High frequency un-mixing of soil samples using a submerged spectrophotometer in a laboratory setting—implications for sediment fingerprinting

Purpose This study tests the feasibility of using a submersible spectrophotometer as a novel method to trace and apportion suspended sediment sources in situ and at high temporal frequency. Methods Laboratory experiments were designed to identify how absorbance at different wavelengths can be used to un-mix artificial mixtures of soil samples (i.e. sediment sources). The experiment consists of a tank containing 40 L of water, to which the soil samples and soil mixtures of known proportions were added in suspension. Absorbance measurements made using the submersible spectrophotometer were used to elucidate: (i) the effects of concentrations on absorbance, (ii) the relationship between absorbance and particle size and (iii) the linear additivity of absorbance as a prerequisite for un-mixing. Results The observed relationships between soil sample concentrations and absorbance in the ultraviolet visible (UV–VIS) wavelength range (200–730 nm) indicated that differences in absorbance patterns are caused by soil-specific properties and particle size. Absorbance was found to be linearly additive and could be used to predict the known soil sample proportions in mixtures using the MixSIAR Bayesian tracer mixing model. Model results indicate that dominant contributions to mixtures containing two and three soil samples could be predicted well, whilst accuracy for four-soil sample mixtures was lower (with respective mean absolute errors of 15.4%, 12.9% and 17.0%). Conclusion The results demonstrate the potential for using in situ submersible spectrophotometer sensors to trace suspended sediment sources at high temporal frequency.

A Development Strategy for SHM Applications

Permanently installed SHM systems are now a viable alternative to traditional periodic inspection (NDT). However, their industrial use is limited and this paper reviews the steps required in developing practical SHM systems. The transducers used in SHM are fixed in location, whereas in NDT they are generally scanned. The aim is to reach similar performance with high temporal frequency, low spatial frequency SHM data to that achievable with conventional high spatial frequency, low temporal frequency NDT inspections. It is shown that this can be done via change tracking algorithms such as the Generalized Likelihood Ratio (GLR) but this depends on the input data being normally distributed, which can only be achieved if signal changes due to variations in the operating conditions are satisfactorily compensated; there has been much recent progress on this topic and this is reviewed. Since SHM systems can generate large volumes of data, it is essential to convert the data to actionable information, and this step must be addressed in SHM system design. It is also essential to validate the performance of installed SHM systems, and a methodology analogous to the model assisted POD (MAPOD) scheme used in NDT has been proposed. This uses measurements obtained from the SHM system installed on a typical undamaged structure to capture signal changes due to environmental and other effects, and to superpose the signal due to damage growth obtained from finite element predictions. There is a substantial research agenda to support the wider adoption of SHM and this is discussed.

Reviews and syntheses: Ongoing and emerging opportunities to improve environmental science using observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites

Environmental science is increasingly reliant on remotely sensed observations of the Earth's surface and atmosphere. Observations from polar-orbiting satellites have long supported investigations on land cover change, ecosystem productivity, hydrology, climate, the impacts of disturbance, and more and are critical for extrapolating (upscaling) ground-based measurements to larger areas. However, the limited temporal frequency at which polar-orbiting satellites observe the Earth limits our understanding of rapidly evolving ecosystem processes, especially in areas with frequent cloud cover. Geostationary satellites have observed the Earth's surface and atmosphere at high temporal frequency for decades, and their imagers now have spectral resolutions in the visible and near-infrared regions that are comparable to commonly used polar-orbiting sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), or Landsat. These advances extend applications of geostationary Earth observations from weather monitoring to multiple disciplines in ecology and environmental science. We review a number of existing applications that use data from geostationary platforms and present upcoming opportunities for observing key ecosystem properties using high-frequency observations from the Advanced Baseline Imagers (ABI) on the Geostationary Operational Environmental Satellites (GOES), which routinely observe the Western Hemisphere every 5–15 min. Many of the existing applications in environmental science from ABI are focused on estimating land surface temperature, solar radiation, evapotranspiration, and biomass burning emissions along with detecting rapid drought development and wildfire. Ongoing work in estimating vegetation properties and phenology from other geostationary platforms demonstrates the potential to expand ABI observations to estimate vegetation greenness, moisture, and productivity at a high temporal frequency across the Western Hemisphere. Finally, we present emerging opportunities to address the relatively coarse resolution of ABI observations through multisensor fusion to resolve landscape heterogeneity and to leverage observations from ABI to study the carbon cycle and ecosystem function at unprecedented temporal frequency.

In-situ UV-Visible spectrometry as an alternative to determine solute concentrations at high temporal frequency in organic-rich stream waters

<p>In-situ monitoring of the temporal variation of solutes’ (nutrients and metals) concentrations as tracers can enhance knowledge of the hydrological and biogeochemical behavior of catchments. UV-Visible spectrometry represents a relatively inexpensive and easily used tool to explore how those concentrations vary in time at high temporal frequency. However, it is not yet clear which are the best calibration methods and which solutes can be modeled with this approach. In this investigation we explored the relationship between solutes’ concentrations and wavelength absorbance in the UV-Visible range to find the best calibration method and to identify solutes that could be effectively predicted. To this end, we installed a UV–Visible spectrometer probe in a high-altitude and organic-rich tropical Andean (Páramo) stream to record the wavelength absorbance at a 5-min temporal resolution from December 2017 to March 2019. Simultaneously, we sampled stream water at 4-hour frequency for subsequent determination of solutes via ICP-MS in the laboratory. Our results show that multivariate statistical methods outperformed simpler calibration strategies to model the solutes’ concentrations that could be effectively predicted using calibration and validation datasets. Eleven out of 21 evaluated solutes (Al, DOC, Ca, Cu, K, Mg, N, Na, Rb, Si and Sr) were successfully calibrated (NSE > 0.50). This finding suggests the possibility of calibrating solutes (i.e., metals) that had not previously been calibrated through UV-Visible spectrometry in the field. Interestingly, the calibration was feasible for all solutes that presented a statistically significant correlation with dissolved organic carbon. The findings of this research provide insights into the value of in-situ operation of spectrometers to monitor water quality in organic-rich streams (e.g., peatlands). This research contributes to our understanding of aquatic ecosystems alongside assessing catchment hydrological functioning and also can enhance the protection of human water supplies.</p>

Reviews and syntheses: Ongoing and emerging opportunities to improve environmental science using observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites

Environmental science is increasingly reliant on remotely-sensed observations of the Earth's surface and atmosphere. Observations from polar-orbiting satellites have long supported investigations on land cover change, ecosystem productivity, hydrology, climate, the impacts of disturbance, and more, and are critical for extrapolating (upscaling) ground-based measurements to larger areas. However, the limited temporal frequency at which polar-orbiting satellites observe the Earth limits our understanding of rapidly evolving ecosystem processes, especially in areas with frequent cloud cover. Geostationary satellites have observed the Earth's surface and atmosphere at high temporal frequency for decades, and their imagers now have spectral resolutions in the visible and near-infrared regions that are comparable to commonly-used polar-orbiting sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), or Landsat. These advances extend applications of geostationary Earth observations from weather monitoring to multiple disciplines in ecology and environmental science. We review a number of existing applications that use data from geostationary platforms and present upcoming opportunities for observing key ecosystem properties using high-frequency observations from the Advanced Baseline Imagers (ABI) on the Geostationary Operational Environmental Satellites (GOES), which routinely observe the Western Hemisphere every 5–15 minutes. Many of the existing applications in environmental science from ABI are focused on estimating land surface temperature, solar radiation, evapotranspiration, and biomass burning emissions along with detecting rapid drought development and wildfire. Ongoing work in estimating vegetation properties and phenology from other geostationary platforms demonstrates the potential for expanding ABI observations to estimate vegetation greenness, moisture, and productivity at high temporal frequency across the Western Hemisphere. Finally, we present emerging opportunities to address the relatively coarse resolution of ABI observations through multi-sensor fusion to resolve landscape heterogeneity and to leverage observations from ABI to study the carbon cycle and ecosystem function at unprecedented temporal frequency.

Flicker fusion thresholds as a clinical identifier of a magnocellular-deficit dyslexic subgroup

The magnocellular-dorsal system is well isolated by high temporal frequency. However, temporal processing thresholds have seldom been explored in developmental dyslexia nor its subtypes. Hence, performances on two, four-alternative forced-choice achromatic flicker fusion threshold tasks modulated at low (5%) and high (75%) temporal contrast were compared in dyslexic and neurotypical children individually matched for age and intelligence (8–12 years, n = 54 per group). As expected, the higher modulation resulted in higher flicker fusion thresholds in both groups. Compared to neurotypicals, the dyslexic group displayed significantly lower ability to detect flicker at high temporal frequencies, both at low and high temporal contrast. Yet, discriminant analysis did not adequately distinguish the dyslexics from neurotypicals, on the basis of flicker thresholds alone. Rather, two distinct dyslexic subgroups were identified by cluster analysis – one characterised by significantly lower temporal frequency thresholds than neurotypicals (referred to as ‘Magnocellular-Deficit’ dyslexics; 53.7%), while the other group (‘Magnocellular-Typical’ dyslexics; 46.3%) had comparable thresholds to neurotypicals. The two dyslexic subgroups were not differentially associated with phonological or naming speed subtypes and showed comparable mean reading rate impairments. However, correlations between low modulation flicker fusion threshold and reading rate for the two subgroups were significantly different (p = .0009). Flicker fusion threshold performances also showed strong classification accuracy (79.3%) in dissociating the Magnocellular-Deficit dyslexics and neurotypicals. We propose that temporal visual processing impairments characterize a previously unidentified subgroup of dyslexia and suggest that measurement of flicker fusion thresholds could be used clinically to assist early diagnosis and appropriate treatment recommendations for dyslexia.

Testing the ability of submersible spectrophotometers to trace suspended sediment sources at high-temporal frequency

<p>Reliable and detailed information on the primary sources of suspended sediment (SS) and sediment-associated nutrient and contaminant transfers is needed to target mitigation measures for delivering healthy ecosystems and meeting environmental policy objectives. To this end, the SS source fingerprinting approach is proven an effective tool for assembling reliable information on the sources of SS and SS-associated nutrients and contaminants within a catchment. However, SS source estimates at a high temporal resolution are often lacking due to the high workload and costs involved in collecting and analysing SS and soil samples using conventional means. Given this background, here, we propose the use of submersible spectrophotometers that measure absorbance spectra at 2.5 nm intervals in the 200-750 nm range (UV-VIS) in-situ and at high temporal frequency (i.e. minutes) to fingerprint SS sources. We hypothesise that increasing the measurement frequency will eventually help to better characterise changes in sources over time, whilst also giving further insights on how to improve the classical sediment fingerprinting approach, which is currently based on the use of temporally-lumped data. In this research, we first test our approach under fully controlled conditions in a laboratory experiment. To this end, we use a large cylindrical tank (40-L) equipped with a spectrophotometer as well as a LISST sensor (measuring the effective particle size distribution (PSD)). A mechanical stirring device ensures homogeneous conditions in the system and prevents the settling of soil particles (added in solution). The used soil samples originate from different areas within Luxembourg, whereby a selection was made based on differences in tracer properties and colour. The soils were sieved to three different fractions to take account of PSD control on tracer properties. Using the laboratory experiment, we investigated how suspended particle properties affect the absorbance spectra readings. In particular, we looked at the effects of: (i) increasing concentrations of suspended particles, and; (ii) differences in PSD. We then created artificial mixtures composed of two, three and four soil types mixed in different proportions to investigate if the absorbance readings at different wavelengths (i.e., considered as tracers or fingerprints) can be used to un-mix the known proportions of the SS sources. For this, we used the predictions of MixSIAR, a well-established Bayesian tracer un-mixing model. Our preliminary results indicate the promising use of high resolution absorbance data to un-mix artificial sediment mixtures. Ongoing work is testing the approach at larger scales.</p>