ALBERT

Description: Between mid-March and the beginning of April 2019, extremely high precipitation affected the whole Iran, leading to widespread flash flooding and landslides. Approximately 10 million people were affected, among them 2 million were in humanitarian needs. The event caused 78 fatalities, more than 1000 injuries and widespread damage in 25 out of the 31 provinces. In this work, we use both high resolution – spatial and temporal – optical and radar satellite remote sensing to characterize spatiotemporal pattern of landslide occurrence related to the main hydro-meteorological triggering events in Golestan province, North Iran. Large-area landslide detection has been performed in a semi-automated way using time series of optical Planet Scope and Sentinel-2A/B data. The obtained satellite remote sensing based results were evaluated by field surveys conducted in September 2019 in cooperation between the GFZ Potsdam and the Forest, Range and Watershed Management Organization of Iran (FRWM) being responsible for landslide hazard and risk assessment as well as the design and implementation of mitigation measures. Moreover, we report on our deformation monitoring using Sentinel-1/B based differential interferometric synthetic aperture radar (DInSAR) on hot-spots areas to investigate whether any of the catastrophic landslides that happened in spring of 2019 have shown precursory signs in form of preparatory deformation. In particular, we present our detailed investigation for Hossein Abad Kalpush landslide, located at the border between Golestan and Semnan provinces. In April 2019, this slide slipped at an unprecedented scale, causing total destruction of one part of the village nearby with complete destruction of 250 houses. Using an integrated approach exploring satellite imagery, in-situ measurements and field survey, we perform detailed time-series analysis of the evolution of Hossein Abad Kalpush landslide and examine the role of meteorological and anthropogenic influencing factors in controlling the behaviour of this landslide.

Description: The densely populated neighborhoods of Pinheiro, Bebedouro, Mutange, Bom Parto and Levada in the Municipality of Maceió (Brazil) are suffering serious geological instability. Fractures, on both buildings and roads, have intensified since the beginning of 2018 and some of the areas were evacuated, due to safety reasons, by the local authorities during the second half of 2019. The preliminary investigation conducted by the Brazilian Geological Service (Serviço Geologico do Brazil - CPRM), suggested that the direct cause of the instability is connected to the salt mining activities carried out on near the cost of the Mundaú Lagoon. In this study we use radar interferomtery (InSAR) and 2D geomechanical modelling to characterize almost 16 years of continuous deformation in Municipality of Maceió (Brazil). We exploited the full potential of the well-known Multi Temporal Interferometry techniques (MTI) based on Advanced Synthetic Aperture Radar Differential Interferometry (A-DInSAR) and processed all available historical and currently operational SAR missions: the C-band ASAR ENVISAT, the L-band ALOS-1 POLSAR, L-band ALOS-2 POLSAR and C-band Sentinel-1 missions. The results show clear main deformation field over the neighborhood of Pinheiro with concentric pattern to the shore and increasing deformation intensity up to 25cm per year from 2003 to 2019. A minor deformation area is detected also south of the lagoon corresponding to the neighborhood of Bom Parto and Levada. A 2D geomechanical modelling of salt-cavern stability using Distinct Elements is developed to derive the relationship between the detected deformations and the salt mining activities. As a general conclusion, our study shows how MTI analysis is very efficient and reliable tool for emergency management purposes. Especially after the launch of the Sentinel-1 mission, which provides an acquisition in single pass every 12 days, we are able to detect when a surface displacement commence and monitor the deformation progress and status in time.

Description: Numerical simulation has become an inevitable tool for improving the understanding on coupled processes in the geological subsurface and its utilisation. However, most of the available open source and commercial modelling codes do not come with flexible chemical modules or simply do not offer a straight-forward way to couple third-party chemical libraries. For that reason, the simple and efficient TRANsport Simulation Environment (TRANSE) has been developed based on the Finite Difference Method in order to solve the density-driven formulation of the Darcy flow equation, coupled with the equations for transport of heat and chemical species. Simple explicit, weighted semi-implicit or fully-implicit numerical schemes are available for the solution of the system of partial differential equations, whereby the entire numerical code is composed of less than 1000 lines of Python code, only. A diffusive flux-corrected advection scheme can be employed in addition to pure upwinding to minimise numerical diffusion in advection-dominated transport problems. The objective of the present study is to verify the numerical code implementation by means of benchmarks for density-driven fluid flow and advection-dominated transport. In summary, TRANSE exhibits a very good agreement with established numerical simulation codes for the benchmarks investigated here. Consequently, its applicability to numerical density-driven flow and transport problems is proven. The main advantage of the presented numerical code is that the implementation of complex problem-specific couplings between flow, transport and chemical reactions becomes feasible without substantial investments in code development using a low-level programming language, but the easy-to-read and -learn Python programming language.

Description: Land subsidence hazard affects many highly populated urban areas of the world as a consequence of natural and/or anthropogenic derived geomechanical rock alterations. Here we exploit the full archive of Synthetic Aperture Radar (SAR data) and present a 16-years history (2004-2020) of surface displacement affecting the federal capital of Maceió (Alagoas, Brazil), where sinkhole formation and fractures on infrastructures have been intensified since early 2018, forcing authorities to relocate the affected residence and pose the building under demolition. The geodetic result shows that precursory deformations were already visible in early 2000’s, reaching in November 2020 a maximum cumulative subsidence of approximately 2 m near the Mundaú lagoon coast. The maximum rate of subsidence is estimated at 27 cm/year. Numerical elastic source modelling proves that the subsidence is associated with localized, deep seated material removal at the location and depth where salt mining is performed. More sophisticated 2D distinct element method highlights the formation of cracks in sedimentary layers that eventually enables strong water percolation from rather superficial aquifers into the deeper underground, with potential increase of material dissolution and erosion. We discuss the accelerating subsidence rates, the influence of severe precipitation events to the aforementioned geological instability and the related dynamic evolution of the subsidence hazard by generating dynamic geohazard maps valuable for further infrastructure risk assessment.

Description: In southern Kyrgyzstan extensive landsliding is primarily caused by ongoing tectonic deformation which is superposed by other landslide triggering factors, such as lithological setting, relief, climate and surface cover. The goal is to develop a multi-sensor approach combining analysis of optical (Landsat-TM, declassified US intelligence imagery) and SAR intensity (ERS-1/2) remote sensing data with results from Differential SAR Interferometry in a GIS environment to assess the potential for hazardous mass movements on a regional basis. For this purpose a pilot study area of approx. 100 by 100 km containing a typical variety of landslides was chosen and first field investigations were carried out last summer. Present work is focused on developing techniques for remote sensing based spatial derivation of parameters characterizing main landslide triggering factors in the area. Emphasis is put on a spatially accurate representation of these parameters to create a high quality digital database for further analysis towards a GIS-based regionalisation of typical landslide processes. These investigations support the ongoing monitoring activities of the MECD.