CN110188404B - Method for determining forest and grass vegetation coverage rate threshold capable of restraining sand production in river basin - Google Patents
Method for determining forest and grass vegetation coverage rate threshold capable of restraining sand production in river basin Download PDFInfo
- Publication number
- CN110188404B CN110188404B CN201910379175.0A CN201910379175A CN110188404B CN 110188404 B CN110188404 B CN 110188404B CN 201910379175 A CN201910379175 A CN 201910379175A CN 110188404 B CN110188404 B CN 110188404B
- Authority
- CN
- China
- Prior art keywords
- forest
- sand production
- grass
- area
- sand
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 239000004576 sand Substances 0.000 title claims abstract description 116
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 90
- 244000025254 Cannabis sativa Species 0.000 title claims abstract description 66
- 230000000452 restraining effect Effects 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 title claims abstract description 20
- 230000008859 change Effects 0.000 claims abstract description 15
- 238000011160 research Methods 0.000 claims abstract description 15
- 238000010276 construction Methods 0.000 claims description 3
- 230000000903 blocking effect Effects 0.000 claims description 2
- 230000002262 irrigation Effects 0.000 claims description 2
- 238000003973 irrigation Methods 0.000 claims description 2
- 230000008901 benefit Effects 0.000 abstract description 5
- 230000009467 reduction Effects 0.000 abstract description 2
- 239000002689 soil Substances 0.000 description 10
- 230000004044 response Effects 0.000 description 6
- 238000012876 topography Methods 0.000 description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- RQNWIZPPADIBDY-UHFFFAOYSA-N arsenic atom Chemical compound [As] RQNWIZPPADIBDY-UHFFFAOYSA-N 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 229910052785 arsenic Inorganic materials 0.000 description 2
- MJLGNAGLHAQFHV-UHFFFAOYSA-N arsenopyrite Chemical compound [S-2].[Fe+3].[As-] MJLGNAGLHAQFHV-UHFFFAOYSA-N 0.000 description 2
- 229910052964 arsenopyrite Inorganic materials 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000004162 soil erosion Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 238000013075 data extraction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 239000013049 sediment Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 239000004575 stone Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Cultivation Of Plants (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for determining a forest and grass vegetation coverage rate threshold value capable of restraining sand production in a river basin, which is characterized by carrying out data acquisition for completely covering an easily-eroded area of a loess plateau by using a remote sensing image, analyzing the influence rule of forest and grass vegetation change on the sand production in the river basin by combining data of the past year and obtaining a sand production amount threshold value to obtain effective forest and grass coverage rate threshold values in different areas and under different rains, and further providing the forest and grass vegetation coverage rate threshold value capable of effectively restraining the sand production in the river basin on the scale of the river basin. The method can not only quantitatively describe the sand reduction benefit of the vegetation coverage rate, but also effectively avoid the limitation on scale, and even gradually research and popularize and apply the watershed scale to landscape scale, global scale and regional scale based on the thought.
Description
Technical Field
The invention belongs to the field of data acquisition and analysis, and particularly relates to acquisition, processing and analysis of rainfall, water sand, vegetation and terrace data in a loess plateau area easy to erode.
Background
The loess plateau is one of the most serious regions in China, and is also the main source of the yellow river sediment. Rainfall, soil, terrain and vegetation are key elements in determining sand production in the watershed, and changes in any of these factors can exacerbate or slow the water and soil loss phenomenon. At present, natural factors such as rainfall, macroscopic topography and soil components are difficult to change, but the sand production in a river basin can be influenced by changing the ground coverage degree and the micro topography of vegetation. In recent years, the vegetation coverage of the loess plateau is greatly improved, and the yellow mud and sand are also greatly reduced. However, in general, the research mainly makes a simple qualitative analysis on the relationship between the two, and the research on the quantitative relationship between the vegetation change of the loess plateau and the sand production of the watershed and the threshold is relatively few; the method for determining the vegetation forest and grass coverage rate threshold value capable of restraining sand production is mainly based on the observation data extraction of runoff cells, the research on the scale of a watershed or an area with a large area is relatively few, and the conventional research method is continued by the current research technology, so that the relation between the vegetation change of the loess plateau and the sand production of the watershed cannot be quantized, and the research on the vegetation forest and grass coverage rate threshold value capable of restraining sand production is limited.
Therefore, a new method is urgently needed to obtain vegetation coverage and sand production index and other related data of the loess plateau area easy to erode, so that the influence rule of loess plateau vegetation change on the sand production of the drainage basin is known, and the quantitative relation and the threshold between the vegetation coverage and the sand production index are revealed.
Disclosure of Invention
The invention aims to provide a method for determining a forest and grass vegetation coverage rate threshold value capable of restraining sand production in a river basin, which is suitable for calculating the forest and grass vegetation coverage rate and the sand production index on a larger river basin scale, and has the advantages of simple calculation method and high calculation precision.
The technical scheme of the invention is as follows: a method for determining a forest and grass vegetation coverage rate threshold capable of restraining sand production in a river basin is characterized in that a remote sensing image is used for carrying out data acquisition for completely covering an easily-eroded area of a loess plateau, influence rules of forest and grass vegetation change on the sand production in the river basin are analyzed by combining data of a past year, a sand production amount threshold is obtained, effective forest and grass coverage rate thresholds in different areas and under different rain intensities are obtained, and then the forest and grass vegetation coverage rate threshold capable of effectively restraining the sand production in the river basin is provided on the scale of the river basin. The method specifically comprises the following steps:
(1) Determining erodible zones
Although rainfall, soil, terrain and vegetation are key elements determining sand production in the river basin, natural factors such as macroscopic terrain, soil components and the like of loess plateau are difficult to change by human beings, so that sand production in the river basin can be influenced by changing the covering degree of the vegetation close to the ground and micro-terrain (such as building terraces or horizontal steps).
A large number of researches show that in urban land and rocky mountain areas of loess plateau and river lands and plain areas (tablelands) with the slope less than 3 degrees, the influence on the sand production in the watershed is found to be very small by changing the vegetation coverage, the microtopography and other artificial factors. Therefore, the lands of river lands, plain areas, construction lands and hilly areas behind rocky mountain areas with the ground gradient less than 3 degrees are to be removed, and the other areas are the areas which are most concerned in researching the sand production of the watershed and are called as 'easily-eroded areas' in the text.
In contrast to the "classification of current land utilization" (GB/T21010-2007), the easily erodible zones of loess plateau mainly include four land utilization types: the water and soil erosion degree of cultivated land, forest land, grassland and unused land depends on the vegetation coverage of forest and grass and the terraced field degree of slope cultivated land.
(2) Calculating the vegetation coverage rate of the forest and grass
Wherein, V c -vegetation coverage of the forest lawn; a. The is -area of orthographic projection of the leaves and stems of forest grass in Km 2 ；A e Area of erodible zone in km 2 。
Wherein, V e -forest and grass vegetation coverage; a. The v -area of forest and grass in Km 2 ；V c Vegetation coverage of forest grassland, orthographic projection area A of forest grass leaves and stems ls Area of forest lawn A v In the presence of a suitable solvent.
(3) Calculating sand production index
Wherein S is i -sand production index, which refers to the sand production amount per unit area of unit rainfall in the easily erodable drainage basin; w s -the sand production in the watershed,unit is m 3 In the formula, the sum of the actual measured sand conveying amount, the sand blocking amount of a silt dam and a reservoir and the irrigation sand guiding amount of a port section is calculated; p 25 -total annual rainfall greater than 25mm daily, which is more sensitive to watershed sand production on a watershed scale.
(4) Determining forest and grass vegetation coverage rate threshold capable of restraining sand production in drainage area
Respectively constructing the relationship between vegetation and sand according to three rain intensities of 0.075, 0.15 and 0.3, taking the rain intensity =0.15 and the rain intensity =0.3 as rain intensity references for determining a Ve threshold value, and taking S as a reference for determining the rain intensity of the Ve threshold value i ≤7t/km 2 Mm is used as a mark for basically restraining sand production in the drainage area, and the corresponding effective coverage rate V of the forest and grass e I.e. V capable of basically restraining sand production in the drainage area e And (4) a threshold value.
Aiming at the defects that manually acquired data cannot be widely covered and the time consumption is long, the method acquires the data of the loess plateau which is completely covered by the remote sensing image in the easily-eroded area, analyzes the influence rule of the change of the forest grass vegetation on the sand production in the drainage area by combining the data of the past year and obtains the sand production threshold value to obtain the effective coverage rate threshold values of the forest grass in different areas and under different rain intensities, and has great significance for the construction of water and soil loss vegetation control measures, the control of the sand production modulus and the final control of the sand production amount. Compared with the prior art, the invention has the following advantages
(1) The remote sensing image has higher spatial resolution and short data acquisition time, and can make up the defects of artificial investigation. Compared with the prior art, the method has the advantages of large coverage area, wide range, comprehensive information, high truth degree and easy operation, can comprehensively cover the easily-eroded area of the loess plateau, which is the research area, and better reflects the actual coverage condition of local forest and grass vegetation.
(2) The research scale is not limited to the slope scale, and can be popularized from the watershed scale to the landscape scale, the global scale and the regional scale. The influence rule of forest and grass vegetation change on the river basin sand production and the vegetation threshold value capable of restraining the river basin sand production are quantitatively analyzed on a larger scale, and a solid theoretical basis and practical guiding significance are provided for research on reducing yellow mud and sand entering in the later period, water and soil loss treatment, evaluation, prediction and control of the river basin sand production.
(3) The calculation method is simple and has high calculation precision.
Drawings
FIG. 1 (a), (b) and (c) are the relationship between effective forest coverage rate and sand production index of sub-1-3 areas of loess hills on the early bedding surface under three rain intensities.
Fig. 2 (a), (b) and (c) respectively show the verification of the relation between the effective coverage rate of the forest and grass terrace and the sand production in the 1 st to 4 th sub-areas of the hills under three rain intensities.
Fig. 3 (a), (b) and (c) show the relationship between the effective coverage rate of the forest and grass terrace and the sand production index of the loess plateau and the dune 5 sub-area under three rain strengths, respectively.
FIG. 4 (a), (b) and (c) are the relations between effective coverage rate of forest and grass in arsenopyrite area, sand covered area, gravel hill area and loess area and sand production index.
FIG. 5 (a) and (b) show the influence of the river basin area change on the response relation of the effective coverage rate of the forest and grass to the sand production index.
Detailed Description
The technical scheme of the invention is further explained by combining the examples. The invention relates to a method for effectively restraining forest and grass vegetation coverage rate threshold value of sand production in a river basin, which can quantitatively describe the sand reduction benefit of vegetation coverage rate and effectively avoid limitation on scale.
The method utilizes the remote sensing image to obtain data such as forest and grass land, combines natural rainfall data to obtain forest and grass coverage rate and sand production index, analyzes the influence rule of forest and grass vegetation change on the river basin sand production under different landforms, spatial scales and rainfall conditions of loess plateau, and further provides a forest and grass vegetation coverage rate threshold value capable of effectively restraining the river basin sand production on the river basin scale.
The satellite remote sensing image with the spatial resolution of 30m is mainly used for extracting the area of an easily-eroded area of each branch (area), and analyzing the influence rule and the threshold value of the change of forest grass vegetation on the sand production of the drainage area under the conditions of different landforms, spatial scales and rainfall of the loess plateau by combining and acquiring data such as forest grass, terrace, rainfall, sand production and the like.
Loess plateau landform types are complicated, including loess hills gully region (yellow hilly region for short), loess high tableland gully region (high tableland for short), loess hilly forest region, loess rank region, high-land grassland region, flush plain region, soil and stone mountain area, arid grassland area, wind sand area, gaishadun district, arsenic sand rock area, gravel hilly region and loess incomplete tableland area. The above classification is divided into a loess area and a non-loess area according to whether there is loess coverage, and the loess hilly gully area, the loess high plateau gully area, the loess hilly forest area, the loess rank area and the high-land grassland area belong to the loess area, the high-land grassland area, the alluvial plain area, the soil and rocky mountain area, the arid grassland area, the wind and sand area, the dun hilly area, the arsenic sand area, the gravel hilly area and the loess stub area. Due to the difference in topography, topography and erosion strength, the yellow hill area is divided into 5 subregions (hereinafter referred to as the hill 1 subregion, the hill 2 subregion, the hill 3 subregion, the hill 4 subregion, and the hill 5 subregion). 90% of silt in the yellow river comes from the yellow hill area and the high tableland area, so the two areas are focused on.
And simulating a curve in the research area according to the relation of the three rain intensities to the effective coverage rate of the forest and the sand production index to analyze the relation of the effective coverage rate of the forest and the sand production index and finally obtain a threshold value.
1. Research method
Firstly, on the basis that a method for acquiring forest and grass data is defined, new concepts such as an area of an area easy to erode, an effective coverage rate of forest and grass, a sand production index and the like are introduced, and tributaries with different basin areas and different rainfall conditions have a unified sand production capacity judgment standard, the following methods are adopted to develop research:
1. aiming at the soil type and the topographic characteristics, a drainage basin with a medium drainage basin area and few terraces is selected as a sample drainage basin, a response relation is directly established between the actually measured sand production index before 1999 and the effective coverage rate of the forest and grass in the same period, and the change rule is analyzed.
2. In view of the fact that the current forest and grass vegetation types, leaf and stem and root system protection modes on the earth surface and the like in the main sand producing area of the yellow river are different from those before 90 years, measured data of a sample basin in nearly ten years are collected, and response relations are verified or corrected.
3. The scientific connotation of 'being capable of restraining the sand production in the river basin' is defined, and the effective coverage rate threshold value of the forest and grass capable of effectively restraining the sand production in the river basin is provided.
Rain intensity is obviously a key factor affecting sand production. According to the actual conditions of the loess plateau, the relationship between vegetation and sand production is respectively constructed according to three rain intensity conditions of 0.075, 0.15, 0.3 and the like.
2. Forest and grass effective coverage rate threshold capable of effectively restraining sand production
As can be seen from FIGS. 1 (a) (b) (c) and 2 (a) (b) (c), when the effective coverage of the forest and grass is 60%, although the average value of Si is 4.4t/km 2 Mm, but with a few data Si reaches 10-15 t/km 2 Mm. Therefore, the meaning of "being able to suppress the sand production in the drainage area" needs to be defined.
According to the soil erosion Classification and Classification Standard (SL 190-2007), "S" is set from the safety perspective i ≤7t/km 2 Mm' as the mark for basically restraining the sand production in the watershed and the corresponding effective coverage rate V of the forest and grass e I.e. V capable of basically restraining sand production in the drainage area e A threshold value. From the safety perspective, "rain intensity =0.15" and "rain intensity =0.3" are taken as the rain intensity reference for determining the Ve threshold value for the low rain intensity region and the high rain intensity region, respectively.
Strictly following the principle of "terrace proportion is less than 3%", 85 pairs, 124 pairs and 62 pairs of data (forest and grass coverage rate V) are respectively selected from the data of fig. 2 (a) (b) (c) and fig. 3 (a) (b) (c) e The range is 5.7-95%, the terrace proportion is counted into V e ) And point-plotted V under three rain intensities e -S i Obtaining a relation line to obtain a quantitative response relation between the effective forest coverage rate and the sand production index of the sub-area 1-4 of the loess hills under three rain intensities, wherein the relation line is as follows: r is 2 For the correlation coefficient, the larger the correlation, the better the correlation.
S i ＝365e -0.078Ve R 2 =0.75 (formula 1)
S i ＝418e -0.076Ve R 2 =0.80 (formula 2)
S i ＝540e -0.074Ve R 2 =0.69 (formula 3)
(1) FIG. 1 (a), (b) and (c) show the effective coverage rate of the forest and grass to the sand production index response relationship of the 1 st to 3 rd sub-areas of the yellow hill under three rain intensities, and the data are 1966-1999 data. As can be seen in fig. 1 (a) (b) (c): despite the different topography of the three subregions, the sand production indexes under the same forest and grass covering condition are not different, namely the sand production amount per unit area under the same rainfall is basically the same.
(2) With the regression line of fig. 1 (a) (b) (c) as the background, distinguishing between the terrace proportion less than 6% and the terrace proportion more than 15%, and plotting the measured data in 2009-2018 in fig. 2 (a) (b) (c) respectively (the terrace proportion is equivalent to the effective coverage rate of the forest and grass), the results show that: the relation between the effective coverage rate of the forest and the terrace and the river basin sand production index in the last decade still obeys the former rule no matter the magnitude of the rain intensity.
Based on the three formulas, according to the sand production index of less than or equal to 7t/km 2 Mm ", ve thresholds of 55% and 60% for the low and high rain intensity zones of the 1 st to 4 th subregions of the hill, respectively. For loess plateau with severe natural conditions, the sand production modulus is less than or equal to 1000t/km 2 A "is an extremely high standard. Therefore, the sand production model is controlled to be 2500t/km 2 A is less than or equal to 17.5t/km 2 Mm). To achieve this, the forest and grass threshold Ve is 42% and 47%, respectively, for the low and high rain intensity regions of the 1 st to 4 th subregions of the hill, and 42 to 47% are located right at the inflection point of the relation line, see fig. 1 (a) (b) (c) and fig. 2 (a) (b) (c).
(3) For a 5-stage district of a dune and a high loess tableland, the effective coverage rate of the forest and grass terrace is more than 45-50%, and the sand yield of the river basin tends to be stable. However, due to the special mechanism of sand production, even if the effective coverage rate of forest and grass and terraced fields reaches 70%, it is difficult to suppress sand production.
(4) With the response relationship (formula 2) of the hills 1-4 as background, the relationship between forest and grass and sand production in sandstone, sand covered, gravelly and loess areas is shown in fig. 4 (a), (b) and (c), respectively. Under the same vegetation and rainfall conditions, the sand yield of the arsenopyrite area is the highest, the sand yield of the loess area is the second lowest, and the sand yield of the sand covered area and the gravel hilly area is the least. The Ve threshold value of the sand covering area and the gravelly hilly area is 45-50 percent; the content of the arsenicum sablimatum area is 70-80%.
(5) The sample flow field area variation of FIGS. 1 (a) (b) (c) to 3 (a) (b) (c) is 500-5000 km 2 Therefore, the influence of the spatial scale change on the relationship between forest grass and sand production needs to be demonstrated. Two groups of data with larger difference of the river basin area are selected from the data with the rain intensities of 0.075 and 0.15 for redrawing, as shown in fig. 5 (a) (b), and the result shows that the influence of the river basin area size on the relation between the forest grass effective coverage rate and the sand production index is not obvious.
The above embodiments are only used to illustrate the technical solutions of the present invention, and the present invention is not limited to the above embodiments, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. A method for determining a forest and grass vegetation coverage rate threshold value capable of restraining sand production in a river basin is characterized in that a remote sensing image is used for carrying out data acquisition for completely covering an easily-eroded area of a loess plateau, influence rules of forest and grass vegetation change on the sand production in the river basin are analyzed by combining historical data, a sand production amount threshold value is obtained, effective forest and grass coverage rate threshold values in different areas and under different rain intensities are obtained, and then the forest and grass vegetation coverage rate threshold value capable of effectively restraining the sand production in the river basin is provided on the scale of the river basin;
the method specifically comprises the following steps:
(1) Determining erodible zones
The method is characterized in that other areas of the land in the hilly area after removing river lands, plain areas, construction lands and rocky mountain areas with the ground gradient less than 3 degrees are also the areas most concerned in the research of the sand production in the watershed;
(2) Calculating the vegetation coverage rate of the forest and grass
Wherein, V e -forest and grass vegetation coverage; a. The v -area of forest and grass in Km 2 ；V c Vegetation coverage of forest grassland, orthographic projection area A of forest grass leaves and stems ls Area of forest lawn A v The ratio of (a); a. The is -area of orthographic projection of the leaves and stems of forest grass in Km 2 ；A e Area of erodible zone in km 2 ；
(3) Calculating sand production index
Wherein S is i -sand production index, which refers to the sand production per unit area per unit rainfall in the easily erodable watershed; w s -sand production in river basin in m 3 The sum of the sand conveying amount, the sand blocking amount of the check dam and the reservoir and the irrigation sand guiding amount is actually measured on the section of the opening in the formula; p is 25 -total annual rainfall of more than 25mm daily, which is more sensitive to watershed sand production on a watershed scale;
(4) Determining forest and grass vegetation coverage rate threshold capable of restraining sand production in drainage area
Respectively constructing the relationship between vegetation and produced sand according to three rain intensity conditions of 0.075, 0.15 and 0.3, taking rain intensity =0.15 and rain intensity =0.3 as rain intensity references for determining a Ve threshold value, and taking S as a reference for determining the Ve threshold value i ≤7t/km 2 Mm is used as a mark for basically restraining sand production in the drainage area, and the corresponding effective coverage rate V of the forest and grass e I.e. V capable of basically restraining sand production in the drainage area e A threshold value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910379175.0A CN110188404B (en) | 2019-05-08 | 2019-05-08 | Method for determining forest and grass vegetation coverage rate threshold capable of restraining sand production in river basin |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910379175.0A CN110188404B (en) | 2019-05-08 | 2019-05-08 | Method for determining forest and grass vegetation coverage rate threshold capable of restraining sand production in river basin |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110188404A CN110188404A (en) | 2019-08-30 |
| CN110188404B true CN110188404B (en) | 2022-11-04 |
Family
ID=67714249
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910379175.0A Expired - Fee Related CN110188404B (en) | 2019-05-08 | 2019-05-08 | Method for determining forest and grass vegetation coverage rate threshold capable of restraining sand production in river basin |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110188404B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113095694B (en) * | 2021-04-19 | 2022-07-22 | 黄河勘测规划设计研究院有限公司 | Rainfall sand transportation model construction method suitable for multiple landform type areas |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103942408A (en) * | 2014-02-19 | 2014-07-23 | 西北农林科技大学 | Annual erosion sediment yield model calculation method of mesoscale drainage basin of loess plateau |
| WO2018103510A1 (en) * | 2016-12-05 | 2018-06-14 | 中国水利水电科学研究院 | Method for evaluation of surface runoff storage capacity of river basin green infrastructure |
-
2019
- 2019-05-08 CN CN201910379175.0A patent/CN110188404B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103942408A (en) * | 2014-02-19 | 2014-07-23 | 西北农林科技大学 | Annual erosion sediment yield model calculation method of mesoscale drainage basin of loess plateau |
| WO2018103510A1 (en) * | 2016-12-05 | 2018-06-14 | 中国水利水电科学研究院 | Method for evaluation of surface runoff storage capacity of river basin green infrastructure |
Non-Patent Citations (1)
| Title |
|---|
| 黄河主要来沙区林草植被变化及对产流产沙的影响机制;刘晓燕等;《中国科学:技术科学》;20151020(第10期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110188404A (en) | 2019-08-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20180058932A1 (en) | Method for analyzing the types of water sources based on natural geographical features | |
| Meade et al. | Changes in sediment loads in rivers of the Atlantic drainage of the United States since 1900 | |
| Skaggs et al. | Effects of land use on soil properties and hydrology of drained coastal plain watersheds | |
| Huang et al. | Surface runoff volumes from vegetated slopes during simulated rainfall events | |
| Huckleberry et al. | Combining radiocarbon and single-grain optically stimulated luminescence methods to accurately date pre-ceramic irrigation canals, Tucson, Arizona | |
| Pande et al. | Thematic mapping for watershed development | |
| Tilahun | Observations and modeling of erosion from spatially and temporally distributed sources in the (semi) humid Ethiopian highlands | |
| Addis et al. | Gully morphology and rehabilitation measures in different agroecological environments of northwestern Ethiopia | |
| Wrońska-Wałach et al. | Impact of ski run construction on atypical channel head development | |
| Mishra et al. | Management of soil losses in South Mahanadi delta, India | |
| Wohl et al. | Synthesizing the scientific foundation for ordinary high water mark delineation in fluvial systems | |
| CN110188404B (en) | Method for determining forest and grass vegetation coverage rate threshold capable of restraining sand production in river basin | |
| Gupta | Drainage engineering: Principles and practices | |
| Muldavin et al. | Handbook of wetland vegetation communities of New Mexico | |
| Schmid et al. | Development of a Regional Groundwater Model for the Indus Basin Irrigation System of Pakistan | |
| KR20150139012A (en) | System for evaluating river landization and method thereof | |
| Atkins et al. | Channel head response to anthropogenic landscape modification: A case study from the North Carolina Piedmont, USA, with implications for water quality | |
| Acreman et al. | Guidance on using wetland sensitivity to climate change tool-kit. A contribution to the Wetland Vision Partnership | |
| Mararakanye | A comparative study of gully erosion contributing factors in two tertiary catchments in Mpumalanga South Africa | |
| Umuhire et al. | Evaluation of Filtering Methods for Hydrograph Separation in Small Agricultural Watersheds in Québec, Canada | |
| Murray et al. | A regional guidebook for applying the hydrogeomorphic approach to assessing functions of forested wetlands in the Mississippi Alluvial Valley | |
| Weiser | Soil Survey of Oliver County, North Dakota | |
| Tebebu | Assessment of hydrological controls on gully formation near Lake Tana, northern highlands of Ethiopia | |
| Shellberg et al. | Alluvial gully erosion rates and processes in Northern Queensland: an example from the Mitchell River fluvial megafan | |
| RAWAT | Geospatial analysis of frontal Himalayan spring hydrology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20221104 |