Nicolas d’Oreye

Ground deformation associated with post-mining activity at the French–German border revealed by novel InSAR time series method

Abstract We present a novel methodology for integration of multiple InSAR data sets for computation of two dimensional time series of ground deformation. The proposed approach allows combination of SAR data acquired with different acquisition parameters, temporal and spatial sampling and resolution, wavelength and polarization. Produced time series have combined coverage, improved temporal resolution and lower noise level. We apply this methodology for mapping coal mining related ground subsidence and uplift in the Greater Region of Luxembourg along the French–German border. For this we processed 167 Synthetic Aperture Radar ERS-1/2 and ENVISAT images acquired between 1995 and 2009 from one ascending (track 29) and one descending (track 337) tracks and created over five hundred interferograms that were used for time series analysis. Derived vertical and east–west linear deformation rates show with remarkable precision a region of localized ground deformation located above and caused by mining and post-mining activities. Time series of ground deformation display temporal variability: reversal from subsidence to uplift and acceleration of subsidence in the vertical component, and horizontal motion toward the center of the subsidence on the east–west component. InSAR results are validated by leveling measurements collected by the French Geological Survey (BRGM) during 2006–2008. We determined that deformation rate changes are mainly caused by water level variations in the mines. Due to higher temporal and spatial resolution the proposed space-borne method detected a larger number of subsidence and uplift areas in comparison to leveling measurements restricted to annual monitoring of benchmark points along roads. We also identified one deformation region that is not precisely located above the mining sites. Comparison of InSAR measurements with the water levels measured in the mining pits suggest that part of the water that filled the galleries after termination of the dewatering systems may come from this region. Providing that enough SAR data is available, this method opens new opportunities for detecting and locating man-made and natural ground deformation signals with high temporal resolution and precision.

Nyamulagira’s magma plumbing system inferred from 15 years of InSAR

Abstract Nyamulagira, located in the east of the Democratic Republic of Congo on the western branch of the East African rift, is Africa’s most active volcano, with an average of one eruption every 3 years since 1938. Owing to the socio-economical context of that region, the volcano lacks ground-based geodetic measurements but has been monitored by interferometric synthetic aperture radar (InSAR) since 1996. A combination of 3D Mixed Boundary Element Method and inverse modelling, taking into account topography and source interactions, is used to interpret InSAR ground displacements associated with eruptive activity in 1996, 2002, 2004, 2006 and 2010. These eruptions can be fitted by models incorporating dyke intrusions, and some (namely the 2006 and 2010 eruptions) require a magma reservoir beneath the summit caldera. We investigate inter-eruptive deformation with a multi-temporal InSAR approach. We propose the following magma plumbing system at Nyamulagira by integrating numerical deformation models with other available data: a deep reservoir (c. 25 km depth) feeds a shallower reservoir (c. 4 km depth); proximal eruptions are fed from the shallow reservoir through dykes while distal eruptions can be fed directly from the deep reservoir. A dyke-like conduit is also present beneath the upper southeastern flank of Nyamulagira.

Multiparameter monitoring of Fogo Island, Cape Verde, for volcanic risk mitigation

Fogo Island in the Cape Verde Archipelago (North Atlantic) is a stratovolcano of nearly conical shape that rises 2829 m above sea level and V6000 m above the surrounding seafloor. With a population of 40 000, the island has known intense historical volcanic activity since AD 1500, with an average interval between eruptions of the order of 20 years. Twentieth-century rates were more subdued, with only two flank eruptions in 1951 and 1995. Following the 1995 eruption, increased awareness of the volcanic hazard affecting the population of the island led to the deployment of the permanent VIGIL Network. Seismographic stations (both broadband and short-period), tiltmeters and a CO2 sensor where installed in Fogo, together with a telemetry infrastructure to allow remote real-time monitoring. A broadband seismographic station was installed in neighbour Brava Island. The operation of the network was complemented by the introduction of routine geodetic and microgravity surveying and the operation of an automatic meteorological station. In this paper, we describe the methodology adopted to monitor the volcanic activity, combining real-time data analysis (volcanotectonic and volcanic earthquakes, volcanic tremor and tilt) with repeated surveying at intervals of several months (GPS, microgravity). Examples of data from the first years of operation are presented. In particular, the data pertaining to a period of anomalous activity in September^October 2000 are discussed, in the context of the risk mitigation strategy currently being developed.

KivuSNet: The First Dense Broadband Seismic Network for the Kivu Rift Region (Western Branch of East African Rift)

ABSTRACT The Kivu rift is located in the bordering region of the Democratic Republic of Congo and Rwanda, in the western branch of the East African rift. Here, the active volcanoes Nyamulagira (the most active in Africa) and Nyiragongo (host to the largest persistent lava lake on Earth) threaten the city of Goma and neighboring agglomerations, and destructive earthquakes can also affect the region. Despite this high level of hazard, modern seismic monitoring infrastructure was lacking in the area until very recently, leaving many aspects about the volcanic activity and seismicity up to speculation. In order to remedy this unsatisfactory situation, the first dense real‐time telemetered broadband seismic network, KivuSNet, was deployed in the region, with the first two stations in 2012/2013 followed by six additional ones in 2014. Since October 2015, a network of 13 stations is running in the Kivu rift, and with currently seven additional stations in the process of installation, this network is under continuous development. KivuSNet opens a new window for the seismological knowledge in this highly active rifting region. It allows for unprecedented insights into tectonic and volcanic seismicity, tremor patterns, and Earth structure as well as for sustainable real‐time monitoring of the volcanoes. Together with the often collocated KivuGNet geodetic stations, KivuSNet closes a dramatic observational gap in this region. This article presents the key features of the network, discusses technical aspects, and provides an overview of first results obtained using the thus far acquired data, showing KivuSNet’s wide potential.

Multi-Temporal DInSAR to Characterise Landslide Ground Deformations in a Tropical Urban Environment: Focus on Bukavu (DR Congo)

Landslides can lead to high impacts in less developed countries, particularly in tropical environments where a combination of intense rainfall, active tectonics, steep topography, and high population density can be found. However, the processes controlling landslide initiation and their evolution through time remains poorly understood. Here we show the relevance of the use of the multi-temporal differential radar interferometric (DInSAR) technique to characterise ground deformations associated with landslides in the rapidly-expanding city of Bukavu (DR Congo). We use 70 COSMO-SkyMed synthetic aperture radar images acquired between March 2015 and April 2016 with a mean revisiting time of eight days to produce ground deformation rate maps and displacement time series using the small baseline subset approach. We find that various landslide processes of different ages, mechanisms, and states of activity can be identified. Ground deformations revealed by DInSAR are found consistent with field observations and differential GPS measurements. Our analysis highlights the ability of DInSAR to grasp landslide deformation patterns affecting the complex tropical-urban environment of the city of Bukavu. However, longer time series will be needed to infer landside responses to climate, seismic, and anthropogenic drivers.