CN113052455A - Method and device for fine evaluation of watershed runoff hydrological conditions - Google Patents

Method and device for fine evaluation of watershed runoff hydrological conditions Download PDF

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CN113052455A
CN113052455A CN202110303522.9A CN202110303522A CN113052455A CN 113052455 A CN113052455 A CN 113052455A CN 202110303522 A CN202110303522 A CN 202110303522A CN 113052455 A CN113052455 A CN 113052455A
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廖云
潘连荣
郑志豪
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Guangxi Power Grid Co Ltd
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Abstract

The invention discloses a method and a device for fine evaluation of watershed runoff hydrological conditions, wherein the method comprises the following steps: acquiring data of historical runoff of a drainage basin, and determining a sample matrix according to the data; fitting according to the sample matrix to obtain a normal distribution probability density function; obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution, and determining a critical value of the drainage basin runoff level through the cumulative distribution function of normal distribution; obtaining an accumulated probability matrix of the sample matrix through calculation, and obtaining the accumulated probability of the critical value of the runoff plump and flat level through calculation; and comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample. In the implementation of the method, the hydrological conditions of the runoff of the drainage basin can be reflected finely, the calculation speed is high, and the engineering application is facilitated.

Description

Method and device for fine evaluation of watershed runoff hydrological conditions
Technical Field
The invention relates to the technical field of watershed runoff hydrological conditions, in particular to a method and a device for fine evaluation of the watershed runoff hydrological conditions.
Background
The strategy of 'three-step walking' in the development of hydropower in China is provided, and the first step is that the installed capacity of the hydropower can reach 3.5 hundred million kilowatts and the annual generated energy can reach 13220 hundred million kilowatt hours in 2020; the second step is that the installed capacity of the conventional water is estimated to reach 4.3 hundred million kilowatts in 2030 years, and the annual generated energy is 18530 hundred million kilowatt hours; and the third step is that the installed capacity of the conventional water is estimated to reach 5.1 hundred million kilowatts in 2050, and the annual energy generation is 14050 hundred million kilowatt hours.
In order to reasonably and effectively utilize hydroelectric power generation, hydrologic prediction plays an important role, and the longer the forecast period of hydrologic prediction is, the higher the prediction precision is, and the stronger the guiding significance on power generation, flood control, navigation and the like of a hydropower station is. And the analysis and evaluation of the annual runoff hydrological conditions of the watershed have important significance for knowing the evolution characteristics of a hydrological power system and effectively guiding medium and long term hydrological forecast and reservoir dispatching operation management. At present, the research on the hydrological condition analysis of the runoff of the drainage basin is only divided into intervals according to the rich level, the flat level and the dry level, and the refinement degree is not enough.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method and a device for finely evaluating the hydrological conditions of runoff in a basin, which can finely reflect the hydrological conditions of the runoff in the basin.
In order to solve the technical problem, an embodiment of the present invention provides a method for fine evaluation of a watershed runoff hydrological condition, where the method includes:
acquiring data of historical runoff of a drainage basin, and determining a sample matrix according to the data;
fitting according to the sample matrix to obtain a normal distribution probability density function;
obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution, and determining a critical value of the drainage basin runoff level through the cumulative distribution function of normal distribution;
obtaining an accumulated probability matrix of the sample matrix through calculation, and obtaining the accumulated probability of the critical value of the runoff plump and flat level through calculation;
and comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample.
Optionally, the obtaining a normal distribution probability density function according to the sample matrix fitting includes:
determining whether the sample matrix conforms to normal distribution through K-S test;
and fitting according to the sample matrix to obtain a formula f (x) of a normal distribution probability density function.
Optionally, the obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution, and determining the critical value of the level of fluvial runoff peak-to-average level according to the cumulative distribution function of normal distribution includes:
according to the formula f (x) of the normal distribution density function, obtaining a formula F (x) of a cumulative distribution function of normal distribution through calculation;
and according to a formula F (x) of the cumulative distribution function of the normal distribution, considering the probability of different hydrological conditions of the runoff of the basin, and determining the critical value of the level of the runoff of the basin to be level.
Optionally, the obtaining of the cumulative probability matrix of the sample matrix through calculation includes:
and calculating to obtain a cumulative probability matrix of the sample matrix based on the cumulative distribution function of the normal distribution.
In addition, the embodiment of the invention also provides a device for fine evaluation of the hydrological conditions of the runoff in the basin, which comprises the following steps:
a data acquisition module: the method comprises the steps of obtaining data of historical runoff of a watershed and determining a sample matrix according to the data;
a function fitting module: the normal distribution probability density function is obtained according to the sample matrix fitting;
a threshold determination module: the system is used for obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution and determining a critical value of the level of the drainage basin runoff abundance and average dryness through the cumulative distribution function of normal distribution;
a cumulative probability calculation module: the accumulated probability matrix of the sample matrix is obtained through calculation, and the accumulated probability of the critical value of the runoff abundance level of the drainage basin is obtained through calculation;
a cumulative probability comparison module: and the method is used for comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample.
Optionally, the function fitting module further includes: for determining whether the sample matrix conforms to a normal distribution by a K-S test; and fitting according to the sample matrix to obtain a formula f (x) of a normal distribution probability density function.
Optionally, the critical value determining module further includes: a formula F (x) for obtaining a cumulative distribution function of normal distribution by calculation according to the formula f (x) of the normal distribution density function; and according to a formula F (x) of the cumulative distribution function of the normal distribution, considering the probability of different hydrological conditions of the runoff of the basin, and determining the critical value of the level of the runoff of the basin to be level.
Optionally, the cumulative probability calculating module further includes: and the cumulative probability matrix is used for obtaining the cumulative probability matrix of the sample matrix through calculation based on the cumulative distribution function of the normal distribution.
In the implementation of the invention, according to the characteristics of the historical runoff data of the drainage basin, a normal distribution probability density function is fitted through the historical data, and an accumulative distribution function is obtained according to the normal distribution probability density function; considering the historical occurrence probability of hydrological conditions of different drainage basins, formulating classification grade standard for different rugged critical values of the drainage basins according to the accumulated probability, and finally comparing the accumulated probability of actual runoff data of the drainage basins with the accumulated probability corresponding to each rugged critical value to obtain corresponding refined hydrological conditions; starting from the internal rules of the basin historical data, the hydrological conditions of the basin runoff can be reflected finely, the calculation speed is high, and engineering application is facilitated.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for fine evaluation of watershed runoff hydrological conditions in an embodiment of the invention;
fig. 2 is a schematic structural composition diagram of a device for fine evaluation of watershed runoff hydrological conditions in the embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for fine evaluation of watershed runoff hydrological conditions in an embodiment of the present invention.
As shown in fig. 1, a method for fine evaluation of hydrological conditions of runoff in a drainage basin includes:
s11: acquiring data of historical runoff of a drainage basin, and determining a sample matrix according to the data;
specifically, acquiring data of basin historical runoff in the nth year, and setting a runoff process in the nth year, wherein the runoff process is represented as an n x 1 order matrix.
S12: fitting according to the sample matrix to obtain a normal distribution probability density function;
in a specific implementation process of the present invention, the obtaining of the normal distribution probability density function according to the sample matrix fitting includes: determining whether the sample matrix conforms to normal distribution through K-S test; and fitting according to the sample matrix to obtain a formula f (x) of a normal distribution probability density function.
Specifically, the K-S test of a single sample is a method for checking whether a single sample conforms to a certain specific distribution; comparing the accumulated frequency distribution of the sample data with a specific theoretical distribution, and if the difference between the accumulated frequency distribution and the specific theoretical distribution is small, concluding that the sample conforms to the specific distribution; the method comprises the following steps:
(1) definition hypothesis H0: the overall distribution from which the sample came obeys a particular distribution;
(2) definition hypothesis H1: the overall distribution from which the sample came does not follow a particular distribution;
(3) f (x) represents the cumulative distribution function of the sampled cost matrix of the present invention, Fn(x) A cumulative distribution function representing a particular distribution; d is F (x) and Fn(x) The maximum value of the gap is given by the formula D ═ max | Fn(x)-F(x)|；
(4) When actually observing D>D (n, α) (where D (n, α) is a rejection threshold for D with a significance level of α and a sample size of n), rejecting hypothesis H0Accept hypothesis H1On the contrary, the hypothesis H is rejected1Accept hypothesis H0。
S13: obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution, and determining a critical value of the drainage basin runoff level through the cumulative distribution function of normal distribution;
in a specific implementation process of the present invention, the obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution, and determining a critical value of the level of the drainage basin runoff abundance and average dryness through the cumulative distribution function of normal distribution includes: according to the formula f (x) of the normal distribution density function, obtaining a formula F (x) of a cumulative distribution function of normal distribution through calculation; and according to a formula F (x) of the cumulative distribution function of the normal distribution, considering the probability of different hydrological conditions of the runoff of the basin, and determining the critical value of the level of the runoff of the basin to be level.
Specifically, the division standards of different Fengping critical values are shown in table 1, and when F (x) is less than or equal to 0.05, the hydrological conditions are extremely withered; the hydrological condition is (extremely dry, dry) when F (x) is more than 0.05 and less than or equal to 0.2, (dry, flat) when F (x) is more than 0.2 and less than or equal to 0.5, (flat, rich) when F (x) is more than 0.5 and less than or equal to 0.8, (rich, ultra-rich) when F (x) is more than 0.8 and less than 0.95, and (ultra-rich) when F (x) is more than or equal to 0.95.
TABLE 1 different Fengping Range division criteria
Critical value of Fengping Division criteria
Super withered F(x)＝0.05
Withered food F(x)＝0.2
Flat plate F(x)＝0.5
Feng (Chinese character of 'feng') F(x)＝0.8
Tefeng (super harvest) F(x)＝0.95
S14: obtaining an accumulated probability matrix of the sample matrix through calculation, and obtaining the accumulated probability of the critical value of the runoff plump and flat level through calculation;
in a specific implementation process of the present invention, the obtaining of the cumulative probability matrix of the sample matrix by calculation includes: and calculating to obtain a cumulative probability matrix of the sample matrix based on the cumulative distribution function of the normal distribution.
S15: and comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample.
It should be noted that the fine division of the hydrological conditions refers to: withered X, flat soft X, and soft X (X is in the range of (0, 1)).
Specifically, the cumulative probability matrix of the sample matrix is m, the interval where m is located is judged, the value of the sample is extremely withered if m belongs to (0, 0.05), the value of the sample is extremely withered X and X is (0.2-m)/0.15 if m belongs to (0.05, 0.2), the value of the sample is flat parawithered X and X is (0.5-m)/0.3 if m belongs to (0.2, 0.5), the value of the sample is flat paraplump X and X is (m-0.5)/0.3 if m belongs to (0.8,0.95), the value of the sample is FenteFengX and X is (m-0.8)/0.15 if m belongs to [0.95,1 ], and the value of the sample is extremely plump.
In the implementation of the invention, according to the characteristics of the historical runoff data of the drainage basin, a normal distribution probability density function is fitted through the historical data, and an accumulative distribution function is obtained according to the normal distribution probability density function; considering the historical occurrence probability of hydrological conditions of different drainage basins, formulating classification grade standard for different rugged critical values of the drainage basins according to the accumulated probability, and finally comparing the accumulated probability of actual runoff data of the drainage basins with the accumulated probability corresponding to each rugged critical value to obtain corresponding refined hydrological conditions; starting from the internal rules of the basin historical data, the hydrological conditions of the basin runoff can be reflected finely, the calculation speed is high, and engineering application is facilitated.
Example two
In the specific implementation, taking the runoff data of a certain watershed 1956-1964 as an example, the specific steps are as follows:
(1) acquiring historical runoff data of a drainage basin, and determining a sample matrix; take runoff data of a certain watershed 1956-1964 as an example, and represent the runoff data as a 55-by-1 order matrix;
(2) fitting a normal distribution probability density function according to the sample matrix, solving the mean value and the standard deviation of all samples in the sample matrix, and determining that the sample matrix conforms to normal distribution through K-S test of a single sample; table 2 shows the single K-S test result of the sample matrix, which indicates that the sample matrix conforms to normal distribution; f (x) is obtained according to a formula of a normal distribution probability density function;
Figure BDA0002987213250000061
TABLE 2 sample matrix Individual K-S test results
Figure BDA0002987213250000062
Figure BDA0002987213250000071
(3) Determining a critical value of the drainage basin runoff plump and flat level by utilizing a cumulative distribution function of normal distribution; the division standards of different peak-to-average dry critical values are shown in table 1; the specific process is as follows: calculating a cumulative distribution function F (x) according to the probability density function f (x) obtained in the step (2), considering the probability of different hydrological conditions of the runoff of the drainage basin, and when the F (x) is less than or equal to 0.05, the hydrological conditions are extremely withered; the hydrological condition is (extremely dry, dry) when F (x) is more than 0.05 and less than or equal to 0.2, (dry, flat) when F (x) is more than 0.2 and less than or equal to 0.5, (flat, rich) when F (x) is more than 0.5 and less than or equal to 0.8, (rich, ultra-rich) when F (x) is more than 0.8 and less than 0.95, and (ultra-rich) when F (x) is more than or equal to 0.95.
(4) Comparing the cumulative probability corresponding to each sample of the sample matrix with the cumulative probability of the corresponding critical value to obtain a hydrologic condition refined evaluation result of each sample; the fine division of the hydrological conditions refers to: withered X, flat soft X, and soft X (X is in the range of (0, 1)); the specific calculation steps are as follows:
1) calculating the cumulative probability m corresponding to each sample of the sample matrix by using a cumulative distribution function of normal distribution;
2) judging the interval where m is located, and if m belongs to (0, 0.05), determining the value of the sample to be extremely dry; the value of the sample is extremely withered and partial withered X and X is (0.2-m)/0.15 if m e (0.2, 0.5), flat partial withered X and X is (0.5-m)/0.3 if m e (0.5, 0.8), flat partial rich X and X is (m-0.5)/0.3 if m e (0.8,0.95), and extremely rich X and X is (m-0.8)/0.15 if m e [0.95,1 ].
The fine evaluation results of the watershed runoff hydrological conditions obtained by the method are shown in table 3.
Table 3 table of fine division results of watershed hydrological conditions
Year of year Fengping withering level Year of year Fengping withering level Year of year Fengping withering level
1956 Tefeng (super harvest) 1975 Fengteifeng 44.5% 1994 Average rate is 52%
1957 Average degree is 41.1% 1976 Fengteifeng 37.7% 1995 Subtilan 22.9%
1958 Flat and rich 1.7% 1977 Subtitylum kumtschaticum 85.3% 1996 Is flat and rich in 16.1 percent
1959 46.7 percent of Subtilan 1978 Flat plate 1997 Flat and rich 81.1 percent
1960 Even slightly withered by 30.2 percent 1979 Fengteifeng 28.4% 1998 Is flat and rich in 79.8 percent
1961 Fengteifeng 15.6% 1980 Fengteifeng 10.4% 1999 Subtilan 16.2%
1962 Tefeng (super harvest) 1981 Flat and rich 15.3% 2000 67.1 percent of Subtilasu
1963 Is 50.9 percent flat and rich 1982 Is flat and slightly rich in 40.5 percent 2001 Fengteifeng 2.4%
1964 Even slightly withered 91.4% 1983 Flat and rich 43.1% 2002 Flat and rich 95.2%
1965 Flat and rich 88.2 percent 1984 32.1 percent of Pingfeng 2003 43.4 percent of Subtilan
1966 38.6 percent of Subtilan 1985 Average degree is 48% 2004 Is flat and rich in 67.3 percent
1967 Even though it is 34% 1986 Tefeng (super harvest) 2005 82.9 percent of average withered fruit
1968 Super withered 1987 Fengteifeng 69.8% 2006 98.1 percent of average withered fruit
1969 Subtitylvanine 59.1% 1988 38.6 percent of Subtilan 2007 Super withered
1970 Subtitylvanine 59.1% 1989 34.9 percent of flat and flat 2008 Flat and rich 17.7%
1971 35.5 percent of Subtilan 1990 Average rate is 52% 2009 Even partial withered 60.7%
1972 Flat and rich88.6％ 1991 Average degree is 22.9% 2010 Fengteifeng 22.6%
1973 Fengteifeng 33% 1992 Fengteifeng 86% / /
1974 62.4 percent of Subtilan 1993 46.6 percent of Subtilan / /
In the implementation of the invention, according to the characteristics of the historical runoff data of the drainage basin, a normal distribution probability density function is fitted through the historical data, and an accumulative distribution function is obtained according to the normal distribution probability density function; considering the historical occurrence probability of hydrological conditions of different drainage basins, formulating classification grade standard for different rugged critical values of the drainage basins according to the accumulated probability, and finally comparing the accumulated probability of actual runoff data of the drainage basins with the accumulated probability corresponding to each rugged critical value to obtain corresponding refined hydrological conditions; starting from the internal rules of the basin historical data, the hydrological conditions of the basin runoff can be reflected finely, the calculation speed is high, and engineering application is facilitated.
EXAMPLE III
Referring to fig. 2, fig. 2 is a schematic structural composition diagram of a device for fine evaluation of watershed runoff hydrological conditions in an embodiment of the present invention.
As shown in fig. 2, an apparatus for fine evaluation of hydrological conditions of runoff in a drainage basin, the apparatus comprising:
the data acquisition module 11: the method comprises the steps of obtaining data of historical runoff of a watershed and determining a sample matrix according to the data;
function fitting module 12: the normal distribution probability density function is obtained according to the sample matrix fitting;
in a specific implementation process of the present invention, the function fitting module 12 further includes: determining whether the sample matrix conforms to normal distribution through K-S test; and fitting according to the sample matrix to obtain a formula f (x) of a normal distribution probability density function.
The critical value determination module 13: the system is used for obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution and determining a critical value of the level of the drainage basin runoff abundance and average dryness through the cumulative distribution function of normal distribution;
in an implementation process of the present invention, the critical value determining module 13 further includes: a formula F (x) for obtaining a cumulative distribution function of normal distribution by calculation according to the formula f (x) of the normal distribution density function; and according to a formula F (x) of the cumulative distribution function of the normal distribution, considering the probability of different hydrological conditions of the runoff of the basin, and determining the critical value of the level of the runoff of the basin to be level.
Cumulative probability calculation module 14: the accumulated probability matrix of the sample matrix is obtained through calculation, and the accumulated probability of the critical value of the runoff abundance level of the drainage basin is obtained through calculation;
in a specific implementation process of the present invention, the cumulative probability calculating module 14 further includes: and the cumulative probability matrix is used for obtaining the cumulative probability matrix of the sample matrix through calculation based on the cumulative distribution function of the normal distribution.
Cumulative probability comparison module 15: and the method is used for comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample.
Specifically, the working principle of the device related function module according to the embodiment of the present invention may refer to the related description of the method embodiment, and is not described herein again.
In the implementation of the invention, according to the characteristics of the historical runoff data of the drainage basin, a normal distribution probability density function is fitted through the historical data, and an accumulative distribution function is obtained according to the normal distribution probability density function; considering the historical occurrence probability of hydrological conditions of different drainage basins, formulating classification grade standard for different rugged critical values of the drainage basins according to the accumulated probability, and finally comparing the accumulated probability of actual runoff data of the drainage basins with the accumulated probability corresponding to each rugged critical value to obtain corresponding refined hydrological conditions; starting from the internal rules of the basin historical data, the hydrological conditions of the basin runoff can be reflected finely, the calculation speed is high, and engineering application is facilitated.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
In addition, the method and the device for fine evaluation of the runoff hydrological conditions of the watershed provided by the embodiment of the invention are described in detail, a specific example is adopted to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (8)

1. A method for fine evaluation of watershed runoff hydrological conditions is characterized by comprising the following steps:
acquiring data of historical runoff of a drainage basin, and determining a sample matrix according to the data;
fitting according to the sample matrix to obtain a normal distribution probability density function;
obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution, and determining a critical value of the drainage basin runoff level through the cumulative distribution function of normal distribution;
obtaining an accumulated probability matrix of the sample matrix through calculation, and obtaining the accumulated probability of the critical value of the runoff plump and flat level through calculation;
and comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample.
2. The method for fine evaluation of the hydrological conditions of watershed runoff according to claim 1, wherein the fitting of the sample matrix to obtain a normally distributed probability density function comprises:
determining whether the sample matrix conforms to normal distribution through K-S test;
and fitting according to the sample matrix to obtain a formula f (x) of a normal distribution probability density function.
3. The method for fine evaluation of the hydrological condition of the drainage basin runoff according to claim 1, wherein the step of obtaining the cumulative distribution function of the normal distribution according to the probability density function of the normal distribution, and the step of determining the critical value of the level of the drainage basin runoff peak-to-average level through the cumulative distribution function of the normal distribution comprises the following steps:
according to the formula f (x) of the normal distribution density function, obtaining a formula F (x) of a cumulative distribution function of normal distribution through calculation;
and according to a formula F (x) of the cumulative distribution function of the normal distribution, considering the probability of different hydrological conditions of the runoff of the basin, and determining the critical value of the level of the runoff of the basin to be level.
4. The method for fine evaluation of hydrological conditions of watershed runoff according to claim 1, wherein the obtaining of the cumulative probability matrix of the sample matrix through calculation comprises:
and calculating to obtain a cumulative probability matrix of the sample matrix based on the cumulative distribution function of the normal distribution.
5. A device for fine evaluation of hydrological conditions of runoff in a drainage basin, the device comprising:
a data acquisition module: the method comprises the steps of obtaining data of historical runoff of a watershed and determining a sample matrix according to the data;
a function fitting module: the normal distribution probability density function is obtained according to the sample matrix fitting;
a threshold determination module: the system is used for obtaining a cumulative distribution function of normal distribution according to the probability density function of normal distribution and determining a critical value of the level of the drainage basin runoff abundance and average dryness through the cumulative distribution function of normal distribution;
a cumulative probability calculation module: the accumulated probability matrix of the sample matrix is obtained through calculation, and the accumulated probability of the critical value of the runoff abundance level of the drainage basin is obtained through calculation;
a cumulative probability comparison module: and the method is used for comparing the cumulative probability matrix of the sample matrix with the cumulative probability of the critical value of the runoff plump and flat level of the drainage basin to obtain a hydrographic condition refined evaluation result of the sample.
6. The apparatus for fine-evaluation of hydrological conditions of watershed runoff according to claim 5, wherein the function fitting module further comprises: for determining whether the sample matrix conforms to a normal distribution by a K-S test; and fitting according to the sample matrix to obtain a formula f (x) of a normal distribution probability density function.
7. The apparatus for fine evaluation of hydrological conditions of runoff according to claim 5, wherein the critical value determining module further comprises: a formula F (x) for obtaining a cumulative distribution function of normal distribution by calculation according to the formula f (x) of the normal distribution density function; and according to a formula F (x) of the cumulative distribution function of the normal distribution, considering the probability of different hydrological conditions of the runoff of the basin, and determining the critical value of the level of the runoff of the basin to be level.
8. The apparatus for fine evaluation of hydrological conditions of runoff according to claim 5, wherein the cumulative probability calculation module further comprises: and the cumulative probability matrix is used for obtaining the cumulative probability matrix of the sample matrix through calculation based on the cumulative distribution function of the normal distribution.
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