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: Mineral dissolution is a micro-scale process, which may significantly alter the microstructure of rocks, and consequently affect their effective mechanical behavior at the macro scale. Predicting changes in rock stiffness is of paramount importance within the context of risk assessment for most applications related to geological subsurface utilization, where reduction of mechanical parameters is of particular relevance to assess reservoir, caprock and fault integrity [1]. In the present study, the effective elastic properties of typical reservoir rocks are determined based on micro-computer tomography (micro-CT) scans. The resulting three-dimensional rock geometry comprises a more realistic microstructure regarding the shapes of grains, cements and the overall porous network compared to available empirical approaches. Effective rock stiffness is calculated by a static finite element method, which imposes an uniform strain on the digital rock sample and calculates the resulting stresses. The effect of spatial cement distribution within the pore network is taken into account, considering passive pore filling as well as framework supporting cements. Rock stiffness increases due to the precipitation of pore-filling minerals. This quantitative approach substantially improves the accuracy in predicting elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in mineral distribution.

Description: Geochemical processes change the microstructure of rocks and thereby affect their physical behaviour at the macro scale. A micro-computer tomography (micro-CT) scan of a typical reservoir sandstone is used to numerically examine the impact of three spatial alteration patterns on pore morphology, permeability and elastic moduli by correlating precipitation with the local flow velocity magnitude. The results demonstrate that the location of mineral growth strongly affects the permeability decrease with variations by up to four orders in magnitude. Precipitation in regions of high flow velocities is characterised by a predominant clogging of pore throats and a drastic permeability reduction, which can be roughly described by the power law relation with an exponent of 20. A continuous alteration of the pore structure by uniform mineral growth reduces the permeability comparable to the power law with an exponent of four or the Kozeny–Carman relation. Preferential precipitation in regions of low flow velocities predominantly affects smaller throats and pores with a minor impact on the flow regime, where the permeability decrease is considerably below that calculated by the power law with an exponent of two. Despite their complete distinctive impact on hydraulics, the spatial precipitation patterns only slightly affect the increase in elastic rock properties with differences by up to 6.3% between the investigated scenarios. Hence, an adequate characterisation of the spatial precipitation pattern is crucial to quantify changes in hydraulic rock properties, whereas the present study shows that its impact on elastic rock parameters is limited. The calculated relations between porosity and permeability, as well as elastic moduli can be applied for upscaling micro-scale findings to reservoir-scale models to improve their predictive capabilities, what is of paramount importance for a sustainable utilisation of the geological subsurface

Description: Landslides represent a worldwide natural hazard and often occur as cascading effects related to triggering events, such as earthquakes and hydrometeorological extremes. Recent examples are the Kaikoura earthquake in New Zealand (November 2016), the Gorkha earthquake in Nepal (April/May 2015), and the Typhoon Morakot in Taiwan (August 2009) as well as less intense rainfall events persisting over unusually long periods of time as observed for Central Asia (spring 2017) and Iran (spring 2019). Each of these events has caused thousands of landslides that account substantially to the primary disaster’s impact. Moreover, their initial failure usually represents the onset of long-term progressing slope destabilization leading to multiple reactivations and thus to long-term increased hazard and risk. Therefore, regular systematic high-resolution monitoring of landslide prone regions is of key importance for characterization, understanding and modelling of spatiotemporal landslide evolution in the context of different triggering and predisposing settings. Because of the large extent of the affected areas of up to several ten thousands km2, the use of multi-temporal and multi-scale remote sensing methods is of key importance for large area process analysis. In this context, new opportunities have opened up with the increasing availability of satellite remote sensing data of suitable spatial and temporal resolution (Sentinels, Planet) as well as the advances in UAV based very high resolution monitoring and mapping. During the last decade, we have been pursuing extensive methodological developments in remote sensing based time series analysis including optical and radar observations with the goal of performing large area and at the same time detailed spatiotemporal analysis of landslide prone regions. These developments include automated post-failure landslide detection and mapping as well as assessment of the kinematics of pre- and post-failure slope evolution. Our combined optical and radar remote sensing approaches aim at an improved understanding of spatiotemporal dynamics and complexities related to evolution of landslide prone slopes at different spatial and temporal scales. In this context, we additionally integrate UAV-based observation for deriving volumetric changes also related to globally available DEM products, such as SRTM and ALOS. We present results for selected settings comprising large area co-seismic landslide occurrence related to the Kaikoura 2016 and the Nepal 2015 earthquakes. For the latter one we also analyzed annual pre- and post-seismic monsoon related landslide activity contributing to a better understanding of the interplay between these main triggering factors. Moreover, we report on ten years of large area systematic landslide monitoring in Southern Kyrgyzstan resulting in a multi-temporal regional landslide inventory of so far unprecedented spatiotemporal detail and completeness forming the basis for further analysis of the obtained landslide concentration patterns. We also present first results of our analysis of landslides triggered by intense rainfall and flood events in spring of 2019 in the North of Iran. We conclude that in all cases, the obtained results are crucial for improved landslide prediction and reduction of future landslide impact. Thus, our methodological developments represent an important contribution towards improved hazard and risk assessment as well as rapid mapping and early warning