CN113837891A - Balanced and efficient water resource allocation method for large-area agricultural irrigation area coping with climate change - Google Patents
Balanced and efficient water resource allocation method for large-area agricultural irrigation area coping with climate change Download PDFInfo
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- 238000003973 irrigation Methods 0.000 title claims abstract description 63
- 230000002262 irrigation Effects 0.000 title claims abstract description 63
- 238000000034 method Methods 0.000 title claims abstract description 33
- 230000008859 change Effects 0.000 title claims abstract description 23
- 238000013468 resource allocation Methods 0.000 title claims abstract description 18
- 230000010485 coping Effects 0.000 title claims abstract description 16
- 230000008901 benefit Effects 0.000 claims abstract description 46
- 230000000694 effects Effects 0.000 claims abstract description 27
- 238000005457 optimization Methods 0.000 claims abstract description 12
- 230000008569 process Effects 0.000 claims abstract description 3
- 230000006870 function Effects 0.000 claims description 26
- 239000002352 surface water Substances 0.000 claims description 20
- 230000008878 coupling Effects 0.000 claims description 16
- 238000010168 coupling process Methods 0.000 claims description 16
- 238000005859 coupling reaction Methods 0.000 claims description 16
- 239000003673 groundwater Substances 0.000 claims description 12
- 239000003621 irrigation water Substances 0.000 claims description 6
- 238000013076 uncertainty analysis Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 4
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- NIXOWILDQLNWCW-UHFFFAOYSA-N 2-Propenoic acid Natural products OC(=O)C=C NIXOWILDQLNWCW-UHFFFAOYSA-N 0.000 claims description 3
- 238000007476 Maximum Likelihood Methods 0.000 claims description 3
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- 150000001875 compounds Chemical class 0.000 claims description 3
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- 239000003337 fertilizer Substances 0.000 claims description 3
- 238000005192 partition Methods 0.000 claims description 3
- 239000000575 pesticide Substances 0.000 claims description 3
- 238000007726 management method Methods 0.000 abstract description 4
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- 230000009471 action Effects 0.000 description 2
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Abstract
The invention discloses a method for balanced and efficient allocation of water resources in a large-area agricultural irrigation area, which can cope with climate change. The method comprises the following steps: s1: collecting basic data; s2: constructing a crop water utilization efficiency function, and quantifying the crop water resource allocation in a research area; s3: constructing an economic benefit function of the crop, and quantifying the economic benefit allocation fairness based on the user jealousy value; s4: constructing a social welfare function, establishing a multi-objective optimization model, and balancing irrigation district water resource allocation efficiency and economic benefit fairness; s5: setting a model boundary; s6, constructing a Bayesian network, and determining meteorological variables influencing the runoff of the research area; s7: and constructing a multi-objective optimization model, and calculating water resource allocation data of the large-area agricultural irrigation area coping with climate change. The method gives consideration to the comprehensive effect of multiple targets, processes the economic benefit relation from the perspective of subjectivity and objectivity, and comprehensively considers the uncertainty of the influence of multiple factors on the runoff from the current situation and the future, so that the sustainable and efficient management of water resources in the irrigation area is realized.
Description
Technical Field
The invention belongs to the technical field of agricultural water management, and particularly relates to a large-area agricultural irrigation area water resource balanced and efficient allocation method for coping with climate change.
Background
Agricultural water resources are important strategic resources for ensuring agricultural production, and currently, water resource shortage and uneven space-time distribution are important restriction factors for food safety and ecological safety in China. With the increasing demand of the national people on the grain, the contradiction between the supply and the demand of agricultural water resources is increasingly highlighted. In addition, extreme weather conditions exacerbate the uncertainty of water resources, and limit the sustainable development of agriculture. The agricultural irrigation area is an important support for guaranteeing national food safety as the center of agricultural production in China, and the reasonable and efficient allocation of water resources in the agricultural irrigation area based on climate change is a hot problem to be solved urgently in China.
At present, most of traditional water resource allocation optimization methods only consider the decision-making target of economic benefit or water resource utilization efficiency independently, and ignore the comprehensive effect and social effect of the two on water resource management. The existing water resource optimization configuration model only calculates the income and the output of economy from an objective angle when processing the relation of economic benefits, but fails to consider the subjective factors and the resource allocation fairness of customers and properly adjusts the actual conditions of each water unit in time, thereby having no universality and flexibility. In addition, the existing water resource optimization configuration model rarely considers the coupling uncertainty among various hydrological meteorological elements, and the random uncertainty of the water resource supply amount is caused by the change of natural conditions such as rainfall, runoff and the like caused by climate change, so that the calculation accuracy and the application range of the existing model are limited. Therefore, the water resource allocation of the large-area agricultural irrigation area which can cope with the climate change needs to be considered comprehensively, and a balanced and efficient water resource allocation method of the large-area agricultural irrigation area which can cope with the climate change needs to be developed.
Disclosure of Invention
The invention aims to solve the problems in the prior art, provides a method for balanced and efficient allocation of water resources in a large-area agricultural irrigation area for coping with climate change, gives consideration to multi-target comprehensive effects such as resource utilization efficiency, economic benefit and social effect, processes the linkage relationship between resource utilization and social and economic effects from the subjective and objective aspects, comprehensively considers the uncertainty of multi-factor influence on runoff from the current situation and the future and predicts the future runoff quantity, can meet the cooperative regulation and control among different water decision departments, and allocates agricultural water resources more reasonably, thereby realizing sustainable and efficient management of water resources in the irrigation area.
(1) On the basis of considering the decision-making target of economic benefit or water resource utilization efficiency, the comprehensive action and social effect of multiple targets are considered, and the cooperative regulation and control among different decision-making departments are met; (2) from the subjective angle, by reflecting the jealousy value of user fairness and combining with the objective angle, economic income and output are calculated to fully quantify the economic benefit, so that agricultural resources can be more reasonably allocated; (3) and by means of the Bayesian network, the influence of multiple factors on the path flow is comprehensively considered from the current situation and the future, uncertainty analysis is carried out, and the future path flow is predicted.
The technical scheme of the invention is realized as follows: a method for balanced and efficient allocation of water resources in a large-area agricultural irrigation area for coping with climate change is characterized by comprising the following steps: s1: collecting basic data: the meteorological hydrological data comprise effective rainfall, irrigation water utilization coefficient and crop water demand; the social and economic data comprise crop price, planting cost, irrigation area, crop water productivity, complete rate of supporting engineering, and consumption of fertilizer, pesticide, agricultural machinery and agricultural film in unit area; the environmental data comprises temperature, evapotranspiration, specific humidity and pressure intensity;
s2: constructing a crop water utilization efficiency function, and quantifying the crop water resource allocation in a research area; wherein the water use efficiency function is:
in the formula (I), the compound is shown in the specification,
and
the irrigation quota of surface water and underground water of the crops in the irrigation area i and the irrigation area k in a time period m3/hm2；aikIs the ratio of the irrigation area to the planting area; k represents the crop index, K is 1,2, …, K; sur represents a surface water landmark; gro represents an underground water mark; a. theikIs the planting area of k crops in the i irrigation area, hm2；YikThe yield per unit area of k crops in the irrigation area is kg/hm2(ii) a IWUE is a water use efficiency function.
S3: constructing an economic benefit function of the crop, and quantifying the economic benefit allocation fairness based on the user jealousy value: establishing economic benefit, engineering effect and ecological effect index data of a plurality of research areas, respectively evaluating and scoring the economic benefit, the engineering effect and the ecological effect of each research area through weight determination of a primary index and weight calculation of a secondary index, and calculating coupling degree, coordination degree and coupling co-scheduling of the research areas; the first-level indexes comprise economic benefit, engineering effect and ecological effect; wherein, the secondary indexes of the economic effect comprise unit area yield value and single water yield; the secondary indexes of the engineering effect comprise irrigation water utilization coefficient, water-saving potential and complete rate of matched engineering; the secondary indexes of the ecological effect comprise ecological water demand, underground water supply and effective rainfall; evaluating the coupling coordination degree grade, and determining the coupling coordination degree grade and the interval form; and inputting the coupling coordination value into an economic benefit model as a jealousy value of economic benefit, and evaluating the influence of each research region on the overall utility, wherein the weight of the primary index and the weight of the secondary index are calculated by an AHP method and an entropy method respectively.
Wherein the economic fairness model is:
wherein R is yield, Yuan; ccosIs cost, yuan; diJealousy value for each i irrigation region; α is a maximum jealousy value acceptable to the user; ε is a sufficiently small number. When a → + ∞ is reached,
0, the loss due to unfairness is 0; when a is 0, the alpha is not zero,
individuals are completely unable to accept unfairness;
in the formula, PCkRepresents the k price of the crops, yuan/kg; YA (Yam acrylic acid)ikIndicates the yield per unit area of the crop k in the irrigation area i, kg/hm2。
Ccos＝ECF+WCF
Wherein ECF is the total planting cost of the crop, yuan/ha; WCF is the water cost of the crop, Yuan; deltakRepresents the cost, Yuan/hm, required to plant a unit area of crop k2；
Representing the price of surface water, Yuan/m3；
Represents the price of groundwater, Yuan/m3。
S4: establishing a social welfare function, establishing a multi-objective optimization model, and balancing irrigation district water resource allocation efficiency and economic benefit fairness, wherein the social welfare function is as follows:
W[f(U),f(F)]＝f(U)a×f(F)1-a
wherein f (U) is a water utilization efficiency function, f (F) is an economic benefit function, and a is a fairness parameter;
s5: setting a model boundary: the model boundary constraint conditions comprise surface water available quantity constraint, underground water available quantity constraint, grain supply constraint, irrigation quota constraint and decision variables which are not negative constraint; the surface water available quantity constraint:
wherein SWA is total surface water amount, m3；ηsurRepresenting the utilization efficiency of surface water;
the available amount of groundwater is constrained:
wherein, TGWA Total groundwater amount, m3；ηgroRepresenting groundwater utilization efficiency;
and grain supply constraint:
in the formula, POiRepresenting a population of partitions; FD represents the grain demand, kg/person;
the irrigation quota constraints are:
in the formula, IQminAnd IQmaxIs the minimum and maximum quota that the crop is allowed to irrigate;
the decision variables should not be negatively constrained to be:
s6: constructing a Bayesian network, and determining meteorological variables influencing runoff of a research area; learning the Bayesian network structure by a hill climbing method, checking the correlation strength of each variable, and adjusting the Bayesian network structure by a black and white table; parameter learning is carried out by utilizing a maximum likelihood method; bayesian reasoning is carried out, posterior probability distribution of each parameter is determined, and probability density of influence of each variable on radial flow is obtained; forecasting water resource supply and demand of irrigation areas through two scenes of RCP4.5 and RCP8.5, and carrying out uncertainty analysis on the forecast values;
s7: constructing a multi-objective optimization model, and calculating balanced and efficient water resource allocation data of the large-area agricultural irrigation area coping with climate change:
maxW[f(U),f(F)]＝f(U)a×f(F)1-a＝(IWUE)a×(z)1-a。
compared with the prior art, the method has the advantages that the economic benefit function and the jealousy value reflecting the fairness of the user are quantized into the same target, and a multi-target optimization configuration model is established by utilizing the comprehensive target of the social benefit function coupling the economic benefit and the water utilization efficiency: (1) on the basis of considering the decision-making target of economic benefit or water resource utilization efficiency, the comprehensive action and social effect of multiple targets are considered, and the cooperative regulation and control among different decision-making departments are met; (2) from the subjective angle, the jealousy value reflecting the fairness of users is combined with the objective angle to comprehensively quantify the economic benefit by calculating the income and the output of the economy, so that the water resources of the large-area agricultural irrigation area can be more reasonably allocated; (3) and by means of the Bayesian network, the influence of multiple factors on the path flow is comprehensively considered from the current situation and the future, uncertainty analysis is carried out, and the future path flow is predicted.
Drawings
FIG. 1 is a schematic flow chart of a method for balanced and efficient allocation of water resources in a large-area agricultural irrigation area, which can cope with climate change;
Detailed Description
A method for balanced and efficient allocation of water resources in a large-area agricultural irrigation area for coping with climate change is characterized by comprising the following steps: s1: collecting basic data: the meteorological hydrological data comprise effective rainfall, irrigation water utilization coefficient and crop water demand; the social and economic data comprise crop price, planting cost, irrigation area, crop water productivity, complete rate of supporting engineering, and consumption of fertilizer, pesticide, agricultural machinery and agricultural film in unit area; the environmental data comprises temperature, evapotranspiration, specific humidity and pressure intensity;
s2: constructing a crop water utilization efficiency function, and quantifying the crop water resource allocation in a research area; wherein the water use efficiency function is:
in the formula (I), the compound is shown in the specification,
and
the irrigation quota of surface water and underground water of the crops in the irrigation area i and the irrigation area k in a time period m3/hm2；aikIs the ratio of the irrigation area to the planting area; k represents the crop index, K is 1,2, …, K; sur represents a surface water landmark; gro represents an underground water mark; a. theikIs the planting area of k crops in the i irrigation area, hm2；YikThe yield per unit area of k crops in the irrigation area is kg/hm2(ii) a IWUE is a water use efficiency function.
S3: constructing an economic benefit function of the crop, and quantifying the economic benefit allocation fairness based on the user jealousy value: establishing economic benefit, social benefit and ecological benefit index data of a plurality of research areas, respectively evaluating and scoring the economic benefit, social benefit and ecological benefit of each research area through weight determination of a primary index and weight calculation of a secondary index, and calculating coupling degree, coordination degree and coupling co-scheduling of the research areas; the first-level indexes comprise economic benefit, engineering effect and ecological effect; wherein, the secondary indexes of the economic effect comprise unit area yield value and single water yield; the secondary indexes of the engineering effect comprise irrigation water utilization coefficient, water-saving potential and complete rate of matched engineering; the secondary indexes of the ecological effect comprise ecological water demand, underground water supply and effective rainfall; evaluating the coupling coordination degree grade, and determining the coupling coordination degree grade and the interval form; and inputting the coupling coordination value into an economic benefit model as a jealousy value of economic benefit, and evaluating the influence of each research region on the overall utility, wherein the weight of the primary index and the weight of the secondary index are calculated by an AHP method and an entropy method respectively.
Wherein the economic fairness model is:
wherein R is yield, Yuan; ccosIs cost, yuan; diJealousy value for each i irrigation region; α is a maximum jealousy value acceptable to the user; ε is a sufficiently small number. When a → + ∞ is reached,
0, the loss due to unfairness is 0; when a is 0, the alpha is not zero,
individuals are completely unable to accept unfairness;
in the formula, PCkRepresents the k price of the crops, yuan/kg; YA (Yam acrylic acid)ikIndicates the yield per unit area of the crop k in the irrigation area i, kg/hm2。
Ccos＝ECF+WCF
Wherein ECF is the total planting cost of the crop, yuan/ha; WCF is the water cost of the crop, Yuan; deltakRepresents the cost, Yuan/hm, required to plant a unit area of crop k2；
Representing the price of surface water, Yuan/m3；
Represents the price of groundwater, Yuan/m3。
S4: establishing a social welfare function, establishing a multi-objective optimization model, and balancing irrigation district water resource allocation efficiency and economic benefit fairness, wherein the social welfare function is as follows:
W[f(U),f(F)]＝f(U)a×f(F)1-a
wherein f (U) is a water utilization efficiency function, f (F) is an economic benefit function, and a is a fairness parameter;
s5: setting a model boundary: the model boundary constraint conditions comprise surface water available quantity constraint, underground water available quantity constraint, grain supply constraint, irrigation quota constraint and decision variables which are not negative constraint; the surface water available quantity constraint:
wherein SWA is total surface water amount, m3；ηsurRepresenting the utilization efficiency of surface water;
the available amount of groundwater is constrained:
wherein, TGWA Total groundwater amount, m3；ηgroRepresenting groundwater utilization efficiency;
and grain supply constraint:
in the formula, POiRepresenting a population of partitions; FD represents the grain demand, kg/person;
the irrigation quota constraints are:
in the formula, IQminAnd IQmaxIs the minimum and maximum quota that the crop is allowed to irrigate;
the decision variables should not be negatively constrained to be:
s6: constructing a Bayesian network, and determining meteorological variables influencing runoff of a research area; learning the Bayesian network structure by a hill climbing method, checking the correlation strength of each variable, and adjusting the Bayesian network structure by a black and white table; parameter learning is carried out by utilizing a maximum likelihood method; bayesian reasoning is carried out, posterior probability distribution of each parameter is determined, and probability density of influence of each variable on radial flow is obtained; forecasting water resource supply and demand of irrigation areas through two scenes of RCP4.5 and RCP8.5, and carrying out uncertainty analysis on the forecast values;
s7: constructing a multi-objective optimization model, and calculating balanced and efficient water resource allocation data of the large-area agricultural irrigation area coping with climate change:
maxW[f(U),f(F)]＝f(U)a×f(F)1-a＝(IWUE)a×(z)1-a。
Claims (6)
1. a method for balanced and efficient allocation of water resources in a large-area agricultural irrigation area for coping with climate change is characterized by comprising the following steps:
s1: collecting basic data: the meteorological hydrological data comprise effective rainfall, irrigation water utilization coefficient and crop water demand;
the social and economic data comprise crop price, planting cost, irrigation area, crop water productivity, complete rate of supporting engineering, and consumption of fertilizer, pesticide, agricultural machinery and agricultural film in unit area; the environmental data comprises temperature, evapotranspiration, specific humidity and pressure intensity;
s2: establishing a crop water utilization efficiency function, and quantifying crop water resource allocation in a research area:
s3: constructing an economic benefit function of the crop, and quantifying the economic benefit allocation fairness based on the user jealousy value: establishing economic benefit, engineering effect and ecological effect index data of a plurality of research areas, respectively evaluating and scoring the economic benefit, the engineering effect and the ecological effect of each research area through weight determination of a primary index and weight calculation of a secondary index, and calculating coupling degree, coordination degree and coupling co-scheduling of the research areas; evaluating the coupling coordination degree grade; inputting the coupling coordination value serving as a jealousy value of economic benefit into an economic benefit model, and evaluating the influence of each research area on overall utility;
s4: establishing a social welfare function, establishing a multi-objective optimization model, and balancing irrigation district water resource allocation efficiency and economic benefit fairness, wherein the social welfare function is as follows:
W[f(U),f(F)]＝f(U)a×f(F)1-a
wherein f (U) is a water utilization efficiency function, f (F) is an economic benefit function, and a is a fairness parameter;
s5: setting a model boundary: the model boundary constraint conditions comprise surface water available quantity constraint, underground water available quantity constraint, grain supply constraint, irrigation quota constraint and decision variables which are not negative constraint;
s6: constructing a Bayesian network, and determining meteorological variables influencing runoff of a research area; learning the Bayesian network structure by a hill climbing method, checking the correlation strength of each variable, and adjusting the Bayesian network structure by a black and white table; parameter learning is carried out by utilizing a maximum likelihood method; bayesian reasoning is carried out, posterior probability distribution of each parameter is determined, and probability density of influence of each variable on radial flow is obtained; forecasting water resource supply and demand of irrigation areas through two scenes of RCP4.5 and RCP8.5, and carrying out uncertainty analysis on the forecast values;
s7: constructing a multi-objective optimization model, and calculating balanced and efficient water resource allocation data of the large-area agricultural irrigation area coping with climate change:
maxW[f(U),f(F)]＝f(U)a×f(F)1-a＝(IWUE)a×(z)1-a
2. the method for balanced and efficient allocation of water resources in a large-area agricultural irrigation district for coping with climate change as claimed in claim 1, wherein: and the weight of the first-level index and the weight of the second-level index in the S3 are calculated by an Analytic Hierarchy Process (AHP) and an entropy weight method respectively.
3. The method for balanced and efficient allocation of water resources in a large-area agricultural irrigation district for coping with climate change as claimed in claim 1, wherein: the water use efficiency function is:
in the formula (I), the compound is shown in the specification,
and
i irrigation area irrigates the ground surface of k crops in a time periodIrrigation quota of water, groundwater, m3/hm2；aikIs the ratio of the irrigation area to the planting area; k represents the crop index, K is 1,2, …, K; sur represents a surface water landmark; gro represents an underground water mark; a. theikIs the planting area of k crops in the i irrigation area, hm2；YikThe yield per unit area of k crops in the irrigation area is kg/hm2(ii) a IWUE is a water use efficiency function.
4. The method for balanced and efficient allocation of water resources in a large-area agricultural irrigation district for coping with climate change as claimed in claim 1, wherein: the economic fairness model in S3 is:
wherein R is yield, Yuan; ccosIs cost, yuan; diJealousy value for each i irrigation region; α is a maximum jealousy value acceptable to the user; ε is a sufficiently small number. When a → + ∞ is reached,
0, the loss due to unfairness is 0; when a is 0, the alpha is not zero,
individuals are completely unable to accept unfairness;
in the formula, PCkRepresents the k price of the crops, yuan/kg; YA (Yam acrylic acid)ikIndicates the yield per unit area of the crop k in the irrigation area i, kg/hm2。
Ccos＝ECF+WCF
Wherein ECF is the total planting cost of the crop, yuan/ha; WCF is the water cost of the crop, Yuan; deltakRepresents the cost, Yuan/hm, required to plant a unit area of crop k2；WPi surRepresenting the price of surface water, Yuan/m3；WPi groRepresents the price of groundwater, Yuan/m3。
5. The method for balanced and efficient allocation of water resources in a large-area agricultural irrigation district for coping with climate change as claimed in claim 1, wherein: surface water available quantity constraint:
wherein SWA is total surface water amount, m3；ηsurRepresenting the utilization efficiency of surface water;
restriction of available amount of underground water:
wherein, TGWA Total groundwater amount, m3；ηgroRepresenting groundwater utilization efficiency;
grain supply restraint:
in the formula, POiRepresenting a population of partitions; FD represents the grain demand, kg/person;
the irrigation quota constraints are:
in the formula, IQminAnd IQmaxIs the minimum and maximum quota that the crop is allowed to irrigate;
the decision variables should not be negatively constrained to be:
6. the method for balanced and efficient allocation of water resources in a large-area agricultural irrigation district for coping with climate change as claimed in claim 1, wherein: the first-level indexes in the S3 comprise economic benefit, engineering effect and ecological effect; wherein, the secondary indexes of the economic effect comprise unit area yield value and single water yield; the secondary indexes of the engineering effect comprise irrigation water utilization coefficient, water-saving potential and complete rate of matched engineering; the secondary indexes of the ecological effect comprise ecological water demand, underground water supply and effective rainfall.
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| CN116596344A (en) * | 2023-05-29 | 2023-08-15 | 东北农业大学 | Cold region drought and flood prevention sustainable efficient regulation and control method based on snow-melting water utilization |
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