The Soil Moisture Active Passive Marena, Oklahoma, In Situ Sensor Testbed (SMAP-MOISST): Testbed Design and Evaluation of In Situ Sensors

n situ soil moisture monitoring networks are critical to the development of soil moisture remote sensing missions as well as agricultural and environmental management, weather forecasting, and many other endeavors. These in situ networks utilize a variety of sensors and installation practices, which confounds the development of a unified reference database for satellite calibration and validation programs. As part of the Soil Moisture Active Passive Mission, the Marena, Oklahoma, In Situ Sensor Testbed (SMAP-MOISST) was initiated to perform inter-comparisons and study sensor limitations. Soil moisture sensors that are deployed in major monitoring networks were included in the study, along with new and emerging technologies, such as the Cosmic Ray Soil Moisture Observing System (COSMOS), passive/active distributed temperature sensing (DTS), and global positioning system reflectometers (GPSR). Four profile stations were installed in May of 2010, and soil moisture was monitored to a depth of 1 m on an hourly basis. The four stations were distributed within a circular domain of approximately 600 m diameter, adequate to encompass the sensing range of COSMOS. The sensors included in the base station configuration included the Stevens Water Hydra Probe, Campbell Scientific 616 and 229, Decagon EC-TM, Delta-T Theta Probe, Acclima, and Sentek EnviroSMART capacitance system. In addition, the Pico TRIME system and additional time-domain reflectometry (TDR) systems were deployed when available. It was necessary to apply site-specific calibration to most sensors to reach an RMSE below 0.04 m³ m⁻³. For most sensor types, a single near surface sensor could be scaled to represent the areal-average of a field domain by simple linear regression, resulting in RMSE values around 0.03 m³ m⁻³.This is the publisher’s final pdf. The published article is copyrighted by the Soil Science Society of America and can be found at: https://dl.sciencesocieties.org/publications/vz

Detecting forest response to droughts with global observations of vegetation water content

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analog of the pressure-volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions-which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Validation of the Body Concealment Scale for Scleroderma (BCSS): Replication in the Scleroderma Patient-centered Intervention Network (SPIN) Cohort

© 2016 Elsevier Ltd Body concealment is an important component of appearance distress for individuals with disfiguring conditions, including scleroderma. The objective was to replicate the validation study of the Body Concealment Scale for Scleroderma (BCSS) among 897 scleroderma patients. The factor structure of the BCSS was evaluated using confirmatory factor analysis and the Multiple-Indicator Multiple-Cause model examined differential item functioning of SWAP items for sex and age. Internal consistency reliability was assessed via Cronbach's alpha. Construct validity was assessed by comparing the BCSS with a measure of body image distress and measures of mental health and pain intensity. Results replicated the original validation study, where a bifactor model provided the best fit. The BCSS demonstrated strong internal consistency reliability and construct validity. Findings further support the BCSS as a valid measure of body concealment in scleroderma and provide new evidence that scores can be compared and combined across sexes and ages

Modeling SAR Observables by Combining a Crop-Growth Model With Machine Learning

In this article, our aim is to estimate synthetic aperture radar (SAR) observables, such as backscatter in VV and VH polarizations, as well as the VH/VV ratio, cross ratio, and interferometric coherence in VV, from agricultural fields. In this study, we use the decision support system for agrotechnology transfer (DSSAT) crop-growth simulation model to simulate parcel-level phenological and growth parameters for over 1500 parcels of silage maize in the Netherlands. The crop model was calibrated using field data, including silage maize phenological phases, leaf area index, and above-ground dry biomass (AGB). The simulations incorporate fine-resolution gridded precipitation data and soil parameters to model the interaction between soil–plant–atmosphere and genotype in DSSAT. The crop variables produced by DSSAT are then used as inputs to a support vector regression model. This model is trained to simulate SAR observables in 2017, 2018, and 2019, and its performance is evaluated using independent fields in each of these years. The results show a close fit between modeled and observed SAR C-band observables. The importance of vegetation variables in the estimation of SAR observables is assessed. The AGB showed significant importance in the estimation of backscatter. This study demonstrates the potential value of combining crop-growth simulation models and machine learning to simulate SAR observables. For example, the SVR model developed here could be used as an observation operator in an assimilation context to constrain vegetation and soil water dynamics in a crop-growth model

Non-invasive estimation of moisture content in tuff bricks by GPR

Measuring water content in buildings of historical value requires non-invasive techniques to avoid the damage that sample taking or probe insertion may cause to the investigated walls. With this aim, a stepped frequency ground penetrating radar (GPR) system was tested to assess its applicability in moisture measurements of porous masonry elements. The technique was tested on a real scale wall made with yellow Neapolitan tuff bricks, a material commonly found in historical buildings of Campania (Southern Italy). First, the antenna was calibrated to find its characteristic transfer functions. Then 64 GPR acquisitions, coupled with gravimetric measurements of the volumetric water content, were performed on the tuff wall in laboratory controlled conditions. A full inverse modelling of the GPR signal on tuff was used to retrieve dielectric permittivity and electrical conductivity of tuff at various water contents. By linking these characteristic electromagnetic parameters to the water content, the calibration relationships specific for yellow Neapolitan tuff are defined, which can be used for moisture measurements by GPR in real case studies. The experimental results lead to a robust identification of clearly defined monotonic relationships for dielectric permittivity and electrical conductivity. These are characterized by high values of the correlation coefficient, indicating that both parameters are potentially good proxies for water content of tuff. The results indicate that GPR represents a promising indirect technique for reliable measurements of water content in tuff walls and, potentially, in other porous building materials

Non-invasive water content estimation in a tuff wall by DTS

Undesired presence of water in historical masonries has a negative effect on the walls and causes deterioration of decorative works covering the walls, such as frescoes and valuable plasters. To prevent this, non-invasive moisture measurements are needed that avoid damage during masonry inspection caused by sample taking or probe insertion. Active heated distributed temperature sensing (DTS) with optical fibres is widely used in hydrology to assess soil moisture content. The aim of this study is to examine the potential of this technique for non-invasive water content measurements in a real scale wall. The tested masonry is made of yellow Neapolitan tuff bricks, a material widely used in historical buildings of Campania (Southern Italy). Distributed temperature measurements are carried out with three different heating strategies (different power and duration) during the drying process following the complete saturation of the wall. The acquired temperature data are then processed with three different methods (estimators), so to identify the best combination of heating strategy and data processing approach. Despite the presence of a significant bias, it is possible to identify relationships between the gravimetric moisture content and the different estimators. Those relationships are influenced to a large degree by the thermal contact between the DTS cable and the masonry. This research shows it is possible to measure water content in tuff masonry using non-invasive active heated fibre optic cable when establishing good thermal contact between the cable and the masonry