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2010

Soil moisture

Articles 1 - 8 of 8

Full-Text Articles in Physical Sciences and Mathematics

Characterization Of Soil Water Content Variability And Soil Texture Using Gpr Groundwave Techniques, Katherine R. Grote, Cale T. Anger, Bridget Kelly, Susan Sharpless Hubbard, Yoram N. Rubin Sep 2010

Characterization Of Soil Water Content Variability And Soil Texture Using Gpr Groundwave Techniques, Katherine R. Grote, Cale T. Anger, Bridget Kelly, Susan Sharpless Hubbard, Yoram N. Rubin

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Accurate characterization of near-surface soil water content is vital for guiding agricultural management decisions and for reducing the potential negative environmental impacts of agriculture. Characterizing the near-surface soil water content can be difficult, as this parameter is often both spatially and temporally variable, and obtaining sufficient measurements to describe the heterogeneity can be prohibitively expensive. Understanding the spatial correlation of near-surface soil water content can help optimize data acquisition and improve understanding of the processes controlling soil water content at the field scale. In this study, ground penetrating radar (GPR) methods were used to characterize the spatial correlation of water …

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Factors Influencing Soil Moisture At The Hillslope Scale In A Semi-Arid Mountainous Environment, Ivan John Geroy Aug 2010

Factors Influencing Soil Moisture At The Hillslope Scale In A Semi-Arid Mountainous Environment, Ivan John Geroy

Boise State University Theses and Dissertations

Soil moisture couples ground, surface, and atmospheric water interactions via the processes of evapotranspiration, infiltration, and runoff generation (Grayson et al., 1997). Consequently, understanding the factors that influence the spatial distribution of soil moisture is vitally important to the accurate conceptualization and modeling of watershed processes. Typically, topographic indexing methods for the prediction of soil moisture have been studied in temperate or humid areas where the soil profile is often saturated and redistribution of soil moisture is driven by topography (Famiglietti et al., 1998; Grayson et al., 1997; Western et al., 1999). By contrast, in semi-arid environments, long periods of …

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Sensitivity Analysis Of B-Factor In Microwave Emission Model For Soil Moisture Retrieval: A Case Study For Smap Mission, Dugwon Seo, Tarendra Lakhankar, Reza Khanbilvardi May 2010

Sensitivity Analysis Of B-Factor In Microwave Emission Model For Soil Moisture Retrieval: A Case Study For Smap Mission, Dugwon Seo, Tarendra Lakhankar, Reza Khanbilvardi

Publications and Research

Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS) and measured field soil moisture from Southern Great Plains experiment (SGP99). The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated …

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Using Soil Moisture Trends Across Topographic Gradients To Examine Controls On Semi-Arid Ecosystem Dynamics, Toni Jo Smith May 2010

Using Soil Moisture Trends Across Topographic Gradients To Examine Controls On Semi-Arid Ecosystem Dynamics, Toni Jo Smith

Boise State University Theses and Dissertations

This study investigated controls on soil water storage and its effect on vegetation cover in a semi-arid, mountainous environment characterized by warm-dry summers and wet-cold winters. Soil moisture and soil temperature were monitored over 286 days at eight sites spanning four elevations (approx. 1100, 1300, 1500, and 1800 m asl), and paired north and south exposures. These sites span an ecological gradient from grass and shrub land to conifer forest. Measurements of soil texture, soil depth, vegetation cover (normalized difference vegetation index, NDVI), and soil carbon content were made at the same sites. Variables that strongly influence the soil water …

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Reproducibility Of Soil Moisture Ensembles When Representing Soil Parameter Uncertainty Using A Latin Hypercube–Based Approach With Correlation Control, Alejandro N. Flores, Dara Entekhabi, Rafael L. Bras Apr 2010

Reproducibility Of Soil Moisture Ensembles When Representing Soil Parameter Uncertainty Using A Latin Hypercube–Based Approach With Correlation Control, Alejandro N. Flores, Dara Entekhabi, Rafael L. Bras

Alejandro N. Flores

Representation of model input uncertainty is critical in ensemble-based data assimilation. Monte Carlo sampling of model inputs produces uncertainty in the hydrologic state through the model dynamics. Small Monte Carlo ensemble sizes are desirable because of model complexity and dimensionality but potentially lead to sampling errors and correspondingly poor representation of probabilistic structure of the hydrologic state. We compare two techniques to sample soil hydraulic and thermal properties (SHTPs): (1) Latin Hypercube (LH) based sampling with correlation control and (2) random sampling from SHTP marginal distributions. A hydrology model is used to project SHTP uncertainty onto the soil moisture state …

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Reproducibility Of Soil Moisture Ensembles When Representing Soil Parameter Uncertainty Using A Latin Hypercube-Based Approach With Correlation Control, Alejandro N. Flores, Dara Entekhabi, Rafael L. Bras Apr 2010

Reproducibility Of Soil Moisture Ensembles When Representing Soil Parameter Uncertainty Using A Latin Hypercube-Based Approach With Correlation Control, Alejandro N. Flores, Dara Entekhabi, Rafael L. Bras

Geosciences Faculty Publications and Presentations

Representation of model input uncertainty is critical in ensemble‐based data assimilation. Monte Carlo sampling of model inputs produces uncertainty in the hydrologic state through the model dynamics. Small Monte Carlo ensemble sizes are desirable because of model complexity and dimensionality but potentially lead to sampling errors and correspondingly poor representation of probabilistic structure of the hydrologic state. We compare two techniques to sample soil hydraulic and thermal properties (SHTPs): (1) Latin Hypercube (LH) based sampling with correlation control and (2) random sampling from SHTP marginal distributions. A hydrology model is used to project SHTP uncertainty onto the soil moisture state …

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Water Source Partitioning For Shrubland Transpiration Using Innovative Field Methods, Dale A. Devitt, Michael Young, Matthew S. Lachniet, Jeremy Koonce, Amanda Wagner, Brian M. Bird, J. Healey Feb 2010

Water Source Partitioning For Shrubland Transpiration Using Innovative Field Methods, Dale A. Devitt, Michael Young, Matthew S. Lachniet, Jeremy Koonce, Amanda Wagner, Brian M. Bird, J. Healey

2010 Annual Nevada NSF EPSCoR Climate Change Conference

37 PowerPoint slides Convener: Franco Biondi, UNR & Michael Young, DRI Session 4: Ecological Change and Water Resources Abstract: -Climate change models predict a decline in precipitation over the next few decades throughout much of the southwest. -Such change has the potential to shift water uptake dynamics of phreatophytes -If groundwater pumping also occurs, the impact of climate change could be exacerbated. -A better understanding of the forces that drive the coupling and decoupling of phreatophytes to groundwater is needed.

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Sensitivity Of Planetary Boundary Layer To Varying Volumetric Soil Moisture: A Mesoscale Models Comparision, Asrid Suarez Gonzalez Jan 2010

Sensitivity Of Planetary Boundary Layer To Varying Volumetric Soil Moisture: A Mesoscale Models Comparision, Asrid Suarez Gonzalez

Mahurin Honors College Capstone Experience/Thesis Projects

A comparison between two Mesoscale models, Colorado State University Regional Atmospheric Model System (RAMS) version 4.4 coupled with the Land‐Ecosystem– Atmosphere Feedback Model (LEAF2) and Penn State/NCAR’s Mesoscale Model (MM5) coupled with NOAH Land Surface Model, was conducted in order to assess the sensitivity of forecasted boundary layer variables to anomalous volumetric soil moistures. The study elaborates on the findings of Quintanar et al. (2008) using the study’s experimental design as a template for our numerical model comparison. The experiments were conducted using the same synoptic events examined by Quintanar et al. (2008): June 11, June 17 and June 22, …

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