CN115099697A - Method for dynamically adjusting annual water total quantity control index in southern rich water region - Google Patents
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Abstract
本发明公开了一种南方丰水地区面临年度用水总量控制指标动态调整方法，基于遗传规划建立区域农田灌溉亩均净用水量和年降水量关系曲线，计算平水年区域农田灌溉用水量静态控制指标，通过采用Copula函数预测面临年度区域降水量，调整确定面临年度区域用水总量动态控制指标。本发明可以考虑南方丰水地区面临年度区域天然来水的丰枯变化，根据面临年度天然来水情势对区域用水总量静态控制指标进行适应性调整得到区域用水总量动态控制指标，实现不同来水频率的差别化管控，更好地发挥水资源的刚性约束作用，有助于提高区域水资源管理精细化水平和可操作性。
The invention discloses a dynamic adjustment method for the annual total water consumption control index in the southern regions with abundant water. Based on genetic programming, a relationship curve between the average net water consumption per mu and annual precipitation for regional farmland irrigation is established, and the static control of the regional farmland irrigation water consumption in a flat water year is calculated. By using the Copula function to predict the annual regional precipitation, adjust and determine the dynamic control index of the total annual regional water consumption. The present invention can take into account the changes of the annual regional natural inflow in the southern high-water areas, and adapts the static control index of the total regional water consumption according to the situation of the annual natural inflow to obtain the dynamic control index of the regional total water consumption, so as to achieve different Differential management and control of water frequency can better exert the rigid constraint of water resources and help improve the refinement and operability of regional water resources management.
Description
Technical Field
The invention belongs to the field of water resource management, and particularly relates to a dynamic adjustment method for an annual water use total amount control index in a southern rich water region.
Background
The implementation of the total water consumption control of the region is an important component of the strictest water resource management system, and the reasonable determination of the total water consumption control index of the region is a basic support for realizing scientific and refined water resource management. The regional water total amount control index of the current southern rich water region is redistributed to be a fixed value and a static value, which reflects the restriction of the regional water total amount under the condition of average natural water supply for many years (open water years), and the regional water total amount static control index is used for annual water plan formulation and total water amount assessment of a certain practical adjacent year.
For southern rich water areas, natural incoming water of a certain adjacent year is not fixed in open water but shows withered change. In addition, although the water consumption of industrial, domestic and the like in a certain annual region is not basically influenced by meteorological factors in the same year, the change of the meteorological factors has important influence on the water consumption of farmland irrigation, so that the water consumption and the total water consumption of the farmland irrigation in the region between the years show obvious fluctuation, and sometimes the difference between different years is large. The actual static control index of the total water consumption of a certain face of the face directly adopting the existing annual water use amount is not adaptive to the natural abundant and withered incoming water, and is not beneficial to realizing scientific and fine management of water resources. Therefore, research and development of a dynamic adjustment method for annual water use total control indexes in southern rich water areas are urgently needed to adapt to the natural water supply situation of the facing years and improve the refinement level and operability of regional water resource management.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a dynamic adjustment method for the annual water use total amount control index in southern rich water areas.
In order to solve the technical problems, the invention adopts the following technical scheme: a method for dynamically adjusting annual water use total control indexes in southern rich water areas comprises the following steps:
step 1, establishing a relation curve between the average net water consumption per mu and the annual precipitation of regional farmland irrigation based on genetic programming;
step 2, calculating a static control index of farmland irrigation water consumption in an open water year region;
step 3, forecasting the precipitation of the facing annual area by adopting a Copula function;
and 4, adjusting and determining dynamic control indexes of total water consumption of the facing annual region.
Further, establishing a relation curve of the average net water consumption per mu and the annual precipitation of regional farmland irrigation based on genetic programming, enabling H and P to respectively represent the average net water consumption per mu and the annual precipitation of regional farmland irrigation, and performing symbolic regression by utilizing the genetic programming to establish the relation curve of the average net water consumption per mu and the annual precipitation of regional farmland irrigation, wherein the basic steps are as follows:
(1) determining an individual expression structure, including a function set F and a terminator set T, wherein F { +, -,/, √ log, exp }, T { q, w };
(2) generating an initial population, randomly generating by using a mixing method, selecting formulas with different character compositions from a function set F and a terminator set T as initial individuals by using a growth method and a complete method which are respectively 50%, and setting the population number as M;
(3) calculating individual fitness, and judging the quality of the individual by taking the root mean square error as a fitness function, wherein the smaller the fitness value is, the better the individual is;
(4) generating a new generation population, executing genetic operations and generating new individuals, wherein the main genetic operations comprise: firstly, copying existing excellent individuals, adding new groups, and correspondingly deleting inferior individuals; exchanging, namely exchanging partial nodes of the two selected individuals, and adding the two generated new individuals into a new group; mutating, randomly changing a certain part of the individuals, and inserting new individuals into a new group;wherein the probability of duplication P r The cross probability is P c Probability of mutation P m ；
(5) Repeating (3) and (4) until a termination condition is met, and selecting the best result as a final solution, wherein G represents the iteration number, the initial population is the 0 th generation, and the termination criterion is that the maximum iteration algebra G is reached max ；
The explicit expression of the relation curve of the average net water consumption per mu and the annual precipitation of regional farmland irrigation obtained by the steps is as follows:
wherein,
the average net water consumption per mu for field irrigation by using genetic programming to perform symbolic regression calculation, wherein P is annual precipitation, f re And the equation (t) represents the functional relationship between the average acre net water consumption and the annual precipitation of regional farmland irrigation built by symbolic regression through genetic programming.
Further, calculating a static control index of the farmland irrigation water consumption in the open water year region; the method comprises the following specific steps:
(1) calculating the design frequency of the regional historical annual precipitation series year by year, and selecting the year closest to 50% of the design frequency of the annual precipitation as the representative year of the horizontal year;
(2) calculating the proportion beta of the representative year farmland irrigation water consumption to the total water consumption, and further combining the static control index W of the total water consumption of the open water year area ST Calculating the static control index of the irrigation water consumption of the farmland in the open water year by the following formula:
W SA ＝β·W ST (2)
wherein, W SA And (3) representing the static control index of the irrigation water consumption of farmland in open water year areas.
Further, forecasting the annual regional precipitation by adopting a Copula function, and specifically comprises the following steps:
(1) determining an edge probability distribution function of regional annual precipitation;
predicting the annual regional precipitation by using a Copula function; the method specifically comprises the following steps: gamma distribution is adopted as an edge distribution line type of annual precipitation, and a linear moment method is adopted to estimate parameters of the edge distribution line type;
(2) constructing a joint probability distribution function of annual and early annual precipitation of the region by using a Copula function;
determining the longest time lag L of the early annual precipitation on the face of annual influence according to the autocorrelation analysis of the regional historical annual precipitation series, and assuming P t 、P t-i (i-1, 2, … L) indicates the annual and early annual precipitation respectively for the region, p t 、p t-i Respectively corresponding realized values, P t 、P t-i Having the same edge probability distribution function F P (. o) the corresponding probability density function is f P (·)；
P t 、P t-i The joint distribution function of (a) can be represented by a two-dimensional Copula function:
F(p t ,p t-i )＝C θ (F P (p t ),F P (p t-i ))＝C θ (u,v) (3)
wherein, θ is a parameter of the Copula function; u ═ F P (p t ),v＝F P (p t-i ) Is an edge distribution function;
adopting Gumbel-Hougaard Copula function to construct a joint probability distribution function of the annual and early annual precipitation amount of an area, wherein the expression is as follows:
estimating parameters of a Gumbel-Hougaard Copula function by adopting a Kendall rank correlation coefficient method; the Kendall correlation coefficient tau is related to the parameter theta by:
let { (x) 1 ,y 1 ),…,(x n ,y n ) Denotes a random sample of n observations taken from successive random variables (X, Y), of which there are samples
Different combinations of observations (x) i ,y i ) And (x) j ,y j ) (ii) a The Kendall rank correlation coefficient tau of the sample is calculated by the following formula
Wherein sign (·) is a sign function;
(3) forecasting the precipitation of the facing annual area;
given early annual precipitation P t-i (i-1, 2, … L) value p t-i The corresponding face annual precipitation P t The value of (a) has a conditional probability distribution function;
wherein Pro (·) represents a probability;
when the annual precipitation P facing the early L years of the year is given t-i (i-1, 2, … L) value p t-i When confronted with annual precipitation P t Conditional probability distribution function F cL (p t ) Calculated by the following formula:
wherein, delta i The weight coefficient of earlier year i is represented, and the calculation formula is as follows:
wherein, tau i Is P t 、P t-i Calculating Kendall rank correlation coefficients of two variables by using a formula (6);
obtaining the apparent annual precipitation P t Conditional probability distribution function F cL (p t ) Then, according to the principle of mathematical statistics, a median can be calculated and obtained as the annual precipitation P t The predicted value of (2); face annual precipitation P t Median p of tm Solving by:
F cL (p tm )＝0.5 (10)
and (5) solving the formula (10) by adopting a dichotomy trial calculation to obtain a numerical solution.
Further, the adjustment determines dynamic control indexes of total water consumption of the facing annual region; the method specifically comprises the following steps:
dynamic adjustment coefficient K for farmland irrigation water consumption facing annual region t The calculation formula is as follows:
wherein p is 50％ In order to design regional annual precipitation corresponding to 50% horizontal years of frequency, an edge probability distribution function F is inquired P (. to obtain;
according to the dynamic adjustment coefficient K t Faced with dynamic control index W of total water consumption in annual region DT Can be calculated by the following formula:
W DT ＝W ST+ (K t -1)W SA (12)。
the method is based on genetic programming to establish a relation curve of the average net water consumption per mu of regional farmland irrigation and the annual precipitation, calculate static control indexes of the farmland irrigation water consumption of the open-water annual region, predict the precipitation of the facing annual region by adopting a Copula function, and adjust and determine dynamic control indexes of the total water consumption of the facing annual region.
Compared with the prior art, the invention has the beneficial effects that: according to the regional water consumption dynamic control method, the withering change of natural incoming water of the regional area in the south rich water region can be considered, the regional water consumption static control index is adaptively adjusted according to the natural incoming water situation of the regional area to obtain the regional water consumption dynamic control index, the differentiated control of different incoming water frequencies is realized, the rigid constraint effect of water resources is better exerted, and the refinement level and operability of regional water resource management are improved.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention is further illustrated by the following examples in connection with the accompanying drawings.
As shown in figure 1, the method for dynamically adjusting the total annual water consumption control index in the southern rich water region is characterized in that a relation curve between the average net water consumption per mu of regional farmland irrigation and the annual precipitation is established based on genetic programming, the static control index of the annual regional farmland irrigation water consumption in the open water is calculated, the annual regional precipitation is predicted by adopting a Copula function, and the dynamic control index of the total annual regional water consumption is adjusted and determined. Fig. 1 is a calculation flowchart of the present embodiment, which is performed according to the following steps:
1. and establishing a relation curve between the average net water consumption per mu and the annual precipitation of regional farmland irrigation based on genetic programming.
Genetic programming is a new evolutionary calculation method provided on the basis of genetic algorithm, has strong heuristic automatic search and optimization capability, has the advantages of automatically finding out the change rule between a dependent variable and an independent variable, does not need to determine the functional relationship among the variables in advance, and is widely applied to aspects of data mining, symbolic regression, engineering empirical formula discovery and the like.
H and P respectively represent the average net water consumption per mu and the annual precipitation of regional farmland irrigation. In the specific implementation, genetic programming is utilized to carry out symbolic regression to establish a relation curve between the average net water consumption per mu and the annual precipitation of regional farmland irrigation. The basic steps are as follows:
(1) an individual expression structure is determined, including F (function set) and T (terminator set). In this embodiment, F { +, -, ×,/, √ log, exp }, and T { q, w }.
(2) An initial population is generated. In the specific implementation, a mixed method is used for random generation, 50% of each of a growth method and a complete method is used for selecting a formula with different character compositions from a function set F and a terminator set T as an initial individual. In this embodiment, the population number is set to M.
(3) And calculating the individual fitness. In the specific implementation, the root mean square error is used as a fitness function to judge the quality of the individual, and the smaller the fitness value is, the better the individual is.
(4) And generating a new generation of population. Performing genetic manipulation to generate new individuals, the main genetic manipulation comprising: firstly, copying existing excellent individuals, adding new groups, and correspondingly deleting inferior individuals; exchanging, exchanging partial nodes of the two selected individuals, and adding the two generated new individuals into a new group; mutation, randomly changing some part of individuals, and inserting new individuals into new population. Probability of replication P in this embodiment r The cross probability is P c Probability of variation P m 。
(5) And (4) repeating the steps (3) and (4) until a termination condition is met (the maximum iteration algebra is reached or the optimal individual fitness reaches a preset value), and selecting the best result as a final solution. In this embodiment, G represents the number of iterations, the initial population is the 0 th generation, and the termination criterion is the maximum iteration generation G max 。
The explicit expression of the relationship curve between the acre average net water consumption and the annual precipitation amount of regional farmland irrigation can be obtained through the steps as follows:
wherein,
the average net water consumption per mu for field irrigation by using genetic programming to perform symbolic regression calculation, wherein P is annual precipitation and f re And the equation (t) represents the functional relationship between the average acre net water consumption and the annual precipitation of regional farmland irrigation built by symbolic regression through genetic programming.
2. And calculating the static control index of the irrigation water consumption of the farmland in the open water year area.
Calculating the design frequency of the regional historical annual precipitation series year by year, and selecting the year closest to 50% of the design frequency of the annual precipitation as the representative year of the horizontal year.
The proportion beta of the farmland irrigation water consumption in the representative year to the total water consumption is calculated in a statistical manner, and then the static control index W of the total water consumption in the open water year region issued by the superior people government is combined ST Calculating the static control index of the irrigation water consumption of the farmland in the open water year by the following formula:
W SA ＝β·W ST (2)
wherein, W SA And (3) representing the static control index of the irrigation water consumption of farmland in open water year areas.
3. And predicting the precipitation facing the annual region by using a Copula function.
The method comprises the following three substeps:
3.1 determining marginal probability distribution function of regional annual precipitation
Since the overall distribution frequency profile of regional annual precipitation is unknown, a profile is generally chosen that better fits the annual precipitation data series.
In this embodiment, Gamma distribution is used as the edge profile of annual precipitation.
The methods commonly used for estimating the edge distribution line type parameters at present mainly include a moment method, a maximum likelihood method, an adaptive line method, a probability weight moment method, a weight function method, a linear moment method and the like. The linear moment method is an effective parameter estimation method recognized at home and abroad at present, and has the advantage that the obtained parameter estimation value is more stable.
In this embodiment, a linear moment method is used to estimate the parameters of the edge profile.
3.2 construction of Joint probability distribution function of annual and early annual precipitation of region by using Copula function
Determining the longest stagnation of the early annual precipitation on the facing annual influence according to the autocorrelation analysis of the regional historical annual precipitation seriesAnd is L. Suppose P t 、P t-i (i-1, 2, … L) indicates the annual and early annual precipitation of the region, respectively, p t 、p t-i Respectively corresponding realized values. P t 、P t-i Having the same edge probability distribution function F P (. o) the corresponding probability density function is f P (·)。
P t 、P t-i The joint distribution function of (a) can be represented by a two-dimensional Copula function:
F(p t ,p t-i )＝C θ (F P (p t ),F P (p t-i ))＝C θ (u,v) (3)
wherein, θ is a parameter of the Copula function; u ═ F P (p t ),v＝F P (p t-i ) Is an edge distribution function.
In the specific implementation, a Gumbel-Hougaard Copula function is adopted to construct a joint probability distribution function of the annual and early annual precipitation amount of the region, and the expression is as follows:
in the specific implementation, a Kendall rank correlation coefficient method is adopted to estimate parameters of a Gumbel-Hougaard Copula function. The Kendall correlation coefficient tau is related to the parameter theta by:
let { (x) 1 ,y 1 ),…,(x n ,y n ) Denotes random samples of n observations taken from successive random variables (X, Y), among which are samples
Different combinations of observations (x) i ,y i ) And (x) j ,y j ). The Kendall rank correlation coefficient tau of the sample is calculated by the following formula
Where sign (·) is a sign function.
3.3 forecasting facing annual regional precipitation
The early annual precipitation P is given t-i (i-1, 2, … L) value p t-i The corresponding face annual precipitation P t Has a conditional probability distribution function
Wherein Pro (. cndot.) represents the probability.
When the annual precipitation P facing the early annual period of L years is given t-i (i-1, 2, … L) value p t-i When confronted with annual precipitation P t Conditional probability distribution function F cL (p t ) Calculated by the following formula:
wherein, delta i The weight coefficient of earlier year i is represented, and the calculation formula is as follows:
wherein, tau i Is P t 、P t-i The two-variable Kendall rank correlation coefficient is calculated by equation (6).
Obtaining the apparent annual precipitation P t Conditional probability distribution function F cL (p t ) Then, according to the mathematical statistics principle, the median can be calculated and obtained as the face annual precipitation P t The predicted value of (2). Face annual precipitation P t Median p of tm Solving by:
F cL (p tm )＝0.5 (10)
in the present embodiment, a numerical solution is obtained by trial calculation of the solution equation (10) by the dichotomy.
4. And adjusting and determining dynamic control indexes of total water consumption of the facing annual region.
Face dynamic adjustment coefficient K of annual regional farmland irrigation water consumption t The calculation formula is as follows:
wherein p is 50％ In order to design regional annual precipitation corresponding to frequency 50% (horizontal years), an edge probability distribution function F is inquired P (. smallcap.) to give.
According to the dynamic adjustment coefficient K t Faced with dynamic control index W of total water consumption in annual region DT Can be calculated by the following formula:
W DT ＝W ST+ (K t -1)W SA (12)
in conclusion, the method establishes a relation curve of the average net water consumption per mu of regional farmland irrigation and the annual precipitation based on genetic programming, calculates the static control index of the farmland irrigation water consumption of the open-water annual region, predicts the precipitation of the facing annual region by adopting a Copula function, and adjusts and determines the dynamic control index of the total water consumption of the facing annual region. According to the regional water utilization dynamic control method, the withering change of natural incoming water of the regional regions facing the annual regions in the southern rich water areas can be considered, the regional water utilization static control index is adaptively adjusted according to the natural incoming water situation facing the annual regions to obtain the regional water utilization dynamic control index, the differentiated control of different incoming water frequencies is realized, the rigid constraint effect of water resources is better exerted, and the refinement level and the operability of regional water resource management are improved.
Claims (5)
1. A method for dynamically adjusting annual water total quantity control indexes in southern abundant water areas is characterized by comprising the following steps:
step 1, establishing a relation curve between the average net water consumption per mu and the annual precipitation of regional farmland irrigation based on genetic programming;
step 2, calculating a static control index of farmland irrigation water consumption in an open water year region;
step 3, forecasting the precipitation of the facing annual area by adopting a Copula function;
and 4, adjusting and determining dynamic control indexes of total water consumption of the faced annual region.
2. The method for dynamically adjusting the annual water total amount control index in the southern rich water region according to claim 1, wherein the method comprises the following steps: establishing a relation curve of the average net water consumption per mu and the annual precipitation of regional farmland irrigation based on genetic programming, enabling H and P to respectively represent the average net water consumption per mu and the annual precipitation of regional farmland irrigation, and performing symbolic regression by utilizing the genetic programming to establish the relation curve of the average net water consumption per mu and the annual precipitation of regional farmland irrigation, wherein the basic steps are as follows:
(1) determining an individual expression structure comprising a function set F and a terminator set T, F { +, -, ×,/, -V, log, exp }, T { (q, w };
(2) generating an initial population, randomly generating by using a mixing method, selecting formulas with different character compositions from a function set F and a terminator set T as initial individuals by using a growth method and a complete method which are respectively 50%, and setting the population number as M;
(3) calculating individual fitness, and judging the quality of the individual by taking the root mean square error as a fitness function, wherein the smaller the fitness value is, the better the individual is;
(4) generating a new generation of population, executing genetic operations and generating new individuals, wherein the main genetic operations comprise: firstly, copying existing excellent individuals, adding new groups, and correspondingly deleting inferior individuals; exchanging, namely exchanging partial nodes of the two selected individuals, and adding the two generated new individuals into a new group; mutation, randomly changing a certain part of individuals, and inserting new individuals into a new group; wherein the probability of duplication P r The cross probability is P c Probability of variation P m ；
(5) Repeating (3) and (4) until the termination condition is met, and selecting the bestThe result is used as the final solution, wherein G represents the iteration number, the initial population is the 0 th generation, and the termination criterion is that the maximum iteration algebra G is reached max ；
The explicit expression of the relation curve of the average net water consumption per mu and the annual precipitation of regional farmland irrigation obtained by the steps is as follows:
wherein,
the average net water consumption per mu for field irrigation by using genetic programming to perform symbolic regression calculation, wherein P is annual precipitation, f re And the equation (t) represents the functional relationship between the average acre net water consumption and the annual precipitation of regional farmland irrigation built by symbolic regression through genetic programming.
3. The method for dynamically adjusting the annual water total amount control index in the southern rich water region according to claim 1, wherein the method comprises the following steps: calculating a static control index of farmland irrigation water consumption in an open water year region; the method comprises the following specific steps:
(1) calculating the design frequency of the regional historical annual precipitation series year by year, and selecting the year closest to 50% of the design frequency of the annual precipitation as the representative year of the horizontal year;
(2) the proportion beta of the irrigation water consumption of the farmland in the representative year to the total water consumption is calculated by statistics, and then the static control index W of the total water consumption of the horizontal year area is combined ST Calculating the static control index of the irrigation water consumption of the farmland in the open water year by the following formula:
W SA ＝β·W ST (2)
wherein, W SA And (3) representing the static control index of the irrigation water consumption of farmland in open water year areas.
4. The method for dynamically adjusting the annual water total amount control index in the southern rich water region according to claim 1, wherein the method comprises the following steps: adopting a Copula function to predict the annual regional precipitation, and specifically comprising the following steps:
(1) determining an edge probability distribution function of regional annual precipitation;
forecasting the precipitation of the facing annual area by adopting a Copula function; the method specifically comprises the following steps: gamma distribution is adopted as an edge distribution line type of annual precipitation, and a linear moment method is adopted to estimate parameters of the edge distribution line type;
(2) constructing a joint probability distribution function of annual and early annual precipitation of the region by using a Copula function;
determining the longest time lag L of the early annual precipitation on the face of annual influence according to the autocorrelation analysis of the regional historical annual precipitation series, and assuming P t 、P t-i (i-1, 2, … L) indicates the annual and early annual precipitation of the region, respectively, p t 、p t-i Respectively corresponding realized values, P t 、P t-i Having the same edge probability distribution function F P (. o) the corresponding probability density function is f P (·)；
P t 、P t-i The joint distribution function of (a) can be represented by a two-dimensional Copula function:
F(p t ,p t-i )＝C θ (F P (p t ),F P (p t-i ))＝C θ (u,v) (3)
wherein, theta is a parameter of a Copula function; u ═ F P (p t ),v＝F P (p t-i ) Is an edge distribution function;
adopting Gumbel-Hougaard Copula function to construct a joint probability distribution function of the annual and early annual precipitation amount of an area, wherein the expression is as follows:
estimating parameters of a Gumbel-Hougaard Copula function by adopting a Kendall rank correlation coefficient method; the Kendall correlation coefficient tau is related to the parameter theta by:
let { (x) 1 ,y 1 ),…,(x n ,y n ) Denotes random samples of n observations taken from successive random variables (X, Y), among which are samples
Different combinations of observations (x) i ,y i ) And (x) j ,y j ) (ii) a The Kendall rank correlation coefficient tau of the sample is calculated by the following formula
Wherein sign (·) is a sign function;
(3) forecasting the precipitation of the facing annual area;
the early annual precipitation P is given t-i (i-1, 2, … L) value p t-i The corresponding face annual precipitation P t The value of (a) has a conditional probability distribution function;
wherein Pro (·) represents a probability;
when the annual precipitation P facing the early annual period of L years is given t-i (i-1, 2, … L) value p t-i When confronted with annual precipitation P t Conditional probability distribution function F cL (p t ) Calculated by the following formula:
wherein, delta i Representing the ith year of the previous periodThe weight coefficient is calculated by the formula:
wherein, tau i Is P t 、P t-i Kendall rank correlation coefficients of the two variables are calculated through an equation (6);
obtaining the apparent annual precipitation P t Conditional probability distribution function F cL (p t ) Then, according to the mathematical statistics principle, the median can be calculated and obtained as the face annual precipitation P t The predicted value of (2); face annual precipitation P t Median p of tm Solving by:
F cL (p tm )＝0.5 (10)
and (4) solving the formula (10) by adopting a dichotomy trial calculation to obtain a numerical solution.
5. The method for dynamically adjusting the annual water total amount control index in the southern rich water region according to claim 1, wherein the method comprises the following steps: the adjustment determines dynamic control indexes of total water consumption of the facing annual region; the method comprises the following specific steps:
dynamic adjustment coefficient K for farmland irrigation water consumption facing annual region t The calculation formula is as follows:
wherein p is 50％ In order to design regional annual precipitation corresponding to 50% horizontal years of frequency, an edge probability distribution function F is inquired P (. to obtain;
according to the dynamic adjustment coefficient K t Faced with dynamic control index W of total water consumption in annual region DT Can be calculated by the following formula:
W DT ＝W ST+ (K t -1)W SA (12)。
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