Regional water safety-oriented water demand prediction method, electronic equipment and storage medium

Abstract

The invention discloses a regional water safety-oriented water demand prediction method, electronic equipment and a storage medium, and the method comprises the steps: firstly collecting an industrial water impact factor, a living water demand prediction impact factor, and an agricultural irrigation water demand prediction impact factor; then, a prediction equation for reflecting the future evolution trend of each influence factor is established for each influence factor, then an industrial water demand prediction model, a living water demand prediction model and an agricultural irrigation water demand prediction model are established, and the water demand prediction models are subjected to validity inspection; and finally, performing water demand prediction on a to-be-predicted area by using the inspected water demand prediction model to obtain a water demand prediction result. According to the method, economic driving, social influence, climate change and other factors are fully considered, the water demand change mechanism is researched from the internal structure of the system, the problems that in existing water demand prediction, factor selection is not comprehensive, and the simulation effect is poor are solved, and the prediction effectiveness and accuracy are improved from the two aspects of the model structure and the prediction factors.

Description

Technical Field

[0001] The invention belongs to the field of water demand forecasting, and in particular relates to a water demand forecasting method, electronic equipment and storage medium oriented to regional water security. Background Art

[0002] Under the influence of complex factors such as the natural environment and the social environment, the water resource crisis is getting worse. At the same time, with the emergence of climate warming, resource shortages and global ecological problems, there is a more complex contradiction between sustainable development goals and water consumption, and the uncertainty faced by the water resource system has further increased. How to effectively solve the imbalance between water supply and demand is the key to achieving sustainable development. Therefore, the prediction of future water demand under a changing environment and the conduct of systematic and in-depth research work are not only to develop water demand prediction research theory, but also to promote the attention of water supply and demand planning, which involves many aspects such as sustainable development. Summary of the invention

[0003] In view of the problems existing in the prior art, the present invention provides a water demand forecasting method, electronic equipment and storage medium for regional water security, which can better cope with the water demand forecasting problem under different climate modes in a changing environment.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a water demand prediction method for regional water security, comprising the following steps:

[0005] S1. Collect influencing factors of industrial water demand, establish influencing factor prediction equations for each influencing factor of industrial water, and establish an industrial water demand prediction model based on the influencing factor prediction equations;

[0006] S2. Collect the influencing factors of domestic water demand prediction, establish a prediction equation for each of the influencing factors of domestic water demand prediction to reflect its future evolution trend, and establish a domestic water demand prediction model based on the prediction equation;

[0007] S3, collecting the influencing factors of agricultural irrigation water demand prediction, establishing a prediction equation for the water demand of each crop during its entire growth period, and then establishing an agricultural irrigation water demand prediction model;

[0008] S4. Predict the area to be tested according to the industrial water demand prediction model, the domestic water demand prediction model, and the agricultural irrigation water demand prediction model to obtain industrial water demand prediction results, domestic water demand prediction results, and agricultural irrigation water demand prediction results. Finally, the three water demand prediction results are added together to obtain the total water demand prediction result.

[0009] Furthermore, the aforementioned influencing factors of industrial water demand include: water consumption of industrial added value, industrial added value, per capita GDP, scientific research funding investment of industrial enterprises above designated size, and temperature.

[0010] Furthermore, the aforementioned influencing factors for domestic water demand prediction include: permanent population, per capita domestic water consumption, urban pipe network leakage rate, per capita GDP, and temperature.

[0011] Furthermore, the aforementioned influencing factors for agricultural irrigation water demand prediction include crop irrigation water demand per unit area, crop area, rainfall, and temperature.

[0012] Furthermore, in the aforementioned step S1, an influencing factor prediction equation is established for each industrial water influencing factor, including the following sub-steps:

[0013] S1.1. Use the logarithmic model to predict the gross industrial output value and obtain the prediction equation for the gross industrial output value, as follows

[0014] G I =m×ln(f×(tt 0 ))+n

[0015] Among them, G I represents the forecast value of industrial output, t represents the forecast time, t 0 represents the reference period, m, f, and n are all constants;

[0016] S1.2. Use the logistic regression model to predict the total population and obtain the population prediction equation as follows:

[0017]

[0018] Among them, N S represents the total population, NGR represents the natural population growth rate, t 0 represents the base time, WRCC is the water resources carrying capacity, representing the population growth scale of the region is limited by resource supply; WRCC = A(1-e -x ) f , A, x, and f are all constants; S1.3, using the logarithmic model to predict the development trend of regional GDP, the prediction equation of regional total GDP is obtained as follows:

[0019]

[0020] Among them, A and B are constants;

[0021] Divide the total GDP forecast by the total population to get the per capita GDP forecast:

[0022]

[0023] Among them, GDP t is the forecast result of GDP in year t;

[0024] S1.4. Establish a prediction equation for industrial water demand of 10,000 yuan, as follows:

[0025] WDI=(Ae T / 10 -1)×(BC·10 -4 ×GDPC-D·10 -3 ×RDM)

[0026] Among them, T represents temperature, GDPC represents regional GDP per capita, RDM represents regional public enterprise research and experiment expenditure, and A, B, C, and D all represent constants;

[0027] S1.5. Establish an industrial water demand prediction model, as follows:

[0028] WD ind =G I ×WDI

[0029] Among them, WD ind represents industrial water demand, G I WDI represents the gross industrial output value and it represents the water demand per 10,000 yuan of gross industrial output value.

[0030] Furthermore, in the aforementioned step S2, a prediction equation for reflecting the future evolution trend of each domestic water demand prediction influencing factor is established, including the following sub-steps:

[0031] S2.1. Establish the urbanization rate prediction equation as follows:

[0032]

[0033] Among them, 1 represents the urbanization rate, t 0 Identify the base time, Z and r are both constants;

[0034] S2.2. Establish a prediction equation for per capita living water demand of urban population. As follows:

[0035] WDC ci =(Ae -B·T +C)×GDPC+D,

[0036] Among them, T represents temperature, GDPC represents the per capita GDP of the region, and A, B, C, and D are all constants.

[0037] S2.3. Establish a prediction equation for per capita living water demand of rural population, as follows:

[0038] WDC coun -(Aln(T)-B)+Cln(GDPC)+D,

[0039] Among them, T represents temperature, A, B, C, and D represent constants;

[0040] S2.4. Establish a domestic water demand prediction model as follows:

[0041] WD D =δ×N S ×WDC ci +(1-δ)×N S ×WDC coun .

[0042] Furthermore, the aforementioned step S3 includes the following sub-steps:

[0043] S3.1. For each crop, establish a prediction equation for the water requirement during the entire growth period of the crop, as follows:

[0044]

[0045] Among them, k i Indicates the starting time t of the i-th growth period of crop A i The corresponding crop coefficient is represents the reference crop evapotranspiration corresponding to the growth period, S represents the crop planting area, and η represents the effective channel utilization coefficient of farmland;

[0046] The calculation method of reference crop evapotranspiration is as follows:

[0047]

[0048] Among them, T i represents the temperature at time i, a represents the temperature elasticity coefficient, b represents the temperature threshold, P represents the rainfall, e represents the rainfall evaporation correction coefficient, and E represents the evaporation conversion coefficient: P i and P j Respectively represent the rainfall at time i and time j, E 1 、E 2 and E 3 Indicates the rainfall evaporation conversion coefficient in different periods;

[0049] S3.2. Establish an agricultural irrigation water demand prediction model as follows:

[0050] WD arg =WD 1 +WD 2 +…WD A +…+WD N ,

[0051] Among them, WD arg represents the total water demand for agricultural irrigation, WD 1 Indicates the water requirement of crop 1 during its entire growth period, WD AIt represents the water requirement of crop A during its entire growth period, and N is the number of crop types considered.

[0052] Another aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described in the present invention when executing the computer program.

[0053] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of any one of the methods described in the present invention when executed by a processor.

[0054] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0055] 1. The present invention considers the water resource system as a complex system and constructs the water resource system using the system dynamics method, which can effectively explain the water use mechanism problem. It has the advantages of clear logic, simple structure, and easy implementation, and can improve the prediction efficiency.

[0056] 2. The present invention introduces climate factors into the water demand prediction model, adopts the three SSP climate scenario paths provided in CMIP6 (the Sixth International Coupled Comparison Program), and explores the evolution trend of water demand under different paths. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a flow chart of the present invention.

[0058] Figure 2 It is a system dynamics model diagram of the present invention.

[0059] Figure 3 The figures are the industrial, agricultural irrigation and domestic water demand results predicted by the present invention; in the figures, (a) is the industrial water demand result diagram, (b) is the agricultural irrigation water demand prediction result diagram, and (c) is the domestic water storage prediction result diagram.

[0060] Figure 4 This is a diagram showing the water demand results predicted by the present invention. DETAILED DESCRIPTION

[0061] In order to better understand the technical content of the present invention, specific embodiments are given and described as follows in conjunction with the accompanying drawings.

[0062] Various aspects of the invention are described herein with reference to the accompanying drawings, in which many illustrative embodiments are shown. The embodiments of the invention are not limited to those described in the accompanying drawings. It should be understood that the invention is implemented by any of the various concepts and embodiments described above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed in the invention are not limited to any implementation. In addition, some aspects disclosed in the invention may be used alone or in any appropriate combination with other aspects disclosed in the invention.

[0063] like Figure 1 As shown in the flow chart of the present invention, a water demand prediction method for regional water security is disclosed. The following steps S1 to S4 are performed for the area to be tested to obtain a total water demand prediction result:

[0064] S1. Collect influencing factors of industrial water demand, establish influencing factor prediction equations for each influencing factor of industrial water, and establish an industrial water demand prediction model based on the influencing factor prediction equations;

[0065] S2. Collect the influencing factors of domestic water demand prediction, establish a prediction equation for each of the influencing factors of domestic water demand prediction to reflect its future evolution trend, and establish a domestic water demand prediction model based on the prediction equation;

[0066] S3, collecting the influencing factors of agricultural irrigation water demand prediction, establishing a prediction equation for the water demand of each crop during its entire growth period, and then establishing an agricultural irrigation water demand prediction model;

[0067] S4. Predict the area to be tested according to the industrial water demand prediction model, the domestic water demand prediction model, and the agricultural irrigation water demand prediction model to obtain industrial water demand prediction results, domestic water demand prediction results, and agricultural irrigation water demand prediction results, and further obtain the total water demand prediction results.

[0068] refer to Figure 2 In step S1, the influencing factors of industrial water demand include: water consumption per unit of industrial added value, industrial added value, per capita GDP, scientific research funding investment of industrial enterprises above designated size, and temperature. The influencing factors of domestic water demand prediction include: permanent population, per capita domestic water consumption, urban pipe network leakage rate, per capita GDP, and temperature. The influencing factors of agricultural irrigation water demand prediction include crop irrigation water demand per unit area, crop area, rainfall, and temperature.

[0069] As a preferred embodiment of the present invention, in step S1, an influencing factor prediction equation is established for each industrial water influencing factor, including the following sub-steps:

[0070] S1.1. Use the logarithmic model to predict the gross industrial output value and obtain the prediction equation for the gross industrial output value, as follows

[0071] GI =m×ln(f×(tt 0 ))+n

[0072] Among them, G I represents the forecast value of industrial output, t represents the forecast time, t 0 represents the reference period, m, f, and n are all constants;

[0073] S1.2. Use the logistic regression model to predict the total population and obtain the population prediction equation as follows:

[0074]

[0075] Among them, N S represents the total population, NGR represents the natural population growth rate, t 0 represents the base time, WRCC is the water resources carrying capacity, representing the population growth scale of the region is limited by resource supply; WRCC = A(1-e -x ) f , A, x, and f are all constants; S1.3, using the logarithmic model to predict the development trend of regional GDP, the prediction equation of regional total GDP is obtained as follows:

[0076] Among them, A and B are constants;

[0077] Divide the total GDP forecast by the total population to get the per capita GDP forecast:

[0078]

[0079] Among them, GDP t This is the total GDP forecast result;

[0080] S1.4. Establish a prediction equation for industrial water demand of 10,000 yuan, as follows:

[0081] WDI=(Ae T / 10 -1)×(BC·10 -4 ×GDPC-D·10 -3 ×RDM)

[0082] Among them, T represents temperature, GDPC represents regional GDP per capita, RDM represents regional public enterprise research and experiment expenditure, and A, B, C, and D all represent constants;

[0083] The present invention establishes a prediction equation for industrial water demand per 10,000 yuan of industrial output value, which is based on the fact that the water demand per 10,000 yuan of industrial output value is related to the regional development level and the investment that can be made by industrial enterprises above a certain scale. At the same time, the impact of climate change on the water demand per 10,000 yuan of industrial output value is taken into account. By establishing a ridge regression model of temperature and historical 10,000 yuan of industrial water demand, the climate change influencing factor is obtained, and the climate change influencing factor is introduced into the prediction equation for water demand per 10,000 yuan of industrial output value.

[0084] S1.5. Establish an industrial water demand prediction model:

[0085] WD ind =G I ×WDI

[0086] Among them, WD ind represents industrial water demand, G I WDI represents the gross industrial output value and it represents the water demand per 10,000 yuan of gross industrial output value.

[0087] Further, as a preferred embodiment of the present invention, in step S2, a prediction equation for reflecting the future evolution trend of each domestic water demand prediction influencing factor is established, including the following sub-steps:

[0088] S2.1. Establish the urbanization rate prediction equation as follows:

[0089]

[0090] Among them, 1 represents the urbanization rate, t 0 Identify the base time, Z and r are both constants;

[0091] S2.2. Establish a prediction equation for per capita living water demand of urban population. As follows:

[0092] WDC ci =(Ae -B·T +C)×GDPC+D,

[0093] Among them, T represents temperature, GDPC represents the per capita GDP of the region, and A, B, C, and D are all constants.

[0094] S2.3. Establish a prediction equation for per capita living water demand of rural population, as follows:

[0095] WDC coun -(Aln(T)-B)+Cln(GDPC)+D,

[0096] Among them, T represents temperature, A, B, C, and D represent constants;

[0097] S2.4. Establish a domestic water demand prediction model as follows:

[0098] WDD =δ×N S ×WDC ci +(1-δ)×N S ×WDC coun .

[0099] Further, as a preferred embodiment of the present invention, step S3 includes the following sub-steps:

[0100] S3.1. For each crop, establish a prediction equation for the water requirement during the entire growth period of the crop, as follows:

[0101]

[0102] Among them, k i Indicates the starting time t of the i-th growth period of crop A i The corresponding crop coefficient is represents the reference crop evapotranspiration corresponding to the growth period, S represents the crop planting area, and η represents the effective channel utilization coefficient of farmland;

[0103] The calculation method of reference crop evapotranspiration is as follows:

[0104]

[0105] Among them, T i represents the temperature at time i, a represents the temperature elasticity coefficient, b represents the temperature threshold, P represents the rainfall, e represents the rainfall evaporation correction coefficient, and E represents the evaporation conversion coefficient: P i and P j Respectively represent the rainfall at time i and time j, E 1 、E 2 and E 3 Indicates the rainfall evaporation conversion coefficient in different periods;

[0106] S3.2. Establish an agricultural irrigation water demand prediction model, that is, add up the water requirements of various crops during the entire growth period, as follows:

[0107] WD arg =WD 1 +WD 2 +…WD A +...+WD N ,

[0108] Among them, WD arg represents the total water demand for agricultural irrigation, WD 1 Indicates the water requirement of crop 1 during its entire growth period, WD A It represents the water requirement of crop A during its entire growth period, and N is the number of crop types considered.

[0109] In the present invention, the prediction method of annual rainfall and temperature specifically includes: first simulating future climate scenarios, then downscaling the results through historical data, and finally simulating future rainfall and temperature under different carbon emission models using the downscaled results.

[0110] On the other hand, the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described in the present invention when executing the computer program.

[0111] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of any one of the methods described in the present invention when executed by a processor.

[0112] The present invention selects the results of Henan Province for comparative study. Figure 3 and Figure 4 is the prediction result of the water demand of the present invention, Figure 3 In the figure, (a) is the industrial water demand result diagram, (b) is the agricultural irrigation water demand prediction result diagram, and (c) is the domestic water storage prediction result diagram. It can be seen that the prediction flow process of the method of the present invention is close to the measured process. Therefore, it can be seen that the proposed method can effectively and integratedly predict regional water demand.

[0113] Although the present invention has been described above with preferred embodiments, it is not intended to limit the present invention. A person skilled in the art of the present invention may make various modifications and improvements without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the definition of the claims.

Claims

1. A water demand forecasting method for regional water security, characterized in that: The steps include: S1. Collect the influencing factors of industrial water demand, establish the influencing factor prediction equation for each industrial water influencing factor, and establish the industrial water demand prediction model according to the influencing factor prediction equation; S2. Collect the influencing factors of domestic water demand prediction, establish a prediction equation for each of the influencing factors of domestic water demand prediction to reflect its future evolution trend, and establish a domestic water demand prediction model based on the prediction equation; S3, collect the influencing factors of agricultural irrigation water demand prediction, establish the water demand prediction equation of each crop during the whole growth period, and then establish the agricultural irrigation water demand prediction model; S4. Predict the area to be tested according to the industrial water demand prediction model, the domestic water demand prediction model, and the agricultural irrigation water demand prediction model to obtain industrial water demand prediction results, domestic water demand prediction results, and agricultural irrigation water demand prediction results. Finally, the three water demand prediction results are added together to obtain the total water demand prediction result.

2. A method for water demand prediction for regional water security according to claim 1, characterized in that: The influencing factors of industrial water demand include: water consumption of industrial added value, industrial added value, per capita GDP, scientific research funding investment of industrial enterprises above designated size, and temperature.

3. A method for water demand prediction for regional water security according to claim 1, characterized in that: The influencing factors for the domestic water demand prediction include: permanent population, per capita domestic water consumption, urban pipe network leakage rate, per capita GDP, and temperature.

4. A method for water demand prediction for regional water security according to claim 1, characterized in that: The influencing factors for agricultural irrigation water demand prediction include crop irrigation water demand per unit area, crop area, rainfall, and temperature.

5. The method for water demand prediction for regional water security according to claim 1, characterized in that: In step S1, an influencing factor prediction equation is established for each industrial water influencing factor, including the following sub-steps: S1.

1. Use the logarithmic model to predict the gross industrial output value and obtain the prediction equation of the gross industrial output value, as follows: G I =m×ln(f×(t-t0))+n Among them, G I represents the forecast value of gross industrial output, t represents the forecast time, t0 represents the base period, and m, f, and n are all constants; S1.

2. Use the logistic regression model to predict the total population and obtain the population prediction equation as follows: Among them, N S represents the total population, NGR represents the natural population growth rate, t0 represents the base time, WRCC represents the water resources carrying capacity, and represents the regional population growth scale is limited by resource supply; WRCC = A(1-e -x ) f , A, x, and f are all constants; S1.3, using the logarithmic model to predict the development trend of regional GDP, the prediction equation of regional total GDP is obtained as follows: Among them, A and B are constants; Divide the total GDP forecast by the total population to get the per capita GDP forecast: Among them, GDP t is the forecast result of GDP in year t; S1.

4. Establish a prediction equation for industrial water demand of 10,000 yuan, as follows: WDI=(Ae T / 10 -1)×(BC·10 -4 ×GDPC-D·10 -3 ×RDM) Among them, T represents temperature, GDPC represents regional GDP per capita, RDM represents regional public enterprise research and experiment expenditure, and A, B, C, and D all represent constants; S1.

5. Establish an industrial water demand prediction model, as follows: WD ind =G I ×WDI Among them, WD ind represents industrial water demand, G I WDI represents the gross industrial output value and it represents the water demand per 10,000 yuan of gross industrial output value.

6. A method for water demand prediction for regional water security according to claim 1, characterized in that: In step S2, a prediction equation for reflecting the future evolution trend of each domestic water demand prediction influencing factor is established, including the following sub-steps: S2.

1. Establish the urbanization rate prediction equation as follows: Among them, 1 represents the urbanization rate, t0 represents the reference time, and Z and r are both constants; S2.

2. Establish the prediction equation of per capita living water demand of urban population as follows: WDC ci =(Ae -B·T +C)×GDPC+D, Among them, T represents temperature, GDPC represents regional per capita GDP, and A, B, C, and D are all constants; S2.

3. Establish a prediction equation for per capita living water demand of rural population, as follows: WDC coun -(Aln(T)-B)+Cln(GDPC)+D, Among them, T represents temperature, A, B, C, and D represent constants; S2.

4. Establish a domestic water demand prediction model as follows: WD D =δ×N S ×WDC ci +(1-δ)×N S ×WDC coun 。 7. The method for water demand prediction for regional water security according to claim 1, characterized in that: Step S3 includes the following sub-steps: S3.

1. Establish a prediction equation for the water requirement of each crop during its entire growth period, as follows: Among them, k i Indicates the starting time t of the i-th growth period of crop A i The corresponding crop coefficient is represents the reference crop evapotranspiration corresponding to the growth period, S represents the crop planting area, and η represents the effective channel utilization coefficient of farmland; The calculation method of reference crop evapotranspiration is as follows: Among them, T i represents the temperature at time i, a represents the temperature elasticity coefficient, b represents the temperature threshold, P represents the rainfall, e represents the rainfall evaporation correction coefficient, and E represents the evaporation conversion coefficient: P i and P j They represent the rainfall at time i and time j respectively, and E1, E2 and E3 represent the rainfall evaporation conversion coefficients at different time periods; S3.

2. Establish an agricultural irrigation water demand prediction model as follows: WD arg =WD 1 +WD 2 +…WD A +…+WD N , Among them, WD arg represents the total water demand for agricultural irrigation, WD 1 Indicates the water requirement of crop 1 during its entire growth period, WD A It represents the water requirement of crop A during its entire growth period, and N is the number of crop types considered.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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