CN112561214B - Method and system for automatically identifying flood of field - Google Patents

Method and system for automatically identifying flood of field Download PDF

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CN112561214B
CN112561214B CN202110200096.6A CN202110200096A CN112561214B CN 112561214 B CN112561214 B CN 112561214B CN 202110200096 A CN202110200096 A CN 202110200096A CN 112561214 B CN112561214 B CN 112561214B
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李匡
刘可新
梁犁丽
吉海
吴恒卿
刘舒
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China Institute of Water Resources and Hydropower Research
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Abstract

The invention provides a method and a system for automatically identifying flood in a field, wherein the method comprises the following steps of obtaining hydrological information data in a continuous flood process: selecting continuous N elements from the hydrologic information data to form an array y (); searching elements with values larger than a threshold value in the array y (), recording the positions of the elements, and forming a peak value array by the elements meeting the conditions; screening peak values from the peak value array according to the distance, and reserving the peak value with a larger value; searching a starting position and an ending position of a process corresponding to the peak value; dividing the flood of the field from the continuous flood. The method and the system for automatically identifying the flood of the field time provided by the invention automatically identify the flood process of the field time by starting from the extreme value and the concave-convex property of the function and combining the limit conditions of the flood peak threshold value, the flood peak distance threshold value, the start-stop flow threshold value and the like.

Description

Method and system for automatically identifying flood of field
Technical Field
The invention relates to the technical field of flood prediction, in particular to a method and a system for automatically identifying flood in a field.
Background
Hydrologic observations are continuous and are generally analyzed and counted in units of years. Within a year, multiple floods may occur, and in practical applications, a field of flood needs to be extracted for use unit research and application. The field flood can be used for extracting data of flood elements in hydrological yearbook, researching field flood characteristics and the like. At present, the method for extracting the field flood from the continuous hydrological data is manual extraction, the method is to observe the starting time and the ending time of the field flood and extract by combining with the expert experience, and the efficiency is low.
The invention patent application with publication number CN109785979A discloses a method for defining a field flood rainfall runoff process, which comprehensively considers the rainfall process and the flow rising process of a basin outlet section when determining the starting time and the ending time of the flood rainfall runoff process and defining the rainfall runoff process through the starting time and the ending time. The method only provides a mathematical identification method of the peak flow, is suitable for flood with smooth and non-fluctuating flow, and cannot accurately identify the flood with larger flow fluctuation. In addition, no specific identification method is given for the initial time and the initial time of flood, manual judgment is still needed, and generally, the method is still manual identification essentially and is low in efficiency.
Disclosure of Invention
In order to solve the technical problems, the method and the system for automatically identifying the flood of the field, which are provided by the invention, are used for automatically identifying the flood process of the field by combining the limiting conditions such as a flood peak threshold, a flood peak distance threshold, a start-stop flow threshold and the like from the extreme value and the concave-convex property of a function.
The first purpose of the invention is to provide a method for automatically identifying flood in a field, which comprises the following steps of obtaining hydrologic information data of a continuous flood process:
step 1: selecting continuous N elements from the hydrologic information data to form an array y ();
step 2: searching elements with values larger than a threshold value in the array y (), recording the positions of the elements, and forming a peak value array by the elements meeting the conditions;
and step 3: screening peak values from the peak value array according to the distance, and reserving the peak value with a larger value;
and 4, step 4: searching a starting position and an ending position of a process corresponding to the peak value;
and 5: dividing the flood of the field from the continuous flood.
Preferably, the step 2 comprises the following sub-steps:
step 21: calculating a first order backward difference y' () of the array y ();
step 22: traverse y ' (), let y ' (i +1) = y ' (i) when y ' (i) >0 and y ' (i +1) =0,
1≦i≦N-2；
step 23: traversing y ' (), finding a peak value when y ' (i) >0, y ' (i +1) <0 and y (i) ≧ ypthres, recording the peak value to an array yp ' (), and recording the peak value position to an array ypIndex ' (), wherein ypthres is a peak value threshold, yp ' () is a peak value array, and ypIndex ' (j) is a peak value position array;
step 24: after the traversal is completed, the element numbers of yp ' () and ypIndex ' () are recorded as Np '.
In any of the above solutions, preferably, the step 3 includes the following sub-steps:
step 31: starting from the first element of yp ' (), calculating the position distance yd = abs (ypIndex ' (ii) -ypIndex ' (jj)), 1 ≦ ii ≦ Np ', ii ≦ jj ≦ Np ', respectively;
step 32: screening the position distance yd between the element and other elements;
step 33: the screened array of the number of the peak values is recorded as yp (), the array of the position of the peak values is recorded as ypIndex (), and the two arrays have the same number of elements and are recorded as Np.
In any of the above embodiments, preferably, the screening method is: when yd ≦ ydthres, then the larger peak is kept in the arrays yp () and ypIndex (), where ydthres is the distance threshold.
In any of the above schemes, preferably, the step 4 includes the following sub-steps:
step 41: calculating a five-point moving average array ya ();
step 42: calculating a second order backward difference ya' () of ya ();
step 43: calculating a corresponding start position yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjj = ypIndex (iii) as an initial position, searching forwards, wherein the value range of jjj is int (M/2) +1 and less than or equal to jjjj and less than or equal to ypIndex (iii), and when ya '' (jj) >0, ya '' (jj-1) =0 and y (jj) ≦ yvthres, finding the initial position, and making ybIndex (iii) = jj; wherein, ybIndex () is a start position array, yvthres is a start end threshold;
step 44: calculating the corresponding end position of yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjj = ypIndex (iii) as the initial position, searching backwards, wherein the value range of jjj is that ypIndex (iii) and less than or equal to jjjj and less than or equal to N- (int (M/2) +1), and when ya '' (jj) >0, ya '' (jj +1) =0 and y (jj) ≦ yvthres, finding the end position, and making yeIndex (iii) = jj; where yeIndex () is the end position array.
In any of the above schemes, it is preferable that the calculation formula of the five-point moving average array ya () is as follows:
Figure 914573DEST_PATH_IMAGE001
when in uset-int(M/2)When the ratio is less than or equal to 0, y is (t-int(M/2))Is noted as y (1), whent+int(M/2)When the value is more than or equal to N, y: (t+int (M/2)) As a result of the notation y (N),Mis a positive odd number
Figure 959890DEST_PATH_IMAGE002
In any of the above solutions, preferably, the step 5 includes the following sub-steps:
step 51: extracting continuous rainfall sequences and flow sequences of the equal time interval, respectively recording the continuous rainfall sequences and the flow sequences as P () and Q (), wherein the number of elements is N1;
step 52: searching the peak flow and the starting and ending positions of the corresponding process;
step 53: finding the rainfall peak value and the starting and ending position of the corresponding process;
step 54: and determining a flood starting position and a flood ending position.
In any of the above schemes, preferably, the step 52 includes calculating a flood peak Qp (), a flood peak position QpIndex (), a flow process starting position QbIndex (), a flow process ending position qendex (), and the number of elements is NQp according to the calculation methods in the steps 1 to 4.
In any of the above schemes, step 53 preferably includes calculating a rain peak Pp (), a rain peak position Pp index (), a rain process start position PbIndex (), a rain process end position PeIndex (), and the number of elements is NPp according to the calculation methods in steps 1 to 4.
In any of the above schemes, preferably, the calculation method of step 54 includes the following sub-steps:
step 541: setting the starting position and the ending position of each flood to be the same as the starting position and the ending position of the flow process;
step 542: and for each flood, finding the rainfall process closest to the flow process (judging according to the position of the flood peak and the position of the rain peak), judging whether the starting position of the rainfall process of the flood is before the starting position of the flow process, and if so, adjusting the starting position of the flood to be the starting position of the rainfall process.
The second purpose of the invention is to provide a system for automatically identifying the flood of a field, which comprises a data acquisition module and further comprises the following modules:
a peak determination module: the system is used for acquiring the peak value and the starting position and the ending position of the corresponding process from the array;
the field flood calculation module: for dividing the flood of a field from the continuous flood;
the system performs automatic identification of flood sessions according to the method described in the first object.
Preferably, the peak determination module work method includes the following steps:
step 1: selecting continuous N elements from the hydrologic information data to form an array y ();
step 2: searching elements with values larger than a threshold value in the array y (), recording the positions of the elements, and forming a peak value array by the elements meeting the conditions;
and step 3: screening peak values from the peak value array according to the distance, and reserving the peak value with a larger value;
and 4, step 4: and finding the starting position and the ending position of the process corresponding to the peak value.
In any of the above schemes, preferably, the step 2 includes the following sub-steps:
step 21: calculating a first order backward difference y' () of the array y ();
step 22: traverse y ' (), let y ' (i +1) = y ' (i) when y ' (i) >0 and y ' (i +1) =0,
1≦i≦N-2；
step 23: traversing y ' (), finding a peak value when y ' (i) >0, y ' (i +1) <0 and y (i) ≧ ypthres, recording the peak value to an array yp ' (), and recording the peak value position to an array ypIndex ' (), wherein ypthres is a peak value threshold, yp ' () is a peak value array, and ypIndex ' (j) is a peak value position array;
step 24: after the traversal is completed, the element numbers of yp ' () and ypIndex ' () are recorded as Np '.
In any of the above solutions, preferably, the step 3 includes the following sub-steps:
step 31: starting from the first element of yp ' (), calculating the position distance yd = abs (ypIndex ' (ii) -ypIndex ' (jj)), 1 ≦ ii ≦ Np ', ii ≦ jj ≦ Np ', respectively;
step 32: screening the position distance yd between the element and other elements;
step 33: the screened array of the number of the peak values is recorded as yp (), the array of the position of the peak values is recorded as ypIndex (), and the two arrays have the same number of elements and are recorded as Np.
In any of the above embodiments, preferably, the screening method is: when yd ≦ ydthres, then the larger peak is kept in the arrays yp () and ypIndex (), where ydthres is the distance threshold.
In any of the above schemes, preferably, the step 4 includes the following sub-steps:
step 41: calculating a five-point moving average array ya ();
step 42: calculating a second order backward difference ya' () of ya ();
step 43: calculating a corresponding start position yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjj = ypIndex (iii) as an initial position, searching forwards, wherein the value range of jjj is int (M/2) +1 and less than or equal to jjjj and less than or equal to ypIndex (iii), and when ya '' (jj) >0, ya '' (jj-1) =0 and y (jj) ≦ yvthres, finding the initial position, and making ybIndex (iii) = jj; wherein, ybIndex () is a start position array, yvthres is a start end threshold;
step 44: calculating the corresponding end position of yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjj = ypIndex (iii) as the initial position, searching backwards, wherein the value range of jjj is that ypIndex (iii) and less than or equal to jjjj and less than or equal to N- (int (M/2) +1), and when ya '' (jj) >0, ya '' (jj +1) =0 and y (jj) ≦ yvthres, finding the end position, and making yeIndex (iii) = jj; where yeIndex () is the end position array.
In any of the above schemes, it is preferable that the calculation formula of the five-point moving average array ya () is as follows:
Figure 636990DEST_PATH_IMAGE003
when in uset-int(M/2)When the ratio is less than or equal to 0, y is (t-int(M/2))Is noted as y (1), whent+int(M/2)When the value is more than or equal to N, y: (t+int (M/2)) As a result of the notation y (N),Mis a positive odd number.
In any of the above solutions, preferably, the step 5 includes the following sub-steps:
step 51: extracting continuous rainfall sequences and flow sequences of the equal time interval, respectively recording the continuous rainfall sequences and the flow sequences as P () and Q (), wherein the number of elements is N1;
step 52: searching the peak flow and the starting and ending positions of the corresponding process;
step 53: finding the rainfall peak value and the starting and ending position of the corresponding process;
step 54: and determining a flood starting position and a flood ending position.
In any of the above schemes, preferably, the step 52 includes calculating a flood peak Qp (), a flood peak position QpIndex (), a flow process starting position QbIndex (), a flow process ending position qendex (), and the number of elements is NQp according to the calculation methods in the steps 1 to 4.
In any of the above schemes, step 53 preferably includes calculating a rain peak Pp (), a rain peak position Pp index (), a rain process start position PbIndex (), a rain process end position PeIndex (), and the number of elements is NPp according to the calculation methods in steps 1 to 4.
In any of the above schemes, preferably, the calculation method of step 54 includes the following sub-steps:
step 541: setting the starting position and the ending position of each flood to be the same as the starting position and the ending position of the flow process;
step 542: and for each flood, finding the rainfall process closest to the flow process (judging according to the position of the flood peak and the position of the rain peak), judging whether the starting position of the rainfall process of the flood is before the starting position of the flow process, and if so, adjusting the starting position of the flood to be the starting position of the rainfall process.
The invention provides a method and a system for automatically identifying field flood, which can accurately identify field flood in a continuous flood process, including single-peak flood and multi-peak flood. Compared with a manual method, the method has higher efficiency and equal accuracy to the manual extraction method.
Drawings
Fig. 1 is a flow chart of a preferred embodiment of a method of automatically identifying session floods in accordance with the present invention.
Fig. 2 is a block diagram of a preferred embodiment of the system for automatically identifying session floods in accordance with the present invention.
Fig. 3 is a schematic diagram of the results of an embodiment of flood forecasting according to the method of automatically identifying session floods of the present invention.
Fig. 4 is a flowchart of an embodiment of a threshold determination method of the method of automatically identifying session floods according to the present invention.
Fig. 5 is a flow chart of another preferred embodiment of a method of automatically identifying session floods in accordance with the present invention.
Detailed Description
The invention is further illustrated with reference to the figures and the specific examples.
Example one
As shown in fig. 1 and 2, in a method for automatically identifying a flood in a field, step 1000 is executed, and a data obtaining module 200 obtains hydrological information data of a continuous flood process.
In step 1100, the peak determining module 210 selects N consecutive elements from the hydrologic information data to form an array y ().
Executing step 1200, the peak determining module 210 finds the element whose value is greater than the threshold in the array y (), records the position of the element, and combines the elements meeting the condition into a peak array. The method comprises the following substeps: step 1210 is executed to calculate a first order backward difference y' () of the array y (). Step 1220 is executed to traverse y ' (), and when y ' (i) >0 and y ' (i +1) =0, let y ' (i +1) = y ' (i), 1 ≦ i ≦ N-2. Step 1230 is executed to traverse y ' (), and when y ' (i) >0, y ' (i +1) <0, and y (i) ≧ ypthres, a peak is found and recorded to array yp ' (), and a peak position is recorded to array yplndex ' (, where ypthres is a peak threshold, yp ' () is a peak array, and yplndex ' (j) is a peak position array. Step 1240 is executed, and after the traversal is completed, the number of the elements yp ' () and ypIndex ' () is recorded as Np '.
In step 1300, the peak determining module 210 selects a peak from the peak array according to the distance, and retains a peak with a larger value. The method comprises the following substeps: step 1310 is executed to calculate the position distance yd = abs (ypIndex ' (ii) -ypIndex ' (jj)), from the first element of yp ' (), 1 ≦ ii ≦ Np ', ii ≦ jj ≦ Np ', respectively. Step 1320 is executed, and the position distance yd between the position distance yd and other elements is screened, wherein the screening method comprises the following steps: when yd ≦ ydthres, then the larger peak is kept in the arrays yp () and ypIndex (), where ydthres is the distance threshold. Step 1330 is executed, the filtered array of the number of the peak values is marked as yp (), the array of the position of the peak values is marked as ypIndex (), and the two arrays have the same number of elements and are marked as Np.
Step 1400 is executed, and the peak determining module 210 finds the starting position and the ending position of the process corresponding to the peak. The method comprises the following substeps: executing step 1410, 1 to calculate the five-point moving average array ya () of y (), the calculation formula of the five-point moving average array ya () is as follows:
Figure 513679DEST_PATH_IMAGE003
when in uset-int(M/2)When the ratio is less than or equal to 0, y is (t-int(M/2))Is noted as y (1), whent+int(M/2)When the value is more than or equal to N, y: (t+int (M/2)) As a result of the notation y (N),Mis a positive odd number.
Step 1420 is executed to compute the second order backward difference ya' ().
Executing step 1430, calculating a start position corresponding to yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjjj = ypIndex (iii) as the start position, searching forward, wherein the value range of jjj is int (M/2) +1 and less than or equal to jjjjj and less than or equal to ypIndex (iii), when ya '' (jj) >0, ya '' (jj-1) =0 and y (jj) ≦ yvthres, finding the start position, and making ybIndex (iii) = jj; where ybIndex () is the start position array and yvthres is the start end threshold.
Executing step 1440, calculating an end position corresponding to yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjjj = ypIndex (iii) as a starting position, searching backwards, wherein the value range of jjj is ypIndex (iii) and less than or equal to jjjj and less than or equal to N- (int (M/2) +1), and when ya "(jjj) >0, ya" (jjj +1) =0, and y (jj) ≦ yvthres, finding the end position, and making yeIndex (iii) = jj; where yeIndex () is the end position array.
In step 1500, the session flood calculation module 220 divides the session flood from the continuous flood. The method comprises the following substeps: step 1510 is executed to extract a continuous rainfall sequence and a traffic sequence of the equal time interval, which are respectively marked as P () and Q (), and the number of elements is N1.
And executing a step 1520, finding the peak flow and the starting and ending position of the corresponding process, and calculating the peak Qp (), the peak position QpIndex (), the starting position qblndex () of the flow process, the ending position QeIndex () of the flow process, and the number of elements which are NQp according to the calculation methods from the step 1000 to the step 1400.
And a step 1530 is executed, the rainfall peak value and the start and end position of the corresponding process are found, and the rainfall peak Pp (), the rainfall process start position PbIndex (), the rainfall process end position PeIndex (), the number of elements is NPp, are calculated according to the calculation methods from the step 1000 to the step 1400.
Step 1540 is performed to determine the flood start and end locations. The method comprises the following substeps: step 1541 is performed to set the start and end positions of each flood to be the same as the start and end positions of the flow process. Step 1542 is executed, for each flood, finding the rainfall process closest to the flow process (judged by the flood peak position and the rain peak position), judging whether the start position of the rainfall process of the flood is before the start position of the flow process, if so, adjusting the start position of the flood to be the start position of the rainfall process.
Example two
Principle of method
A typical flooding process of a natural watershed is shown in fig. 3, and includes a rainfall process and a flow process. The rainfall process starts at time D and ends at time E. The flow process starts from the moment A, the moment B ends, the starting stage is stable base flow, along with the development of rainfall, the flow rises from the moment A, the moment C reaches a peak, then the flow begins to subside, and the flow subsides to the base flow at the moment B. From D to B, a complete flood process is recorded. The flood process may be determined by first determining a flow process time A, B, then determining a rainfall process time D, E, and finally determining a flood process time D, B.
The starting point and the stopping point of the flood can be determined by using the extreme value and the concave-convex property of the function. The principle is as follows: function Q = f (for flow process)t) It is shown that,tis time. Function is ast= C maximum, when f (C) first derivative on left>0, right first derivative<0; to the left of the flow initiation point, i.e.t<When A, the function has no unevenness, f ″ (t) =0, whent= A, the function becomes a concave function, f ″ (A)>0; at the end point of the flow, i.e.tWhen = B, the function is a concave function, f ″ (B)>0, right side of the flow end point, i.e. whent>B, the function has no concave-convex, f ″ (t)=0。
When the start and stop time of the flow process is determined, the position C of the flood peak is determined, then the start point A is determined forwards, and the end point B is determined backwards. The rainfall process is similar to the flow process data and is a set of time series data with a rolling process, and similarly the start and stop points D, E of the rainfall process can be determined. In the calculation, since the flow and the rainfall are discrete time series, the difference is used for replacing the derivative for calculation.
Setting a flood peak threshold value to select floods with different magnitudes when the floods are identified; setting a flood peak time distance threshold value for the peak-recovery flood, and only reserving the flood with larger flood peak within the threshold value; setting a starting flow threshold and an ending flow threshold, and determining the starting time and the ending time of a flow process by combining with the functional concave-convex; and setting a rain peak threshold to identify the rainfall process. The setting of the threshold is determined by observing, analyzing the graph and data of the continuous hydrological process.
Step two, calculating
1. Obtaining the peak value and the start and end position of the corresponding process from the array
The calculation steps for obtaining the peak values in the array and the start and end positions of the peak value corresponding process are as follows:
(1) data preparation
A set of data having a smooth and undulating process is prepared. The number of elements is N and is marked as array y ().
(2) Finding peak values
The purpose is as follows: finding the peak value whose value is greater than the threshold value in the array, and recording the position of the peak value.
Inputting: y (), threshold value ypthres
And (3) outputting: a peak array yp ' (), a peak position array ypIndex ' (), a peak number Np '
A calculation step:
1) calculating a first order backward difference y' () of y ();
2) go through y '(), when y' ((m))i)>0、y’(i(ii) when +1) =0, let y =0i+1)=y’(i)，1≤i≤N-2；
3) Go through y '(), when y' ((m))i)>0、y’(i+1)<0、y(i) When the value is larger than or equal to ypthres, a peak value is found and recorded to an array yp '(), and the position of the peak value is recorded to an array ypIndex' (). After the traversal is completed, the element numbers of yp ' () and ypIndex ' () are recorded as Np '.
The purpose of step 2) in the above steps is to process the situation that a plurality of continuous identical peaks exist in the data, and the peak can be found at the last point through processing.
(3) Screening peaks according to distance
The purpose is as follows: and screening peaks from the peak array yp' (), and reserving peaks with larger values.
Inputting: yp ' (), ypIndex ' (), Np ', distance threshold, ydthres
And (3) outputting: the peak value array yp (), the peak value position array ypIndex (), and the peak value element number Np
A calculation step:
starting from the first element of yp ' (), calculating the position distance yd = abs (ypIndex ' (ii) -ypIndex ' (jj)), 1 ≦ ii ≦ Np ', ii ≦ jj ≦ Np ', respectively, and if yd is not more than ydthres, retaining the larger peak and its position in the arrays yp () and ypIndex (); the number of peaks after screening was designated as Np.
(4) Finding start and end positions
The purpose is as follows: finding the start and end positions of the peak correspondence process
Inputting: y (), N, yp (), ypIndex (), Np, and threshold value yvthres;
and (3) outputting: the start position array ybIndex (); end position array yeIndex ();
a calculation step:
1) the actually observed flow sequence data has small oscillation in the stationary phase, and can be smoother through the calculation of the moving average, so that the searching of the starting point and the stopping point is facilitated. And calculating an M-point moving average array of y (), which is denoted as ya (), wherein the calculation formula is as follows:
Figure 867300DEST_PATH_IMAGE003
when in uset-int(M/2)When the ratio is less than or equal to 0, y is (t-int(M/2))Is noted as y (1), whent+int(M/2)When the value is more than or equal to N, y: (t+int (M/2)) As a result of the notation y (N),Mthe number of the data is positive and odd, and the data is determined according to the intensity of data oscillation during actual calculation;
2) calculating a second order backward difference ya' () of ya (), the calculated value retaining 2 decimal places;
3) calculate yp: (i) Corresponding start position ybIndex (i)，1≤iNot more than Np. Order toj=ypIndex(i) The starting position is searched forward,jthe value range of (b) is int (M/2) +1 ≦j≤ypIndex(i) When ya' < x >j)>0，ya’’(j-1)=0，y(j) When yvthres is less than or equal to yvthres, find the starting position and let ybIndex (i)=j；
4) Calculate yp: (i) Corresponding end position yeIndex (i)，1≤iNot more than Np. Order toj=ypIndex(i) The starting position is searched backwards,jthe value range of (A) is ypIndex (C)i)≤jN- (int (M/2) +1), when ya ″ (M/2) +1)j)>0，ya’’(j+1)=0，y(j) When yvthres is less than or equal to yvthres, find the ending position, let yeIndex (i)=j。
2. Dividing field flood from continuous flood
(1) Data preparation
Preparing continuous rainfall sequence and flow sequence of equal time interval, and respectively recording as P () and Q (), wherein the number of elements is N1;
(2) finding flood peak and start and end position of corresponding process
Inputting: a flow sequence group Q () and the number N of elements; peak flood threshold Qpthres, peak separation threshold Qpdist, and start-stop flow threshold Qvthres.
And (3) outputting: and (3) calculating a flood peak Qp (), a flood peak position QpIndex (), a flow process starting position QbIndex (), a flow process ending position QeIndex (), and recording the number of elements as NQp according to the calculation steps in the step 1.
(3) Finding the rainfall peak and the start and end position of the corresponding process
Inputting: a rainfall sequence group P () and the number N of elements; a rain peak threshold value Ppthres, a rain peak pitch threshold value Ppdist, and a start and stop rainfall threshold value Pvthres.
And (3) outputting: and (3) calculating a rain peak Pp (), a rain peak position PpIndex (), a rain process starting position PbIndex (), a rain process ending position PeIndex (), and recording the number of elements as NPp according to the calculation steps in the step 1.
(4) Determining flood start and end locations
The purpose is as follows: the beginning and ending positions of each flood are determined in connection with the flow process and the rainfall process.
Inputting: a flood peak position QpIndex (), a flow start position QbIndex (), a flow end position qendex (); a rain peak position PpIndex (), a rain amount start position PbIndex (), a rain amount end position PeIndex ();
and (3) outputting: flood start position FbIndex (), end position FeIndex ()
A calculation step:
1) setting the starting position and the ending position of each flood to be the same as the starting position and the ending position of the flow process;
2) and for each field flood, finding the nearest rainfall process (judged by the flood peak position and the rain peak position) before the flow process, judging whether the start position of the rainfall process of the field is before the start position of the flow process, and if so, adjusting the start position of the flood to be the start position of the rainfall process.
The invention provides a method for automatically identifying flood in a field, which can identify flood peaks and peak occurrence time, identify the start and end time of a flow process corresponding to each flood peak, identify the start and end time of a rainfall process for forming flood, and finally determine the flood process by combining the rainfall process, wherein the flood process comprises start and end time, flood peak flow and peak occurrence time. Particularly, the method can identify single peak flood and multi-peak flood, and has strong adaptability. The method can automatically identify the flood process only by preparing continuous rainfall and flow processes and inputting related threshold values, and has high work automation degree and small work load. Compared with the current mainstream manual identification method, the method can greatly improve the identification efficiency on the premise of ensuring the identification precision.
EXAMPLE III
The hydrological process of the Fujian Shaxi flood land hydrological station 2015-1-10: 00-12-3123: 00 is shown in FIG. 4. The flow rate sequence and the rainfall sequence are represented by Q (), P (), respectively, the period length is 1h, and the number of elements N = 8760. Flood peak in sequence is greater than 400m3The flood field of/s is 5 fields in total.
The purpose is to sort out the flood peak larger than 400m3Flood/s, so set the flood peak threshold Qpthres =400m3S; wherein, the 4 th field and the 5 th field have longer duration, are complex peak floods, observe and analyze the interval between complex peak floods and peak not to exceed 72h, and set the peak interval Qpdist =72 h; observing the analysis graph, and setting a start-stop flow threshold value Qvthres =100m3And s. The flow process in the stationary phase has certain fluctuation and needs to be carried outThe data is smoothed, and the number of data moving average points M is set to 5.
Observing the rainfall process, the peak value of the peak-producing rain is more than 5mm, so that a rain peak threshold value Ppthres =5mm is set, the rain peak pitch is the same as the flood peak pitch, Ppdist =24 time period, the start and stop rainfall threshold value Pvthres =0mm is set, and the rainfall data process does not need to carry out sliding average.
The identified flow process has 5 fields and the rainfall process has 42 fields. The flow process and the rainfall process are integrated, the identified flood process is 5 fields in total, flood peak and start-stop information are shown in table 1, and a flood process graph of each field is shown in fig. 5.
Figure 711497DEST_PATH_IMAGE005
Table 1 flood process information table
For a better understanding of the present invention, the foregoing detailed description has been given in conjunction with specific embodiments thereof, but not with the intention of limiting the invention thereto. Any simple modifications of the above embodiments according to the technical essence of the present invention still fall within the scope of the technical solution of the present invention. In the present specification, each embodiment is described with emphasis on differences from other embodiments, and the same or similar parts between the respective embodiments may be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

Claims (5)

1. A method for automatically identifying flood in field includes acquiring hydrologic information data of continuous flood process, and is characterized by also including the following steps:
step 1: selecting continuous N elements from the hydrologic information data to form an array y ();
step 2: finding the elements with the values larger than the threshold value in the array y (), recording the positions of the elements, and forming a peak value array by the elements meeting the conditions, wherein the method comprises the following substeps:
step 21: calculating a first order backward difference y' () of the array y ();
step 22: traversing y ' (), when y ' (i) >0 and y ' (i +1) ═ 0, let y ' (i +1) ≦ y ' (i), 1 ≦ i ≦ N-2;
step 23: traversing y ' (), finding a peak value when y ' (i) >0, y ' (i +1) <0 and y (i) ≧ ypthres, recording the peak value to an array yp ' (), and recording the peak value position to an array ypIndex ' (), wherein ypthres is a peak value threshold, yp ' () is a peak value array, and ypIndex ' (j) is a peak value position array;
step 24: after the traversal is completed, the element numbers of yp ' () and ypIndex ' () are recorded as Np ';
and step 3: screening peaks from the peak array according to the distance, and reserving peaks with larger values, wherein the method comprises the following substeps:
step 31: starting from the first element of yp ' (), calculating the position distance yd from other elements by abs (ypIndex ' (ii) -ypIndex ' (jj)), 1 ≦ ii ≦ Np ', ii ≦ jj ≦ Np ', respectively;
step 32: screening the position distance yd between the position distance yd and other elements, and when yd is less than or equal to ydthres, keeping a larger peak value to arrays yp () and ypIndex ();
step 33: the screened peak number array is recorded as yp (), the peak position array is recorded as ypIndex (), the number of elements of the two arrays is the same and is recorded as Np; and 4, step 4: finding the starting position and the ending position of the process corresponding to the peak value comprises the following substeps:
step 41: calculating a five-point moving average array ya () of y (), the calculation formula of the five-point moving average array ya () is as follows:
Figure FDA0003057722810000011
when t-int (M/2) is less than or equal to 0, y (t-int (M/2)) is recorded as y (1), when t + int (M/2) is more than or equal to N, y (t + int (M/2)) is recorded as y (N), M is a positive odd number
Step 42: calculating a second order backward difference ya "() of ya ();
step 43: calculating a corresponding start position yp (iii), wherein iii is more than or equal to 1 and less than or equal to Np, making jjj ═ ypIndex (iii) as an initial position, searching forward, wherein the value range of jjj is int (M/2) +1 and less than or equal to jjjj and less than or equal to ypIndex (iii), when ya (jjj) >0, ya (jj-1) is 0 and y (jj) is less than or equal to yvthres, finding the initial position, and making ybIndex (iii) and jj; wherein, ybIndex () is a start position array, yvthres is a start end threshold;
step 44: calculating an end position corresponding to yp (iii), wherein iii is not less than 1 and not more than Np, making jjjj ═ ypIndex (iii) as an initial position, searching backwards, wherein the value range of jjj is ypIndex (iii) and not more than jjj ≤ N- (int (M/2) +1), and when ya "(jjj) >0, ya" (jj +1) is 0 and y (jj) ≦ yvthres, finding the end position, and making yeIndex (iii) and jj; wherein yeIndex () is the end position array;
and 5: dividing the flood of the field from the continuous flood.
2. Method for automatically identifying session floods according to claim 1, characterized in that said step 5 comprises the following sub-steps:
step 51: extracting continuous rainfall sequences and flow sequences of the equal time interval, respectively recording the continuous rainfall sequences and the flow sequences as P () and Q (), wherein the number of elements is N1;
step 52: searching the peak flow and the starting and ending positions of the corresponding process;
step 53: finding the rainfall peak value and the starting and ending position of the corresponding process;
step 54: and determining a flood starting position and a flood ending position.
3. The method of automatically identifying a lot of flood as claimed in claim 2, wherein said step 52 includes calculating the flood peak Qp () according to the calculation method of said steps 1 to 4, the flood peak position QpIndex (), the flow process start position QbIndex (), the flow process end position qendex (), and the number of elements are NQp.
4. The method of automatically identifying a lot flood of claim 3, wherein step 53 includes calculating a rain peak Pp (), a rain peak position Pp index (), a rain process start position PbIndex (), a rain process end position PeIndex (), and the number of elements is NPp according to the calculation methods of the steps 1 to 4.
5. The system for automatically identifying the flood of the field comprises a data acquisition module, and is characterized by further comprising the following modules:
a peak determination module: the system is used for acquiring the peak value and the starting position and the ending position of the corresponding process from the array;
the field flood calculation module: for dividing the flood of a field from the continuous flood;
the system performs automatic identification of flood sessions according to the method of claim 1.
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