Reservoir rainstorm resistance calculation method considering soil humidity state

Abstract

The invention discloses a method for calculating the rainstorm resistance of a reservoir by considering the soil humidity state. The method comprises the following specific steps: acquiring data such as terrain, soil, vegetation, rainfall, water level and ex-warehouse flow; the water level, the warehouse-out flow and the water level-warehouse capacity curve data are used for reversely deducing the warehouse-in flow; constructing a VIC hydrological model as a reservoir flood forecasting model; according to the reservoir characteristic parameters and the reservoir scheduling schedule, constructing a reservoir scheduling model; coupling the reservoir entering flood forecasting model and the reservoir dispatching model; constructing a reservoir anti-rainstorm capability model; acquiring SMAP remote sensing soil humidity data, and performing data assimilation on the SMAP remote sensing soil humidity data and the VIC model; and on the basis of the VIC model after the soil humidity state is updated, reservoir flood forecasting is carried out, and reservoir rainstorm resistance calculation considering the current soil humidity is realized. According to the method, by dynamically updating the soil humidity state of the drainage basin, the accuracy of reservoir flood forecasting is remarkably improved, the precision of reservoir rainstorm resistance assessment is enhanced, and technical support is provided for reservoir flood control dispatching.

Description

Technical Field

[0001] The invention relates to the technical field of hydrology and water resources, and in particular to a method for calculating the rainstorm resistance capacity of a reservoir taking into account the soil moisture state. Background Art

[0003] For flood control safety of reservoirs, the prediction of reservoir anti-rainstorm capacity is usually used to achieve flood control warning. The concept of reservoir anti-rainstorm capacity was proposed by the Ministry of Water Resources. It refers to the ability of a reservoir to safely withstand the amount of rainstorm under the current basin underlying surface, reservoir water level, and reservoir scheduling mode. By predicting the reservoir's anti-rainstorm capacity under the current conditions, the reservoir scheduling plan can be improved, reservoir warnings can be issued in a timely manner, and the risk of dam failure or downstream flooding due to untimely scheduling can be reduced. From the concept of reservoir anti-rainstorm capacity, it can be seen that the uncertainty of the soil moisture state of the basin underlying surface has a great impact on the calculation of reservoir anti-rainstorm capacity, but due to insufficient soil moisture observation, this key factor has often been ignored in the calculation of reservoir anti-rainstorm capacity in the past. In recent years, with the development of remote sensing technology, we can more accurately monitor and evaluate the underlying surface conditions of the basin, especially the key factor of soil moisture. Soil moisture directly affects the infiltration of precipitation and surface runoff, which in turn affects the formation and evolution of floods. Traditional flood forecasting models often find it difficult to accurately simulate the dynamic changes of soil moisture, especially in the absence of real-time monitoring data. The introduction of remote sensing technology provides a new way to solve this problem.

[0004] This application proposes a method for calculating the rainstorm resistance capacity of reservoirs taking into account the soil moisture state. This method can achieve more accurate and reliable calculation of the rainstorm resistance capacity of reservoirs and provide scientific guidance for reservoir scheduling and flood control safety management. It has important practical significance for improving my country's ability to respond to flood disasters and protecting people's lives and property. Summary of the invention

[0005] In view of this, the object of the present invention is to provide a method for calculating the rainstorm resistance capacity of a reservoir taking soil moisture into consideration, so as to improve the safety and reliability of flood control of the reservoir.

[0006] The technical solution adopted by the present invention is: a method for calculating the rainstorm resistance capacity of a reservoir taking into account soil moisture, comprising the following steps:

[0007] S100: Obtaining terrain, soil, vegetation, weather, measured precipitation, measured water level, and measured outflow data;

[0008] S200: Based on the water level and outflow data of S100, combined with the water level-storage capacity curve, the inflow flow is reversed based on the water balance principle;

[0009] S300: Based on the basic data obtained from S100 and S200, the VIC hydrological model is constructed as the reservoir inflow flood forecasting model, and the model parameters are calibrated;

[0010] S400: Construct a reservoir operation model according to the reservoir operation regulations;

[0011] S500: Couple the flood forecasting model and reservoir operation model to achieve reservoir water level simulation forecast;

[0012] S600: Construct a reservoir's ability to resist heavy rain;

[0013] S700: Obtain SMAP remote sensing soil moisture data, assimilate the data with the VIC model, and update the current watershed soil moisture status;

[0014] S800: Based on the VIC model after updating the soil moisture status, flood forecasting is carried out to calculate the reservoir's ability to resist heavy rains taking into account the current soil moisture.

[0015] Preferably, the S100 specifically includes: collecting DEM data covering the watershed; collecting data such as soil type and soil texture in the watershed; collecting data such as vegetation type and vegetation coverage in the watershed; obtaining observed meteorological data, including temperature, humidity, wind direction, wind speed, etc.; obtaining measured precipitation data, and using the Thiessen polygon method to achieve grid precipitation interpolation; obtaining reservoir water level time series data; and obtaining measured reservoir outflow data.

[0016] Preferably, the S200 specifically includes: obtaining the water level-storage capacity curve of the reservoir according to the water level and outflow flow data obtained in step S100, and reversely calculating the inflow flow according to the water balance principle to obtain the measured inflow flow time series.

[0017] Preferably, the S300 specifically includes: constructing a VIC hydrological model of the target basin based on the data processed by steps S100 and S200, determining the optimal parameters of the VIC hydrological model by combining manual parameter adjustment with the Rosenbrock automatic optimization algorithm, and using the calibrated VIC model as a reservoir inflow flood forecasting model.

[0018] Preferably, the S400 specifically includes: acquiring reservoir characteristic parameters and reservoir flood control dispatching rules, further constructing a reservoir dispatching model, and determining the outflow flow process under different inflow flow states.

[0019] Preferably, the S500 specifically includes: coupling the reservoir flood forecasting model constructed in step S300 and the reservoir scheduling model constructed in step S400, and performing reservoir water level simulation forecasting according to the water level-reservoir capacity curve.

[0020] Preferably, the S600 specifically includes: selecting a typical rainstorm process in the basin, setting design rainstorm processes of different magnitudes according to the same-multiple scaling method, obtaining the reservoir water level process under design rainstorms of different magnitudes according to step S500, determining the relationship curve between the total rainfall and the highest water level, and further constructing a reservoir anti-rainstorm capacity model based on the relationship curve between the total rainfall and the highest water level of the reservoir.

[0021] Preferably, the S700 specifically includes: acquiring SMAP remote sensing soil moisture data according to the geographical location of the target watershed, using an ensemble Kalman filter algorithm to perform data assimilation on the VIC simulated soil moisture and the SMAP remote sensing soil moisture data, and updating the current watershed soil moisture state value.

[0022] Preferably, the S800 specifically includes: using step S700 to complete the soil moisture status update, carry out reservoir inflow flood forecast, and then calculate the reservoir's rainstorm resistance capacity based on the reservoir's rainstorm resistance capacity model constructed in step S600, and use the calculation results for reservoir scheduling and flood control management.

[0023] Beneficial effects of the present invention:

[0024] This invention patent provides a method for calculating the ability of a reservoir to resist heavy rains by taking into account the soil moisture state, which has significant beneficial effects: by introducing the VIC hydrological model and SMAP remote sensing soil moisture data, and combining data assimilation technology, this method dynamically updates the soil moisture state of the basin, significantly improving the accuracy of the flood forecast entering the reservoir, and enhancing the accuracy of the assessment of the reservoir's ability to resist heavy rains. By coupling the flood forecast model entering the reservoir and the reservoir scheduling model, it is possible to simulate and predict reservoir water level changes under different heavy rain scenarios, provide a scientific basis for the optimization of reservoir scheduling plans, and ensure the timeliness and effectiveness of scheduling decisions. By using the updated soil moisture state and the designed heavy rain process to construct a reservoir's ability to resist heavy rains model, it is possible to more accurately predict the reservoir's ability to withstand different heavy rain intensities, provide strong support for flood control safety management, and reduce the risk of dam breaches or downstream flooding. This method is based on remote sensing technology and hydrological models, can adapt to different geographical environments and river basin characteristics, has strong universality and adaptability, can be promoted and applied in different types of reservoirs and river basins, and effectively solves the problem that traditional flood forecasting models are difficult to accurately simulate the dynamic changes of soil moisture, fills the gap of insufficient soil moisture observation, and has important practical significance for improving my country's flood disaster response capabilities and protecting people's lives and property. In summary, this invention patent provides a more accurate and reliable method for calculating the reservoir's ability to resist heavy rain, and provides scientific guidance and technical support for reservoir scheduling and flood control safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1Shown is a rainstorm pattern diagram designed in one embodiment of a method for calculating the rainstorm resistance capacity of a reservoir taking into account the soil moisture state of the present invention;

[0026] Figure 2 Shown is a curve diagram showing the relationship between the total rainfall and the highest water level under different soil moisture conditions in one embodiment of the method for calculating the rainstorm resistance capacity of a reservoir considering the soil moisture state of the present invention; DETAILED DESCRIPTION

[0027] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0028] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0029] The technical solutions in the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0030] In one embodiment, this example takes the Ersheng Reservoir in Jiangsu Province as an example, and the method for calculating the reservoir's rainstorm resistance capacity considering the soil moisture state of the present invention includes steps S100 to S800.

[0031] Step S100: Acquire data on topography, soil, vegetation, weather, measured precipitation, measured water level, and measured outflow flow.

[0032] Specifically:

[0033] S110: Terrain data:

[0034] The SRTM digital elevation model (DEM) was obtained and the DEM data was processed using ArcGIS software, including cropping to cover the entire watershed, adjusting the resolution to suit the model requirements, and performing terrain analysis such as calculation of slope, aspect, flow direction, outlet section, etc.

[0035] S120: Soil data:

[0036] The soil type and soil texture data in the watershed are collected. The target database for collection is the HWSD database. The data types include soil sand content, clay content, silt content, organic matter content, bulk density, etc.

[0037] S130: Collect the MODIS satellite 1km land cover type database.

[0038] S140: Weather data:

[0039] The daily maximum temperature, minimum temperature, humidity, wind direction, wind speed and radiation data of the study basin from 1956 to 2022 were collected from the China Meteorological Data Sharing Network.

[0040] S150: Measured precipitation data:

[0041] Collect precipitation data observed at basin stations provided by the Jiangsu Provincial Hydrological Bureau.

[0042] S160: Measured water level data:

[0043] The water level time series data of Ersheng Reservoir provided by the Hydrological Bureau of Jiangsu Province were collected.

[0044] S170: Measured flow data:

[0045] Collect the outflow data of Ersheng Reservoir provided by the Hydrological Bureau of Jiangsu Province.

[0046] Step S200: According to the water level and outflow flow data obtained in step S100, the water level-storage capacity curve of the reservoir is obtained, and according to the water balance principle, the inflow flow is reversed to obtain the measured inflow flow time series.

[0047] Specifically:

[0048] S210: Construct hourly water level and outflow flow time series data, interpolate missing data, and clean abnormal data.

[0049] S220: Implement water level-reservoir capacity conversion calculation according to the water level-reservoir capacity curve fitting calculation formula.

[0050] S230: Inverse calculation of inflow flow:

[0051] According to the water balance principle, the difference between the average amount of water entering the reservoir and the average amount of water discharged from the reservoir over a period of time is equal to the change in the reservoir's water storage capacity during that period (excluding rainfall and evaporation losses), as shown in the following formula:

[0052]

[0053] In the formula, I1 and I2 are the inflow at the beginning and end of the time period, respectively; Q1 and Q2 are the outflow at the beginning and end of the time period, respectively; V2 and V1 represent the reservoir water storage at the end and beginning of the time period, respectively; Δt is the calculation period. In the current inflow reverse calculation, the inflow process is known, that is, Q is a known item; Δt is selected according to the calculation accuracy; according to the change of the reservoir water demand V, the actual inflow process can be reversed.

[0054] Since the reservoir water level and outflow data are accurate to the minute, the time resolution is set to minute by minute in this processing, and the water level, reservoir capacity, outflow and inflow are calculated every minute, and then the mean of all minutes of the corresponding hourly period of the VIC model is calculated.

[0055] Step S300: Based on the basic data obtained in S100 and S200, a VIC hydrological model is constructed as a reservoir inflow flood forecasting model, and model parameter calibration is completed.

[0056] Specifically:

[0057] S310: VIC hydrological model construction:

[0058] Initialize the basic settings of the VIC hydrological model based on the terrain, soil, vegetation, and meteorological data obtained in step S100. Select an appropriate model grid resolution and define the watershed boundary conditions.

[0059] The saturated infiltration capacity curve is used for runoff calculation to take into account the uneven spatial distribution of soil water storage within the watershed grid.

[0060] Configure the hydrological processes of the VIC model, including precipitation, evaporation, soil moisture dynamics, etc. Set model parameters according to the characteristics of the watershed, such as the number of soil layers, vegetation type, etc.

[0061] S320: Flash confluence model construction:

[0062] The Yamazaki river network division method is used to divide the basin into several sub-basin fusion units based on high-precision DEM information.

[0063] The fusion unit response function is obtained based on the geomorphic unit line for storage calculation, and the river confluence calculation is performed using the diffusion wave analytical method.

[0064] Based on the basin DEM data and combined with ArcGIS operation, the basin area, basin flow direction and runoff accumulation parameters are obtained and input into the constructed Flash runoff model.

[0065] The Flash runoff model is integrated into the VIC hydrological model to achieve the coupling of runoff generation and runoff models.

[0066] S330: Parameter calibration:

[0067] Based on the measured and simulated reservoir inflow data, the preliminary parameter calibration of the VIC model is carried out.

[0068] Select an optimization algorithm (such as the Rosenbrock algorithm) to adjust the model parameters and combine manual parameter tuning for parameter calibration.

[0069] S340: Inflow flood forecasting:

[0070] Based on the calibrated VIC model, the inflow flood forecasting can be realized.

[0071] Step S400: Construct a reservoir operation model according to the reservoir operation regulations.

[0072] Specifically:

[0073] S410: Obtain the reservoir flood control operation rules:

[0074] Collect the flood control operation regulations of the reservoir, including reservoir characteristic parameters such as the water level-discharge capacity curve and reservoir characteristic water levels, and flood control operation strategies.

[0075] The reservoir operation strategy of the Ersheng Reservoir in the example is as follows:

[0076] When the reservoir water level is Z ≤ 14.00m, the reservoir does not discharge.

[0077] When the reservoir water level is 14.00m < Z ≤ 14.50m, the reservoir discharge ≤ 30 m³ / s.

[0078] When the reservoir water level is 14.50m < Z ≤ 15.00m, the reservoir discharge ≤ 50 m³ / s.

[0079] When the reservoir water level is 15.00m < Z ≤ 17.00m, the reservoir discharge ≤ 80 m³ / s.

[0080] When the reservoir water level is 17.00m < Z ≤ 18.00m, the reservoir discharge ≤ 100 m³ / s.

[0081] When the reservoir water level exceeds 18.00m, the reservoir discharge can be temporarily increased to more than 100 / s depending on the downstream water conditions.

[0082] S420: Construct a reservoir operation model:

[0083] Based on the principle of water balance, according to the inflow flood forecast, reservoir operation regulations, the initial state of the reservoir (initial reservoir water level, initial inflow and initial discharge), and reservoir characteristic parameters (water level-storage curve, water level-discharge capacity curve, etc.), the reservoir outflow process, reservoir storage volume, and reservoir water level change process can be calculated.

[0084] The accuracy of the dispatching model is verified using actual reservoir operation data to ensure that it can reasonably predict the dispatching effect of the reservoir.

[0085] S430: Obtaining the outbound flow process under different inbound flow states:

[0086] Based on different inflow conditions, the outflow process of the reservoir is simulated.

[0087] The reservoir operation model parameters are adjusted according to the simulation results to ensure that it can provide accurate outflow flow prediction under various flow conditions.

[0088] Step S500: coupling the reservoir flood forecasting model and the reservoir operation model to realize reservoir water level simulation forecasting.

[0089] Specifically:

[0090] S510: Coupled inflow flood forecasting model and reservoir operation model:

[0091] Design the interface between the inflow flood forecast model and the reservoir operation model to ensure that the two can effectively interact and integrate data.

[0092] The inflow forecast data of the VIC hydrological model is transmitted to the reservoir operation model to ensure that the reservoir operation model can perform operation calculations based on accurate inflow.

[0093] The coupling of the two models is achieved to ensure that the output of the reservoir inflow flood forecasting model can directly affect the calculation process of the reservoir operation model.

[0094] S520: Reservoir water level simulation forecast:

[0095] Run the coupled model to simulate the water level changes in the reservoir during rainfall events.

[0096] Adjustments are made based on actual observation data and model output results to improve the accuracy of reservoir water level simulation forecasts.

[0097] Step S600: constructing a reservoir anti-rainstorm capability model.

[0098] Specifically:

[0099] S610: Typical rainstorm process in selected basins:

[0100] Based on historical meteorological data and watershed characteristics, representative typical rainstorm processes are selected, including parameters such as intensity, duration and frequency.

[0101] In this example, the typical rainstorm process selected is a typical rainstorm process in May 2015, such as Figure 1 shown.

[0102] S620: Design storm generation:

[0103] Based on the same-ratio scaling method, design rainstorms under different rainfall levels are generated.

[0104] In this example, the rainstorm levels are set to 50mm, 100mm, 200mm, 300mm, 400mm, 500mm, 600mm, 700mm, 800mm, etc.

[0105] S630: Design Flood Process Generation:

[0106] Taking design rainstorms of different magnitudes as input, the VIC model is run to simulate the inflow flood.

[0107] The reservoir operation model is coupled to determine the design flood process under different design rainstorm processes, that is, the reservoir water level process.

[0108] S640: Determination of the relationship between total rainfall and maximum water level:

[0109] Calculate the maximum water level of the reservoir under different designed rainstorm processes.

[0110] A relationship model between total rainfall and maximum reservoir water level was established, and the relationship between the two was determined using a mapping method.

[0111] S650: Calculation of reservoir's ability to resist heavy rain:

[0112] Based on the relationship curve between total rainfall and maximum reservoir water level, the corresponding rainfall when the maximum reservoir water level reaches the design flood level is determined, which is the reservoir's rainstorm resistance capacity value at this time, thus completing the construction of the reservoir's rainstorm resistance capacity model.

[0113] Different rainfall processes were selected to verify the rationality of the reservoir's ability to resist heavy rain.

[0114] Step S700: Acquire SMAP remote sensing soil moisture data, perform data assimilation with the VIC model, and update the current watershed soil moisture status.

[0115] Specifically:

[0116] S710: Get SMAP remote sensing soil moisture:

[0117] The SMAP satellite remote sensing soil moisture data were obtained from NASA’s official website, and the corresponding data range was determined according to the location and time of the study area.

[0118] Establish a data download channel to obtain the latest SMAP data in real time.

[0119] The acquired data is usually in HDF5 or NetCDF format and needs to be converted or read accordingly depending on the processing software used.

[0120] S720: SMAP soil moisture data processing:

[0121] Preprocessing of SMAP remote sensing soil moisture data includes data quality check, noise processing, and spatial matching.

[0122] S730: Soil moisture data assimilation:

[0123] Select an appropriate data assimilation method, such as the ensemble Kalman filter algorithm, to combine the SMAP soil moisture data with the soil moisture data simulated by the VIC model.

[0124] Carry out data assimilation process to integrate SMAP remote sensing data into VIC model and update soil moisture status in the model.

[0125] Verify the soil moisture status after data assimilation to ensure that it can reflect the actual soil moisture conditions in the current basin.

[0126] S740: Model status update:

[0127] Based on the assimilated soil moisture data, the soil moisture state in the VIC model is updated.

[0128] Step S800: Based on the VIC model after updating the soil moisture status, flood forecasting is carried out to calculate the reservoir's ability to resist heavy rains taking into account the current soil moisture.

[0129] Figure 2 This is a comparison chart of the reservoir's ability to resist heavy rain under different soil moisture conditions during a typical flood.

[0130] Specifically:

[0131] S810: Update soil moisture status:

[0132] Apply the updated soil moisture status to the VIC model to ensure that the model reflects the latest soil moisture conditions.

[0133] S820: Calculation of reservoir's ability to resist heavy rain:

[0134] The updated VIC model is used for reservoir inflow forecasting to generate inflow flow predictions that take into account the current soil moisture status.

[0135] Based on the forecast results and the reservoir's rainstorm resistance model, the reservoir's rainstorm resistance under current soil moisture conditions is calculated.

[0136] The calculation results will be used for reservoir scheduling and flood control management, providing scientific guidance to improve the reservoir's ability to resist heavy rains and flood control safety.

[0137] Compared with the prior art, this application has at least the following beneficial technical effects:

[0138] By introducing the VIC hydrological model and SMAP remote sensing soil moisture data, and combining with data assimilation technology, this method dynamically updates the soil moisture state of the basin, significantly improves the accuracy of the reservoir flood forecast, and enhances the accuracy of the assessment of the reservoir's ability to resist heavy rain. By coupling the reservoir flood forecast model and the reservoir operation model, it can simulate and predict the changes in reservoir water levels under different heavy rain scenarios, provide a scientific basis for the optimization of reservoir operation plans, and ensure the timeliness and effectiveness of operation decisions. Using the updated soil moisture state and the designed heavy rain process to construct a reservoir's ability to resist heavy rain, it can more accurately predict the reservoir's ability to withstand different heavy rain intensities, provide strong support for flood control safety management, and reduce the risk of dam breach or downstream flooding. Based on remote sensing technology and hydrological models, this method can adapt to different geographical environments and basin characteristics, has strong universality and adaptability, and can be promoted and applied in different types of reservoirs and basins. It effectively solves the problem that traditional flood forecasting models are difficult to accurately simulate the dynamic changes of soil moisture, fills the gap in insufficient soil moisture observation, and has important practical significance for improving my country's ability to respond to flood disasters and protecting people's lives and property. In summary, this invention patent provides a more accurate and reliable method for calculating the reservoir's ability to resist heavy rains, and provides scientific guidance and technical support for reservoir scheduling and flood control safety management.

[0139] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A method for calculating the rainstorm resistance capacity of a reservoir taking into account the soil moisture state, characterized in that: The steps include: S100: Obtaining terrain, soil, vegetation, weather, measured precipitation, measured water level, and measured outflow data; S200: Based on the water level and outflow data obtained by S100, combined with the water level-storage capacity curve, the inflow flow is reversed based on the water balance principle; S300: Based on the basic data obtained from S100 and S200, the VIC hydrological model is constructed as the reservoir inflow flood forecasting model, and the model parameters are calibrated; S400: Construct a reservoir operation model according to the reservoir operation regulations; S500: Couple the flood forecasting model and reservoir operation model to achieve reservoir water level simulation forecast; S600: Construct a reservoir's ability to resist heavy rain; S700: Acquire SMAP remote sensing soil moisture data, assimilate the data with the VIC model, and update the current soil moisture status of the basin; S800: Based on the VIC model after the updated soil moisture status, carry out reservoir inflow flood forecasting and realize the calculation of the reservoir's ability to resist heavy rain considering the current soil moisture.

2. A method for calculating the rainstorm resistance capacity of a reservoir taking into account the soil moisture state according to claim 1, characterized in that: The S100 specifically includes: collecting DEM data covering the watershed; collecting data such as soil type and soil texture in the watershed; collecting data such as vegetation type and vegetation coverage in the watershed; obtaining observed meteorological data, including temperature, humidity, wind direction, wind speed, etc.; obtaining measured precipitation data, and using the Thiessen polygon method to achieve grid precipitation interpolation; obtaining reservoir water level time series data; and obtaining measured reservoir outflow data.

3. The method for calculating the rainstorm resistance capacity of a reservoir considering the soil moisture state according to claim 1 is characterized in that: The S200 specifically includes: obtaining the water level-storage capacity curve of the reservoir according to the water level and outflow flow data obtained in step S100, and performing reverse calculation of the inflow flow according to the water balance principle to obtain the measured inflow flow time series.

4. The method for calculating the rainstorm resistance capacity of a reservoir considering the soil moisture state according to claim 1 is characterized in that: The S300 specifically includes: constructing a VIC hydrological model of the target basin based on the data processed by steps S100 and S200, determining the optimal parameters of the VIC hydrological model by combining manual parameter adjustment with the Rosenbrock automatic optimization algorithm, and using the calibrated VIC model as a reservoir inflow flood forecasting model.

5. The method for calculating the rainstorm resistance capacity of a reservoir considering the soil moisture state according to claim 1 is characterized in that: The S400 specifically includes: obtaining reservoir characteristic parameters and reservoir flood control dispatching rules, further constructing a reservoir dispatching model, and determining the outflow process under different inflow states.

6. A method for calculating the rainstorm resistance capacity of a reservoir taking into account the soil moisture state according to claim 1, characterized in that: The S500 specifically includes: coupling the reservoir flood forecasting model constructed in step S300 and the reservoir dispatching model constructed in step S400, and performing reservoir water level simulation forecasting according to the water level-reservoir capacity curve.

7. The method for calculating the rainstorm resistance capacity of a reservoir considering the soil moisture state according to claim 1 is characterized in that: The S600 specifically includes: selecting a typical rainstorm process in the basin, setting design rainstorm processes of different magnitudes according to the same-multiple scaling method, obtaining the reservoir water level process under design rainstorms of different magnitudes according to step S500, determining the relationship curve between the total rainfall and the highest water level, and further constructing a reservoir anti-rainstorm capacity model based on the relationship curve between the total rainfall and the highest water level of the reservoir.

8. The method for calculating the rainstorm resistance capacity of a reservoir considering the soil moisture state according to claim 1 is characterized in that: The S700 specifically includes: acquiring SMAP remote sensing soil moisture data according to the geographical location of the target watershed, using the ensemble Kalman filter algorithm to perform data assimilation on the VIC simulated soil moisture and the SMAP remote sensing soil moisture data, and updating the current watershed soil moisture state value.

9. The method for calculating the rainstorm resistance capacity of a reservoir considering soil moisture status according to claim 1, characterized in that: The S800 specifically includes: using the S700 step to complete the soil moisture status update, carry out the reservoir flood forecast, and then calculate the reservoir rainstorm resistance capacity based on the reservoir rainstorm resistance capacity model constructed in the S600 step, and use the calculation results for reservoir scheduling and flood control management.

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