CN112904458B - Hydrological forecasting method and system for super-seepage-full-storage mixed runoff yield mode - Google Patents
Hydrological forecasting method and system for super-seepage-full-storage mixed runoff yield mode Download PDFInfo
- Publication number
- CN112904458B CN112904458B CN202110104956.6A CN202110104956A CN112904458B CN 112904458 B CN112904458 B CN 112904458B CN 202110104956 A CN202110104956 A CN 202110104956A CN 112904458 B CN112904458 B CN 112904458B
- Authority
- CN
- China
- Prior art keywords
- flood
- drainage basin
- rainfall
- basin
- infiltration capacity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000013277 forecasting method Methods 0.000 title description 6
- 238000000034 method Methods 0.000 claims abstract description 102
- 230000008569 process Effects 0.000 claims abstract description 82
- 230000008595 infiltration Effects 0.000 claims abstract description 64
- 238000001764 infiltration Methods 0.000 claims abstract description 64
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 61
- 239000002689 soil Substances 0.000 claims abstract description 37
- 230000000630 rising effect Effects 0.000 claims abstract description 24
- 238000000746 purification Methods 0.000 claims abstract description 4
- 238000011156 evaluation Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- 238000001704 evaporation Methods 0.000 claims description 3
- 230000008020 evaporation Effects 0.000 claims description 3
- 230000002123 temporal effect Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 description 7
- 230000007547 defect Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000013316 zoning Methods 0.000 description 2
- KHOITXIGCFIULA-UHFFFAOYSA-N Alophen Chemical compound C1=CC(OC(=O)C)=CC=C1C(C=1N=CC=CC=1)C1=CC=C(OC(C)=O)C=C1 KHOITXIGCFIULA-UHFFFAOYSA-N 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/14—Rainfall or precipitation gauges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/24—Earth materials
- G01N33/246—Earth materials for water content
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Environmental & Geological Engineering (AREA)
- Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Remote Sensing (AREA)
- Medicinal Chemistry (AREA)
- Environmental Sciences (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geology (AREA)
- Biodiversity & Conservation Biology (AREA)
- Atmospheric Sciences (AREA)
- Hydrology & Water Resources (AREA)
- Food Science & Technology (AREA)
- Ecology (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a hydrologic prediction method and a hydrologic prediction system for a super-seepage-full-storage mixed runoff yield mode, which belong to the field of hydrologic prediction in hydrology, and comprise the following steps: calculating the rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to the early rainfall data and the rainfall process data of the corresponding flood; determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage capacity of the drainage basin, the stable infiltration capacity of the drainage basin, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve; calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the rainfall of the drainage basin surface; and substituting the rain purification process into the confluence unit line to obtain a flood process. Therefore, the method and the device optimize the problems of complexity and large calculation amount of the existing mixed runoff yield model, improve the flood forecasting precision, and have the advantages of wide application range and high fitting precision.
Description
Technical Field
The invention belongs to the field of hydrologic prediction in hydrology, and particularly relates to a hydrologic prediction method and a hydrologic prediction system for a super-seepage-full mixed runoff yield mode.
Background
The hydrologic forecast is a qualitative or quantitative prediction of the hydrologic state in a certain period in the future according to known information, wherein the research of the runoff generating mode is the core direction of the hydrologic forecast. At present, most hydrological models adopt a single full-productive flow mode or super-seepage productive flow mode productive flow structures, and have limited precision and larger uncertainty. The mixed production flow as a new production flow mode is expected to solve the problem of single production flow structure.
Currently, there are three common mixed birth flow modes, which are: a vertical mixed production flow mode, a compatible production flow mode and a VIC-3L mixed production flow mode. Compared with a single runoff yield mode, although the accuracy of the conventional mixed runoff yield forecast is improved, the defects of complex model, large calculation amount and strong uncertainty are still not solved.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a hydrologic forecasting method and a hydrologic forecasting system for an ultra-seepage-accumulation mixed runoff yield mode, and aims to solve the technical problems of complexity, large calculated amount and strong uncertainty of the conventional mixed runoff yield forecasting model.
To achieve the above object, according to one aspect of the present invention, there is provided a hydrologic prediction method for a super-osmotic-full mixed runoff yield mode, comprising the steps of:
(1) calculating the rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to the early rainfall data and the rainfall process data of the corresponding flood;
(2) determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage capacity of the drainage basin, the stable infiltration capacity of the drainage basin, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve;
(3) calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the rainfall of the drainage basin surface;
(4) and substituting the rain purification process into the confluence unit line to obtain a flood process.
Further, the rainfall data and rainfall process data corresponding to the flood in the step (1) in the earlier period comprise: hourly rainfall data, evaporation data, longitude and latitude data of each station and rainfall data of previous M days of rainfall of the rainfall station;
the calculating the rainfall of the watershed surface comprises the following steps: and dividing station weight ratios according to a Thiessen polygon method, and performing weight addition on the corresponding rainfall data of each station to obtain the rainfall of the drainage basin surface.
Further, the soil water content calculation formula of the initial stage of the flood process in the step (1) is as follows:
in the formula, Wj_0The soil water content of the initial stage of the flood process in day j; pjThe daily rainfall is j days; pa,j-1The rainfall is influenced for the day-ahead of j-1; n is the early rainfall days influencing the current runoff; k is a soil regression coefficient; when P is presenta,j>WmWhen is, Pa,j=WmWherein W ismThe maximum water storage capacity of the basin.
Further, in the step (2), the calculation formula of the infiltration capacity of the watershed at each time after the flood process occurs is as follows:
in the formula (f)tThe infiltration capacity of the watershed at the time t is satisfied with ft≥fc;fmThe maximum infiltration capacity of the drainage basin; f. ofcStabilizing the infiltration capacity for the drainage basin; wmThe maximum water storage capacity of the basin is obtained; wtWhen the soil water content of the drainage basin is t and t is 0, W0=Wj_0;TtDefault to 1 for the initial value of the number of the flood rising periods, and then adding 1 in each time period until the flood subsides; a is a constant coefficient.
Further, in the step (2), when the water level or the flow of the basin reservoir continuously rises for m hours and the rising amplitude reaches a threshold value, it is determined that the flood starts rising.
Further, after the step (4), the method further comprises: taking a flood peak target, a peak time target and a certainty target as evaluation indexes, and performing maximum infiltration capacity f in a convection domainmStable infiltration capacity of drainage basin fc、WmOptimizing the maximum water storage capacity and the constant coefficient a of the watershed so that the difference between the flood process obtained in the step (4) and the actual flood process is within an allowable range; wherein,
the flood peak target Obj1Expressed as:
the peak temporal target Obj2Expressed as:
the deterministic target Obj3Expressed as:
in the formula, Qobs,iIs the measured value of the flow; qsim,iThe flow prediction value is used; t isobs,iIs a peak reality measured value; t issim,,iThe peak current predicted value is obtained;the measured flow mean value is obtained; q'obs,iThe flood peak value of the actual measurement field is obtained; qs'im,iPredicting the flood value of the field; and N is the number of flood times.
According to another aspect of the present invention, there is provided a hydrologic prediction system for a mixed super-osmotic-full runoff yield mode, comprising:
the first calculation module is used for calculating rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to early rainfall data and rainfall process data of flood corresponding to the field times;
the second calculation module is used for determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage basin infiltration capacity, the stable drainage basin infiltration capacity, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve;
the third calculation module is used for calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the drainage basin surface rainfall;
and the flood process acquisition module is used for substituting the clean rain process into the confluence unit line to obtain a flood process.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
firstly, the soil water content of the initial stage of the flood process is calculated based on the early rainfall situation; then determining the drainage basin infiltration capacity at each moment after the flood process occurs according to the maximum drainage basin infiltration capacity, the stable drainage basin infiltration capacity, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content in the initial stage; and calculating the clean rain of the drainage basin by combining the rainfall of the drainage basin surface, and finally obtaining the flood process. Therefore, the problems of complexity and large calculation amount of the existing mixed runoff yield model are solved, the infiltration mechanism is explored, the runoff yield mode method is improved, the flood forecasting precision is improved, and the method has the advantages of wide application range and high fitting precision.
Drawings
FIG. 1 is a flow chart of a hydrological forecasting method for a super-osmotic-full mixed runoff yield mode according to an embodiment of the present invention;
FIG. 2 is a Thiessen polygonal zoning map of a zone of investigation of the present invention;
FIG. 3 is a diagram illustrating a selected flood process and its rainfall process according to an embodiment of the present invention;
FIG. 4 is a graph comparing measured rainfall to calculated net rainfall;
FIG. 5 is a graph of the infiltration capacity of a mixed super-infiltration-reservoir runoff formation model;
figure 6 is a comparison of simulated flood versus measured flood for each runoff yield mode.
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, a flow chart of a hydrologic prediction method for a super-osmotic-full mixed runoff yield mode provided by an embodiment of the present invention includes the following steps:
(1) calculating the rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to the early rainfall data and the rainfall process data of the corresponding flood;
specifically, before the step (1), collecting flood process data of each hydrological site in the river basin, and dividing the river basin into a plurality of sub-river basins by using a Thiessen polygon method; wherein, each hydrology website flood process data includes: flood of 2 years and above, hourly water level and flow data of corresponding flow stations, and station longitude and latitude data.
The step of calculating the rainfall of the watershed surface comprises the following steps: and dividing station weight ratios according to a Thiessen polygon method, and performing weight addition on the corresponding rainfall data of each station to obtain the rainfall of the drainage basin surface. Wherein, rainfall data and rainfall process data in earlier stage that correspond the flood of field include: hourly rainfall data of the rainfall stations, evaporation data, longitude and latitude data of each station and rainfall data of M days in the early period.
The formula for calculating the water content of the soil at the initial stage of the flood process is as follows:
in the formula, Wj_0The soil water content of the initial stage of the flood process in day j; pjThe daily rainfall is j days; pa,j-1The rainfall is influenced for the day-ahead of j-1; n is the early rainfall days influencing the current runoff; k is a soil regression coefficient; when P is presenta,j>WmWhen is, Pa,j=WmWherein W ismThe maximum water storage capacity of the basin.
(2) Determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage capacity of the drainage basin, the stable infiltration capacity of the drainage basin, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve;
specifically, according to the Horton runoff yield theory and the Dunne runoff yield theory, aiming at the super-osmotic runoff yield, the infiltration capacity f at the time t of the watershedtAt this moment, the water content W of the soiltIt is related. When the water content of the soil in the drainage basin is zero, the drainage basin infiltration capacity reaches the maximum value fmWhen the water content of the soil reaches the maximum water storage capacity Wm of the basin, the infiltration capacity reaches the minimum, namely the stable infiltration capacity f of the basinc. Accordingly, the watershed soil water content has a certain inverse relationship with its corresponding infiltration capacity, which can be given as the following expression:
through simple conversion, the formula (1) can be transformed into
In the formula, ft is the infiltration capacity of the watershed at the moment t; fm is the maximum infiltration capacity of the drainage basin; fc is stable infiltration capacity of a drainage basin; wmThe maximum water storage capacity of the basin is obtained; wtWhen the soil water content of the drainage basin is t and t is 0, W0=Wj_0。
However, with the continuation of the rainfall process and the increase of the duration of runoff production, considering the nonuniformity of the underlying surface of the drainage basin, the water content of the soil in a part of the area is increased to a full state in advance, at the moment, the whole infiltration amount of the drainage basin is gradually reduced, and if a calculation formula of the excess infiltration runoff is still adopted, the conditions of overlarge calculated infiltration amount and small forecast ground runoff can be caused, so that the flood control is adversely affected. Thus, the actual infiltration capacity f of the basintAlso rises with the flood for a time TtIn relation to this, as the rise duration increases,the basin full-storage area is continuously increased, and the corresponding infiltration capacity is continuously reduced until the full basin reaches a full-storage state. In contrast, for simplicity and convenience of engineering application, the present invention assumes a permeability ftRise with flood for time TtThere is a linear relationship between them. Considering the influence of the full-scale runoff on the net rain calculation, the calculation formula of the formula (2) is revised, and the concrete expression is as follows:
in the formula, TtThe initial value of the number of the time periods after the time t of the flood rises is defaulted to 1, and then 1 is added every time period until the flood subsides; a is a constant coefficient, and each drainage basin (different underlying surface characteristics) corresponds to different parameters.
(3) Calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the rainfall of the drainage basin surface;
(4) and substituting the rain purification process into the confluence unit line to obtain a flood process.
Further, after the step (4), the method further comprises the following steps: taking a flood peak target, a peak time target and a certainty target as evaluation indexes, and performing maximum infiltration capacity f in a convection domainmStable infiltration capacity of drainage basin fc、WmOptimizing the maximum water storage capacity and the constant coefficient a of the watershed so that the difference between the flood process obtained in the step (4) and the actual flood process is within an allowable range; wherein,
flood peak target Obj1Expressed as:
peak time target Obj2Expressed as:
deterministic target Obj3Is shown as:
In the formula, Qobs,iIs the measured value of the flow; qsim,iThe flow prediction value is used; t isobs,iIs a peak reality measured value; t issim,,iThe peak current predicted value is obtained;the measured flow mean value is obtained; q'obs,iThe flood peak value of the actual measurement field is obtained; q'sim,iPredicting the flood value of the field; and N is the number of flood times.
On the other hand, the invention also provides a hydrologic forecast system of the super-seepage-full mixed runoff yield mode, which comprises the following components:
the first calculation module is used for calculating rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to early rainfall data and rainfall process data of flood corresponding to the field times;
the second calculation module is used for determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage basin infiltration capacity, the stable drainage basin infiltration capacity, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve;
the third calculation module is used for calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the drainage basin surface rainfall;
and the flood process acquisition module is used for substituting the clean rain process into the confluence unit line to obtain a flood process.
The division of each module in the hydrological forecasting system in the super-infiltration-full storage mixed runoff yield mode is only used for illustration, and in other embodiments, the hydrological forecasting system in the super-infiltration-full storage mixed runoff yield mode can be divided into different modules as required to complete all or part of the functions of the hydrological forecasting system in the super-infiltration-full storage mixed runoff yield mode.
In order to more clearly show the purpose, structure and technical scheme of the invention, the invention is further described in detail by using the meizhou watershed and the attached drawings, and the specific implementation steps comprise:
(1) collecting the flood process extract data of each hydrological site above the mountainous point in the Muzhou drainage basin, and dividing the target drainage basin into a plurality of sub-drainage basins by using a Thiessen polygon method;
specifically, the area of the region above the Sharp mountain station of the Muzhou drainage basin is 1578km2There were 21 rainfall stations and one traffic station, and the region of investigation was a Thiessen polygon zoning as shown in FIG. 2.
(2) Collecting early rainfall data and rainfall process data corresponding to a field flood, and correspondingly processing the early rainfall data and the rainfall process data into surface rainfall data;
specifically, the example study was performed by taking the actual flood measured in 2016, month 1, day 28 to month 1, day 30, and the rainfall and flood process in the scene is shown in fig. 3.
(3) Calculating the soil water content of the initial stage of the flood process according to the early rainfall data;
specifically, the soil moisture content at the early stage of flood occurrence is shown in table 1 below.
Table 1 site flood earlier soil moisture content units (mm) for each site
(4) Determining the rising time of the flood according to the actually measured water level-flow relation curve;
specifically, as can be seen from fig. 3, the rising time is t-11.
(5) Calculating the net rain process of the watershed surface by using a mixed super-seepage-storage full runoff yield model;
specifically, the net rain event for the face calculated by the extracted runoff model is shown in FIG. 4 below, and the infiltration capacity curve for the extracted model is shown in FIG. 5 below.
(6) And substituting the clean rain process into the confluence unit line, simulating and calculating the flood process, and comparing and analyzing the flood process with the actual flood process.
Specifically, the flood process simulated by each runoff yield mode is shown in fig. 6, and through comparison with the actually measured flood process, each comparison index calculated value is shown in table 2 below.
TABLE 2 vertical mixed hyper-osmotic-storage full-productive flow model each index calculation value
The results of fig. 6 and table 2 show that the flood process simulated by the vertical hybrid hyper-osmotic-storage flood model is the closest to the actual flood process, with the best results. The flood peak relative error is-0.023%, the peak time error is-2 h, and the certainty coefficient 0.874, compared with the traditional single full-productive flow mode or super-seepage productive flow mode, the flood peak relative error of the mixed productive flow mode provided by the invention is smaller, the certainty coefficient is higher, and the harm of larger actual engineering risk caused by lower predicted flood peak in the traditional single productive flow mode is reduced. The time for simulating the flood peak is advanced by 2h compared with the actual time, enough time can be reserved for relevant defense measures in actual forecasting, and the method has certain actual engineering value.
In conclusion, the hydrologic forecasting method of the super-seepage-full mixed runoff yield mode is established, the problems that an existing mixed runoff yield model is complex and large in calculation amount are solved, the infiltration mechanism is explored, the runoff yield mode method is improved, the flood forecasting precision is improved, and the hydrologic forecasting method has the advantages of being wide in application range and high in fitting precision.
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 (5)
1. A hydrologic forecast method for a super-seepage-full mixed runoff yield mode is characterized by comprising the following steps:
(1) calculating the rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to the early rainfall data and the rainfall process data of the corresponding flood;
(2) determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage capacity of the drainage basin, the stable infiltration capacity of the drainage basin, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve;
the calculation formula of the infiltration capacity of the drainage basin at each moment after the flood process is generated is as follows:
in the formula (f)tThe infiltration capacity of the watershed at the time t is satisfied with ft≥fc;fmThe maximum infiltration capacity of the drainage basin; f. ofcStabilizing the infiltration capacity for the drainage basin; wmThe maximum water storage capacity of the basin is obtained; wtThe water content of the soil in the basin at the moment t; t istDefault to 1 for the initial value of the number of the flood rising periods, and then adding 1 in each time period until the flood subsides; a is a constant coefficient;
(3) calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the rainfall of the drainage basin surface;
(4) substituting the rain purification process into a confluence unit line to obtain a flood process;
(5) taking a flood peak target, a peak time target and a certainty target as evaluation indexes, and performing maximum infiltration capacity f in a convection domainmStable infiltration capacity of drainage basin fcMaximum water storage capacity W of basinmOptimizing the constant coefficient a so that the difference between the flood process obtained in the step (4) and the actual flood process is within an allowable range; wherein,
the flood peak target Obj1Expressed as:
the peak temporal target Obj2Expressed as:
the deterministic target Obj3Expressed as:
in the formula, Qobs,iIs the measured value of the flow; qsim,iThe flow prediction value is used; t isobs,iIs a peak reality measured value; t issim,,iThe peak current predicted value is obtained;the measured flow mean value is obtained; q'obs,iThe flood peak value of the actual measurement field is obtained; q'sim,iPredicting the flood value of the field; and N is the number of flood times.
2. The method of claim 1, wherein the rainfall events data and rainfall events data corresponding to the flood session in step (1) comprises: hourly rainfall data, evaporation data, longitude and latitude data of each station and rainfall data of previous M days of rainfall of the rainfall station;
the calculating the rainfall of the watershed surface comprises the following steps: and dividing station weight ratios according to a Thiessen polygon method, and performing weight addition on the corresponding rainfall data of each station to obtain the rainfall of the drainage basin surface.
3. The method according to claim 1 or 2, wherein the soil moisture content at the initial stage of the flooding process in step (1) is calculated as follows:
in the formula, Wj_0The soil water content of the initial stage of the flood process in day j; pjThe daily rainfall is j days; pa,j-1The rainfall is influenced for the day-ahead of j-1; n is the early rainfall days influencing the current runoff; k is a soil regression coefficient; when P is presenta,j>WmWhen is, Pa,j=WmWherein W ismThe maximum water storage capacity of the basin.
4. The method of claim 1, wherein in the step (2), when the reservoir level or flow of the basin continuously rises for m hours and the rising amplitude reaches a threshold value, it is determined that the flood starts rising.
5. A hydrologic prediction system for a super-osmotic-flooded mixed runoff yield mode, comprising:
the first calculation module is used for calculating rainfall of the drainage basin surface and the soil water content of the initial stage of the flood process according to early rainfall data and rainfall process data of flood corresponding to the field times;
the second calculation module is used for determining the drainage basin infiltration capacity at each moment after the flood process occurs based on the maximum drainage basin infiltration capacity, the stable drainage basin infiltration capacity, the maximum water storage capacity of the drainage basin, the flood rising moment and the soil water content of the initial stage; the flood rising time is determined by an actually measured water level-flow relation curve;
the calculation formula of the infiltration capacity of the drainage basin at each moment after the flood process is generated is as follows:
in the formula (f)tThe infiltration capacity of the watershed at the time t is satisfied with ft≥fc;fmMaximum infiltration capacity for drainage basin;fcStabilizing the infiltration capacity for the drainage basin; wmThe maximum water storage capacity of the basin is obtained; wtThe water content of the soil in the basin at the moment t; t istDefault to 1 for the initial value of the number of the flood rising periods, and then adding 1 in each time period until the flood subsides; a is a constant coefficient;
the third calculation module is used for calculating the rain clearing process of the drainage basin based on the drainage basin infiltration capacity at each moment and the drainage basin surface rainfall;
the flood process acquisition module is used for substituting the net rain process into the confluence unit line to obtain a flood process; and taking a flood peak target, a peak time target and a certainty target as evaluation indexes, and performing maximum infiltration capacity f on the drainage basinmStable infiltration capacity of drainage basin fcMaximum water storage capacity W of basinmOptimizing the constant coefficient a so that the difference between the obtained flood process and the actual flood process is within an allowable range; wherein,
the flood peak target Obj1Expressed as:
the peak temporal target Obj2Expressed as:
the deterministic target Obj3Expressed as:
in the formula, Qobs,iIs the measured value of the flow; qsim,iThe flow prediction value is used; t isobs,iIs a peak reality measured value; t issim,,iThe peak current predicted value is obtained;the measured flow mean value is obtained; q'obs,iThe flood peak value of the actual measurement field is obtained; q'sim,iPredicting the flood value of the field; and N is the number of flood times.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110104956.6A CN112904458B (en) | 2021-01-26 | 2021-01-26 | Hydrological forecasting method and system for super-seepage-full-storage mixed runoff yield mode |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110104956.6A CN112904458B (en) | 2021-01-26 | 2021-01-26 | Hydrological forecasting method and system for super-seepage-full-storage mixed runoff yield mode |
Publications (2)
Publication Number | Publication Date |
---|---|
CN112904458A CN112904458A (en) | 2021-06-04 |
CN112904458B true CN112904458B (en) | 2021-11-19 |
Family
ID=76120267
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110104956.6A Active CN112904458B (en) | 2021-01-26 | 2021-01-26 | Hydrological forecasting method and system for super-seepage-full-storage mixed runoff yield mode |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112904458B (en) |
Families Citing this family (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114240106B (en) * | 2021-12-06 | 2022-07-01 | 中国水利水电科学研究院 | Basin flood response similarity analysis method based on hydrologic data mining |
CN114943051B (en) * | 2022-05-16 | 2023-05-23 | 广东省水文局梅州水文分局 | Flood peak forecasting method based on comprehensive rainfall factors |
CN117687127B (en) * | 2023-12-07 | 2024-07-23 | 广东省水文局梅州水文分局 | Hydrologic forecasting method and system based on optimized super-seepage full-accumulation mixed flow production mode |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2000048755A1 (en) * | 1999-02-18 | 2000-08-24 | Shell Oil Company | Remediation of contaminated groundwater |
CN104090974A (en) * | 2014-07-18 | 2014-10-08 | 河海大学 | Dynamic data mining method and system of extension reservoir subsequent floods |
CN107220496A (en) * | 2017-05-26 | 2017-09-29 | 上海市气象灾害防御技术中心 | A kind of urban rainstorm waterlogging assesses modeling method |
CN108897940A (en) * | 2018-06-22 | 2018-11-27 | 中国科学院地理科学与资源研究所 | The unidirectional couplings method of hydrological distribution model and two-dimentional hydrodynamic model based on rectangular mesh |
-
2021
- 2021-01-26 CN CN202110104956.6A patent/CN112904458B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2000048755A1 (en) * | 1999-02-18 | 2000-08-24 | Shell Oil Company | Remediation of contaminated groundwater |
CN104090974A (en) * | 2014-07-18 | 2014-10-08 | 河海大学 | Dynamic data mining method and system of extension reservoir subsequent floods |
CN107220496A (en) * | 2017-05-26 | 2017-09-29 | 上海市气象灾害防御技术中心 | A kind of urban rainstorm waterlogging assesses modeling method |
CN108897940A (en) * | 2018-06-22 | 2018-11-27 | 中国科学院地理科学与资源研究所 | The unidirectional couplings method of hydrological distribution model and two-dimentional hydrodynamic model based on rectangular mesh |
Non-Patent Citations (1)
Title |
---|
垂向混合模型在湫水河洪水预报预警中的应用;李大洋等;《人民黄河》;20180630;第40卷(第6期);正文24-28页 * |
Also Published As
Publication number | Publication date |
---|---|
CN112904458A (en) | 2021-06-04 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN112904458B (en) | Hydrological forecasting method and system for super-seepage-full-storage mixed runoff yield mode | |
CN111582755B (en) | Mountain torrent disaster comprehensive risk dynamic assessment method based on multi-dimensional set information | |
Svensson et al. | Review of rainfall frequency estimation methods | |
CN114372685B (en) | Urban storm waterlogging risk assessment method based on SWMM model | |
CN112733337A (en) | Method for evaluating urban road traffic efficiency under influence of rainstorm and waterlogging | |
Wagner et al. | Impact of relict rock glaciers on spring and stream flow of alpine watersheds: Examples of the Niedere Tauern Range, Eastern Alps (Austria). | |
CN113435630B (en) | Basin hydrological forecasting method and system with self-adaptive runoff yield mode | |
CN116362419A (en) | Urban flood control early warning system and method | |
Noh et al. | Long‐Term Simulation of Daily Streamflow Using Radar Rainfall and the SWAT Model: A Case Study of the Gamcheon Basin of the Nakdong River, Korea | |
CN117436619A (en) | Cascade reservoir flood control reservoir capacity combined reservation method based on equivalent flood control effect | |
Bajracharya et al. | Effects of Urbanization on Storm Water Run-off: A Case Study of Kathmandu Metropolitan City, Nepal. | |
CN111680886A (en) | Waterlogging risk prediction method and system | |
Roelevink et al. | Flood forecasting system for the Maritsa and Tundzha Rivers | |
Jang et al. | A probabilistic model for real‐time flood warning based on deterministic flood inundation mapping | |
Yang et al. | Joint probability study of destructive factors related to the “Triad” phenomenon during typhoon events in the coastal regions: Taking Jiangsu Province as an example | |
Javadinejad et al. | Modeling the effects of climate change on probability of maximum rainfall and on variations in storm water in the Zayandeh Rud River | |
Teng et al. | Early warning index of flash flood disaster: a case study of Shuyuan watershed in Qufu City | |
Muleta et al. | Rainfall-Runoff Modeling and Hydrological Responses to the Projected Climate Change for Upper Baro Basin, Ethiopia | |
Fava et al. | Integration of information technology systems for flood forecasting with hybrid data sources | |
خلیلی et al. | The effects of forecasted precipitation amount on probable maximum precipitation and probable maximum flood parameters | |
CN111639627B (en) | Runoff control effect rapid evaluation method based on automatic identification technology | |
Hao et al. | Improvement and application research of the SRM in alpine regions | |
US20240256746A1 (en) | Scheduling method and system for operation of reservoirs to recharge freshwater for repelling saltwater intrusion under changing conditions | |
Luo et al. | Operational real-time flood forecasting under climate change impacts: The coffee model for coastal storm dominated watersheds in British Columbia | |
Doliso et al. | Comparative performance evaluation of HEC-HMS and SWAT models in stream flow simulation: The case of Bilate and Gidabo Watersheds, Ethiopia |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |