Method for realizing small watershed flood flow and inundation forecast

Abstract

The application discloses a kind of automatic realization small watershed mountain torrent flood flow and inundation prediction method, including steps: step S1, the parameters of the preset basin are obtained, including grid water flow direction, grid slope, basin river network, river network width;Step S2, the CN value and K value of each grid in the preset basin are obtained;Step S3, the flow and confluence of each grid in the preset basin are calculated;Step S4, a mountain torrent inundation model based on the open source model LISFLOOD-FP is constructed;Step S5, the basin flow prediction value and flood inundation range are automatically calculated and output by the mountain torrent inundation model.The present application can realize the automatic real-time prediction from rainfall to flow prediction to inundation range.

Description

Technical Field

[0001] This invention relates to the field of flood forecasting technology, specifically to an automated method for forecasting flash flood flow and inundation in small watersheds. Background Technology

[0002] Floods are among the most serious natural disasters. Flash floods in small watersheds are a common type of flood disaster, characterized by high frequency of occurrence, strong destructiveness and suddenness, and great difficulty in forecasting and prediction. This places high demands on the accuracy of forecasts and early warnings, as well as the computational efficiency of models.

[0003] Methods for forecasting and issuing early warnings of flash floods in small watersheds include: critical rainfall and hydrodynamic models. Critical rainfall uses empirical formulas to generalize parameters reflecting the unevenness of rainfall; the accuracy and precision of forecasts are easily affected by the spatial distribution of rainfall and topography. Lumped hydrological models are effective for forecasting flow at a specified outlet section but lack flow forecasting for other sections of the river. Distributed (grid) hydrological models can forecast flow at multiple river sections, but they are complex to program and cannot determine the extent of flood inundation. Summary of the Invention

[0004] In order to overcome the shortcomings of the above technologies, this invention provides a method for automatically predicting the flow and inundation of flash floods in small watersheds, realizing automated real-time forecasting from rainfall to flow forecast to inundation range.

[0005] Terminology Explanation:

[0006] 1. DEM: Digital Elevation Model.

[0007] 2. SCS-CN model: The Soil Conservation ServiceRunoffCurveNumber Method.

[0008] 3. K value: velocity coefficient.

[0009] 4. CN value: Curve Number value.

[0010] The technical solution adopted by this invention to overcome its technical problems is:

[0011] A method for automatically forecasting flash flood flow and inundation in small watersheds, comprising the following steps:

[0012] Step S1: Obtain parameters of the preset watershed, including grid water flow direction, grid slope, watershed river network, and river network width;

[0013] Step S2: Obtain the CN and K values ​​of each grid cell within the preset watershed;

[0014] Step S3: Calculate the flow rate and runoff conditions of each grid cell within the preset watershed;

[0015] Step S4: Construct a flash flood inundation model based on the open-source model LISFLOOD-FP;

[0016] Step S5: Automatically calculate and output the watershed flow forecast value and flood inundation range using the flash flood inundation model.

[0017] Further, in step S1, the grid water flow direction, grid slope, watershed river network, and river network width are obtained through DEM, specifically including:

[0018] Step S1.1: Download the DEM data of the preset watershed from a public website;

[0019] Step S1.2: Use ArcGIS to fill depressions in the downloaded DEM;

[0020] Step S1.3: Calculate the raster water flow direction using ArcGIS;

[0021] Step S1.4: Use ArcGIS to calculate the elevation difference between adjacent grids and obtain the slope of each grid.

[0022] Step S1.5: Using ArcGIS, by statistically analyzing the direction of water flow in the raster, the number of raster cells flowing into each upstream raster is calculated to obtain the catchment area of ​​the raster. Then, a catchment area threshold is set to extract the river network of the preset watershed.

[0023] Step S1.6: Using ArcGIS, specify a point in the preset watershed, find the watershed outlet according to the raster water flow direction, and comprehensively analyze the river network, watershed outlet and raster water flow direction to obtain the river network of the preset watershed.

[0024] Step S1.7: Obtain the width of the river network.

[0025] Furthermore, step S2 specifically includes:

[0026] Step S2.1: Obtain the soil use and soil type of the preset watershed through a public website, divide the soil of the preset watershed into four categories according to the infiltration rate, look up the CN value relationship table according to the soil use of each type of soil, investigate the soil moisture content in the early stage, and obtain the CN value of the grid according to different moisture conditions and the CN value relationship table.

[0027] Step S2.2: Based on the soil utilization, find the slope velocity coefficient table and read the K value of the grid.

[0028] Furthermore, step S3 specifically includes:

[0029] Step S3.1: Obtain data from rain gauge stations in the preset watershed and calculate the areal rainfall data through interpolation;

[0030] Step S3.2: Calculate the flow rate of each grid cell using the SCS-CN model;

[0031] Step S3.3: Based on the grid water flow direction obtained in step S1, find the outlet of the watershed and mark it as 0. The grid that flows into the grid marked as 0 is marked as 1, the grid that flows into the grid marked as 1 is marked as 2, and so on, until the entire watershed is traversed. Read the grid number to obtain the order of grid confluence.

[0032] Step S3.4: Calculate the flow velocity of the water in the grid, multiply the flow velocity by the time step to obtain the distance the water flows through, and use the distance the water flows through to determine the grid that the water reaches within the time step; based on the flow rate of each grid obtained in step S3.2, perform flow rate calculation on the watershed according to the order of grid flow convergence, and the flow rate of a grid is equal to the flow rate of the current grid plus the amount of water flowing into the grid from other grids;

[0033] Step S3.5: Calculate the river grid flow using the Muskingum method.

[0034] Further, in step S3.2, the production flow rate of each grid is calculated as follows:

[0035] (1)

[0036] In the above formula, This refers to runoff volume, measured in mm. This is the initial loss coefficient; Rainfall amount for a given period; The maximum possible retention capacity of the watershed is calculated using the following formula:

[0037] (2)

[0038] In the above formula, The value is determined by soil type, land use, and soil moisture content in the past.

[0039] Further, in step S3.4, the calculation of the water flow velocity in the grid is specifically as follows:

[0040] (3)

[0041] In the above formula, For flow rate; The velocity coefficient is determined at least by land use characteristics; This is an empirical coefficient; The slope.

[0042] Furthermore, in step S4, the flash flood inundation model is calculated using the open-source model LISFLOOD-FP, where the river water depth at each river grid point is calculated using the shallow water equation:

[0043]

[0044]

[0045] In the above formula, and for Flow and speed in different directions; The cross-sectional area of ​​the river channel; It is the acceleration due to gravity; This is the Manning roughness coefficient; The hydraulic radius; For water depth; This refers to the elevation of the riverbed.

[0046] Furthermore, step S4 specifically includes:

[0047] Step S4.1: Based on the direction of water flow in the grid, count the number of grids that flow into the adjacent river grid. The number of river grids flowing into the starting point of the river grid is 0. The number of river grids flowing into the grid point of the tributary is greater than or equal to 2. The outlet point of the watershed does not flow into other river grids in the watershed.

[0048] Step S4.2: Extracting the flow rates at the river's starting point, outlet, and tributary inflow points from the river grid flow rate calculated in step S3;

[0049] Step S4.3: Based on the characteristics of the river channel and the floodplain, obtain the Manning roughness coefficient of the river channel and the Manning roughness coefficient of the floodplain by looking up the table.

[0050] Step S4.4: Prepare the data according to the LISFLOOD-FP input requirements, including the DEM of the preset watershed, the river grid flow process, river width, Manning roughness coefficient of the river channel, Manning roughness coefficient of the floodplain, the address of the input and output files, the total duration of the flash flood forecast, the initial time step, and whether the river flow simulation uses diffused waves.

[0051] Furthermore, step S5 specifically includes:

[0052] Step S5.1: Run the LISFLOOD-FP model and generate an exe file;

[0053] Step S5.2: Using the data prepared in step S4.4 as the input file, call the exe file generated in step S5.1 to generate flooded data;

[0054] Step S5.3: Read the flooding data and store it in geotiff format.

[0055] Furthermore, in step S5.2, the flooding data output by the LISFLOOD-FP model is in WD file format by default. The preset algorithm is used to change it to output CSV, TXT or Excel format files.

[0056] The beneficial effects of this invention are:

[0057] 1. This invention realizes automated real-time forecasting from rainfall to flow forecast to inundation range.

[0058] 2. The flash flood inundation model of the present invention uses information such as soil type, land use and previous hydrological conditions as model inputs, which gives the method a very strong physical basis.

[0059] 3. The flash flood inundation model of the present invention uses raster data, which can fully take into account the non-uniformity of spatial distribution.

[0060] 4. In this invention, the rainfall process is an area rainfall process, which can comprehensively consider the spatial distribution of rainfall. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating the method for automatically predicting flash flood flow and inundation in small watersheds, as described in an embodiment of the present invention.

[0062] Figure 2 This is a schematic diagram of the EDM of the preset watershed described in an embodiment of the present invention.

[0063] Figure 3 This is a schematic diagram of the grid water flow direction according to an embodiment of the present invention.

[0064] Figure 4 This is a schematic diagram of the CN value of the preset watershed as described in an embodiment of the present invention.

[0065] Figure 5 This is a schematic diagram of the K value of the preset watershed as described in an embodiment of the present invention.

[0066] Figure 6 This is a schematic diagram of the slope of the preset watershed as described in an embodiment of the present invention.

[0067] Figure 7 This is a schematic diagram of the river network of the preset watershed described in an embodiment of the present invention.

[0068] Figure 8 This is a schematic diagram of the width of the preset watershed river network as described in an embodiment of the present invention.

[0069] Figure 9This is a schematic diagram of the flow rate of a river network grid at a certain moment calculated by the method of an embodiment of the present invention.

[0070] Figure 10 This is a schematic diagram of the inundation depth of the study area at a certain moment calculated by the method of an embodiment of the present invention. Detailed Implementation

[0071] To facilitate a better understanding of the present invention by those skilled in the art, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The following are merely exemplary and do not limit the scope of protection of the present invention.

[0072] like Figure 1 As shown in the figure, the method for automatically predicting flash flood flow and inundation in small watersheds according to this embodiment includes the following steps:

[0073] Step S1: Obtain parameters of the preset watershed, including grid water flow direction, grid slope, watershed river network, and river network width;

[0074] Step S2: Obtain the CN and K values ​​of each grid cell within the preset watershed;

[0075] Step S3: Calculate the flow rate and runoff conditions of each grid cell within the preset watershed;

[0076] Step S4: Construct a flash flood inundation model based on the open-source model LISFLOOD-FP;

[0077] Step S5: Automatically calculate and output the watershed flow forecast value and flood inundation range using the flash flood inundation model.

[0078] Based on the grid flow direction and the watershed river network, the topological relationship of grid confluence is calculated; the flow velocity of each grid is calculated, and the flow rate of each grid is calculated according to the grid topological relationship; for the river grid, the Muskingan method is used to calculate the river flow rate.

[0079] The river network is analyzed to obtain its starting point, tributary confluence points, and watershed outlet, and the flow processes at these grid points are extracted. The river width at these points is measured, and interpolation is used to obtain the river width of the entire river network grid. The flow processes of the grid points, the river width of the channel grid, the roughness coefficients of the river network and other grid points in the watershed, and the DEM are input into the flash flood inundation model.

[0080] Specifically, the following example, using a certain district / county, illustrates an illustrative method for automatically predicting flash flood flow and inundation in a small watershed, as described in this embodiment, but is not limited to this embodiment. In this embodiment, the data input to the flash flood inundation model is as follows: Figures 2-8As shown, other input data include areal rainfall in a preset watershed (the preset watershed in this embodiment refers to the watershed studied in this embodiment) and any point within the preset watershed. The given point within the watershed is used to locate the study watershed. These data are input into the flash flood inundation model, which automatically completes the calculation, and the output results are as follows. Figure 9 and Figure 10 As shown, this represents the flood inundation area of ​​the watershed. It should be noted that... Figures 2-10 In the diagram, both the horizontal and vertical axes are represented by grid cells.

[0081] Step S1: Obtain the parameters of the preset watershed, including grid flow direction, grid slope, watershed river network, and river network width. Details are as follows:

[0082] Step S1.1: Download the DEM data of the preset watershed from public websites. Free DEM data can be obtained from the following three websites: ASTER Global Digital Elevation Model, Space Shuttle Radar Terrain Mission (SRTM), and Global Digital Land Model (ALOS World 3D-30m).

[0083] Step S1.2: In order to extract the complete river network, ArcGIS is used to perform depression filling processing on the downloaded DEM. The DEM of the preset watershed after depression filling processing in this embodiment is as follows: Figure 2 As shown, Figure 2 The legend values ​​on the right represent elevations, in meters.

[0084] Step S1.3: Calculate the raster water flow direction using ArcGIS. Specifically, this involves calling the D8 algorithm in the ArcGIS toolbox to calculate the raster water flow direction. Figure 3 As shown, Figure 3 The legend values ​​on the right indicate the direction of water flow. The correspondence between the values ​​and the direction of water flow is as follows: 1: East, 2: Southeast, 4: South, 8: Southwest, 16: West, 32: Northwest, 64: North, 128: Northeast.

[0085] Step S1.4: Use ArcGIS to calculate the elevation difference between adjacent rasters and obtain the slope of each raster, such as... Figure 6 As shown, Figure 6 The values ​​in the legend on the right represent the tangent of the slope angle.

[0086] Step S1.5: Using ArcGIS, calculate the number of grid cells upstream of each grid cell by statistically analyzing the flow direction of the water flow in the grid cells, obtain the catchment area of ​​each grid cell, then set a catchment area threshold, and extract the river network of the preset watershed, such as... Figure 7 As shown, the white lines represent the river network. Figure 7 It includes a river network with multiple sub-basins.

[0087] Step S1.6: Using ArcGIS, specify a point in the preset watershed, find the watershed outlet according to the raster water flow direction, and comprehensively analyze the river network, watershed outlet and raster water flow direction to obtain the river network of the preset watershed.

[0088] Step S1.7: Obtain the river network width. The river network width can be obtained through actual measurement or by obtaining satellite imagery. The obtained river network width data is as follows: Figure 8 As shown, Figure 8 The legend values ​​on the right represent the width of the river, in meters.

[0089] In addition to using the methods described above, steps S1.1-S1.6 can also be completed by writing your own code.

[0090] Step S2: Obtain the CN and K values ​​of each raster within the preset watershed. Specifically, this includes:

[0091] Step S2.1: Obtain soil utilization and soil type data for the pre-defined watershed from a public website. Classify the soil in the pre-defined watershed into four categories (A, B, C, and D) based on infiltration rate. Category A soil has an infiltration rate greater than 7.5 mm / hour; Category B soil has an infiltration rate of 3.8–7.5 mm / hour; Category C soil has an infiltration rate of 1.3–3.8 mm / hour; and Category D soil has an infiltration rate less than 1.3 mm / hour. Based on the soil utilization data for each soil category, consult the CN value relationship table. Investigate the previous soil moisture content and obtain the CN value of the raster based on different moisture conditions and the CN value relationship table. Figure 4 As shown, Figure 4 The legend values ​​on the right are CN values. The amount of data obtained from the graph is relatively large and the data is more intuitive.

[0092] Step S2.2: Based on soil utilization, locate the slope velocity coefficient table and read the K value of the grid, such as... Figure 5 As shown, Figure 5 The values ​​in the legend on the right are K values, which represent the flow velocity coefficient.

[0093] Step S3: Calculate the runoff and runoff conditions for each grid cell within the preset watershed. Specifically, this includes:

[0094] Step S3.1: Obtain data from rain gauge stations in the preset watershed. This data is point data. The areal rainfall data is obtained by interpolation. The interpolation method can be Kriging interpolation, bilinear interpolation, nearest neighbor interpolation, or inverse distance interpolation. Select the appropriate interpolation method according to the interpolation effect.

[0095] Step S3.2: Calculate the flow rate of each grid cell using the SCS-CN model. The specific calculation of the flow rate of each grid cell is as follows:

[0096] (1)

[0097] In the above formula, This refers to runoff volume, measured in mm. This is the initial loss coefficient; Rainfall amount for a given period; The maximum possible retention capacity of the watershed is calculated using the following formula:

[0098] (2)

[0099] In the above formula, The value is determined by soil type, land use, and soil moisture content in the past.

[0100] Step S3.3: Based on the grid water flow direction obtained in step S1, find the outlet of the watershed and mark it as 0. The grid inflow marked as 0 is marked as 1, the grid inflow marked as 1 is marked as 2, and so on, until the entire watershed is traversed. Read the grid number to obtain the order of grid confluence.

[0101] Step S3.4: Calculate the flow velocity of the water in the grid, multiply the flow velocity by the time step to obtain the distance the water flows through, and use the distance the water flows through to determine the grid that the water reaches within the time step; based on the flow rate of each grid obtained in step S3.2, perform flow rate calculation on the watershed according to the order of grid flow convergence, and the flow rate of the grid is equal to the flow rate of the current grid plus the amount of water flowing into the grid from other grids.

[0102] Specifically, the flow velocity of the water in the grid is calculated as follows:

[0103] (3)

[0104] In the above formula, For flow rate; The velocity coefficient is determined at least by land use characteristics; This is an empirical coefficient; The slope.

[0105] Step S3.5: Calculate the river grid flow using the Muskingan method, such as... Figure 9 As shown, Figure 9 The legend values ​​on the right represent flow rates, in cubic meters per second. Figure 9 You can see the specific data volume directly.

[0106] Step S4: Construct a flash flood inundation model based on the open-source model LISFLOOD-FP. That is, the flash flood inundation model is calculated using the open-source model LISFLOOD-FP, where the river water depth at each river grid point is calculated using the shallow water equation.

[0107]

[0108]

[0109] In the above formula, and for Flow and speed in different directions; The cross-sectional area of ​​the river channel; It is the acceleration due to gravity; This is the Manning roughness coefficient; The hydraulic radius; For water depth; This refers to the elevation of the riverbed.

[0110] Step S4 specifically includes the following steps:

[0111] Step S4.1: Based on the direction of water flow in the grid, count the number of grid cells flowing into the adjacent river grid cells. The number of river grid cells flowing into the starting point of the river grid is 0. The number of river grid cells flowing into the grid point of the tributary is greater than or equal to 2. The outlet point of the watershed does not flow into other river grid cells of the watershed. The starting point of the river is found by this method.

[0112] Step S4.2: Extracting the flow rates at the river's starting point, outlet, and tributary inflow points from the river grid flow rate calculated in step S3;

[0113] Step S4.3: Based on the characteristics of the river channel and the floodplain, obtain the Manning roughness coefficient of the river channel and the Manning roughness coefficient of the floodplain by looking up tables (such as tables of Manning roughness coefficients found on some public websites or in professional technical manuals).

[0114] Step S4.4: Prepare the data according to the LISFLOOD-FP input requirements, including the DEM of the preset watershed, the river grid flow process, river width, Manning roughness coefficient of the river channel, Manning roughness coefficient of the floodplain, the address of the input and output files, the total duration of the flash flood forecast, the initial time step, and whether the river flow simulation uses diffused waves.

[0115] Step S5: Automatically calculate and output the watershed discharge forecast and flood inundation range using the flash flood inundation model. Specifically, this includes:

[0116] Step S5.1: Run the LISFLOOD-FP model to generate an exe file.

[0117] Step S5.2: Using the data prepared in step S4.4 as the input file, call the exe file generated in step S5.1 to generate flooding data. The flooding data output by the LISFLOOD-FP model is in WD file format by default. In this embodiment, it can be changed to output csv, txt or excel format files through a preset algorithm.

[0118] Step S5.3: Read the flooding data and store it in geotiff format, such as... Figure 10 As shown, Figure 10 The legend values ​​on the right represent the submerged water depth, in meters. Figure 10 You can see the specific value of the submerged water depth directly.

[0119] The method described in this embodiment can achieve automated real-time forecasting from rainfall to flow forecast to inundation range.

[0120] The above description only outlines the basic principles and preferred embodiments of the present invention. Those skilled in the art can make many changes and modifications based on the above description, and these changes and modifications should fall within the protection scope of the present invention.

Claims

1. A method for automatically predicting flash flood flow and inundation in small watersheds, characterized in that, Including the following steps: Step S1: Obtain parameters of the preset watershed, including grid water flow direction, grid slope, watershed river network, and river network width; Step S2: Obtain the CN and K values ​​of each grid cell within the preset watershed; Step S3: Calculate the flow rate and runoff conditions of each grid cell within the preset watershed; Step S3 specifically includes: Step S3.1: Obtain data from rain gauge stations in the preset watershed and calculate the areal rainfall data through interpolation; Step S3.2: Calculate the flow rate of each grid cell using the SCS-CN model; Step S3.3: Based on the grid water flow direction obtained in step S1, find the outlet of the watershed and mark it as 0. The grid that flows into the grid marked as 0 is marked as 1, the grid that flows into the grid marked as 1 is marked as 2, and so on, until the entire watershed is traversed. Read the grid number to obtain the order of grid confluence. Step S3.4: Calculate the flow velocity of the water in the grid, multiply the flow velocity by the time step to obtain the distance the water flows through, and use the distance the water flows through to determine the grid that the water reaches within the time step; based on the flow rate of each grid obtained in step S3.2, perform flow rate calculation on the watershed according to the order of grid flow convergence, and the flow rate of a grid is equal to the flow rate of the current grid plus the amount of water flowing into the grid from other grids; Step S3.5: Calculate the river grid flow using the Muskingan method; Step S4: Construct a flash flood inundation model based on the open-source model LISFLOOD-FP; Step S4 specifically includes: Step S4.1: Based on the direction of water flow in the grid, count the number of grids that flow into the adjacent river grid. The number of river grids flowing into the starting point of the river grid is 0. The number of river grids flowing into the grid point of the tributary is greater than or equal to 2. The outlet point of the watershed does not flow into other river grids in the watershed. Step S4.2: Extracting the flow rates at the river's starting point, outlet, and tributary inflow points from the river grid flow rate calculated in step S3; Step S4.3: Based on the characteristics of the river channel and the floodplain, obtain the Manning roughness coefficient of the river channel and the Manning roughness coefficient of the floodplain by looking up the table. Step S4.4: Prepare the data according to the LISFLOOD-FP input requirements, including the DEM of the preset watershed, the river grid flow process, river width, Manning roughness coefficient of the river channel, Manning roughness coefficient of the floodplain, the address of the input and output files, the total duration of flash flood forecast, the initial time step, and whether the river flow simulation uses diffused waves. Step S5: Automatically calculate and output the watershed flow forecast value and flood inundation range using the flash flood inundation model.

2. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 1, characterized in that, In step S1, the grid water flow direction, grid slope, watershed river network, and river network width are obtained through DEM, specifically including: Step S1.1: Download the DEM data of the preset watershed from a public website; Step S1.2: Use ArcGIS to fill depressions in the downloaded DEM; Step S1.3: Calculate the raster water flow direction using ArcGIS; Step S1.4: Use ArcGIS to calculate the elevation difference between adjacent grids and obtain the slope of each grid. Step S1.5: Using ArcGIS, by statistically analyzing the direction of water flow in the raster, the number of raster cells flowing into each upstream raster is calculated to obtain the catchment area of ​​the raster. Then, a catchment area threshold is set to extract the river network of the preset watershed. Step S1.6: Using ArcGIS, specify a point in the preset watershed, find the watershed outlet according to the raster water flow direction, and comprehensively analyze the river network, watershed outlet and raster water flow direction to obtain the river network of the preset watershed. Step S1.7: Obtain the width of the river network.

3. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 1, characterized in that, Step S2 specifically includes: Step S2.1: Obtain the soil use and soil type of the preset watershed through a public website, divide the soil of the preset watershed into four categories according to the infiltration rate, look up the CN value relationship table according to the soil use of each type of soil, investigate the soil moisture content in the early stage, and obtain the CN value of the grid according to different moisture conditions and the CN value relationship table. Step S2.2: Based on the soil utilization, find the slope velocity coefficient table and read the K value of the grid.

4. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 1, characterized in that, In step S3.2, the production flow rate of each grid cell is calculated as follows: （1）； In the above formula, This refers to runoff volume, measured in mm. This is the initial loss coefficient; Rainfall amount for a given period; The maximum possible retention capacity of the watershed is calculated using the following formula: （2）； In the above formula, The value is determined by soil type, land use, and soil moisture content in the past.

5. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 1, characterized in that, In step S3.4, the calculation of the water flow velocity in the grid is specifically as follows: （3）； In the above formula, For flow rate; The velocity coefficient is determined at least by land use characteristics; This is an empirical coefficient; The slope.

6. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 1, characterized in that, In step S4, the flash flood inundation model is calculated using the open-source model LISFLOOD-FP, where the river water depth at each river grid point is calculated using the shallow water equation: ； ； In the above formula, and for Flow and speed in different directions; The cross-sectional area of ​​the river channel; It is the acceleration due to gravity; The roughness coefficient is Manning's coefficient. The hydraulic radius; For water depth; This refers to the elevation of the riverbed.

7. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 1, characterized in that, Step S5 specifically includes: Step S5.1: Run the LISFLOOD-FP model to generate an exe file; Step S5.2: Using the data prepared in step S4.4 as the input file, call the exe file generated in step S5.1 to generate flooded data; Step S5.3: Read the flooding data and store it in geotiff format.

8. The method for automatically predicting flash flood flow and inundation in small watersheds according to claim 7, characterized in that, In step S5.2, the flooding data output by the LISFLOOD-FP model is in WD file format by default. It can be changed to CSV, TXT or Excel format files by using a preset algorithm.

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