CN112966960A - Multi-threshold drought comprehensive risk evaluation method based on soil humidity - Google Patents

Multi-threshold drought comprehensive risk evaluation method based on soil humidity Download PDF

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CN112966960A
CN112966960A CN202110307262.2A CN202110307262A CN112966960A CN 112966960 A CN112966960 A CN 112966960A CN 202110307262 A CN202110307262 A CN 202110307262A CN 112966960 A CN112966960 A CN 112966960A
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权全
杨思敏
李平治
许美娇
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Abstract

The invention discloses a soil humidity-based multi-threshold drought comprehensive risk evaluation method, which comprises the following steps of: carrying out meshing division on a research area in advance and constructing a VIC model to simulate to obtain soil humidity of different meshes; and extracting the soil texture classification map of the research area according to the mask and rasterizing the soil texture classification map so as to determine the soil corresponding to each gridA type; field water capacity F according to different soil propertiescAnd wilting water content WpDetermining a grid soil moisture threshold value; determining drought indexes and grades; and (4) evaluating the drought comprehensive risk according to a catastrophe system theory. The method realizes drought risk evaluation by adopting the gridding-based soil humidity multi-threshold drought index, not only accurately realizes the drought risk occurrence range, but also has wider applicability by adopting the multi-threshold drought index.

Description

Multi-threshold drought comprehensive risk evaluation method based on soil humidity
Technical Field
The invention relates to the technical field of drought risk assessment, in particular to a soil humidity-based multi-threshold drought comprehensive risk assessment method.
Background
Under the global warming background, a plurality of regions have long-term serious drought disasters, huge losses are caused to social economy, and soil moisture plays a role in regulating plant growth in different seasons of vegetation growth. The water stress degree of vegetation is closely related to the soil water content, and the drought stress and water demand of plants need to be estimated accurately by the water content so as to provide drought early warning and reduce the crop production loss.
The sources of water are different, and the monitoring value of the precipitation amount cannot be obtained if no precipitation exists in a certain period, but no drought occurs if the area is irrigated every day, so that the drought index is calculated, and the accuracy needs to be considered. But the soil water does not take into account from which the water came, which expresses the change in soil water content at that moment. Soil moisture is intermediate between meteorological and hydrographic drought and may represent an agricultural drought. The use of soil moisture may better characterize the occurrence of drought in the short term compared to insufficient precipitation over a period of time.
Soil moisture content is constantly changing, including thousands. The soil with different properties has different requirements on soil moisture, and the field water holding capacity and the wilting water content of the soil also have different requirements. At present, the evaluation accuracy of drought in a research area is not high by adopting a single threshold drought index, and the drought research is mostly carried out by dividing administrative areas, so that the risk evaluation in a small-scale area is limited, and the drought risk evaluation result is incomplete. Therefore, a multi-threshold drought comprehensive risk evaluation method based on soil humidity is urgently needed and becomes a problem concerned by researchers.
Disclosure of Invention
The method realizes drought risk evaluation by adopting the soil humidity multi-threshold drought index based on networking, so that the drought risk occurrence range is accurate, and the practicability is wider by adopting the multi-threshold drought index.
In order to achieve the purpose, the invention provides the following scheme:
s1, selecting a research area, carrying out grid division on the research area, and constructing a VIC model for simulation to obtain soil humidity W in different grids;
s2, extracting the soil texture classification map of the research area, performing rasterization processing on the soil texture classification map, determining the soil type and different types of soil moisture threshold values corresponding to each grid, and performing quantitative analysis on plant water demand to obtain the field water capacity F of the soil property corresponding to each gridcAnd wilting water content Wp；
S3, mixing the soil humidity W of each grid with the wilting water content W corresponding to the gridpThe ratio of the soil drought indexes is used as a drought index, and the soil drought degree is graded according to the drought index;
and S4, performing drought comprehensive risk evaluation according to the catastrophe system theory and by combining the comprehensive effects of the drought risk, the vulnerability and the sensitivity factors in the research area.
Preferably, in step S1, the research area is divided into grids of the same size by the Arcgis application, and the daily soil moisture content of each grid is obtained through VIC model simulation.
Preferably, three layers of soil are used for simulation in the VIC model, top and bottom layers respectively.
Preferably, in step S2, the research area is mask-extracted by a soil geological classification map provided by the world food and agriculture organization, so as to obtain a soil geological classification map of the research area, and determine a corresponding soil type in each grid.
Preferably, in the step S2, the soil humidity W of each grid and the wilting moisture content W corresponding to the grid are determinedpThe ratio of (A) is used as the drought index, and the drought degree is divided when W is equal toWpIt is the critical point for drought to occur.
Preferably, in step S4, the drought risk, the vulnerability and the sensitivity factor in the research area are disaster-causing factor risk characteristic information, disaster-bearing body vulnerability characteristic information and disaster-pregnant environment sensitivity characteristic information, respectively.
Preferably, the disaster-causing factor risk characteristic information includes: drought frequency and drought intensity, the risk of disaster-causing factors in each grid, HI, is expressed as:
HI＝aF+(1-a)I
wherein F is a disaster frequency index; i is a disaster intensity index; a is a weighting factor between 0 and 1, and a is 0.5.
Preferably, the vulnerability characteristic information of the disaster object includes: and the GDP index and the normalized vegetation index NDVI, the vulnerability VI of the disaster-bearing body in each grid is expressed as:
VI＝βG+(1-β)N
wherein G is a GDP index; n is the normalized vegetation index NDVI; beta is 0.5.
Preferably, by combining the topographic features and the climatic features of the research area and taking the influence of the land utilization condition and the human activities as the characteristic information of the pregnancy disaster environment sensitivity, the pregnancy disaster environment sensitivity EI is expressed as:
EI＝γL+(1-γ)P
wherein L is the LUCC land use condition; p is population density; gamma is 0.5.
The invention has the beneficial effects that:
(1) compared with the prior art, the method has the advantages that the drought disaster risk assessment is carried out on the spatial gridding of the research area, and the drought occurrence condition can be more accurately shown compared with the site-based drought monitoring; the drought risk of each research area is evaluated by combining the multi-threshold drought index with the disaster risk model, the drought risk evaluation result is comprehensive, and the multi-threshold drought index can be more widely used in different areas.
(2) The method realizes drought risk evaluation by adopting the gridding-based soil humidity multi-threshold drought index, not only accurately realizes the drought risk occurrence range, but also has wider applicability by adopting the multi-threshold drought index.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a grid of selected regions in an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in FIG. 1, the invention provides a soil humidity-based multi-threshold drought comprehensive risk evaluation method, which comprises the following steps:
s1, selecting a research area, carrying out grid division on the research area, and constructing a VIC model for simulation to obtain soil humidity W in different grids;
this example selects inner Mongolia as the study area, divides inner Mongolia into 515 grids of the same size and resolution of 50 × 50km by Arcgis, as shown in FIG. 2, and constructs VIC model of version 4.1.2 g.
The VIC model can simultaneously simulate the energy balance and the water balance in the water circulation process, and makes up for the deficiency of the traditional hydrological model in describing the energy process. In practical application, the VIC model can only calculate water balance, output runoff and evaporation on each grid, and then be coupled with the flow converging model to convert the runoff on the grids into a flow process of the outlet section of the drainage basin. As a distributed hydrological model, the VIC model has some significant characteristics, such as for a water circulation process, a water balance and energy balance process is considered; meanwhile, the snow melting process and the soil freezing and thawing process are considered; canopy evaporation, leaf cluster transpiration and bare soil evaporation are also considered; and the parameterization process of two runoff components of surface runoff and base runoff and the nonlinear problem of base runoff water withdrawal. For the secondary grid, the unevenness of the surface vegetation type, the unevenness of the spatial distribution of the soil water storage capacity and the unevenness of the spatial distribution of precipitation are respectively considered.
In this embodiment, the driver files selected in the VIC model include the following 5 types: the system comprises a meteorological driving file, a soil parameter file, a vegetation library file, a vegetation parameter file and a global control file. The vegetation parameter file selects land cover type data with 1km resolution ratio all over the world published by Maryland university; the soil parameter classification refers to a soil texture classification map provided by FAO world grain and agriculture organization; the weather driving data is a day-by-day weather data set provided by a Chinese weather data network.
And (4) simulating to obtain the day-by-day soil water content of each grid in the research area in 1991-2017. Three layers of soil are used in the simulation, and the depth of the top layer is 0.1 m; the depth of the upper layer is between 0.1 and 0.5 m; the lower layer is between 0.5 and 2 m. The water movement between the soil layers is mainly gravity water. The formula of the change of the water content of each layer of soil is as follows:
Figure BDA0002988006310000061
Figure BDA0002988006310000062
Figure BDA0002988006310000063
wherein, theta1Is the volumetric water content of the top soil, theta2Is the volume water content of the upper soil layer, theta3The volume water content of the lower soil layer; z1The depth of the top soil from the surface, Z2The depth of the upper soil from the surface, Z3The volume water content of the lower soil layer; k (theta) is hydraulic conductivity; d (theta) is hydraulic diffusivity; p is precipitation; r is surface runoff; e is evaporation; qbIs a base stream. Evapotranspiration was calculated using the P-M formula.
The water movement between the soil layers is mainly gravity water. The surface soil water cannot represent drought conditions, such as sudden rains, can solve the local drought conditions to a certain extent, but the drought conditions can be aggravated along with evaporation, the root systems of the vegetations are generally mostly positioned in the upper soil, the water content of the upper soil is relatively stable, and therefore the upper soil water (0.1-0.5m) is selected as a main research object.
S2, extracting the soil texture classification map of the research area, performing rasterization processing on the soil texture classification map, determining the soil type and different types of soil moisture threshold value corresponding to each grid, and performing quantitative analysis on plant water demand to obtain the highest soil moisture F which can be stably maintained by the soil corresponding to each gridcAnd the water content W of the soil when the plants begin to wither permanentlyp；
When W exceeds FcWhen the water-retaining agent is used, redundant water can permeate, and the water-retaining agent can permeate into underground water under the action of gravity without being interfered by a water-impermeable layer. I.e. saturated, water holding, while the soil is in a wet state.
When W is in FcAnd WpIn the meantime, the soil humidity is proper, the soil moisture can be fully absorbed by the roots of the plants, which is called as effective soil moisture, and at the moment, the soil is in a normal state;
when W is at WpWhen the water content is insufficient, the plant growth is retarded, withering begins to occur, and the life growth of crops cannot be recovered even if a large amount of rainfall exists, at the moment, soilDrought is caused by soil;
so whether W is lower than WpIs the key to drought development.
And (4) performing mask extraction on the region of the research area by using a soil texture classification map provided by FAO world grain and agriculture organization, and determining the corresponding soil type in each grid. Quantitative analysis is carried out on the water demand of the plants, and F of the soil property corresponding to each grid is foundcAnd Wp。
At WpThe water is absorbed by the soil tightly, and the vegetation is difficult to absorb the water from the soil, thereby influencing the growth and development of crops. With WpAs a limit, the threshold value of drought of the vegetation at different soil moisture is determined.
TABLE 1 reference of different soil properties of inner MongoliacAnd WpThe requirements of (1).
TABLE 1
Figure BDA0002988006310000081
S3, mixing the soil humidity W of each grid with the wilting water content W corresponding to the gridpThe ratio of the soil drought indexes is used as a drought index, and the soil drought degree is graded according to the drought index;
the drought of the soil has a critical threshold value, when the drought degree does not exceed the threshold value, the influence degree of the vegetation physiological process is small, and the influence is not caused after the normal water supply is recovered. However, when the drought degree exceeds the threshold value, crops are permanently damaged, and even if normal water supply is recovered, the physiological indexes cannot be recovered.
In order to further determine the drought threshold indexes of different soil types, the W of each grid and the W corresponding to the grid are usedpThe ratio of (A) to (B) is used as a drought index, and then the drought degree is divided by taking the proportion as a grade. When W is equal to WpIt is the critical point for drought to occur. Thus, the occurrence and grade of drought for each grid were analyzed as shown in Table 2 below.
TABLE 2
Figure BDA0002988006310000082
Figure BDA0002988006310000091
And S4, performing drought comprehensive risk evaluation according to the catastrophe system theory and by combining the comprehensive effects of the drought risk, the vulnerability and the sensitivity factors in the research area.
The disaster-causing factor risk characteristic information of the selected region drought comprises:
risk of disaster-causing factor: drought frequency and drought intensity are considered as risk indicators.
Disaster-causing factor risk hi (hazard index) for each grid, expressed as:
HI＝aF+(1-a)I
wherein F is a disaster frequency index; i is a disaster intensity index; a is a weighting factor between 0 and 1, and a is 0.5.
The vulnerability characteristic information of disaster-bearing bodies of the selected regional drought comprises:
vulnerability of disaster-bearing body: the GDP index and the NDVI normalized vegetation index are taken into consideration as vulnerability indexes.
Disaster-bearing vulnerability vi (vulnerability index) of each grid is expressed as:
VI＝βG+(1-β)N
wherein G is a GDP index; n is the NDVI normalized vegetation index; beta is 0.5.
The method for selecting the pregnant disaster environment sensitivity characteristic information of the drought disaster in the selected area comprises the following steps:
pregnant disaster environment sensitivity: the landform and the climatic characteristics of the research area are considered, and the influence of the land utilization condition and the human activities is used as the index of the environmental sensitivity of the pregnant disaster.
The pregnancy environmental sensitivity ei (exposure index) for each grid is expressed as:
EI＝γL+(1-γ)P
wherein L is the LUCC land use condition; p is population density; gamma is 0.5.
The comprehensive evaluation drought risk characteristic information of the drought disaster of the selected area comprises the following steps:
according to the disaster department system theory, 3 subsystems of disaster-causing factors, disaster-bearing bodies and pregnant disaster environments are used, and the comprehensive effect of drought danger, vulnerability and sensitivity factors in a research area is considered. And comprehensively evaluating the drought risk DRI and determining the risk grade:
DRI＝HI+VI+EI
and constructing a drought comprehensive risk evaluation model based on multiple thresholds of soil humidity, totally reflecting the drought comprehensive risk level of the research area, and providing a basis for disaster risk management and drought-resisting and disaster-reducing actions of the research area.
The method realizes drought risk evaluation by adopting the gridding-based soil humidity multi-threshold drought index, not only accurately realizes the drought risk occurrence range, but also has wider applicability by adopting the multi-threshold drought index.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.

Claims (9)

1. A soil humidity-based multi-threshold drought comprehensive risk evaluation method is characterized by comprising the following steps:
s1, selecting a research area, carrying out grid division on the research area, and constructing a VIC model for simulation to obtain soil humidity W in different grids;
s2, extracting the soil texture classification map of the research area, performing rasterization processing on the soil texture classification map, determining the soil type and different types of soil moisture threshold values corresponding to each grid, and performing quantitative analysis on plant water demand to obtain the field water capacity F of the soil property corresponding to each gridcAnd wilting water content Wp；
S3, adjusting the soil humidity of each gridW and withering water content W corresponding to the gridspThe ratio of the soil drought indexes is used as a drought index, and the soil drought degree is graded according to the drought index;
and S4, performing drought comprehensive risk evaluation according to the catastrophe system theory and by combining the comprehensive effects of the drought risk, the vulnerability and the sensitivity factors in the research area.
2. The soil humidity-based multi-threshold drought integrated risk assessment method according to claim 1, wherein in step S1, the research area is divided into grids with the same size through Arcgis application, and the daily soil water content of each grid is obtained through VIC model simulation.
3. The soil moisture-based multi-threshold drought integrated risk assessment method according to claim 2, wherein three layers of soil are used for simulation in the VIC model, namely a top layer, an upper layer and a lower layer.
4. The soil humidity-based multi-threshold drought integrated risk assessment method according to claim 1, wherein in step S2, the research area is mask-extracted with a soil geological classification map provided by the world grain and agriculture organization, so as to obtain a soil texture classification map of the research area, and determine the corresponding soil type in each grid.
5. The soil humidity-based multi-threshold drought comprehensive risk assessment method according to claim 1, wherein in step S2, the soil humidity W of each grid and the wilting water content W corresponding to the grid are determinedpThe ratio of (A) is used as the drought index, and the drought degree is divided when W is WpIt is the critical point for drought to occur.
6. The soil humidity-based multi-threshold drought comprehensive risk assessment method according to claim 1, wherein in step S4, the drought risk, vulnerability and susceptibility factors in the research area are disaster-causing factor risk characteristic information, disaster-bearing body vulnerability characteristic information and disaster-pregnant environment susceptibility characteristic information, respectively.
7. The soil humidity-based multi-threshold drought comprehensive risk assessment method according to claim 6, wherein the disaster-causing factor risk characteristic information comprises: drought frequency and drought intensity, the risk of disaster-causing factors in each grid, HI, is expressed as:
HI＝aF+(1-a)I
wherein F is a disaster frequency index; i is a disaster intensity index; a is a weighting factor between 0 and 1, and a is 0.5.
8. The soil humidity-based multi-threshold drought comprehensive risk assessment method according to claim 6, wherein the vulnerability characteristic information of disaster-bearing bodies comprises: and the GDP index and the normalized vegetation index NDVI, the vulnerability VI of the disaster-bearing body in each grid is expressed as:
VI＝βG+(1-β)N
wherein G is a GDP index; n is the normalized vegetation index NDVI; beta is 0.5.
9. The soil humidity-based multi-threshold drought integrated risk assessment method according to claim 6, wherein the landform and climate characteristics of the research area are combined, and the influence of the land utilization and human activities is used as the disaster environment susceptibility characteristic information, so that the disaster environment susceptibility EI is expressed as:
EI＝γL+(1-γ)P
wherein L is the LUCC land use condition; p is population density; gamma is 0.5.
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Publication number Priority date Publication date Assignee Title
CN113516418A (en) * 2021-08-27 2021-10-19 中国农业科学院农业环境与可持续发展研究所 Apple planting area drought disaster risk assessment method
CN113516418B (en) * 2021-08-27 2024-04-26 中国农业科学院农业环境与可持续发展研究所 Drought disaster risk assessment method for apple planting area
CN113742947A (en) * 2021-10-12 2021-12-03 宁夏大学 Method for determining field planting water threshold of warm-zone desert grassland plant seedlings
CN113742947B (en) * 2021-10-12 2024-05-03 宁夏大学 Method for determining planting water threshold of young plants in temperate desert grassland

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