CN117953648A - Mountain torrent disaster early warning method and system based on distributed hydrologic model - Google Patents
Mountain torrent disaster early warning method and system based on distributed hydrologic model Download PDFInfo
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Abstract
The invention discloses a mountain torrent disaster early warning method based on a distributed hydrological model, which comprises the following steps: constructing a distributed watershed hydrological model comprising a plurality of sub-watershed correlations based on geological data and historical data in the watershed; collecting real-time meteorological data, and simulating a converging evolution process of a sub-river basin where a disaster prevention object in the river basin is located by combining a distributed river basin hydrological model; according to the simulated convergence evolution process, calculating to obtain the mountain torrent risk grade of the disaster prevention object by combining the risk assessment index of the preset disaster prevention object; a mountain torrent disaster early warning system based on the distributed hydrological model is also disclosed. According to the invention, a distributed watershed hydrological model is adopted, a sub-watershed is used as a calculation unit, the confluence evolution process simulation in the watershed is realized, in addition to the real-time rainfall, the real-time terrain data is combined in the early warning analysis process, a mountain torrent early warning mode combining rainfall, flow and water level is improved, and the result of mountain torrent early warning is more accurate.
Description
Technical Field
The invention relates to the technical field of flood early warning, in particular to a mountain torrent disaster early warning method and system based on a distributed hydrological model.
Background
The mountain torrent disaster has strong burst property, multiple supervision surfaces and large forecasting difficulty, various data of mountain torrent disaster influence factors relate to a plurality of different functional departments, such as a meteorological department, a water conservancy department, a natural resource planning department and the like, and the mountain torrent disaster influence factor data checked among the departments are not communicated and cannot be analyzed together to carry out mountain torrent early warning. At present, the acquisition source of the mountain torrent disaster hidden danger data is relatively single, only rainfall information is adopted for forecasting and early warning, and in the actual application process, the problem that the rainfall information is not matched with the water level information often exists, and the problems that the rainfall forecasting reaches the transfer condition but the water level does not reach the transfer condition or the water level is over-warned and the like often exist. Therefore, the analysis and prediction based on rainfall information is difficult to realize accurate early warning of mountain torrent disasters, and the early warning precision is low.
The method for early warning rainfall, storm and mountain floods based on real-time accumulated rainfall and rainfall runoff response disclosed in Chinese patent literature is disclosed as CN109902395B and has publication date of 2020-08-18, and comprises the steps of (1) selecting a small-river-area river reach of a mountain area needing to be subjected to early warning of the storm and mountain floods as a target river reach, and collecting flood characteristic data of n times of storm and mountain floods of the target river reach and rainfall characteristic data of corresponding times of storm and mountain floods of the n times of mountain floods; determining a flood steep time point of each scene of storm mountain torrents according to flood characteristic data; (2) analyzing n times of storm mountain floods; (3) Determining a critical accumulated rainfall index for giving out a storm mountain torrent early warning; (4) ① when heavy rain occurs on the upstream of a target river reach, collecting period rainfall data of the scene heavy rain, and calculating accumulated rainfall from the beginning of rainfall to the time point of collecting rainfall data of different periods in real time; ② And when the accumulated rainfall in the step ① reaches a critical accumulated rainfall index for sending out the storm torrent warning, immediately sending out the storm torrent warning. The technology still only carries out mountain torrent early warning analysis based on a single rainfall data index, does not consider the influence of actual topography factors, under-pad conditions and other mountain torrent disaster influencing factors, and is difficult to realize accurate early warning of mountain torrent disasters, and the early warning precision is low.
Disclosure of Invention
The invention provides a mountain torrent disaster early warning method and a mountain torrent disaster early warning system based on a distributed hydrological model, which are used for realizing confluence evolution process simulation in a river basin by taking a sub-river basin as a calculation unit and combining actual topography data in addition to real-time rainfall in the early warning analysis process, so that the mountain torrent disaster early warning method and the mountain torrent disaster early warning system are improved to be more accurate aiming at mountain torrent early warning results by combining rainfall, flow and water level in addition to the real-time rainfall in the early warning analysis process.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
A mountain torrent disaster early warning method based on a distributed hydrological model comprises the following steps:
Constructing a distributed watershed hydrological model comprising a plurality of sub-watershed correlations based on geological data and historical data in the watershed; collecting real-time meteorological data, and simulating a converging evolution process of a sub-river basin where a disaster prevention object in the river basin is located by combining a distributed river basin hydrological model;
and according to the simulated convergence evolution process, calculating the mountain torrent risk grade of the disaster prevention object by combining the risk assessment index of the preset disaster prevention object.
In the invention, the critical rainfall threshold value or the early warning water level and the flow are determined essentially according to the thought of rainfall, flow and water level; according to topological relation and hydraulic connection among all sub-watersheds in a watershed, establishing a correlation, endowing all calculation modules and parameters to corresponding sub-watersheds, constructing a distributed watershed hydrologic model, and analyzing the mountain torrent disasters according to the processes of full-watershed-sub-watershed division-distributed grid division-grid evaporation distribution calculation, stream production calculation-river network confluence calculation, confluence evolution, flow early warning, rainfall early warning, water level early warning and mountain torrent disaster early warning.
Preferably, the construction process of the distributed watershed hydrological model comprises the following steps:
sub-drainage basin division and grid unit division are carried out on the drainage basins according to geological data, and a drainage mechanism is determined; calculating evapotranspiration data of each sub-drainage basin grid unit;
Determining a flow model algorithm according to a flow mechanism, and calculating flow data of grid units of the sub-flow areas;
and after the stream data of each sub-drainage basin grid unit are converged, simulating a convergence evolution process by a motion wave method.
The river basin is formed by hillsides responding to precipitation, the construction of the distributed river basin hydrologic model is to analyze precipitation of specific topography to form a mechanism of generating flow, and the corresponding relation between hillside landform sub-river basin grid units and the precipitation mechanism is established based on geological data (topography, land utilization, vegetation coverage, soil types and the like) in the river basin; combining with a modularized hydrologic model construction method, determining a sub-basin grid unit yield calculation method based on the dominant yield characteristics of the hillside landform sub-basin grid unit, comprehensively obtaining the yield of the sub-basin, and converging the yield of each sub-basin to the outlet of the basin according to the topological serial relation of the sub-basin by utilizing the slope and the river channel converging process to complete the simulation of the converging evolution process.
Preferably, the calculation of the evapotranspiration data adopts a three-layer evaporation model, and parameters of the three-layer evaporation model are calculated based on historical meteorological data and historical hydrological data;
The runoff model algorithm selects a soil humidity method to simulate a canopy interception layer, a ground surface depression filling layer, a soil section layer, a shallow underground aquifer and a deep underground aquifer, and calculates runoff data by real-time meteorological data and evapotranspiration data.
The three-layer evaporation model belongs to an existing evapotranspiration data calculation method, and parameters of the three-layer evaporation model are optimized and debugged based on historical meteorological data and historical hydrological data of a river basin to obtain an evapotranspiration calculation model suitable for the river basin; the runoff generation refers to the process that precipitation on a watershed generates net rain through plant interception, depression filling, infiltration, evaporation and the like, and generates various runoff components, and different runoff model algorithms can be selected according to the runoff generation mechanism of a specific sub-watershed, including but not limited to a soil humidity method.
Preferably, the simulating the convergence evolution process by a motion wave method comprises:
Wherein I 0 is the water surface ratio drop; Along-the-way variation of the flood wave propagation flow; /(I) Is the change of the cross section area of the river channel along with the time; v is the average flow velocity of the section; m 1 is the rough coefficient of the river channel; r is the hydraulic radius of the section; q is the average water supply intensity of the slope surfaces at two sides of the river channel.
The motion wave method simulation confluence evolution process is carried out by solving a finite difference continuity equation and a simplified momentum equation, and the required data comprise the section shape of a river channel, the size of the river channel, a slope coefficient, the length, a Manning coefficient and the like, wherein physical parameters such as the size and the like can be extracted through a map, and the Manning coefficient can be estimated through different land utilization types; besides the motion wave simulation method, a Mastink root method, a hysteresis algorithm and the like can be adopted to simulate the convergence evolution process according to the requirement.
Preferably, the real-time weather data includes real-time rainfall data, and the process of converting the rainfall into the surface rainfall of the sub-watershed includes:
constructing Thiessen polygons of each rainfall station according to the space positions of the rainfall stations in the sub-watershed, and determining the control area of each rainfall station; and taking the ratio of the control area of each rainfall station to the area of the sub-drainage basin as the corresponding weight of the rainfall station, and carrying out weighted calculation on the point rainfall to obtain the face rainfall of the sub-drainage basin.
The real-time rainfall data substituted into the distributed watershed hydrological model for simulating the confluence evolution process are surface rainfall data, which means average rainfall on the area of a certain watershed; the rainfall detected by the rainfall station or other rainfall testing devices is the rainfall at a specific place, and the rainfall cannot accurately represent the rainfall condition in the drainage basin range due to the height non-uniformity of rainfall in the horizontal direction, so that the rainfall is required to be converted into surface rainfall for subsequent simulation.
Preferably, the calculating process of the rainfall station weight comprises the following steps:
Connecting all adjacent rainfall stations in the sub-watershed into a triangle, surrounding each rainfall station with a Thiessen polygon corresponding to the vertical bisector of each side of the triangle, and taking the area of the Thiessen polygon as the control area of the corresponding rainfall station;
and regarding the Thiessen polygon cut with the boundary of the sub-drainage basin, taking the polygonal area enclosed by the Thiessen polygon line segment inside the sub-drainage basin and the boundary of the sub-drainage basin as the control area of the corresponding rainfall station.
The processing method of the mapping relation between the rainfall stations and the sub-drainage basin adopts a Thiessen polygon interpolation mode, real-time data of the effective rainfall stations are constructed into Thiessen polygons, the space analysis is carried out by the sub-drainage basin and the Thiessen polygons, and then the weight information of each rainfall station of the sub-drainage basin is obtained by an area weighting calculation method; for a rain station near the boundary of a sub-basin, the control area may be partially beyond the range of the sub-basin, and only the control area within the range of the sub-basin is considered for weight calculation.
Preferably, setting an upper limit threshold of the calculated quantity of rainfall stations in the sub-watershed in the process of converting the point rainfall into the surface rainfall; when the number of the rainfall stations in the sub-watershed is larger than the upper threshold, the rainfall stations with the largest control area and the upper threshold number are reserved, and the corresponding rainfall station weights are readjusted.
The invention sets the upper limit threshold of the calculated quantity of the rainfall stations in each sub-stream domain, not only ensures the accuracy of the face rainfall data in the sub-stream domain, but also improves the calculation efficiency in the mountain torrent disaster early warning analysis process, eliminates the rainfall stations with smaller rainfall station weights exceeding the upper limit threshold quantity, reserves the rainfall stations with larger residual rainfall station weights, and adjusts the weights so as to ensure that the sum of the rainfall station weights is one.
Preferably, the evaluation process of the mountain torrent risk level of the disaster prevention object includes:
Presetting an influence factor which plays a direct or indirect role on the torrent disaster as a risk assessment index, and scoring the risk assessment index based on periodically updated torrent disaster investigation evaluation data, real-time meteorological data and simulation data of a confluence evolution process; and the result of weighting calculation by scores of various risk assessment indexes corresponds to different torrent risk grades.
According to the mountain torrent disaster investigation evaluation data, the relevant departments are used for carrying out field investigation and collecting and analyzing the historical data to obtain results, so that investigation and updating can be regularly carried out to ensure the accuracy and reliability of the data; the mountain torrent risk assessment index comprises: the rainfall, water level, confluence time, geological disaster dangerous situation information, current flood control capacity and field information including dam engineering, bridges, road culverts and the like in the range of the mountain torrents threat zone of the river village are scored manually or automatically and then comprehensively calculated to obtain the mountain torrents risk grade.
A mountain torrent disaster warning system based on a distributed hydrological model, comprising:
the data access module is used for accessing real-time meteorological data and geological data and historical data related to the mountain torrent disasters;
the model construction module is used for generating a distributed drainage basin hydrological model based on geological data and historical data in the drainage basin;
The risk assessment module is used for carrying out mountain torrent risk level assessment on the disaster prevention object based on real-time meteorological data and simulation data of the convergence evolution process; and carrying out mountain torrent early warning according to the evaluation result.
The mountain torrent disaster early warning system disclosed by the invention is not only connected with meteorological data about rainfall for early warning, but also connected with detection data of mountain torrent disaster related factors of a plurality of departments such as a water conservancy department and a natural resource department, and carries out mountain torrent disaster early warning through combination analysis of various data of multiple sources, so that identification elements of mountain torrent disaster risks are expanded, mountain torrent risk discrimination basis is increased, and risk identification capacity and accuracy are improved.
Preferably, the system further comprises:
The data visualization module displays a topographic image in the drainage basin range, and monitors and pre-warns real-time meteorological data and evaluation analysis results of each sub-drainage basin based on the topographic image;
And the risk early warning module is used for generating a risk early warning list and pushing the risk early warning list to users in the mountain torrent disaster threat area and related disaster related departments.
The data visualization module converts the data into the image for display, so that specific topography in the river basin range can be more intuitively embodied, and in addition, visual monitoring of the mountain torrent risk condition in the river basin can be realized based on river village marks, river channels, houses, bridges, barrages, sluice gates and other wading projects in the river basin, and the acquired and analyzed data in real time; the early warning information of the mountain torrent risk can be transmitted to the user in the mountain torrent disaster threat area through various channels such as short message notification, network release and the like besides informing related disaster related departments through the system of the invention, so that the danger is avoided in time.
The invention has the following beneficial effects: the distributed watershed hydrologic model is adopted, the sub-watershed is used as a computing unit, the confluence evolution process simulation in the watershed is realized, the real-time rainfall is considered in the early warning analysis process, the real topography data is combined, the method is improved into a mountain torrent early warning mode combining rainfall, flow and water level, and the result of mountain torrent early warning is more accurate; the method can carry out targeted refined mountain torrent risk assessment aiming at each sub-river basin and disaster prevention object, enhance the effectiveness and timeliness of mountain torrent disaster early warning and strive for time for relevant treatment measures of mountain torrent disaster threat areas.
Drawings
FIG. 1 is a flow chart of a mountain flood warning method of the present invention;
FIG. 2 is a schematic diagram of the current calculation using soil moisture method in the present invention;
FIG. 3 is a block diagram of a mountain flood early warning system according to the present invention;
Fig. 4 is a data flow chart of the mountain torrent disaster warning in the present invention.
Detailed Description
The invention is further described below with reference to the drawings and detailed description.
As shown in fig. 1, a mountain torrent disaster early warning method based on a distributed hydrological model includes:
Constructing a distributed watershed hydrological model comprising a plurality of sub-watershed correlations based on geological data and historical data in the watershed; collecting real-time meteorological data, and simulating a converging evolution process of a sub-river basin where a disaster prevention object in the river basin is located by combining a distributed river basin hydrological model;
and according to the simulated convergence evolution process, calculating the mountain torrent risk grade of the disaster prevention object by combining the risk assessment index of the preset disaster prevention object.
The construction process of the distributed watershed hydrological model comprises the following steps:
Sub-drainage basin division and grid cell division are carried out on the drainage basins according to geological data, and a drainage mechanism is determined. Specifically, the whole river basin is connected according to the topological relation and the hydraulic connection combination among a plurality of sub-river basins, high-precision topography and relief telemetry data of the river basin are obtained, hydrological characteristics and geological and relief analysis are carried out, and different grid units are divided according to actual geographical river basin conditions (including the characteristics of the underlying surface, the gradient, the slope direction, the water and sand migration direction, the confluence network, the boundary line of the river basin and the like) in a mountain torrent early warning scene and by combining the characteristics (such as semiarid and semi-moist areas) of the river basin and actual requirements.
And calculating the evapotranspiration data of each sub-basin grid unit. And the calculation of the evapotranspiration data adopts a three-layer evaporation model, and parameters of the three-layer evaporation model are calculated based on historical meteorological data and historical hydrological data. The three-layer evapotranspiration model data are not described in detail because of the prior art.
The evapotranspiration data is used as an independent data source, a unified calculation mode can be adopted, and the abnormal identification, the delay identification and the evapotranspiration surface distribution calculation of the evapotranspiration data are realized by utilizing a database trigger. Meanwhile, the main objective of the calculation of the evapotranspiration data is to quickly obtain the evapotranspiration data of the period of the sub-drainage basin, and to ensure the calculation speed and comprehensively consider the occurrence of the abnormality of the evapotranspiration data, the calculation is realized by adopting a method combining the pre-interpolation calculation and the dynamic interpolation calculation, firstly, the weight coefficients of all weather stations corresponding to all stations in the sub-drainage basin when all the weather stations are normal are calculated, and the real-time interpolation mode of surrounding normal stations is adopted for the abnormal stations.
And determining a flow model algorithm according to the flow mechanism, and calculating flow data of the grid units of the sub-flow areas. The specific runoff model algorithm can select a soil humidity method to simulate a canopy interception layer, a ground surface depression filling layer, a soil section layer, a shallow underground aquifer and a deep underground aquifer, and real-time meteorological data and evapotranspiration data are used for calculating runoff data.
Specifically, the soil humidity method uses a five-layer model considering evaporation to simulate infiltration, and the generalized model is as shown in fig. 2, and the three layers of models are sequentially from top to bottom: a forest canopy interception layer, a ground surface depression filling layer, a soil section layer, a shallow underground aquifer and a deep underground aquifer. The precipitation firstly meets the interception of vegetation canopy, then meets the well filling of the earth surface, the precipitation in the depression infiltrates into the soil profile, and after the depression is filled, the precipitation exceeding the maximum infiltration rate becomes net rain; the soil section layer is divided into two areas: a tension zone where water is only used for evaporation and a non-tension zone where water has two directions: down to the shallow underground aquifer and transpiration. One part of water of the shallow underground aquifer flows out in underground runoff, and the other part of water infiltrates into the deep underground aquifer; also, a part of the water in the deep underground aquifer flows out in a lateral flow form to form a base flow, and the other part leaks into a deeper layer. Soil moisture methods assume that evaporation occurs only in the canopy entrapment, the earth's surface depression and the soil profile. Firstly, intercepting water from a canopy to begin evaporation, and if the water intercepted by the canopy cannot meet the requirement of evaporation, beginning evaporation of water in a surface depression filling layer; and secondly, a soil profile non-tension zone and finally a soil profile tension zone. Under the condition that the real-time rainfall and the evapotranspiration data are known, the data such as the surface runoff of the outflow region, the underground production flow, the evapotranspiration loss, the supply of deep underground water and the like can be calculated.
The rainwater falling on the sub-river basin is subtracted from the loss in the flow production stage to form net rainwater, and the net rainwater is injected into the river network through the slope land confluence. During the converging process on a sloping field, different runoff components may be formed along different converging paths. The flow rate of surface runoff is large, the flow path is short, the converging time is short, the flow rate of underground runoff is small, the converging time is long, and the flow in soil is between the two. After runoffs with different water source components enter the river network, a river network converging stage is started, and the converged water flow is injected into a river channel to cause the rapid increase of the flow. And after the stream data of each sub-drainage basin grid unit are converged, simulating a convergence evolution process by a motion wave method.
The simulating confluence evolution process by a motion wave method comprises the following steps:
Wherein I 0 is the water surface ratio drop; Along-the-way variation of the flood wave propagation flow; /(I) Is the change of the cross section area of the river channel along with the time; v is the average flow velocity of the section; m 1 is the rough coefficient of the river channel; r is the hydraulic radius of the section; q is the average water supply intensity of the slope surfaces at two sides of the river channel.
The real-time meteorological data comprise real-time rainfall data, and the process of converting the rainfall into the surface rainfall of the sub-watershed comprises the following steps:
Constructing Thiessen polygons of each rainfall station according to the space positions of the rainfall stations in the sub-watershed, and determining the control area of each rainfall station; and taking the ratio of the control area of each rainfall station to the area of the sub-drainage basin as the corresponding weight of the rainfall station, and carrying out weighted calculation on the spot rainfall of each rainfall station to obtain the surface rainfall of the sub-drainage basin.
For real-time rainfall data of the rainfall station, the anomaly of the rainfall station and the delay of the rainfall value data need to be processed, and whether the station is abnormal can be judged according to whether a safe report arrives at the station at a fixed time every day; in addition, reasonable rules can be set to judge whether the incoming rainfall value data of a certain site is abnormal or not; if the abnormality occurs, the adjacent station is utilized to conduct data interpolation. If delay occurs in data of a certain station, the rainfall of the small drainage basin surface needs to be recalculated from the delay period
The calculation process of the rainfall station weight comprises the following steps:
Connecting all adjacent rainfall stations in the sub-watershed into a triangle, surrounding each rainfall station with a Thiessen polygon corresponding to the vertical bisector of each side of the triangle, and taking the area of the Thiessen polygon as the control area of the corresponding rainfall station;
and regarding the Thiessen polygon cut with the boundary of the sub-drainage basin, taking the polygonal area enclosed by the Thiessen polygon line segment inside the sub-drainage basin and the boundary of the sub-drainage basin as the control area of the corresponding rainfall station.
Setting an upper limit threshold of the calculated quantity of rainfall stations in the sub-watershed in the process of converting the point rainfall into the surface rainfall;
when the number of the rainfall stations in the sub-watershed is larger than the upper threshold, the rainfall stations with the largest control area and the upper threshold number are reserved, and the corresponding rainfall station weights are readjusted.
Specifically, in order to ensure the calculation efficiency of the mountain torrent disaster early warning analysis, the number of rainfall stations related to each sub-basin is set to be an upper threshold, for example, 5. When the number of the rainfall stations calculated according to the Thiessen polygon is more than 5, removing the rainfall station with smaller weight according to the polygon area in the subbasin from small to large, and simultaneously adjusting the weight value of the 5 rainfall stations selected, so as to ensure that the sum of the weights is 1.
The evaluation process of the mountain torrent risk level of the disaster prevention object comprises the following steps:
Presetting an influence factor which plays a direct or indirect role on the torrent disaster as a risk assessment index, and scoring the risk assessment index based on periodically updated torrent disaster investigation evaluation data, real-time meteorological data and simulation data of a confluence evolution process; and the result of weighting calculation by scores of various risk assessment indexes corresponds to different torrent risk grades.
Specifically, a mountain torrent risk assessment index system is established, rainfall is forecasted in different periods of 1-24 hours in a meteorological department as an information source, a sub-river basin is used as a unit, rainfall in a leading period is determined, risk factor characteristics such as storm rainfall, flood peak modulus, confluence time, current flood control capacity, real-time water level, river course drop, ground disaster early warning and the like are comprehensively considered in different recurring periods, and weights of different indexes and corresponding scoring standards are determined. And (5) adjusting in consideration of early rainfall or soil water content states and the like, and determining mountain torrent risk assessment indexes of different grades. And scoring and weighting the evaluation indexes of each disaster prevention object according to the mountain torrent disaster investigation evaluation data, the real-time meteorological data and the simulation data of the confluence evolution process to obtain final overall scores corresponding to different mountain torrent risk grades.
Such as the ratio of the previous one-hour rainfall to the one-hour critical rainfall (weight is 0.1, the ratio is multiplied by one hundred to be scored), the ratio of the previous three-hour rainfall to the three-hour critical rainfall (weight is 0.1, the ratio is multiplied by one hundred to be scored), the ratio of the previous six-hour rainfall to the six-hour critical rainfall (weight is 0.1, the ratio is multiplied by one hundred to be scored), the real-time water level (weight is 0.3, obtained through simulation data of the confluence evolution process, and the water level is less than or equal to the warning water level of 70 minutes; the water level is 90 minutes between the warning water level and the dangerous water level, the water level is 100 minutes greater than the dangerous water level, the river channel specific drop (weight is 0.1, obtained from mountain flood investigation evaluation data), the current flood control capacity (weight is 0.1, obtained from mountain flood investigation evaluation data), the ground disaster early warning (weight is 0.1, provided by natural resource planning, real-time early warning is 70 minutes, 80 minutes in three hours, and 90 minutes in one hour) and the confluence time (weight is 0.1, obtained from mountain flood investigation evaluation data, is 70 minutes in three hours, 80 minutes in two hours to three hours, and 100 minutes in one hour). And (3) carrying out weighted calculation to obtain the total score of the disaster prevention object, wherein the total score is greater than or equal to eighty-five points and corresponds to the extremely high risk mark as red early warning, the total score is greater than or equal to seventy-five points and corresponds to the high risk mark as yellow early warning, and the total score is less than seventy-five points and corresponds to the low risk mark as green early warning.
In the invention, the critical rainfall threshold value or the early warning water level and the flow are determined essentially according to the thought of rainfall, flow and water level; according to topological relation and hydraulic connection among all sub-watersheds in a watershed, establishing a correlation, endowing all calculation modules and parameters to corresponding sub-watersheds, constructing a distributed watershed hydrologic model, and analyzing the mountain torrent disasters according to the processes of full-watershed-sub-watershed division-distributed grid division-grid evaporation distribution calculation, stream production calculation-river network confluence calculation, confluence evolution, flow early warning, rainfall early warning, water level early warning and mountain torrent disaster early warning.
The river basin is formed by hillsides responding to precipitation, the construction of the distributed river basin hydrologic model is to analyze precipitation of specific topography to form a mechanism of generating flow, and the corresponding relation between hillside landform sub-river basin grid units and the precipitation mechanism is established based on geological data (topography, land utilization, vegetation coverage, soil types and the like) in the river basin; combining with a modularized hydrologic model construction method, determining a sub-basin grid unit yield calculation method based on the dominant yield characteristics of the hillside landform sub-basin grid unit, comprehensively obtaining the yield of the sub-basin, and converging the yield of each sub-basin to the outlet of the basin according to the topological serial relation of the sub-basin by utilizing the slope and the river channel converging process to complete the simulation of the converging evolution process.
The three-layer evaporation model belongs to an existing evapotranspiration data calculation method, and parameters of the three-layer evaporation model are optimized and debugged based on historical meteorological data and historical hydrological data of a river basin to obtain an evapotranspiration calculation model suitable for the river basin; the runoff generation refers to the process that precipitation on a watershed generates net rain through plant interception, depression filling, infiltration, evaporation and the like, and generates various runoff components, and different runoff model algorithms can be selected according to the runoff generation mechanism of a specific sub-watershed, including but not limited to a soil humidity method.
The motion wave method simulation confluence evolution process is carried out by solving a finite difference continuity equation and a simplified momentum equation, and the required data comprise the section shape of a river channel, the size of the river channel, a slope coefficient, the length, a Manning coefficient and the like, wherein physical parameters such as the size and the like can be extracted through a map, and the Manning coefficient can be estimated through different land utilization types; besides the motion wave simulation method, a Mastink root method, a hysteresis algorithm and the like can be adopted to simulate the convergence evolution process according to the requirement.
The real-time rainfall data substituted into the distributed watershed hydrological model for simulating the confluence evolution process are surface rainfall data, which means average rainfall on the area of a certain watershed; the rainfall detected by the rainfall station or other rainfall testing devices is the rainfall at a specific place, and the rainfall cannot accurately represent the rainfall condition in the drainage basin range due to the height non-uniformity of rainfall in the horizontal direction, so that the rainfall is required to be converted into surface rainfall for subsequent simulation.
The processing method of the mapping relation between the rainfall stations and the sub-drainage basin adopts a Thiessen polygon interpolation mode, real-time data of the effective rainfall stations are constructed into Thiessen polygons, the space analysis is carried out by the sub-drainage basin and the Thiessen polygons, and then the weight information of each rainfall station of the sub-drainage basin is obtained by an area weighting calculation method; for a rain station near the boundary of a sub-basin, the control area may be partially beyond the range of the sub-basin, and only the control area within the range of the sub-basin is considered for weight calculation.
The invention sets the upper limit threshold of the calculated quantity of the rainfall stations in each sub-stream domain, not only ensures the accuracy of the face rainfall data in the sub-stream domain, but also improves the calculation efficiency in the mountain torrent disaster early warning analysis process, eliminates the rainfall stations with smaller rainfall station weights exceeding the upper limit threshold quantity, reserves the rainfall stations with larger residual rainfall station weights, and adjusts the weights so as to ensure that the sum of the rainfall station weights is one.
According to the mountain torrent disaster investigation evaluation data, the relevant departments are used for carrying out field investigation and collecting and analyzing the historical data to obtain results, so that investigation and updating can be regularly carried out to ensure the accuracy and reliability of the data; the mountain torrent risk assessment index comprises: the rainfall, water level, confluence time, geological disaster dangerous situation information, current flood control capacity and field information including dam engineering, bridges, road culverts and the like in the range of the mountain torrents threat zone of the river village are scored manually or automatically and then comprehensively calculated to obtain the mountain torrents risk grade.
A mountain torrent disaster warning system based on a distributed hydrological model, comprising:
the data access module is used for accessing real-time meteorological data and geological data and historical data related to the mountain torrent disasters;
the model construction module is used for generating a distributed drainage basin hydrological model based on geological data and historical data in the drainage basin;
The risk assessment module is used for carrying out mountain torrent risk level assessment on the disaster prevention object based on real-time meteorological data and simulation data of the convergence evolution process; and carrying out mountain torrent early warning according to the evaluation result.
The data visualization module displays a topographic image in the drainage basin range, and monitors and pre-warns real-time meteorological data and evaluation analysis results of each sub-drainage basin based on the topographic image;
And the risk early warning module is used for generating a risk early warning list and pushing the risk early warning list to users in the mountain torrent disaster threat area and related disaster related departments.
Specifically, as shown in fig. 3, the architecture diagram of the mountain torrent disaster early warning system includes a base layer, a data layer, a service layer and an application layer; and integrating the existing computing environment and communication network environment in the base layer, and building software and hardware environments required by system operation by utilizing the existing network, security and the like. And unified system application service is provided in the service layer, and unified public service support such as basic data access, data analysis, interface expression, app information push and the like is provided for the mountain torrent disaster early warning system.
Accessing data from different departments in a data layer, wherein the data comprises space thematic data, rainwater condition data, investigation evaluation data, model data and topological relation data; the space thematic data comprises drainage basin related data, high-resolution satellite images, high-precision digital elevation models, working base diagrams and the like, and is convenient for visual display of drainage basin range information and construction of a drainage basin three-dimensional model. The rainwater condition data comprise distribution data, real-time rainfall data, real-time water level data, real-time flow data and the like of each measuring station, and early warning analysis is carried out on the mountain torrent disaster risk based on the real-time data; the investigation evaluation data comprise wading engineering data, section measurement data, socioeconomic data, analysis comment data and the like, and relevant evaluation results are obtained through the field visit investigation of each department. The model data comprises parameters of a distributed watershed hydrological model, parameters of an evapotranspiration model, parameters of a runoff model, parameters of a confluence evolution model and the like. The topological relation data is the topological relation of each sub-basin in the stream domain and each grid cell in the sub-basin.
And building a three-dimensional basic platform, a real-time rain condition, a real-time water condition, flood analysis and early warning module and the like in an application layer according to a modularized development thought. Real-time rain condition and water condition information of the river basin can be displayed, and meanwhile, the mountain torrent disaster risk level assessment result in the river basin is displayed. And monitoring and early warning prompt are carried out on the real-time data and the analysis and calculation results, including monitoring of site rainfall data and flow data. And monitoring and judging according to the early warning threshold value, automatically early warning when the threshold value is exceeded, and displaying early warning data in real time. The early warning data are divided into two types, namely actual measurement data early warning and forecast data early warning. The display mode adopts a GIS+ chart form, macroscopically checks the distribution of the early warning section and the rainfall distribution area, and checks the specific rainfall, water level and flow data and the rainfall and water level change process of each drainage basin outlet in detail. And labeling and highlighting the map according to the longitude and latitude of the site. GIS map supports operations such as two-dimensional vector diagram, satellite diagram, remote sensing diagram amplifying, shrinking, positioning, plotting, measuring and the like. The chart data are presented in accordance with the map, and the data such as the rain condition, the water level, the flow velocity and the flow rate in the river channel are displayed in detail.
The mountain torrent disaster early warning system disclosed by the invention is not only connected with meteorological data about rainfall for early warning, but also connected with detection data of mountain torrent disaster related factors of a plurality of departments such as a water conservancy department and a natural resource department, and carries out mountain torrent disaster early warning through combination analysis of various data of multiple sources, so that identification elements of mountain torrent disaster risks are expanded, mountain torrent risk discrimination basis is increased, and risk identification capacity and accuracy are improved.
The data visualization module converts the data into the image for display, so that specific topography in the river basin range can be more intuitively embodied, and in addition, visual monitoring of the mountain torrent risk condition in the river basin can be realized based on river village marks, river channels, houses, bridges, barrages, sluice gates and other wading projects in the river basin, and the acquired and analyzed data in real time; the early warning information of the mountain torrent risk can be transmitted to the user in the mountain torrent disaster threat area through various channels such as short message notification, network release and the like besides informing related disaster related departments through the system of the invention, so that the danger is avoided in time.
In the embodiment of the invention, as shown in fig. 4, the whole data for mountain torrent disaster early warning comprises river basin data, model parameter data, real-time meteorological data and the like, the main flow comprises initializing calculation parameter data, and the real-time meteorological data comprises access of real-time water conditions and real-time rainfall data. The initialization calculation parameter data part mainly reads in the river basin information and the model parameter information of the calculation units, so that the real-time meteorological data are calculated in a distributed mode through the plurality of calculation units, and early warning forecast information data are output.
The basic data collection for constructing the distributed watershed hydrological model mainly comprises mountain torrent disaster investigation and evaluation data, geological data and rain condition data. The mountain torrent disaster investigation and evaluation data include: the mountain torrent disaster investigation basic layer and form data (administrative district overall situation, social economic situation, prevention district basic situation, danger district basic situation, prevention district administrative district and small river basin, history mountain torrent disaster summary table, important village resident investigation table along river, important town resident investigation result table, automatic monitoring station summary table, wireless early warning broadcast summary table, simple rainfall station summary table, simple water level station summary table, prevention district reservoir, sluice, embankment, pond dam, road culvert, bridge summary table and section measurement result class); mountain torrent disaster analysis and evaluation result list (analysis and evaluation directory, design storm result list, control section design flood result list, control section water level-flow-population relation list, early warning index water level result list). The topographic data is mainly divided into mountain torrent work base map data (map layer data such as small river basin, river channel, node, land utilization, soil texture and the like) and high-precision DEM, DLG, DOM data in the small river basin, and is processed into a specified format for the system. The rainwater condition data mainly comprises a station basic attribute table, a water-reducing table, a reservoir water condition table, a river channel water condition table, a reservoir (lake) volume curve table, a typical flood water level flow relation table, a section test result table and the like.
In the construction process of the distributed watershed hydrologic model, 7 types of hydrologic elements (small watershed, river reach, reservoir, node, water diversion, water source and depression) are utilized to generalize a larger watershed into a watershed model consisting of a plurality of hydrologic elements according to the hydraulic relation. Each element represents a portion of the overall response of the basin to rainfall.
The small watershed has only one outflow and no inflow, and is one of two production flow elements in the watershed model. And during runoff calculation, firstly deducting rainfall loss to obtain net rain, then converting the net rain to obtain direct runoff, and finally overlapping the direct runoff with a base stream to obtain a total runoff process.
The river reach has one outflow and one or more inflow from other hydrologic elements in the river basin model. If there is more than one inflow in the river reach, they must be superimposed before calculating the outflow. A calculated outflow is selected from a plurality of methods that may be used to simulate a river runoff process. River segments are used to simulate rivers.
The reservoir has more than one inflow from other hydrologic elements in the basin model and one calculated outflow. If there is more than one inflow, it is necessary to first superimpose them before the outflow can be calculated. In calculating the outflow, the user is required to provide a "reservoir" drainage relationship while assuming the water surface is planar. The reservoir is used for simulating reservoirs, lakes, ponds and the like.
A node is a hydrologic element with one or more flows and only one flow. All the inflow is superimposed to give an outflow assuming zero water storage at the node. The nodes are used to simulate the junction of a river.
The water splitting has one or more inflow and two outflow, one of which is the primary outflow and one of which is the secondary outflow, the inflow coming from other elements in the basin model. If there are multiple streams, the streams should be superimposed and then calculated. In calculating the outflow, it is necessary to provide an inflow-water separation relationship for determining the secondary water output, and the total inflow minus the secondary water output yields the primary outflow. The secondary effluent may be connected to elements representing downstream waterways. The device is mainly used for simulating a diversion channel, an aqueduct or a weir of a non-river reservoir.
The water source has one outflow, no inflow, and is one of two types of production flow elements in the basin model. The water source is used primarily to simulate boundary conditions of a basin model, such as outflow from a reservoir or source area.
The depression has more than one inflow and no outflow. The total water volume entering the depression is obtained after superposition of the inflow. The depression may be used to simulate the lowest point of an inland drainage area or the exit of a drainage basin model.
The watershed is generalized to a distributed watershed hydrologic model consisting of a number of hydrologic elements in a hydraulic relationship. The distributed watershed hydrologic model uses natural sub-watershed as a computational unit and considers the spatial distribution of rainfall within each sub-watershed to be uniform, but the underlying surface condition spatial distribution to be non-uniform. And establishing a correlation according to the topological relation and the hydraulic connection among the sub-watershed in the watershed, endowing the corresponding sub-watershed with each calculation module and parameters, and constructing a distributed watershed hydrological model. The distributed hydrologic model covers all hydrologic processes including face rainfall analysis calculation, runoff calculation, evapotranspiration calculation, confluence evolution calculation and the like.
And the analysis result of the real-time rainfall data and the data simulated in the confluence evolution process are combined with the mountain torrent disaster investigation and evaluation data, and the rainfall and water level (flow) are used as indexes to realize the flood risk assessment of villages, rivers and reservoirs, and the risk assessment results of mountain torrent disaster prevention villages, small watershed and small and medium-sized reservoirs are updated in a rolling manner. And giving out the flood disaster risk grades of different villages, riverways and reservoirs of each flood, and the number of villages along the river, population and house affected by the flood by fully utilizing the flood prevention capability of each village, the design flood data of the riverway and the water level-flow-population (house number) data of the village in the flood disaster investigation evaluation data. And forming disaster evaluation of a single time and two scales according to time, generating a flood evaluation report, and providing comprehensive data support for flood prevention and disaster reduction decisions.
The foregoing embodiments are further illustrative and explanatory of the invention, as is not restrictive of the invention, and any modifications, equivalents, and improvements made within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A mountain torrent disaster early warning method based on a distributed hydrological model is characterized by comprising the following steps:
Constructing a distributed drainage basin hydrological model containing a plurality of correlations among the sub-drainage basins based on geological data and historical data in the drainage basin; collecting real-time meteorological data, and simulating a converging evolution process of a sub-river basin where a disaster prevention object in the river basin is located by combining a distributed river basin hydrological model;
and according to the simulated convergence evolution process, calculating the mountain torrent risk grade of the disaster prevention object by combining the risk assessment index of the preset disaster prevention object.
2. The mountain torrent disaster warning method based on the distributed hydrological model as claimed in claim 1, wherein the construction process of the distributed watershed hydrological model comprises the following steps:
sub-drainage basin division and grid unit division are carried out on the drainage basins according to geological data, and a drainage mechanism is determined; calculating evapotranspiration data of each sub-drainage basin grid unit;
Determining a flow model algorithm according to a flow mechanism, and calculating flow data of grid units of the sub-flow areas;
and after the stream data of each sub-drainage basin grid unit are converged, simulating a convergence evolution process by a motion wave method.
3. The mountain torrent disaster warning method based on the distributed hydrologic model according to claim 2, wherein the calculation of the evapotranspiration data adopts a three-layer evaporation model, and parameters of the three-layer evaporation model are calculated based on historical meteorological data and historical hydrologic data;
The runoff model algorithm selects a soil humidity method to simulate a canopy interception layer, a ground surface depression filling layer, a soil section layer, a shallow underground aquifer and a deep underground aquifer, and calculates runoff data by real-time meteorological data and evapotranspiration data.
4. The mountain torrent disaster warning method based on the distributed hydrological model as claimed in claim 2, wherein the simulating the converging evolution process by the motion wave method comprises the following steps:
Wherein I 0 is the water surface ratio drop; Along-the-way variation of the flood wave propagation flow; /(I) Is the change of the cross section area of the river channel along with the time; v is the average flow velocity of the section; m 1 is the rough coefficient of the river channel; r is the hydraulic radius of the section; q is the average water supply intensity of the slope surfaces at two sides of the river channel.
5. The mountain torrent disaster warning method based on a distributed hydrological model as claimed in any one of claims 1 to 4, wherein the real-time weather data includes real-time rainfall data, and the process of converting the rainfall into the face rainfall of the sub-watershed includes:
constructing Thiessen polygons of each rainfall station according to the space positions of the rainfall stations in the sub-watershed, and determining the control area of each rainfall station; and taking the ratio of the control area of each rainfall station to the area of the sub-drainage basin as the corresponding weight of the rainfall station, and carrying out weighted calculation on the point rainfall to obtain the face rainfall of the sub-drainage basin.
6. The mountain torrent disaster warning method based on the distributed hydrological model as claimed in claim 5, wherein the calculation process of the rainfall station weight comprises the following steps:
Connecting all adjacent rainfall stations in the sub-watershed into a triangle, surrounding each rainfall station with a Thiessen polygon corresponding to the vertical bisector of each side of the triangle, and taking the area of the Thiessen polygon as the control area of the corresponding rainfall station;
and regarding the Thiessen polygon cut with the boundary of the sub-drainage basin, taking the polygonal area enclosed by the Thiessen polygon line segment inside the sub-drainage basin and the boundary of the sub-drainage basin as the control area of the corresponding rainfall station.
7. The mountain torrent disaster warning method based on the distributed hydrological model as claimed in claim 5, wherein the upper limit threshold of the calculated number of rainfall stations in the sub-watershed in the process of converting the point rainfall into the face rainfall is set;
when the number of the rainfall stations in the sub-watershed is larger than the upper threshold, the rainfall stations with the largest control area and the upper threshold number are reserved, and the corresponding rainfall station weights are readjusted.
8. The mountain torrent disaster warning method based on the distributed hydrological model according to claim 1 or 2 or 3 or 4 or 6 or 7, wherein the evaluation process of the mountain torrent risk level of the disaster prevention object comprises:
Presetting an influence factor which plays a direct or indirect role on the torrent disaster as a risk assessment index, and scoring the risk assessment index based on periodically updated torrent disaster investigation evaluation data, real-time meteorological data and simulation data of a confluence evolution process; and the result of weighting calculation by scores of various risk assessment indexes corresponds to different torrent risk grades.
9. A mountain torrent disaster early warning system based on a distributed hydrological model, which is suitable for the mountain torrent disaster early warning method as set forth in any one of claims 1 to 8, and is characterized by comprising:
the data access module is used for accessing real-time meteorological data and geological data and historical data related to the mountain torrent disasters;
the model construction module is used for generating a distributed drainage basin hydrological model based on geological data and historical data in the drainage basin;
The risk assessment module is used for carrying out mountain torrent risk level assessment on the disaster prevention object based on real-time meteorological data and simulation data of the convergence evolution process; and carrying out mountain torrent early warning according to the evaluation result.
10. A torrent disaster warning system based on a distributed hydrological model as claimed in claim 9, wherein the system further comprises:
The data visualization module displays a topographic image in the drainage basin range, and monitors and pre-warns real-time meteorological data and evaluation analysis results of each sub-drainage basin based on the topographic image;
And the risk early warning module is used for generating a risk early warning list and pushing the risk early warning list to users in the mountain torrent disaster threat area and related disaster related departments.
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