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

2020 ◽  
Author(s):  
Niels Lake ◽  
Núria Martínez-Carreras ◽  
Peter Shaw ◽  
Adrian Collins
Keyword(s):  
Laboratory Experiment ◽  
Suspended Sediment ◽  
Suspended Particle ◽  
Temporal Frequency ◽  
Soil Samples ◽  
Mitigation Measures ◽  
High Temporal Resolution ◽  
Mechanical Stirring ◽  
High Temporal Frequency ◽  
Absorbance Spectra

<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>

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

2021 ◽  
Author(s):  
Niels F. Lake ◽  
Núria Martínez-Carreras ◽  
Peter J. Shaw ◽  
Adrian L. Collins
Keyword(s):  
Particle Size ◽  
Soil Sample ◽  
Suspended Sediment ◽  
Temporal Frequency ◽  
Soil Samples ◽  
Sediment Sources ◽  
High Temporal Frequency ◽  
Novel Method ◽  
The Relationship

Abstract 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.

scholarly journals STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product

2020 ◽  
Vol 12 (19) ◽  
pp. 3209
Author(s):  
Yunan Luo ◽  
Kaiyu Guan ◽  
Jian Peng ◽  
Sibo Wang ◽  
Yizhi Huang
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Satellite Data ◽  
Temporal Frequency ◽  
Fusion Product ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Land Surfaces ◽  
Fine Resolution ◽  
Sentinel 2

Remote sensing datasets with both high spatial and high temporal resolution are critical for monitoring and modeling the dynamics of land surfaces. However, no current satellite sensor could simultaneously achieve both high spatial resolution and high revisiting frequency. Therefore, the integration of different sources of satellite data to produce a fusion product has become a popular solution to address this challenge. Many methods have been proposed to generate synthetic images with rich spatial details and high temporal frequency by combining two types of satellite datasets—usually frequent coarse-resolution images (e.g., MODIS) and sparse fine-resolution images (e.g., Landsat). In this paper, we introduce STAIR 2.0, a new fusion method that extends the previous STAIR fusion framework, to fuse three types of satellite datasets, including MODIS, Landsat, and Sentinel-2. In STAIR 2.0, input images are first processed to impute missing-value pixels that are due to clouds or sensor mechanical issues using a gap-filling algorithm. The multiple refined time series are then integrated stepwisely, from coarse- to fine- and high-resolution, ultimately providing a synthetic daily, high-resolution surface reflectance observations. We applied STAIR 2.0 to generate a 10-m, daily, cloud-/gap-free time series that covers the 2017 growing season of Saunders County, Nebraska. Moreover, the framework is generic and can be extended to integrate more types of satellite data sources, further improving the quality of the fusion product.

Nutrient release from decomposing crop residues in soil: A laboratory experiment

1997 ◽  
Vol 12 (1) ◽  
pp. 10-13 ◽  
Author(s):  
A. Scagnozzi ◽  
A. Saviozzi ◽  
R. Levi-Minzi ◽  
R. Riffaldi
Keyword(s):  
Laboratory Experiment ◽  
Crop Residues ◽  
Nutrient Release ◽  
Soil Samples ◽  
Water Soluble ◽  
Microbial Immobilization ◽  
Total N ◽  
Available N ◽  
Treated Soil ◽  
Quantitative Changes

AbstractIn a 400-day laboratory experiment, soil was amended with rape, sunflower and soybean residues to monitor the quantitative changes in the main inorganic nutrients. Total N, available P, exchangeable K+, Ca2+, and Mg2+ in all the amended samples increased significantly. Generally, the increase in the amounts of these nutrients was maintained until the end of the incubation period, suggesting that the mineralization of the three crop residues enhanced soil fertility. In amended soil samples, disappeared within 14 days, while available N was released as after 60 days in soybean-treated and after 120 days in rape- and sunflower-treated soil, respectively. Water-soluble P was completely lacking in each treatment because of microbial immobilization and adsorption or precipitation processes in soil.

Hazardous nature of high-temporal-frequency strobe light stimulation: neural mechanisms revealed by magnetoencephalography

Neuroscience ◽  
2010 ◽  
Vol 166 (2) ◽  
pp. 482-490 ◽  
Author(s):  
Y. Shigihara ◽  
M. Tanaka ◽  
N. Tsuyuguchi ◽  
H. Tanaka ◽  
Y. Watanabe
Keyword(s):  
Temporal Frequency ◽  
Neural Mechanisms ◽  
Light Stimulation ◽  
Strobe Light ◽  
High Temporal Frequency

scholarly journals Description and validation of an AOT product over land at the 0.6 μm channel of the SEVIRI sensor onboard MSG

2011 ◽  
Vol 4 (11) ◽  
pp. 2543-2565 ◽  
Author(s):  
E. Bernard ◽  
C. Moulin ◽  
D. Ramon ◽  
D. Jolivet ◽  
J. Riedi ◽  
...  
Keyword(s):  
Near Infrared ◽  
Weather Prediction ◽  
Temporal Frequency ◽  
Reasonable Assumption ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Aerosol Model ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Level 2 ◽  
Good Agreement

Abstract. The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to the provision of observations for climate monitoring and research. We use the data in visible and near infrared (NIR) channels to derive the aerosol optical thickness (AOT) over land. The algorithm is based on the assumption that the top of the atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-days time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models is used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and NIR spectral bands. The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3 km at sub-satellite point, over the entire SEVIRI disk covering Europe, Africa and part of South America. The resulting AOT, a level 2 product at the native temporal and spatial SEVIRI resolutions, is presented and evaluated in this paper. The AOT has been validated using ground based measurements from AErosol RObotic NETwork (AERONET), a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, r = 0.64, with a slight overestimate, bias = −0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both datasets show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of Moderate Resolution Imaging Spectroradiometer (MODIS) AOT level 3 product shows qualitative good agreement in the retrieved geographic patterns of AOT. Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies. This paper presents a first evaluation and validation of the derived AOT over Europe in order to document the overall quality of a product that will be made publicly available to the users of the aforementioned research communities.

scholarly journals A Development Strategy for SHM Applications

2021 ◽  
pp. 1-17
Author(s):  
Peter Cawley
Keyword(s):  
Spatial Frequency ◽  
Development Strategy ◽  
Temporal Frequency ◽  
High Spatial Frequency ◽  
Operating Conditions ◽  
Damage Growth ◽  
Periodic Inspection ◽  
High Temporal Frequency ◽  
Industrial Use ◽  
Signal Changes

Abstract 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.

River loggers - a new tool to monitor riverine suspended particle fluxes

2001 ◽  
Vol 43 (9) ◽  
pp. 115-120 ◽  
Author(s):  
A. W. Mitchell ◽  
M. J. Furnas
Keyword(s):  
Suspended Sediment ◽  
Suspended Particle ◽  
Sediment Concentration ◽  
Wet Season ◽  
Overlying Water ◽  
Optical Surfaces ◽  
Sufficient Power ◽  
Suspended Sediment Concentrations ◽  
Fine Suspended Sediment

The Australian Institute of Marine Science (AIMS) has developed an in situ digital turbidity logger (AIMS River Logger) to record time series of fine suspended sediment concentrations in North Queensland rivers. The loggers use dual LED transmissometers (15 and 85 mm pathlength) to measure in situ turbidity associated with the range of suspended sediment concentrations (0-5 g L-1) encountered in regional rivers. A system of wiper brushes clean the optical surfaces prior to instrument readings. Overlying water depth and temperature are concurrently recorded. Internal batteries provide sufficient power for unattended deployments of 6+ months with readings taken at 30 minute intervals. Records of suspended sediment concentrations in the lower Tully River over three wet seasons (1996, 1997, 2000) are shown in relation to concurrent river discharge. Peaks in suspended sediment concentration coincide with discharge events. During each event, peak sediment concentrations typically occur during the rising stage of the hydrograph, then decline rapidly prior to significant falls in water level. Derived suspended loads during discharge events are generally proportional to the size of the event, though higher responses are recorded during the initial flood event of each wet season.

PECULIARITIES OF THE SAND PARTICLES SUSPENDING UNDER INFLUENCE OF THE REGULAR WAVES

2018 ◽  
Author(s):  
М. Крыленко ◽  
M. Krylenko ◽  
Й. Грюне ◽  
Y. Gryune ◽  
Р. Косьян ◽  
...  
Keyword(s):  
Laboratory Experiment ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Time Interval ◽  
Regular Waves ◽  
Large Wave ◽  
Wave Channel ◽  
Sand Particles ◽  
Using Data

In the presented paper some peculiarities of suspending and distribution of sand particles under influence of the regular waves in time interval less than the wave period are discussed using data from laboratory experiment “Hannover 2008”. The experiment was carried out in the Large Wave Channel (GWK). The presented data show that fluctuations of suspended sediment concentration are very largely initiated by individual waves.

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