CN108280773A - A method of differentiating that interzone staple food crop fits water plantation - Google Patents
A method of differentiating that interzone staple food crop fits water plantation Download PDFInfo
- Publication number
- CN108280773A CN108280773A CN201810057532.7A CN201810057532A CN108280773A CN 108280773 A CN108280773 A CN 108280773A CN 201810057532 A CN201810057532 A CN 201810057532A CN 108280773 A CN108280773 A CN 108280773A
- Authority
- CN
- China
- Prior art keywords
- water
- crop
- production
- cereal crops
- value
- 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.)
- Granted
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 117
- 238000000034 method Methods 0.000 title claims abstract description 32
- 235000013305 food Nutrition 0.000 title claims abstract description 23
- 235000013339 cereals Nutrition 0.000 claims abstract description 69
- 238000004519 manufacturing process Methods 0.000 claims abstract description 60
- 238000001556 precipitation Methods 0.000 claims abstract description 16
- 238000004458 analytical method Methods 0.000 claims abstract description 15
- 238000003973 irrigation Methods 0.000 claims abstract description 9
- 230000002262 irrigation Effects 0.000 claims abstract description 9
- 238000010606 normalization Methods 0.000 claims abstract description 8
- 239000011159 matrix material Substances 0.000 claims description 29
- 239000003621 irrigation water Substances 0.000 claims description 22
- 238000009395 breeding Methods 0.000 claims description 15
- 230000001488 breeding effect Effects 0.000 claims description 15
- 235000021307 Triticum Nutrition 0.000 claims description 11
- 235000007164 Oryza sativa Nutrition 0.000 claims description 10
- 235000009566 rice Nutrition 0.000 claims description 10
- 240000008042 Zea mays Species 0.000 claims description 9
- 235000002017 Zea mays subsp mays Nutrition 0.000 claims description 9
- 239000000047 product Substances 0.000 claims description 9
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 claims description 8
- 235000005822 corn Nutrition 0.000 claims description 8
- 241000196324 Embryophyta Species 0.000 claims description 6
- 244000017020 Ipomoea batatas Species 0.000 claims description 6
- 235000002678 Ipomoea batatas Nutrition 0.000 claims description 6
- 239000002689 soil Substances 0.000 claims description 5
- 238000012271 agricultural production Methods 0.000 claims description 4
- 230000007423 decrease Effects 0.000 claims description 4
- 238000011161 development Methods 0.000 claims description 4
- 238000010521 absorption reaction Methods 0.000 claims description 3
- 230000010354 integration Effects 0.000 claims description 3
- 230000000750 progressive effect Effects 0.000 claims description 3
- 230000005855 radiation Effects 0.000 claims description 3
- 239000013589 supplement Substances 0.000 claims description 3
- 238000013316 zoning Methods 0.000 claims description 3
- 244000062793 Sorghum vulgare Species 0.000 claims description 2
- 238000013459 approach Methods 0.000 claims description 2
- 238000000227 grinding Methods 0.000 claims description 2
- 239000000463 material Substances 0.000 claims description 2
- 235000019713 millet Nutrition 0.000 claims description 2
- 240000007594 Oryza sativa Species 0.000 claims 1
- 244000098338 Triticum aestivum Species 0.000 claims 1
- 230000004069 differentiation Effects 0.000 abstract description 4
- 238000009826 distribution Methods 0.000 abstract description 3
- 241000209140 Triticum Species 0.000 description 10
- 241000209094 Oryza Species 0.000 description 9
- 238000005516 engineering process Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 244000283207 Indigofera tinctoria Species 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 241000288147 Meleagris gallopavo Species 0.000 description 1
- 235000002595 Solanum tuberosum Nutrition 0.000 description 1
- 244000061456 Solanum tuberosum Species 0.000 description 1
- 235000016383 Zea mays subsp huehuetenangensis Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 235000009973 maize Nutrition 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/152—Water filtration
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Marine Sciences & Fisheries (AREA)
- Primary Health Care (AREA)
- Mining & Mineral Resources (AREA)
- Animal Husbandry (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Cultivation Of Plants (AREA)
Abstract
The present invention relates to a kind of methods that differentiation interzone staple food crop fits water plantation, including：Divide region；Crop divides；Cereal crops water requirement is calculated by ten days；Effective precipitation in cereal crops growth period is calculated by ten days；Irrigation requirement calculates；Production estimation element characteristic vector analysis；Normalization；Suitable water plantation is judged.The present invention is theoretical based on Virtual water, water footprints, the discrimination formula that staple food crop fits water plantation is established with Hierarchy Analysis Method, and the method for differentiating that interzone staple food crop fits water plantation is proposed using the formula, objective, comprehensive reflection grain-production and water resource use, that is effective rainfall and duty, space characteristics are that the rationalization utilization of agricultural water resources and staple food crop fit water planting structure distribution and provide scientific basis.
Description
Technical field
The present invention relates to a kind of methods that differentiation interzone staple food crop fits water plantation, are a kind of cereal crops production
The method of water resources rational use is a kind of method rationally to control and configuring area cereal crops irrigation water uses.
Background technology
As population increases the continuous promotion with living standards of the people, grain demand amount will be further increased, agricultural development
It is faced with the challenge that more grains are produced with limited water resources.It is planted by suitable water, reduction cereal crops production needs water consumption, spy
It is not blue water demand, the grain production capacity for improving folk prescription water is the root for alleviating regional water resources pressure and Ensuring Food Safety
This measure.
In recent years, the utilization of the water resources such as Virtual water, water footprints and management theory method, provide for agricultural water resources management
New thinking.A kind of measuring method of grain production water footprint of region（Wu Pute, 2013）Calculate the indigo plant in grain-production
Water footprints and clear water footprint, a method of calculating interzone fictitious flow momentum（Ma Jing, 2014）Analyze Agricultural Water money
The transregional flow in source.Still lack grain-production to clear water, Lan Shui, Productive statistics and output spatial framework relative quantification at present
Method of discrimination lacks and agricultural production, water resources management and policymaker is allowed intuitively to differentiate cereal crops space planting structure distribution and optimization
Quick method.
Invention content
In order to overcome problem of the prior art, the present invention to propose a kind of suitable water plantation of differentiation interzone staple food crop
Method.Ratio, production cost, cost of land, the per unit area yield synthesis that the method accounts for water requirement using water requirement, irrigation volume are sentenced
The space characteristics and its adaptability of disconnected plant of grain crops for optimization cereal crops space layout, control and reduce grain-production
Irrigation water capacity provides help.
The object of the present invention is achieved like this：A method of differentiating that interzone staple food crop fits water plantation, institute
The step of stating method is as follows：
The step of dividing region：Extensive area classification is divided into according to the characteristics of landform, weather, socio-economic development situation
Several survey regions；It collects each survey region staple food crop breeding time, provided with breeding time relevant meteorological data, rainfall
Material；
The step of crop divides：Cereal crops are divided into i class cereal crops, and i is natural number, represents rice, wheat, corn, height
One kind in fine strain of millet, sweet potato, sweet potato, purple sweet potato；
The step of cereal crops water requirement being calculated by ten days：
I class cereal crops evapotranspiration of the survey region by ten days is calculated by formulaET 0：
Wherein：Δ is saturation vapour pressure-temperature curve slope；R n To input the net radiation of crop canopies；GIt is consumed for gain of heat soil
Energy；γFor hygrometer constant；TFor temperature on average；U 2For 2m high wind speeds；e a For saturation vapour pressure；e d For actual observation steam
Pressure；
Group cereal crops water requirement of the survey region by ten days is calculated by formulaET i ：
ET i = ET 0×Kc i
Wherein：Kc i For i kind cereal crops coefficients；
The step of effective precipitation in cereal crops growth period being calculated by ten days：Using in region each meteorological site ten days precipitation as base
Plinth calculates areal rainfall, in conjunction with the water demand of crop in ten days, in zoning difference cereal crops breeding time with Thiessen polygon method
Effectiv precipitation：
PE i = f（P）= min（P,PE i ）
In formula,PIt is survey region by ten days precipitation magnitude；PE i For the effectiv precipitation of each subregion i kind cereal crops；
The step of irrigation requirement calculates：Effective rainfall in growth period is drawn in cereal crops growth first, insufficient section again by
Duty supplements：
In formula,IR i For the irrigation requirement of i-th kind of cereal crops of each subregion；
The step of irrigation water accounting calculates：Irrigation water proportion in water requirementCalculating：
；
The step of production estimation element characteristic vector analysis：, input small, output greatly criterion few with water consumption, utilizes level
Analytic approach carries out comprehensive diagnos to the complicated cereal crops production system of multiple target, multiple criteria, amorphousness, according to cereal crops
Classification between each production factors and level are carried out organic assembling and distinguishing hierarchy, establish progressive hierarchical structure, referred to using two-stage
Mark judgment matrix group acquires integration objective maximum, step analysis matrix：
The first order：Including production water requirement, Productive statistics, production output three classes index, increased using water resource, volume increase for saving
For receipts, on the one hand it is expected that production water requirement is small, output is big, the two is slightly more important than the latter compared to the former；On the one hand it is expected production
Put into that small, output is big, the two is suitable compared to importance, and judgment matrix A is：
；
The second level：Including three production water requirement, input, output index matrixs, analyzed using matrix group, water requirement matrix
Including grain-production water requirement ET and irrigation water accounting two indices, it is expected that cereal crops breeding time ET values are small, irrigation water accounts for ET
Ratio it is low, with the shortage of agricultural production water amount, the significance level of two indices is suitable, and judgment matrix is：；
Absorption matrix includes production cost, cost of land two indices, it is expected that production cost is small, cost of land is small, and index is important
Property is ordered as a little higher than cost of land of production cost, judgment matrix：
；
To matrixB 1、B 2Maximum characteristic root calculating is carried out, determines its corresponding feature vector；
Normalized step：, input small, output greatly criterion few with water requirement chooses element standard value, and wherein ET, irrigation water account for
Than, production cost, cost of land using minimum value as standard value, use standard value divided by various regions actual value as normalization after standard
Change value, major product yield use various regions actual value divided by standard value as the standardized value after normalization to be up to standard value；
The step of suitable water plantation is judged：Multiple cereal crops, which are calculated, using following formula fits water plantation comprehensive scoreVValue：
In formula,Water, which is fitted, for crop i plants comprehensive score；For the standard value of crop i water requirements；Water is needed for crop i
The actual value of amount；For the standard value of crop i irrigation water accountings；For the actual value of crop i irrigation water accountings；For
The standard value of crop i production costs per acre；For the actual value of crop i production costs per acre；For the soils per acre crop i
The standard value of cost；For the actual value of crop i cost of land per acre；For the standard value of crop i grain yields per acre；For the actual value of crop i grain yields per acre；
It will be multipleVValue is ranked up, and is drawn respectively eachVThe decline curve of value, according to V value slope of curve constant intervals, in conjunction with grinding
Study carefully the actual conditions of region cereal crops, analyzes the suitable water plantation combination distinguishing section for determining survey region.
The beneficial effect comprise that：The present invention is based on Virtual water, water footprints theories, are built with Hierarchy Analysis Method
Vertical staple food crop fits the discrimination formula of water plantation, and is proposed using the formula and differentiate that interzone staple food crop fits water
The method of plantation.The method is objective, comprehensive reflection grain-production and water resource use, i.e. effective rainfall and duty,
Space characteristics are that the rationalization utilization of agricultural water resources and staple food crop fit water planting structure distribution and provide scientific basis.
Description of the drawings
The invention will be further described with reference to the accompanying drawings and examples.
Fig. 1 is the flow chart of the embodiment of the present invention the method；
Fig. 2 is the decline curve schematic diagram of the suitable water plantation integrated value of the wheat in the application example of the present invention.
Specific implementation mode
Embodiment：
The present embodiment is a kind of method that differentiation interzone staple food crop fits water plantation, and process is as shown in Figure 1.The present embodiment
Calculated or combined water resource assets irrigation requirement inquiry system to obtain crop water, blue water accounting according to meteorological data,
In conjunction with China《National agricultural product cost-benefit data compilation》Production cost, cost of land, major product yield data establish master
Cereal crops are wanted to fit the discrimination formula of water plantation, the suitable water of analysis staple food crop spatially is planted feature, filled to realize
Divide using clear water, save using blue water, reasonably optimizing grain-production space layout and Agricultural Water safety analysis offer technology branch
Support.
The present embodiment is few with water consumption, input is small, and output greatly target setting fits water and plants discriminant criterion, and water consumption lacks mesh
Mark is lower to account for two indexs of ET ratios using cereal crops Evapotranspiration ET (mm) He Lanshui, uses and is produced under input Small object
Originally, two indexs of cost of land, output is lower greatly to use one index of major product yield, but is not limited only to this several targets, studies
Person can flexibly increase the element that need to be considered according to actual conditions and needs, rationally be adjusted to matrix.
The method detailed process and steps are as follows, the present embodiment is divided with the national areas of China and agricultural crops are
Example：
1, crop water demand calculation
（1）The whole nation is divided into several regions first, in accordance with the features such as landform, weather, socio-economic development situation.Collect each area
Domain staple food crop breeding time and breeding time relevant meteorological data, rainfall data etc..Staple food crop can be divided into water
Rice further can be subdivided into early rice, semilate rice and late rice, wheat by rice, wheat, corn, other cereal, potato etc. as needed
It is subdivided into winter wheat, spring wheat, corn is subdivided into spring maize, summer corn.
（2）Object is allocated as by the gross water requirement calculated in ten days in breeding time.By Penman formula（Penman-Menteith）Based on ten days
The cereal crops evapotranspiration in the areas Suan GeET 0, in conjunction with crop coefficient obtain in different cereal crops breeding times by ten days water requirement.
（1）
（2）
In formula, Δ is saturation vapour pressure-temperature curve slope；R n To input the net radiation of crop canopies；GIt is consumed for gain of heat soil
Energy；γFor hygrometer constant；TFor temperature on average；U 2For 2m high wind speeds；e a For saturation vapour pressure；e d For actual observation steam
Pressure；Kc i For i kind cereal crops coefficients；It is i kinds cereal crops by the water requirement in ten days, unit。
（3）Object is allocated as by the effectiv precipitation calculated in ten days in breeding time.Ten days precipitation with each meteorological site in region is
Basis calculates areal rainfall, in conjunction with the water demand of crop in ten days, in zoning difference cereal crops breeding time with Thiessen polygon method
Effectiv precipitation.
(3)
In formula,It is subregion by ten days precipitation magnitude, unit；It is single for the effectiv precipitation of each subregion i kind cereal crops
Position。
（4）Irrigation requirement calculates.The effective rainfall in growth period is drawn in cereal crops growth first（Clear water）, no
Foot point is again by duty（Lan Shui）Supplement.
(4)
In formula,For the irrigation requirement of each subregion i kind cereal crops, unit。
（5）Different cereal crops indigo plant water（Irrigation water）AccountingIt calculates
(5)
2, the production estimation element characteristic vector analysis based on analytic hierarchy process (AHP)：
（1）, input small, output greatly criterion few with water consumption, using analytic hierarchy process (AHP) to multiple target, multiple criteria, amorphousness
Complicated grain biological production system carry out comprehensive diagnos, according to the classification and level between each production factors of cereal crops, carry out
Organic assembling and distinguishing hierarchy establish progressive hierarchical structure, and integration objective maximum is acquired using two-stage index judgment matrix group.Layer
Secondary analysis scale meaning is listed in table 1.
1 step analysis scale meaning of table
（2）Two-stage index judgment matrix group is as follows：
The first order：Including production water requirement, Productive statistics, production output three classes index.Increased using water resource, volume increase for saving
For receipts, on the one hand it is expected that production water requirement is small, output is big, the two is slightly more important than the latter compared to the former；On the one hand it is expected production
Put into that small, output is big, the two is suitable compared to importance, according to the standard of weight analysis（Table one）, judgment matrix A is：
The second level：Including three production water requirement, input, output index matrixs, analyzed using matrix group.Water requirement matrix
Including grain-production water requirement ET（mm）With irrigation water accounting two indices, it is expected that cereal crops breeding time ET values are small, irrigation water
The ratio for accounting for ET is low, and with the shortage of agricultural production water amount, the significance level of two indices is suitable, and judgment matrix is such asInstitute
Show.Absorption matrix includes production cost（Member/mu）, cost of land（Member/mu）Two indices, it is expected that production cost is small, soil at
This is small, and index importance is ordered as a little higher than cost of land of production cost, and judgment matrix is such asIt is shown.Output matrix is only led
Product yield（kg/hm2）One index.
（3）Maximum characteristic root calculating is carried out to above-mentioned matrix, determines its corresponding feature vector（Table 2）.
2 target layers structure of table and weight score value
3, normalization is judged with the plantation of suitable water：
（1）, input small, output greatly criterion few with water requirement chooses element standard value, wherein ET, irrigation water accounting, is produced into
Originally, cost of land uses standard value divided by various regions actual value as the standardized value after normalization, main product using minimum value as standard value
Product yield uses various regions actual value divided by standard value as the standardized value after normalization to be up to standard value.Lacking basis
Crop in China producing region in 2015 can be used in data or in the case of not having special high request to result of calculation, each element standard value
Analog value calculates（Table 3）.
3 2015 years cereal crops production factors indicators standard values of table
Crop based on analytic hierarchy process (AHP) fits water and plants discrimination formula：
(6)
In formula,Water, which is fitted, for crop i plants comprehensive score, dimensionless；For the standard value of crop i water requirements（Take minimum
Value）, unit mm,For the actual value of crop i water requirements, unit mm；For the standard value of crop i irrigation water accountings（It takes most
Small value）, dimensionless；For the actual value of crop i irrigation water accountings, dimensionless；For the mark of crop i production costs per acre
Quasi- value（It is minimized）, identical element/mu；For the actual value of crop i production costs per acre, identical element/mu；For crop i
The standard value of cost of land per acre（It is minimized）, identical element/mu；For the actual value of crop i cost of land per acre, unit
Member/mu；For the standard value of crop i grain yields per acre（It is maximized）, units/kg/hm2；For crop i grains per acre
The actual value of yield, units/kg/hm2。
（2）Staple food crop is fitted water implanting and is differentiated：
Using formula（6）Rice, wheat, corn crop comprehensive evaluation value that Chinese main food production in 2015 saves is calculated（V
Value）, by sorting from big to small, it is as a result listed in table 4, the decline curve of three kinds of cereal crops V values is drawn respectively, according to V value curves
Slope variation section, in conjunction with 13 grain main products provinces of China and grain ration（Paddy and wheat）The actual conditions of big producing province, point
Analysis determines suitable water plantation comprehensive distinguishing section（Referring to Fig. 2）, rice, wheat, corn crop fit water plantation and differentiate that section is listed in table
5。
Table grain-production in 4 2015 years, which saves, fits water plantation integrated value analysis result
5 staple food crop of table fits water plantation integrated value V and differentiates section
Table 5 give three kinds of crops the hydrophile of CHINESE REGION range.For directly calculating V values between a certain area, and
By table 5 can obtain this area whether suitable planting rice, wheat or corn.If increasing the type of crop, Huo Zhegai
Become survey region, the method, can obtain larger range of comprehensive conclusion through this embodiment.
Finally it should be noted that above be merely illustrative of the technical solution of the present invention and it is unrestricted, although with reference to preferable cloth
The scheme of setting describes the invention in detail, it will be understood by those of ordinary skill in the art that, it can be to the technology of the present invention
Scheme（Such as the dividing mode in area, the utilizations of various formula, step sequencing etc.）It is modified or replaced equivalently,
Without departing from the spirit of the technical scheme of the invention and range.
Claims (1)
1. a kind of method for differentiating interzone staple food crop and fitting water plantation, which is characterized in that the step of the method is as follows：
The step of dividing region：Extensive area classification is divided into according to the characteristics of landform, weather, socio-economic development situation
Several survey regions；It collects each survey region staple food crop breeding time, provided with breeding time relevant meteorological data, rainfall
Material；
The step of crop divides：Cereal crops are divided into i class cereal crops, and i is natural number, represents rice, wheat, corn, height
One kind in fine strain of millet, sweet potato, sweet potato, purple sweet potato；
The step of cereal crops water requirement being calculated by ten days：
I class cereal crops evapotranspiration of the survey region by ten days is calculated by formulaET 0：
Wherein：Δ is saturation vapour pressure-temperature curve slope；R n To input the net radiation of crop canopies；GIt is consumed for gain of heat soil
Energy；γFor hygrometer constant；TFor temperature on average；U 2For 2m high wind speeds；e a For saturation vapour pressure；e d For actual observation steam
Pressure；
Group cereal crops water requirement of the survey region by ten days is calculated by formulaET i ：
ET i = ET 0×Kc i
Wherein：Kc i For i kind cereal crops coefficients；
The step of effective precipitation in cereal crops growth period being calculated by ten days：Using in region each meteorological site ten days precipitation as base
Plinth calculates areal rainfall, in conjunction with the water demand of crop in ten days, in zoning difference cereal crops breeding time with Thiessen polygon method
Effectiv precipitation：
PE i = f（P）= min（P,PE i ）
In formula,PIt is survey region by ten days precipitation magnitude；PE i For the effectiv precipitation of each subregion i kind cereal crops；
The step of irrigation requirement calculates：Effective rainfall in growth period is drawn in cereal crops growth first, insufficient section again by
Duty supplements：
In formula,IR i For the irrigation requirement of i-th kind of cereal crops of each subregion；
The step of irrigation water accounting calculates：Irrigation water proportion in water requirementCalculating：
；
The step of production estimation element characteristic vector analysis：, input small, output greatly criterion few with water consumption, utilizes level
Analytic approach carries out comprehensive diagnos to the complicated grain biological production system of multiple target, multiple criteria, amorphousness, each according to cereal crops
Classification between production factors and level carry out organic assembling and distinguishing hierarchy, progressive hierarchical structure are established, using two-stage index
Judgment matrix group acquires integration objective maximum, step analysis matrix：
The first order：Including production water requirement, Productive statistics, production output three classes index, increased using water resource, volume increase for saving
For receipts, on the one hand it is expected that production water requirement is small, output is big, the two is slightly more important than the latter compared to the former；On the one hand it is expected production
Put into that small, output is big, the two is suitable compared to importance, and judgment matrix A is：
；
The second level：Including three production water requirement, input, output index matrixs, analyzed using matrix group, water requirement matrix
Including grain-production water requirement ET and irrigation water accounting two indices, it is expected that cereal crops breeding time ET values are small, irrigation water accounts for ET
Ratio it is low, with the shortage of agricultural production water amount, the significance level of two indices is suitable, and judgment matrix is：；
Absorption matrix includes production cost, cost of land two indices, it is expected that production cost is small, cost of land is small, and index is important
Property is ordered as a little higher than cost of land of production cost, judgment matrix：
；
To matrixB 1、B 2Maximum characteristic root calculating is carried out, determines its corresponding feature vector；
Normalized step：, input small, output greatly criterion few with water requirement chooses element standard value, and wherein ET, irrigation water account for
Than, production cost, cost of land using minimum value as standard value, use standard value divided by various regions actual value as normalization after standard
Change value, major product yield use various regions actual value divided by standard value as the standardized value after normalization to be up to standard value；
The step of suitable water plantation is judged：Multiple cereal crops, which are calculated, using following formula fits water plantation comprehensive scoreVValue：
In formula：Water, which is fitted, for crop i plants comprehensive score；For the standard value of crop i water requirements；Water is needed for crop i
The actual value of amount；For the standard value of crop i irrigation water accountings；For the actual value of crop i irrigation water accountings；To make
The standard value of object i production costs per acre；For the actual value of crop i production costs per acre；For crop i cost of land per acre
Standard value；For the actual value of crop i cost of land per acre；For the standard value of crop i grain yields per acre；To make
The actual value of object i grain yields per acre；
It will be multipleVValue is ranked up, and is drawn respectively eachVThe decline curve of value, according to V value slope of curve constant intervals, in conjunction with grinding
Study carefully the actual conditions of region cereal crops, analyzes the suitable water plantation combination distinguishing section for determining survey region.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810057532.7A CN108280773B (en) | 2018-01-22 | 2018-01-22 | A method of differentiating that ground section staple food crop fits water plantation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810057532.7A CN108280773B (en) | 2018-01-22 | 2018-01-22 | A method of differentiating that ground section staple food crop fits water plantation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108280773A true CN108280773A (en) | 2018-07-13 |
| CN108280773B CN108280773B (en) | 2019-05-28 |
Family
ID=62802501
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810057532.7A Active CN108280773B (en) | 2018-01-22 | 2018-01-22 | A method of differentiating that ground section staple food crop fits water plantation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108280773B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110580657A (en) * | 2019-10-12 | 2019-12-17 | 中国水利水电科学研究院 | agricultural irrigation water demand prediction method |
| CN111626526A (en) * | 2020-06-09 | 2020-09-04 | 北京农学院 | Ecological cycle-oriented regional planting, breeding and processing prediction method |
| CN114009281A (en) * | 2021-12-07 | 2022-02-08 | 中国农业大学 | Crop planting suitability recommendation method |
| CN114882500A (en) * | 2022-07-11 | 2022-08-09 | 深圳市赛泰诺生物技术有限公司 | Multifunctional transgenic grain and oil intelligent detection method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103226791A (en) * | 2013-04-12 | 2013-07-31 | 西北农林科技大学 | Measuring and calculating method of grain production water footprint of region |
| CN106295953A (en) * | 2016-07-26 | 2017-01-04 | 中国农业大学 | A kind of production estimation suitability evaluation methods and system |
| CN107491844A (en) * | 2017-08-28 | 2017-12-19 | 中国水利水电科学研究院 | The analysis method of field irrigation level water requirement |
| CN107609686A (en) * | 2017-08-25 | 2018-01-19 | 西安理工大学 | A kind of Stands in Arsenic Sandstone Area sand ground agricultural development utilizes the determination method of adaptability scale |
-
2018
- 2018-01-22 CN CN201810057532.7A patent/CN108280773B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103226791A (en) * | 2013-04-12 | 2013-07-31 | 西北农林科技大学 | Measuring and calculating method of grain production water footprint of region |
| CN106295953A (en) * | 2016-07-26 | 2017-01-04 | 中国农业大学 | A kind of production estimation suitability evaluation methods and system |
| CN107609686A (en) * | 2017-08-25 | 2018-01-19 | 西安理工大学 | A kind of Stands in Arsenic Sandstone Area sand ground agricultural development utilizes the determination method of adaptability scale |
| CN107491844A (en) * | 2017-08-28 | 2017-12-19 | 中国水利水电科学研究院 | The analysis method of field irrigation level water requirement |
Non-Patent Citations (1)
| Title |
|---|
| 盖燕如 等: "灌溉水经济价值与粮棉作物种植布局", 《中国水利水电科学研究院学报》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110580657A (en) * | 2019-10-12 | 2019-12-17 | 中国水利水电科学研究院 | agricultural irrigation water demand prediction method |
| WO2021068540A1 (en) * | 2019-10-12 | 2021-04-15 | 中国水利水电科学研究院 | Agricultural irrigation water demand prediction method |
| US11209574B2 (en) | 2019-10-12 | 2021-12-28 | China Institute Of Water Resources And Hydropower Research | Method for forecasting an agricultural irrigation water requirement |
| JP2022512047A (en) * | 2019-10-12 | 2022-02-02 | チャイナ インスティチュート オブ ウォータ リソースィズ アンド ハイドロパワー リサーチ | Agricultural irrigation water demand forecast method |
| JP7149348B2 (en) | 2019-10-12 | 2022-10-06 | チャイナ インスティチュート オブ ウォータ リソースィズ アンド ハイドロパワー リサーチ | Agricultural irrigation water demand forecast method |
| CN111626526A (en) * | 2020-06-09 | 2020-09-04 | 北京农学院 | Ecological cycle-oriented regional planting, breeding and processing prediction method |
| CN111626526B (en) * | 2020-06-09 | 2023-04-07 | 北京农学院 | Ecological cycle-oriented regional planting, breeding and processing prediction method |
| CN114009281A (en) * | 2021-12-07 | 2022-02-08 | 中国农业大学 | Crop planting suitability recommendation method |
| CN114882500A (en) * | 2022-07-11 | 2022-08-09 | 深圳市赛泰诺生物技术有限公司 | Multifunctional transgenic grain and oil intelligent detection method and system |
| CN114882500B (en) * | 2022-07-11 | 2022-09-16 | 深圳市赛泰诺生物技术有限公司 | Multifunctional transgenic grain and oil intelligent detection method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108280773B (en) | 2019-05-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108280773B (en) | A method of differentiating that ground section staple food crop fits water plantation | |
| Panda et al. | Effective management of irrigation water for maize under stressed conditions | |
| Arora et al. | Analyzing wheat productivity responses to climatic, irrigation and fertilizer-nitrogen regimes in a semi-arid sub-tropical environment using the CERES-Wheat model | |
| Grassini et al. | High-yield irrigated maize in the Western US Corn Belt: II. Irrigation management and crop water productivity | |
| Amichev et al. | Hybrid poplar growth in bioenergy production systems: biomass prediction with a simple process-based model (3PG) | |
| Su et al. | Optimal allocation of agricultural water resources based on virtual water subdivision in Shiyang River Basin | |
| Mo et al. | Attributing regional trends of evapotranspiration and gross primary productivity with remote sensing: a case study in the North China Plain | |
| CN103226791B (en) | The measuring method of grain production water footprint of region | |
| Karandish et al. | Application of virtual water trade to evaluate cropping pattern in arid regions | |
| Duan et al. | Spatial pattern characteristics of water footprint for maize production in Northeast China | |
| Wei et al. | Optimising yield and resource utilisation of summer maize under the conditions of increasing density and reducing nitrogen fertilization | |
| CN102754592A (en) | Method for screening variety with relatively-high phosphor utilization efficiency from multiple cut-flower chrysanthemum varieties | |
| Aktar | Agricultural productivity and productivity regions in West Bengal | |
| Tappeiner et al. | Model simulation of spatial distribution of photosynthesis in structurally differing plant communities in the Central Caucasus | |
| Wang et al. | Cotton growth model under drip irrigation with film mulching: A case study of Xinjiang, China | |
| Ma et al. | Effects of crop-slope interaction on slope runoff and erosion in the Loess Plateau | |
| Gao et al. | Relationship and distribution of in-field dry-down and equilibrium in maize grain moisture content | |
| Yang et al. | Spatiotemporal variations of water productivity for cropland and driving factors over China during 2001–2015 | |
| Odey et al. | Modeling the influence of seasonal climate variability on soybean yield in a temperate environment: South Korea as a case study | |
| CN110533346A (en) | A kind of Water resources security appraisal procedure of grain-production | |
| Zhao et al. | Modelling water/heat transfer and crop growth under film mulching condition in a seed–maize field | |
| Dan et al. | Climatic and biological simulations in a two-way coupled atmosphere–biosphere model (CABM) | |
| Videla-Mensegue et al. | Modelling water productivity for ecological intensification of crop sequences in the Inner Argentinean Pampas | |
| Zhang et al. | Assessing the response of orchard productivity to soil water depletion using field sampling and modeling methods | |
| CN103294905B (en) | OO crops date of seeding monitoring method |
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 |