CN110852526A - Real-time flood forecasting method based on rainfall flood process similarity judgment - Google Patents
Real-time flood forecasting method based on rainfall flood process similarity judgment Download PDFInfo
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Abstract
The invention relates to a real-time flood forecasting method based on rainfall flood process similarity judgment, which comprises the steps of collecting historical rainfall flood data information, calculating the early soil saturation of each historical flood and constructing a historical flood reservoir; calculating the early soil saturation of the current flood process to be forecasted, and calculating to obtain an early soil saturation similarity factor by combining the early soil saturation of the historical flood; calculating to obtain a runoff process similarity factor based on the real-time runoff data of the region and in combination with the runoff data of the historical flood; calculating to obtain a rainfall process similarity factor based on the real-time rainfall data of the area and combining the rainfall data of the historical flood; based on the three similarity factors, calculating and selecting the historical flood process with the highest similarity factor in the rain flood process to be matched with the current flood process, so as to realize flood forecasting. The flood forecasting method provided by the invention has the advantages of stable and reliable data source, objective and reasonable forecasting result and suitability for large-scale popularization.
Description
Technical Field
The invention relates to the technical field of pipeline hydrological prediction, in particular to a real-time flood forecasting method based on rainfall flood process similarity judgment.
Background
China has numerous rivers and nearly nine thousand small and medium watersheds with the watershed area of 200-3000 square kilometers. In recent years, due to the influence of climate change, sudden floods of medium and small rivers caused by local strong rainfall frequently occur and become main disaster species causing casualties, and the sudden floods of medium and small watersheds are extremely easy to form flood disasters damaging the personal safety and social economy of local residents because the medium and small watersheds are usually located in remote mountain areas with complex terrain and steep gradient, so that the accurate and reliable early warning and forecasting of the sudden floods of the medium and small watersheds becomes an important problem to be solved urgently.
The rainfall flood process (hereinafter referred to as historical rainfall flood process) which has already occurred is an important basis for hydrologic prediction. The current common flood forecasting method is mainly to construct a hydrological model, determine parameters of the model based on historical rainfall flood process data rate and then apply the model to real-time hydrological forecasting. However, since the construction and application of the hydrological model need strong professional foundation, how to explore and analyze the rainfall runoff law of the drainage basin based on historical rainfall flood process data, so that the method for rapidly, simply and conveniently forecasting the possible flood danger is also one of the important difficulties in the process of hydrological forecasting moving to real-time and generalization. In order to further promote the development of the rapid flood forecasting technology, it is necessary to understand the rainfall runoff law in the historical rainfall flood process more deeply and study the rapid flood forecasting technology based on the historical rainfall flood process.
The early soil water content saturation is the ratio of the soil water content to the water holding capacity in the flow area before flood occurs. Generally, the larger the early soil saturation, the larger the rainfall, the larger the runoff already generated by the watershed outlet, and the larger the flood that may occur in the future. When the historical rainfall flood process data is used for flood forecasting, if the influence of the factors on the future flood process is ignored, the flood forecasting is inaccurate.
Aiming at the defects, how to intelligently and automatically extract early-stage soil saturation, rainfall characteristics and occurred runoff process characteristics based on historical rainfall flood process data, judge the similarity between floods which may occur in the future and floods which have occurred in the history according to the three factors, and optimally select the most likely similar flood process from the historical floods which have occurred, so that the flood process is quickly and reliably forecasted, and a real-time flood forecasting method based on rainfall flood process similarity judgment is constructed, which is the technical problem to be solved at present.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a real-time flood forecasting method based on the rainfall flood process similarity judgment, which has the advantages of stable and reliable data source, high calculation efficiency, objective and reasonable forecasting result, is favorable for realizing the rapid calculation of intelligent real-time accurate flood forecasting and is suitable for large-scale popularization.
In order to achieve the purpose, the invention adopts the following technical scheme.
An intelligent real-time flood forecasting method based on rainfall flood process similarity judgment comprises the following steps:
step S1: collecting historical rainfall flood data, calculating early soil saturation of each historical flood, and constructing a historical flood reservoir;
step S2: calculating the early soil saturation of the current flood process to be forecasted, and calculating to obtain an early soil saturation similarity factor by combining the early soil saturation of the historical flood;
step S3: calculating to obtain a runoff process similarity factor based on the real-time runoff data of the region and in combination with the runoff data of the historical flood;
step S4: calculating to obtain a rainfall process similarity factor based on the real-time rainfall data of the area and combining the rainfall data of the historical flood;
step S5: and calculating to obtain a rainfall flood process similarity factor based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor, and selecting the historical flood process with the highest rainfall flood process similarity factor to match with the current flood process, so as to realize flood forecasting.
As a further improvement of the present invention, the step S1 of collecting historical rainfall flood data, calculating the early soil saturation of each historical flood and constructing a historical flood reservoir specifically includes the following steps:
step S101: the method comprises the steps of firstly sorting to obtain period-by-period historical rainfall and flood data, coding the historical rainfall and flood data into i, taking rainfall data 30 days before the flood rising time as input, and calculating to obtain the soil water content saturation S at the historical flood rising time by utilizing a three-layer evapotranspiration principlei；
Step S102: by using the historical flood rise time t of each time0To the historical flood fading time t2Obtaining time-interval historical rainfall data sequence P by the rainfall data in the intervali；
Step S103: by using the historical flood rise time t of each time0Until the flood subsides time t2Obtaining the time-interval historical runoff data sequence Q by the runoff data betweeni；
Step S104: generalizing historical rain flood process into structure [ S ]i,Pi,Qi]And traversing each historical rainfall flood process to construct a historical flood reservoir taking the data element as a basic unit, wherein the number of the data elements is the number N of the historical flood field.
As a further improvement of the present invention, the step S2 of calculating the early soil saturation of the flood process to be forecasted currently, and calculating an early soil saturation similarity factor by combining the early soil saturation of the historical flood, specifically includes the following steps:
step S201: collecting and obtaining real-time rainfall data by time intervals, taking rainfall data 30 days before the current flood rising time as input, and calculating and obtaining the soil water content saturation S at the current flood rising time by utilizing a three-layer evapotranspiration principle0；
Step S202: and calculating to obtain an early soil saturation similarity factor gamma by combining the early soil saturation of the historical floodS,iSpecifically, the formula is as follows:
in the formula: gamma rayS,iIs the soil at the earlier stage between the flood process and the historical flood process with the serial number of iA saturation similarity factor; s0Saturation S of soil water content at current flood rising timeiThe saturation of the water content of the soil at the time of the rise of the historical flood.
As a further improvement of the present invention, the step S3 of calculating the runoff process similarity factor based on the real-time runoff data and in combination with the runoff data of the historical flood includes the following steps:
step 301: arranging to obtain the rising time t from the current flood0Until the forecast time t1Real-time runoff data sequence Q0；
Step 302: combining real-time runoff data sequence Q0And historical runoff data sequence QiCalculating to obtain a runoff process similarity factor gammaQ,iSpecifically, the formula is as follows:
in the formula: gamma rayQ,iA runoff process similarity factor between the current runoff process and the historical runoff process numbered i is obtained; t = T1-t0；Q0,jIs Q0J-th value in the sequence, Qi,jIs QiThe jth value in the sequence, j, is from 0 to T.
As a further improvement of the present invention, the calculating of the rainfall process similarity factor based on the real-time runoff data in step S4 and in combination with the rainfall data of the historical flood includes the following steps:
step S401: arranging to obtain the current rising time t from the flood0To the forecast time t1Real-time rainfall data sequence P in between0；
Step S402: incorporating a real-time rainfall data sequence P0And a historical rainfall data sequence PiCalculating to obtain a rainfall process similarity factor gammaP,iSpecifically, the formula is as follows:
in the formula: gamma rayP,iIs a rainfall process similarity factor between the current rainfall process and the historical rainfall process numbered as i; t = T1-t0；P0,jIs P0Value j in the sequence, Pi,jIs PiThe jth value in the sequence, j, is from 0 to T.
As a further improvement of the present invention, in the step S5, the rainfall process similarity factor is calculated based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor, and the historical flood process with the highest rainfall process similarity factor is selected to match the current flood process, so as to realize flood forecasting, specifically including the following steps:
step S501: similarity factor gamma based on early soil saturationS,iSimilar factor gamma in runoff processQ,iFactor gamma similar to rainfall processP,iAnd calculating to obtain a rain flood process similarity factor gammaiSpecifically, the formula is as follows:
in the formula: gamma rayiα is the rain flood process similarity factor of the current rain flood process and the historical rain flood process numbered is、αqAnd αpThe weight coefficient of the soil saturation similarity factor, the weight coefficient of the runoff process similarity factor and the weight coefficient of the rainfall process similarity factor are respectively required to meet the constraint condition αs+αq+αp=1；αs、αqAnd αpSelecting specific values of the drainage basin according to actual natural geographic conditions of the drainage basin to be forecasted;
step S502: select the largest gammaiMarking the serial number i as best and Q in the runoff process of the corresponding historical flood fieldbestExtracting the forecast time t in the series1And the flood fading time t2The runoff process in between is used as a forecasting result of the flood process.
Due to the application of the technical scheme, the technical scheme of the invention has the following beneficial effects: the real-time flood forecasting method based on the rainfall flood process similarity judgment, provided by the invention, is based on physical factors influencing the future flood process and historical flood parameters, quantifies the influence of the related early soil saturation, rainfall process and occurred runoff process on the future runoff process, finds the historical flood process most similar to the flood which possibly occurs in the future, realizes the fast, simple and convenient flood forecasting of the flood which possibly occurs in the future, is practical, more efficient and more accurate, and further provides the real-time flood forecasting method based on the rainfall flood process similarity judgment; the technical scheme not only ensures the precision and reliability of the calculation result, but also has stable and reliable data source, clear function relation among variables in the method, is beneficial to rapid and automatic quantification of early-stage soil saturation, rainfall characteristics and occurred runoff characteristics, ensures objective rationality of the result, is beneficial to direct calling of a real-time flood forecasting method based on similarity judgment of a rainfall flood process, can further promote deep development of digital hydrology and rapid flood forecasting, and provides important basis for future quantitative hydrological forecasting.
Drawings
FIG. 1 is a schematic view of the overall flow of the forecasting method of the present invention.
Fig. 2 is a schematic diagram of a ferry valley DEM according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of the soil saturation at the early stage of the historical flood according to the embodiment of the invention.
FIG. 4 is a schematic diagram of the early soil saturation similarity factor according to the embodiment of the present invention.
FIG. 5 is a schematic diagram of a runoff process similarity factor according to an embodiment of the present invention.
FIG. 6 is a diagram illustrating the similar factors in the rainfall process according to the embodiment of the present invention.
Fig. 7 is a schematic diagram of similar factors in a rain flood process according to an embodiment of the present invention.
Fig. 8 is a diagram illustrating flood process forecast results according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples.
As shown in fig. 1 to 8, a real-time flood forecasting method based on the rainfall flood process similarity determination includes the following steps:
step S1: collecting historical rainfall flood data, calculating early soil saturation of each historical flood, and constructing a historical flood reservoir; step S101: the method comprises the steps of firstly sorting to obtain period-by-period historical rainfall and flood data, coding the historical rainfall and flood data into i, taking rainfall data 30 days before the flood rising time as input, and calculating to obtain the soil water content saturation S at the historical flood rising time by utilizing a three-layer evapotranspiration principlei(ii) a Step S102: by using the historical flood rise time t of each time0To the historical flood fading time t2Obtaining time-interval historical rainfall data sequence P by the rainfall data in the intervali(ii) a Step S103: by using the historical flood rise time t of each time0Until the flood subsides time t2Obtaining the time-interval historical runoff data sequence Q by the runoff data betweeni(ii) a Step S104: generalizing historical rain flood process into structure [ S ]i,Pi,Qi]And traversing each historical rainfall flood process to construct a historical flood reservoir taking the data element as a basic unit, wherein the number of the data elements is the number N of the historical flood field.
Step S2: calculating the early soil saturation of the current flood process to be forecasted, and calculating to obtain an early soil saturation similarity factor by combining the early soil saturation of the historical flood, specifically comprising the following steps of S201: collecting and obtaining real-time rainfall data by time intervals, taking rainfall data 30 days before the current flood rising time as input, and calculating and obtaining the soil water content saturation S at the current flood rising time by utilizing a three-layer evapotranspiration principle0(ii) a Step S202: and calculating to obtain an early soil saturation similarity factor gamma by combining the early soil saturation of the historical floodS,iSpecifically, the formula is as follows:
in the formula: gamma rayS,iThe early-stage soil saturation similarity factor between the current flood process and the historical flood process numbered i is obtained; s0Saturation S of soil water content at current flood rising timeiThe saturation of the water content of the soil at the time of the rise of the historical flood.
Step S3: based on the real-time runoff data of the area and in combination with the runoff data of the historical flood, calculating to obtain a runoff process similarity factor, specifically comprising the following steps of 301: arranging to obtain the rising time t from the current flood0Until the forecast time t1Real-time runoff data sequence Q0(ii) a Step 302: combining real-time runoff data sequence Q0And historical runoff data sequence QiCalculating to obtain a runoff process similarity factor gammaQ,iSpecifically, the formula is as follows:
in the formula: gamma rayQ,iA runoff process similarity factor between the current runoff process and the historical runoff process numbered i is obtained; t = T1-t0；Q0,jIs Q0J-th value in the sequence, Qi,jIs QiThe jth value in the sequence, j, is from 0 to T.
Step S4: based on the real-time rainfall data of the area and in combination with the rainfall data of the historical flood, calculating to obtain a rainfall process similarity factor, specifically comprising the following steps of S401: arranging to obtain the current rising time t from the flood0To the forecast time t1Real-time rainfall data sequence P in between0(ii) a Step S402: incorporating a real-time rainfall data sequence P0And a historical rainfall data sequence PiCalculating to obtain a rainfall process similarity factor gammaP,iSpecifically, the formula is as follows:
in the formula: gamma rayP,iBetween the current rainfall process and the historical rainfall process with the number of iSimilar factors of the rainfall process; t = T1-t0；P0,jIs P0Value j in the sequence, Pi,jIs PiThe jth value in the sequence, j, is from 0 to T.
Step S5: based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor, calculating to obtain a rainfall flood process similarity factor, selecting the historical flood process with the highest rainfall flood process similarity factor to match with the current flood process, and realizing flood forecasting, wherein the method specifically comprises the following steps of S501: similarity factor gamma based on early soil saturationS,iSimilar factor gamma in runoff processQ,iFactor gamma similar to rainfall processP,iAnd calculating to obtain a rain flood process similarity factor gammaiSpecifically, the formula is as follows:
in the formula: gamma rayiα is the rain flood process similarity factor of the current rain flood process and the historical rain flood process numbered is、αqAnd αpThe weight coefficient of the soil saturation similarity factor, the weight coefficient of the runoff process similarity factor and the weight coefficient of the rainfall process similarity factor are respectively required to meet the constraint condition αs+αq+αp=1；αs、αqAnd αpSelecting specific values of the drainage basin according to actual natural geographic conditions of the drainage basin to be forecasted;
step S502: select the largest gammaiMarking the serial number i as best and Q in the runoff process of the corresponding historical flood fieldbestExtracting the forecast time t in the series1And the flood fading time t2The runoff process in between is used as a forecasting result of the flood process.
The specific embodiment of the ferry basin is as follows:
taking Shanxi province Madu King river basin as an example, the area of the river basin is 1601 km2Located in the west of Shaanxi province, belonging to warm-temperate zone semi-humid continental monsoon climate with clear cold and warm dry and wet in four seasons. The rainstorm center is mostly concentrated inMid-upstream of the watershed. The raw data of the DEM in the research area adopts 90m resolution SRTM (ShuttleRaar Topographic Session) data provided by the United states of America space administration (NASA) and the national institute of defense mapping (NIMA) (see figure 2). Historical rainfall, runoff data adopts the Shaanxi province water and cultural relics resource survey bureau from 2010 to 2017 to provide hourly observation data.
The method comprises the following steps of firstly, calculating early-stage soil saturation of a flood process to be forecasted, and calculating early-stage soil saturation similarity factors by combining the early-stage soil saturation of historical flood, wherein the method specifically comprises the following steps:
1) arranging to obtain real-time rainfall data by time period, taking rainfall data 30 days before 17 o' clock of 28 th year 2017 as input00.6;
2) providing rainfall runoff observation data observed hour by hour based on Shaanxi province water and cultural relic resource survey bureau between 2010 and 2017, dividing to obtain 27 historical flood processes, calculating the early-stage soil saturation of each historical flood according to the method in 1) (see fig. 3), and further combining with the calculation to obtain the early-stage soil saturation similarity factor (see fig. 4).
In the formula: gamma rayS,iAnd the early-stage soil saturation similarity factor between the current flood process and the historical flood process numbered i is obtained.
Step two, calculating to obtain a runoff process similarity factor based on the real-time runoff data and in combination with the runoff data of the historical flood, and specifically comprising the following steps:
1) arranging to obtain the time t of rising from flood0(17 o' clock 6/28/2017) to forecast time t1Real-time runoff data sequence Q between 6 and 29 days of 20170；
2) Real-time runoff data sequence Q0And historical runoff data sequence QiCalculating to obtain runoff process similarity factor (see figure 5)；
In the formula: gamma rayQ,iA runoff process similarity factor between the current runoff process and the historical runoff process numbered i is obtained; t = T1-t0；Q0,jIs Q0J-th value in the sequence, Qi,jIs QiThe jth value in the sequence, j, is from 0 to T.
Step three, calculating to obtain a rainfall process similarity factor based on the real-time runoff data and combined with rainfall data of historical flood, and specifically comprising the following steps:
1) arranging to obtain a real-time rainfall data sequence from the flood rising time (17 points at 28 months and 6 months in 2017) to the forecast time (21 points at 29 months and 6 months in 2017);
2) combining and calculating to obtain a rainfall process similarity factor (see figure 6);
in the formula: in the formula: gamma rayP,iIs a rainfall process similarity factor between the current rainfall process and the historical rainfall process numbered as i; t = T1-t0；P0,jIs P0Value j in the sequence, Pi,jIs PiThe jth value in the sequence, j, is from 0 to T.
Step four, calculating to obtain a rainfall flood process similarity factor based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor, selecting the historical flood process with the highest rainfall flood process similarity factor to match with the current flood process, and realizing flood forecasting, wherein the method specifically comprises the following steps:
1) calculating to obtain a rainfall flood process similarity factor based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor (see fig. 7);
in the formula: gamma rayiα is the rain flood process similarity factor of the current rain flood process and the historical rain flood process numbered is、αqAnd αpThe weight coefficient of the soil saturation similarity factor, the weight coefficient of the runoff process similarity factor and the weight coefficient of the rainfall process similarity factor are respectively required to meet the constraint condition αs+αq+αp=1；αs、αqAnd αp=The selected values are 0.3, 0.3 and 0.4 respectively.
2) Selecting the runoff process of the corresponding historical flood field, marking the sequence number i as best, calculating the corresponding sequence number i as 18, and extracting the forecasting time t in the series1(21 o 29/6/2017) and flood withdrawal time t2The runoff process between (23 o' clock at 6/30/2017) serves as the forecast result of the flood process (see fig. 8).
The above is only a specific application example of the present invention, and the protection scope of the present invention is not limited in any way. All the technical solutions formed by equivalent transformation or equivalent replacement fall within the protection scope of the present invention.
Claims (6)
1. A real-time flood forecasting method based on rainfall flood process similarity judgment is characterized by comprising the following steps:
step S1: collecting historical rainfall flood data, calculating early soil saturation of each historical flood, and constructing a historical flood reservoir;
step S2: calculating the early soil saturation of the current flood process to be forecasted, and calculating to obtain an early soil saturation similarity factor by combining the early soil saturation of the historical flood;
step S3: calculating to obtain a runoff process similarity factor based on the real-time runoff data of the region and in combination with the runoff data of the historical flood;
step S4: calculating to obtain a rainfall process similarity factor based on the real-time rainfall data of the area and combining the rainfall data of the historical flood;
step S5: and calculating to obtain a rainfall flood process similarity factor based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor, and selecting the historical flood process with the highest rainfall flood process similarity factor to match with the current flood process, so as to realize flood forecasting.
2. The method according to claim 1, wherein the step S1 of collecting historical rainfall flood data, calculating early soil saturation of each historical flood and constructing a historical flood reservoir is implemented by the steps of:
step S101: the method comprises the steps of firstly sorting to obtain period-by-period historical rainfall and flood data, coding the historical rainfall and flood data into i, taking rainfall data 30 days before the flood rising time as input, and calculating to obtain the soil water content saturation S at the historical flood rising time by utilizing a three-layer evapotranspiration principlei；
Step S102: by using the historical flood rise time t of each time0To the historical flood fading time t2Obtaining time-interval historical rainfall data sequence P by the rainfall data in the intervali；
Step S103: by using the historical flood rise time t of each time0Until the flood subsides time t2Obtaining the time-interval historical runoff data sequence Q by the runoff data betweeni；
Step S104: generalizing historical rain flood process into structure [ S ]i,Pi,Qi]And traversing each historical rainfall flood process to construct a historical flood reservoir taking the data element as a basic unit, wherein the number of the data elements is the number N of the historical flood field.
3. The method according to claim 1, wherein the step S2 of calculating the early soil saturation of the flood process to be forecasted currently and calculating an early soil saturation similarity factor in combination with the early soil saturation of the historical flood includes the following steps:
step S201: collecting and obtaining real-time rainfall data by time intervals, taking rainfall data 30 days before the current flood rising time as input, and calculating and obtaining the soil water content saturation S at the current flood rising time by utilizing a three-layer evapotranspiration principle0；
Step S202: and calculating to obtain an early soil saturation similarity factor gamma by combining the early soil saturation of the historical floodS,iSpecifically, the formula is as follows:
in the formula: gamma rayS,iThe early-stage soil saturation similarity factor between the current flood process and the historical flood process numbered i is obtained; s0Saturation S of soil water content at current flood rising timeiThe saturation of the water content of the soil at the time of the rise of the historical flood.
4. The method according to claim 1, wherein the step S3 of calculating a runoff process similarity factor based on the real-time runoff data and the runoff data of the historical flood includes the following steps:
step 301: arranging to obtain the rising time t from the current flood0Until the forecast time t1Real-time runoff data sequence Q0；
Step 302: combining real-time runoff data sequence Q0And historical runoff data sequence QiCalculating to obtain a runoff process similarity factor gammaQ,iSpecifically, the formula is as follows:
in the formula: gamma rayQ,iFor the runoff passing between the runoff process and the historical runoff process with the serial number of iA path similarity factor; t = T1-t0；Q0,jIs Q0J-th value in the sequence, Qi,jIs QiThe jth value in the sequence, j, is from 0 to T.
5. The method according to claim 1, wherein the calculating of the rainfall process similarity factor based on the real-time runoff data and the rainfall data of the historical flood in step S4 includes the following steps:
step S401: arranging to obtain the current rising time t from the flood0To the forecast time t1Real-time rainfall data sequence P in between0；
Step S402: incorporating a real-time rainfall data sequence P0And a historical rainfall data sequence PiCalculating to obtain a rainfall process similarity factor gammaP,iSpecifically, the formula is as follows:
in the formula: gamma rayP,iIs a rainfall process similarity factor between the current rainfall process and the historical rainfall process numbered as i; t = T1-t0；P0,jIs P0Value j in the sequence, Pi,jIs PiThe jth value in the sequence, j, is from 0 to T.
6. The method according to claim 1, wherein the step S5 of calculating the rainfall flood process similarity factor based on the early-stage soil saturation similarity factor, the runoff process similarity factor and the rainfall process similarity factor to obtain the rainfall flood process similarity factor, and selecting the historical flood process with the highest rainfall flood process similarity factor to match the current flood process to realize the flood forecasting, specifically comprising the steps of:
step S501: similarity factor gamma based on early soil saturationS,iSimilar factor gamma in runoff processQ,iFactor gamma similar to rainfall processP,iAnd calculating to obtain a rain flood process similarity factor gammaiSpecifically, the formula is as follows:
in the formula: gamma rayiα is the rain flood process similarity factor of the current rain flood process and the historical rain flood process numbered is、αqAnd αpThe weight coefficient of the soil saturation similarity factor, the weight coefficient of the runoff process similarity factor and the weight coefficient of the rainfall process similarity factor are respectively required to meet the constraint condition αs+αq+αp=1，αs、αqAnd αpSelecting specific values of the drainage basin according to actual natural geographic conditions of the drainage basin to be forecasted;
step S502: select the largest gammaiMarking the serial number i as best and Q in the runoff process of the corresponding historical flood fieldbestAnd extracting the runoff process between the forecasting time and the flood fading time in the series as a forecasting result of the flood process.
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