Leaf Surface Reflectance Does Not Affect Biophysical Traits Modelling from VIS-NIR Spectra in Plants with Sparsely Distributed Trichomes

In this study, we examine leaf reflectance as the main optical property used in remote sensing of vegetation. The total leaf reflectance consists of two main components: a diffuse component, originating from the leaf interior, and a component reflected directly from the leaf surface. The latter contains specular (mirror-like) reflectance (SR) and surface particle scattering, driven by the surface roughness. Our study aimed to (1) reveal the effects of key leaf structural traits on SR in 400–2500 nm, and (2) compare the performance of PLSR models of leaf biophysical properties based on the total reflectance and SR removal reflectance. Four Arabidopsis thaliana structural surface mutants and six Hieracium species differing in trichome properties were studied. PCA did not reveal any systematic effect of trichome density, length, and morphology on SR. Therefore, the results do not support the hypothesis that leaves with denser and longer trichomes have lower SR and higher total reflectance than the smooth leaves. SR removal did not remarkably improve PLSR models of biophysical traits (up to 2% of RMSE). Thus, in herbaceous dorsiventral leaves with relatively sparse trichomes of various morphology and without apparent waxy surface, we cannot confirm that SR removal significantly improves biophysical trait prediction.

Volumetric Flow Rate Measurement using Surface Imaging Techniques

The purpose of our research is to validate an experimental method developed by Johnson and Cowen (2016) aimed at measuring volumetric discharge in an open channel using Surface particle image velocimetry (SPIV) combined with turbulent boundary layer analysis to infer the bathymetry and calculate volumetric flow rate, ultimately extending this work to natural systems (Hendrickson, 2020).

Numerical Study on the Mechanism and Application of Artificial Free Surfaces in Bedrock Blasting of Shield Tunnels

During the pretreatment construction of blasting in shield tunnel bedrock, in order to reduce the impact of blasting vibration on the surrounding environment and improve the effect of rock blasting, the method of creating an artificial free surface is proposed. From the point of creating an artificial free surface, this paper numerically studies the function mechanism and parameter optimization of artificial free faces in shield tunnel bedrock blasting construction. The propagation characteristics of explosion stress waves at the interface between the rock and the artificial free face and the effect of the artificial free face on the shield tunnel bedrock blasting were analyzed. The results indicate that, as the explosion stress wave transmits to the artificial free face, a part of the stress wave is reflected back to the bedrock, increasing the energy in the bedrock that needs blasting and improving the blasting effect and utilization rate of the blasting energy. The reduction degree of the peak velocity of the surface particle is more than 50%, and the reduction degree of the peak velocity of the particle near the artificial free face is more than 77%. The existence of the artificial free face reflects the stress wave and superimposes with the original stress waves, increasing the effective stress in the blasting area, and the effective stress can be increased by 5 MPa or more. The peak vibration velocity of the surface particle decreases with an increasing diameter of the empty holes and the distance between the empty holes and the blasting holes. The parameter design value of the artificial free face is put forward: the diameter of the hole is 200 mm, the distance between the empty holes and the center of the blasting holes is 60 cm, and the depth of the empty hole is the same as the blasting hole.

Processing parameters optimization of cotton stalk (Gossypium hirsutum L.) particleboards with emulsifiable polymeric isocyanate adhesive

The compaction behavior of cotton stalk particle mats, temperature profile inside the particle mats, and influence of surface particle size were studied relative to the properties of three-layered cotton stalk particleboards. Modulus of rupture (MOR), modulus of elasticity (MOE), internal bond, and thickness swelling were used as a measure for mechanical and physical performance. Two types of cotton stalk particleboard were manufactured. Results indicated that compression stiffness of the particle mat increased with increasing particle size; however, it decreased with increasing mat moisture content and temperature. At mat moisture contents of 12% and 18%, the plateau temperature at the centerline was not significantly different between boards having coarse and fine particles. However, the plateau time of boards with coarse particles was significantly lower than that of boards with fine particles. Additionally, thickness swelling of boards with a surface particle size of 2 mm was significantly lower than that of boards with surface particle size of 4 mm. Boards with a surface particle size of 2 mm had MOR and MOE values 15% and 10% higher, respectively, than boards with surface particle size of 4 mm. Internal bond decreased 6.5% with decreasing surface particle size from 4 mm to 2 mm.

Identification of coral spawn source areas around Sekisei Lagoon for recovery and poleward habitat migration by using a particle-tracking model

A massive coral bleaching event occurred in 2016 in the interior of Japan’s largest coral lagoon, the Sekisei Lagoon, located in the Kuroshio upstream region in southwestern Japan. Recovery of the coral lagoon will require the influx of coral spawn and larvae; therefore, it is important to identify and conserve source sites. A surface-particle-tracking simulation of coral spawn and larvae was used to identify source areas of coral spawn outside of the Sekisei Lagoon for potential recovery of the interior lagoon. The northern coastal zone of Iriomote Island, including Hatoma Island, was identified as a major source area. Hatoma Island was also identified as a key source for the Kuroshio downstream region and for aiding the poleward migration of coral habitat under ongoing global climate change, making it one of the most important source areas in the Nansei Archipelago.

Improving the sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosols of the Weather Research and Forecasting-Chemistry (WRF-Chem) model with the revised Gridpoint Statistical Interpolation system and multi-wavelength aerosol optical measurements: the dust aerosol observation campaign at Kashi, near the Taklimakan Desert, northwestern China

The Gridpoint Statistical Interpolation data assimilation (DA) system was developed for the four size bin sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol mechanism in the Weather Research and Forecasting-Chemistry (WRF-Chem) model. The forward and tangent linear operators for the aerosol optical depth (AOD) analysis were derived from WRF-Chem aerosol optical code. We applied three-dimensional variational DA to assimilate the multi-wavelength AOD, ambient aerosol scattering coefficient, and aerosol absorption coefficient, measured by the sun–sky photometer, nephelometer, and aethalometer, respectively. These measurements were undertaken during a dust observation field campaign at Kashi in northwestern China in April 2019. The results showed that the DA analyses decreased the model aerosols' low biases; however, it had some deficiencies. Assimilating the surface particle concentration increased the coarse particles in the dust episodes, but AOD and the coefficients for aerosol scattering and absorption were still lower than those observed. Assimilating aerosol scattering coefficient separately from AOD improved the two optical quantities. However, it caused an overestimation of the particle concentrations at the surface. Assimilating the aerosol absorption coefficient yielded the highest positive bias in the surface particle concentration, aerosol scattering coefficient, and AOD. The positive biases in the DA analysis were caused by the forward operator underestimating aerosol mass scattering and absorption efficiency. As compensation, the DA system increased particle concentrations excessively to fit the observed optical values. The best overall improvements were obtained from the simultaneous assimilation of the surface particle concentration and AOD. The assimilation did not substantially change the aerosol chemical fractions. After DA, the clear-sky aerosol radiative forcing at Kashi was −10.4 W m−2 at the top of the atmosphere, which was 55 % higher than the radiative forcing value before DA.

Improving the Sectional MOSAIC Aerosol models of WRF-Chem with the revised Gridpoint Statistical Interpolation System and multi-wavelength aerosol optical measurements: DAO-K experiment 2019 at Kashi, near the Taklamakan Desert, northwestern China

The Gridpoint Statistical Interpolation data assimilation (DA) system was developed for the four-size bin sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol mechanism in the Weather Research and Forecasting-Chemistry (WRF-Chem) model. The forward and adjoint operators for the aerosol optical depth (AOD) analysis were derived from WRF-Chem aerosol optical code. We applied three-dimensional variational DA to assimilate the multi-wavelength AOD, ambient aerosol scattering coefficient, and aerosol absorption coefficient, measured by the sun-sky photometer, nephelometer, and aethalometer, respectively. These were undertaken during a dust observation field campaign at Kashi in northwestern China in April 2019. The results showed that the DA analyses decreased the low biases in the model aerosols; however, it had had some deficiencies. Assimilating the surface particle concentration increased the coarse particles in the dust episodes, but AOD, and the coefficients for aerosol scattering and absorption, were still lower than observed values. Assimilating aerosol scattering coefficient separately from AOD improved the two optical quantities. However, it caused an overestimation of the particle concentrations at the surface. Assimilating the aerosol absorption coefficient yielded the highest positive bias in the surface particle concentration, aerosol scattering coefficient, and AOD. The positive biases in the DA analysis were caused by the forward operator underestimating particle scattering and absorption efficiency. As a compensation, the DA system increased particle concentrations excessively so as to fit the observed optical values. The best overall improvements were obtained from the simultaneous assimilation of the surface particle concentration and AOD. The assimilation did not substantially change the aerosol chemical fractions. After DA, the clear-sky aerosol radiative forcing at Kashi was −10.5 W m−2 at the top of the atmosphere, which was 46 % higher than the background radiative forcing value.