with relatively high precipitation, moderate vegetation, and a steep hillslope gradient (Figure ). After the first topographic barrier (knickpoint ~40 km upstream of its outlet at Campo Quijano; Figures a and a), vegetation density decreases dramatically to sparse or no vegetation cover, as shown by the normalized difference vegetation index (NDVI < 0.3; Figure c), while storms continue to penetrate the basin until the second orographic barrier represented by a knickpoint at ~110 km (Hilley & Strecker, ; Purinton & Bookhagen, ; Tofelde et al, ), where storm precipitation dramatically decreases for the remaining upstream area (Figure b). Coherence is correspondingly low in the lower Quebrada del Toro (Figure d) and increases rapidly as vegetation density and precipitation decrease at the first orographic barrier (Figure b; Bookhagen & Strecker, ; Rohrmann et al, ).…”

Introducing PebbleCounts: A grain-sizing tool for photo surveys of dynamic gravel-bed rivers

“…9). This is an area of strong precipitation, topographic, and environmental gradients, and the rivers surveyed are dynamic environments capable of transporting enormous quantities of sand, gravel, and boulders of various lithology (Bookhagen and Strecker, 2012;Purinton and Bookhagen, 2018). Catchmentaverage erosion rates from the area, based on cosmogenic nuclide inventories, suggest rates on the order of 0.6-1 mm/yr (Bookhagen and Strecker, 2012), with large variability during the Pleistocene and Holocene (Tofelde et al, 2017).…”

Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset

“…In practice, datasets will not have homogeneous noise across grid spacings -coarser parameterizations of a surface will include more uncertainty as fine-scale features are aggregated into single pixels. Additionally, noise in real-world datasets is influenced by non-uniform landscape features such as slope, aspect, terrain relief, and vegetation cover (e.g., Kraus and Pfeifer, 1998;Kyriakidis et al, 1999;Holmes et al, 2000;Smith and Sandwell, 2003;Carlisle, 2005;Oksanen and Sarjakoski, 2006;Rodriguez et al, 2006;Figure 5. TE and PEU magnitudes for two noise levels, (a) 1e −4 and (b) 1e −6 , compared to grid spacing.…”