CN113850465B - Hydrologic drought monitoring system in non-data area - Google Patents

Hydrologic drought monitoring system in non-data area Download PDF

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CN113850465B
CN113850465B CN202110895931.2A CN202110895931A CN113850465B CN 113850465 B CN113850465 B CN 113850465B CN 202110895931 A CN202110895931 A CN 202110895931A CN 113850465 B CN113850465 B CN 113850465B
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许海婷
刘勇
朱永华
吕海深
丁振宙
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Hohai University HHU
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Abstract

The invention discloses a hydrologic drought monitoring system for a non-data area, and belongs to the technical field of drought monitoring. It comprises the following steps: the data simulation module is used for calculating simulation data according to remote sensing data, wherein 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 measuring distance average 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 grade division module is used for determining the drought grade according to the comprehensive drought index and the grade division standard of the comprehensive drought index. The invention can accurately identify the whole and partial hydrologic drought conditions of the research area and grade the severity of drought.

Description

Hydrologic drought monitoring system in non-data area
Technical Field
The invention belongs to the technical field of drought monitoring, and particularly relates to a hydrologic drought monitoring system for a non-data area.
Background
Drought is one of the most common and most affected climatic disasters in China. The frequency and intensity of drought caused by global warming have tended to increase significantly since the 70 s of the 20 th century. The global drought risk in the 21 st century is further increased, the grain safety and the social stability of China are seriously threatened, and the method becomes one of important factors for restricting the sustainable development of socioeconomic. Drought is traditionally a slowly evolving natural phenomenon, often taking months or even longer to reach maximum in strength and range, and is thus clearly perceived by humans. However, recent studies have found that short-term drought (duration of days or weeks) due to abnormal atmospheric flow characteristics and changes in underlying conditions is increasing. The rapid short-term drought occurs in the United states, east Asia, europe and south Africa, and causes the death of large-area crops and livestock, and the direct economic loss is high. Short-term drought cause analysis, monitoring and forecasting have become a common concern in the current world.
Research has shown that in the future china, especially in the south, the risk of short-term drought will likely increase significantly, and by the middle of this century, the short-term drought risk of some southern wet provinces will increase by 40%. Global climate warming causes the increase of the variability of numerous hydrological elements, drought is more easy to occur, meanwhile, the increase of greenhouse gases changes the intensity of external radiation of the atmosphere, on one hand, more high-temperature high waves are brought, the evaporation of moisture in a humid region is accelerated, on the other hand, the enhancement of external radiation also changes the cloud distribution, seasonal rainfall becomes more unstable, and the traditional regional rainfall distribution is changed, so that short-term drought is more easy to occur in a humid semi-humid region.
With the improvement of strait western coast economic area strategy, the strategic status and effect of the field are increasingly prominent. Coastal areas are important ports open to the outside, have very important strategic positions, are developed in economy, have less water resources per capita, and have large water consumption ratio. The water resource distribution is not matched with population and economic development, coastal economy development is faster, water resources are relatively tense, along with the rapid growth of coastal socioeconomic, especially the economic development of the Zhou Bay and the like, the water for production and living is continuously increased, the problem of water resource shortage is increasingly outstanding, and the influence of drought risks in coastal areas on the development of the economic society is increasingly greater. Hydrologic drought is not simply caused by lack of precipitation, and is closely related to human water resource development and utilization activities. For a non-data area like a Pu field coastal area, how to jointly use ground observation data, multi-source remote sensing data and a hydrologic model to better monitor hydrologic drought, evaluate potential influences of hydrologic drought on various aspects of society and economy, reduce water resource supply and demand gaps by appropriate water management measures in combination with research area characteristics on the basis, reduce the influence of hydrologic drought, be the development direction of hydrologic drought research, be the actual working requirement of drought management, and provide a technical approach for solving mismatching of water resource shortage and economic development in a coastal area like Fujian.
Disclosure of Invention
The technical problems to be solved are as follows: aiming at the technical problems, the invention provides a hydrological drought monitoring system for a non-data area, which can accurately identify the overall and local hydrological drought conditions of a research area and grade the severity of drought.
The technical scheme is as follows: a hydrologic drought monitoring system for a data-free area, said monitoring system comprising:
the data simulation module is used for calculating simulation data according to remote sensing data, wherein 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 SRI and an underground water storage measuring distance flat percentage I wt And soil moisture stress index K sw Constructing a comprehensive drought index CWRI according to the weight of each drought index in the comprehensive drought indexes;
and the drought identification and grade division module is used for determining the drought grade according to the comprehensive drought index CWRI and the grade division standard of the comprehensive drought index.
Preferably, the natural runoff amount data is obtained through remote sensing precipitation data processing, and the natural runoff amount data comprises a natural runoff amount representing a research period and an average runoff amount for the same period for a plurality of years;
the objective function of the natural runoff amount in the study period is as follows:
Y r =aX p +b
wherein X is p To represent the contemporaneous rainfall of hydrologic sites, Y r To represent the contemporaneous runoff of the hydrologic site,for the contemporaneous surface rainfall of the investigation region, < > water>For the synchronous surface runoff of the research area, the units are m 3 The method comprises the steps of carrying out a first treatment on the surface of the The P values of the relational expression all satisfy P>0.5, and for the relation which does not meet the precision requirement, increasing the degree of the polynomial until the precision requirement is met;
the method for calculating the average diameter flow of the same period for many years comprises the following steps:
wherein Q is b Representing the average runoff of the study area in the same period for years; q (Q) a Representing the runoff quantity representing the hydrologic site; f (F) b Representing the area of the investigation region; f (F) a Representing an area representing a hydrologic site; p (P) b Representing the surface rainfall of the research area; p (P) a Representing the amount of surface rain representing the hydrologic site.
Preferably, the underground water storage data is obtained through remote sensing precipitation data processing, and comprises an underground water storage in a research period and an average underground water storage in the same period for years, wherein the objective function of the underground water storage in the research period is as follows:
Y w =cX p +d
wherein X is r To represent the contemporaneous rainfall of hydrologic sites, Y w To represent the contemporaneous underground water storage of the administrative area in which the hydrological site is located,for the contemporaneous surface rainfall of the investigation region, < > water>For the contemporaneous underground water storage of the research area, the unit is m 3
The average underground water storage capacity of the same period for many years is the average value of the underground water storage capacity of the research period for many years.
Preferably, the soil moisture content data is obtained by remote sensing soil moisture content data processing, which includes study period soil moisture content and contemporaneous multi-year average soil moisture content.
Preferably, the normalized runoff index SRI is constructed from natural runoff data, and the calculation method is as follows:
assuming that the runoff amount x for a certain period of time satisfies the T distribution probability density function f (x) is:
wherein: gamma and beta are the shape and scale parameters respectively,
x >0, gamma >0, beta >0, gamma, beta are calculated by adopting a maximum likelihood method, and the cumulative probability of the runoff X of a certain time scale is calculated:
and (3) carrying out normal standardization on the T distribution probability to obtain:
wherein, when F>At 0.5, s=1; when F is less than or equal to 0.5, S= -1, wherein c 0 =2.515517,c 1 =0.802853,c 2 =0.010328,d 1 =1.432788,d 2 =0.189269,d 3 =0.001308。
PreferablyIn the above-mentioned underground water storage measurement distance and level percentage I wt The method is constructed by underground water storage data, and comprises the following steps:
wherein WTD represents the underground water storage capacity during the study period, WTD 0 Representing average underground water storage for the same years.
Preferably, the soil moisture stress index K sw The soil water content data is constructed by the following calculation method:
wherein θ represents the root zone soil moisture; θ wp Indicating wilting water content, theta cr Represents a critical water content; θ fc Representing the field water holding capacity; n is an empirical constant, and the value range of n is 1-2 according to the plant type and the resistance of the plant type to drought stress.
Preferably, the method for calculating the comprehensive drought index CWRI comprises the following steps:
CWRI=a*SRI+b*(-K sw )+c*I wt
wherein a, b and c respectively represent the weight of each drought index in the comprehensive drought index, a is the ratio of the average diameter flow of the same period for many years to the total water resource, b is the ratio of the average soil water content of the same period for many years to the total water resource, and c is the ratio of the average underground water storage amount of the same period for many years to the total water resource; the total water resource amount is the sum of the average runoff amount of the same period for many years, the average soil water content of the same period for many years and the average underground water storage amount of the same period for many years.
Preferably, the drought classification standard of the comprehensive drought index is determined by the drought classification standard of each drought index, and the calculation method is as follows:
wherein the drought class includes drought free, light, medium, heavy and extreme drought, SRI Drought ratingI weight drought rating The method comprises the steps of respectively representing a threshold interval corresponding to drought grade division standards of each drought index, wherein a, b and c respectively represent weights of each drought index in the comprehensive drought index, a is a ratio of average runoff quantity of the same period for years to the total quantity of water resources, b is a ratio of average soil water content of the same period for years to the total quantity of water resources, and c is a ratio of average underground water storage quantity of the same period for years to the total quantity of water resources; the total water resource amount is the sum of the average runoff amount of the same period for many years, the average soil water content of the same period for many years and the average underground water storage amount of the same period for many years.
Preferably, the drought classification criteria for each drought index are as follows:
the beneficial effects are that: the method can monitor hydrologic drought by jointly utilizing ground observation data, multi-source remote sensing data and a hydrologic model aiming at a non-data area, accurately identify the overall and local hydrologic drought conditions of a research area, and grade the severity of drought; therefore, potential influence of hydrologic drought on various aspects of society and economy can be evaluated, water resource supply and demand gaps are reduced by appropriate water management measures based on the potential influence of hydrologic drought, and the problem that water resource shortage and economic development of a research area are not matched is solved.
Drawings
FIG. 1 is a flow chart of a hydrologic drought monitoring system for a data-free area;
fig. 2 is a graph of drought rating for each region of the coastal zone of Pu-field in 2011.
Detailed Description
The invention is further described below with reference to the drawings and specific embodiments.
Example 1
As shown in fig. 1, a hydrologic drought monitoring system for a data-free area, the monitoring system comprising:
the data simulation module is used for calculating simulation data according to remote sensing data, wherein 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 SRI and an underground water storage measuring distance flat percentage I wt And soil moisture stress index K sw Constructing a comprehensive drought index CWRI according to the weight of each drought index in the comprehensive drought indexes;
and the drought identification and grade division module is used for determining the drought grade according to the comprehensive drought index and the grade division standard of the comprehensive drought index.
Since the identification of drought involves the determination of a relational expression and the cumulative probability density of runoff, the time series of the various variables to be input should be as long as possible.
The coastal tablets of Pu-Tian city are taken as an example, and are specifically carried out according to the following steps:
1. the data simulation module is constructed as follows:
(1) Calculating the runoff of each moon in Putian city:
the objective function for simulating runoff for each month is as follows:
Y r =aX p +b
wherein X is p To represent the contemporaneous rainfall of hydrologic sites, Y r To represent the contemporaneous runoff of the hydrologic site,for the contemporaneous surface rainfall (input remote sensing rainfall data) of the research area>For the synchronous surface runoff of the research area, the units are m 3 . The P value of the above relation satisfies the precision requirement (P>0.5 For unsatisfied degree of polynomial to be raised until satisfied.
Table 1 is simulated from contemporaneous data of measured rainfall and measured runoff from a hydrologic site located upstream of the Mulanxi basin in Pu's city in 2006-2016, which is similar to the underlying features of the research area, has less human activity in the controlled basin, is less affected by the reservoir, and can be basically seen as natural runoff. In each of the formulas in Table 1, P satisfies the precision requirement (P>0.5, the same applies below), x is the synchronous rainfall, y is the synchronous runoff, and the unit is m 3 . The relation is used for runoff simulation in coastal areas without data in Pu-pad cities, and the input rainfall is obtained through remote sensing images, so that the natural runoff can be output.
TABLE 1 rainfall and runoff relations for each month of Pu field
And then the average diameter flow rate of the same period for many years can be calculated:
wherein Q is b Representing the years average diameter flow of the study area; q (Q) a Representing the runoff quantity representing the hydrologic site; f (F) b Representing the area of the investigation region; f (F) a Representing an area representing a hydrologic site; p (P) b Representing the surface rainfall of the research area; p (P) a Representing the amount of surface rain representing the hydrologic site.
(2) Calculating the underground water storage capacity of each area of the Pu field:
and simulating the objective function of the underground water storage amount and the objective function simulation process.
Table 2 is modeled by contemporaneous data of surface rainfall and measured underground water storage in regions of the Pu' an urban area of 2009-2016, wherein x is contemporaneous rainfall, and the unit is m 3 The method comprises the steps of carrying out a first treatment on the surface of the y is synchronous underground water storage capacity with unit of hundred million m 3 . The relation is used for simulating the underground water storage capacity in coastal areas without data in the Pu-pad cities, and the input rainfall capacity is acquired through remote sensing images, so that the underground water storage capacity data can be output.
TABLE 2 rainfall and underground Water storage relations for each region of Pu-field
Furthermore, the average soil water storage capacity (average value of the underground water storage capacity in the research period) in the same period for years can be calculated.
(3) And (5) calculating the water content of the soil. The soil water content data is derived from a land data assimilation system (China meteorological administration land data assimilation system, CLDAS) of the China weather office, and the data form is 0-10 cm, 10-40 cm and the daily soil volume water content (m) of the soil layer of 40-100 cm 3 /m 3 ) The spatial resolution is 0.0625 ° x 0.0625 °.
2. The construction process of the comprehensive drought index construction module of the Putian coastal tablets is as follows:
calculate SRI, I wt 、K sw
(1) The specific calculation method of the normalized runoff index SRI is as follows:
assuming that the runoff amount x for a certain period of time satisfies the T distribution probability density function f (x) is:
wherein: gamma and beta are shape and scale parameters, respectively.
X >0, γ >0, β >0, γ, β can be calculated by maximum likelihood method, cumulative probability of the traffic X over a time scale:
and (3) carrying out normal standardization on the T distribution probability to obtain:
when F >0.5, s=1; when F is less than or equal to 0.5, s= -1, where c0= 2.515517, c1= 0.802853, c2= 0.010328, d1= 1.432788, d2= 0.189269, d3= 0.001308.
(2) Underground water storage measuring distance flat percentage I wt The calculation method comprises the following steps:
wherein WTD is the underground water storage capacity in the research period, one hundred million m 3 ;WTD 0 Is the average underground water storage capacity in the same period for many years, and is one hundred million m 3
(3) Soil moisture stress index K sw Calculated using the following formula:
wherein θ is the root zone soil moisture; θ wp Is withering water content, theta cr Is critical water content; θ fc Is the field water holding capacity; n is an empirical constant, and varies with the plant type and resistance to drought stress, generally between 1 and 2, and 1.53 is calculated.
(4) The method for calculating the comprehensive drought index CWRI comprises the following steps:
CWRI=a*SRI+b*(-K sw )+c*I wt
wherein a represents the ratio of the average diameter flow of the same period for many years to the total water resource, b represents the ratio of the average soil water content of the same period for many years to the total water resource, and c represents the ratio of the average underground water storage of the same period for many years to the total water resource; the total water resource amount is the sum of the average runoff amount of the same period for many years, the average soil water content of the same period for many years and the average underground water storage amount of the same period for many years.
Thus, the comprehensive drought index (CWRI) of Pu field coastal tablets is calculated a ):
CWRI a =0.5314SRI+0.3015(-K sw )+0.1671I wt
The comprehensive drought index of each region of the Pu field coastal tablets is calculated by the method:
the Putian coastal tablet mainly comprises five parts, including: the calculation formulas of Meuzhou island, xuyu area, north bank, litchi urban area and culvert Jiang Ou are shown in Table 3:
TABLE 3 comprehensive drought index for each region of Pu-field
3. The drought identification and grading module is constructed as follows:
the respective drought class division criteria for the integrated drought index are as follows (the weight of each drought class of the integrated drought index is the same as the weight (a, b, c) of the integrated drought index):
wherein the drought class includes drought free, light, medium, heavy and extreme drought, SRI Drought ratingI weight drought rating And respectively 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 and obtaining the drought grade division standard of the comprehensive drought indexes of the field coastal slices and the areas in the table 5 by referring to the drought grade division standard of each drought index in the table 4.
TABLE 4 drought class rating criteria for each drought index
Table 5 drought rating criteria for comprehensive drought index
According to Table 5, the hydrodrought conditions of the coastal slices of Pu' an and the respective areas can be obtained. Because the remotely sensed data are 2010-2016 precipitation data and soil moisture data, drought conditions of the coastal slices of the Pu field in 2010-2016 and the areas can be identified, and fig. 2 shows drought grade conditions of the areas of the coastal slices of the Pu field in 2011.
According to the method, aiming at a non-data area, hydrologic drought is monitored by jointly utilizing ground observation data, multi-source remote sensing data and a hydrologic model, the overall and local hydrologic drought conditions of a research area are accurately identified, and the severity of drought is graded; therefore, potential influence of hydrologic drought on various aspects of society and economy can be evaluated, water resource supply and demand gaps are reduced by appropriate water management measures based on the potential influence of hydrologic drought, and the problem that water resource shortage and economic development of a research area are not matched is solved.

Claims (3)

1. A hydrologic drought monitoring system for a data-free area, said monitoring system comprising:
the data simulation module is used for calculating simulation data according to remote sensing data, wherein 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 SRI and an underground water storage measuring distance flat percentage I wt And soil moisture stress index K sw Constructing a comprehensive drought index CWRI according to the weight of each drought index in the comprehensive drought indexes;
the drought identification and grade division module is used for determining drought grades according to the comprehensive drought index CWRI and the grade division standard of the comprehensive drought index;
the natural runoff data are obtained through remote sensing precipitation data processing, and the natural runoff data comprise natural runoff representing a research period and average runoff of the same period for years;
the objective function of the natural runoff amount in the study period is as follows:
Y r =aX p +b
wherein a and b respectively represent constant coefficients of the objective function, X p To represent contemporaneous rainfall of hydrologic sitesAmount, Y r To represent the contemporaneous runoff of the hydrologic site,for the contemporaneous surface rainfall of the investigation region, < > water>For the synchronous surface runoff of the research area, the units are m 3 The method comprises the steps of carrying out a first treatment on the surface of the The P values of the relational expressions all meet the precision requirement that P is more than 0.5, and the degree of the polynomial is increased until the precision requirement is met for the relational expressions which do not meet the precision requirement;
the method for calculating the average diameter flow of the same period for many years comprises the following steps:
wherein Q is b Representing the average runoff of the study area in the same period for years; q (Q) a Representing the runoff quantity representing the hydrologic site; f (F) b Representing the area of the investigation region; f (F) a Representing an area representing a hydrologic site; p (P) b Representing the surface rainfall of the research area; p (P) a Representing the amount of surface rain representing the hydrologic site;
the underground water storage data is obtained through remote sensing precipitation data processing, and comprises an underground water storage in a research period and an average underground water storage in the same period for years, wherein the objective function of the underground water storage in the research period is as follows:
Y w =cX p +d
wherein c and d respectively represent constant coefficients of the objective function, X r To represent the contemporaneous rainfall of hydrologic sites, Y w To represent the contemporaneous underground water storage of the administrative area in which the hydrological site is located,for the contemporaneous surface rainfall of the investigation region, < > water>For the contemporaneous underground water storage of the research area, the unit is m 3
The average underground water storage capacity of the same period for many years is an average value of the underground water storage capacity of the research period for many years;
the soil moisture content data is obtained through remote sensing soil moisture content data processing, and comprises a research period soil moisture content and a contemporaneous multi-year average soil moisture content;
the normalized runoff index SRI is constructed by natural runoff data, and the calculation method comprises the following steps:
assuming that the runoff amount x for a certain period of time satisfies the T distribution probability density function f (x) is:
wherein: gamma and beta are shape and scale parameters, respectively, lambda represents a rate parameter;
x is more than 0, gamma is more than 0, beta is more than 0, gamma, beta and lambda are calculated by adopting a maximum likelihood method, and the cumulative probability of the runoff X with a certain time scale is calculated:
and (3) carrying out normal standardization on the T distribution probability to obtain:
wherein s=1 when F > 0.5; when F is less than or equal to 0.5, S= -1, wherein c 0 =2.515517,c 1 =0.802853,c 2 =0.010328,d 1 =1.432788,d 2 =0.189269,d 3 =0.001308;
The underground water storage measuring distance is equal to the percentage I wt The method is constructed by underground water storage data, and comprises the following steps:
wherein WTD represents the underground water storage capacity during the study period, WTD 0 Represents average underground water storage for the same period for years;
the soil water stress index K sw The soil water content data is constructed by the following calculation method:
wherein θ represents the root zone soil moisture; θ wp Indicating wilting water content, theta cr Represents a critical water content; θ fc Representing the field water holding capacity; n is an empirical constant, and the value range of n is 1-2 according to the change of the plant type and the resistance of the plant type to drought stress;
the method for calculating the comprehensive drought index CWRI comprises the following steps:
CWRI=a*SRI+b*(-K sw )+c*I wt
wherein a, b and c respectively represent the weight of each drought index in the comprehensive drought index, a is the ratio of the average diameter flow of the same period for many years to the total water resource, b is the ratio of the average soil water content of the same period for many years to the total water resource, and c is the ratio of the average underground water storage amount of the same period for many years to the total water resource; the total water resource amount is the sum of the average runoff amount of the same period for many years, the average soil water content of the same period for many years and the average underground water storage amount of the same period for many years.
2. The hydrologic drought monitoring system of a data-free area according to claim 1, wherein the drought rating criteria of the integrated drought index is determined by the drought rating criteria of each drought index, and the calculation method is as follows:
CWRI drought rating =a*SRI Drought rating +b*(-K sw drought rating )+c*I weight drought rating
Wherein the drought class includes drought free, light, medium, heavy and extreme drought, SRI Drought rating 、K sw drought rating 、I weight drought rating The method comprises the steps of respectively representing a threshold interval corresponding to drought grade division standards of each drought index, wherein a, b and c respectively represent weights of each drought index in the comprehensive drought index, a is a ratio of average runoff quantity of the same period for years to the total quantity of water resources, b is a ratio of average soil water content of the same period for years to the total quantity of water resources, and c is a ratio of average underground water storage quantity of the same period for years to the total quantity of water resources; the total water resource amount is the sum of the average runoff amount of the same period for many years, the average soil water content of the same period for many years and the average underground water storage amount of the same period for many years.
3. The system of claim 2, wherein the drought classification criteria for each drought index is as follows:
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