Time‐averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM‐X interferometry: Implications for magma supply and storage during 2011–2013

Abstract

Differencing digital elevation models (DEMs) derived from TerraSAR add-on for Digital Elevation Measurements (TanDEM-X) synthetic aperture radar imagery provides a measurement of elevation change over time. On the East Rift Zone (EZR) of Kīlauea Volcano, Hawai'i, the effusion of lava causes changes in topography. When these elevation changes are summed over the area of an active lava flow, it is possible to quantify the volume of lava emplaced at the surface during the time spanned by the TanDEM-X data-a parameter that can be difficult to measure across the entirety of an~100 km 2 lava flow field using ground-based techniques or optical remote sensing data. Based on the differences between multiple TanDEM-X-derived DEMs collected days to weeks apart, the mean dense-rock equivalent time-averaged discharge rate of lava at Kīlauea between mid-2011 and mid-2013 was approximately 2 m 3 /s, which is about half the long-term average rate over the course of Kīlauea's 1983-present ERZ eruption. This result implies that there was an increase in the proportion of lava stored versus erupted, a decrease in the rate of magma supply to the volcano, or some combination of both during this time period. In addition to constraining the time-averaged discharge rate of lava and the rates of magma supply and storage, topographic change maps derived from space-based TanDEM-X data provide insights into the four-dimensional evolution of Kīlauea's ERZ lava flow field. TanDEM-X data are a valuable complement to other space-, air-, and ground-based observations of eruptive activity at Kīlauea and offer great promise at locations around the world for aiding with monitoring not just volcanic eruptions but any hazardous activity that results in surface change, including landslides, floods, earthquakes, and other natural and anthropogenic processes.

Synthesis of global satellite observations of magmatic and volcanic deformation: implications for volcano monitoring & the lateral extent of magmatic domains

“…DLR's TanDEM-X, Albino et al, 2015). Although the effectiveness of SAR measurements of topography during an effusive eruption have been demonstrated (Poland, 2014), such bistatic data are not yet widely available for use in monitoring. Finally, interferometric phase coherence captures how rapidly surface scatterers are changing and can in some circumstances be used to track the development of fresh lava flows as they are emplaced, settle and cool (e.g.…”

Sub-seasonal thaw slump mass wasting is not consistently energy limited at the landscape scale

“…Our estimates of topographic changes are obtained from repeated topographic observations using the radar remote sensing technique single-pass interferometry (Bamler and Hartl, 1998). By repeated application of single-pass measurements, time series of the topography and hence topographic changes can be derived (Poland, 2014). Repeated observations of two permafrost regions with high ground ice content were made by the TanDEM-X satellite pair in the Science Phase (June -August 2015).…”

“…While it has not been employed in permafrost environments, the technology is mature, as evidenced by the widespread use of the digital elevation models obtained from the shuttle radar topography mission or TanDEM-X, or the application of such 15 data for quantifying temporal changes in volcanology and glaciology (Krieger et al, 2007;Poland, 2014). The ability to cover large areas and to do so frequently are key advantages over both in-situ measurements and the remote sensing techniques photogrammetry and LiDAR (Günther et al, 2015;Jones et al, 2013;Obu et al, 2016).…”

“…Rather than following the standard approach of first deriving a digital elevation model from each image pair interferogram and subsequently 25 forming the differences (Poland, 2014), we directly differenced interferograms. Our rationale was that the baselines were essentially constant for all acquisitions, so that the differencing of interferograms yielded a direct estimate of ∆h and phase unwrapping was greatly facilitated.…”

“…due to orbital errors which changes only slowly across the interferogram. We removed it by mild high-pass filtering (Rizzoli et al, 2012;Poland, 2014) with a length-scale of 600 m that is much larger than the individual thermokarst 10 disturbances. The filtering procedure was robust to outliers as it was based on the median and was not applied to masked pixels like radar shadow or water surfaces.…”