CN116070955A - Regional possible maximum rainfall determining method for mountain flood ditch drainage basin - Google Patents
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Abstract
The invention discloses a method for determining the regional possible maximum rainfall for mountain and flood ditches, which comprises the following steps: step 1, collecting hydrological data and scene rainfall flood data of a research area; step 2, determining the spatial distribution of maximum rainfall in different duration of the scene rainfall; step 3, determining a storm similar area; step 4, determining the possible maximum rainfall in the storm similar area; and 5, determining the possible maximum rainfall time course distribution of the storm similar area. The method fully utilizes the existing data such as hydrological weather in various places, increases the short-duration rainfall sample capacity, ensures the consistency of analysis results of the upstream and downstream of the watershed, and avoids uncertainty caused by subjective selection of typical heavy storm; and fully consider the influence of the regional complex topography change of hilly area to regional rainfall continuous space distribution, the suitability is strong, and the degree of accuracy is high, can supply mountain torrent disaster defense department to select to support work such as mountain torrent disaster defense risk decision-making and planning under the extreme storm scene.
Description
Technical Field
The invention belongs to the technical field of hydrological weather, and particularly relates to a method for determining regional possible maximum rainfall for mountain and flood ditches.
Background
In the background of global climate change and gradual increase of economic and social activities of mountain areas, extremely heavy rains of mountain areas, especially short-duration heavy rainfall events of local areas are increasingly serious and frequent, and the mountain torrent disaster risk is further aggravated. In order to scientifically defend mountain torrents, a county-town-village multi-stage mountain torrents disaster defense plan is needed to be compiled, the mountain torrents forming evolution process, the mountain torrents disaster risk and the influence range under extreme storm scenes are analyzed and evaluated, and the possible maximum rainfall of mountain torrents river basin is needed to be determined as the upper boundary condition of rainfall driving.
Currently, the calculation methods of the maximum rainfall are classified into a statistical estimation method and a hydro-meteorological method, wherein the hydro-meteorological method comprises a local heavy rain amplification method, a heavy rain displacement method, a heavy rain combination method, a physical mode method, a generalized estimation method and the like. On one hand, the method is generally used for estimating the maximum rainfall possible for a long duration (more than 24 hours) when a single hydraulic engineering flood control planning design, and the accuracy of estimating the maximum rainfall possible for a short duration in a mountain area is relatively poor; on the other hand, the method has higher technical requirements on basic data and the hydrological profession; the statistical estimation method and the storm combining method need to design a large amount of actual measured storm data of an engineering river basin, the effectiveness and errors of the statistical estimation method are still to be researched, the statistical estimation method is less applied in China, and the storm combining method needs to reconstruct typical storm data according to the weather climatology principle; the physical model method needs to design a large amount of actual measurement high altitude meteorological data of an engineering river basin, and builds a physical equation based on a generalized stormwater weather system structure to estimate; the local storm amplifying method, the storm displacement method and the generalized estimation method need to design engineering watershed or one or more places of weak meeting or bad influence typical heavy storm data, correct by combining the shape, the elevation and the like of the engineering watershed, amplify by combining a power factor and a water vapor factor, and have larger uncertainty of the amplifying factor. The area of the mountain torrent river basin is generally hundreds of square kilometers, the converging duration of disaster storm and river basin is short, the duration is more than 6 hours, and the mountain torrent region has complex terrain and mostly lacks long-sequence rainfall monitoring data, so that the method cannot meet the requirement of determining the possible maximum rainfall of the mountain torrent river basin.
Therefore, for the situations of small mountain and flood drainage basin area, short duration of disaster-induced heavy rain, complex terrain, actual measurement heavy rain data shortage and the like, a simple and feasible method is needed to determine the possible maximum rainfall of the mountain and flood drainage basin, so that the works of mountain and flood drainage basin possible maximum flood simulation deduction, mountain and flood disaster area risk assessment, defense planning and the like are carried out.
Disclosure of Invention
The invention aims to provide a method for determining the maximum rainfall possible in a region of a mountain and flood ditch river basin so as to solve the technical problems.
The invention is realized by the following technical scheme:
the invention provides a method for determining the regional possible maximum rainfall for mountain and flood ditches, which comprises the following steps: a method for determining regional likely maximum rainfall for a mountain flood valley basin, the method comprising the steps of:
step 2, determining the spatial distribution of maximum rainfall of different duration of the scene rainfall: determining the analyzed kilometer grid size and the sliding window radius according to the collected field rainfall extract data in the step 1, constructing a rainfall regression interpolation model, determining regression parameters of each kilometer grid, and interpolating to determine the spatial distribution of the maximum rainfall in different durations in each field rainfall process;
step 3, determining a storm similar area: according to the collected hydrological weather characteristic indexes in the step 1, initially determining a storm similar area, then according to the collected storm statistical parameters in the step 1 and the determined maximum rainfall of different duration of each rainfall, judging the initially determined storm similar area by adopting a non-parameter test method, and determining a final storm similar area;
step 4, determining the possible maximum rainfall in the storm similar area: taking the final storm similar area determined in the step 3 as a basic unit, and determining the coverage area of each field rainfall based on the spatial distribution of the maximum rainfall of different duration in each field rainfall process determined in the step 2 according to a specified rainfall threshold value of the kilometer grid; in the area of each field rainfall cage of each storm similar area, taking a kilometer grid with the largest rainfall as a center, determining the corresponding maximum rainfall of different rain collecting areas under different rainfall histories of each field rainfall process of each storm similar area according to the principle of the largest accumulated rainfall of adjacent grids, drawing a relationship curve of the maximum rainfall and the rain collecting areas, drawing upper envelope curves of the relationship curves of the maximum rainfall and the rain collecting areas of all fields by adopting an overcladding method, and determining the regional maximum rainfall under different rainfall durations and different rain collecting areas of each storm similar area;
step 5, determining the possible maximum rainfall time course distribution of the storm similar area: normalizing the collected fraction data of the precipitation in the step 1, determining standardized time course distribution and accumulated distribution of all precipitation, and determining flood time scales of all precipitation based on the ratio of flood volume and flood peak flow of each precipitation-induced flood; the final rainfall similar areas determined in the step 3 are taken as basic units, and the flood time scale of each rainfall is taken as an index, so that the flood types induced by each rainfall in each rainfall similar area are determined; according to the determined cumulative distribution of all the field rainfall, determining corresponding rainfall cumulative distribution and typical rainfall standardized time course distribution of each flood type in each storm similar area by adopting a median method, selecting typical rainfall standardized time course distribution according to the most unfavorable flood type for a flood control protection object, and determining the time course distribution of the regional possible maximum rainfall under different durations according to the same-time ratio amplification method and the water balance method based on different rainfall durations and the regional possible maximum rainfall under different rainfall areas in each storm similar area in the step 4.
Further, the hydrographic characteristic index comprises a plurality of years of average rainfall, an evapotranspiration amount, a mean value of maximum rainfall in different durations and a ratio of standard deviation to the mean value of the maximum rainfall in different durations; the different durations range from 1 to 24 hours.
Further, the storm statistical parameters including the variation coefficient and the deviation coefficient are determined according to a storm map set and a hydrological manual of the region where the study area is located.
Further, in the scene rainfall extract data, the collected scene rainfall in the wet and semi-wet areas reaches the extremely heavy storm level, the collected scene rainfall in the semiarid areas reaches the heavy storm level, and the collected scene rainfall in the arid areas reaches the heavy storm level; and for areas lacking measured flood peak flow and flood, adopting a watershed hydrologic model method or a hydrologic comparison method to calculate.
Further, the process of determining the analyzed kilometer grid size and sliding window radius is as follows: and (2) determining the analyzed kilometer grid size by combining the kilometer grid size adopted in the storm map set of the research area and the small river basin unit area of the catchment area of the mountain torrent station, and determining the radius of the sliding window by adopting a cross verification method according to the maximum rainfall amounts of different durations of each rainfall determined in the step (1).
Further, the process of constructing the rainfall regression interpolation model and determining regression parameters of each kilometer grid is as follows: and (3) taking each kilometer grid in a research area as a center, determining rainfall stations and mountain torrents positioned in the radius of a sliding window of the kilometer grid, analyzing the height difference, the distance and the slope direction of each rainfall station and each mountain torrent station, constructing a rainfall regression interpolation model based on the change of the topography, the distance and the slope direction of each mountain torrent station, determining the comprehensive weight of all rainfall stations and each mountain torrent station, and determining the regression parameters of each kilometer grid by adopting a weighted least square method.
Further, the preliminary determination of the storm similar area comprises the following steps: based on the collected hydrological characteristic indexes in the step 1, determining the correlation among the indexes by adopting a correlation analysis method, and determining key indexes for storm similarity analysis by adopting a principal component analysis method; and dividing the cluster group number by adopting a cluster analysis method according to the determined key indexes, evaluating the clustering effect, and preliminarily determining the storm similar area.
Further, the process of distinguishing the initially determined storm similar area and determining the final storm similar area by adopting a non-parameter inspection method comprises the following steps: judging whether the storm statistical parameters are remarkably different or not among all the subareas by adopting a heterogeneity test method, an independence test method and an dissonance test method based on the storm statistical parameters collected in the step 1 and the determined maximum rainfall of different duration of each rainfall for the preliminarily determined storm similar area; judging whether the maximum rainfall in different durations is significantly different or not between the subareas by using a Mannheim rank sum test method; for the storm similar areas which do not pass the non-parametric test, carrying out partition adjustment by combining the topographic distribution and the storm causes, and repeating the test process until the non-parametric test is passed, thereby determining the final storm similar areas.
Further, the number of the relation curves of the maximum rainfall and the rain collecting area is i×j×k clusters, wherein i represents the number of similar areas of heavy rain, j represents the number of field rainfall, and k represents the number of rainfall calendar hours.
Further, the flood types include peak high volume small flood, large peak low volume flood, intermediate flood; the typical rainfall standardized time course distribution is selected according to the type of flood which is least favorable for flood protection objects, and is specifically as follows: when high-intensity flood with large destructive power is most unfavorable for flood control protection objects, typical rainfall standardization time course distribution corresponding to small-sized flood with peak height is selected; when a large amount of flood with a large submerging range is least beneficial to flood control protection objects, typical rainfall standardization time course distribution corresponding to a large amount of peak low-level flood is selected; when both high intensity floods and large flood volumes are most unfavorable for flood protection objects, typical rainfall standardized time course distribution corresponding to intermediate type floods is selected.
The beneficial effects of the invention are as follows: the method is used for determining the possible maximum rainfall in the areas of the mountain floods and the river basins, is simple, convenient and easy to operate, increases the short-duration rainfall sample capacity by utilizing the existing hydrological weather and other data in each area, ensures the consistency of the upstream and downstream analysis results of the river basins, and avoids the uncertainty caused by subjective selection of typical heavy storm; and fully consider the influence of the complicated topography change of hilly area to regional rainfall continuous space distribution, the suitability is strong, the degree of accuracy is high, easily promotes, can supply mountain torrent disaster defense department to select to support work such as mountain torrent disaster defense risk decision-making and planning under the extreme storm scene.
The invention is described in further detail below with reference to the drawings and the detailed description.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a process for determining storm similar areas;
FIG. 3 is a schematic diagram of the maximum possible rainfall for three rainfall areas of a storm similar area 1 under different rain areas;
FIG. 4 is a schematic diagram of the maximum possible rainfall for three rainfall areas of a storm similar area 2 over different rain areas;
FIG. 5 is a typical rainfall normalized time course distribution diagram corresponding to the flood type of the storm surge area 1;
FIG. 6 is a typical rainfall normalized time course distribution diagram corresponding to the flood type of the storm surge area 2;
FIG. 7 is a graph showing the possible maximum rainfall schedule for the storm surge area 1;
fig. 8 is a graph showing the possible maximum rainfall schedule of the storm surge area 2.
Detailed Description
The invention provides a method for determining the regional possible maximum rainfall for mountain and flood ditches, which is shown in fig. 1 and comprises the following steps:
The hydrological characteristic indexes comprise average rainfall over a plurality of years, evapotranspiration, average value of maximum rainfall in different durations, ratio of standard deviation of the maximum rainfall in different durations to the average value and the like; the range of different duration is 1-24 hours; wherein the storm statistical parameters comprise a variation coefficient and a deviation coefficient, which are determined according to a storm chart set and a hydrological manual of the region where the study area is located.
In the scene rainfall extract data, the collected scene rainfall in wet and semi-wet areas should reach the level of extremely heavy storm, the collected scene rainfall in semiarid areas should reach the level of heavy storm, and the collected scene rainfall in arid areas should reach the level of heavy storm; for areas lacking measured flood peak flow and flood volume, the method such as a river basin hydrologic model method or a hydrologic comparison method can be adopted for deduction.
Step 2, determining the spatial distribution of maximum rainfall of different duration of the scene rainfall: according to the collected and tidied scene rainfall extract data in the step 1, the kilometer grid size adopted in the storm map set of the research area and the small river basin unit area of the mountain torrent station water collecting area are combined, the analyzed kilometer grid size is determined, and according to the maximum rainfall amounts of different durations of each scene rainfall determined in the step 1, the sliding window radius is preferably determined by adopting a cross verification method; determining rainfall stations and mountain torrents in the sliding window radius of the kilometer grid by taking each kilometer grid in a research area as a center, analyzing the height difference, the distance and the slope direction of each rainfall station and each mountain torrent station of the kilometer grid, constructing a rainfall regression interpolation model based on the change of the topography, the distance and the slope direction of each mountain torrent station, determining the comprehensive weight of all rainfall stations and each mountain torrent station, and determining the regression parameters of each kilometer grid by adopting a weighted least square method; and (3) according to the maximum rainfall of different durations of each rainfall, which is determined in the step (1), taking a kilometer grid as a basic unit, adopting a constructed rainfall regression interpolation model, and interpolating to determine the spatial distribution of the maximum rainfall of different durations in each rainfall process.
Step 3, determining a storm similar area: as shown in fig. 2, according to the hydrological characteristic indexes in the step 1, a correlation analysis method is adopted to determine the correlation among the indexes, and a principal component analysis method is adopted to determine key indexes for storm similarity analysis; dividing the clustering group number by adopting a clustering analysis method according to the determined key indexes, evaluating the clustering effect, and preliminarily determining a plurality of mutually independent storm similar areas according to the clustering effect; and then judging the preliminarily determined storm similar area by adopting a non-parameter test method according to the collected storm statistical parameters in the step 1 and the determined maximum rainfall of different durations of each rainfall, wherein the specific process is as follows: judging whether the storm statistical parameters of all the subareas have significant differences or not by adopting a heterogeneity test method, an independence test method and an dissonance test method, and judging whether the maximum rainfall of different durations is significantly different or not by adopting a Mannheim rank sum test method; for the storm similar areas which do not pass the non-parametric test, carrying out partition adjustment by combining the topographic distribution and the storm causes, and repeating the test process until the non-parametric test is passed, thereby determining the final storm similar areas.
Step 4, determining the possible maximum rainfall in the storm similar area: taking the final storm similar area determined in the step 3 as a basic unit, and determining the coverage area of each field rainfall based on the spatial distribution of the maximum rainfall of different duration in each field rainfall process determined in the step 2 according to a specified rainfall threshold value of the kilometer grid; and determining the corresponding maximum rainfall amount of different rainfall collecting areas in different rainfall calendars of each field rainfall process in each storm similar area by taking the kilometer grid with the largest rainfall amount as the center and according to the principle that the accumulated rainfall amount of the adjacent grids is largest. And drawing a relation curve of the maximum rainfall and the rain collecting area of the i multiplied by j multiplied by k clusters, wherein i represents the number of similar areas of the storm, j represents the number of field rainfall, and k represents the number of rainfall calendar hours. And drawing upper envelope curves of relation curves of maximum rainfall and rain collecting areas of all sites by adopting an envelope curve method aiming at each rainfall duration of each storm similar area, and determining the possible maximum rainfall of areas under different rainfall durations and different rain collecting areas of each storm similar area.
Step 5, determining the possible maximum rainfall time course distribution of the storm similar area: normalizing the collected fraction data of the precipitation in the step 1, determining the normalized time course distribution and the accumulated distribution of all the precipitation, and determining the flood time scale of all the precipitation based on the ratio of the flood volume and the flood peak flow volume of each precipitation-induced flood. The final rainfall similar areas determined in the step 3 are taken as basic units, the flood time scale of each rainfall is taken as an index, the clustering group number is divided by adopting a clustering analysis method, the clustering effect is evaluated, and the flood type induced by each rainfall in each rainfall similar area is determined; among the flood types are peak high volume small flood, large peak low volume flood, and intermediate flood.
According to the determined cumulative distribution of all the field rainfall, determining the corresponding rainfall cumulative distribution and typical rainfall standardized time interval distribution of each flood type in each storm similar area by adopting a median method, and then selecting the typical rainfall standardized time interval distribution according to the most unfavorable flood type for the flood control protection object, wherein the typical rainfall standardized time interval distribution is specifically as follows: if the high-intensity flood with large destructive power is most unfavorable to the flood control protection object, selecting typical rainfall standardized time course distribution corresponding to the small-sized flood with high peak height; if the large flood with a large submerged range is most unfavorable to the flood control protection object, selecting typical rainfall standardized time course distribution corresponding to the large peak low flood; if the high-intensity flood and the large-volume flood are both the most unfavorable for the flood control protection object, the typical rainfall standardized time course distribution corresponding to the intermediate type flood is selected. And finally, determining the time course distribution of the possible maximum rainfall of the area under different durations according to a same-magnification ratio amplification method and a water balance method based on the different rainfall durations of the storm similar areas and the possible maximum rainfall of the area under different rainfall areas in the step 4.
Example 1
The present embodiment is a specific application example of the above method.
And step 1, collecting hydrological data and scene rainfall flood data of a research area.
In this embodiment, the downstream area in Yuan Shui is selected as a research area, and the hydrological characteristic indexes and the storm statistical parameters of each rainfall station in the area, and the extracted data of each rainfall station and the mountain torrent station in the area, and the peak flow and the flood of each rainfall induced flood are collected and arranged.
The collected hydrological characteristic indexes comprise average rainfall, evapotranspiration, average maximum rainfall in different durations and standard deviation to average ratio of the maximum rainfall in different durations; respectively selecting 1 hour, 6 hours and 24 hours in different durations; the storm variance and bias coefficients for each of the rain stations in the study area were determined for 1 hour, 6 hours and 24 hours.
The research area of the embodiment is positioned in a humid area, and the collected rainfall reaches the level of extremely large storm, namely, the rainfall is not less than 250mm in 24 hours, not less than 120mm in 6 hours and not less than 50mm in 1 hour; and (3) for peak flood and flood, adopting a Chinese mountain torrent hydrologic model method to calculate.
And step 2, determining the spatial distribution of the maximum rainfall in different duration of the scene rainfall.
The kilometer grid size and the sliding window radius analyzed in this embodiment are 5km and 20km, respectively, taking a certain grid in the research area as an example, 10 rainfall stations and torrential flood stations are arranged in the sliding window radius, the comprehensive weight of each station is 0.0001-0.2189, and the regression parameters of the grid are 0.261mm/km and 1523.9mm.
And (3) according to the maximum rainfall of different durations of each rainfall, which is determined in the step (1), taking a kilometer grid as a basic unit, adopting a constructed rainfall regression interpolation model, and interpolating to determine the spatial distribution of the maximum rainfall of different durations in each rainfall process.
And 3, determining a storm similar area.
The key indexes of the storm similarity analysis determined by the embodiment are shown in table 1, the clustering analysis method adopts a dynamic K-means clustering method, the clustering effect is evaluated by adopting an elbow rule, and the number of the preliminarily determined storm similarity areas is 2.
TABLE 1 storm similarity analysis Key index
And taking the preliminarily determined storm similar areas as units, wherein the storm variation coefficients and the bias coefficients of each rainfall station in each storm similar area for 1 hour, 6 hours and 24 hours pass through the heterogeneity test, the independence test and the dissonance test. There were significant differences in the maximum rainfall for 1 hour, 6 hours and 24 hours in the 2 stormwater-like areas, with a significance level p <5%. Thus, the final storm similar area was determined to be 2.
And 4, determining the possible maximum rainfall in the storm similar area.
The rainfall threshold value of the kilometer grid specified in the embodiment is 1.27mm, the number of similar areas of the heavy rain i=2, the number of field rainfall j=150 and the number of rainfall calendar time k=3; drawing a relation curve of the maximum rainfall and the rain collecting area, drawing upper envelope curves of the relation curves of the maximum rainfall and the rain collecting area of all field times by adopting an envelope curve method aiming at each rainfall duration of each storm similar area, determining the different rainfall durations of each storm similar area and the possible maximum rainfall of areas under different rain collecting areas, and finally obtaining the possible maximum rainfall of areas under 3 rainfall durations of 2 storm similar areas and different rain collecting areas, wherein the possible maximum rainfall is shown in figures 3 and 4.
And 5, determining the possible maximum rainfall time course distribution of the storm similar area.
The clustering analysis method of the embodiment adopts a dynamic K-means clustering method, adopts an elbow rule to evaluate the clustering effect, determines that the flood type of the heavy rain similar area 1 is a large-peak low-level flood, the flood type of the heavy rain similar area 2 is a peak-height small-scale flood, and typical rainfall standardized time interval distribution corresponding to each flood type of each heavy rain similar area is shown in fig. 5 and 6.
And finally, determining the time course distribution of the possible maximum rainfall of the areas under different durations of each storm similar area according to a same-magnification ratio amplification method and a water balance method based on the different rainfall durations of each storm similar area and the possible maximum rainfall of the areas under different rain collecting areas in the step 4. In the embodiment, the water collection area of the mountain flood ditch drainage basin is 200km 2 The peak rainfall in the mountain and flood valley drainage areas of the storm similar areas 1 and 2 obtained by looking up the fig. 3 and 4 is 420mm and 292mm respectively, corresponding to the maximum rainfall for 24 hoursThe 24 hour time course distribution of (2) is shown in fig. 7 and 8, respectively.
Finally, it should be noted that the above description is only for the purpose of illustrating the technical solution of the present invention and not for the purpose of limiting the same, and that although the present invention has been described in detail with reference to the preferred arrangement, it will be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. A method for determining regional likely maximum rainfall for a mountain flood valley basin, the method comprising the steps of:
step 1, collecting hydrological data and scene rainfall flood data of a research area: collecting hydrological weather characteristic indexes and storm statistical parameters of each rainfall station in a research area, and collecting rainfall extraction data of each rainfall station and mountain torrent station in the research area, and flood peak flow and flood volume of each rainfall induced flood; determining the maximum rainfall of different duration of each rainfall;
step 2, determining the spatial distribution of maximum rainfall of different duration of the scene rainfall: determining the analyzed kilometer grid size and the sliding window radius according to the collected field rainfall extract data in the step 1, constructing a rainfall regression interpolation model, determining regression parameters of each kilometer grid, and interpolating to determine the spatial distribution of the maximum rainfall in different durations in each field rainfall process;
step 3, determining a storm similar area: according to the collected hydrological weather characteristic indexes in the step 1, initially determining a storm similar area, then according to the collected storm statistical parameters in the step 1 and the determined maximum rainfall of different duration of each rainfall, judging the initially determined storm similar area by adopting a non-parameter test method, and determining a final storm similar area;
step 4, determining the possible maximum rainfall in the storm similar area: taking the final storm similar area determined in the step 3 as a basic unit, and determining the coverage area of each field rainfall based on the spatial distribution of the maximum rainfall of different duration in each field rainfall process determined in the step 2 according to a specified rainfall threshold value of the kilometer grid; in the area of each field rainfall cage of each storm similar area, taking a kilometer grid with the largest rainfall as a center, determining the corresponding maximum rainfall of different rain collecting areas under different rainfall histories of each field rainfall process of each storm similar area according to the principle of the largest accumulated rainfall of adjacent grids, drawing a relationship curve of the maximum rainfall and the rain collecting areas, drawing upper envelope curves of the relationship curves of the maximum rainfall and the rain collecting areas of all fields by adopting an overcladding method, and determining the regional maximum rainfall under different rainfall durations and different rain collecting areas of each storm similar area;
step 5, determining the possible maximum rainfall time course distribution of the storm similar area: normalizing the collected fraction data of the precipitation in the step 1, determining standardized time course distribution and accumulated distribution of all precipitation, and determining flood time scales of all precipitation based on the ratio of flood volume and flood peak flow of each precipitation-induced flood; the final rainfall similar areas determined in the step 3 are taken as basic units, and the flood time scale of each rainfall is taken as an index, so that the flood types induced by each rainfall in each rainfall similar area are determined; according to the determined cumulative distribution of all the field rainfall, determining corresponding rainfall cumulative distribution and typical rainfall standardized time course distribution of each flood type in each storm similar area by adopting a median method, selecting typical rainfall standardized time course distribution according to the most unfavorable flood type for a flood control protection object, and determining the time course distribution of the regional possible maximum rainfall under different durations according to the same-time ratio amplification method and the water balance method based on different rainfall durations and the regional possible maximum rainfall under different rainfall areas in each storm similar area in the step 4.
2. The regional likely maximum rainfall determination method for mountain floods and valley streams of claim 1, wherein the hydrographic characteristic indicators comprise annual average rainfall, evapotranspiration, average maximum rainfall over different durations, standard deviation to average ratio of maximum rainfall over different durations; the different durations range from 1 to 24 hours.
3. The method for determining the regional likely maximum rainfall for mountain and flood drainage basins according to claim 1, wherein the storm statistical parameters comprise a variation coefficient and a bias coefficient, and are determined according to a storm atlas and a hydrological manual of the region where the study area is located.
4. The method for determining the maximum possible rainfall in areas of mountain and flood valley drainage basins according to claim 1, wherein in the scene rainfall extract data, the collected scene rainfall in wet and semi-wet areas reaches an extra-heavy level, the collected scene rainfall in semi-arid areas reaches a heavy level, and the collected scene rainfall in arid areas reaches a heavy level; and for areas lacking measured flood peak flow and flood, adopting a watershed hydrologic model method or a hydrologic comparison method to calculate.
5. A method for determining regional likely maximum rainfall for mountain and flood drainage basins as claimed in claim 3, wherein the process of determining the analyzed kilometer grid size and sliding window radius is: and (2) determining the analyzed kilometer grid size by combining the kilometer grid size adopted in the storm map set of the research area and the small river basin unit area of the catchment area of the mountain torrent station, and determining the radius of the sliding window by adopting a cross verification method according to the maximum rainfall amounts of different durations of each rainfall determined in the step (1).
6. The method for determining regional likely maximum rainfall for mountain and flood drainage basins according to claim 5, wherein the process of constructing a rainfall regression interpolation model and determining regression parameters of each kilometer grid is as follows: and (3) taking each kilometer grid in a research area as a center, determining rainfall stations and mountain torrents positioned in the radius of a sliding window of the kilometer grid, analyzing the height difference, the distance and the slope direction of each rainfall station and each mountain torrent station, constructing a rainfall regression interpolation model based on the change of the topography, the distance and the slope direction of each mountain torrent station, determining the comprehensive weight of all rainfall stations and each mountain torrent station, and determining the regression parameters of each kilometer grid by adopting a weighted least square method.
7. The method for determining regional likely maximum rainfall for mountain and flood drainage basin according to claim 1, wherein the preliminary determination of the storm similar region is: based on the collected hydrological characteristic indexes in the step 1, determining the correlation among the indexes by adopting a correlation analysis method, and determining key indexes for storm similarity analysis by adopting a principal component analysis method; and dividing the cluster group number by adopting a cluster analysis method according to the determined key indexes, evaluating the clustering effect, and preliminarily determining the storm similar area.
8. The method for determining the regional likely maximum rainfall for mountain and flood drainage basins according to claim 7, wherein the process of distinguishing the preliminarily determined storm similar areas and determining the final storm similar areas by adopting a non-parametric test method is as follows: judging whether the storm statistical parameters are remarkably different or not among all the subareas by adopting a heterogeneity test method, an independence test method and an dissonance test method based on the storm statistical parameters collected in the step 1 and the determined maximum rainfall of different duration of each rainfall for the preliminarily determined storm similar area; judging whether the maximum rainfall in different durations is significantly different or not between the subareas by using a Mannheim rank sum test method; for the storm similar areas which do not pass the non-parametric test, carrying out partition adjustment by combining the topographic distribution and the storm causes, and repeating the test process until the non-parametric test is passed, thereby determining the final storm similar areas.
9. The method for determining the regional likely maximum rainfall for mountain and flood drainage basins according to claim 1, wherein the number of the drawn maximum rainfall and rain area relation curves is i x j x k clusters, i represents the number of storm similar regions, j represents the number of field rainfall, and k represents the number of rainfall calendar hours.
10. The regional likely maximum rainfall determination method for mountain floods according to claim 1, wherein the flood types comprise peak high volume small flood, volume large peak low flood, intermediate flood; the typical rainfall standardized time course distribution is selected according to the type of flood which is least favorable for flood protection objects, and is specifically as follows: when high-intensity flood with large destructive power is most unfavorable for flood control protection objects, typical rainfall standardization time course distribution corresponding to small-sized flood with peak height is selected; when a large amount of flood with a large submerging range is least beneficial to flood control protection objects, typical rainfall standardization time course distribution corresponding to a large amount of peak low-level flood is selected; when both high intensity floods and large flood volumes are most unfavorable for flood protection objects, typical rainfall standardized time course distribution corresponding to intermediate type floods is selected.
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