The effect of wind speed averaging time on sand transport estimates

Shen, Yaping; Zhang, Chunlai; Huang, Xiaoqi; Wang, Xuesong; Cen, Songbo

doi:10.1016/j.catena.2018.12.020

Cited by 18 publications

(10 citation statements)

References 34 publications

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“…In this study, we selected the equation of Lettau and Lettau (1978) because it has been proven to predict the sand transport rate well (Sauermann et al, 2001; Sherman et al, 1998, 2013). In addition, based on our previous field and wind tunnel experiments (Jia et al, 2019; Shen et al, 2019), we found that this model is widely applicable for predicting the sand transport rate. Based on an approach similar to that of Bagnold (1936) and Kawamura (1951), Lettau and Lettau (1978) developed their sand transport model to explicitly account for the excess (relative to the entrainment threshold) shear velocity:

q goodbreak= C \sqrt{\frac{d}{D}} \frac{ρ}{g} ((), u_{*} goodbreak- u_{* normalt}) {u_{*}}^{2},

where q is the sand transport rate (kg m −1 s −1 ); C is a constant (taken as 6.7); d is the median grain size (mm); D is the reference grain diameter (0.25 mm); ρ is the fluid density of air (1.25 kg m −3 ); g is the acceleration due to gravity (9.8 m s −2 );

u_{*}

is the shear velocity (m s −1 ); and

u_{* normalt}

is the threshold shear velocity for particle entrainment (m s −1 ).…”

Section: Introductionmentioning

confidence: 66%

“…After using the 1 min datasets to parameterize the Lettau and Lettau equations (Equation ) and after calculating the value of C , we used the longer‐duration datasets to validate the model's predictions. Because fluctuations in wind velocity should not be neglected and these fluctuations tend to be greater over longer measurement periods, the averaging time for wind speed strongly influences the calculation of the sand transport rate (Martin et al, 2013; Shen et al, 2019; Yizhaq et al, 2020). Therefore, it is not reasonable to verify the accuracy of the transport prediction equation using the sand transport rate measured over longer periods.…”

Section: Resultsmentioning

confidence: 99%

“…In addition, based on our previous field and wind tunnel experiments (Jia et al, 2019;Shen et al, 2019), we found that this model is widely applicable for predicting the sand transport rate. Based on an approach similar to that of Bagnold (1936) and Kawamura (1951), Lettau and Lettau (1978) developed their sand transport model to explicitly account for the excess (relative to the entrainment threshold) shear velocity:…”

mentioning

confidence: 79%

“…We utilized the 14 1 min datasets to derive the C value in the Lettau and Lettau model (described in Section 2.3) at different wind velocities and fetch lengths. It is known that the averaging period used to estimate the wind speed strongly influences the calculated sand transport rate (Martin et al, 2013; Shen et al, 2019; Yizhaq et al, 2020) when the wind fluctuates; longer averaging times generally produce larger errors. For the 1 min datasets, the wind's fluctuation was relatively weak, suggesting that measurements in such a duration can optimally reflect the real sand transport rate that corresponds to the measured wind speed.…”

Section: Methodsmentioning

confidence: 99%

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Field investigation of the fetch effect and essential conditions for saturated sand flow

Zhang

Wang

Zou

et al. 2022

Earth Surf Processes Landf

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Several models of classical aeolian sand transport mechanism have been developed to predict the rate of sand transport. However, the values predicted through modeling almost always display large and significant differences from the measured values. The reason for such discrepancies is not fully understood. By studying the effects of wind velocities and fetch lengths on the C values in the model proposed by Lettau and Lettau in 1978, we found that the saturation level of the measured sand flow can significantly affect the accuracy of the predicted value. To solve this problem, we introduced an index (δ) to represent the saturation level. The closer the δ value is to 1, the greater the chance that the sand flow is saturated. This new approach only requires measurement of the saturated sand flow data to verify the robustness of the aeolian sand transport model, a step that has been neglected by previous researchers. Our results suggest that the value of C = 6.7 proposed in the Lettau and Lettau model is sound and reliable if the sand flow is saturated. We proposed the conditions required for the sand flow to reach saturation and generated an equation to predict the sand transport saturation length (Lsat). Accordingly, we estimated Lsat to be approximately 92 m when u* = 0.47 m s−1 for the studied sand surface, which is also the minimum wind shear velocity at which the sand flow can potentially reach saturation.

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q goodbreak= C \sqrt{\frac{d}{D}} \frac{ρ}{g} ((), u_{*} goodbreak- u_{* normalt}) {u_{*}}^{2},

u_{*}

is the shear velocity (m s −1 ); and

u_{* normalt}

is the threshold shear velocity for particle entrainment (m s −1 ).…”

Section: Introductionmentioning

confidence: 66%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 79%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Field investigation of the fetch effect and essential conditions for saturated sand flow

Zhang

Wang

Zou

et al. 2022

Earth Surf Processes Landf

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“…Relevant studies show that sand transported by the wind accumulates around any type of obstacle [ 24 , 25 ], and the decrease in near-surface wind speed easily causes sand material accumulation, while the increase in wind speed easily causes blown sand flow erosion [ 26 , 27 , 28 , 29 ]. In the wind-speed-weakening area upwind, because the wind-speed-weakening range and intensity of the bridge were smaller than those of the subgrade, the range and intensity of sand material accumulation upwind of the bridge were smaller than those of the subgrade.…”

Section: Cause Analysismentioning

confidence: 99%

Characteristic Differences of Wind-Blown Sand Flow Field of Expressway Bridge and Subgrade and Their Implications on Expressway Design

Xie

Zhang

Pang

2022

Sensors

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Bridges and subgrades are the main route forms for expressways. The ideal form for passing through sandy areas remains unclear. This study aims to understand the differences in the influence of expressway bridges and subgrades on the near-surface blown sand environment and movement laws, such as the difference in wind speed and profile around the bridge and subgrade, the difference in wind flow-field characteristics, and the difference in sand transport rate, to provide a scientific basis for the selection of expressway route forms in sandy areas. Therefore, a wind tunnel test was carried out by making models of a highway bridge and subgrade and comparing the environmental effects of wind sand on them. The disturbance in the bridge to near-surface blown sand activities was less than that of the subgrade. The variation ranges of the wind speed of the bridge and its upwind and downwind directions were lower than those of the subgrade. However, the required distance to recover the wind speed downwind of the bridge was greater than that of the subgrade, resulting in the sand transport rate of the bridge being lower than that of the subgrade. The variation in the wind field of the subgrade was more drastic than that of the bridge, but the required distance to recover the wind field downwind of the bridge was greater than that of the subgrade. In the wind speed-weakening area upwind, the wind speed-weakening range and intensity of the bridge were smaller than those of the subgrade. In the wind speed-increasing area on the top of the model, the wind speed-increasing range and intensity of the bridge were smaller than those of the subgrade. In the wind-speed-weakening area downwind, the wind speed weakening range of the bridge was greater than that of the subgrade, and the wind speed-weakening intensity was smaller than that of the subgrade. This investigation has theoretical and practical significance for the selection of expressway route forms in sandy areas.

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Atmospheric aerosol particles before, during, and after a convective dust event on the Jornada experimental range as measured using Raman hyperspectral imaging

Doughty

Dumais

Richman

et al. 2023

J Raman Spectroscopy

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The effects of winds and local mineralogy on ambient aerosol composition are poorly understood. We measured the Raman spectra (RS) of ambient aerosol particles on the Jornada Experimental Range, a desert location in southern New Mexico, used these RS to group spectra by composition or spectral features, and compared the numbers of RS with the winds and minerology. An aerosol Raman hyperspectral imager was used to collect particles onto a tape and measure a hyperspectral Raman image in 15‐ or 20‐min intervals. Over a 48 h period, 6306 RS were above the thresholds used and were analyzed further. Multiple RS may originate from the same particle. Of these 6306 RS, 2567 were classified as luminescence; 2647 contained the D and G peaks of DG Carbon (DGC, which includes soots, black carbon, and similar materials); 43 exhibited peaks consistent with CH stretching; and 130, 102, and 29 RS were consistent with quartz, carbonates (calcite and dolomite), and potassium feldspar, respectively. A convective dust event was concurrent with an increase in the number of RS of luminescent particles >20X the median; numbers of DGC RS in the interquartile range of DGC for the entire measurement period; RS consistent with quartz, calcite, iron oxides, feldspar, and anatase; and no RS consistent with oxalates or nitrates. This work shows that hyperspectral Raman imaging can help understand the time‐dependent composition of ambient aerosol particles at time resolutions below an hour.

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The effect of wind speed averaging time on sand transport estimates

Cited by 18 publications

References 34 publications

Field investigation of the fetch effect and essential conditions for saturated sand flow

Field investigation of the fetch effect and essential conditions for saturated sand flow

Characteristic Differences of Wind-Blown Sand Flow Field of Expressway Bridge and Subgrade and Their Implications on Expressway Design

Atmospheric aerosol particles before, during, and after a convective dust event on the Jornada experimental range as measured using Raman hyperspectral imaging

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