CN107145666A - The GIS modeling methods of wheat Natural water deficit drought assessment model - Google Patents
The GIS modeling methods of wheat Natural water deficit drought assessment model Download PDFInfo
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- CN107145666A CN107145666A CN201710311221.4A CN201710311221A CN107145666A CN 107145666 A CN107145666 A CN 107145666A CN 201710311221 A CN201710311221 A CN 201710311221A CN 107145666 A CN107145666 A CN 107145666A
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Abstract
The invention discloses the GIS modeling methods of wheat Natural water deficit drought assessment model, this method is according to the decomposition to natural moisture deficiency rates model, in the ModelBuilder Modeling Platforms of ArcGIS softwares, point data is processed as by the continuous space lattice data of numerical value using the inverse distance weighted interpolation instrument in ArcGIS softwares, ArcGIS raster symbol-base device is recycled to be overlapped analysis to space lattice data, first to Rn, G, Δ, γ, U2, Ta, Ea, Eb is modeled, wheat potential evapotranspiration ET0 is modeled according to the variate model set up, the water requirement E in wheat time of infertility modeling is completed again, simultaneously, the natural output W in the wheat time of infertility is modeled, on the basis of E and W modeling is completed, complete the natural moisture deficiency rates G of wheat growing stage modeling, constitute a complete natural moisture deficiency rates model.
Description
Technical field
The present invention relates to a kind of GIS modeling methods of wheat Natural water deficit drought assessment model, belong to agricultural disaster
The technical field of assessment.
Background technology
Wheat is one of important cereal crops of China, and Wheat Drought disaster has a strong impact on China's grain security, to wheat
The assessment of arid is particularly important.
Natural moisture deficiency rates model accounts for the percentage of water requirement for the difference of the natural output of crop and water requirement, preferably
Ground reflects the combined influence of soil, plant and meteorological three aspect factor, more truly reflects Crop water deficits situation,
It is one of conventional Crops Drought diagnostic method.Calculating process is as follows：
In formula, E is the water requirement in the wheat time of infertility, and W is the natural output in the wheat time of infertility；Unit is mm.
E=Kc × ET0 (2)
In formula, Kc is crop coefficient, and wheat time of infertility Kc takes 1.04；ET0 is possible steam (mm), using FAO (1998)
The Penman-Monteith formula of recommendation are tried to achieve.
In formula：ET0 is evapotranspiration rate of referential crops (mm/d)；Rn is net radiation [M J/ (m2d)]；G is soil heat flux
[M J/ (m2d)], when calculation interval is in 10~30d, per day soil heat flux value very little can be neglected；And by
Day or when estimating for a long time, G values are usual critically important；U 2 is 2m eminences wind speed (ms-1)；Δ is that saturation water othermohygrometer relation is bent
Tangent slope (kPa/ DEG C) on line at Ta；γ is psychrometer constant (kPa/ DEG C)；Ta is daily mean temperature (DEG C)；Ea is full
With vapour pressure (kPa)；Eb is actual vapour pressure (kPa).
Wheat nature output (W) includes three parts：1. the effective soil moisture of the soil of wheat (W1)；2. in the wheat time of infertility
Effectiv precipitation (W2)；3. yield of groundwater (W3).Calculation formula is：
W=W1+W2+W3 (4)
W1=(Wt-Wd) × ρ × h × 0.1 (5)
In formula, W1 is the effective soil moisture amount of soil before wheat cultivation, and unit is mm；Wt is the actual soil before wheat cultivation
Humidity, unit is %；Wd is wilting moisture, and value 6.5, unit is %；ρ is the soil weight 1.44, and unit is g/cm3；H is soil
Thickness degree, unit is cm；0.1 is unit conversion coefficient.
W2=P (6)
Wherein P is actual precipitation, and unit is millimeter (mm).
In wheat output is actually calculated, yield of groundwater W3 can be neglected.
Model builder (ModelBuilder) is the construction geoanalysis that ArcGIS is provided and processing workflow and script
Graphics data modeling tool.ModelBuilder is by 3 basic knots such as input data, spatial manipulation instrument and output data
Structure is constituted.
Spatial interpolation methods, i.e., by the rule of the sampling point data obtained, extrapolation or interior be inserted into whole survey region and be
The method of face data.
Raster symbol-base device is the basic module for setting up complicated applied mathematical model, based on mathematical operator and mathematics letter
Number is calculated the continuous space lattice data of numerical value, obtains required space lattice data.
Natural moisture deficiency rates model is related to the formula of more data and large amount of complex, exists easily to go out in practical application
Wrong, the low drawback of efficiency.The model is combined with GIS herein, progressively piecemeal sets up the wheat Natural water deficit based on GIS
Drought assessment model, so as to improve the shortcoming of former mathematical modeling, improves the service efficiency of model.
The content of the invention
It is an object of the invention to overcome the shortcomings of that prior art is present to be easy to user to understand there is provided one kind, mould is improved
The GIS modeling methods of the wheat Natural water deficit drought assessment model of type service efficiency.
The technical solution adopted by the present invention is：A kind of GIS modeling methods of wheat Natural water deficit drought assessment model,
Comprise the following steps：
Step one：Natural moisture deficiency rates model is divided into 2 parts first：The water requirement E in the wheat time of infertility and small
The natural output W in the wheat time of infertility.Again by ET0 points of wheat potential evapotranspiration in the water requirement E formula in the wheat time of infertility
For 8 parts.
Step 2：Choose and study the meteorological site data of area for a period of time and soil moisture content form, in ModelBuilder
Point data is processed as by the continuous space lattice data of numerical value using inverse distance weighted interpolation instrument in Modeling Platform.
Step 3：Analysis is overlapped to the variable in wheat potential evapotranspiration ET0 using raster symbol-base device, built respectively
In T on mould, including saturation water othermohygrometer relation curveaThe tangent slope Δ at place, wet table constant γ, soil heat flux G, 2m are high
Locate wind velocity U 2, saturation vapour pressure es, daily mean temperature Ta, actual vapour pressure ea and net radiation RnModeling.
Step 4：According to the model being had built up in step 3, also with the raster symbol-base device in ModelBuilder
Wheat potential evapotranspiration ET0 is modeled, and using wheat potential evapotranspiration ET0 models to wheat time of infertility water requirement E
It is modeled.
Step 5：Using the effective soil moisture W1 of soil, the wheat of the raster symbol-base device in ModelBuilder respectively to wheat
Effectiv precipitation W2 and yield of groundwater W3 in the time of infertility are modeled, while to the natural output in the wheat time of infertility
W is modeled.
Step 6：It is complete with reference to the wheat time of infertility water requirement E models and wheat being had built up in step 4 and step 5
The natural output W models of breeding time, set up the natural moisture deficiency rates G models of wheat growing stage.
Beneficial effects of the present invention：The inventive method, which rationalizes the formula in natural moisture deficiency rates model, decomposes, will
The mathematical modeling is combined with GIS, and is modeled respectively, can be automatically performed after finally constituting complete GIS models, Boot Model
Complicated dimensioning process.Complicated mathematical modeling is changed into conveniently GIS raster symbol-bases by this method, is easy to reader
Understand whole model, the automating of implementation model calculating process, integration, spatial visualization, while model logic relation is clear,
It is easy to data modification to safeguard.
Brief description of the drawings
Fig. 1：Study area's situation map；
Fig. 2：Initial data interpolation result figure；
Fig. 3：In T on saturation water othermohygrometer relation curveaThe tangent slope Δ modeling figure at place；
Fig. 4：Psychrometer constant γ modeling figures；
Fig. 5：The modeling figure of 2m eminences wind velocity U 2；
Fig. 6：Saturation vapour pressure es modeling figure；
Fig. 7：Actual vapour pressure ea modeling figure；
Fig. 8：Net radiation Rn modeling figure；
Fig. 9：Potential evapotranspiration ET0 modeling figure；
Figure 10：Time of infertility water requirement E modeling figure；
Figure 11：The natural output W in time of infertility modeling figure；
Figure 12：The natural moisture deficiency rates G of wheat growing stage modeling figure；
Figure 13：Suiyang District on October 6th, 2013 and Wheat Drought on October 7th, 2013 assess figure；
Figure 14：Method flow diagram.
Embodiment
The invention will be further described with reference to the accompanying drawings and detailed description.
As shown in figure 1, choosing the 6 days October in 2013 and on October 7th, 2013 of 7 websites in Henan Province Shangqiu City Suiyang District
Meteorological site data (being changed by A files) and soil moisture content form.Meteorological site data include daily maximum temperature, day minimum gas
Temperature, daily mean temperature, average relative humidity, sunshine time, mean wind speed and precipitation.Table 1 below is website Basic Information Table,
Table 2 is website meteorological element table.
Table 1
Table 2
(1) as shown in Fig. 2 point data is processed as into the continuous space of numerical value using the spatial interpolation methods of ArcGIS softwares
Raster data.
(2) as shown in Fig. 3-Fig. 9, wheat potential evapotranspiration ET0 is modeled：Wheat potential evapotranspiration ET0 is one
Complicated calculation formula, in order to make it easy to understand, first being modeled one by one to the variable in formula, is finally modeled to ET0 again.
(3) as shown in Figure 10, wheat time of infertility water requirement E is built according to formula and the above-mentioned model having built up
Mould.
(4) as shown in figure 11, the natural output W in the wheat time of infertility is entered using the ModelBuilder in ArcGIS
Row modeling.
(5) as shown in figure 12, according to the natural water supply in the model for the time of infertility water requirement E having built up and the time of infertility
W model is measured, complete natural moisture deficiency rates G model is set up.
(6) as shown in figure 13, completion wheat Natural water deficit drought assessment meter after data path, Boot Model is set
Calculate, and drought assessment result figure is obtained using function is cut.
Such as the GIS modeling method flow charts that Figure 14 is wheat Natural water deficit drought assessment model of the present invention.
It should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention,
Some improvements and modifications can also be made, these improvements and modifications also should be regarded as protection scope of the present invention.In the present embodiment not
Clear and definite each part can use prior art to be realized.
Claims (1)
1. a kind of GIS modeling methods of wheat Natural water deficit drought assessment model, it is characterised in that：Comprise the following steps：
Step one：Natural moisture deficiency rates model is divided into 2 parts first：The water requirement E and wheat in the wheat time of infertility are complete
The natural output W of breeding time；It it is again 8 by ET0 points of wheat potential evapotranspiration in the water requirement E formula in the wheat time of infertility
Part；
Step 2：Choose and study the meteorological site data of area for a period of time and soil moisture content form, in ModelBuilder modelings
Point data is processed as by the continuous space lattice data of numerical value using inverse distance weighted interpolation instrument on platform；
Step 3：Analysis is overlapped to the variable in wheat potential evapotranspiration ET0 using raster symbol-base device, modeled respectively, is wrapped
Include on saturation water othermohygrometer relation curve in TaThe tangent slope Δ at place, wet table constant γ, soil heat flux G, 2m eminence wind
Fast U2, saturation vapour pressure es, daily mean temperature Ta, actual vapour pressure ea and net radiation RnModeling；
Step 4：According to the model being had built up in step 3, also with the raster symbol-base device in ModelBuilder to small
Wheat potential evapotranspiration ET0 is modeled, and wheat time of infertility water requirement E is carried out using wheat potential evapotranspiration ET0 models
Modeling；
Step 5：The effective soil moisture W1 of soil, the wheat of wheat are given birth to entirely respectively using the raster symbol-base device in ModelBuilder
The effectiv precipitation W2 and yield of groundwater W3 educated in the phase is modeled, while entering to the natural output W in the wheat time of infertility
Row modeling；
Step 6：Given birth to entirely with reference to the wheat time of infertility water requirement E models and wheat being had built up in step 4 and step 5
The natural output W models of phase, set up the natural moisture deficiency rates G models of wheat growing stage.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107873435A (en) * | 2017-11-09 | 2018-04-06 | 河北省农林科学院滨海农业研究所 | Utilize the multiple green method than Rapid identification drought resistance of wheat of blade |
| CN110533346A (en) * | 2019-09-09 | 2019-12-03 | 中国科学院地理科学与资源研究所 | A kind of Water resources security appraisal procedure of grain-production |
| CN113533695A (en) * | 2021-07-26 | 2021-10-22 | 山东省农业机械科学研究院 | Farmland soil moisture content data estimation method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103645295A (en) * | 2013-12-03 | 2014-03-19 | 中国科学院遥感与数字地球研究所 | Multilayer soil moisture simulation method and multilayer soil moisture simulation system |
| CN104597526A (en) * | 2014-12-30 | 2015-05-06 | 中国南方电网有限责任公司 | System and method for meteorological drought monitoring and early warning based on power grid geographical information system |
-
2017
- 2017-05-05 CN CN201710311221.4A patent/CN107145666A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103645295A (en) * | 2013-12-03 | 2014-03-19 | 中国科学院遥感与数字地球研究所 | Multilayer soil moisture simulation method and multilayer soil moisture simulation system |
| CN104597526A (en) * | 2014-12-30 | 2015-05-06 | 中国南方电网有限责任公司 | System and method for meteorological drought monitoring and early warning based on power grid geographical information system |
Non-Patent Citations (2)
| Title |
|---|
| 李楠: "聊城地区冬小麦干旱灾害评估", 《中国优秀硕士学位论文全文数据库农业科技辑（月刊）》 * |
| 王红雷: "基于3S技术的干旱区水土资源高效利用研究", 《中国博士学位论文全文数据库农业科技辑（月刊）》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107873435A (en) * | 2017-11-09 | 2018-04-06 | 河北省农林科学院滨海农业研究所 | Utilize the multiple green method than Rapid identification drought resistance of wheat of blade |
| CN110533346A (en) * | 2019-09-09 | 2019-12-03 | 中国科学院地理科学与资源研究所 | A kind of Water resources security appraisal procedure of grain-production |
| CN113533695A (en) * | 2021-07-26 | 2021-10-22 | 山东省农业机械科学研究院 | Farmland soil moisture content data estimation method and system |
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