Tier-Scalable Reconnaissance Missions For The Autonomous Exploration Of Planetary Bodies

A fundamentally new (scientific) reconnaissance mission concept, termed tier-scalable reconnaissance, for remote planetary (including Earth) atmospheric, surface and subsurface exploration recently has been devised that soon will replace the engineering and safety constrained mission designs of the past, allowing for optimal acquisition of geologic, paleohydrologic, paleoclimatic, and possible astrobiologic information of Venus, Mars, Europa, Ganymede, Titan, Enceladus, Triton, and other extraterrestrial targets. This paradigm is equally applicable to potentially hazardous or inaccessible operational areas on Earth such as those related to military or terrorist activities, or areas that have been exposed to biochemical agents, radiation, or natural disasters. Traditional missions have performed local, ground-level reconnaissance through rovers and immobile landers, or global mapping performed by an orbiter. The former is safety and engineering constrained, affording limited detailed reconnaissance of a single site at the expense of a regional understanding, while the latter returns immense datasets, often overlooking detailed information of local and regional significance

Time-lapse gravity data for monitoring and modeling artificial recharge through a thick unsaturated zone

Groundwater-level measurements in monitoring wells or piezometers are the most common, and often the only, hydrologic measurements made at artificial recharge facilities. Measurements of gravity change over time provide an additional source of information about changes in groundwater storage, infiltration, and for model calibration. We demonstrate that for an artificial recharge facility with a deep groundwater table, gravity data are more sensitive to movement of water through the unsaturated zone than are groundwater levels. Groundwater levels have a delayed response to infiltration, change in a similar manner at many potential monitoring locations, and are heavily influenced by high-frequency noise induced by pumping; in contrast, gravity changes start immediately at the onset of infiltration and are sensitive to water in the unsaturated zone. Continuous gravity data can determine infiltration rate, and the estimate is only minimally affected by uncertainty in water-content change. Gravity data are also useful for constraining parameters in a coupled groundwater-unsaturated zone model (Modflow-NWT model with the Unsaturated Zone Flow (UZF) package).USGS Groundwater Resources Program; NSF [EAR-1246619]; Arizona Water, Environmental, and Energy Solutions programFirst published: 22 September 2016; 6 Month Embargo.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression

Surface barriers are commonly installed to reduce downward water movement into contaminated zones. Specifically, evapotranspiration (ET) barriers are used to store water and release it, via ET, before it can percolate into an underlying waste zone. To assess the effectiveness of a surface barrier, we used an existing data set, model‐simulated data, and a dimensionality reduction approach called universal multiple linear regression (uMLR) to optimize the required number of sensors in a 2‐m thick surface barrier. To understand the usefulness of implementing predictive uMLR to accommodate multiple monitoring objectives, we compare several network designs, selected based on down‐sampling of existing data, with a recommended sensor design based on model simulations performed without consideration of existing data. We also added consideration of “fuzzy” design, which allows more practical guidelines for field implementation of uMLR. We found that uMLR, combined with robust decision‐making, provides a simple, flexible, and high‐quality network design for monitoring the total water stored in a surface barrier across multiple uncertain conditions.6 month embargo; published online: 22 October 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

How Soil Freezes and Thaws at a Snow-Dominated Forest Site in the U.S.—A Synthetic Approach Using the Soil and Cold Regions Model (SCRM)

The freeze–thaw process controls several hydrologic processes, including infiltration, runoff, and soil erosion. Simulating this process is important, particularly in cold and mountainous regions. The Soil and Cold Regions Model (SCRM) was used to simulate, study, and understand the behavior of twelve homogenous soils subject to a freeze–thaw process, based on meteorological data at a snow-dominated forest site in Laramie, WY, USA, from 2010 and 2012. The relationships of soil pore size, soil particle contact, and meteorological data were varied. Our analysis of the model compared simulations using metrics such as soil frost depth, days with ice, and maximum ice content. The model showed that the freeze–thaw process was strongest in the period with a shallow snowpack, with particle packing within the soil profile being an important factor in this process; that soil texture and water content control soil thermal properties; and that water movement towards the freezing front was especially important in fine-textured soils, where water and ice were concentrated in the upper layers. Based on these results, future research that combines a broader set of soil conditions with an extended set of field meteorology and real soil data could elucidate the influence of soil texture on the thermal properties related to soil frost

How Soil Freezes and Thaws at a Snow-Dominated Forest Site in the U.S.—A Synthetic Approach Using the Soil and Cold Regions Model (SCRM)

The freeze–thaw process controls several hydrologic processes, including infiltration, runoff, and soil erosion. Simulating this process is important, particularly in cold and mountainous regions. The Soil and Cold Regions Model (SCRM) was used to simulate, study, and understand the behavior of twelve homogenous soils subject to a freeze–thaw process, based on meteorological data at a snow-dominated forest site in Laramie, WY, USA, from 2010 and 2012. The relationships of soil pore size, soil particle contact, and meteorological data were varied. Our analysis of the model compared simulations using metrics such as soil frost depth, days with ice, and maximum ice content. The model showed that the freeze–thaw process was strongest in the period with a shallow snowpack, with particle packing within the soil profile being an important factor in this process; that soil texture and water content control soil thermal properties; and that water movement towards the freezing front was especially important in fine-textured soils, where water and ice were concentrated in the upper layers. Based on these results, future research that combines a broader set of soil conditions with an extended set of field meteorology and real soil data could elucidate the influence of soil texture on the thermal properties related to soil frost

Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles

<p>Code and datasets accompanying HESS article titled: Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles.</p&gt