CN113343488B - Wind erosion rate estimation model containing gravel and vegetation factor and construction method thereof - Google Patents

Wind erosion rate estimation model containing gravel and vegetation factor and construction method thereof Download PDF

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CN113343488B
CN113343488B CN202110729281.4A CN202110729281A CN113343488B CN 113343488 B CN113343488 B CN 113343488B CN 202110729281 A CN202110729281 A CN 202110729281A CN 113343488 B CN113343488 B CN 113343488B
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wind erosion
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李庆
王仁德
张春来
李童洲
查慧敏
周娜
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Institute Of Geography Hebei Academy Of Sciences
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Abstract

The invention relates to a wind erosion rate estimation model containing gravels and vegetation factors and a construction method thereof, wherein the construction method comprises the following steps: a. building a basic wind erosion rate estimation model, b, inputting a vegetation coverage factor, c, inputting a gravel coverage factor, d, inputting a vegetation and gravel coverage comprehensive effect factor, and e, building a wind erosion rate estimation model for covering the earth surface by the vegetation and the gravel together. The wind tunnel simulation experiment result is used as a basis, a basic wind erosion rate estimation model is firstly established, and then vegetation coverage factors, gravel coverage factors, gravels and vegetation coverage comprehensive effect factors are gradually added to the basic model, so that a semi-empirical wind erosion model which is suitable for gobi and desert grasslands in the north of China and covers wind speed, vegetation coverage and gravel coverage is finally established. The method is established according to the Gobi and desert grassland in the North China, has clear structure, clear wind erosion factor relationship, easy acquisition of parameters and simple calculation process, and is suitable for calculating and predicting the wind erosion rate of the Gobi and desert grassland in the North China.

Description

Wind erosion rate estimation model containing gravel and vegetation factor and construction method thereof
Technical Field
The invention relates to construction of a soil wind erosion model, in particular to a wind erosion rate estimation model containing gravels and vegetation factors and a construction method thereof.
Background
Soil erosion by wind is an important type of soil erosion and is deeply suffered by countries and regions worldwide at 2/3. The influence of each wind erosion factor on the wind erosion rate is recognized, and the establishment of an accurate wind erosion rate estimation model is the premise and the basis for scientifically preventing and treating the soil wind erosion. Relevant researches are carried out by many scholars at home and abroad, and the researches find that factors such as wind, vegetation, gravel, soil and the like can obviously influence wind erosion. Wherein, wind is a key factor for determining the strength of wind erosion force; coarse interference factors such as vegetation, gravel, soil blocks and the like are key factors for weakening wind erosion force; factors such as soil specific gravity, particle size composition, water content and the like are key factors for determining the wind erosion resistance of the soil surface. On the basis of related research, scholars at home and abroad develop various wind erosion models, and representative models comprise: WEQ, RWEQ, TEAM, WEAM, WEPS, etc. Most of the models are constructed by taking farmlands or deserts as objects, and the specific attributes of other land types are not considered in the construction process, so that the models are difficult to be directly applied to the farmlands and other land types except the deserts. The gobi and desert grasslands are widely distributed in the north of China and are one of important areas for the occurrence of soil wind erosion in the north of China. Unlike farmlands and deserts, vegetation and gravel are often present on both gobi and desert grasslands, affecting wind erosion. Since the existing wind erosion models do not consider the influence of gravel coverage, accurate estimation of the wind erosion strength of the areas becomes a big problem.
Because the wind erosion process is complex and a plurality of influencing factors are involved, most of the existing wind erosion models are empirical models constructed based on measured data. The empirical model has the advantages of simple operation and easy acquisition of parameters, but the model lacks physical and data bases and is difficult to apply to other areas outside a modeling area. Some researchers have attempted to develop physical models. However, at present, the understanding of the physical mechanism of the soil wind erosion is not clear, so that the physical model becomes a highly simplified model and the objective law of the wind erosion is difficult to reflect.
Disclosure of Invention
The invention aims to provide a wind erosion rate estimation model containing gravels and vegetation factors and a construction method thereof, so as to solve the problem that the existing wind erosion model is inaccurate in wind erosion intensity estimation.
The invention is realized by the following steps: a construction method of a wind erosion rate estimation model containing gravels and vegetation factors comprises the following steps:
a. constructing a basic wind erosion rate estimation model:
a basic wind erosion rate estimation model is constructed by combining a sand transport equation with wind tunnel experiment data as follows:
Figure BDA0003138718670000011
in the formula, Q0The wind erosion rate of the exposed surface; q. q.s0Sand conveying rate of bare ground surface; l is the length of the bed surface; d is the average particle size; d is the standard sand particle size; ρ is the air density; g is the acceleration of gravity; u. of*The friction wind speed of the incoming flow; u. of*tThe critical friction wind speed is.
b. Vegetation coverage factor f1(Cv) The input of (2):
vegetation coverage factor f1(Cv) It can be expressed as a function of wind speed and vegetation coverage:
Figure BDA0003138718670000021
in the formula, CvAnd covering the vegetation.
Substituting the formula (2) into the formula (1), and constructing a wind erosion rate estimation model of the vegetation covered earth surface as follows:
Figure BDA0003138718670000022
the symbols in the formula have the same meaning as in formula (1).
c. Input of gravel coverage factor:
gravel cover factor f2(Cg) It can be expressed as a function of wind speed and gravel coverage:
Figure BDA0003138718670000023
in the formula, CgTo cover the gravel.
Substituting the formula (4) into the formula (1), and combining wind tunnel experiment data to construct a wind erosion rate estimation model of gravel covering the earth surface, wherein the wind erosion rate estimation model comprises the following steps:
Figure BDA0003138718670000024
the symbols in the formula have the same meaning as in formula (1).
d. Input of vegetation and gravel coverage combined effect factors:
vegetation and gravel coverage combined effect factor f3(Cv,Cg) It can be expressed as a function of wind speed, vegetation and gravel coverage:
Figure BDA0003138718670000025
the symbols in the formula have the same meaning as in formula (1), formula (2) and formula (4).
e. Constructing a wind erosion rate estimation model for covering the earth surface by the vegetation and the gravel together:
by integrating the formula (1), the formula (3), the formula (5) and the formula (6), the wind erosion rate estimation model for covering the earth surface by the vegetation and the gravel together is constructed as follows:
Figure BDA0003138718670000026
the meaning of each symbol in the formula is the same as that of the corresponding symbol in the formula (1), the formula (3), the formula (5) and the formula (6); and the number of the first and second electrodes,
vegetation coverage factor f1(Cv) Comprises the following steps:
Figure BDA0003138718670000031
gravel cover factor f2(Cg) Comprises the following steps:
Figure BDA0003138718670000032
vegetation and gravel coverage combined effect factor f3(Cv,Cg) Comprises the following steps:
Figure BDA0003138718670000033
the invention discloses a wind erosion rate estimation model containing gravels and vegetation factors, which is characterized in that:
Figure BDA0003138718670000034
wherein: l is the length of the bed surface; d is the average particle size; d is the standard sand particle size; ρ is the air density; g is the acceleration of gravity; u. of*The friction wind speed of the incoming flow;
Figure BDA0003138718670000038
critical friction drag wind speed; cvCoverage for vegetation, CgCovering degree for gravel; f. of1(Cv) Is a vegetation coverage factor; f. of2(Cg) Is a gravel coverage factor; f. of3(Cv,Cg) Is a vegetation and gravel coverage combined effect factor; and the number of the first and second electrodes,
vegetation coverage factor f1(Cv) Comprises the following steps:
Figure BDA0003138718670000035
gravel cover factor f2(Cg) Comprises the following steps:
Figure BDA0003138718670000036
vegetation and gravel coverage combined effect factor f3(Cv,Cg) Comprises the following steps:
Figure BDA0003138718670000037
the invention uses quantitative function to express the function and quantitative relation of each factor in the soil wind erosion process. In order to avoid the interaction influence among all factors, the method is based on the wind tunnel simulation experiment result, a basic wind erosion rate estimation model is firstly constructed, then vegetation coverage factors, gravel coverage factors, gravels and vegetation coverage comprehensive effect factors are gradually added to the basic model, and finally a semi-empirical wind erosion model which is suitable for gobi and desert grasslands in the north of China and covers wind speed, vegetation coverage and gravel coverage is constructed.
The invention utilizes the wind tunnel simulation experiment result to establish a soil wind erosion rate estimation model which comprises wind speed, gravel coverage factors and vegetation coverage factors and is suitable for gobi and desert grasslands in the north of China.
The invention has the positive effects that: (1) the soil wind erosion rate estimation model comprises main factors influencing soil wind erosion such as wind speed, soil, vegetation coverage, gravel coverage and the like, and is a wind erosion rate estimation model simultaneously comprising gravel coverage factors and vegetation coverage factors. (2) The soil wind erosion rate estimation model is established according to the Gobi and desert grassland in the North China, has the advantages of clear structure, clear wind erosion factor relationship, easy acquisition of parameters, simple calculation process and the like, and is suitable for calculating and predicting the wind erosion rate of the Gobi and desert grassland in the North China.
Drawings
FIG. 1 is a flow chart of the modeling of the wind erosion rate estimation model of the present invention.
Detailed Description
As shown in fig. 1, the soil wind erosion rate estimation model of the present invention is constructed as follows:
constructing a basic wind erosion rate estimation model:
the wind erosion rate of the bare earth surface is generally expressed by a single-width sand conveying rate, which means the sand conveying amount per unit width and unit time. A basic wind erosion rate estimation model is constructed by combining a sand transport equation with wind tunnel experiment data as follows:
Figure BDA0003138718670000041
in the formula, Q0For the wind erosion rate (kg m) of the exposed surface-2s-1)；q0Sand conveying rate (kg m) for bare ground surface-1s-1) (ii) a L is the length of the bed surface (5 m); d is the average particle diameter (mm); d is the standard sand grain diameter (0.25 mm); ρ is the air density (1.29kg m)-3) (ii) a g is gravity acceleration (9.8m s)-2)；u*The friction wind speed for the incoming flow (m s)-1)；u*tIs the critical friction wind speed (ms)-1) It can be calculated by the formula of Bagnold (1941).
② vegetation coverage factor f1(Cv) The input of (2):
the vegetation influences the wind erosion of soil by directly covering the earth surface, absorbing airflow quantity, changing airflow field distribution, intercepting wind erosion particles and the like, so that the wind erosion condition of the earth surface covered by the vegetation is completely different from that of the bare earth surface. By comprehensively considering the practicability and operability of the model, the invention expresses the weathering rate of the vegetation covered earth surface as the product of the weathering rate of the bare earth surface and the vegetation coverage factor. Calculating the vegetation coverage factor f by using experimental data1(Cv) Namely the ratio of the wind erosion rate under different vegetation coverage and wind speed conditions to the wind erosion rate of the corresponding bare earth surface. Along with the increase of the wind speed, the vegetation coverage is reduced, and the factor value of the vegetation coverage is continuously increased. Vegetation coverage factor f1(Cv) It can be expressed as a function of wind speed and vegetation coverage:
Figure BDA0003138718670000042
in the formula, CvIs the vegetation coverage (%).
And (3) constructing a wind erosion rate estimation model of the vegetation covered earth surface by combining the formula (1), the formula (2) and wind tunnel experiment data:
Figure BDA0003138718670000051
the symbols in the formula have the same meaning as in formula (1).
Inputting a gravel coverage factor:
the gravel and the plants are both non-erodible rough elements, and the gravel coverage factor f is constructed by referring to the construction idea of the vegetation coverage factor2(Cg). As the gravel coverage increases, the gravel coverage factor value increases first and then decreases; as wind speed increases, gravel coverage factor values continue to increase. Gravel cover factor f2(Cg) It can be expressed as a function of wind speed and gravel coverage:
Figure BDA0003138718670000052
in the formula, CgThe gravel cover (%) was obtained.
And (3) combining the formula (1), the formula (4) and wind tunnel experimental data to construct a wind erosion rate estimation model of the gravel-covered ground surface:
Figure BDA0003138718670000053
the symbols in the formula have the same meaning as in formula (1).
Inputting vegetation and gravel coverage comprehensive effect factors:
although the vegetation and the gravel are both non-erodible rough elements, the shape, the porosity, the flexibility and other properties of the vegetation and the gravel are different, and the influence on the wind erosion of the soil is also different. As the vegetation coverage increases, the weathering rate decreases continuously; as gravel pack coverage increases, the weathering rate tends to increase and then decrease. The invention relates to a reference plantThe construction idea of the coverage factor constructs the vegetation and gravel coverage comprehensive effect factor f3(Cv,Cg)＝Q/[Q0f1(Cv)f2(Cg)]. The comprehensive effect factor value of vegetation and gravel is increased continuously along with the increase of vegetation coverage and gravel coverage and the reduction of wind speed. In combination with experimental data, the vegetation and gravel coverage combined effect factor can be expressed as a function of wind speed, vegetation and gravel coverage:
Figure BDA0003138718670000054
the symbols in the formula have the same meaning as in formula (1), formula (2) and formula (4).
Constructing a wind erosion rate estimation model (namely the wind erosion rate estimation model containing the gravels and the vegetation factors) by covering the earth surface with the vegetation and the gravels together:
and (3) constructing a wind erosion rate estimation model of the earth surface covered by the vegetation and the gravel together by integrating the formula (1), the formula (3), the formula (5) and the formula (6):
Figure BDA0003138718670000061
the meaning of the symbols in the formula is the same as that of the corresponding symbols in the formula (1), the formula (3), the formula (5) and the formula (6); and the number of the first and second electrodes,
vegetation coverage factor f1(Cv) Comprises the following steps:
Figure BDA0003138718670000062
gravel cover factor f2(Cg) Comprises the following steps:
Figure BDA0003138718670000063
vegetation and gravel coverage combined effect factor f3(Cv,Cg) Comprises the following steps:
Figure BDA0003138718670000064
the invention discloses a verification method of a wind erosion rate estimation model for covering the earth surface by vegetation and gravel together, which comprises the following steps:
the model constructed by the invention has the frictional resistance wind speed of 0.72m s under different vegetation and gravel covering conditions-1Calculating the wind erosion amount of the soil to obtain a model simulation value; meanwhile, the wind tunnel is used for measuring the soil wind erosion amount under the same condition. The results of the simulation calculation of the amount of wind erosion of soil and the actual measurement are shown in table 1.
Table 1: comparison of model simulation results with wind tunnel actual measurement results
Figure BDA0003138718670000065
The results in table 1 show that the soil wind erosion amount calculated by the model is closer to the actual measurement result, the difference between the soil wind erosion amount and the actual measurement result is 1.13-1.56 times, and the average difference is only 1.35 times, which indicates that the simulation result of the model basically accords with the actual soil wind erosion amount.

Claims (1)

1. A method for constructing a wind erosion rate estimation model containing gravels and vegetation factors is characterized by comprising the following steps of:
a. constructing a basic wind erosion rate estimation model:
a basic wind erosion rate estimation model is constructed by combining a sand transport equation with wind tunnel experiment data as follows:
Figure FDA0003457260410000011
in the formula, Q0The wind erosion rate of the exposed surface; q. q.s0Sand conveying rate of bare ground surface; l is the length of the bed surface; d is the average particle size; d is the standard sand particle size; ρ is the air density; g is weightA force acceleration; u. of*The friction wind speed of the incoming flow; u. of*tCritical friction drag wind speed;
b. inputting vegetation coverage factor:
vegetation coverage factor f1(Cv) It can be expressed as a function of wind speed and vegetation coverage:
Figure FDA0003457260410000012
in the formula, CvCovering the vegetation;
substituting the formula (2) into the formula (1), and constructing a wind erosion rate estimation model of the vegetation covered earth surface as follows:
Figure FDA0003457260410000013
wherein the symbols have the same meaning as in formula (1);
c. input of gravel coverage factor:
gravel cover factor f2(Cg) It can be expressed as a function of wind speed and gravel coverage:
Figure FDA0003457260410000014
in the formula, CgCovering degree for gravel;
substituting the formula (4) into the formula (1), and combining wind tunnel experiment data to construct a wind erosion rate estimation model of gravel covering the earth surface, wherein the wind erosion rate estimation model comprises the following steps:
Figure FDA0003457260410000015
wherein the symbols have the same meaning as in formula (1);
d. input of vegetation and gravel coverage combined effect factors:
vegetation and gravel coverage combined effect factor f3(Cv,Cg) It can be expressed as a function of wind speed, vegetation and gravel coverage:
Figure FDA0003457260410000021
the symbols in the formula have the same meaning as in formula (1), formula (2) and formula (4).
e. Constructing a wind erosion rate estimation model for covering the earth surface by the vegetation and the gravel together:
by integrating the formula (1), the formula (3), the formula (5) and the formula (6), the wind erosion rate estimation model for covering the earth surface by the vegetation and the gravel together is constructed as follows:
Figure FDA0003457260410000022
the meaning of each symbol in the formula is the same as that of the corresponding symbol in the formula (1), the formula (3), the formula (5) and the formula (6), and,
vegetation coverage factor f1(Cv) Comprises the following steps:
Figure FDA0003457260410000023
gravel cover factor f2(Cg) Comprises the following steps:
Figure FDA0003457260410000024
the vegetation and gravel coverage combined effect factors are as follows:
Figure FDA0003457260410000025
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104376216A (en) * 2014-11-20 2015-02-25 尚可政 Soil wind erosion model comprising human factors and natural factors
CN106228021A (en) * 2016-07-29 2016-12-14 河北省科学院地理科学研究所 Farmland wind erosion quantity forecast model and wind erosion quantity Forecasting Methodology
CN107145848A (en) * 2017-04-27 2017-09-08 中国科学院遥感与数字地球研究所 A kind of wind erosion of soil monitoring method and system based on remotely-sensed data
CN110569523A (en) * 2019-06-11 2019-12-13 北京林业大学 soil wind erosion model establishing method and wind erosion rapid estimation system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104376216A (en) * 2014-11-20 2015-02-25 尚可政 Soil wind erosion model comprising human factors and natural factors
CN106228021A (en) * 2016-07-29 2016-12-14 河北省科学院地理科学研究所 Farmland wind erosion quantity forecast model and wind erosion quantity Forecasting Methodology
CN107145848A (en) * 2017-04-27 2017-09-08 中国科学院遥感与数字地球研究所 A kind of wind erosion of soil monitoring method and system based on remotely-sensed data
CN110569523A (en) * 2019-06-11 2019-12-13 北京林业大学 soil wind erosion model establishing method and wind erosion rapid estimation system

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
"Logistic growth models for describing the fetch effect of aeolian sand";Zhongling Guo等;《Soil & Tillage Research》;20190628;全文 *
"不同时间尺度农田风沙流模拟";黄亚鹏等;《中国沙漠》;20201030;第40卷(第5期);全文 *
"不同砾石覆盖度戈壁床面风蚀速率定量模拟";谭立海等;《中国沙漠》;20160630;第36卷(第3期);全文 *
"植被对土壤风蚀影响的风洞实验研究";张春来等;《水土保持学报》;20030930;第17卷(第3期);全文 *

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