CN110390428B - Super-long-term prediction method for super-rich water years of reservoir water - Google Patents
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Abstract
The invention discloses a super-long-term prediction method for a super-rich water year of reservoir water. The method comprises the following steps: respectively taking the relative number of the sunblack as an X axis, the lunar declination angle as a Y axis, the date of the near-day point as an X axis and the Ethernet Yang Heizi as a Y axis, drawing a first to a third compound factor point clustering graphs, respectively marking out a super-great-water year point aggregation area on the three compound factor point clustering graphs on the basis of a clustering effect, obtaining the relative number of the sunblack of the year to be predicted, the lunar declination angle and the date of the near-day point, respectively finding out the super-great-water year point aggregation area to which the year to be predicted belongs on the three compound factor point clustering graphs, and finally processing historical year-coming water data with high frequency of occurrence in the super-great-water year point aggregation area to obtain coming water data of the year to be predicted. The method provided by the invention can be used for carrying out ultra-long-term prediction on the extra-rich water years of the incoming water of the reservoir based on a plurality of astronomical factors, and the prediction precision is improved compared with the conventional prediction method based on single astronomical factors.
Description
Technical Field
The invention belongs to the technical field of hydrologic long-term forecasting, and particularly relates to a super-long-term forecasting method for a super-rich water year of reservoir water supply.
Background
At present, long-term prediction and ultra-long-term prediction of water coming from a reservoir, especially the forecast of the super-rich water year (flood year) of the reservoir have the characteristics of high prediction difficulty, low precision, difficult application and the like. Therefore, at present, the reservoir dispatching generally adopts the principle of 'forecasting the rain on the ground and taking long-term prediction as reference'. However, no matter the requirements of cascade reservoir power generation, flood control in drainage basin and the like are met, long-term/ultra-long-term reservoir extra-high water year prediction meeting the precision requirement is urgently needed to give full play to the regulation and storage capacity of the reservoir, so that a reservoir management unit and a drainage basin management mechanism can adopt risk pre-control scheduling in advance, adopt measures of full power generation and large power generation in advance, reduce flood discharge and water abandonment in the later period, convert flood disasters into red benefits, increase the power generation capacity and reduce the flood damage of the cascade reservoir.
The water coming from the reservoir is greatly influenced by astronomical factors, especially the super-rich water year of the reservoir. At present, relevant reports of predicting water coming from a reservoir in the coming years according to astronomical factors exist, but the prediction is generally carried out based on single astronomical factors (such as the relative number of sun and black seeds), and the defect is that the prediction precision is not high.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method for predicting the super-long term of the super-rich water years of the incoming water of the reservoir, which carries out super-long term prediction on the super-rich water years of the incoming water of the reservoir according to the coupling influence effect of a plurality of astronomical factors.
In order to achieve the purpose, the invention adopts the following technical scheme:
a super-long-term prediction method for a super-rich water year of reservoir water comprises the following steps:
step 1, acquiring annual water (annual warehousing flow), sun black relative number, moon declination angle and near-day date of a past year of a reservoir, and determining annual water level of the past year, wherein the annual water level comprises: extra-rich water years, partial-rich water years, open water years, partial-dry water years, extra-dry water years;
step 2, drawing a first composite factor point concentration graph by taking the relative number of the ether Yang Heizi as an X axis and the lunar declination angle as a Y axis and representing the annual water level of data points by different symbols; taking the date of the near-day point as an X axis, taking the declination angle of the moon as a Y axis, representing the annual water level of the data point by different symbols, and drawing a second composite factor point convergence graph; taking the date of the near-day point as an X axis, taking the relative number of the Ethernet Yang Heizi as a Y axis, representing the annual water level of the data point by using different symbols, and drawing a third composite factor point convergence graph;
step 3, marking super-Fengshui annual point gathering areas in the first complex factor point gathering graph, the second complex factor point gathering graph and the third complex factor point gathering graph respectively;
step 5, respectively counting the historical years and the occurrence times corresponding to the data points in the Q1, the Q2 and the Q3, and if a certain historical year appears 3 times and other historical years all appear 1 time, taking the annual water and the monthly water of the historical year as the annual water and the monthly water of the year to be predicted; otherwise, respectively weighing and averaging annual water and monthly water of more than 2 times of historical years according to the occurrence times to obtain the annual water and monthly water of the year to be predicted.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the relative number of the Ether Yang Heizi is taken as an X axis, the lunar declination angle is taken as a Y axis, the date of the near day point is taken as an X axis, the declination angle of the lunar moon is taken as a Y axis, the date of the near day point is taken as an X axis, and the relative number of the Ether Yang Heizi is taken as a Y axis, the first to third composite factor dot concentration maps are drawn, the super-Fengshi year point aggregation areas are respectively marked out on the three composite factor dot concentration maps based on the clustering effect, the relative number of sunblack, the lunar declination angle and the date of the near day point of the year to be predicted are obtained, the super-Fengshi year point aggregation areas Q1, Q2 and Q3 to which the year to be predicted belong are respectively found out on the three composite factor dot concentration maps, and finally, the coming water data of the year to be predicted is obtained by processing the coming water data of the historical year with high occurrence frequency in the Q1, Q2 and Q3, so that the influence of a plurality of astronomical factors is used for carrying out the super-Fengshi super-water long-coming water prediction for the super-coming water long term prediction of the reservoir. Compared with the existing prediction method based on single astronomical factors, the prediction precision is greatly improved.
Drawings
FIG. 1 is a first single-factor point focusing graph of a certain reservoir with the relative number of sun black seeds as the X axis and water in the year as the Y axis;
FIG. 2 is a second single-factor pointfocusing graph of a certain reservoir with moon declination angle as the X-axis and water in the year as the Y-axis;
FIG. 3 is a third single-factor dotting chart of a certain reservoir with the date of the near-day point as the X-axis and the water of the year as the Y-axis;
FIG. 4 is a first composite factor dot concentration diagram and a super-Fengshui annual point concentration area of a certain reservoir with the relative number of Sun black seeds as the X axis and the lunar declination angle as the Y axis;
FIG. 5 is a second complex factor dot-concentration map and a super-Fengshui annual point concentration region of a certain reservoir with the date of the near-day point as the X-axis and the relative number of Ethern Yang Heizi as the Y-axis;
FIG. 6 is a third composite factor dot-concentration chart and a super-Fengshui annual point concentration area of a certain reservoir with the date of the near-day point as the X-axis and the relative number of Ethern Yang Heizi as the Y-axis.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The embodiment of the invention provides a super-long-term prediction method for a super-rich water year of reservoir water, which comprises the following steps:
s101, acquiring the annual water, the relative number of sunblack seeds, the lunar declination angle and the date of the near day (lunar calendar) of the past year of the reservoir, and determining the annual water level of the past year, wherein the annual water level comprises: extra-rich water years, partial-rich water years, open water years, partial-dry water years, extra-dry water years;
s102, taking the relative number of the ether Yang Heizi as an X axis, taking the lunar declination angle as a Y axis, representing the annual water level of a data point by different symbols, and drawing a first composite factor point concentration graph; taking the date of the near-day point as an X axis, taking the lunar declination angle as a Y axis, representing the annual water level of the data point by different symbols, and drawing a second composite factor point convergence graph; taking the date of the near-day point as an X axis, taking the relative number of the Ethernet Yang Heizi as a Y axis, representing the annual water level of the data point by different symbols, and drawing a third composite factor point focusing graph;
s103, marking a super-rich water year point gathering area in the first complex factor point gathering graph, the second complex factor point gathering graph and the third complex factor point gathering graph respectively;
s104, obtaining the relative number a of sunblack seeds, the lunar declination angle b and the near-day date c of the year to be predicted, and finding the special Fengshui annual point gathering areas Q1, Q2 and Q3 to which the points (a, b), (c, b) and (c, a) belong in the first complex factor point gathering graph, the second complex factor point gathering graph and the third complex factor point gathering graph respectively;
s105, respectively counting the historical years and the occurrence times corresponding to the data points in the Q1, the Q2 and the Q3, and if a certain historical year occurs 3 times and other historical years all occur 1 time, taking the annual water and the monthly water of the historical year as the annual water and the monthly water of the year to be predicted; otherwise, respectively weighing and averaging annual water and monthly water of more than 2 times of historical years according to the occurrence times to obtain the annual water and monthly water of the year to be predicted.
In this embodiment, step S101 is mainly used to obtain historical data of the reservoir. Including the year water of the reservoir, the relative number of sun black, the lunar declination angle and the date of the near day. The average value of annual water, namely annual warehousing flow is generally in units of cubic meters per second. According to the provisions of the hydrological information forecast Specification (GB/T22482-2008), the annual water level comprises 5 grades, and the grades are respectively arranged from large to small according to the incoming water: the year of full water, the year of open water, the year of dry water and the year of dry water. On the basis, 1 extra-high water year and 1 extra-low water year are added before the high water year and after the low water year respectively to obtain 7 grades. The relative number of solar black seeds, the lunar declination angle and the date of the near day of each year are three astronomical factors with obvious influence on incoming water.
In this embodiment, step S102 is mainly used to draw 3 complex factor pointgrams based on pairwise combinations of the acquired 3 astronomical factors. The year water level of the data points is represented by different symbols in each multifactor point plot, for example, the texas water year data points are represented by solid squares, and the water year data points are represented by solid triangles, as shown in fig. 4 to 6.
In this embodiment, step S103 is mainly used to mark the super-feng water year point gathering areas in the 3 multiple-factor point gathering maps respectively based on the clustering effect. As shown in fig. 4 to 6, each rectangular area in the figure is a super-rich water year point gathering area. The clustering effect is derived from 'things-by-things and people-by-groups', and means that objects in a certain category objectively have an automatic clustering effect. The characteristics of the data points for expressing the same incoming water level are concentrated to a certain area or a plurality of areas. And enclosing the area with more concentrated super-Fengshui annual points to obtain a super-Fengshui annual point gathering area. Because the water of the extra-high water year is relatively close to that of the year of the extra-high water year, the nearby water-high year points are also brought into the gathering area of the extra-high water year points as much as possible. The purpose of drawing the extra-Feng water annual point gathering area is to estimate the incoming water of the year to be predicted by using data points in the extra-Feng water annual point gathering area to which the year to be predicted belongs.
In this embodiment, step S104 is mainly used to obtain 3 astronomical factor data of the year to be predicted from the national astronomical phenomena and the spatial environment prediction center of the chinese academy of sciences, and find the super-abundance water year point aggregation areas to which the year to be predicted belongs in the 3 composite factor point aggregation maps, respectively. The specific method is that the relative number a of the solar black seeds, the lunar declination angle b and the date c of the near-day point form coordinates (a, b), (c, b) and (c, a), and points corresponding to the coordinates are respectively drawn in the first to third compound factor point concentration graphs, so that the super-Fengshui annual point concentration areas which the coordinates belong to are obtained. If one or more points in (a, b), (c, b) and (c, a) do not belong to the extra-rich water year point gathering area, the possibility that the year to be predicted is the extra-rich water year is not high, and the method is not suitable for predicting the year to be predicted; or, if the method described in this embodiment is still used for prediction in this situation, the prediction result will not meet the accuracy requirement.
In the present embodiment, step S105 is mainly used to calculate the annual water and the monthly water of the year to be predicted. The accuracy of prediction using any combination of 2 astronomical factors is better than that of prediction using a single astronomical factor, as will be demonstrated in the examples that follow. In order to further improve the prediction accuracy, in the embodiment, 3 combinations are obtained by pairwise combination of 3 astronomical factors, a super-rich water annual point aggregation area is obtained by drawing 3 composite factor point aggregation maps corresponding to the 3 combinations and dividing the super-rich water annual point aggregation area on the point aggregation maps, the super-rich water annual point aggregation areas Q1, Q2 and Q3 to which the year to be predicted belongs are obtained, and finally, the incoming water data of the year to be predicted is obtained by processing the incoming water data of the historical years with higher occurrence frequency in the Q1, Q2 and Q3. If the clustering effect of the super-Fengshui annual point is used for the first time, the process is equivalent to using the clustering effect for the second time, namely, clustering the data in Q1, Q2 and Q3 again. Therefore, the prediction accuracy can be obviously improved by adopting the method for predicting according to the embodiment compared with the prediction by adopting a single astronomical factor. Firstly, counting the historical years and the occurrence times in Q1, Q2 and Q3; then, based on the distribution rule of the occurrence times of the historical years, different data processing methods are given according to two conditions: if a certain historical year appears 3 times, namely Q1, Q2 and Q3 all comprise the historical year, and other historical years only appear 1 time, the annual water and the monthly water of the historical year are taken as the annual water and the monthly water of the year to be predicted; otherwise, respectively weighing and averaging annual water and monthly water of more than 2 times of historical years according to the occurrence times to obtain the annual water and monthly water of the year to be predicted. The calculation formula is as follows:
in the formula, m i Number of occurrences of ith historical year, m i =2 or 3,n is the number of historical years, P is the water of the year to be predicted or the water of the months of 1-12 months, P i Is the water of the year of the ith historical year or the water of the months from 1 month to 12 months.
As an alternative embodiment, the method for determining the annual water level of the calendar year in step S101 specifically includes:
calculating the average value P of water in all historical years 0 According to the year water P and P 0 Ratio of (P)/(P) 0 The size of (c) judges the grade of water in the year:
if P/P 0 <0.6, is extra dry water year;
if 0.6. Ltoreq. P/P 0 <0.8, the year of dry water;
if 0.8 is less than or equal to P/P 0 <0.9, in parawithered water years;
if 0.9. Ltoreq. P/P 0 <1.1, the year is open water;
if 1.1. Ltoreq.P/P 0 <1.2, the year is a water-rich year;
if 1.2. Ltoreq.P/P 0 <1.4, the year of full water;
if P/P 0 Not less than 1.4, which is a super-harvest water year.
This embodiment presents a specific method for judging the water grade of the year. According to the annual water P and the average value P of all the historical annual waters 0 The size of the ratio of (a) to (b) is used to judge the water level in the year. For example, 1.2 ≦ P/P 0 <1.4 hours is full water year, P/P 0 When the water content is more than or equal to 1.4, the water is a super-rich water year.
As an alternative embodiment, the method for marking the extra-high water annual-spot gathering area in step S103 includes:
1031, drawing a rectangle in the region where each extra-rich water year point is concentrated, wherein each rectangle at least comprises 1 extra-rich water year point and 1 rich water year point;
s1032, adjusting the boundary of each rectangle to enable the distance between any one extra-rich water year point outside each rectangle and a rich water year point and the nearest extra-rich water year point or a rich water year point in the rectangle to be larger than a first threshold value, and enabling the ratio k of the number of extra-rich water year points in each rectangle to the number of all level data points in the rectangle to be maximum;
s1033, calculating the ratio k of the total number of the super-Fengshui year points to the total number of the data points of all levels 0 Delete k/k 0 And the area surrounded by the rest rectangles is the marked extra-rich water year point gathering area.
The embodiment provides a technical scheme for marking a super-Fengshui annual point gathering area in a composite factor point gathering graph. Step S1031 determines that the super-Fengshui annual point gathering areas are rectangular in shape, each super-Fengshui annual point gathering area at least comprises 2 data points, and at least comprises 1 super-Fengshui annual point and 1 Fengshui annual point. Step S1032 can incorporate all the extra-rich water year points and the extra-rich water year points around the rectangle into the rectangle, so as to embody the clustering effect of the extra-rich water year points/the extra-rich water year points, and on this basis, the probability of occurrence of the extra-rich water year points inside the rectangle reaches the highest (i.e., k is the largest). The distance between two data points can be obtained by squaring and re-developing the distance in the X direction and the Y direction, and the distance in the X or Y direction can be represented by the number of data points separated in the X or Y direction. Step S1033 can ensure that the probability of occurrence of the extra-rich water year point in the rectangle is significantly higher than the average probability of occurrence of the extra-rich water year point (i.e., k) 0 ) That is, if this requirement is not satisfied, a super-rich water annual-spot gathering area cannot be drawn even if the above-mentioned several conditions are satisfied. The magnitudes of the first threshold and the second threshold are empirically determined.
An application example of the method is given below, and the annual water and the monthly water of a certain large reservoir 2010 in China are predicted by using historical water coming data of the large reservoir from 1933 to 2009 (77 years in total).
The average water value was calculated to be 410 cubic meters per second from 1933 to 2009. From this, an incoming water range of 7 incoming water levels can be obtained: extra-rich water years [574, + ∞), rich water years [492,574), partial-rich water years [451,492), flat water years [369,451 ], partial-dry water years [328,369 ], dry water years [246,328 ], extra-dry water years [0, 246), all in cubic meters per second.
Drawing a first composite factor dot-concentration chart, a second composite factor dot-concentration chart and a third composite factor dot-concentration chart according to the relative number of sun black seeds, the lunar declination angle and the date of the near-day point in each year from 1933 to 2009, wherein different symbols are used for representing different levels of incoming water data points; and the super-harvest water annual point gathering areas are marked in each figure, as shown in figures 4-6.
In order to illustrate that the accuracy of prediction by using the composite astronomical factors is better than that of prediction by using a single astronomical factor, a first single-factor point focusing graph with the relative number of Ether Yang Heizi as an X axis and the annual water as a Y axis, a second single-factor point focusing graph with the lunar declination angle as the X axis and the annual water as the Y axis, a third single-factor point focusing graph with the near-day date as the X axis and the annual water as the Y axis are drawn, and each graph is subjected to region division, namely, the water area of each level is divided, and the regions are respectively shown in FIGS. 1 to 3. The dividing method is similar to the method for dividing the super-rich water year point aggregation area, the probability of 7-level data points of a certain area (between two vertical lines) in the graph is subjected to statistical analysis, the ratio of the probability of each level to the average occurrence probability (the total number of data points of a certain level to the total number of data points of all levels) is calculated, and the division is named according to the incoming water level with the highest ratio, for example, the ratio of the data points of the super-rich water year in the leftmost area in the graph 1 is the super-rich water year area. The position of the boundary of the two vertical lines is adjusted to enable the probability of the highest ratio of the incoming water level to be highest in the region.
The relative number of sunblack seeds in 2010 of the year to be predicted is 15.1, the lunar declination angle (annual maximum value) is 25.36 degrees, and the date of the near-day lunar calendar is 12 months and 3 days, which are acquired from organizations such as a national astronomical table and a Chinese academy space environment prediction center.
The relative number of sunblack seeds in 2010 was 15.1. The data point is located in texas water year zone one according to the first single factor point gather plot of fig. 1. The relative number of the black seeds of one sun in the super-Fengshui area is 4.4-21. In 18 years in the region, there are 6 super-rich water years, 1 super-rich water year, 3 slightly-rich water years, 5 horizontal water years and 3 dry water years, and the probability of the super-rich water year appearing in the region is 33.3 percent and is 3.1 times of the average occurrence probability of the super-rich water year, which is 10.6 percent. Therefore, with the first single-factor pointgraphy prediction, 33.3% of the probability in 2010 is in tefeng water years, which is 3.1 times the average probability of occurrence.
The lunar declination angle in 2010 was 25.36 degrees. The data points are located in the tefeng water year zone two according to the second single factor point gather plot of fig. 2. The range of the February ball declination angle in the Tefeng water year area is 25.00-26.29 degrees. In 10 years in the area, 2 super-rich water years, 3 super-rich water years, 1-year slightly-rich water years, 2-year flat water years, 1-year dry water years and 1-year super-dry water years exist, and the probability of the super-rich water years in the area is 20% and is 1.9 times of the average probability of the super-rich water years, wherein the average probability of the super-rich water years is 10.6%. Therefore, with the second single-factor pointgraphy prediction, the 20% probability in 2010 was tefeng water years, which was 1.9 times the average probability of occurrence.
The date of the near-date point in 2010 is 12 months and 3 days. The data points are located in the tefeng water year zone two according to the third single factor point gather plot of fig. 3. The second-nearest-day point date in the super-Fengshui region ranges from 12 months 2 days to 12 months 7 days of the lunar calendar. The area has 6 super-rich water years, 4 super-rich water years, 2 super-rich water years, 3 normal water years, 1 semi-dry water years and 1 semi-dry water years in 19 years, and the probability of the super-rich water years in the area is 31.6 percent and is 3.0 times of the average probability of the super-rich water years, wherein the average probability of the super-rich water years in the area is 10.6 percent. Therefore, with the third single-factor pointgraphy prediction, 31.6% of the probability in 2010 is in tefeng water years, which is 3.0 times the average probability of occurrence.
In the first composite factor dot plot of fig. 4, a point corresponding to a relative number of solar black seeds of 15.1 (abscissa) and lunar declination angle of 25.36 (ordinate) in 2010 is plotted and found to fall in the first super-harvest water year gathering area. The relative number range of the sun and the black son in the first extra-harvest water year gathering area is 4.4-15.1, and the range of the lunar declination angle is 24.28-28.19 degrees. In 8 years of the region, 5 super-full water years, 1 super-full water years and 2 open water years, the probability of occurrence of the super-full water years in the region is 62.5% (namely k = 0.625), and the average probability of occurrence of the super-full water years is 10.6% (namely k = 0.625) 0 = 0.106) of the same factor. Therefore, when the first composite factor dot-blot analysis is used for prediction, the probability of 62.5% in 2010 is the super-rich water year, which is 5.9 times of the average occurrence probability of the super-rich water year.
In the second multifactor pointry plot of FIG. 5, the 2010 year is plottedAnd a point corresponding to the 12-month-3-day near-day date (abscissa) and the lunar declination angle 25.36 (ordinate), which is found to fall in the first extra-high water year gathering area. The near-day point range of the first super-harvest water year gathering area is 12 months and 2 days to 12 months and 3 days, and the lunar declination angle range is 24.28 to 27.36 degrees. The super-full water year in the region is 3 years, 2 years and 1 year, the probability of the super-full water year in the region is 50% (namely k = 0.5), and the average probability of the super-full water year is 10.6% (namely k = 0.5) 0 = 0.106). Therefore, when the second composite factor dot-blot analysis is used for prediction, the probability of 50% in 2010 is the super-harvest year, which is 4.7 times of the average occurrence probability of the super-harvest year.
In the third composite factor dot-plot of fig. 6, a dot corresponding to the date of the near-dated date of 2010, 12 months and 3 days (abscissa) and the relative number of sun-black seeds of 15.1 (ordinate) was plotted and found to fall in the super-harvest water year accumulation area five. The near-day point range of the ultra-Fengsheng aquatic year gathering area five is 12 months and 2 days to 12 months and 3 days, and the relative number range of the sun and the black seeds is 4.4 to 15.6. The super-rich water year of 5 years, the super-rich water year of 1 year and the partial rich water year of 1 year in 7 years in the region has the probability of 71.4 percent (namely k = 0.714) and is 10.6 percent of the average occurrence probability of the super-rich water year (namely k = 0.714) 0 = 0.106). Therefore, when the third composite factor dot-blot analysis chart is used for prediction, the probability of 71.4% in 2010 is the super-rich water year, and is 6.7 times of the average occurrence probability of the super-rich water year.
In conclusion, the prediction by adopting any two astronomical factors in the 3 astronomical factors is obviously superior to the prediction by adopting a single astronomical factor. The results of the prediction of 2010 using the composite astronomical factor are given further below.
The historical years of the tertiary pelagic years contained in the tertiary pelagic year accumulation area I of the first composite factor clickthrough are 1933, 1934, 1953, 1954, 1964, 1965 and 1986, the historical years of the tertiary pelagic years contained in the tertiary pelagic year accumulation area I of the second composite factor clickthrough are 1934, 1953, 1964, 1972 and 1991, and the historical years of the tertiary pelagic years contained in the tertiary pelagic year accumulation area V of the third composite factor clickthrough are 1934, 1953, 1954, 1964, 1975 and 1986. Wherein, the 3 occurrences in 1953, 1964 and 1934, the 2 occurrences in 1954 and 1986, and the other 1 occurrences are regarded as accidental event processing due to low occurrence probability, i.e. not used for prediction calculation. The year water and the month water in 1934, 1953, 1954, 1964 and 1986 are weighted and averaged to obtain the year water and the month water in 2010, respectively. The predicted results are shown in Table 1, where the units of water in Table 1 are all in cubic meters per second.
Table 1 prediction calculation table of water data in 2010
| 1934 | 1953 | 1954 | 1964 | In 1986 | Prediction value | Actual value | |
| 1 month of water | 51 | 26 | 48 | 55 | 148 | 61 | 160 |
| 2 months of running water | 44 | 25 | 38 | 39 | 130 | 51 | 36 |
| 3 months of running water | 107 | 90 | 269 | 91 | 295 | 153 | 25 |
| 4 months of running water | 382 | 354 | 628 | 1405 | 652 | 691 | 933 |
| 5 months of running water | 371 | 784 | 606 | 391 | 595 | 542 | 1138 |
| 6 months old water | 690 | 1469 | 1350 | 551 | 666 | 936 | 462 |
| Water coming after 7 months | 2500 | 1971 | 1096 | 939 | 1632 | 1668 | 1795 |
| 8 |
800 | 2662 | 2548 | 3214 | 2007 | 2241 | 2822 |
| 9 month coming water | 461 | 271 | 1548 | 732 | 1342 | 782 | 805 |
| 10 months of running water | 174 | 141 | 395 | 178 | 284 | 218 | 540 |
| 11 month water | 208 | 65 | 175 | 119 | 237 | 154 | 254 |
| 12 months of running water | 89 | 44 | 53 | 44 | 163 | 74 | 112 |
| Year water | 494 | 665 | 733 | 649 | 683 | 635 | 764 |
| Grade of water supply | Fengshui year | Super rich waterYear of year | Super-rich water year | Super-rich water year | Super-rich water year | Super-rich water year | Super-rich water year |
| Number of occurrences | 3 | 3 | 2 | 3 | 2 |
Practice shows that in 2010, the reservoir basin meets extra-large flood for more than one hundred years, the annual average warehousing flow rate of the reservoir is 764 cubic meters per second, which is 186 percent of the annual average value, and the reservoir basin is the first in the historical super-rich water year. The annual average storage flow of the reservoir is predicted to be 635 cubic meters per second, which is 155 percent of the annual average value of the reservoir and is the eighth special high water year in history. The qualitative and quantitative predictions are correct. The maximum month of water in the year is 8 months (the month of flood occurrence), the average predicted month is 2241 cubic meters per second, the average 8 months is 252% of 891 cubic meters per second, the average actual month is 2822 cubic meters per second, the average 8 months is 317% of 891 cubic meters per second, the month of flood occurrence is accurately predicted, and the magnitude is also correct.
The above description is only for the purpose of illustrating a few embodiments of the present invention, and should not be taken as limiting the scope of the present invention, in which all equivalent changes, modifications, or equivalent scaling-up or down, etc. made in accordance with the spirit of the present invention should be considered as falling within the scope of the present invention.
Claims (3)
1. The super-long-term prediction method for the super-rich water year of the water coming from the reservoir is characterized by comprising the following steps of:
step 1, acquiring the annual water, the relative number of sunblack seeds, the lunar declination angle and the date of the near-day point of the past year of the reservoir, and determining the annual water level of the past year, wherein the annual water level comprises: extra-rich water years, partial-rich water years, open water years, partial-dry water years, extra-dry water years;
step 2, taking the relative number of the ether Yang Heizi as an X axis, taking the lunar declination angle as a Y axis, representing the annual water level of the data points by different symbols, and drawing a first composite factor point concentration graph; taking the date of the near-day point as an X axis, taking the declination angle of the moon as a Y axis, representing the annual water level of the data point by different symbols, and drawing a second composite factor point convergence graph; taking the date of the near-day point as an X axis, taking the relative number of the Ethernet Yang Heizi as a Y axis, representing the annual water level of the data point by different symbols, and drawing a third composite factor point focusing graph;
step 3, marking super-Fengshui annual point gathering areas in the first composite factor point gathering graph, the second composite factor point gathering graph and the third composite factor point gathering graph respectively;
step 4, obtaining the relative number a of sunblack, the lunar declination angle b and the near-day date c of the year to be predicted, and finding the super-Fengshui annual point gathering areas Q1, Q2 and Q3 to which the points (a, b), (c, b) and (c, a) belong in the first complex factor point gathering graph, the second complex factor point gathering graph and the third complex factor point gathering graph respectively;
step 5, respectively counting the historical years and the occurrence times corresponding to the data points in the Q1, the Q2 and the Q3, and if a certain historical year appears 3 times and other historical years all appear 1 time, taking the annual water and the monthly water of the historical year as the annual water and the monthly water of the year to be predicted; otherwise, respectively weighing and averaging annual water and monthly water of more than 2 times of historical years according to the occurrence times to obtain the annual water and monthly water of the year to be predicted.
2. The method for predicting the ultra-long term of the super-rich water years of the water coming from the reservoir according to claim 1, wherein the method for determining the water level of the years in the step 1 specifically comprises the following steps:
calculating the average value P of water in all historical years 0 According to the year water P and P 0 Ratio of (P)/(P) 0 Judging the grade of water in the year:
if P/P 0 <0.6, is extra dry water year;
if 0.6. Ltoreq. P/P 0 <0.8, the year of dry water;
if 0.8 is less than or equal to P/P 0 <0.9, being a partial withered water year;
if 0.9. Ltoreq. P/P 0 <1.1, the year is open water;
if 1.1. Ltoreq.P/P 0 <1.2, the year is a water-rich year;
if 1.2. Ltoreq.P/P 0 <1.4, the year of full water;
if P/P 0 Not less than 1.4, which is a super-harvest water year.
3. The method for predicting the ultra-long term of the super-rich water years of the incoming water of the reservoir according to claim 1, wherein the step 3 of marking out the super-rich water year point gathering areas comprises the following steps:
step 3.1, drawing a rectangle in the region where each extra-rich water year point is concentrated, wherein each rectangle at least comprises 1 extra-rich water year point and 1 rich water year point;
step 3.2, adjusting the boundary of each rectangle to enable the distance between any one extra-rich water year point outside each rectangle and a water-rich year point and the nearest extra-rich water year point or water-rich year point in the rectangle to be larger than a first threshold value, and enabling the ratio k of the number of extra-rich water year points in each rectangle to the number of all level data points in the rectangle to be maximum;
step 3.3, calculating the ratio k of the total number of the super-Fengshui annual points to the total number of the data points of all levels 0 Delete k/k 0 And the area surrounded by the rest rectangles is the marked extra-rich water year point gathering area.
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