Hydrogeophysical characterisation for improved early warning of landslides
Creators: name: Boyd, Jimmy
Publisher: name: Lancaster University
Year: 2024

description: Landslides are gravity driven movements of earth material that can have
 major economic and societal consequences. Most of these movements are
 driven by changes in subsurface moisture, usually resulting from rainfall
 and consequently are likely to become more frequent in regions where more
 extreme wetting events occur due to climate change. This work focuses on
 moisture-driven landslides in clay rich unstable slopes. Conventional
 methods of characterising landslides include intrusive sampling methods,
 such as boreholes and point samples; however, these are only sensitive to
 discrete portions of the subsurface. Remote sensing can be used to map the
 external geometry of landslides but offers little information on internal
 structure and condition. Geophysical methods can enhance the internal
 characterisation of landslides as they are spatially sensitive to
 subsurface properties like electrical resistivity and seismic wave speed.
 Furthermore, repeated geophysical surveys can reveal how these properties
 change with time. Here the use of direct current (DC) electrical
 resistivity measurements for monitoring landslides is explored, as
 near-surface changes in moisture tend to drive changes in electrical
 resistivity. The research is applied to the Hollin Hill Landslide
 Observatory, composed of Jurassic rocks in the north of England, as this
 site is representative of many vulnerable slopes in the United Kingdom. 
 
 By their nature, landslides move downslope. This continuous movement poses
 a challenge for the long-term processing of data from permanently
 installed sensors entrained within these slopes. Here the goal is to
 process long term DC resistivity data using time-lapse Electrical
 Resistivity Imaging (ERI) to aid understanding seasonal moisture content
 dynamics and internal geometry of the Hollin Hill landslide. The
 topography of the slope and locations of the electrodes at the surface
 move with landslide movements, which introduces artefacts in conventional
 ERI processing results. Global positioning systems (GPS) were used to
 track landslide movements via permanently deployed markers (pegs) on the
 slope. A thin plate spline algorithm was used to interpolate changes to
 the slope topography and electrode locations through time, allowing for
 geophysical modelling to account for changes of the slope surface. These
 efforts culminate in a time series of geophysical models with a dynamic
 surface that captures both geomorphological and electrical resistivity
 changes at Hollin Hill, useful for illuminating landslide moisture content
 dynamics. Time series ERI models show low resistivities, linked to
 sustained high moisture contents, are present in an area of the landslide
 actively undergoing movement during this study. 
 
 Clay rich rocks are particularly susceptible to landslides due to their
 low resistance to shearing at high moisture contents. Petrophysical
 relationships between electrical resistivity and moisture content have
 been established for decades, hence ERI can facilitate volumetric imaging
 of moisture content in the field. Such a conversion is useful as it
 presents geophysical properties in an engineering context and makes
 geophysical models more accessible for decision makers (or engineers).
 Electrical resistivity is sensitive to formation lithology, porosity,
 moisture content, pore fluid conductivity, and temperature. Clay
 formations have some unusual properties from a petrophysical perspective
 as they conduct electricity, and their porosity can increase as the clay
 grains swell with increasing moisture content. It is found that accounting
 for the swelling of clay is necessary for reliably fitting established
 petrophysical models. Relationships between matric potential, or negative
 pore pressure, and electrical resistivity are also explored as the former
 can be directly related to the unsaturated shear strength of a geological
 formation. Although, volumetric models of matric potential derived from
 ERI processing are not always realistic, tending towards negative or
 negligible matric potentials. 
 
 Hydrological models of landslides can be used to understand fluid dynamics
 within slopes and predict crucial hydro-mechanical parameters controlling
 slope stability. Given the relationship between electrical resistivity and
 moisture content, electrical resistivity measurements can be used to
 calibrate hydrological parameters in these models. The soil retention
 parameters controlling unsaturated fluid flow are calibrated via coupled
 geophysical and hydrological (hydrogeophysical) modelling, in two
 formations at the Hollin Hill landslide. Parameter sampling is achieved
 using a Markov chain Monte-Carlo approach to find most likely soil
 retention parameters. The workflow is firstly tested against a synthetic
 case study with known parameters and then applied to Hollin Hill. The
 results are promising and show agreement with other (conventional) methods
 of determining these parameters, demonstrating that hydrogeophysical
 modelling can be used successfully for calibrating landslide models.
 However, there are limitations with this approach as assumptions with
 petrophysical relationships and modelling domain must be made. 
 
 Overall ERI is a valuable tool for enhancing the understanding of
 landslide structures and moisture content conditions. Time-lapse
 processing can illuminate moisture content dynamics, and with appropriate
 petrophysical calibration ERI volumes can be mapped into moisture content
 and matric potential. Coupled hydrogeophysical approaches can be further
 used to constrain unsaturated fluid flow parameters in landslide models.
 As such, geoelectrical monitoring of landslides is a viable tool,
 alongside pre-existing conventional methods, for continued assessment of
 unstable slopes and model construction.