CN113850465A - Hydrology arid monitoring system in no data area - Google Patents
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Abstract
The invention discloses a hydrological drought monitoring system for a data-free area, and belongs to the technical field of drought monitoring. It includes: the data simulation module is used for calculating simulation data according to the remote sensing data, the remote sensing data comprise remote sensing precipitation data and remote sensing soil water content data, and the simulation data comprise natural runoff data, underground water storage data and soil water content data; the comprehensive drought index construction module is used for constructing a drought index according to the simulation data, wherein the drought index comprises a standardized runoff index, an underground water storage amount equal percentage and a soil water stress index, and the comprehensive drought index is constructed according to the weight of each drought index in the comprehensive drought index; and the drought identification and grading module is used for determining the drought grade according to the comprehensive drought index and the grading standard of the comprehensive drought index. The method can accurately identify the whole and local hydrological drought conditions in the research area and grade the severity of the drought.
Description
Technical Field
The invention belongs to the technical field of drought monitoring, and particularly relates to a hydrological drought monitoring system for a data-free area.
Background
Drought is one of the most common and most influential climate disasters in China. The frequency and intensity of drought caused by global warming has been on a significantly increasing trend since the 70's of the 20 th century. Global drought risk in the 21 st century will be further increased, seriously threatening food safety and social stability in China, and becoming one of important factors restricting sustainable development of socioeconomic. Drought traditionally refers to a slowly developing natural phenomenon that often takes months or even longer to reach the maximum values in intensity and range, and is thus clearly perceived by people. However, recent studies have found that short term drought (lasting days or weeks) due to abnormal atmospheric circulation characteristics and changes in underlying surface conditions is increasing. This rapid short-term drought in the united states, east asia, europe and south africa, results in large areas of crop loss, mortality of farm animals and high direct economic losses. Analysis of causes of short-term drought and monitoring and forecasting have become a common concern in the world at present.
Research has shown that in future china, especially in the south, the risk of short-term drought may increase significantly, and by the middle of this century, the risk of short-term drought in some southern wet provinces will increase by 40%. The global climate warming leads to the increase of the variability of a plurality of hydrological meteorological elements, the drought is easier to appear, meanwhile, the increase of greenhouse gases changes the intensity of atmospheric external radiation, on one hand, more high-temperature heat waves are brought, the evaporation and the dissipation of moisture in a humid area are accelerated, on the other hand, the distribution of clouds is also changed by the enhancement of the external radiation, seasonal rainfall becomes more unstable, and then the traditional regional rainfall distribution is changed, therefore, the short-term drought is easier to appear in the humid and semi-humid area.
With the increase of the strategy of the economic area of the strait west bank, the strategic position and the function of the Pu field are increasingly prominent. The coastal region is an important port open to the outside, has an important strategic position, is more developed in economy, has less per-capita water resources and has high water consumption ratio. The water resource distribution is not matched with the population and economic development, the coastal economy develops quickly, the water resource is relatively tense, along with the rapid growth of the coastal social economy, particularly the meizhou bay and other economy enter a high-speed development stage, the production and living water is continuously increased, the problem of water resource shortage is increasingly prominent, and the influence of the coastal region drought risk on the development of the economic society is larger and larger. Hydrologic drought is not a water shortage phenomenon caused by the shortage of rainfall, and is closely related to the development and utilization activities of human water resources. For a non-material area like a coastal area of a Pu-Tian, how to jointly utilize ground observation data, multi-source remote sensing data and a hydrological model to better monitor hydrological drought, evaluate the potential influence of the hydrological drought on various aspects of society and economy, reduce a water resource supply and demand gap by proper water management measures in combination with the characteristics of a research area on the basis, reduce the influence of the hydrological drought, and provide a technical approach for solving the problem that the similar Fujian coastal area is short of water resources and unmatched with economic development.
Disclosure of Invention
The technical problem to be solved is as follows: in order to solve the technical problems, the invention provides a hydrological drought monitoring system for a data-free area, which can accurately identify the hydrological drought conditions of the whole and the local area of research and grade the severity of drought.
The technical scheme is as follows: a hydrological drought monitoring system for a data-free area, the monitoring system comprising:
the data simulation module is used for calculating simulation data according to the remote sensing data, the remote sensing data comprise remote sensing precipitation data and remote sensing soil water content data, and the simulation data comprise natural runoff data, underground water storage data and soil water content data;
the comprehensive drought index construction module is used for constructing a drought index according to simulation data, wherein the drought index comprises a Standardized Runoff Index (SRI) and an underground water storage amount-average percentage (I)wtAnd soil moisture stress index KswConstructing a comprehensive drought index CWRI according to the weight of each drought index in the comprehensive drought index;
and the drought identification and grading module is used for determining the drought grade according to the comprehensive drought index CWRI and the grading standard of the comprehensive drought index.
Preferably, the natural runoff data is obtained through remote sensing precipitation data processing and comprises a representative research period natural runoff and a contemporaneous many-year average runoff;
the objective function of the natural runoff for the study period is as follows:
Yr＝aXp+b
wherein XpTo represent contemporaneous rainfall at a hydrological site, YrTo represent contemporaneous runoff of a hydrological site,
for contemporaneous surface rainfall in the study area,
the diameter and flow of the same period of the study area are m3(ii) a The P values of the relational expressions all satisfy P>0.5 precision requirement, and increasing the times of the polynomial for the relational expression which does not meet the precision requirement until the precision requirement is met;
the method for calculating the mean runoff of the years in the same period comprises the following steps:
wherein Q isbMeans representing contemporaneous perennial mean runoff of the study area; qaRepresenting the runoff volume representing a hydrological site; fbRepresents the area of the region of interest; faRepresenting an area representing a hydrological site; pbIndicating the areal rainfall of the study area; paRepresenting the amount of rain that represents a hydrological site.
Preferably, the groundwater volume data is obtained by remote sensing precipitation data processing, and includes a research period groundwater volume and a contemporaneous multi-year average groundwater volume, and the objective function of the research period groundwater volume is as follows:
Yw＝cXp+d
wherein, XrTo represent contemporaneous rainfall at a hydrological site, YwTo represent the amount of groundwater accumulated in the administrative area where the hydrological station is located,
for contemporaneous surface rainfall in the study area,
the unit of the same-period underground water storage amount of the research area is m3；
The mean underground water storage of the same period is the mean underground water storage of the research period.
Preferably, the soil water content data is obtained by remote sensing soil water content data processing, and the data comprises the soil water content in the research period and the average soil water content in the same period for many years.
Preferably, the normalized runoff index SRI is constructed from natural runoff volume data and is calculated as follows:
assuming that the runoff x for a certain time period satisfies the T-distribution probability density function f (x) is:
in the formula: gamma and beta are shape and dimension parameters respectively,
x is greater than 0, gamma is greater than 0, beta is greater than 0, gamma and beta are calculated by adopting a maximum likelihood method, and the cumulative probability of the runoff quantity X in a certain time scale is as follows:
the T distribution probability is normalized normally to obtain:
wherein, when F>At 0.5, S ═ 1; when F is less than or equal to 0.5, S is-1, wherein c0＝2.515517，c1＝0.802853，c2＝0.010328，d1＝1.432788，d2＝0.189269，d3＝0.001308。
Preferably, the groundwater flow is equal to the average percentage IwtThe underground water storage capacity data is constructed, and the calculation method is as follows:
wherein WTD represents underground water storage during research period, WTD0Representing the mean groundwater mass for years in the same period.
Preferably, the soil water stress index KswThe soil water content data is constructed, and the calculation method is as follows:
wherein θ represents the soil moisture of the root zone; thetawpDenotes the wilting water content, thetacrRepresents the critical water content; thetafcRepresenting the field water capacity; n is an empirical constant, and the value of n varies with the type of the plant and the resistance of the plant to drought stress, and ranges from 1 to 2.
Preferably, the calculation method of the comprehensive drought index CWRI is as follows:
CWRI＝a*SRI+b*(-Ksw)+c*Iwt
wherein a, b and c respectively represent the weight of each drought index in the comprehensive drought index, a is the ratio of the mean runoff and the total water resource amount of the same year, b is the ratio of the mean soil water content and the total water resource amount of the same year, and c is the ratio of the mean underground water storage amount and the total water resource amount of the same year; the total water resource amount is the sum of the mean runoff of the years in the same period, the mean soil water content of the years in the same period and the mean underground water storage amount of the years in the same period.
Preferably, the drought grade division standard of the comprehensive drought index is determined by the drought grade division standard of each drought index, and the calculation method comprises the following steps:
wherein the drought levels include no drought, light drought, moderate drought, heavy drought, and extra drought, SRIGrade of drought、
Iwt drought gradeRespectively representing threshold value intervals corresponding to the drought grade division standards of each drought index, wherein a, b and c respectively represent the weight of each drought index in the comprehensive drought index, a is the ratio of the mean runoff and the total water resource amount of the same year, b is the ratio of the mean soil water content and the total water resource amount of the same year, and c is the ratio of the mean underground water storage amount and the total water resource amount of the same year; the total water resource amount is the sum of the mean runoff of the years in the same period, the mean soil water content of the years in the same period and the mean underground water storage amount of the years in the same period.
Preferably, the drought grade division standard of each drought index is as follows:
has the advantages that: the method can monitor the hydrological drought aiming at the non-material areas by jointly utilizing ground observation data, multi-source remote sensing data and a hydrological model, accurately identify the hydrological drought conditions of the whole and the local parts of a research area, and grade the severity of the drought; therefore, the potential influence of the hydrologic drought on all aspects of social economy can be evaluated, and on the basis, the water resource supply and demand gap is reduced by combining the characteristics of the research region through proper water management measures, the influence of the hydrologic drought is reduced, and the problem that the water resource shortage of the research region is not matched with the economic development is solved.
Drawings
FIG. 1 is a flow chart of a hydrological drought monitoring system in a data-free area;
FIG. 2 is a graph showing drought levels in regions of a coastal zone of Putian in 2011.
Detailed Description
The invention is further described below with reference to the accompanying drawings and specific embodiments.
Example 1
As shown in fig. 1, a hydrological drought monitoring system for a data-free area, the monitoring system comprises:
the data simulation module is used for calculating simulation data according to the remote sensing data, the remote sensing data comprise remote sensing precipitation data and remote sensing soil water content data, and the simulation data comprise natural runoff data, underground water storage data and soil water content data;
the comprehensive drought index construction module is used for constructing a drought index according to simulation data, wherein the drought index comprises a Standardized Runoff Index (SRI) and an underground water storage amount-average percentage (I)wtAnd soil moisture stress index KswConstructing a comprehensive drought index CWRI according to the weight of each drought index in the comprehensive drought index;
and the drought identification and grading module is used for determining the drought grade according to the comprehensive drought index and the grading standard of the comprehensive drought index.
Since the identification of drought involves the determination of a relationship and the cumulative probability density of runoff, the time series of the various variables input should be as long as possible.
Taking the coastal slices in Putian city as an example, the method specifically comprises the following steps:
1. the data simulation module construction process is as follows:
(1) calculating the runoff of each month in Putian city:
the objective function for simulating the runoff in each month is as follows:
Yr＝aXp+b
wherein XpTo represent contemporaneous rainfall at a hydrological site, YrTo represent contemporaneous runoff of a hydrological site,
for contemporaneous surface rainfall (input remote sensing precipitation data) of the study area,
the diameter and flow of the same period of the study area are m3. The value of P in the above relation is to satisfy the accuracy requirement (P)>0.5) for unsatisfied orders of the polynomial to be increased until satisfied.
Table 1 is simulated from the contemporaneous data of measured rainfall and measured runoff at a hydrological site located upstream of the magnoliavine stream area in the Pu field city of 2006-2016, the site is similar to the underlying surface characteristics of a research area, human activities in the controlled stream area are less, the influence of a water reservoir is less, and the measured runoff can be basically regarded as natural runoff.In each of the formulas of Table 1, P satisfies the accuracy requirement (P)>0.5, the same below), x is the same-time rainfall, y is the same-time runoff, and the unit is m3. The relation is used for runoff simulation in coastal areas without data in the Pu-Tian city, and the input rainfall is obtained through remote sensing images, so that the natural runoff can be output.
Table 1 relationship between rainfall and runoff in each month of Pu Tian
Further, the perennial average runoff rate can be calculated:
wherein Q isbRepresents the mean runoff over many years for the study area; qaRepresenting the runoff volume representing a hydrological site; fbRepresents the area of the region of interest; faRepresenting an area representing a hydrological site; pbIndicating the areal rainfall of the study area; paRepresenting the amount of rain that represents a hydrological site.
(2) Calculating underground water storage capacity of each area of the Pu Tian:
the objective function of simulating the underground water storage capacity is the same as the objective function simulation process.
Table 2 is modeled from contemporaneous data of rainfall and measured underground impoundment volume at each area in Putian 2009-2016, where x is contemporaneous rainfall in m3(ii) a y is the underground water storage capacity in hundred million m3. The relation is used for simulating the underground water storage capacity in the coastal area without data in the Pu-Tian city, and the input rainfall is obtained through remote sensing images, so that the underground water storage capacity data can be output.
Relationship between rainfall and underground water storage capacity of areas of Tapu (Table 2)
And further the average soil water storage (the average underground water storage in the research period) in the same period can be calculated.
(3) And (5) calculating the water content of the soil. The soil water content data is from a China Meteorological administration land data assimilation system (CLDAS) and has a data form of daily soil volume water content (m) of soil layers of 0-10 cm, 10-40 cm and 40-100 cm3/m3) The spatial resolution is 0.0625 ° × 0.0625 °.
2. The construction process of the integrated drought index construction module of the Pu Tian coastal zone comprises the following steps:
calculating SRI, Iwt、Ksw：
(1) The specific calculation method of the normalized runoff index SRI is as follows:
assuming that the runoff x for a certain time period satisfies the T-distribution probability density function f (x) is:
in the formula: gamma, beta are shape and scale parameters, respectively.
X is greater than 0, gamma is greater than 0, beta is greater than 0, gamma and beta can be calculated by a maximum likelihood method, and the cumulative probability of the runoff quantity X in a certain time scale is as follows:
the T distribution probability is normalized normally to obtain:
when F >0.5, S ═ 1; when F is less than or equal to 0.5, S is equal to-1, wherein C0 is equal to 2.515517, C1 is equal to 0.802853, C2 is equal to 0.010328, d1 is equal to 1.432788, d2 is equal to 0.189269, and d3 is equal to 0.001308.
(2) Underground water storage rate of grade IwtThe calculation method is as follows:
wherein WTD is the underground water storage capacity in the research period of hundred million m3；WTD0Is the average underground water storage of hundreds of millions of years in the same period3。
(3) Soil moisture stress index KswCalculated using the formula:
wherein θ is root zone soil moisture; thetawpIs withered water content, thetacrIs the critical water content; thetafcIs the field water capacity; n is an empirical constant, varies with the type of plant and its resistance to drought stress, generally between 1 and 2, and is calculated at this time to be 1.53.
(4) The method for calculating the comprehensive drought index CWRI comprises the following steps:
CWRI＝a*SRI+b*(-Ksw)+c*Iwt
wherein a represents the ratio of the average runoff and the total water resource in the same period, b represents the ratio of the average soil water content and the total water resource in the same period, and c represents the ratio of the average underground water storage capacity and the total water resource in the same period; the total water resource amount is the sum of the mean runoff of the years in the same period, the mean soil water content of the years in the same period and the mean underground water storage amount of the years in the same period.
Thereby calculating a Putian coastal sheet comprehensive drought index (CWRI)a)：
CWRIa＝0.5314SRI+0.3015(-Ksw)+0.1671Iwt
Thus, the comprehensive drought index of each area of the coastal slices of the Pu field is calculated:
the Pu Tian coastal segment mainly comprises five parts, including: meizhou island, show district, north bank, lychee district and culvert district, and the calculation formula is shown in table 3:
TABLE 3 composite drought index of Putian areas
3. The drought identification and grading module construction process is as follows:
the division standard of each drought grade of the comprehensive drought index is as follows (the weight of each drought grade of the comprehensive drought index is the same as the weight (a, b and c) of the comprehensive drought index):
wherein the drought levels include no drought, light drought, moderate drought, heavy drought, and extra drought, SRIGrade of drought、
Iwt drought gradeRespectively representing the threshold value interval of the drought grade division standard of each drought index. And according to the result calculated by the module 2, calculating the drought grade division standard of the comprehensive drought index of the coastal slices and the regions in the table 5 by referring to the drought grade division standard of each drought index in the table 4.
TABLE 4 drought Scale Standard for Each drought index
TABLE 5 drought Scale Standard for comprehensive drought indices
According to Table 5, the hydrographic drought conditions of the Japanese coastal zones and the regions can be obtained. The data obtained by remote sensing are precipitation data and soil moisture data of 2010-2016, so that drought conditions of coastal slices of 2010-2016 and various areas can be identified, and the drought grade conditions of the coastal slices of 2011 Pu fields are shown in fig. 2.
The method aims at the area without data, monitors the hydrological drought by jointly utilizing ground observation data, multi-source remote sensing data and a hydrological model, accurately identifies the integral and local hydrological drought conditions of a research area, and grades the severity of the drought; therefore, the potential influence of the hydrologic drought on all aspects of social economy can be evaluated, and on the basis, the water resource supply and demand gap is reduced by combining the characteristics of the research region through proper water management measures, the influence of the hydrologic drought is reduced, and the problem that the water resource shortage of the research region is not matched with the economic development is solved.
Claims (10)
1. A hydrological drought monitoring system for a data-free area, the monitoring system comprising:
the data simulation module is used for calculating simulation data according to the remote sensing data, the remote sensing data comprise remote sensing precipitation data and remote sensing soil water content data, and the simulation data comprise natural runoff data, underground water storage data and soil water content data;
the comprehensive drought index construction module is used for constructing a drought index according to simulation data, wherein the drought index comprises a Standardized Runoff Index (SRI) and an underground water storage amount-average percentage (I)wtAnd soil moisture stress index KswConstructing a comprehensive drought index CWRI according to the weight of each drought index in the comprehensive drought index;
and the drought identification and grading module is used for determining the drought grade according to the comprehensive drought index CWRI and the grading standard of the comprehensive drought index.
2. The hydrological drought monitoring system for dataless areas of claim 1, wherein the natural runoff data is obtained by remote sensing precipitation data processing and comprises a natural runoff representative of a research period and a contemporaneous many-year mean runoff; the objective function of the natural runoff for the study period is as follows:
Yr＝aXp+b
wherein XpTo represent contemporaneous rainfall at a hydrological site, YrTo represent contemporaneous runoff of a hydrological site,
for contemporaneous surface rainfall in the study area,
the diameter and flow of the same period of the study area are m3(ii) a The P values of the relational expressions all satisfy P>0.5 precision requirement, and increasing the times of the polynomial for the relational expression which does not meet the precision requirement until the precision requirement is met;
the method for calculating the mean runoff of the years in the same period comprises the following steps:
wherein Q isbMeans representing contemporaneous perennial mean runoff of the study area; qaRepresenting the runoff volume representing a hydrological site; fbRepresents the area of the region of interest; faRepresenting an area representing a hydrological site; pbSurface rain representing the area of investigationAn amount; paRepresenting the amount of rain that represents a hydrological site.
3. The hydrological drought monitoring system of claim 1, wherein the groundwater volume data is obtained by remote sensing precipitation data processing and includes the groundwater volume during the research period and the average groundwater volume during the same period, and the objective function of the groundwater volume during the research period is as follows:
Yw＝cXp+d
wherein, XrTo represent contemporaneous rainfall at a hydrological site, YwTo represent the amount of groundwater accumulated in the administrative area where the hydrological station is located,
for contemporaneous surface rainfall in the study area,
the unit of the same-period underground water storage amount of the research area is m3；
The mean underground water storage of the same period is the mean underground water storage of the research period.
4. The hydrological drought monitoring system for paperless areas of claim 1, wherein the soil moisture data is obtained by remote sensing soil moisture data processing, and comprises a study period soil moisture and a contemporaneous perennial average soil moisture.
5. The system of claim 1, wherein the normalized runoff index (SRI) is constructed from natural runoff data and is calculated as follows:
assuming that the runoff x for a certain time period satisfies the T-distribution probability density function f (x) is:
in the formula: gamma and beta are shape and dimension parameters respectively,
x is greater than 0, gamma is greater than 0, beta is greater than 0, gamma and beta are calculated by adopting a maximum likelihood method, and the cumulative probability of the runoff quantity X in a certain time scale is as follows:
the T distribution probability is normalized normally to obtain:
wherein, when F>At 0.5, S ═ 1; when F is less than or equal to 0.5, S is-1, wherein c0＝2.515517，c1＝0.802853，c2＝0.010328，d1＝1.432788，d2＝0.189269，d3＝0.001308。
6. The system of claim 1, wherein the groundwater drought monitoring system is characterized by the underground water storage capacity being equal to the percentage IwtThe underground water storage capacity data is constructed, and the calculation method is as follows:
wherein WTD represents underground water storage during research period, WTD0Representing the mean groundwater mass for years in the same period.
7. The system of claim 1, wherein the soil water stress index K isswThe soil water content data is constructed, and the calculation method is as follows:
wherein θ represents the soil moisture of the root zone; thetawpDenotes the wilting water content, thetacrRepresents the critical water content; thetafcRepresenting the field water capacity; n is an empirical constant, and the value of n varies with the type of the plant and the resistance of the plant to drought stress, and ranges from 1 to 2.
8. The hydrological drought monitoring system of claim 1, wherein the comprehensive drought index CWRI is calculated by the following method:
CWPI=a*SRI+b*(-Ksw)+c*Iwt
wherein a, b and c respectively represent the weight of each drought index in the comprehensive drought index, a is the ratio of the mean runoff and the total water resource amount of the same year, b is the ratio of the mean soil water content and the total water resource amount of the same year, and c is the ratio of the mean underground water storage amount and the total water resource amount of the same year; the total water resource amount is the sum of the mean runoff of the years in the same period, the mean soil water content of the years in the same period and the mean underground water storage amount of the years in the same period.
9. The hydrological drought monitoring system of claim 1, wherein the drought-ranking criteria of the composite drought index is determined by the drought-ranking criteria of each drought index, and the calculation method is as follows:
wherein the drought levels include no drought, light drought, moderate drought, heavy drought, and extra drought, SRIGrade of drought、
Respectively representing threshold value intervals corresponding to the drought grade division standards of each drought index, wherein a, b and c respectively represent the weight of each drought index in the comprehensive drought index, a is the ratio of the mean runoff and the total water resource amount of the same year, b is the ratio of the mean soil water content and the total water resource amount of the same year, and c is the ratio of the mean underground water storage amount and the total water resource amount of the same year; the total water resource amount is the sum of the mean runoff of the years in the same period, the mean soil water content of the years in the same period and the mean underground water storage amount of the years in the same period.
10. The system of claim 9, wherein the drought classification criteria for each drought index is as follows:
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