CN113343553A - Waterlogging water resource conservation allocation method with supply and demand bilateral prediction - Google Patents

Waterlogging water resource conservation allocation method with supply and demand bilateral prediction Download PDF

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CN113343553A
CN113343553A CN202110399096.3A CN202110399096A CN113343553A CN 113343553 A CN113343553 A CN 113343553A CN 202110399096 A CN202110399096 A CN 202110399096A CN 113343553 A CN113343553 A CN 113343553A
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郭萍
岳琼
王友芝
郭珊珊
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Abstract

The invention discloses a waterlogging water resource conservation allocation method with supply and demand bilateral prediction, belonging to the technical field of water resource optimization allocation. The method comprises the following steps: collecting historical sequence information of the inflow and water demand, and constructing a Bi-LSTM prediction model of water supply and demand; forecasting the inflow and water demand of an area under a future preset scene, and forecasting the drought and flood states of the reservoir area in a future time period by combining the running state of the reservoir and the water consumption balance; constructing a multi-department multi-target mixed integer dynamic optimization model for drought and waterlogging protection; and finally, obtaining a water resource optimal allocation scheme oriented to the drought and waterlogging conditions in the future. The method can not only greatly avoid drought and flood disasters in the reservoir area, but also obtain a water resource efficient allocation scheme oriented to the drought and flood conservation in the future, provide a more reliable solution for sustainable water resource regulation and control, and provide a more robust guarantee for regional grain safety.

Description

Waterlogging water resource conservation allocation method with supply and demand bilateral prediction
Technical Field
The invention relates to the technical field of water resource optimization configuration, in particular to a drought and waterlogging conservation water resource configuration method with supply and demand bilateral prediction.
Background
With the rapid development of social economy and the continuous promotion of urbanization, the contradiction between the increasing water resource demand and the water resource shortage is more prominent. The demand for water resources will continue to increase in the future against the background of global climate change. On the other hand, the water resource supply amount is changed by the comprehensive influence of a plurality of factors such as precipitation, air temperature, surface process and the like. Water resource issues are destined to become a century-oriented challenge that cannot be avoided in the future. Agriculture is a large water consumer in China, and irrigation water is an important prerequisite for guaranteeing the safe production of grains. How to reasonably predict the supply and demand change of the future water resource and scientifically and efficiently configure the limited water resource has profound significance for guaranteeing the grain safety and the regional sustainable development.
The optimization modeling method is used as an important tool for efficient configuration of water resources and is widely applied in academia. Most of related researches are optimized according to the current situation of water resource utilization, but the water resource optimization configuration oriented to the future has a better use prospect. Under the influence of complex conditions such as hydrologic cycle, terrain change, human activities and the like, the future water resource supply and demand show nonlinear and random characteristics, and the accurate prediction of the characteristics has great challenge. With the rapid development of a machine learning algorithm, a technical support is provided for reasonably processing sequence information and improving prediction accuracy. However, how to develop high-precision bilateral unified prediction of water supply and demand by means of a machine learning algorithm, construct a prediction-optimization coupling framework, and realize future-oriented efficient and reasonable allocation of water resources is not provided with a specific and effective implementation scheme.
On the other hand, under the climate change with global warming as the main background, the occurrence frequency of extreme climate and hydrological events such as drought and flooding will increase, and inevitably become one of the important risks affecting the sustainable development of the region. The reservoir can effectively relieve the impact on the effective management of water resources caused by drought and flood disasters by blocking and regulating the natural runoff so as to achieve the aims of flood control, drought resistance and benefit, and meet the requirement of regional development to the maximum extent. The implementation of a scientific reservoir dispatching management scheme is beneficial to exerting the engineering effect of the reservoir to the maximum extent. However, on the premise of considering the priority of the tasks undertaken by the reservoir and ensuring the engineering safety, how to fully utilize the storage capacity of the reservoir to realize the efficient management of water resources and consider the regional grain safety under the drought and flood conditions becomes a problem which needs to be solved urgently.
Disclosure of Invention
The invention aims to provide a method for allocating drought, waterlogging and water resource conservation by supply and demand bilateral prediction, which is characterized by comprising the following steps of:
step S1: collecting historical sequence information of the water inflow and the water demand;
step S2: according to the historical sequence information of the step S1, respectively predicting the area water inflow and the water demand under the future preset situation by using a Bi-directional Long Short-Term Memory (Bi-directional Long Short-Term Memory) prediction model of the water supply and demand;
step S3: on the basis of predicting the water inflow and water demand of a future area, the running state of a reservoir and the water consumption are combined to balance and predict the drought and flood states of the reservoir area in the future time period;
step S4: selecting optimization targets of maximizing the overall net economic benefit of the region, maximizing the total grain yield of the region and minimizing the comprehensive water shortage index, selecting water balance capacity of a reservoir, reservoir capacity limiting capacity of the reservoir, flood storage capacity of a flood diversion region, capacity expansion capacity of the flood diversion region, grain safety and water demand of each water department as constraint conditions, and constructing a multi-department multi-target mixed integer dynamic optimization model for drought and waterlogging conservation;
step S5: and (4) solving the multi-department multi-target mixed integer dynamic optimization model in the step S4 by using an analytic hierarchy process and a weighted minimum deviation method to obtain a water resource optimal configuration result oriented to the drought and waterlogging conditions in the future.
The step S4 includes the following sub-steps:
step S41: selecting the target of maximizing the overall net economic benefit of the region, and constructing a target function by considering the water consumption of all departments in the region, the flood diversion area diversion cost and the flood accumulation area expansion cost:
Figure BDA0003019656900000021
in the formula (f)1Is a net economic benefit; i is administrative region, and takes values of 1,2, …, I; j is the water department, takes the value 1,2, …, J; t is a time interval and takes the values of 1,2, … and T; n is a flood distribution area and takes the values of 1,2, … and N; cijRepresenting the net benefit coefficient of the jth class water usage department of the ith subarea; xijtThe water quantity allocated to the jth class water usage department of the ith subarea in the tth time period is represented; dnRepresenting the flood diversion cost of the nth flood diversion area; wtnThe flow distribution quantity of the nth flood distribution area in the t period is represented; deltatnThe variable is 0-1, 1 represents that the flood distribution area needs to be expanded, and 0 represents that the flood distribution area does not expand; b isnRepresenting the capacity expansion cost of the nth flood area; etnThe capacity expansion capability of the nth flooding area in the t period is represented;
step S42: selecting a target of maximizing the total yield of grains in a region, introducing secondary moisture production functions of different crops, and constructing the target function:
Figure BDA0003019656900000031
in the formula (f)2The total yield of the grains is obtained; k is the crop species and takes the values 1,2, …, K; a. theikThe planting area of the kth type crop in the ith subarea is shown; CWtikAllocating water quantity for the kth type crops in the ith subarea in the t time period; alpha, beta and o are coefficients of a crop secondary water production function obtained by fitting experimental data;
step S43: selecting a target of minimizing the comprehensive water shortage index, considering the configuration weight of each department, and constructing a target function:
Figure BDA0003019656900000032
in the formula (f)3In order to synthesize the water-shortage index,
Figure BDA0003019656900000035
water distribution weight of jth water using department for ith subarea;
Figure BDA0003019656900000033
the maximum water demand of the jth water use department in the ith subarea in the tth time period;
step S44: selecting the water balance capacity of the reservoir, the reservoir capacity limiting capacity of the reservoir, the flood storage capacity of the flood diversion area, the capacity expansion capacity of the flood diversion area, the grain safety and the water demand of each water department as constraint conditions, wherein the specific expression is as follows:
(1) reservoir water balance restraint:
Figure BDA0003019656900000034
in the formula, SRt、SRt-1The water storage capacity of the reservoir is respectively the t-th time period and the t-1 th time period; WR (pulse Width modulation)tThe water inflow amount of the reservoir in the t period; when t is 0, the water storage capacity of the reservoir is a known parameter, and when t is more than or equal to 1, the inflow amount, the outflow amount and the water storage capacity of the reservoir follow a dynamic balance principle;
(2) reservoir capacity limiting and restricting:
DRt≤SRt≤MRt
in the formula, DRtThe reservoir dead storage capacity is t time period; MRtThe maximum water storage capacity of the reservoir is t time period;
(3) flood storage capacity constraint in flood diversion areas:
Wtn≤WCtn
in the formula, WCtnThe maximum flood storage capacity of the flood diversion area n at the time t;
(4) and (3) capacity expansion capacity constraint of the flood distribution area:
Etn≤ECtn
in the formula, ECtnThe maximum capacity expansion capacity of the flood distribution area n in the period t;
(5) grain safety restraint:
Figure BDA0003019656900000041
in the formula, POP is the total population of the area; ND is the minimum grain standard of average human;
(6) water demand restriction of each water consumption department:
Figure BDA0003019656900000042
Figure BDA0003019656900000043
Figure BDA0003019656900000044
in the formula (I), the compound is shown in the specification,
Figure BDA0003019656900000045
the minimum water demand of the jth water department of the ith subarea in the t time period;
Figure BDA0003019656900000046
the minimum water demand of the kth type crop of the ith subarea in the t period;
Figure BDA0003019656900000047
the maximum water demand of the kth type crop of the ith subarea in the t period;
x in the above constraintijt、CWtikAnd WtnAre all non-negative, i.e.
Xijt≥0,CWtik≥0,Wtn≥0。
The invention has the beneficial effects that:
1. the method considers the randomness and the complexity of a future water supply and demand structure, adopts a Bi-LSTM deep learning algorithm to carry out bilateral prediction of water supply and demand of the water reservoir, and can effectively overcome the defects of predicting the water supply and demand in the aspect of prediction accuracy by adopting a traditional prediction model and rarely consider the limitation of dynamic influence of supply and demand bilateral prediction results on future water resource allocation;
2. according to the method, future water resource supply and demand prediction information is fully utilized, and a water resource optimal allocation modeling method is combined, so that early warning of drought and flood disasters in a reservoir area is realized, disasters are avoided to a great extent through efficient allocation of reservoir water resources, and safety of regional grains under water shortage and rich conditions is guaranteed.
Drawings
FIG. 1 is a flow chart of a waterlogging water conservation resource allocation method for supply and demand bilateral prediction according to the present invention.
Detailed Description
The invention provides a method for allocating drought and waterlogging conservation water resources with supply and demand bilateral prediction, which is further explained by combining the accompanying drawings and a specific embodiment.
FIG. 1 is a flow chart of a waterlogging water conservation resource allocation method for supply and demand bilateral prediction according to the present invention. The method specifically comprises the following steps:
s1: collecting historical sequence information of water inflow and water demand, preprocessing the data, determining parameters of a Bi-LSTM model by taking part of the preprocessed data as training data, constructing a Bi-LSTM prediction model of water supply and demand, and taking the rest of the preprocessed data as test verification model effects;
s2: respectively predicting the regional water inflow and the water demand under the future preset situation by using a Bi-LSTM prediction model of water supply and demand;
s3: on the basis of predicting the water inflow and water demand of a future area, the drought and flood states of the reservoir area in the future time period are predicted by combining the running state of the reservoir and the water consumption balance;
s4: the method comprises the steps of constructing a multi-department multi-target mixed integer dynamic optimization model for drought and waterlogging conservation by taking the maximization of the overall net economic benefit of a region, the maximization of the total grain yield and the minimization of a comprehensive water shortage index as optimization targets and taking the storage regulation capacity of a reservoir, the flood storage capacity of a flood diversion area, the water demand of each department, the grain safety and the like as constraint conditions;
s5: and solving the multi-objective optimization model by using an analytic hierarchy process and a weighted minimum deviation method to obtain a water resource optimization configuration result oriented to the condition of drought and waterlogging, and providing theoretical guidance and decision support for regional water resource efficient management and grain safety guarantee.
Step S4 includes:
step S4-1: with the aim of maximizing the overall net economic benefit of the region, considering the water consumption of all the departments in the region, the diversion cost of the flood diversion area and the capacity expansion cost of the flood storage area, constructing an objective function:
Figure BDA0003019656900000051
in the formula (f)1Is net economic benefit (yuan); i is administrative district; j is the water use department; t is a time period; n is a flood diversion area; cijRepresents the net benefit coefficient (element/m) of the jth class water department of the ith subarea3)；XijtIndicating the configured water quantity (m) of the jth class water use department in the ith subarea in the tth time period3)；DnRepresents the flood diversion cost (Yuan/m) of the nth flood diversion area3)；WtnRepresents the split flow (m) of the nth flood zone in the t period3)；δtnThe variable is 0-1, 1 represents that the flood distribution area needs to be expanded, and 0 represents that the flood distribution area does not expand; b isnRepresents the capacity expansion cost (element/m) of the nth flood zone3)EtnThe capacity expansion capacity (m) of the nth flood division area in the t period3)；
Step S4-2: and (3) aiming at maximizing the total yield of regional grains, introducing secondary moisture production functions of different crops, and constructing an objective function:
Figure BDA0003019656900000061
in the formula (f)2The grain yield (kg); k is the crop species; a. theikThe planting area (ha) of the kth type crop of the ith subarea; CWtikThe allocated water quantity (m) of the kth type crop in the ith subarea in the t period3) (ii) a The alpha, the beta, and the omicron are coefficients of a crop secondary water production function and can be obtained by fitting test data;
step S4-3: and (3) constructing an objective function by taking the comprehensive water shortage index minimization as an objective and considering the configuration weight of each department:
Figure BDA0003019656900000062
in the formula (I), the compound is shown in the specification,
Figure BDA0003019656900000065
the water distribution weight of the jth water consumption department of the ith subarea can be obtained by entropy weight calculation;
Figure BDA0003019656900000063
maximum water demand (m) of jth water department in the t time period for the ith subarea3)；
Step S4-4: the method takes reservoir regulation capacity, flood diversion area flood storage capacity, water demand of each department, grain safety and the like as constraint conditions, and the specific constraint expressions are expressed as follows:
reservoir water balance restraint:
Figure BDA0003019656900000064
in the formula, SRtThe water storage capacity (m) of the reservoir in the t-th period3)；WRtWater inflow (m) of reservoir at t-th time3)；
In the constraint condition, when t is 0, the water storage capacity of the reservoir is a known parameter, and when t is more than or equal to 1, the inflow amount, the outflow amount and the water storage amount of the reservoir follow a dynamic balance principle.
Reservoir capacity limiting and restricting:
DRt≤SRt≤MRt
in the formula, DRtIs at t timeSegment reservoir dead storage capacity (m)3)；MRtMaximum water storage capacity (m) of reservoir for t period3)；
Flood storage capacity constraint in flood diversion areas:
Wtn≤WCtn
in the formula, WCtnMaximum flood storage capacity (m) for a t period n flood diversion area3)；
And (3) capacity expansion capacity constraint of the flood distribution area:
Etn≤ECtn
in the formula, ECtnMaximum capacity expansion capacity (m) of flood area n for t period3)；
Grain safety restraint:
Figure BDA0003019656900000071
in the formula, POP is the total population (people) of the area; ND is the minimum grain standard (kg/person) of the average population;
water demand restriction of each water consumption department:
Figure BDA0003019656900000072
Figure BDA0003019656900000073
Figure BDA0003019656900000074
in the formula (I), the compound is shown in the specification,
Figure RE-GDA0003103034030000075
minimum water demand (m) of jth water department in time t period for ith subarea3)；
Figure RE-GDA0003103034030000076
Is as followsMinimum water requirement (m) for ith sub-zone kth category crop in period t3)；
Figure RE-GDA0003103034030000077
Maximum water demand (m) for ith sub-zone kth kind of crop in t period3)；
0-1 variable constraint:
Figure BDA0003019656900000078
non-negative constraints:
Xijt≥0,CWtik≥0,Wtn≥0
the embodiment is only a preferred embodiment of the invention, but the scope of the invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the invention will be covered by the scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (2)

1. A method for allocating drought, waterlogging and water resource conservation with supply and demand bilateral prediction is characterized by comprising the following steps:
step S1: collecting historical sequence information of the water inflow and the water demand;
step S2: respectively predicting the area water inflow and water demand under the future preset situation by using a water supply and demand Bi-LSTM prediction model according to the historical sequence information of the step S1;
step S3: on the basis of predicting the water inflow and water demand of a future area, the running state of a reservoir and the water consumption are combined to balance and predict the drought and waterlogging state of the reservoir area in a future time period;
step S4: selecting optimization targets of maximizing the overall net economic benefit of the region, maximizing the total grain yield of the region and minimizing the comprehensive water shortage index, selecting water balance capacity of a reservoir, reservoir capacity limiting capacity of the reservoir, flood storage capacity of a flood diversion region, capacity expansion capacity of the flood diversion region, grain safety and water demand of each water department as constraint conditions, and constructing a multi-department multi-target mixed integer dynamic optimization model for drought and waterlogging conservation;
step S5: and (4) solving the multi-department multi-target mixed integer dynamic optimization model in the step S4 by using an analytic hierarchy process and a weighted minimum deviation method to obtain a water resource optimal configuration result oriented to the drought and waterlogging conditions in the future.
2. The method for waterlogging reclamation and conservation water resource allocation according to the bilateral supply and demand forecast of claim 1, wherein the step S4 comprises the following sub-steps:
step S41: selecting the target of maximizing the overall net economic benefit of the region, and constructing a target function by considering the water consumption of all departments in the region, the flood diversion area diversion cost and the flood accumulation area expansion cost:
Figure FDA0003019656890000011
in the formula (f)1Is a net economic benefit; i is administrative region, and takes values of 1,2, …, I; j is the water department, takes the value 1,2, …, J; t is a time interval and takes the values of 1,2, … and T; n is a flood distribution area and takes the values of 1,2, … and N; cijRepresenting the net benefit coefficient of the jth class water usage department of the ith subarea; xijtThe water quantity allocated to the jth class water usage department of the ith subarea in the tth time period is represented; dnRepresenting the flood diversion cost of the nth flood diversion area; wtnThe flow distribution quantity of the nth flood distribution area in the t period is represented; deltatnThe variable is 0-1, 1 represents that the flood distribution area needs to be expanded, and 0 represents that the flood distribution area does not expand; b isnRepresenting the capacity expansion cost of the nth flood area; etnThe capacity expansion capacity of the nth flood distribution area in the t period is represented;
step S42: selecting a target of maximizing the total yield of grains in a region, introducing secondary moisture production functions of different crops, and constructing the target function:
Figure FDA0003019656890000021
in the formula (f)2The total yield of the grains is obtained; k is the crop species and takes the values 1,2, …, K; a. theikThe planting area of the kth type crop in the ith subarea is shown; CWtikAllocating water quantity for the kth type crops in the ith subarea in the t time period; alpha, beta and o are coefficients of a crop secondary water production function obtained by fitting experimental data;
step S43: selecting a target of minimizing the comprehensive water shortage index, considering the configuration weight of each department, and constructing a target function:
Figure FDA0003019656890000022
in the formula (f)3In order to synthesize the water-shortage index,
Figure FDA0003019656890000023
water distribution weight of jth water using department for ith subarea;
Figure FDA0003019656890000024
the maximum water demand of the jth water use department in the ith subarea in the tth time period;
step S44: selecting the water balance capacity of the reservoir, the reservoir capacity limiting capacity of the reservoir, the flood storage capacity of the flood diversion area, the capacity expansion capacity of the flood diversion area, the grain safety and the water demand of each water department as constraint conditions, wherein the specific expression is as follows:
(1) reservoir water balance restraint:
Figure FDA0003019656890000025
in the formula, SRt、SRt-1The water storage capacity of the reservoir is respectively the t-th time period and the t-1 th time period; WR (pulse Width modulation)tThe water inflow amount of the reservoir in the t period; when t is 0, the water storage capacity of the reservoir is a known parameter, and when t is more than or equal to 1, the inflow amount, the outflow amount and the water storage capacity of the reservoir follow a dynamic balance principle;
(2) reservoir capacity limiting and restricting:
DRt≤SRt≤MRt
in the formula, DRtThe reservoir dead storage capacity is t time period; MRtThe maximum water storage capacity of the reservoir is t time period;
(3) flood storage capacity constraint in flood diversion areas:
Wtn≤WCtn
in the formula, WCtnThe maximum flood storage capacity of the flood diversion area n at the time t;
(4) and (3) capacity expansion capacity constraint of the flood distribution area:
Etn≤ECtn
in the formula, ECtnThe maximum capacity expansion capacity of the flood distribution area n in the period t;
(5) grain safety restraint:
Figure FDA0003019656890000031
in the formula, POP is the total population of the area; ND is the minimum grain standard of average human;
(6) water demand restriction of each water consumption department:
Figure FDA0003019656890000032
Figure FDA0003019656890000033
Figure FDA0003019656890000034
in the formula (I), the compound is shown in the specification,
Figure FDA0003019656890000035
the minimum water demand of the jth water department of the ith subarea in the t time period;
Figure FDA0003019656890000036
the minimum water demand of the kth type crop of the ith subarea in the t period;
Figure FDA0003019656890000037
the maximum water demand of the kth type crop of the ith subarea in the t period;
x in the above constraintijt、CWtikAnd WtnAre all non-negative, i.e.
Xijt≥0,CWtik≥0,Wtn≥0。
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