CN113569323A - Dynamic modeling method for territorial space planning system for realizing planning scene simulation - Google Patents

Abstract

The invention discloses a dynamic modeling method and a dynamic modeling device for a territorial space planning system for realizing planning scene simulation, wherein the method comprises the following steps: determining a model system boundary; constructing economic, population, social development, water resource, land utilization and energy subsystems of a territorial space planning model, and determining key variable composition of the territorial space planning model; establishing the relationship between the inside of the subsystems and the subsystems according to the new classical economy and water-land-energy connection relation theory, constructing a cause-effect structure diagram of the system, and drawing a storage flow relation diagram of variable elements; determining parameters and initialization conditions of a territorial space planning model, and inputting the relationship between the parameters and an equation; the territorial space planning model is checked through model storage and flow rate checking and sensitivity analysis; and carrying out the design and simulation of the territorial space planning scene through the examined territorial space planning model. An SD model capable of comprehensively reflecting the characteristics of the territorial space is developed, and the scientificity of territorial space planning and compilation is promoted to be improved.

Description

Dynamic modeling method for territorial space planning system for realizing planning scene simulation

Technical Field

The invention relates to the technical field of territorial space planning, in particular to a method and a device for dynamically modeling a territorial space planning system for realizing planning scenario simulation.

Background

As an important measure for promoting ecological civilization construction, novel urbanization development and promoting national governance capacity and governance system modernization, the establishment of the territorial space planning needs to be directed to rationalization and scientization. The invention provides a dynamic model of a territorial space planning system based on multiple elements, multiple dimensions and multiple systems, and aims to realize dynamic quantitative simulation of planning multiple scenario schemes by analyzing element constitution of the territorial space planning model system and interaction relations among elements and solving the technical problem of how to quantitatively analyze and simulate the territorial space element interaction relations.

Cities and regions serve as basic working objects in the planning field and have the characteristics of a complex huge system. The system dynamics is a model system for mainly researching an information feedback system and recognizing and solving the system dynamic problem, and has good connectivity and adaptability with various planning problems which need to fully consider and balance multi-subject and multi-level requirements and mutual relations thereof. In recent years, a plurality of relevant system dynamics models are developed aiming at the aspects of land utilization planning, urban planning, ecological environment planning and evaluation, and the like, but the core contents and research methods of various plans are different, so the emphasis points of the developed model systems are also different. However, none of these model systems is developed for the planning of homeland space, and cannot fully reflect the system characteristics of the homeland space.

The prior art has the following disadvantages:

(1) in the aspect of determining the structure of the model subsystem, the model subsystem set by the existing model is not completely directed to the territorial space system, and cannot be completely suitable for the territorial space planning scenario simulation.

(2) In the aspect of determining model variable elements and the storage flow relationship between the model variable elements, the variable elements and the storage flow relationship related to the planning SD model established for the original various space plans cannot completely reflect the rich connotation of a national and local space system, the operation mechanism of the socioeconomic related system is weakened to a great extent, and the feedback and constraint effects of water, land and energy systems on the socioeconomic related elements are relatively ignored.

(3) In the aspects of model parameter setting and simulation application, the existing models mostly only make a simple trend assumption on driving condition elements such as social economy and the like, parameter setting is performed by methods such as trend extrapolation and the like, and power mechanism simulation of the social economy process is neglected. When the simulation application is carried out, the simulation setting of space planning attention indexes such as water, land, energy and the like is lacked, so that the effective connection with related planning targets is lacked.

Disclosure of Invention

The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.

Therefore, one purpose of the invention is to provide a dynamic modeling method for a territorial space planning system for realizing planning scene simulation, which further develops an SD model capable of comprehensively reflecting characteristics of the territorial space on the basis of fully inheriting important progress of a current related planning SD model, and promotes improvement of scientificity of territorial space planning and compiling.

The invention also aims to provide a dynamic modeling device of the territorial space planning system for realizing planning scenario simulation.

In order to achieve the above object, an embodiment of the present invention provides a dynamic modeling method for a territorial space planning system, which implements planning scenario simulation, and includes the following steps:

determining a model system boundary according to a plurality of elements of the territorial space and a multi-dimensional architecture of the territorial space planning model;

constructing an economic subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem and an energy subsystem of the territorial space planning model, and determining the key variable composition of the territorial space planning model;

establishing the relationship between the inside of the subsystems and the subsystems according to the new classical economy and water-land-energy connection relation theory, constructing a cause-effect structure diagram of the system, and drawing a storage flow relation diagram of variable elements;

determining parameters and initialization conditions of the territorial space planning model, and inputting the relationship between the parameters and an equation;

the territorial space planning model is checked through model flow storage and discharge inspection and sensitivity analysis, and the territorial space planning model performance is judged;

and carrying out territorial space planning scene design and simulation through the examined territorial space planning model.

In order to achieve the above object, an embodiment of the present invention provides a dynamic modeling apparatus for a territorial space planning system, which implements scenario planning simulation, and includes:

the boundary determining module is used for determining the boundary of the model system according to the plurality of elements of the territorial space and the multi-dimensional architecture of the territorial space planning model;

the subsystem building module is used for building an economic subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem and an energy subsystem of the territorial space planning model and determining the key variable composition of the territorial space planning model;

the internal association module is used for establishing the relationship between the inside of the subsystem and the subsystem according to the new classical economic and water-land-energy connection relationship theory, constructing a cause-and-effect structure diagram of the system and drawing a storage flow relationship diagram of variable elements;

the parameter determination module is used for determining parameters and initialization conditions of the territorial space planning model and inputting the relationship between the parameters and an equation;

the inspection module is used for inspecting the territorial space planning model through model storage flow rate inspection and sensitivity analysis and judging the performance of the territorial space planning model;

and the simulation module is used for carrying out the design and simulation of the territorial space planning scene through the examined territorial space planning model.

According to the dynamic modeling method and device for the territorial space planning system for realizing planning scenario simulation, provided by the embodiment of the invention, the territorial space is subjected to system analysis and modeling on the basis of inheriting the advantages of the dynamic model of the current related planning system, and a model capable of realizing territorial space planning scenario simulation is further provided. On one hand, the scientific simulation of the social economic system is strengthened, and model construction and parameter setting are carried out based on a new classical economic theory and a Kobuk-Douglas production function method; on the other hand, relevant variables of water resources, land and energy are used as model constraint conditions, bidirectional action and incidence relation between a social and economic related system and a water, land and energy related system are concerned, a system dynamics model capable of comprehensively reflecting characteristics of the territorial space is developed, and scientificity of a planning model is improved.

Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 is a flow chart of a method for modeling dynamics of a geospatial planning system for implementing planning scenario simulation according to an embodiment of the present invention;

FIG. 2 is a flowchart framework of a dynamic modeling method of a geospatial planning system for implementing planning scenario simulation according to an embodiment of the present invention;

FIG. 3 is a model dimension architecture and system boundaries in accordance with one embodiment of the present invention;

FIG. 4 is a model causal loop according to one embodiment of the present invention;

FIG. 5 is an economic subsystem inventory relationship according to one embodiment of the invention;

FIG. 6 is a population subsystem traffic volume relationship according to one embodiment of the present invention;

FIG. 7 is a social evolving subsystem traffic-storage relationship, according to one embodiment of the present invention;

FIG. 8 illustrates a water resource subsystem traffic flow relationship, according to one embodiment of the present invention;

FIG. 9 is a land use subsystem inventory relationship according to one embodiment of the invention;

FIG. 10 is an energy subsystem inventory relationship, according to one embodiment of the present invention;

FIG. 11 is a general diagram of a dynamic model traffic-storage relationship of a territorial space planning system according to an embodiment of the invention;

fig. 12 is a schematic structural diagram of a dynamic modeling device of a geospatial planning system for implementing planning scenario simulation according to an embodiment of the present invention.

Detailed Description

Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.

The design scheme of the invention aims at providing a dynamic model of a national-soil space planning system for realizing planning scene simulation by relying on a water-land-energy coupling theory and a method aiming at the characteristics of a complex national-soil space huge system. Firstly, determining the boundary of a model system by taking a complex national-soil space giant system as an object, setting a dynamic model of the national-soil space planning system, wherein the dynamic model comprises an economy subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem and an energy 6 subsystem, defining the composition of the model subsystem and key variables, and writing the composition into a Vensim PLE platform. Secondly, establishing the relationship inside the subsystems and among the subsystems according to the new classical economic and water-land-energy connection relationship theory, constructing a cause-effect structure diagram of the system, and drawing a storage flow relationship diagram of variable elements in a Vensim PLE platform. And thirdly, determining parameters and initialization conditions, and comprehensively utilizing methods such as a perpetual inventory method, a Kobub-Douglas production function, linear regression, curve estimation, a knowledge production function, a table function, a (piecewise) arithmetic mean method and the like to input parameters and equation relations. Fourthly, model testing is carried out from the aspects of model storage flow rate inspection and sensitivity analysis, and whether the model can reproduce past system dynamic changes and model stability when parameters change is checked. And finally, running a dynamic model of the territorial space planning system facing to planning decision support in the Vensim PLE platform by selecting multi-dimensional planning indexes such as economy, population, society, water, land, energy and the like and designing planning scenes, and carrying out simulation of the planning scenes.

The dynamic modeling method and device for the territorial space planning system for realizing planning scenario simulation provided by the embodiment of the invention are described below with reference to the attached drawings.

Firstly, a dynamic modeling method of a territorial space planning system for realizing planning scenario simulation, which is provided by the embodiment of the invention, is described with reference to the attached drawings.

As shown in fig. 1 and fig. 2, the dynamic modeling method for the territorial space planning system for realizing planning scenario simulation includes the following steps:

in step S101, a model system boundary is determined according to a plurality of elements of the territorial space and a multidimensional architecture of the territorial space planning model.

Optionally, in one embodiment of the present invention, the plurality of elements includes: natural resources and asset variable elements, economic input and output variable elements, social development and service variable elements, and environmental impact and stress variable elements. The multi-dimensional architecture includes: production function dimensions, element flow support dimensions, development policy dimensions, and external condition constraint dimensions.

The homeland space is an open and comprehensive complex huge system and is not only understood from the perspective of a closed boundary and a local department. Generally, the homeland space is regarded as a comprehensive connection system which is composed of key element systems of economy, population, society, water resources, land, energy and the like, and the elements are mutually connected and interacted. The model system boundaries are shown in fig. 3.

The invention screens out 150 variable elements mainly related to the homeland space, classifies the variable elements into natural resource and asset variable elements, economic input and output variable elements, social development and service variable elements and environmental impact and stress variable elements, and correspondingly inputs a Vensim PLE platform:

first, natural resources and asset variable elements. Both the resource attributes of water, land and energy related elements in the natural environment are of concern and the asset attributes as natural capital are emphasized.

Second, economic input and output variable factors. Not only the economic growth condition concerned by the growth theory, but also the variable elements related to the economic development quality and the technical progress under the new economic state, and the investment of traditional production elements such as capital, labor force and the like.

Third, social development and service variable elements. The method comprises the relevant variable elements of population quantity related to social development and structural conditions thereof, education and medical development levels reflecting social public services, and daily living levels of residents characterized by consumption demands of population on various resources.

Fourth, environmental impact and coercion variable elements. The method reflects the overall demand condition of water resources and energy resources formed by activities such as human production, life and the like on the environment, and influences and stresses of resource utilization on water environment and atmospheric environment.

On the basis, the multi-dimensional architecture of the territorial space planning model for planning scene simulation is further determined, and the multi-dimensional architecture is divided into four dimensions of a production function, element flow support, a development policy and external condition constraint.

First, a production function dimension. The regional economic growth dynamic mechanism based on the production element investment and accumulation action is reflected, and the economic growth influences the dynamic evolution of the whole territorial space system to a great extent, so that the production function is the basic dimension of the territorial space planning model. This dimension involves a total of five levels: one is capital, which directly or indirectly constitutes capacity, including first, second, third industry capital inventories, and the like. And the second is labor force, including the first, second and third industry labor force supply reflecting the labor force quantity, and the labor force productivity reflecting the labor force quality of different industries. Thirdly, the land emphasizes the property of the assets of the land as production data, including the land utilization types such as agricultural land, urban industrial land, urban third industrial land and the like and the economic output level thereof. And fourthly, the technology is a power source for promoting the lasting growth of economy and reflects the capabilities and functions of research, development and innovation. And fifthly, yield, which reflects the economic yield level and increase under the action of related production elements such as capital, labor force, land and technical progress.

Second, the element flow support dimension. The external support system and the foundation required by elements in the flow process of different departments are mainly characterized. This dimension involves three levels in total: the energy system comprises energy production and energy consumption, industrial production, traffic logistics and daily life of residents depend on various energy resources such as coal, petroleum, natural gas and non-fossil energy, and changes of the energy system in the aspects of structure and energy consumption intensity reflect changes of production modes and adjustment of industrial structures in the development process to a great extent. And secondly, traffic logistics, which is a link for connection between different territorial space areas, provides a foundation for the flow of elements such as people flow, logistics and the like. The maintenance level of the motor vehicle is greatly improved, and the construction of road traffic facilities and the energy consumption of traffic transportation are stimulated. Thirdly, the population structure, the population amount and the age structure basically determine the labor supply level, and particularly, the aging directly influences the labor scale; the urbanization process, in which the population flows from countryside to city, has a significant impact on the flow of labor among different industrial sectors and drives the flow of production elements such as capital. Thus, dynamic changes in the population system can inherently impact economic development by impacting the flow and changes in production factors such as labor, human capital, and physical capital investment.

Third, the policy dimension is developed. Mainly reflects the regulation and control of development policies of different levels of economy, population, education, medical treatment, water supply, housing, traffic, grain, national soil, energy and the like. Among them, the economic aspect mainly reflects the development policy on economic growth speed, industrial structure, capital accumulation, labor employment. The population level reflects mainly the developing policy on population fertility characterized by the total fertility rate. The education layer mainly reflects the development policies of basic education and higher education of cities. The medical level reflects largely the evolving policies regarding health technician configuration. The water supply level mainly reflects the control of water resource supply, allocation and the like. The housing level mainly reflects the development policy of the housing supply level characterized by the average housing building area of towns and people. The traffic layer mainly reflects the development policy in the automobile consumption represented by automobiles. The grain mainly reflects the development policies of grain self-sufficiency, livestock meat and aquatic product consumption. The homeland level mainly reflects the control of the development strength of the homeland. The energy level mainly reflects development policies on fossil energy such as coal, petroleum and natural gas and non-fossil energy production.

Fourth, the external condition constrains the dimensions. Mainly comprising ecological constraints and environmental constraints. Ecological constraints mainly reflect the constraints of water resources and land resources in the process of developing and utilizing the national space, agricultural water, industrial water, domestic water, ecological water and the like are rigidly constrained by the resources for developing and utilizing the water resources, grain production, forest ecological functions, livestock meat and aquatic products depend on various non-construction land resources such as cultivated land, woodland, grassland, water areas and the like, and the construction space for developing and utilizing also forms certain ecological constraints due to the limitation of the bearing capacity of the resource environment and the suitability of the national space for developing. Here, the resource attribute among the land dual attributes is embodied. The environmental constraint mainly reflects the stress on the water environment and atmospheric environment in the process of utilizing water resources and energy resources, including the capabilities of waste water discharge and treatment and reuse, fossil energy carbon dioxide discharge, sulfur dioxide discharge and the like.

In step S102, an economic subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem, and an energy subsystem of the territorial space planning model are constructed, and a key variable composition of the territorial space planning model is determined.

The economic subsystem is mainly used for simulating the first, second and third industrial growth conditions, and mainly comprises industrial production values, capital stock, labor force and the like. The core thought of the construction method is to utilize a production function to simulate through analyzing and estimating production factors such as capital, labor force and the like and the relationship between the production factors and economic growth. The equations involved in the economy subsystem are shown in table 1.

(1) And (3) industrial growth: the new classical economic growth theory of solio states that economic output depends on labor input, capital input, and the level of integrated technology. The model adopts a Kobuk-Douglas production function method for simulating three industrial growths. The workforce yield elasticity, capital yield elasticity, and full factor productivity growth rate in the production function determine economic growth trends.

(2) Capital inventory: increased capital investment is an important source of economic growth as an inventory of capital that directly or indirectly contributes to the capacity, including the direct production and provision of various physical products, various tangible and intangible assets of labor, and also various service and welfare facility assets that serve living processes. The perpetual inventory method is a common method for calculating the capital inventory calculated by a comparable price, and the basic principle is that the T year data accumulation is T-1 year data accumulation plus T year investment, and if the ratio of the capital increment and the output increment is equal to the ratio of the capital inventory to the total output, then K is GDP x (delta K/delta GDP), wherein K is the capital inventory and delta K is the net increment of the current year.

(3) Labor force: labor supply depends on the size of the population and the age composition characteristics of the population, and the model assumes that the urban and rural population 15-64 years old is the labor age population. Meanwhile, for the sake of model building operability, it is assumed that the urban population is mainly engaged in the second industry and the third industry activities and the rural population is mainly engaged in the first industry activities.

TABLE 1 economic subsystem equation

Note: GDP is the total value of domestic production; dyyzjz is a first industry added value; DECYZJZ is a second industry added value; DSCYZJZ is added value for the third industry; NDYCYZJZZL is the added value increment of the first industry of the year; dycycl is the first industrial labor; dyyzbcl is the first industry capital inventory; NDECYZJZZL is the value increment added by the second industry of the year; DECYLDL is a second industrial labor; DECYZBCL is a second industry capital inventory; NDSCYZJZZL is the increment of the third-year industry added value; DSCYLDL is third industry labor; dscyzbccl is the third industry capital inventory; DYYZJZZZL is the added value increase rate of the first industry; DECYZJZZZL increases value growth rate for the second industry; DSCYZJZZZL increases the value growth rate for the third industry; ZZBCLNZJZ is an annual added value to the total capital inventory; ZBJLL is the capital accumulation rate; dyyzbclbl is the first industry capital inventory proportion; DECYZBCLBL is the second industry capital inventory ratio; DSCYZBCLBL is the third industry capital stock proportion; decycyryzl is the second industry practitioner growth rate; DECYJYRYXS is the second industry employment personnel coefficient; DSCYCYRYZL is the growth rate of third-industry practitioners; DSCYJYRYXS is the coefficient of third industry employment personnel; NYLDLLXQ is the agricultural labor demand; SJDECYZJZZZL increases the value increase rate for the actual second industry; DECYLDSLCLZZL is the second industry labor productivity growth rate; SJDSCYJZZZL increases the value increase rate for the actual third industry; dscyldslclzzl is the third industry labor productivity growth rate.

The population subsystem is mainly used for simulating population change conditions of different age structures of cities and villages, including urban population and rural population parts. On one hand, the method can reflect the urbanization process of population transferred from villages to town areas to represent the urbanization level, and on the other hand, the method can reflect the process that the total fertility rate of China is reduced and the population tends to age in the future. In connection with other subsystems, the population subsystem provides a basic interface for simulating various industrial labor force changes in the economic subsystem through changes of working age-appropriate population, and is associated with the social development subsystem through the influence of urban education and medical level changes on the urbanization level. The equations involved in the population subsystem are shown in table 2.

(1) The fertility level is as follows: the total fertility rate (ZHSYL) characterizes the fertility potential and level and is the basis for determining the development situation of the population. The model sets the total fertility rate as a controllable scene variable, simulates the natural condition of the population by fitting the relationship between the total fertility rate and the urban total fertility rate (CSZHSCL), the urban population birth rate (CSRKCSL), the rural total fertility rate (XCZHSCL) and the rural population birth rate (XCRKCSL), and further simulates the dynamic and aging characteristics of the population in a certain period by designing different total fertility rate scenes.

The markas population model assumes that the population growth rate remains constant and thus the population growth will exhibit exponential growth over time. However, under the constraint of various conditions such as resource environment carrying capacity, the population does not necessarily have an infinite and rapid growth trend. The population block growth model considers that population growth is subject to blocking by external constraints, as the population growth rate gradually decreases as the population increases. The population growth rate is set as r, the population total amount is set as x, if r is a linear function of x, r (x) is r-sx (r >0, x >0), and in the formula, s is a coefficient to be estimated.

(2) Urban and rural population

The model divides the urban and rural population into three age groups, wherein the urban population (CSRK) is 0-14 years old (CSRK)_0-14) City 15-64 years old (CSRK)_15-64) And city 65 years old and older (CSRK)_≥65) The country population (XCRK) is 0-14 years old (XCRK)_0-14) Country 15-64 years old (XCRK)_15-64) And the rural population 65 years old and older (XCRK)_≥65) The age structure of urban and rural children, urban and rural middle-aged and urban and rural old people is represented, and a three-order aging chain structure of the population is formed. The general population (ZRK) is the sum of the urban population and the rural population, and the proportion of the urban population to the general population is the urbanization level (CZHSP).

(3) Floating population

With the improvement of agricultural labor productivity and the development demand of non-agricultural industry, a large amount of rural residual labor force is diverted to the non-agricultural production activities such as industry, business, service industry and the like, and the crowd constitutes the main body of the floating population. The model assumes that the agricultural labor migration speed (NYLDLQYSD) is the difference between the first industry labor supply acceleration rate and the demand acceleration rate. On the basis, by considering the influence of the progress of the urban education level and the urban medical level, the population subsystem is connected with the social development subsystem, and the annual and rural transfer urban population (NXCZYCSRKL) is estimated.

TABLE 2 population subsystem equations

Note: RKZZZZXS is the population growth retardation coefficient; CSRK is a city population; CSRK_0-14Is urban 0-14 years old; CSRK_15-64Is urban 15-64 years old; CSRK_≥65Is the population 65 years old and older in cities; XCRK is a rural population; XCRK_0-14Is the rural 0-14 year old population; XCRK_15-64Is the rural population of 15-64 years old; XCRK_≥65Is the population of villages 65 years old and above; ZRK is the general population; CZHSP is urbanization level; NCSRKCSL is annual urban population birth; CSZRRK_0-14Transferring the city into 0-14 year old population; CSRKSWL_0-14Is urban 0-14 year old population death; CSRKZL_15-64Urban population increments of 15-64 years; CSZRRK_15-64Transferring to 15-64 years old population for city; CSRKSWL_15-64Urban 15-64 years of population mortality; CSRKZL_≥65Population increments for cities 65 years old and older; CSZRRK_≥65The population is shifted to 65 years old and older for cities; CSLLRKSWL is the death rate of the urban aged population; NXCRKCSL is the birth weight of the annual village population; XCRKSWL_0-14Is the rural 0-14 year old population death; XCRKZL_15-64The population increment is between 15 and 64 years old in villages; XCZCRK_0-14The population is transferred to the country at the age of 0-14 years; XCRKSWL_15-64Is the rural death rate of 15-64 years; XCRKZL_≥65Population increment of 65 years old and above for villages; XCZCRK_15-64The population is transferred to the country between 15 and 64 years old; XCLLRKSWL is the death rate of the rural elderly population; XCZCRK_≥65The population is transferred to the country at age 65 and above; ZDRKCZL is the maximum population load; dyycylldlzl is the first industry labor growth rate; CZHSPYZ is a urbanization level factor; CSCYLDLXQYZ is a labor demand factor of the urban industry; CSJYSPYZ is a city education level factor; CSYLSPYZ is a municipal medical level factor; XCRKZXCRKBL_0-14The proportion of people in the country is 0-14 years old; XCRKZXCRKBL_15-64The proportion of people in the country is 15-64 years old; XCRKZXCRKBL_≥65The proportion of people aged 65 years and above in villages to village population is shown.

The social development subsystem is mainly used for simulating the urban basic education development level, the higher education talent culture condition, the urban medical development level and the patent authorization condition reflecting innovation output in the urban and regional development process, and comprises the education development part, the medical development part and the innovation output part. The social development sub-system is associated with the population sub-system through the impact of advances in education and medical levels on the level of urbanization. The equations involved in the social development subsystem are shown in table 3.

(1) Education level: the model represents the development level of basic education of cities by the number of teachers owned by ten thousand students in middle and primary schools (CSZXXWMXSYJSS), and represents the culture condition of talents of higher education by the number of colleges and students in the academic calendar. The higher primary and secondary school teacher level and resources in the city can attract part of rural population to flow to the city to a certain extent, so that the population of the urban transferred from the rural area is increased, and the urbanization is accelerated. The number of colleagues and colleges (WRDZJYSXLRS) is the proportion of the total population of the colleagues and colleges (DZJYSXLRZS) to the total population.

(2) Medical level: the model represents the medical development level by the number of urban ten thousand persons in possession (CSWRYWSJSRYS), namely the ratio of the number of urban health technicians (CSWSJSRYS) to the urban population. The rapid development of the urban medical level can attract partial population to flow from rural areas to urban areas, so that the population of the urban transferred from rural areas is increased, and the urbanization development is promoted.

(3) And (3) innovative production: the model represents innovation output level by patent authorization number (ZLSGS), is used as a knowledge production process, is associated with innovation input elements such as scientific and technical staff full-time equivalent (KJRYQSDL), outsourcer direct investment amount (WSZJTZJE) and research and test development expenditure (YJYSYFZJFZC) and is simulated by adopting a knowledge production function.

TABLE 3 social development subsystem equation

Note: CSZXXJSX is the number of teachers in middle and primary schools of a city; CSZXXXSS is the number of students in middle and primary schools in the city; RJGDP is human-average GDP; YLFZYZ is a medical development factor.

The water resource subsystem comprises water resource supply, water resource demand and water resource environment parts and is in direct contact with population, economy and land subsystems. Specifically, in the water resource supply section, the total amount of water resource supply mainly relates to the exploitable and utilizable water resources, the amount of rainwater collection project water, the amount of overseas water allocation resources, the amount of seawater desalination and the amount of reclaimed water resources. Along with the improvement of the water resource development and utilization rate, the total water resource supply amount is gradually increased and is controlled within a reasonable range, and the continuously improved sewage treatment and reuse technology provides supplementary sources for water resource supply to a certain extent, so that the reduction of water resource supply and demand gaps is facilitated. In the water resource demand sector, there are mainly agricultural, industrial, domestic and ecological water demands involved. In agricultural production, it is necessary to ensure both the need for irrigation of the farmland and the need for water for forestry, grazing and fisheries, i.e. to be associated with land subsystems by means of cultivated land, woodland, pasture and water areas. In the industrial production process, a certain scale of industrial water needs to be ensured, but the industrial water demand may show a descending trend along with the improvement of water utilization efficiency and the adjustment of industrial structure. With the advancement of urbanization and the improvement of the quality of daily life of residents, the demand of domestic water of urban and rural residents is continuously increased. The water requirement of the ecological environment is preferentially ensured along with the promotion of ecological protection. When various water requirements exceed the total water resource supply amount, a water resource supply and demand gap appears, so that a rigid constraint effect is formed on population growth, urbanization and industrial development. In the water resource environment part, the industrial wastewater discharge, the domestic sewage discharge and the chemical oxygen demand discharge are mainly involved. On the one hand, industrial production and daily life of residents discharge waste water in a certain scale, and generate pollutants such as chemical oxygen demand and the like, thereby influencing the sustainable utilization of the homeland space. However, with the adjustment of industrial structure and the improvement of wastewater and pollutant treatment technology, the pressure and stress of the water resource system are relieved, so that the benign and harmonious human-water relationship in the soil-space system is formed. The equations involved in the water resource subsystem are shown in table 4.

(1) Water resource supply: the module is mainly used for simulating the condition of the total water resource Supply (SZYGJZL) of a research area, the sources of the module comprise a locally exploitable and utilizable water resource (KKFLYSZY) of the research area, an overseas allocation water resource (JWDPSZY), a rainwater collection engineering water quantity (JYGCSL), a seawater desalination quantity (HSDHL) and a reclaimed water resource quantity (ZSZZZYL) and the like, and the module is limited by a water resource supply total control target (SZYGJZLKMB).

(2) Water resource demand: the estimation of water resource demand is the core of a water resource subsystem, and is mainly used for simulating production, living and ecological water caused by farmland irrigation, forest, animal husbandry and fishery development, industrial production, daily life of urban and rural residents and ecological environment water replenishing. Therefore, the total water demand (XSZL) is the sum of the agricultural water demand (NYXS), the industrial water demand (GYXS), the domestic water demand (SHXS) and the ecological water demand (STHJXS).

(3) Water resource environment: the water resource environment module associates the water resource environment quality with the water resource supply and demand condition and is mainly used for simulating the waste water discharge and measuring the discharge condition of the chemical oxygen demand which is an important index of water body pollution.

TABLE 4 Water resource subsystem equation

Note: SZYZL is the total amount of water resources; the SZYKFLYL is used for developing and utilizing water resources; DBSZYL is the amount of surface water resources; DXSZYL is groundwater resource amount; DBDXSCFL is the repeated quantity of surface water and underground water resources; FWSPFZL is the total amount of waste sewage discharge; ZSSYL is the reuse rate of the regenerated water; NTGGXS is water requirement for farmland irrigation; LMYYS is water for forestry, animal husbandry and fishery; NTGGDE is the farmland irrigation quota; GDYXGMJ is the effective irrigation area of the cultivated land; LMYYS is water for forestry, animal husbandry and fishery; LMYGGDE is irrigation quota for forest, herd and fish; GYZJZ is an industry added value; WYGYZJZXSL is a water demand quantity of ten thousand yuan industry added value; CZSHYS is urban domestic water; NCSHYS is rural domestic water; STHJXSNZHZZL comprehensively increases water demand for ecological environmentThe length is long; SZYGXQK is a gap for water resource supply and demand; QSCD is the water shortage degree; SZYDQZS is a water resource shortage index; GYFSFLZ is the total amount of industrial wastewater discharge; SHWSPFZL is the total amount of domestic sewage discharge; SHWSPFXS is the domestic sewage discharge coefficient; GYFSPFXS is the discharge coefficient of industrial wastewater; HXXYLFL is the discharge amount of chemical oxygen demand; HXXYLFXS is the discharge coefficient of chemical oxygen demand; the CZRJSHXSDE is the quota of the daily water demand of urban people; the NCRJSHXSDE is the water demand quota for the rural per capita life; NSTHJXSBHL is the annual ecological environment water demand variable quantity; STHJXS_T-1The water demand for the ecological environment in T-1 year.

The land subsystem mainly comprises a construction land and a non-construction land and is directly connected with the population, economy and water resource subsystems. Specifically, in the construction land portion, urban land such as urban residential land, urban industrial land, urban third industrial land, urban road traffic facility land, and village and town construction land are mainly involved. In the urbanization process, the living room demand is formed due to the fact that the population of the village continuously migrates to the city, and in addition, the total living room demand is gradually increased due to the miniaturization of the scale of the family and the improvement demand of partial urban residents on the living room conditions, which is reflected in the fact that the scale of the living land of the city is continuously increased. The development of the second industry, particularly industrial production, and the third industry needs to be basically guaranteed by the investment of urban industrial land and third industrial land with corresponding scales. With the development of economic society and the improvement of living standard, the quantity of motor vehicles kept will gradually rise, and the demand for urban road transportation facilities will also gradually increase. The village and town construction land is used for meeting the production and living requirements of village and town population, but the total amount of the village and town construction land may show a descending trend due to the gradual flow of the village and town population. In the non-construction land portion, cultivated land, woodland, grassland, water area, and the like are mainly involved. The cultivated land is the basis for guaranteeing the grain safety, and the grain quantity demand of residents on grain, livestock feed and grain and oil processing grain must be met. Forest coverage is a precondition for guaranteeing and playing important ecological production functions of the forest. The pasture and the water area can respectively meet the requirements on meat products such as meat, eggs and milk and aquatic products. In addition, arable land, woodland, pasture and water areas will also be used as agricultural land, become important production factors for the development of the first industry, and constitute water demand for farmland irrigation and forestry, animal husbandry and fishery to water resource systems. The equations involved in the land use subsystem are shown in table 5.

(1) Land for non-construction: the module is primarily used to simulate the trend of non-construction land such as arable land, woodland, pasture, water areas, through the general population and its changes to grain, forest ecology, livestock meat products and aquatic product needs to be associated with population subsystems, through being associated with economic subsystems as an important agricultural production element in the first industry growth, and through field irrigation and water demand for forestry, grazing and fishery to be associated with water resource subsystems.

(2) Land for construction: the module is mainly used for simulating the change trend of various types of construction land such as urban residential land, urban industrial land, urban third industrial land, urban road traffic facility land, village and town construction land and the like.

TABLE 5 land utilization subsystem equation

Note: GDMJ is the cultivated land area; LSXQ is the grain demand; GDLSDC is the per unit yield of grain in cultivated land; FZZS is a multiple breeding index; LSZZWBZBZZ is the proportion of grains in the crop seeding; LSZJL is the self-sufficient rate of grains; RJLSZYL is the occupied amount of average grain for human; LDMJ is the area of the forest land; RJSLZYL is the occupation amount of the forest per capita; MCDMJ is the pasture area; CRXQ is a meat requirement; DWMJMCDCRCL is the livestock meat yield of a unit area of pasture; RJCRXQL is the demand of the meat of the average human animal; SYMJ is the area of the water area; SCPXQ is the demand of aquatic products; DWMJSYSCPCL is the yield of aquatic products in a unit area of water; RJCRXQL is the demand of the meat of the average human animal; CSJZYDMJ is the area of urban residential land; ZFJZMJXQ is the area requirement of the housing building; JZYDZHXS is a conversion coefficient of the residential land; RJZFJZMJ is the area of the civil housing building; CSGYYDMJ is the area of the urban industrial land; GYYDDJCZ is an industrial average yield value; decygdzzctz is the second industry fixed asset investment; CSDSCYYDMJ is the area of the third-generation industrial land in the city; CSDSCYYDDJCZ is used as third-generation urban landAverage local yield value; DSCYGDZCTZ is the third industry fixed asset investment; CSDLJTSSYDMJ is the area of urban road traffic facilities; JDCBYL is the motor vehicle inventory; RJJDCYYL is owned quantity of all vehicles; JDCZCGY is vehicle policy intervention; CZJSYDMJ is the area of the village and town construction land; NCRJJJSYD is a rural construction land for everyone; JSYZL is the total amount of the construction land; TDZMJ is the total land area; GTKFQD develops strength for the territory; JSYDJYLYZ is an intensive utilization factor for construction land; alpha is alpha_i,β_i(i ═ 0,1,2,3) is the parameter to be estimated; v^*Gamma and delta are parameters of the Gompertz model; GTKFQDYSMB is a constraint target for developing strength of the homeland.

The energy subsystem comprises energy supply, energy consumption and energy environment parts and is directly connected with the population and the economic subsystem. Specifically, in the energy supply section, the total amount of energy supply mainly relates to fossil energy production and non-fossil energy production, and is influenced by the amount of energy import and the amount of energy export. The fossil energy production comprises three energy types of coal, fossil and natural gas. In the energy demand section, the three-time industrial energy consumption, the living energy consumption and the transportation energy consumption are mainly involved. In the process of the first, second and third industries, especially the rapid promotion of industrialization, a large amount of energy resources are consumed, and the reduction of energy consumption intensity and the GDP scale determine the industrial energy consumption condition. With the increase of the per capita income level, the daily life energy consumption level of urban and rural residents is also improved, the total life energy consumption is integrally improved, but the rural life energy consumption is probably reduced along with the migration of the population from the rural areas to the cities. In addition, as the level of motor vehicle reserves is increased, the energy consumption of transportation is gradually increased. When the total energy consumption is larger than the energy supply, an energy supply and demand gap is generated, and then a constraint effect is formed on the growth of the second industry and the third industry. In the energy environment sector, carbon dioxide emissions and sulphur dioxide emissions are mainly concerned. The part reflects the environmental impact and the stress of energy structures, the carbon dioxide emission mainly comes from coal, petroleum and natural gas, and the sulfur dioxide emission mainly comes from coal. Therefore, the specific gravity of fossil energy, especially coal production, has obvious effect on environmental effect. When the energy structure tends to be green and clean, the energy environmental constraint of the homeland space system is favorably reduced. The equations involved in the energy subsystem are shown in table 6.

(1) Energy supply: the module mainly reflects the energy production structure and the energy supply condition of China. The energy supply (NYGYL) is the sum of fossil energy production (HSNYSCL) of coal, oil, natural gas and the like, non-fossil energy production and energy import (NYJKL), and energy export (NYCKL) is deducted.

(2) Energy consumption: the module is mainly used for simulating the production and living energy demands formed by three industrial growth, daily life of urban and rural residents and transportation logistics. Therefore, the total energy consumption (NYXFZL) is the sum of the tertiary industrial energy consumption (sccynyffl), the domestic energy consumption (SHNYXFL), and the transportation energy consumption (JTYSNYXFL).

(3) Energy environment: the module relates the energy environmental effect to the energy production structure, and is mainly used for simulating the emission conditions of greenhouse gases such as carbon dioxide and pollutant sulfur dioxide.

TABLE 6 energy subsystem equation

Note: MTSCL is the coal production; SYSCL is oil production; trsscl for natural gas production; FHSNYSCL is non-fossil energy production; MTSCZLL is the coal production growth rate; SYSCZLL is the petroleum production growth rate; TRQSCZLL is the natural gas production growth rate; FHSSNYSCZLL is the growth rate of non-fossil energy production; WYGDPNHQD is the gross domestic production energy consumption strength; CSSHNYXFL is the consumption of urban living energy; NCSHNYXFL is rural life energy consumption; CSRJSHNHYXFL is the consumption of urban per capita living energy; NCRJSHHNYXFL is the energy consumption of the rural per capita life; CSRJKZPSR is the dominant income of all urban people; NCRJCSR is the income of people in rural areas; CO 2₂PFL is carbon dioxide emission; MTCO₂PFL is the carbon dioxide emission of coal; SYCO₂PFL is petroleum dioxygenCarbon emission; TRQCO₂PFL is the emission of carbon dioxide in natural gas; SO (SO)₂PFL is the discharge amount of sulfur dioxide; NYSCL is energy production; NMTSCZ is annual coal production increment; NSYSCZL is annual oil production increment; NTRQSCZL is the annual natural gas production increase; NFHSNYSCZL is the annual non-fossil energy production increment; MTCO₂PFXS is the carbon dioxide emission coefficient of coal; SYCO₂PFXS is the petroleum carbon dioxide emission coefficient; TRQCO₂PFXS is the natural gas carbon dioxide emission coefficient; SO (SO)₂HL is the content of sulfur dioxide; SO (SO)₂QCL is the sulfur dioxide removal amount; ZDMTXFL is the terminal coal consumption; ZDMTSO₂ZHL is the conversion rate of sulfur dioxide of the terminal coal; DLHML is the power consumption coal amount; DLSO₂ZHL is the conversion rate of power sulfur dioxide; MZQLFHL is the content of the total sulfur in the coal; DWMTTLXL is the unit coal desulfurization efficiency.

In step S103, based on the new classical economic and water-land-energy association relation theory, the relationships inside and among subsystems are established, a cause-effect structure diagram of the system is constructed, and a storage flow relation diagram of variable elements is drawn.

In step S104, parameters and initialization conditions of the territorial space planning model are determined, and the parameters and equation relations are input.

Specifically, the parameters of a territorial space planning model are designed, the model parameters are set in a Vensim PLE platform, and the method relates to the following 8 types of methods:

(1) the cobb-douglas production function is mainly used for simulating the industrial growth process. The basic form of the function is:

Y＝A₁·f(K₁,L₂)

in the formula, Y is total yield; a. the₁Reflecting the comprehensive technical level; k₁Is a capital investment; l is₂Is labor input.

(2) And linear regression, namely establishing a unitary or multivariate linear regression relationship based on a least square method, and determining a linear quantitative relationship between variables and key influence factors thereof, such as a relationship between the total urban fertility rate and the urban population birth rate.

(3) And (4) curve estimation, wherein if the variable and the key influence factor are in a nonlinear relation, a nonlinear function is adopted for carrying out relation fitting.

(4) Knowledge production function, which basically assumes the output of an innovative process as a function of development capital or personnel investment, is generally in the form of:

Q＝A₂·f(K₂,L₂)

wherein Q is the development activity outcome; a. the₁Reflecting the total knowledge stock; k₁Capital investment for related research and development; l is₂The investment of related scientific and technological human resources is realized.

(5) The table function, which is a specific function of the system dynamics model, is used to establish a non-linear relationship between two variables, especially a relationship between soft variables, which is difficult to directly quantify with a continuous function, and can be used as a setting of a policy and control variable, for example.

(6) (piecewise) arithmetic averaging, based on historical statistics of the variables at different stages.

(7) The trend extrapolation method is usually used for extrapolating the future of the development rule of a prediction object in a gradual change rather than a jump change according to the variation trend revealed by the historical time sequence of the prediction variable.

(8) According to the literature value assignment method, part of variable parameters can be assigned according to classical literature research, such as carbon dioxide emission coefficients of coal, petroleum and natural gas, and for example, the IPCC report of the special committee of climate change between the governments of the united states can be referred.

In step S105, the territorial space planning model is checked through model traffic verification and sensitivity analysis, and the territorial space planning model performance is determined.

Specifically, model checking is carried out from two aspects, namely, flow storage checking and analysis of whether the model can accurately reflect historical state changes. And carrying out system simulation on the Vensim PLE according to preset parameters, wherein the simulation time range is limited in the time range of the acquired historical data. Then, selecting key variables in the model, comparing the difference between the annual actual value and the simulated value of each variable, and calculating the relative error rate. If the average relative error rate is controlled within 10%, the model simulation effect is good and the reliability is high. The average relative error rate calculation formula is as follows:

in the formula, RE_XIs the average relative error rate of variable X; x (t)_simuIs the simulation value of the variable X in t years; x (t)_realIs the actual value of variable X in t years.

And secondly, sensitivity analysis, namely, the stability and the robustness of the model are tested, namely, when the parameter value changes, the degree of change of the model simulation calculation result correspondingly occurs. By increasing or decreasing the value of the parameter by 10%, the influence degree of the parameter change on the key variable is respectively calculated, namely the sensitivity average value is calculated. The calculation method comprises the following steps:

in the formula, S_QIs the sensitivity of the variable Q to the parameter X; t is time; q_tAnd X_tIs the value of the variable Q and the parameter X at time t; delta Q_tAnd Δ X_tThe time is t, the variable Q and the parameter X are changed values caused by parameter adjustment; n is the number of key variables; s_QiIs a variable Q_iSensitivity to parameter X; s is the average sensitivity level of parameter X.

In step S106, a territorial space planning scenario is designed and simulated by the examined territorial space planning model.

After the reliability and stability of the model are proved through storage flow rate inspection and sensitivity analysis, the model can be used for designing and simulating the territorial space planning scene, namely, the change trend of key elements in the future in the medium-long term scale is analyzed under a plurality of condition hypothesis combinations. Scenario design can be developed from three levels:

firstly, making scenario assumption on urbanization development. The method can decompose the planning scene indexes of urbanization development from the aspects of economic growth, population dynamics, social development and the like, reflect future economic growth potential by GDP annual growth rate, reflect future population change by total fertility rate, reflect the social development levels of future education, medical treatment and the like by the levels of primary education teachers and advanced education talent culture and health technicians, and set the scene by regulating and controlling different combinations of variables.

Secondly, making situational assumptions on the ecological coercion. The water resource utilization and stress can be represented by a total water resource supply control target, a farmland irrigation quota, a ten thousand yuan industrial added value water demand, a per-capita life water demand quota, an ecological environment water demand year comprehensive growth rate and a reclaimed water reuse rate, the land utilization and stress are represented by a grain self-supply rate, a per-capita forest occupation amount, a unit area water area aquatic product yield, a unit area grassland livestock meat yield, a town per-capita housing construction area, a city industrial land area average yield value and a city third industrial land area average yield value, and the scenes are constructed by carrying out various combinations on the control variables to reflect the future urbanization development and ecological stress faced by the homeland space.

And thirdly, making scenario assumptions about energy constraints. The situation is constructed by carrying out various combinations on the control variables such as the total primary energy production amount, the coal production peak year and the production increase rate thereof, the petroleum production increase rate, the natural gas production increase rate, the proportion of non-fossil energy production in the total energy, the ten thousand yuan domestic production total value energy consumption intensity reduction target and the like so as to reflect the change trend of future urbanization development and national space energy constraint.

The present invention will be described in further detail below with reference to examples and the accompanying drawings.

Model system boundary determination

The invention screens out 150 variable elements mainly related to the territorial space, classifies the variable elements, defines the basic structure of a territorial space planning model system, inputs all the variable elements into a Vemsim PLE platform, and determines causal loops among key elements of the system, as shown in figure 5. The variable elements involved in the model system are classified as follows:

first, natural resources and asset variable elements. The categories involved include: the water resource supply mainly reflects the water resource supply and development and utilization conditions from different sources such as the earth surface, the underground and the outside of a local area in a certain area or a space unit. And secondly, protecting and utilizing the non-construction land, which mainly reflects the protection and utilization conditions of the non-construction land such as cultivated land, woodland, grassland, water areas and the like in a certain area or space unit. And thirdly, the development and utilization of the construction land mainly reflect the development and utilization conditions of the construction land of cities and villages in a certain area or space unit. And fourthly, energy supply which mainly reflects the supply total amount, production structure and speed condition of various fossil energy and non-fossil energy resources in a certain area or space unit.

Table 7 model system element variable classification: natural resources and assets

Second, economic input and output variable factors. The categories involved include: the economic development level mainly reflects the economic output and the national income level in a certain period of time in a certain area or space unit. Secondly, economic growth and structure mainly reflect the economic growth speed and industrial structure condition in a certain period of time in a certain area or space unit. And economic quality mainly reflects economic output efficiency based on specific resource consumption in a certain area or space unit. And fourthly, the capital investment mainly reflects the capital investment condition which promotes economic growth in a certain area or space unit. The labor input mainly reflects the labor input condition of promoting economic growth in a certain area or space unit. Sixthly, the technical progress mainly reflects the technical progress situation of promoting economic growth in a certain area or space unit.

Table 8 model system element variable classification: variable elements of economic input and output

Third, social development and service variable elements. The categories involved include: the population quantity and structure mainly reflect the population quantity, the urban and rural structure, the age structure and the aging condition of the population in a certain area or space unit. Second, the birth and death of the population mainly reflect the birth rate and death rate affecting the change of population number in a certain area or space unit. And thirdly, the education level mainly reflects the basic education and the higher education development level in a certain area or space unit. The medical level mainly reflects the medical and sanitary condition conditions in a certain area or space unit. And fifthly, living consumption of residents mainly reflects the consumption level conditions of the residents in a certain area or space unit in daily life in various resources, houses and motor vehicles.

Table 9 model system element variable classification: social development and service variable elements

Fourth, environmental impact and coercion variable elements. The categories involved include: the water resource demand mainly reflects the overall situation of the water resource demand for the environment due to production, life and ecology in a certain region or space unit. Secondly, the energy resource demand mainly reflects the general condition of the energy resource demand on the environment in a certain area or space unit due to industrial growth, urban and rural life and traffic. And thirdly, the water environment quality mainly reflects the influence and stress effect of water resource utilization in a certain area or space unit on the water environment quality. And fourthly, energy environmental effect which mainly reflects atmospheric environmental influence and stress effect of energy resource utilization in a certain area or space unit.

Table 10 model system element variable classification: social development and service variable elements

Constructing economic subsystem and establishing storage flow relation

The economic subsystem memory flow relationship built in the Vensim PLE platform is shown in FIG. 5. The specific equations are shown in the appendix. The following are the ideas and methods for constructing the modules involved in the subsystem:

(1) growth of industry

The first industry increment value (dyyzjz), the second industry increment value (DECYZJZ), and the third industry increment value (DSCYZJZ) are key level variables, the annual first industry increment value (NDYCYZJZZL) is a function of the first industry labor (dyyldl) and the first industry inventory (dyyzbcl), the annual second industry increment value (ndecoyzjzzl) is a function of the second industry labor (DECYLDL) and the second industry inventory (DECYZBCL), and the annual third industry increment value (NDSCYZJZZL) is a function of the third industry labor (DSCYLDL) and the third industry inventory (DSCYZBCL).

2) Capital inventory

The model is used for measuring and calculating the capital stock based on the fixed asset investment data of the whole society, and because the index is an official statistical index with long-time sequence data, the data source is adopted in the related research on the capital stock. The model takes the total capital stock (ZZBCL) as a horizontal variable and is divided into a first industry capital stock (DYCYYZCCL), a second industry capital stock (DECYZCCL) and a third industry capital stock (DSCYZBC) according to corresponding proportions, and the first industry incremental value increment, the first industry incremental value increment and the first industry incremental value increment are promoted respectively, and further the increase of the third industry production value, namely the increase of the domestic production total value, promotes the accumulation of the capital stocks.

(3) Labor force

The annual first industry labor force increment (NDYCYLLDLZJL) is related to the rural 15-64-year-old population, the annual second industry labor force increment (NDECYLLDLZJL) and the annual third industry labor force increment (NDSCYLLDLZL) are related to the urban 15-64-year-old population, and on the basis, the simulation is carried out through the growth rate of the first, second and third industry workers and the coefficients of the first, second and third industry workers, wherein the latter is equivalent to the proportion of actual workers occupying the urban and rural 15-64-year-old population. In general, the first industrial labor (dycycld) shows a descending trend, the second industrial labor (decycld) shows a descending trend in recent years with the adjustment of industrial structure after a period of growth, and the third industrial labor (dscycld) shows a rapid growth trend.

The close relationship exists between the labor demand and the economic growth speed and the labor productivity, and the functional relationship can be expressed as L_T＝(1+g-p)×L_T-1Wherein L is_TAnd L_T-1The labor demand in the period T and the period T-1, g and p are the total domestic production value increase rate and the labor productivity increase rate, and the specific derivation process can be referred to. Accordingly, when the economic growth rate is high, the corresponding labor demand is also high, and when the economic growth rate is constant, if the labor productivity is high, the labor demand is relatively low. The second industry labor demand (DECYLDLXQ) and the third industry labor demand (DSCYLDLXQ) in the model were modeled according to the above equations.

According to the theory of smith and lujia diagram about labor and output, the labor quantity (L) and the labor productivity (P) have the following relationship with the total domestic production value, i.e., GDP is L × P. Accordingly, agricultural labor demand (NYLDLXQ) can be determined from a first industry increment and agricultural labor productivity (NYLDSCL), which relationship can be expressed as: NYLDLLXQ ═ DYCYYZJZ/(NYLDSCL × (1+ NYLDSLZZSD)), where NYLDSLZZSD is the rate of agricultural labor productivity increase.

Building population subsystem and establishing storage and flow relation

The population subsystem traffic volume relationship built in the Vensim PLE platform is shown in FIG. 6. The specific equations are shown in the appendix. The following are the ideas and methods for constructing the modules involved in the subsystem:

(1) level of fertility

The maximum population size which can be carried by the limitation of resource environment capacity is assumed to be x_mWhen x grows to x_mTime, population growth rate r (x)_m) When s is equal to r/x, r is equal to 0_mThen, r (x) is obtained as r (1-x/x)_m). Thus, in the model canWill be in the formula of 1-x/x_mThe "part of the population growth retardation factor (RKZZZZZZXS) has certain influence on the birth rate of urban population and rural population.

(2) Urban and rural population

The 'urban 0-14 year population' has two input streams and two output stream variables, wherein the input streams comprise 'annual urban population birth weight (NCSRKCSL)' reflecting the natural birth condition of the urban population and 'urban transition 0-14 year population (CSZRRK)' reflecting the flow of the urban and rural population_0-14) "; included in the output stream is "City 0-14 years of population mortality (CSRKSWL) reflecting the status of death in that age group_0-14) And the city of the current year is 14 years old, the population is transferred to the group of ' city 15-64 years old ' in the next year due to age increase after deducting death number, and becomes ' city 15-64 years old population increment (CSRKZL)_15-64) "source of the composition.

There are also two input streams and two output stream variables for the "city 15-64 years old population", one of which is the output stream "city 15-64 years old population increment" from the last year city 14 years old population, i.e., the "city 0-14 years old population" group, and the other is the "city transfer 15-64 years old population (CSZRRK) reflecting the urban and rural population mobility_15-64) "; included in the output stream is "City 15-64 years old population mortality (CSRKSWL) reflecting the status of death in this age group_15-64) And the city 64 years old population in the current year is transferred to the group of ' city 65 years old and over ' population in the next year after the death number is deducted to become ' city 65 years old and over population increment (CSRKZL)_≥65) "source of the composition. The model uses "city 15-64 years old population" as the working age-appropriate population, which becomes the source of second and third industry labor force variation, whereby the population subsystem is interconnected with the economic subsystem.

The 'city population 65 years old and above' has two input streams and one output stream variable, wherein one of the input streams is an output stream 'city population 65 years old and above' derived from the last year city population 64 years old, namely 'city population 15-64 years old' group, and the other input stream is 'city transition population 65 years old and above' (CSZRRK)_≥65) "; transfusion systemThe outflow is "urban aged population mortality (CSLLRKSWL)" reflecting the death status of this age group. The proportion of the population of 65 years old or more in cities in urban population, namely the proportion of the population of the urban aged population, becomes an important component of the total population of the national aged population.

The 'village 0-14 year old population' has an input stream and an output stream variable, wherein the input stream is 'annual village population birth weight (NXCRKCSL)' reflecting the natural birth condition of the village population; one of the output streams is "Country 0-14 years old population mortality (XCRKSWL) reflecting the status of death in this age group_0-14) 'secondly, the 14-year-old population in the country of the year, which is shifted to the' Country 15-64-year-old population 'group in the next year due to age increase after deducting the death number, becomes' Country 15-64-year-old population increment (XCRKZL)_15-64) "the origin of the three is" Country 0-14 year old transferred population (XCZCRK)_0-14) "same as" city shift to 0-14 years old ".

There is also one input stream and three output stream variables for the "Country 15-64 year old population", the input stream originating from the 14 year old population in the Country of the last year, i.e., the output stream "Country 15-64 year old population increment" in the group "Country 0-14 year old population"; one of the output streams is "Country 15-64 years old population mortality (XCRKSWL) reflecting the status of death in this age group_15-64) ' secondly, the population of the country of 64 years old in the current year is switched into the group of ' the population of 65 years old and over ' in the country in the next year after deducting the death number, and becomes ' the population increment of 65 years old and over ' in the country (XCRKZL)_≥65) "the origin of the three is the" Country 15-64 years old transferred population (XCZCRK) reflecting the mobility of the urban and rural population_15-64) "same as" city shift into 15-64 years old population ". The model uses "rural 15-64 year old population" as the working age-appropriate population, which becomes the source of the first industry labor force variation population, on the basis of which the population subsystem is interconnected with the economic subsystem.

"Country population 65 years old and older" one input stream and two output streams, the input stream is derived from the previous year Country population 64 years old, i.e., "Country population 15-64 years old" group output stream "Country population 65 years old and older population increment"; one of the output streams reflects death of this age groupThe "country aged population death (XCLLRKSWL)" in the state, and the "country transit population (XCZCRK) of 65 years old or more" reflecting the mobility of the urban and rural population_≥65) "same as" city shifted to 65 years old and older ". The proportion of population of 65 years old and above in villages, namely the proportion of population of the village aged population, becomes another major component of the population of the nationwide aged population.

(3) Floating population

On the basis of estimation of urban population transfer to rural and urban (NXCZYCSRKL), according to the proportion of the population of each age group of rural and urban to the population of rural and urban respectively, the population is distributed to the age groups of rural to be transferred to cities, and the population of each age group of cities is transferred from rural to urban.

Building social development subsystem and establishing storage flow relation

The memory-flow relationship of the social development subsystem constructed in the Vensim PLE platform is shown in FIG. 7. The specific equations are shown in the appendix. The following are the ideas and methods for constructing the modules involved in the subsystem:

(1) level of education

In the module, ten thousand students in middle and primary cities have the teacher number which is the ratio of the teacher number in the middle and primary Cities (CSZXXJSX) to the student number in the middle and primary Cities (CSZXXXSS), wherein the teacher number in the middle and primary cities and the student number in the middle and primary cities are both subjected to curve estimation by being associated with urban population. The population of the college and academic calendars was estimated by correlating with the average population gdp (rjgdp) curve. In addition, the educational development factors are set in the model as adjustable variables, the adjustable variables are related to the number of teachers in primary and secondary schools in cities and the total number of colleges and the school calendars, and the development trends of different educational comprehensive levels and the influence of the development trends on the urbanization process can be reflected by adjusting the sizes of the educational development factors.

(2) Medical level

The model relates the number of urban health technicians to the urban population and performs curve estimation. Setting a medical development factor (YLFZYZ) as an adjustable variable, relating the adjustable variable with the number of urban health technicians, and reflecting the development trends of different medical comprehensive levels and the influence of the development trends on the urbanization process by adjusting the size of the medical development factor.

(3) Output of innovation

And establishing a relation between the patent authorization number and the full-time equivalent of scientific and technical personnel, the direct investment amount of foreign merchants and the research and experimental development expenditure by adopting a knowledge production function. Wherein, the scientific and technical personnel full-time equivalent, the direct investment amount of foreign merchants and the expenses of research and experimental development are all estimated by correlating with the total value of domestic production.

Constructing a water resource subsystem and establishing a storage flow relation

The water resource subsystem storage and flow relationships built in the Vensim PLE platform are shown in FIG. 8. The specific equations are shown in the appendix. The following are the ideas and methods for constructing the modules involved in the subsystem:

(1) water resource supply

The development and utilization of water resources depend on the total water resource amount (SZYZL) and the water resource development utilization rate (SZYKFLYL), the total water resource amount is obtained by the sum of the surface water resource amount (DBSZYL) and the underground water resource amount (DXSZYL) and deducting the repeated amount of the surface water and the underground water resource (DBSSSCFL), and the value is calculated by taking the average value of data in 1956 and 2017 years so as to reduce the influence caused by climate fluctuation. The water resource development utilization rate, namely the ratio of the actual development utilization water amount to the total water resource amount, is set as a table function of time according to the historical data conditions of 1998 + 2017 to reflect the change of the water resource development utilization conditions at different stages, and the water resource is allocated overseas, for the water-deficient area, related sources such as water transfer engineering water resources and emergency water resource allocation can be included, but for the national scale, the water source is not considered for the moment, so the value is set to 0. The water quantity of the rain collecting project is small in annual variation amplitude, has no obvious rule and is small in proportion in the total water resource supply amount, so that the average value of the historical data of many years is adopted. The desalination amount of seawater is small in proportion to the total water resource supply amount, and extrapolation simulation is carried out according to the general trend of historical data for many years. The quantity of the reclaimed water resources is determined by the total waste water discharge quantity (FWSPFLZ) and the reclaimed water reuse rate (ZSHYL), wherein the reclaimed water reuse rate represents the proportion of the reclaimed water resources which can be recycled after being treated in the total waste water discharge quantity. Under the effect of the progress of the sewage treatment technology, the reuse rate of the reclaimed water generally shows the trend of improving year by year.

(2) Water resource demand

Agricultural water demand in the module comprises farmland irrigation water demand (NTGGXS) and forestry and animal husbandry water consumption (LMYYS), the farmland irrigation water demand depends on a farmland irrigation quota (NTGGDE) and a cultivated land effective irrigation area (GDYXGGMJ), the forestry and animal husbandry water consumption (LMYYS) depends on a forestry and animal husbandry irrigation quota (LMYGGDE) and the sum of areas of a woodland, a grassland and a water area, and the forestry and animal husbandry water consumption are respectively associated with a land subsystem through areas of non-construction lands such as cultivated land, the woodland, the grassland and the water area. The industrial water demand, namely the water quantity which meets the direct and indirect use in the industrial production, depends on an industrial added value (GYZJZ) and a ten-thousand-yuan industrial added value water demand (WYGYZJZXSL), wherein the former is simulated according to the proportion of the industrial added value in the past year to the total production branch in the current year and is associated with an economic subsystem, and the latter can be regulated and controlled through the reduction rate of the ten-thousand-yuan industrial added value water demand. The domestic water demand comprises urban domestic water (CZSHHYS) and rural domestic water (NCSHYS), wherein the former comprises resident domestic water and public water, and the latter is mainly resident domestic water, both of which are simulated by a per-capita domestic water quota method, and the urban and rural domestic water demand is respectively obtained on the basis of the estimation of urban and rural population by a population subsystem. The water demand of the ecological environment is simulated by the comprehensive growth rate (STHJXSNZHZZL) of the water demand of the ecological environment, and the later is an adjustable scene variable to reflect different trends of the water consumption of the ecological environment.

Further, when the total water demand exceeds the total water supply, a water demand gap (SZYGXQK) occurs, which is the water shortage (QSCD) that is the proportion of the total water demand. Correspondingly, the water resource shortage index (SZYDQZS) corresponding to the water shortage degree influences the population volume of the urban transferred from the rural to the annual and rural areas and the population growth retardation coefficient, thereby generating a negative feedback effect on the population growth and the population migration of the rural and urban areas and forming a certain constraint effect on the growth of the production values of the first, second and third industries.

(3) Water resource environment

The total amount of the discharged wastewater in the module is the sum of the total amount of the discharged industrial wastewater (GYFPSPZL) and the total amount of the discharged domestic wastewater (SHWSPFZL), and the discharge amount of the domestic wastewater and the discharge amount of the industrial wastewater are respectively estimated by setting a domestic wastewater discharge coefficient (SHWSPFXS) and an industrial wastewater discharge coefficient (GYFPXS) on the basis of simulating domestic water demand and industrial water demand by a water resource demand module. In addition, the total wastewater discharge is associated with the water resource supply module, and a basis is provided for simulating the renewable water resource amount. The discharge amount of chemical oxygen demand (HXYLPFL) is closely related to the total amount of wastewater and is estimated by the discharge coefficient of chemical oxygen demand (HXYLPFFS). With the improvement of sewage discharge treatment technology and standard, the discharge coefficient of domestic sewage, the discharge coefficient of industrial wastewater and the discharge coefficient of chemical oxygen demand generally show a decreasing trend.

Constructing a land utilization subsystem and establishing a storage flow relation

The land use subsystem inventory flow relationship constructed in the Vensim PLE platform is shown in FIG. 9. The specific equations are shown in the appendix. The following are the ideas and methods for constructing the modules involved in the subsystem:

(1) land for non-construction

Cultivated area (GDMJ) is simulated according to grain demand (LSXQ), cultivated grain yield per unit (GDLSDC), multiple cropping index (FZZS) and grain crop specific sowing weight (LSZNZWBZBZ), wherein the grain demand depends on grain self-sufficiency (LSZJL), per-capita grain occupancy (RJLSZYL) and general population variation, and thus is associated with population subsystems. In the grain production process, the farmland needs to be effectively irrigated, the agricultural water is required, and the agricultural water is associated with a water resource subsystem. The forest area (LDMJ) is modeled by the population and average forest occupancy (RJSLZYL) and is associated with population subsystems. The pasture area (MCDMJ) is determined from meat demand (CRXQ) and pasture per unit area meat yield (DWMJMCDCRCL), where meat demand varies depending on the general population and the average human meat demand (RJCRXQL), and is associated with population subsystems. The water area (SYMJ) is estimated based on the aquatic product demand (SCPXQ), which varies depending on the population and the average human livestock meat demand (RJCRXQL), and the water yield per unit area (dwmjsyscclc), which is associated with population subsystems. The development of forestry, animal husbandry and fisheries involves the water demand for forestry, animal husbandry and fisheries, such as irrigation water for forestry, and water replenishment on aquaculture surfaces, and thus, the woodland, pasture and water areas are also associated with the water resource subsystem. Furthermore, arable land, woodland, pasture land and water areas will collectively serve as agricultural land, being associated with economic subsystems by becoming an element of land production invested in first industry growth.

(2) Land for construction

The urban residential land area (CSJZYDMJ) is closely related to the size of the residential building area requirement (ZFJZMJXQ) and the residential land conversion coefficient (JZYDZHXS), wherein the former is simulated according to the change of urban population and the average residential building area (RJZFJZMJ), and the latter is equivalent to the comprehensive volume ratio, and the type of land is related to the population subsystem. The urban industrial land area (CSGYYDMJ) is determined by an industrial increment value, an industrial land average yield value (GYYDDJCZ) and a second industry fixed asset investment (DECYGDZCTZ), and the equation is determined by adopting a least square regression method, wherein the land is an important production input element in the growth of the second industry and is associated with an economic subsystem. The urban third industry land area (CSDSCYYDMJ) is simulated based on the third industry increment value, the urban third industry land area average yield value (CSDSCYYDDJCZ) and the third industry fixed asset investment (DSCYGDZCTZ), the equation is determined by adopting a least square regression method, and the land is an important production input element in the third industry growth and is associated with an economic subsystem. The urban road traffic infrastructure land area (CSDLJTSSYDMJ) is determined primarily from motor vehicle occupancy (JDCBYL), which is determined from population wide and average motor vehicle occupancy (RJJDCYYL), wherein the average motor vehicle occupancy is a function of the average GDP, is estimated based on Gompertz models, and is influenced by motor vehicle policy intervention (JDCZCGY) preferences, which type land is associated with population and economic subsystems. The village and town construction land area (CZJSYMJ) is related to the rural population and the rural population construction land area (NCRJJJSYD), and is related to population subsystems. In addition, the proportion of the total amount of construction land (JSYDZL) to the total land area (TDZMJ) is the land development intensity (GTKFQD), when the land development intensity exceeds a target constraint value, the intensive utilization level of the construction land needs to be further improved, and at the moment, the intensive utilization factor of the construction land (JSYDJYLYYYYZ) can act on variables related to various requirements of the construction land, such as a conversion coefficient of the residential land, an average output value of the urban industrial land, an average output value of the urban third industrial land and the like, so that the influence of the intensive utilization of the land on the land scale is reflected, and the excessive land development requirement is limited.

Constructing energy subsystem and establishing storage flow relation

The energy subsystem traffic flow relationship constructed in the Vensim PLE platform is shown in FIG. 10. The specific equations are shown in the appendix. The following are the ideas and methods for constructing the modules involved in the subsystem:

(1) energy supply

The coal production (MTSCL), the oil production (SYSCL), the natural gas production (TRQSCL) and the non-fossil energy production (FHSSNYSCL) are all horizontal variables, and the production change conditions of the coal production increase rate (MTSCZLL), the oil production increase rate (SYSCZLL), the natural gas production increase rate (TRQSCZL) and the non-fossil energy production increase rate (FHSSNYSCZL) are controlled respectively. The module is associated with the energy consumption module through an energy supply and demand gap so as to form a constraint effect on the economic subsystem, and is associated with the energy environment subsystem through carbon dioxide emission of fossil energy such as coal, petroleum and natural gas.

(2) Consumption of energy

The energy consumption of the tertiary industry depends on the total domestic production value increase and the total ten thousand yuan domestic production value energy consumption intensity (WYGDPNHQD) change conditions, wherein the total ten thousand yuan domestic production value energy consumption intensity is determined by a scientific and technological progress factor based on a knowledge production function and a total ten thousand yuan domestic production value energy consumption intensity reduction target, and reflects the important effect of the technical progress on reducing the energy consumption intensity. The tertiary industrial energy consumption is related to an economic subsystem and a social development subsystem through a domestic total production value and a technological progress factor. The living energy consumption is the sum of urban living energy Consumption (CSSHNYXFL) and rural living energy consumption (NCSHNYXFL), wherein the former is determined according to urban population and urban per-capita living energy Consumption (CSRJSHNYXFL), and the latter is determined according to rural population and rural per-capita living energy consumption (NCRJSHNYXFL). The living energy consumption is related to the population subsystem through urban population and rural population, and is related to the economic subsystem through urban-person-all-dominant income (CSRJKZPSR) and rural-person-all-pure income (NCRJCSR). Energy consumption of transportation is mainly considered due to transportation of motor vehicles, rapid increase of the quantity of motor vehicles is the main reason of energy consumption increase of transportation, and railway, water transportation and civil aviation transportation are limited by data acquireability and are not considered. In the model, the relation between the traffic transportation energy consumption and the motor vehicle holding capacity is estimated by adopting a logarithmic function curve, and the energy consumption is related to an economic subsystem through the human-average GDP.

In addition, when the energy consumption exceeds the energy supply, an energy supply and demand gap occurs, and the proportion of the energy consumption is the energy shortage degree. Accordingly, the energy shortage index corresponding to the energy shortage degree will have a certain constraint effect on the increase of the second industry and the third industry by influencing the increase of the second industry and the increase of the third industry.

(3) Energy environment

Carbon dioxide emissions are mainly due to fossil energy usage and, therefore, carbon dioxide emissions (CO)₂PFL) as carbon dioxide emissions (MTCO) of coal₂PFL), petroleum carbon dioxide emissions (SYCO)₂PFL) and natural gas carbon dioxide emissions (TRQCO)₂PFL). And estimating the emission of carbon dioxide related to various energy sources by adopting a carbon dioxide emission coefficient method. Emission of sulfur dioxide (SO)₂PFL) is mainly determined by coal consumption and coal desulfurization technology progress, wherein the unit coal desulfurization efficiency is influenced by technological progress factors and is associated with a social development subsystem.

As shown in fig. 11, a general diagram of the dynamic model storage/discharge relationship of the territorial space planning system is shown.

Model parameter setting

The parameter setting can be based on the following 8 methods, and the parameter assignment is shown in the appendix:

(1) cobb-douglas production function: the method is mainly used for determining the capital and labor elasticity coefficients simulating the growth of the first, second and third industries, the elasticity coefficient of the agricultural land for the growth of the first industry, the elasticity coefficient of the urban industrial land for the growth of the second industry and the elasticity coefficient of the urban third industrial land for the growth of the third industry.

(2) Linear regression: establishing a one-element or multi-element linear regression relation based on a least square method, such as estimating the urban total fertility rate, the rural total fertility rate, the urban population birth rate and the rural population birth rate; and the urban industrial land area, the urban third-generation industrial land area and the like are simulated.

(3) And (3) curve estimation: according to the data characteristics, the estimation is carried out by adopting forms of power functions, exponential functions, quadratic functions and the like, such as the simulated owned quantity of the motor vehicles in the population and the area of urban road traffic facilities.

(4) Knowledge production function: the method is mainly used for simulating patent authorization numbers and determining the elastic coefficient of innovation input elements.

(5) Table function: parameters are input in the VensimP PLE, and special nonlinear relations or response relations among variables are reflected.

(6) (piecewise) arithmetic mean method: taking the arithmetic mean value according to the historical data of 1998 + 2017, it should be noted that for the part variables with different trends in different periods, such as the growth rate of the first, second and third industrial production values, different mean values can be taken in different periods in combination with the form of the table function to reflect the stage characteristics.

(7) Trend extrapolation: the trend of the change of the data over time is fitted according to the history data of 1998 and 2017.

(8) Literature value assignment method: the carbon dioxide emission coefficient of coal, petroleum and natural gas can be directly determined based on related classical research literature.

Model inspection

(1) Inventory flow verification

The dynamic model of the national territorial space planning system constructed by the invention is subjected to storage and flow rate inspection, and is shown in table 11. Firstly, a 1998-year numerical value which can be obtained by a variable is taken as a system initial state, system simulation is carried out on Vensim PLE according to preset parameters, and the simulation time range is 1998-2017. Secondly, selecting key variables from the model, comparing the difference between the annual actual value and the simulated value of each variable, and calculating the relative error rate. In general, the fitting degree of the simulation value and the actual value of the critical variable of each subsystem is good, the average relative error rate does not exceed +/-5%, and the modeling requirement is met.

Table 11 model inventory verification results

Therefore, the dynamic model of the territorial space planning system constructed by the method has good simulation effect, and can reflect the social and economic driving process suffered by the development and utilization of the territorial space and the energy and ecological stress effect.

(2) Sensitivity analysis

Selecting a plurality of parameters from each subsystem of a dynamic model of a national space planning system, increasing or reducing the numerical value of the parameter in the year of 1998 + 2050 by 10 year by year, respectively calculating the key points of the parameter change on the total value of domestic production, general population, urbanization level and the like, and relatively speaking, the parameters which have relatively large influence on the total value of domestic production mainly comprise the change rate of the mean production value of the third production land in the city, the increase rate of the increase value of the third production, the increase rate of the increase value of the second industry, the increase rate of non-fossil energy production and the increase rate of coal production. The parameters which have great influence on the general population mainly comprise the total fertility rate, the urban population birth rate, the rural population birth rate, the food self-sufficiency rate and the like. Parameters that have a large impact on the urbanization level include the birth rate of rural population, education factors, the water demand quota for urban average life and the food self-supply rate.

From the sensitivity mean value, the sensitivity of only a part of parameters is more than 10%, the influence on the system global is relatively large, and the sensitivity of most parameters is not more than 10%, namely, the model is not sensitive to the value change of most parameters, thereby having good stability and robustness.

The influence degree of the variable is sensitivity, and the sensitivity mean value is used as the sensitivity analysis result of the model to the parameter change. The sensitivity calculation method is as before.

TABLE 12 results of model sensitivity analysis

Model multi-scenario simulation application

Firstly, determining scene indexes from three levels of urbanization development, water and soil ecological stress and energy constraint. The indexes in the urbanization development aspect are GDP annual growth rate, total fertility rate, education development factors reflecting the culture level of urban elementary education teachers and higher education talents and medical development factors reflecting the allocation level of health technicians. The indexes of the water and soil ecology stress represent the water resource utilization and stress by the total water resource supply control target, the farmland irrigation quota, the ten thousand yuan industry added value water demand, the per-capita life water demand quota, the ecological environment water demand year comprehensive growth rate and the reclaimed water reuse rate, and represent the land utilization and stress by the grain self-supply rate, the per-capita forest occupation amount, the unit area water area aquatic product yield, the unit area grassland livestock meat yield, the town per-capita housing building area, the urban industrial land area average output value and the urban third production land area average output value. In the aspect of energy constraint, a situation is constructed by combining various control variables such as coal production peak year and production increase rate, petroleum production increase rate, natural gas production increase rate, proportion of non-fossil energy production to total energy, and a ten thousand yuan domestic production total value energy consumption intensity reduction target.

Secondly, the situation parameters can be determined according to the analysis of related research at home and abroad on the index trend or by combining policy objectives, related planning and the like. In the embodiment, 3 types of schemes of low economy, medium economy and high-speed growth are set through different combinations of the control variables, and 2 specific scenes (table 13) are respectively set according to different indexes under each type of scheme so as to reflect the ecological and energy constraint trends of the utilization of the Chinese soil space under different scenes in 2020 + 2050.

TABLE 13 Multi-scenario design for territorial space planning

Multi-scenario simulation results

Because the model has more related variables, the simulation result of the key variables of each subsystem is taken as an example here to explain the simulation result of the model in multiple situations.

In the economic subsystem, as for the GDP (with the constant price in 2017), under the situation of not considering the energy-ecological constraint, the increase in 2050 is 44159-52275 dollars, and if the GDP in the United states keeps an annual increase level of 1.6% in the future, the GDP in China is about 44.34% -52.49% relative to the United states level at that time. Under the situation of considering energy-ecological constraint, the GDP of the Chinese population is improved to 27962-.

In the population subsystem, if the future total fertility rate is maintained at 1.3-1.4, the Chinese population will reach the peak value in 2028 + 2029, the scale is about 143530-144287 ten thousand, and after that, the negative increase is started, the population is reduced to 135482-137499 ten thousand by 2050, and the proportion of the aged population at 65 years and above is about 29.08% -29.36% of the total population. If the future fertility rate is maintained at 1.5-1.6, the Chinese population reaches the peak value in 2030-year 2031, the scale is about 145108-year 145996-year, the negative increase starts from this point, the population is reduced to 139493-year 141446-year by 2050, and the aging degree reaches about 28.55-28.80%. If the future fertility rate is maintained at 1.7-1.8, the Chinese population reaches the peak value in 2033-4 years, the scale is about 146959-148000-ten-thousand, the negative growth starts from the end, the population is reduced to 143371-145266-ten-thousand-year in 2050, and the aging degree reaches about 28.07-28.29%.

In the water resource subsystem, the total water demand of China in 2020-. The maximum water demand can be controlled to be about 6200 hundred million m³About 5755.84-6081.37 hundred million m in 2050³Far less than 6700 hundred million m of comprehensive plan of water resources nationwide³The target within.

In the land utilization subsystem, the total quantity of the construction land for each scene is increased to different degrees along with the improvement of the urbanization level in the future. The total amount of construction land in 2050 is 3978.32-4146.76 kilohm²Compared with the net increase of 130.44-282.16 kilohm in 2020². The cultivated land in the year of 2050 of 2020 and the year of 2050 of 2020 is reduced to 11718.60-12144.70 kilohm². Ecological land shows the general trend of increasing first and then decreasing. Wherein, the forest land is obviously increased under strict protection, and the growth in 2050 is 29318.00-30182.30 ten thousand hm²(ii) a The pasture is increased firstly and then reduced, and the pasture is about 27433.90-28216.60 kilohm in 2050²(ii) a The water area is not reduced or even slightly increased, and about 4270.85-4384.79 ten thousand hm in 2050²。

In the energy subsystem, the overall trend of energy consumption in 2020-. The energy consumption center of gravity is changed from production demand to life demand, the energy consumption of tertiary industry is increased and then reduced, and the energy consumption of life and transportation is increased continuously. The total energy consumption by 2050 is about 510831-544350 ten thousand tce, wherein the three-time industrial energy consumption is about 379767-403259 ten thousand tce, the domestic energy consumption is about 81893-92754-tce, and the transportation energy consumption is about 49170-50123-tce.

According to the dynamic modeling method for the territorial space planning system for realizing planning scenario simulation, provided by the embodiment of the invention, planning multi-scenario design and simulation can be carried out aiming at different aspects such as water resource utilization, territorial development protection, energy system transformation and the like, so that under the macro background of currently promoting high-quality development, beautiful Chinese construction and the like, scientific and reasonable scale and structural arrangement are carried out on relevant elements of the territorial space complex giant system by auxiliary planning, and a scientific, quantitative, qualitative and quantitative combined simulation model tool is provided for the territorial space planning scheme and planning implementation evaluation.

Next, a dynamic modeling device of a territorial space planning system for realizing planning scenario simulation according to an embodiment of the present invention is described with reference to the accompanying drawings.

Fig. 12 is a schematic structural diagram of a dynamic modeling device of a geospatial planning system for implementing planning scenario simulation according to an embodiment of the present invention.

As shown in fig. 12, the dynamic modeling apparatus 10 for a geospatial planning system that implements a planning scenario simulation includes: a boundary determination module 100, a subsystem creation module 200, an internal association module 300, a parameter determination module 400, a verification module 500, and a simulation module 600.

The boundary determining module 100 is configured to determine a boundary of the model system according to a plurality of elements of the homeland space and a multidimensional architecture of the homeland space planning model. And the subsystem establishing module 200 is used for establishing an economic subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem and an energy subsystem of the territorial space planning model and determining the key variable composition of the territorial space planning model. And the internal association module 300 is used for establishing the relationship between the inside of the subsystem and the subsystem according to the new classical economic and water-land-energy connection relation theory, constructing a cause-effect structure diagram of the system and drawing a storage flow relation diagram of variable elements. And the parameter determining module 400 is used for determining parameters and initialization conditions of the territorial space planning model and inputting the relationship between the parameters and the equation. And the inspection module 500 is used for inspecting the territorial space planning model through model storage flow rate inspection and sensitivity analysis and judging the territorial space planning model performance. And the simulation module 600 is configured to design and simulate a territorial space planning scenario through the examined territorial space planning model.

Optionally, in one embodiment of the present invention, the plurality of elements includes: natural resource and asset variable elements, economic input and output variable elements, social development and service variable elements and environmental impact and stress variable elements; the multi-dimensional architecture includes: production function dimensions, element flow support dimensions, development policy dimensions, and external condition constraint dimensions.

Optionally, in one embodiment of the invention, the economic subsystem comprises industry value, capital inventory, labor;

the population subsystem includes: urban and rural population segments;

the social development subsystem comprises: educational development, medical development and innovation output parts;

the water resource subsystem includes: water resource supply, water resource demand, and water resource environment segments, and is associated with population, economic, and land subsystems;

the land utilization subsystem comprises: the construction land and the non-construction land are associated with a population subsystem, an economic subsystem and a water resource subsystem;

the energy subsystem includes: energy supply, energy consumption and energy environment, and is associated with population subsystems and economic subsystems.

Optionally, in one embodiment of the invention, the input parameters and the equation relationship comprise: input parameters and equation relationships are entered using a perpetual inventory method, a cobb-douglas production function, linear regression, curve estimation, a knowledge production function, a table function, an arithmetic mean method, a trend extrapolation method, and a document assignment method.

Optionally, in an embodiment of the present invention, the checking module is further configured to analyze whether the territorial space planning model can accurately reflect the historical state change through a traffic flow check, and check a change degree of the territorial space planning model simulation calculation result when the parameter value is changed through a sensitivity analysis.

It should be noted that the foregoing explanation of the method embodiment is also applicable to the apparatus of this embodiment, and is not repeated herein.

According to the dynamic modeling device of the territorial space planning system for realizing planning scenario simulation, provided by the embodiment of the invention, planning multi-scenario design and simulation can be carried out aiming at different aspects such as water resource utilization, territorial development protection, energy system transformation and the like, so that under the macro background of currently promoting high-quality development, beautiful Chinese construction and the like, scientific and reasonable scale and structural arrangement are carried out on relevant elements of a territorial space complex giant system by auxiliary planning, and a scientific, quantitative, qualitative and quantitative combined simulation model tool is provided for the territorial space planning scheme and planning implementation evaluation.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (10)

1. A dynamic modeling method for a territorial space planning system for realizing planning scenario simulation is characterized by comprising the following steps:

determining a model system boundary according to a plurality of elements of the territorial space and a multi-dimensional architecture of the territorial space planning model;

constructing an economic subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem and an energy subsystem of the territorial space planning model, and determining the key variable composition of the territorial space planning model;

establishing the relationship between the inside of the subsystems and the subsystems according to the new classical economy and water-land-energy connection relation theory, constructing a cause-effect structure diagram of the system, and drawing a storage flow relation diagram of variable elements;

determining parameters and initialization conditions of the territorial space planning model, and inputting the relationship between the parameters and an equation;

the territorial space planning model is checked through model flow storage and discharge inspection and sensitivity analysis, and the territorial space planning model performance is judged;

and carrying out territorial space planning scene design and simulation through the examined territorial space planning model.

2. The method of claim 1,

the plurality of elements includes: natural resource and asset variable elements, economic input and output variable elements, social development and service variable elements and environmental impact and stress variable elements;

the multi-dimensional architecture comprises: production function dimensions, element flow support dimensions, development policy dimensions, and external condition constraint dimensions.

3. The method of claim 1,

the economic subsystem comprises industrial production value, capital stock, labor force;

the population subsystem includes: urban and rural population segments;

the social development subsystem comprises: educational development, medical development and innovation output parts;

the water resource subsystem includes: a water resource supply, a water resource demand, and a water resource environment component, and associated with the population subsystem, the economic subsystem, and the land subsystem;

the land use subsystem comprises: the construction land and the non-construction land are partially associated with the population subsystem, the economic subsystem and the water resource subsystem;

the energy subsystem includes: energy supply, energy consumption and energy environment, and is associated with the population subsystem and the economic subsystem.

4. The method of claim 1, wherein the input parameters and equation relationships comprise: input parameters and equation relationships are entered using a perpetual inventory method, a cobb-douglas production function, linear regression, curve estimation, a knowledge production function, a table function, an arithmetic mean method, a trend extrapolation method, and a document assignment method.

5. The method of claim 1, wherein the testing the territorial space planning model by model inventory flow testing and sensitivity analysis comprises:

and analyzing whether the territorial space planning model can accurately reflect the historical state change or not through the flow storage inspection, and testing the change degree of the territorial space planning model simulation calculation result when the parameter value is changed through the sensitivity analysis.

6. A dynamic modeling device of a territorial space planning system for realizing planning scenario simulation is characterized by comprising the following components:

the boundary determining module is used for determining the boundary of the model system according to the plurality of elements of the territorial space and the multi-dimensional architecture of the territorial space planning model;

the subsystem building module is used for building an economic subsystem, a population subsystem, a social development subsystem, a water resource subsystem, a land utilization subsystem and an energy subsystem of the territorial space planning model and determining the key variable composition of the territorial space planning model;

the internal association module is used for establishing the relationship between the inside of the subsystem and the subsystem according to the new classical economic and water-land-energy connection relationship theory, constructing a cause-and-effect structure diagram of the system and drawing a storage flow relationship diagram of variable elements;

the parameter determination module is used for determining parameters and initialization conditions of the territorial space planning model and inputting the relationship between the parameters and an equation;

the inspection module is used for inspecting the territorial space planning model through model storage flow rate inspection and sensitivity analysis and judging the performance of the territorial space planning model;

and the simulation module is used for carrying out the design and simulation of the territorial space planning scene through the examined territorial space planning model.

7. The apparatus of claim 6,

the plurality of elements includes: natural resource and asset variable elements, economic input and output variable elements, social development and service variable elements and environmental impact and stress variable elements;

the multi-dimensional architecture comprises: production function dimensions, element flow support dimensions, development policy dimensions, and external condition constraint dimensions.

8. The apparatus of claim 6,

the economic subsystem comprises industrial production value, capital stock, labor force;

the population subsystem includes: urban and rural population segments;

the social development subsystem comprises: educational development, medical development and innovation output parts;

the water resource subsystem includes: a water resource supply, a water resource demand, and a water resource environment component, and associated with the population subsystem, the economic subsystem, and the land subsystem;

the land use subsystem comprises: the construction land and the non-construction land are partially associated with the population subsystem, the economic subsystem and the water resource subsystem;

the energy subsystem includes: energy supply, energy consumption and energy environment, and is associated with the population subsystem and the economic subsystem.

9. The apparatus of claim 6, wherein the input parameters and equation relationships comprise: input parameters and equation relationships are entered using a perpetual inventory method, a cobb-douglas production function, linear regression, curve estimation, a knowledge production function, a table function, an arithmetic mean method, a trend extrapolation method, and a document assignment method.

10. The device according to claim 6, wherein the checking module is further configured to analyze whether the territorial space planning model can accurately reflect the historical state change through the traffic storage amount check, and check a change degree of the calculation result simulated by the territorial space planning model when the parameter value changes through the sensitivity analysis.

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