scholarly journals Application of laser profilograph in the assessment of mechanical tillage of slope lands

2021 ◽  
pp. 68-74
Author(s):  
Mikhail Andriyanovich Vasiliev ◽  
Sergey Anatolyevich Vasiliev ◽  
Alexey Anatolyevich Vasiliev
Keyword(s):  
Surface Roughness ◽  
Average Method ◽  
Soil Cover ◽  
Moving Average ◽  
Surface Profile ◽  
Soil Surface ◽  
Morphological Parameters ◽  
Treated Soil ◽  
Data Points ◽  
Measured Profile

The article analyzes an extensive set of measurements of the daily surface profile of cultivated soil in order to justify the moving average method for evaluating morphological parameters and studying the influence of the base length of the profile on the accuracy of the obtained values. The surface roughness for the elementary platform was 5.08 mm, the surface ridge formed by technological furrows was 21.9 mm, and the slope of the platform was 0.056 or 3.2 degrees. The accuracy of the obtained values of roughness and ridges of the surface of the treated soil depends significantly on the length of the profile under study, determined by the number of measurements performed. For one turn of the device for the elementary platform, 9616 data points were obtained on the profile length of 6.3 m (3 measurements are performed per 2 mm). The surface roughness varied from 2 mm to 6 mm, and the ridge – 16 ... 28 mm with the number of measurements from 2000 to 9600. When the measured profile length is about 1.3 m or less (no more than 2000 points), the parameters of the treated soil cover are greatly underestimated, and this error is greater for ploughed soil than for cored soil. On flatter surfaces, the base profile length of 2.5 m may be sufficient to adequately calculate the parameters of the daily soil surface.

scholarly journals Application of profilograph for evaluation of mechanical tillage of slope lands

2020 ◽  
Vol 193 ◽  
pp. 01066
Author(s):  
Mikhail Vasiliev ◽  
Sergey Vasiliev ◽  
Alexey Vasiliev
Keyword(s):  
Surface Roughness ◽  
Average Method ◽  
Soil Cover ◽  
Moving Average ◽  
Surface Profile ◽  
Soil Surface ◽  
Morphological Parameters ◽  
Wide Range ◽  
Data Points ◽  
Measured Profile

In this paper, we analyze a wide range of measurements of the day surface profile of tilled soil in order to substantiate the moving average method for evaluating morphological parameters and studying the influence of the base profile length on the accuracy of the obtained values. The surface roughness of the elementary plot was 4 mm, the surface ridgeness formed by technological furrows was 16 mm, and the slope of the plot was 0.198. The accuracy of the obtained values of roughness and ridgeness of the tilled soil surface depends significantly on the profile length determined by the number of measurements performed. We obtained 5273 data points per one turn of the device on a 6.3 m profile length (1 measurements are made per 1 mm) for the elementary plot. The surface roughness varied from 3, 1 mm to 4, 3 mm, and the ridgeness – 12 ... 21 mm when the number of measurements is from 2000 to 5273. When the measured profile length is about 1.3 m or less (not more 2000 points), the parameters of the tilled soil cover are not considered important. However, they are more critical for ploughed soil than for harrowed soil. On flatter surfaces, the base profile length of 2.5 m may be sufficient to adequately calculate the parameters of the day soil surface.

scholarly journals IMPLEMENTATION OF THE METHOD FOR DETERMINING AND PROCESSING OF DATA ON THE PARAMETERS OF THE SUBSTRATE SURFACE OF AGROLLDSHIPS OF SLOPE LAND

2018 ◽  
Vol 13 (2) ◽  
pp. 81-85
Author(s):  
Феофан Самуилов ◽  
Feofan Samuilov ◽  
Сергей Васильев ◽  
Sergey Vasil'ev ◽  
Иван Максимов ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Average Method ◽  
Moving Average ◽  
Substrate Surface ◽  
Experimental Studies ◽  
Surface Profile ◽  
Soil Surface ◽  
Scientific Article ◽  
Field Station ◽  
Average Slope

The scientific article considers methods for studying the underlying surface of agro landscapes of slope lands - local and integral: contact and non-contact. Each group in turn includes a visual, optical and mechanical approach. For carrying out experimental studies on sloping lands, a method has been developed for determining the average slope, roughness and waviness of an elementary site in the field, and profilographs for its implementation. Using the moving average method, it is possible to break the data into components and isolate, on a general background, the average surface slope, randomly distributed irregularities, surface roughness and technological furrows with a corrugation of the surface. In order to automate the process of determining these parameters, a program has been developed that allows you to directly calculate and display information on the monitor screen. Field studies using a profiler with contactless profilograph were conducted on different soil fertility, including the examination of the field station, located on the slope of the complex after the pre-winter tillage BDM-3x4P in Morgaushskiy District of the Chuvash Republic. After data processing, the average slope of the elementary area for a certain point of the field was 0.06 or 3.440. The direction of the main soil cultivation was determined from the angle of deviation of the technological grooves from the direction of the slope, which amounted to 93.60. The data obtained are presented in the Excel spreadsheet as a relationship between two parameters: the angle of rotation and the height of the surface profile of the soil, in the form of a sweep. Further, using the moving average method for the field section with soil disking, the average slope of the surface was determined to be 3.440, the surface roughness was 3.54 mm, and the waviness (soreness) of the soil surface was 7.94 cm.

scholarly journals Geostatistical analysis of microrelief of an oxisol as a function of tillage and cumulative rainfall

2009 ◽  
Vol 66 (2) ◽  
pp. 225-232 ◽  
Author(s):  
Eva Vidal Vázquez ◽  
Sidney Rosa Vieira ◽  
Isabella Clerici De Maria ◽  
Antonio Paz González
Keyword(s):  
Surface Roughness ◽  
Soil Surface ◽  
Geostatistical Analysis ◽  
Soil Tillage ◽  
Model Parameters ◽  
Natural Rainfall ◽  
Cumulative Rainfall ◽  
Data Points ◽  
Plot Area ◽  
Chisel Plow

Surface roughness can be influenced by type and intensity of soil tillage among other factors. In tilled soils microrelief may decay considerably as rain progresses. Geostatistics provides some tools that may be useful to study the dynamics of soil surface variability. The objective of this study was to show how it is possible to apply geostatistics to analyze soil microrelief variability. Data were taken at an Oxisol over six tillage treatments, namely, disk harrow, disk plow, chisel plow, disk harrow + disk level, disk plow + disk level and chisel plow + disk level. Measurements were made initially just after tillage and subsequently after cumulative natural rainfall events. Duplicated measurements were taken in each one of the treatments and dates of samplings, yielding a total of 48 experimental surfaces. A pin microrelief meter was used for the surface roughness measurements. The plot area was 1.35 × 1.35 m and the sample spacing was 25 mm, yielding a total of 3,025 data points per measurement. Before geostatistical analysis, trend was removed from the experimental data by two methods for comparison. Models were fitted to the semivariograms of each surface and the model parameters were analyzed. The trend removing method affected the geostatistical results. The geostatistical parameter dependence ratio showed that spatial dependence improved for most of the surfaces as the amount of cumulative rainfall increased.

scholarly journals Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface

2017 ◽  
Vol 24 (3) ◽  
pp. 569-579 ◽  
Author(s):  
Benjamin K. B. Abban ◽  
A. N. (Thanos) Papanicolaou ◽  
Christos P. Giannopoulos ◽  
Dimitrios C. Dermisis ◽  
Kenneth M. Wacha ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Laser Scanner ◽  
Gaussian Model ◽  
Surface Profile ◽  
Soil Surface ◽  
Soil Conditions ◽  
Agricultural Field ◽  
Quantitative Evidence ◽  
Soil Surface Roughness ◽  
Surface Microroughness

Abstract. This study examines the rainfall-induced change in soil microroughness of a bare smooth soil surface in an agricultural field. The majority of soil microroughness studies have focused on surface roughness on the order of ∼ 5–50 mm and have reported a decay of soil surface roughness with rainfall. However, there is quantitative evidence from a few studies suggesting that surfaces with microroughness less than 5 mm may undergo an increase in roughness when subject to rainfall action. The focus herein is on initial microroughness length scales on the order of 2 mm, a low roughness condition observed seasonally in some landscapes under bare conditions and chosen to systematically examine the increasing roughness phenomenon. Three rainfall intensities of 30, 60, and 75 mm h−1 are applied to a smoothened bed surface in a field plot via a rainfall simulator. Soil surface microroughness is recorded via a surface-profile laser scanner. Several indices are utilized to quantify the soil surface microroughness, namely the random roughness (RR) index, the crossover length, the variance scale from the Markov–Gaussian model, and the limiting difference. Findings show a consistent increase in roughness under the action of rainfall, with an overall agreement between all indices in terms of trend and magnitude. Although this study is limited to a narrow range of rainfall and soil conditions, the results suggest that the outcome of the interaction between rainfall and a soil surface can be different for smooth and rough surfaces and thus warrant the need for a better understanding of this interaction.

Forecast of COVID-19 Cases in Nigeria: An implementation of an ARIMA model (Preprint)

2020 ◽  
Author(s):  
Sanyaolu Ameye ◽  
Michael Awoleye ◽  
Emmanuel Agogo ◽  
Ette Etuk
Keyword(s):  
Predictive Model ◽  
Time Series Data ◽  
Moving Average ◽  
Arima Model ◽  
Epidemiological Data ◽  
Series Data ◽  
Global Pandemic ◽  
First Case ◽  
Epidemiological Trend ◽  
Data Points

BACKGROUND The Coronavirus disease 2019 (COVID-2019) is a global pandemic and Nigeria is not left out in being affected. Though, the disease is just over three months since first case was identified in the country, we present a predictive model to forecast the number of cases expected to be seen in the country in the next 100 days. OBJECTIVE To implement a predictive model in forecasting the near future number of positive cases expected in the country following the present trend METHODS We performed an Auto Regressive Integrated Moving Average (ARIMA) model prediction on the epidemiological data obtained from Nigerian Centre for Disease Control to predict the epidemiological trend of the prevalence and incidence of COVID-2019. RESULTS There were 93 time series data points which lacked stationarity. From our ARIMA model, it is expected that the number of new cases declared per day will keep rising and towards the early September, 2020, Nigeria is expected to have well above sixty thousand confirmed cases. CONCLUSIONS We however believe that as we have more data points our model will be better fine-tuned.

scholarly journals Effect of tillage, slope, and rainfall on soil surface microtopography quantified by geostatistical and fractal indices during sheet erosion

2020 ◽  
Vol 12 (1) ◽  
pp. 232-241
Author(s):  
Na Ta ◽  
Chutian Zhang ◽  
Hongru Ding ◽  
Qingfeng Zhang
Keyword(s):  
Surface Roughness ◽  
Fractal Dimension ◽  
Soil Surface ◽  
Rainfall Events ◽  
Tillage Practices ◽  
Surface Microtopography ◽  
Artificial Rainfall ◽  
Soil Surface Roughness ◽  
The Difference ◽  
Sheet Erosion

AbstractTillage and slope will influence soil surface roughness that changes during rainfall events. This study tests this effect under controlled conditions quantified by geostatistical and fractal indices. When four commonly adopted tillage practices, namely, artificial backhoe (AB), artificial digging (AD), contour tillage (CT), and linear slope (CK), were prepared on soil surfaces at 2 × 1 × 0.5 m soil pans at 5°, 10°, or 20° slope gradients, artificial rainfall with an intensity of 60 or 90 mm h−1 was applied to it. Measurements of the difference in elevation points of the surface profiles were taken before rainfall and after rainfall events for sheet erosion. Tillage practices had a relationship with fractal indices that the surface treated with CT exhibited the biggest fractal dimension D value, followed by the surfaces AD, AB, and CK. Surfaces under a stronger rainfall tended to have a greater D value. Tillage treatments affected anisotropy differently and the surface CT had the strongest effect on anisotropy, followed by the surfaces AD, AB, and CK. A steeper surface would have less effect on anisotropy. Since the surface CT had the strongest effect on spatial variability or the weakest spatial autocorrelation, it had the smallest effect on runoff and sediment yield. Therefore, tillage CT could make a better tillage practice of conserving water and soil. Simultaneously, changes in semivariogram and fractal parameters for surface roughness were examined and evaluated. Fractal parameter – crossover length l – is more sensitive than fractal dimension D to rainfall action to describe vertical differences in soil surface roughness evolution.

scholarly journals Impact of Weed Control by Hand Tools on Soil Erosion under a No-Tillage System Cultivation

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 974
Author(s):  
Rafael Blanco-Sepúlveda ◽  
Amilcar Aguilar-Carrillo ◽  
Francisco Lima
Keyword(s):  
Soil Erosion ◽  
Weed Control ◽  
Soil Cover ◽  
Soil Surface ◽  
Conservation Agriculture ◽  
Soil Disturbance ◽  
No Tillage ◽  
Tropical Mountains ◽  
Litter Cover ◽  
Vegetal Cover

In conservation agriculture, the no-tillage cultivation system and the retention of permanent vegetal cover are crucial to the control of soil erosion by water. This paper analyses the cultivation of maize under no-tillage, with particular reference to the effect produced on soil erosion when weed control is performed by a hand tool (machete), which disturbs the surface of the soil, and to the behavior of the soil cover in these circumstances. The study area is located in the humid tropical mountains of northern Nicaragua (Peñas Blancas Massif Nature Reserve). The results obtained show that 59.2% of the soil surface was affected by appreciable levels of sheet and splash erosion, although the vegetal cover of the soil was relatively high (with average weed and litter cover of 33.9% and 33.8%, respectively). The use of machetes for weed control provoked considerable soil disturbance, which explained the high rates of erosion observed. Moreover, this form of soil management disturbs the litter layer, making it less effective in preventing erosion. The litter remains loose on the soil surface, and so an increase in soil cover does not achieve a proportionate reduction in the area affected by erosion; thus, even with 80–100% weed and litter cover, 42% of the cultivated area continued to present soil erosion.

scholarly journals Estimation of Soil Surface Roughness Using Stereo Vision Approach

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4386
Author(s):  
Afshin Azizi ◽  
Yousef Abbaspour-Gilandeh ◽  
Tarahom Mesri-Gundoshmian ◽  
Aitazaz A. Farooque ◽  
Hassan Afzaal
Keyword(s):  
Surface Roughness ◽  
Stereo Vision ◽  
Agricultural Soils ◽  
Depth Map ◽  
Soil Surface ◽  
Regression Equations ◽  
Height Profile ◽  
Peak Fitting ◽  
Soil Surface Roughness ◽  
Tillage Operations

Soil roughness is one of the most challenging issues in the agricultural domain and plays a crucial role in soil quality. The objective of this research was to develop a computerized method based on stereo vision technique to estimate the roughness formed on the agricultural soils. Additionally, soil till quality was investigated by analyzing the height of plow layers. An image dataset was provided in the real conditions of the field. For determining the soil surface roughness, the elevation of clods obtained from tillage operations was computed using a depth map. This map was obtained by extracting and matching corresponding keypoints as super pixels of images. Regression equations and coefficients of determination between the measured and estimated values indicate that the proposed method has a strong potential for the estimation of soil shallow roughness as an important physical parameter in tillage operations. In addition, peak fitting of tilled layers was applied to the height profile to evaluate the till quality. The results of this suggest that the peak fitting is an effective method of judging tillage quality in the fields.

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