CN111462450A - Mountain torrent early warning method considering rainfall spatial heterogeneity - Google Patents
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- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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Abstract
The invention discloses a mountain torrent early warning method considering rainfall spatial heterogeneity, belonging to the field of hydrologic prediction and comprising the following steps: acquiring soil saturation and composite rainfall in a set time period before occurrence of multi-field historical flood peaks of a drainage basin to be pre-warned; the composite rainfall gives consideration to the rainfall and the rainfall spatial distribution; constructing a mountain torrent early warning model according to the soil saturation and the composite rainfall; the method comprises the steps of collecting the soil saturation of the drainage basin to be pre-warned, obtaining a critical composite rainfall index corresponding to the current soil saturation according to a mountain torrent pre-warning model, and judging whether the rainfall-generated flood is the super-warning flood or not by comparing the current composite rainfall of the drainage basin to be pre-warned with the critical composite rainfall index. The method can specifically quantify the unevenness of rainfall spatial distribution and the distribution condition of rainstorm centers, and the calculated critical composite rainfall index takes the rainfall into account as well as the rainfall spatial distribution, so that the accuracy of mountain torrents early warning can be improved.
Description
Technical Field
The invention belongs to the technical field of hydrologic forecasting, and particularly relates to a mountain torrent early warning method considering rainfall spatial heterogeneity.
Background
Under the influence of global warming, the local heavy rainfall frequency in the hilly area is increased, and along with the aggravation of human activities in the hilly area, the mountain flood disaster gradually becomes a short board for flood prevention and disaster reduction in China. Therefore, national mountain torrent disaster investigation and evaluation work is carried out in 2010-2016 in China, great progress is made in key technologies of mountain torrent disaster prevention such as mountain torrent disaster risk zoning, forecasting and early warning, and a mountain torrent disaster prevention system is initially built. On one hand, however, the prevention and treatment amount of mountain torrent disasters in China is wide, and the treatment difficulty is high; on the other hand, the existing defense technology still has some 'neck clamping' problems to be broken through urgently, such as accuracy and timeliness of mountain torrents early warning and the like.
The early warning of the mountain torrents can be generally realized by establishing a high-precision flood forecasting model and carrying out early warning according to the fact that whether the forecast flood peak exceeds the warning flow of a river channel or not. Another feasible way is to establish early warning indexes closely related to mountain torrents and judge whether to perform early warning according to the early warning indexes. The critical rainfall is one of the commonly used early warning indexes, and is directly related to the rainfall, and is also influenced by the water content of soil, the heterogeneity of rainfall space and the like. The spatial heterogeneity of rainfall means that rainfall exhibits different distributions in different spatial regions of the flow field.
Quantitative indexes of rainfall spatial heterogeneity comprise a variation coefficient, an uneven coefficient and the like; the variation coefficient reflects the spatial discrete degree of rainfall data, and the non-uniform coefficient reflects the point-surface reduction degree of rainfall. Although the indexes can reflect the spatial difference of rainfall, the distribution condition of a rainstorm center cannot be reflected, the information contained in the indexes is not comprehensive enough, and the critical rainfall cannot be directly calculated, so that the accuracy of mountain torrent early warning is influenced.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a mountain torrent early warning method considering rainfall spatial heterogeneity, aiming at accurately quantifying the unevenness of rainfall spatial distribution and the distribution situation of rainstorm centers, and calculating a critical composite rainfall index which can consider the rainfall and the rainfall spatial distribution situation so as to improve the accuracy of mountain torrent early warning.
In order to achieve the purpose, the invention provides a mountain torrent early warning method considering rainfall spatial heterogeneity, which comprises the following steps:
s1: acquiring soil saturation and composite rainfall in a set time period before occurrence of multi-field historical flood peaks of a drainage basin to be pre-warned; the composite rainfall is calculated according to the surface average rainfall and the rainfall spatial heterogeneous index; the rainfall spatial heterogeneity index is obtained by calculating the average rainfall of the surface of the watershed to be pre-warned, the relative area of the equal-flow time surface and the average rainfall of the equal-flow time surface in a set time period;
s2: constructing a mountain torrent early warning model according to the soil saturation and the composite rainfall to obtain critical composite rainfall indexes corresponding to different soil saturations;
s3: the method comprises the steps of collecting the soil saturation of the drainage basin to be pre-warned, obtaining a critical composite rainfall index corresponding to the current soil saturation according to a mountain torrent pre-warning model, and judging whether the rainfall-generated flood is the super-warning flood or not by comparing the current composite rainfall of the drainage basin to be pre-warned with the critical composite rainfall index.
Further, the calculation method of the rainfall spatial heterogeneity index specifically comprises the following steps:
01: calculating the area of a Thiessen polygon corresponding to each rainfall site in the area to be early-warned, and calculating the average rainfall of the drainage basin surface to be early-warned according to the area of the Thiessen polygons corresponding to each rainfall site and the historical rainfall;
02: calculating the relative area and the average rainfall of each equal-flow time surface of the area to be pre-warned;
03: calculating the rainfall spatial heterogeneity index according to the following formula:
wherein SHIP represents rainfall spatial heterogeneity index, RkThe surface average rainfall of the k-th equal-flow surface is shown.
Further, the calculation formula of the average rainfall of the drainage basin surface to be pre-warned is as follows:
wherein the content of the first and second substances,
for the average rainfall of the drainage basin surface to be pre-warned, lambdaiThe proportion of the area of the Thiessen polygon corresponding to the ith rainfall station to the total area of the drainage basin is represented, wherein i is 1,2 …, n represents the total number of the rainfall stations in the drainage basin to be pre-warned; piIndicating the historical rainfall of the ith rainfall site.
Further, the relative area calculation formula of the equal flow time surface is as follows:
wherein f isjDenotes the relative area of the jth equal flow time plane, j is 1,2, …, m, m denotes the total number of equal flow time planes, ri,jAnd the proportion of the area of the Thiessen polygon corresponding to the rainfall station i contained in the jth equal-flow time plane to the total area of the drainage basin is shown.
Further, the surface average rainfall of the equal-flow time surface is calculated by the following formula:
wherein R isjThe surface average rainfall of the jth equal-flow surface is shown.
Further, the soil saturation S is calculated by the formula:
wherein, PaInfluence of rainfall in the early stages of flood peak occurrence, WmThe maximum soil moisture content in the drainage basin.
Further, the compound rainfall PsComprises the following steps:
further, the step S2 of constructing the mountain torrent early warning model according to the above indexes specifically includes the following steps:
01. data set D { (x)l,yl) 1,2, …, L } as input, yl1 as output; wherein x isl＝[Ps,S]，PsThe composite rainfall is represented by y which is 1 and represents an overtemperature, y which is 0 and represents no overtemperature, and L represents the number of actually measured historical peaks;
02. based on the classification principle of the support vector machine, the following objective function is obtained to enable the classification interval of the super-alarm flood and the non-super-alarm flood to be maximum:
wherein w ═ w1,w2]TOptimal hyperplane w for maximizing classification interval of hypersonic floods and non-hypersonic floodsTxl+ b is a normal vector of 0, b is a displacement term; c>0 is a penalty parameter, so as to make misclassification pointξ in as small a number as possiblelThe relaxation variable is more than or equal to 0, so that the influence of outliers on the classification model is reduced;
03. solving the objective function by adopting a Lagrange multiplier method and a sequence minimum optimization algorithm to obtain an optimal classification hyperplane wTxlThe + b is the parameter w and b of 0, and the critical composite rainfall index P corresponding to different soil saturation degrees is obtainedcComprises the following steps:
in general, the above technical solutions contemplated by the present invention can achieve the following advantageous effects compared to the prior art.
Compared with the traditional mountain torrent early warning model, the method and the system have the advantages that the influence of rainfall spatial heterogeneity on the critical rainfall of the mountain torrent is considered, the unevenness of rainfall spatial distribution and the distribution situation of a rainstorm center can be accurately quantized, the critical composite rainfall index which can consider the rainfall and the rainfall spatial distribution situation is obtained, and accordingly the accuracy of flood early warning is effectively improved.
Drawings
Fig. 1 is a flowchart of a mountain torrent early warning method considering rainfall spatial heterogeneity according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a rainfall spatial distribution curve;
fig. 3(a) is a schematic diagram of flood warning results without considering spatial heterogeneity;
fig. 3(b) is a schematic diagram of flood warning results considering spatial heterogeneity.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, the present invention provides a mountain torrent early warning method considering rainfall spatial heterogeneity, including:
s1: acquiring soil saturation and composite rainfall in a set time period before occurrence of multi-field historical flood peaks of a drainage basin to be pre-warned; the composite rainfall is calculated according to the surface average rainfall and the rainfall spatial heterogeneous index; the rainfall spatial heterogeneity index is obtained by calculating the average rainfall of the surface of the watershed to be pre-warned, the relative area of the equal-flow time surface and the average rainfall of the equal-flow time surface in a set time period;
specifically, in the embodiment of the present invention, in order to obtain the rainfall spatial distribution of the multi-field flood peak which occurs in the history, the soil saturation and the composite rainfall corresponding to 3 hours before each flood peak occurs and with the maximum continuous rainfall amount are calculated, and in a specific application, data corresponding to 6 hours, 12 hours, and 24 hours before the flood peak occurs and with the maximum continuous rainfall amount can also be obtained.
Wherein, the calculation formula of the soil saturation S is as follows:
wherein, PaInfluence of rainfall in the early stages of flood peak occurrence, WmThe maximum soil water content of the drainage basin;
wherein the compound rainfall PsThe calculation formula is as follows:
wherein, SHIP is rainfall spatial heterogeneity index,
the average rainfall of the drainage basin surface is obtained;
the method for calculating the rainfall spatial heterogeneity index comprises the following steps:
01: drawing a Thiessen polygon corresponding to each rainfall site in the area to be early-warned to obtain the area of the Thiessen polygon corresponding to each rainfall site, and calculating the average rainfall of the drainage basin surface to be early-warned according to the area of the Thiessen polygon corresponding to each rainfall site and the historical rainfall, wherein the specific calculation formula is as follows:
wherein the content of the first and second substances,
for the average rainfall of the drainage basin surface to be pre-warned, lambdaiThe proportion of the area of the Thiessen polygon corresponding to the ith rainfall station to the total area of the drainage basin is represented, wherein i is 1,2 …, n represents the total number of the rainfall stations in the drainage basin to be pre-warned; piRepresenting the historical rainfall of the ith rainfall station;
02: drawing an equal flow time line of a region to be pre-warned to obtain a plurality of equal flow time surfaces, and calculating the relative area and surface average rainfall of each equal flow time surface; the relative area calculation formula of the equal flow time surface is as follows:
wherein f isjDenotes the relative area of the jth equal flow time plane, j is 1,2, …, m, m denotes the total number of equal flow time planes, ri,jAnd the proportion of the area of the Thiessen polygon corresponding to the rainfall station i contained in the jth equal-flow time plane to the total area of the drainage basin is shown.
The surface average rainfall of the surface during equal flow is calculated according to the formula:
wherein R isjThe surface average rainfall of the jth equal-flow surface is shown.
03: calculating the rainfall spatial heterogeneity index according to the following formula:
wherein R iskSurface average of k-th equal flow surfaceAnd (4) rainfall. With equal flow time surface relative area fjThe accumulated value of (A) is an abscissa, and the surface average rainfall R of the corresponding equal-flow time surface isjThe accumulated value of (2) is a vertical coordinate, a rainfall spatial distribution curve is drawn, the result shown in fig. 2 is obtained, when the SHIP is positive, the rainstorm center is located at the downstream, such as a curve A in fig. 2; when SHIP is negative, it indicates that the storm centre is upstream, as shown by curve B in FIG. 2.
S2: constructing a mountain torrent early warning model according to the indexes, and calculating dynamic critical composite rainfall indexes under different soil saturation degrees;
specifically, S2 includes the steps of:
2.1, dividing actually measured L flood peaks into two types of super-alarm and non-super-alarm according to the warning flow, respectively representing that y is 1 and y is 0, and combining two indexes [ P ] corresponding to each flood peaks,S]Construct dataset D { (x)l,yl)|l＝1,2,…,L}，xl＝[Ps,S]As an input; y islAs output {0,1 }.
2.2 based on the classification principle of the support vector machine, there is an optimal classification hyperplane
wTxl+b＝0
The classification interval (2/| w | |) of the flood with the excess flood and the flood without the excess flood is maximized. Wherein w ═ w1,w2]TB is a displacement term for optimally classifying the normal vector of the hyperplane. Thus, the problem of finding the optimal hyperplane translates into the following optimization problem:
in the formula, C>0 is a penalty parameter, the number of misclassification points can be reduced as much as possible by introducing C ξ l0 or more as a relaxation variable ξlThe introduction of (2) can reduce the influence of outliers on the classification model.
2.3, obtaining the dual problem of the optimization problem by using a Lagrange multiplier method, solving by using a sequence minimum optimization algorithm to obtain parameters w and b of the optimal hyperplane equation, wherein the hyperplane equation is a critical early warning plane equation, and thus obtaining the corresponding relation between the critical composite rainfall index and the soil saturation, namely the corresponding relation between the critical composite rainfall index and the soil saturation
Wherein, PcIs a critical composite rainfall index.
S3: collecting the soil saturation of the drainage basin to be pre-warned, obtaining a critical composite rainfall index corresponding to the current soil saturation according to the mountain torrent pre-warning model, and judging whether the flood generated by rainfall is over-warning flood or not by comparing the current composite rainfall of the drainage basin to be pre-warned with the critical rainfall index.
When the current average rainfall of the watershed to be pre-warned is greater than the critical composite rainfall index, judging that the watershed to be pre-warned is over-warning flood; otherwise, the flood is not over-police.
In order to verify the effectiveness of the method, the embodiment of the invention takes the river basin of Hanjiang river as an example to carry out mountain torrent early warning. Specifically, hydrological data of each rainfall site of the constant river basin in 1980-2017 are obtained, 30 floods of the basin are selected for model training, and 350m is measured3The flood of more than s is taken as early warning flood, and the soil saturation and the composite rainfall corresponding to 3 hours with the maximum continuous rainfall within 24 hours before the flood peak of each field occurs are only calculated in the embodiment of the invention.
The critical composite rainfall indexes corresponding to different soil saturation degrees of the constant river basin are obtained by the method, and are shown in table 1:
TABLE 1
In consideration of the spatial distribution characteristics of rainfall and watershed topographic features, the heavy rainfall process near the downstream of the rainstorm center often causes the downstream river channel to have steep rising flood, so that the mountain torrents rise very quickly, while the rainfall process near the upstream of the rainstorm center needs to pass through the long regulation and storage effect of the watershed, so that the mountain torrents rise slowly. In the invention, the influence of spatial non-uniformity of rainfall on the flood in the drainage basin is considered, critical composite rainfall is used as an early warning index, the composite rainfall depends on the product of (1+ SHIP) and surface average rainfall, when the rainfall center position is at the upstream of the drainage basin, the SHIP value is a negative value, and the drainage basin can reach the early warning value of the flood only by larger rainfall; when the rainfall center is positioned at the downstream of the drainage basin, the SHIP value is a positive value, and the drainage basin can reach the early warning value of flood only by small rainfall. The critical composite rainfall index is more consistent with the actual result because the spatial heterogeneity of rainfall and the surface average rainfall are simultaneously considered.
The mountain torrent early warning result considering spatial heterogeneity is shown in fig. 3(a), and the early warning accuracy reaches 80%; the mountain torrent early warning result without considering spatial heterogeneity is shown in fig. 3(b), the early warning accuracy is only 66.67%, and it can be seen that the method of the invention can effectively improve the accuracy of flood early warning.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A mountain torrent early warning method considering rainfall spatial heterogeneity is characterized by comprising the following steps:
s1: acquiring soil saturation and composite rainfall in a set time period before occurrence of multi-field historical flood peaks of a drainage basin to be pre-warned; the composite rainfall is calculated according to the surface average rainfall and the rainfall spatial heterogeneous index; the rainfall spatial heterogeneity index is obtained by calculation according to the average rainfall of the surface of the watershed to be pre-warned in a set time period, the relative area of the equal-flow time surface and the average rainfall of the equal-flow time surface;
s2: constructing a mountain torrent early warning model according to the soil saturation and the composite rainfall to obtain critical composite rainfall indexes corresponding to different soil saturations;
s3: collecting the soil saturation of the drainage basin to be pre-warned, obtaining a critical composite rainfall index corresponding to the current soil saturation according to the mountain torrent pre-warning model, and judging whether the rainfall-generated flood is the super-warning flood or not by comparing the current composite rainfall of the drainage basin to be pre-warned with the critical composite rainfall index.
2. The mountain torrent early warning method considering rainfall spatial heterogeneity as claimed in claim 1, wherein the calculation method of the rainfall spatial heterogeneity index specifically comprises:
01: calculating the area of a Thiessen polygon corresponding to each rainfall site in the area to be early-warned, and calculating the average rainfall of the drainage basin surface to be early-warned according to the area of the Thiessen polygons corresponding to each rainfall site and the historical rainfall;
02: calculating the relative area and the average rainfall of each equal-flow time surface of the area to be pre-warned;
03: calculating the rainfall spatial heterogeneity index according to the following formula:
wherein, SHIP represents a rainfall spatial heterogeneity index,
for average rainfall of the watershed surface to be warned, fjDenotes the relative area of the jth equal flow time surface, m denotes the total number of equal flow time surfaces, RkThe surface average rainfall of the k-th equal-flow surface is shown.
3. The mountain torrent early warning method considering rainfall spatial heterogeneity as claimed in claim 2, wherein the calculation formula of the average rainfall of the drainage basin to be early warned is as follows:
wherein λ isiThe proportion of the area of the Thiessen polygon corresponding to the ith rainfall station to the total area of the drainage basin is represented, wherein i is 1,2 …, n represents the total number of the rainfall stations in the drainage basin to be pre-warned; piIndicating the historical rainfall of the ith rainfall site.
4. The mountain torrent early warning method considering rainfall spatial heterogeneity as claimed in claim 2 or 3, wherein the formula for calculating the relative area of the equal flow time surface is as follows:
wherein r isi,jAnd the proportion of the area of the Thiessen polygon corresponding to the rainfall station i contained in the jth equal-flow time plane to the total area of the drainage basin is shown.
5. The mountain torrent early warning method considering rainfall spatial heterogeneity as claimed in any one of claims 2 to 4, wherein a surface average rainfall calculation formula of the equal flow time surface is as follows:
wherein R isjThe surface average rainfall of the jth equal-flow surface is shown.
6. The mountain torrent early warning method considering rainfall spatial heterogeneity as claimed in any one of claims 1 to 5, wherein a soil saturation S calculation formula is:
wherein, PaInfluence of rainfall in the early stages of flood peak occurrence, WmThe maximum soil moisture content in the drainage basin.
7. The mountain torrent early warning method considering rainfall spatial heterogeneity as claimed in any one of claims 1 to 6, wherein composite rainfall PsComprises the following steps:
8. the method as claimed in any one of claims 1 to 7, wherein the step of constructing the mountain torrent early warning model according to the above indexes in step S2 comprises the following steps:
01. data set D { (x)l,yl) 1, 2.., L } as input, yl1 as output; wherein x isl＝[Ps,S]，PsThe composite rainfall is represented by y which is 1 and represents an overtemperature, y which is 0 and represents no overtemperature, and L represents the number of actually measured historical peaks;
02. based on the classification principle of the support vector machine, the following objective function is obtained to enable the classification interval of the super-alarm flood and the non-super-alarm flood to be maximum:
wherein w ═ w1,w2]TOptimal hyperplane w for maximizing classification interval of hypersonic floods and non-hypersonic floodsTxl+ b is a normal vector of 0, b is a displacement term; c>0 is penalty parameter to minimize the number of misclassification points ξlThe relaxation variable is more than or equal to 0, so that the influence of outliers on the classification model is reduced;
03. solving the objective function by adopting a Lagrange multiplier method and a sequence minimum optimization algorithm to obtain an optimal classification hyperplane wTxlThe + b is the parameter w and b of 0, and the critical composite rainfall index P corresponding to different soil saturation degrees is obtainedcComprises the following steps:
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