Absolute Gravity and Uplift in the Yellowstone Caldera

GPS time-series of uplift show that points in and around the caldera have gone through cycles of uplift, followed by subsidence since observations began about three decades ago. A dramatic increase in the uplift rate started in 2004 at the GPS station LKWY near Yellowstone Lake and Old Faithful, OFWY. Since 2010, the sites have subsided, began uplifting again in 2014 coincidentally after a M 4.8 earthquake near the Norris Geyser Basin, and then started subsiding again in 2016. The cause of the episodic uplift and subsidence and the spatial pattern of the surface displacement are not yet well understood. The 2003-2009 episode of rapid uplift is believed to result from deep source magma intrusion simultaneous with depressurization of the hydrothermal systems beneath the Norris Geyser Basin. But whether it is caused by the intrusion of magma from a distant reservoir, or by the expulsion and localized trapping of pressurized water and gas from rock that is already in-place, is not known. We have taken observations of absolute gravity at LKWY and OFWY almost annually since 2009. In this presentation, we compare gravity and uplift and provide some insight into the mechanism driving the uplift/subsidence cycles

Autonomous Formation Flight using Solar Radiation Pressure

Autonomous formation flight enables new satellite missions for novel applications. The cost and limits of propulsion systems can be overcome if environmental resources are being benefitted of. Currently, atmospheric drag is used in low Earth orbit to this end. Solar radiation pressure, which is of similar order of magnitude as aerodynamic ram pressure, is, however, always neglected. We introduce this force and show that it can be exploited. We demonstrate through simulations that a formation geometry is established quicker if the solar radiation pressure is modeled

Absolute Gravity Measurements in Yellowstone in September 2009

This report contains the results of absolute gravity measurements carried out in Yellowstone in September 2009. The absolute gravimeter FG5#111 from the National Science Foundation (USA) has been used. The vertical gravity gradient as well as local gravity tied were measured with the spring gravimeter Scintrex from the University of Luxembourg. The objective of this first absolute gravity campaign was to establish two new AG stations in Yellowstone. One was installed in Lake and the other one at Old Faithful

Hybrid mesh/particle meshless method for modeling geological flows with discontinuous transport properties

In the present paper, we introduce the Finite Difference Method-Meshless Method (FDM-MM) in the context of geodynamical simulations. The proposed numerical scheme relies on the well-established FD method along with the newly developed “meshless” method and, is considered as a hybrid Eulerian/Lagrangian scheme. Mass, momentum, and energy equations are solved using an FDM method, while material properties are distributed over a set of markers (particles), which represent the spatial domain, with the solution interpolated back to the Eulerian grid. The proposed scheme is capable of solving flow equations (Stokes flow) in uniform geometries with particles, “sprinkled” in the spatial domain and is used to solve convection- diffusion problems avoiding the oscillation produced in the Eulerian approach. The resulting algebraic linear systems were solved using direct solvers. Our hybrid approach can capture sharp variations of stresses and thermal gradients in problems with a strongly variable viscosity and thermal conductivity as demonstrated through various benchmarking test cases. The present hybrid approach allows for the accurate calculation of fine thermal structures, offering local type adaptivity through the flexibility of the particle method

Using random circular models to simulate stochastic anisotropic flow in aquifer systems with FEniCSx

The flow of water in many aquifers is driven by strong anisotropy created by preferential flow features such as cracks and faults. This anisotropy can be modelled by introducing anisotropic hydraulic conductivity tensor (AHC) into the equations of poroelasticity. Our overall goal is to assimilate InSAR remote sensing data into a model of an aquifer system in order to infer information about AHC. Previous studies have modelled the hydraulic conductivity as a spatially varying isotropic Gaussian process (Alghamdi et al. 2020). In this work we develop a flexible stochastic prior model of the AHC tensor that respects its underlying symmetry and positive definiteness. Our method for calibrating and constructing a random model for the AHC tensor consists of three steps; 1) We fit a Bayesian model consisting of a mixture of circular von Mises distributions to fracture outcrop data. 2) We fit a Bayesian model of two independent log-normals to existing estimates of the hydraulic conductivity in the principal directions. Then in the last step 3) these stochastic models are then simultaneously fed into an extended version of the model by Shivanand et al. (2024) for constructing random symmetric positive definite tensors. This model leverages the spectral decomposition to enable the separate encoding of size and orientation. The overall methodology is demonstrated via a stochastic finite element model of the Anderson Junction aquifer test developed in our previous study (Salehian et al. 2024) following the aquifer pumping test described in Heilweil and Hsieh (2006).15. Life on lan

Using random circular models in aquifer flow simulation

15. Life on lan

Assimilation of GRACE terrestrial water storage into a land surface model: Evaluation and potential value for drought monitoring in western and central Europe

A land surface model’s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff estimates (in temporal correlation and root mean square error) in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. GRACE data assimilation also had significant impacts in groundwater estimates including trend and seasonality. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. The assimilation downscaled (in space and time) and disaggregated GRACE data into finer scale components of TWS which exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation. Mass imbalances associated with GRACE data assimilation and challenges of using GRACE data for drought monitoring are discussed

Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation