Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data

Studies indicate greenhouse gas emissions following permafrost thaw will amplify current rates of atmospheric warming, a process referred to as the permafrost carbon feedback. However, large uncertainties exist regarding the timing and magnitude of the permafrost carbon feedback, in part due to uncertainties associated with subsurface permafrost parameterization and structure. Development of robust parameter estimation methods for permafrost-rich soils is becoming urgent under accelerated warming of the Arctic. Improved parameterization of the subsurface properties in land system models would lead to improved predictions and a reduction of modeling uncertainty. In this work we set the groundwork for future parameter estimation (PE) studies by developing and evaluating a joint PE algorithm that estimates soil porosities and thermal conductivities from time series of soil temperature and moisture measurements and discrete in-time electrical resistivity measurements. The algorithm utilizes the Model-Independent Parameter Estimation and Uncertainty Analysis toolbox and coupled hydrological-thermal-geophysical modeling. We test the PE algorithm against synthetic data, providing a proof of concept for the approach. We use specified subsurface porosities and thermal conductivities and coupled models to set up a synthetic state, perturb the parameters, and then verify that our PE method is able to recover the parameters and synthetic state. To evaluate the accuracy and robustness of the approach we perform multiple tests for a perturbed set of initial starting parameter combinations. In addition, we varied types and quantities of data to better understand the optimal dataset needed to improve the PE method. The results of the PE tests suggest that using multiple types of data improve the overall robustness of the method. Our numerical experiments indicate that special care needs to be taken during the field experiment setup so that (1) the vertical distance between adjacent measurement sensors allows the signal variability in space to be resolved and (2) the longer time interval between resistivity snapshots allows signal variability in time to be resolved

Hydrological Parameter Estimations from a Conservative Tracer Test with Variable-Density Effects at the Boise Hydrogeophysical Research Site

Reliable predictions of groundwater flow and solute transport require an estimation of the detailed distribution of the parameters (e.g., hydraulic conductivity, effective porosity) controlling these processes. However, such parameters are difficult to estimate because of the inaccessibility and complexity of the subsurface. In this regard, developments in parameter estimation techniques and investigations of field experiments are still challenging and necessary to improve our understanding and the prediction of hydrological processes. Here we analyze a conservative tracer test conducted at the Boise Hydrogeophysical Research Site in 2001 in a heterogeneous unconfined fluvial aquifer. Some relevant characteristics of this test include: variable-density (sinking) effects because of the injection concentration of the bromide tracer, the relatively small size of the experiment, and the availability of various sources of geophysical and hydrological information. The information contained in this experiment is evaluated through several parameter estimation approaches, including a grid-search-based strategy, stochastic simulation of hydrological property distributions, and deterministic inversion using regularization and pilot-point techniques. Doing this allows us to investigate hydraulic conductivity and effective porosity distributions and to compare the effects of assumptions from several methods and parameterizations. Our results provide new insights into the understanding of variable-density transport processes and the hydrological relevance of incorporating various sources of information in parameter estimation approaches. Among others, the variable-density effect and the effective porosity distribution, as well as their coupling with the hydraulic conductivity structure, are seen to be significant in the transport process. The results also show that assumed prior information can strongly influence the estimated distributions of hydrological properties

Three-Dimensional Stochastic Estimation of Porosity Distribution: Benefits of Using Ground-Penetrating Radar Velocity Tomograms in Simulated-Annealing-Based or Bayesian Sequential Simulation Approaches

Estimation of the three-dimensional (3-D) distribution of hydrologic properties and related uncertainty is a key for improved predictions of hydrologic processes in the subsurface. However it is difficult to gain high-quality and high-density hydrologic information from the subsurface. In this regard a promising strategy is to use high-resolution geophysical data (that are relatively sensitive to variations of a hydrologic parameter of interest) to supplement direct hydrologic information from measurements in wells (e.g., logs, vertical profiles) and then generate stochastic simulations of the distribution of the hydrologic property conditioned on the hydrologic and geophysical data. In this study we develop and apply this strategy for a 3-D field experiment in the heterogeneous aquifer at the Boise Hydrogeophysical Research Site and we evaluate how much benefit the geophysical data provide. We run high-resolution 3-D conditional simulations of porosity with both simulated-annealing-based and Bayesian sequential approaches using information from multiple intersecting crosshole gound-penetrating radar (GPR) velocity tomograms and neutron porosity logs. The benefit of using GPR data is assessed by investigating their ability, when included in conditional simulation, to predict porosity log data withheld from the simulation. Results show that the use of crosshole GPR data can significantly improve the estimation of porosity spatial distribution and reduce associated uncertainty compared to using only well log measurements for the estimation. The amount of benefit depends primarily on the strength of the petrophysical relation between the GPR and porosity data, the variability of this relation throughout the investigated site, and lateral structural continuity at the site

Understanding the relative importance of vertical and horizontal flow in ice-wedge polygons

Ice-wedge polygons are common Arctic landforms. The future of these landforms in a warming climate depends on the bidirectional feedback between the rate of ice-wedge degradation and changes in hydrological characteristics. This work aims to better understand the relative roles of vertical and horizontal water fluxes in the subsurface of polygonal landscapes, providing new insights and data to test and calibrate hydrological models. Field-scale investigations were conducted at an intensively instrumented location on the Barrow Environmental Observatory (BEO) near Utqiagvik, AK, USA. Using a conservative tracer, we examined controls of microtopography and the frost table on subsurface flow and transport within a low-centered and a high-centered polygon. Bromide tracer was applied at both polygons in July 2015 and transport was monitored through two thaw seasons. Sampler arrays placed in polygon centers, rims, and troughs were used to monitor tracer concentrations. In both polygons, the tracer first infiltrated vertically until encountering the frost table and was then transported horizontally. Horizontal flow occurred in more locations and at higher velocities in the low-centered polygon than in the high-centered polygon. Preferential flow, influenced by frost table topography, was significant between polygon centers and troughs. Estimates of horizontal hydraulic conductivity were within the range of previous estimates of vertical conductivity, highlighting the importance of horizontal flow in these systems. This work forms a basis for understanding complexity of flow in polygonal landscapes

Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High-Resolution Remote Sensing and Surface Geophysical Data

This study aims to investigate the microtopographic controls that dictate the heterogeneity of plant communities in a mountainous floodplain-hillslope system, using remote sensing and surface geophysical techniques. Working within a lower montane floodplain-hillslope study site (750 m × 750 m) in the Upper Colorado River Basin, we developed a new data fusion framework, based on machine learning and feature engineering, that exploits remote sensing optical and light detection and ranging (LiDAR) data to estimate the distribution of key plant meadow communities at submeter resolution. We collected surface electrical resistivity tomography data to explore the variability in soil properties along a floodplain-hillslope transect at 0.50-m resolution and extracted LiDAR-derived metrics to model the rapid change in microtopography. We then investigated the covariability among the estimated plant community distributions, soil information, and topographic metrics. Results show that our framework estimated the distribution of nine plant communities with higher accuracy (87% versus 80% overall; 85% versus 60% for shrubs) compared to conventional classification approaches. Analysis of the covariabilities reveals a strong correlation between plant community distribution, soil electric conductivity, and slope, indicating that soil moisture is a primary control on heterogeneous spatial distribution. At the same time, microtopography plays an important role in creating particular ecosystem niches for some of the communities. Such relationships could be exploited to provide information about the spatial variability of soil properties. This highly transferable framework can be employed within long-term monitoring to capture community-specific physiological responses to perturbations, offering the possibility of bridging local plot-scale observations with large landscape monitoring

The use of happiness research for public policy

Research on happiness tends to follow a "benevolent dictator" approach where politicians pursue people's happiness. This paper takes an antithetic approach based on the insights of public choice theory. First, we inquire how the results of happiness research may be used to improve the choice of institutions. Second, we show that the policy approach matters for the choice of research questions and the kind of knowledge happiness research aims to provide. Third, we emphasize that there is no shortcut to an optimal policy maximizing some happiness indicator or social welfare function since governments have an incentive to manipulate this indicator

A micromanipulation setup for comparative tests of microgrippers

A micromanipulation setup allowing comparative tests of manipulation micro tools has been developed. Repeatability measurements of positioning as well as optimization of manipulation conditions can be run with parts of typically 5 to 50μm over a large set of parameters including environment conditions, substrate and tip specifications, and different strategies (robot trajectories at picking and releasing time). The workstation consists of a high precise parallel robot, the Delta3, to position the gripper, linear stages to place the parts in the field of view and two microscopes for the visual feedback and position measurement. The setup is placed in a chamber for controlling relative humidity and temperature. An interface was developed to integrate every kind of tool on the robot. Automated operations and measurement have been carried out based on localization and tracking of micro objects and gripper. Integration of micro tools was successfully accomplished and comparative tests were executed with micro tweezers. Sub micrometer position repeatability was achieved with a success rate of pick and pick operations of 95%

Characterization of micro manipulation tasks operated with various controlled conditions by microtweezers

Micro manipulation tasks with micro tweezers were operated in different configurations. This paper discusses the main issues of pick and place operations with micro tweezers as geometric consideration, grasping force and quality of the contact surfaces. This study is based on positioning repeatability measurements and success rate of the tasks operated automatically on our micro manipulation setup. Results for a MEMS micro gripper show a high reliability of more than 90% of success rate and positioning repeatability under the micrometer

Micro-gripper à haute dynamique

Dans le monde microscopique, la force de gravité devient négligeable par rapport aux forces d’adhésion (capillarité, Van der Waals). Ce projet vise à utiliser ces forces pour la prise de bille d’une taille caractéristique de 50[μm]. La dépose quand à elle s’effectue de manière dynamique, en utilisant l’inertie de la bille soumise à une forte accélération. Le but de ce projet est de caractériser la prise (taux de succès) et la dépose (seuil d’accélération, taux de succès, précision et répétabilité). La prise dépend essentiellement du type de matériaux utilisés ; sa caractérisation a été faite pour un gripper en silicium et un gripper en verre dans l’air ambiant (20% humidité relative) et l’azote (3%). Pour fournir une accélération, un piézoélectrique est utilisé (cristal qui se déforme lorsqu’une tension est appliquée à ses bornes). L’avantage principal est que la déformation est bien contrôlable en intensité et direction. La dépose quand à elle a été caractérisée dans les mêmes conditions que la prise et en excitant le piézoélectrique avec des sinus continus ou en créant une seule impulsion Au final, il a été montré que cette technique est viable pour la micromanipulation. Toutefois des points clés nécessaires à un bon contrôle des opérations ont été identifiés, notamment au niveau de la rigidité du substrat pour éviter l’écrasement des objets et au niveau de la qualité des surfaces de contact