A flood control and drought relief early warning method and system

Abstract

A flood control and drought relief warning method and system, relating to the field of data processing technology. The method comprises: obtaining meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored; determining meteorological-hydrological response characteristics based on the meteorological monitoring data and the hydrological monitoring data, and determining meteorological-soil response characteristics based on the meteorological monitoring data and the soil monitoring data; determining the flood control risk index and drought resistance risk index of the area to be monitored in combination with the meteorological-hydrological response characteristics and the meteorological-soil response characteristics; when the flood control risk index is greater than or equal to the flood control threshold, a flood control warning is issued to the area to be monitored, and when the drought resistance risk index is greater than or equal to the drought resistance threshold, a drought resistance warning is issued to the area to be monitored. The implementation of the technical solution provided by the present application achieves the effect of improving the accuracy of flood control and drought relief warnings.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to a flood control and drought relief early warning method, system, electronic equipment and storage medium. Background Art

[0002] As global climate change intensifies, the frequent occurrence of extreme weather events such as floods and droughts poses a serious threat to human social security and economic development. Effective early warning is particularly important for mitigating the impact of these natural disasters.

[0003] At present, the existing flood and drought early warning methods mainly collect data through meteorological stations or hydrological stations, and issue early warnings for single-dimensional monitoring data. However, in actual applications, due to the mutual influence of different factors in the natural environment, relying on a single indicator for early warning often fails to reflect the actual disaster risk situation in the region, resulting in deviations between the early warning results and the actual situation, which leads to low accuracy of flood and drought early warnings. Summary of the invention

[0004] The present application provides a flood control and drought relief early warning method and system, which has the effect of improving the accuracy of flood control and drought relief early warning.

[0005] In a first aspect, the present application provides a flood and drought early warning method, comprising: Obtain meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored; Determining meteorological-hydrological response characteristics based on the meteorological monitoring data and the hydrological monitoring data, and determining meteorological-soil response characteristics based on the meteorological monitoring data and the soil monitoring data; Determine the flood risk index and drought risk index of the area to be monitored by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics; When the flood risk index is greater than or equal to the flood threshold, a flood warning is issued to the area to be monitored; when the drought risk index is greater than or equal to the drought threshold, a drought warning is issued to the area to be monitored.

[0006] In a second aspect of the present application, a flood control and drought relief early warning system is provided, the system comprising: A data acquisition module is used to acquire meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored; a feature determination module, configured to determine a meteorological-hydrological response feature based on the meteorological monitoring data and the hydrological monitoring data, and to determine a meteorological-soil response feature based on the meteorological monitoring data and the soil monitoring data; An index calculation module, used to determine the flood risk index and drought risk index of the monitored area by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics; The risk warning module is used to issue a flood warning to the monitored area when the flood risk index is greater than or equal to the flood threshold, and to issue a drought warning to the monitored area when the drought risk index is greater than or equal to the drought threshold.

[0007] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program can implement a flood and drought relief early warning method when loaded and executed by the processor.

[0008] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements a flood control and drought relief early warning method.

[0009] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By adopting the above technical scheme, the meteorological, hydrological and soil monitoring data of the monitored area are obtained, and a systematic early warning mechanism for flood and drought disasters is established. By analyzing the correlation between meteorological monitoring data and hydrological monitoring data, the meteorological-hydrological response characteristics are determined, which can accurately reflect the evolution law of hydrological processes such as rainfall and runoff; at the same time, by analyzing the correlation between meteorological monitoring data and soil monitoring data, this comprehensive analysis of multi-source data overcomes the limitation of incomplete information of single-dimensional data source and improves the depth of understanding of the causes of flood and drought disasters. Secondly, by comprehensively integrating the meteorological-hydrological response characteristics and the meteorological-soil response characteristics, the flood control risk index and the drought resistance risk index are calculated, and the quantitative assessment of regional flood and drought disaster risks is realized. This risk assessment method based on multi-dimensional response characteristics not only considers the direct impact of atmospheric precipitation processes on flood and drought disasters, but also fully considers the regulatory effect of underlying surface conditions on hydrological cycles, making the risk assessment results more comprehensive. Finally, by comparing the risk index with the preset flood control threshold and drought resistance threshold, a clear early warning trigger mechanism is established, which can timely discover potential disaster risks and initiate corresponding early warning procedures. By combining multi-dimensional data, the flood and drought risks in the monitored area are analyzed, thereby improving the accuracy of flood and drought warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a flow chart of a flood control and drought relief early warning method provided in an embodiment of the present application; Figure 2It is a structural schematic diagram of a flood control and drought relief early warning system provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0011] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0012] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0013] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0014] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0015] The present application embodiment provides a flood control and drought relief early warning method. In one embodiment, please refer to Figure 1 , Figure 1 This is a flow chart of a flood and drought warning method provided in an embodiment of the present application. The method can be implemented by a computer program, which can be integrated into an application or run as an independent tool application. The method can also be implemented by a single-chip microcomputer or run on a flood and drought warning system based on a von Neumann system. Specifically, the method can include the following steps: Step 101: Acquire meteorological monitoring data, hydrological monitoring data, and soil monitoring data in the area to be monitored.

[0016] Among them, meteorological monitoring data refers to a data set collected by meteorological monitoring equipment that reflects the atmospheric environment status of the monitored area, mainly including parameters such as rainfall, temperature and humidity. Among them, rainfall represents the amount of rain falling per unit time, temperature reflects the degree of coldness and heat of the air, and humidity indicates the amount of water vapor in the air. These meteorological monitoring data can be collected in real time through automatic weather stations, rain gauges, temperature and humidity sensors and other equipment.

[0017] Hydrological monitoring data refers to a set of data collected by hydrological monitoring equipment that reflects the spatial distribution and dynamic changes of water bodies in the monitored area, mainly including two key parameters: surface water level and groundwater level. Among them, the surface water level represents the water surface elevation of surface water bodies such as rivers and lakes, while the groundwater level reflects the water level elevation of groundwater in underground aquifers. These hydrological monitoring data can be continuously collected through equipment such as water level meters, water level sensors, and groundwater level monitoring wells.

[0018] Soil monitoring data refers to a set of data collected by soil monitoring equipment that reflects the soil moisture status and change patterns in the monitored area, mainly including the parameter of soil moisture content. Soil moisture content represents the volume content of water per unit volume of soil. These soil monitoring data can be continuously collected through monitoring equipment such as soil moisture sensors and tensiometers. The monitoring equipment is generally deployed at different soil depths to obtain the moisture distribution characteristics of the soil profile.

[0019] Specifically, meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored are obtained. Since there is a close interaction between meteorological conditions, hydrological conditions and soil conditions in the natural environment, it is necessary to collect these three types of data at the same time to fully reflect the actual situation of the area to be monitored. Specifically, multiple monitoring stations can be set up in the area to be monitored, and each monitoring station is equipped with meteorological monitoring equipment, hydrological monitoring equipment and soil monitoring equipment. Among them, meteorological monitoring equipment is used to collect meteorological monitoring data such as rainfall, temperature and humidity; hydrological monitoring equipment is used to collect hydrological monitoring data such as surface water level and groundwater level; soil monitoring equipment is used to collect soil monitoring data such as soil moisture content. The monitoring equipment can transmit the collected monitoring data to the data processing center in real time through wired or wireless communication. The data processing center preprocesses the received monitoring data, including outlier removal, data standardization and other operations, to ensure the data quality used in subsequent analysis. By establishing a complete multi-dimensional monitoring data collection system, a reliable data basis can be provided for the subsequent analysis of meteorological-hydrological response characteristics and meteorological-soil response characteristics, thereby improving the accuracy of flood control and drought relief warning. In addition, considering that the topographic features and hydrogeological conditions of the monitored area may be different, the layout of monitoring stations should fully consider regional representativeness to ensure that the collected monitoring data can accurately reflect the overall situation of the monitored area. Through scientific and reasonable monitoring station layout and data collection scheme, the warning deviation problem caused by single-dimensional data collection in existing technologies can be effectively overcome, laying the foundation for accurate warning.

[0020] Step 102: Determine meteorological-hydrological response characteristics based on meteorological monitoring data and hydrological monitoring data, and determine meteorological-soil response characteristics based on meteorological monitoring data and soil monitoring data.

[0021] Among them, the meteorological-hydrological response characteristics refer to the quantitative relationship characteristics that characterize the changes in hydrological conditions caused by changes in meteorological conditions in the monitored area, mainly including two key parameters: the first rainfall critical value that causes the water level to rise and the first evaporation critical value that causes the water level to drop. Among them, the first rainfall critical value represents the minimum rainfall intensity threshold that causes the water level to start to rise significantly. When the actual rainfall intensity exceeds this threshold, the regional water level will show a significant upward trend; the first evaporation critical value represents the minimum evaporation threshold that causes the water level to start to drop significantly. When the actual evaporation exceeds this threshold, the regional water level will show a significant downward trend.

[0022] The meteorological-soil response characteristics refer to the quantitative relationship characteristics that characterize the change in soil moisture state caused by changes in meteorological conditions in the monitored area, mainly including two key parameters: the second rainfall critical value that causes soil saturation and the second evaporation critical value that causes soil drying. Among them, the second rainfall critical value represents the minimum rainfall intensity threshold that makes the soil tend to saturation. When the actual rainfall intensity exceeds this threshold, the soil will approach or reach saturation; the second evaporation critical value represents the minimum evaporation threshold that causes the soil to dry. When the actual evaporation exceeds this threshold, the soil moisture content will significantly decrease.

[0023] Specifically, the rainfall intensity and evaporation are calculated based on the meteorological monitoring data, wherein the rainfall intensity is obtained by calculating the change value of the rainfall in a preset unit time, and the evaporation is calculated based on the temperature and humidity data. At the same time, the water level change rate is calculated based on the hydrological monitoring data, specifically by respectively calculating the change amount of the surface water level and the groundwater level in a preset time interval and performing weighted summation. By analyzing the correlation between the rainfall intensity, evaporation and the water level change rate, a meteorological-hydrological response feature is established, which includes the first rainfall critical value that causes the water level to rise and the first evaporation critical value that causes the water level to drop. Among them, the first rainfall critical value represents the minimum rainfall intensity that causes the water level to start to rise significantly, and the first evaporation critical value represents the minimum evaporation that causes the water level to start to drop significantly. In addition, the soil saturation is calculated based on the soil monitoring data, specifically by calculating the ratio of the measured soil water content to the saturated water content of this type of soil. By analyzing the corresponding relationship between the rainfall intensity, evaporation and soil saturation, a meteorological-soil response feature is established, which includes the second rainfall critical value that causes soil saturation and the second evaporation critical value that causes soil drying. Among them, the second rainfall critical value represents the minimum rainfall intensity that makes the soil tend to the saturated state, and the second evaporation critical value represents the minimum evaporation that causes the soil to tend to the dry state. By establishing these two sets of response characteristics, the influence of meteorological changes on hydrology and soil conditions in the monitored area can be fully characterized, providing a basis for subsequent flood control and drought relief warnings based on a dual judgment mechanism. This method based on multi-dimensional data analysis not only considers the direct impact of meteorological conditions on hydrological processes, but also pays attention to the regulatory role of soil on water migration, thereby improving the accuracy of warning results.

[0024] Based on the above embodiment, as an optional embodiment, in step 102: determining the meteorological-hydrological response characteristics based on the meteorological monitoring data and the hydrological monitoring data, and determining the meteorological-soil response characteristics based on the meteorological monitoring data and the soil monitoring data, this step may also include the following steps: Step 201: Calculate rainfall intensity and evaporation according to rainfall, temperature and humidity in meteorological monitoring data.

[0025] The rainfall intensity refers to the change in rainfall per unit time, indicating the severity of the precipitation process. It is calculated based on the rainfall in the meteorological monitoring data, and is obtained by dividing the change in rainfall within a preset time interval by the time interval. For example, if the rainfall increases from 2 mm to 14 mm within 1 hour, the rainfall intensity during this period is 12 mm per hour.

[0026] Evaporation refers to the volume of water converted into water vapor loss per unit time, indicating the intensity of the water evaporation process. Its calculation requires the comprehensive use of temperature and humidity in meteorological monitoring data, and is determined by water vapor pressure difference and water vapor diffusion coefficient.

[0027] Specifically, the calculation of rainfall intensity is based on the rainfall in the meteorological monitoring data, and is obtained by calculating the change value of rainfall in a preset unit time. The calculation formula is: rainfall intensity is equal to the change value of rainfall divided by the preset time interval. Among them, the preset time interval can be set according to the actual monitoring needs, and 1 hour is usually selected as the basic calculation unit. For the calculation of evaporation, it is necessary to comprehensively use temperature and humidity data. First, the saturated water vapor pressure is calculated according to the temperature, and then the actual water vapor pressure is determined in combination with the relative humidity. The evaporation value is finally obtained by calculating the water vapor pressure difference and considering the water vapor diffusion coefficient. The specific calculation formula is: evaporation is equal to the water vapor diffusion coefficient multiplied by (saturated water vapor pressure minus actual water vapor pressure). Among them, the water vapor diffusion coefficient is an empirical parameter related to temperature, which can be obtained by looking up a table or an empirical formula. The rainfall intensity and evaporation calculated in this way have clear physical meanings and can objectively reflect the characteristics of precipitation and evaporation processes in the monitored area. These calculation results will be used as important input parameters to establish a corresponding relationship with the water level change rate and soil saturation in the future, and then determine each critical value. This quantitative processing method based on measured meteorological data provides data support for achieving accurate early warning.

[0028] Based on the above embodiment, as an optional embodiment, in step 201: calculating the rainfall intensity and evaporation according to the rainfall, temperature and humidity in the meteorological monitoring data, this step may also include the following steps: Step 211: Calculate the rainfall change value within a preset unit time, and use the rainfall change value as the rainfall intensity.

[0029] Specifically, it is necessary to first determine the appropriate time resolution according to the actual needs of flood control and drought relief warning, such as 1 hour or 10 minutes, and set it as the preset unit time. Then, the rainfall difference between adjacent time steps is divided by the preset unit time to obtain the average rainfall intensity in the period. For example, if the rainfall in a certain place increases from 5 mm to 20 mm between 10:00 and 11:00, the rainfall change value in that hour is 15 mm, and the corresponding rainfall intensity is 15 mm per hour. In actual calculations, the sliding time window method can be used to achieve continuous monitoring of rainfall intensity, that is, the rainfall intensity value is updated every unit time. This rainfall intensity calculation method based on time resolution not only takes into account the dynamic characteristics of the rainfall process, but also provides quantitative indicators that can be directly compared with the critical value. When the calculated rainfall intensity exceeds the first rainfall critical value or the second rainfall critical value, the system can issue a corresponding warning signal in time. This real-time monitoring method significantly improves the timeliness of flood control warnings and provides reliable technical support for flood control and disaster reduction decisions. At the same time, through continuous monitoring of rainfall intensity, the evolution trend of the rainfall process can also be analyzed, providing a basis for the dynamic adjustment of the warning level.

[0030] Step 221: Determine the saturated water vapor pressure according to the temperature, and determine the actual water vapor pressure according to the humidity and the saturated water vapor pressure.

[0031] Among them, saturated water vapor pressure refers to the water vapor partial pressure corresponding to the maximum water vapor content that the air can hold at a specific temperature. This physical quantity increases with increasing temperature, reflecting the quantitative relationship between the air's water holding capacity and temperature. For example, under standard atmospheric pressure, the saturated water vapor pressure at 0 degrees Celsius is about 6.11 hPa, while it increases to 23.37 hPa at 20 degrees Celsius, indicating that rising temperature significantly enhances the air's water holding capacity.

[0032] Actual water vapor pressure refers to the partial pressure corresponding to the actual water vapor content in the atmosphere. This physical quantity reflects the actual existence of water vapor in the air, and its value is always less than or equal to the saturated water vapor pressure at the same temperature. For example, when the temperature is 25 degrees Celsius and the relative humidity is 60%, if the saturated water vapor pressure is 31.67 hPa, the actual water vapor pressure is 19.00 hPa, indicating that the actual water vapor content in the air has reached 60% of the maximum possible content.

[0033] Specifically, in order to accurately estimate the evaporation capacity of the atmosphere, it is necessary to first determine the actual content and potential maximum content of water vapor in the air, which requires the calculation of saturated water vapor pressure and actual water vapor pressure through temperature and humidity data. This is because the difference in water vapor pressure in the air directly affects the intensity of the evaporation process and is a key parameter for calculating evaporation. Specifically, first calculate the saturated water vapor pressure based on the temperature, and the formula can be used: es = 6.112 × exp((17.67×T) / (T+243.5)), where es is the saturated water vapor pressure and T is the temperature. This empirical formula has high calculation accuracy within the temperature range of -45℃ to 60℃. After obtaining the saturated water vapor pressure, the actual water vapor pressure is calculated in combination with the relative humidity. The calculation formula is: ea=RH×es / 100, where ea is the actual water vapor pressure and RH is the relative humidity. For example, when the temperature is 25℃, the saturated water vapor pressure calculated by the formula is about 31.67 hPa; if the relative humidity is 60% at this time, the actual water vapor pressure is 19.00 hPa. This water vapor pressure calculation method based on a physical model not only takes into account the nonlinear effect of temperature on saturated water vapor pressure, but also reflects the relationship between the actual water vapor content in the atmosphere and its maximum possible content. By calculating the difference between the actual water vapor pressure and the saturated water vapor pressure, the dryness of the air can be quantitatively characterized, and this parameter will be used for subsequent evaporation estimation. Compared with directly using the original temperature and humidity data, this method has a clearer physical meaning, can more accurately reflect the atmosphere's demand for water, and lays the foundation for the accurate calculation of evaporation.

[0034] Step 231: Multiply the pressure difference between the saturated water vapor pressure and the actual water vapor pressure by the preset water vapor diffusion coefficient to obtain the water vapor flux, and use the product of the water vapor flux and the preset evaporation coefficient as the evaporation amount.

[0035] Among them, the preset water vapor diffusion coefficient refers to the amount of water vapor diffusion through a unit area per unit time under a unit water vapor pressure difference. This coefficient reflects the diffusion capacity of water vapor in the air, and its size is affected by atmospheric dynamic conditions such as wind speed, temperature, and turbulence intensity. For example, when the wind speed is high, the preset water vapor diffusion coefficient may reach 0.3, while it may only be 0.1 under calm wind conditions, indicating that atmospheric movement significantly enhances the diffusion efficiency of water vapor.

[0036] Water vapor flux refers to the amount of water vapor transported through a unit area per unit time. This physical quantity characterizes the vertical transport intensity of water vapor, and its magnitude depends on the combined effect of the water vapor pressure difference and the water vapor diffusion conditions. For example, when the water vapor pressure difference is 12.67 hPa and the preset water vapor diffusion coefficient is 0.2, the calculated water vapor flux is 2.534 mm per day, indicating that 2.534 mm of water per square meter of surface diffuses into the atmosphere in the form of water vapor every day.

[0037] Specifically, the pressure difference between the saturated water vapor pressure and the actual water vapor pressure is first calculated. This difference represents the absorption capacity of the atmosphere for water vapor. Then the pressure difference is multiplied by the preset water vapor diffusion coefficient to obtain the water vapor flux through the unit area per unit time. The water vapor diffusion coefficient is a parameter related to aerodynamic characteristics, and its value needs to consider the influence of environmental factors such as wind speed and temperature. For example, when the saturated water vapor pressure is 31.67 hPa and the actual water vapor pressure is 19.00 hPa, the water vapor pressure difference is 12.67 hPa; if the preset water vapor diffusion coefficient is 0.2, the water vapor flux is 2.534 mm per day. In order to convert the water vapor flux into actual evaporation, it is necessary to introduce a preset evaporation coefficient to correct the calculation results. The preset evaporation coefficient is an empirical coefficient that comprehensively considers factors such as the underlying surface characteristics and vegetation coverage, and is used to correct the deviation between the theoretical calculated value and the actual evaporation. If the preset evaporation coefficient is 0.8, the final calculated evaporation is 2.027 mm per day. This evaporation calculation method based on physical mechanisms not only takes into account the driving force of water vapor diffusion, but also reflects the influence of actual environmental conditions by introducing empirical coefficients. By calculating evaporation through real-time monitoring of temperature and humidity changes, the intensity of water loss can be dynamically evaluated, providing a quantitative basis for drought warning.

[0038] Step 202: Calculate the water level change rate based on the surface water level and groundwater level in the hydrological monitoring data.

[0039] Among them, surface water level and groundwater level refer to the elevation values ​​of water bodies in the monitored area. The surface water level indicates the vertical height of the water surface of surface water bodies such as rivers, lakes and reservoirs relative to the reference surface, while the groundwater level indicates the vertical height of the phreatic surface or pressure water level relative to the reference surface. These two types of water level data are collected in real time through hydrological monitoring equipment. The surface water level is mainly measured by water level meters, radar rangefinders and other equipment, while the groundwater level is mainly monitored by observation wells, water level sensors and other equipment.

[0040] The water level change rate refers to the weighted comprehensive change value of the surface water level and groundwater level per unit time, which indicates the overall change trend and intensity of the regional hydrological system. Its calculation requires comprehensive consideration of the change in surface water level and groundwater level, and is obtained by introducing a weight coefficient for weighted averaging and dividing it by a preset time interval. For example, if the weighted comprehensive water level rises by 0.15 meters within 1 hour, the water level change rate during this period is 0.15 meters per hour, indicating an upward trend; if it drops by 0.15 meters, the water level change rate is negative 0.15 meters per hour, indicating a downward trend.

[0041] Specifically, the calculation of the water level change rate needs to process the monitoring data of the surface water level and the groundwater level separately. First, the change of the two types of water levels within the preset time interval is calculated. For the change of the surface water level, it is obtained by calculating the difference between the surface water levels at adjacent times; for the change of the groundwater level, it is obtained by calculating the difference between the groundwater levels at adjacent times. Considering the difference in the contribution of surface water and groundwater to the regional hydrological conditions, it is necessary to introduce a weight coefficient when calculating the comprehensive water level change rate. The calculation formula is: the water level change rate is equal to (the change of the surface water level multiplied by the first weight coefficient plus the change of the groundwater level multiplied by the second weight coefficient) divided by the preset time interval. Among them, the sum of the first weight coefficient and the second weight coefficient is equal to 1, and the specific value can be adjusted according to the hydrogeological conditions and actual monitoring needs of the monitored area. Under normal circumstances, since surface water is more sensitive to short-term hydrological changes, the first weight coefficient will be slightly larger than the second weight coefficient. This calculation method considering weights not only reflects the coordinated change characteristics of surface water and groundwater, but also highlights the changes in surface water that are more critical to flood control and drought relief warning. The water level change rate calculated in this way has a positive value indicating a rising trend in the water level, and a negative value indicating a falling trend in the water level. The larger the absolute value of the value, the more drastic the change. This calculation result will be used as an important parameter to establish a corresponding relationship with rainfall intensity and evaporation, and then determine the first rainfall critical value and the first evaporation critical value. This method of determining the water level change rate based on weighted calculation not only improves the comprehensiveness of hydrological status assessment, but also provides a basis for accurate early warning.

[0042] Based on the above embodiment, as an optional embodiment, in step 202: calculating the water level change rate according to the surface water level and groundwater level in the hydrological monitoring data, this step may also include the following steps: Step 212: Calculate the change in the surface water level within a preset time interval to obtain the surface water level change rate, and calculate the change in the groundwater level within the preset time interval to obtain the groundwater level change rate.

[0043] Specifically, first determine the preset time interval, which can be set to different scales such as hours, days or ten days according to monitoring needs. Then record the surface water level and groundwater level at the start and end of the time interval respectively, and calculate the difference between the water levels at the two times and divide it by the time interval to obtain the surface water level change rate and groundwater level change rate. For example, if the surface water level of a river drops from 5.2 meters to 4.8 meters within 10 days, the surface water level change rate is -0.04 meters / day; during the same period, the groundwater level drops from 12.5 meters to 12.3 meters, and the groundwater level change rate is -0.02 meters / day. Negative values ​​indicate a drop in water level, and positive values ​​indicate a rise in water level. This change rate calculation method based on measured data not only takes into account the absolute change in water level, but also reflects the time characteristics of the change. By monitoring the water level change rate in real time, the consumption of water resources can be dynamically evaluated and abnormal water level drop trends can be discovered in a timely manner. When the rate of change of the surface water level or the rate of change of the groundwater level exceeds the corresponding warning threshold, it indicates that the water resources are being consumed too quickly and corresponding drought prevention measures need to be taken in time. Compared with simply monitoring the absolute value of the water level, this method has a stronger warning capability and can detect the risk of water shortage in advance. Especially in the dry season, by analyzing the evolution trend of the water level change rate, the development trend of drought can be predicted, providing a scientific basis for drought prevention and disaster reduction decisions. At the same time, the coordinated analysis of the rate of change of the surface water level and the groundwater level helps to understand the interaction between surface water and groundwater, and provides a reference for the unified allocation of water resources.

[0044] Step 222: Perform weighted summation on the surface water level change rate and the groundwater level change rate to obtain the water level change rate.

[0045] Specifically, in order to comprehensively evaluate the overall change trend of regional water resources, it is necessary to comprehensively consider the dynamic characteristics of surface water and groundwater systems, and integrate the change rates of the two subsystems into a unified water level change rate indicator by weighted summation. This is because surface water and groundwater have different roles and importance in the regional water cycle, and simple arithmetic averages cannot accurately reflect the overall change characteristics of the water resources system. Specifically, first, according to the hydrogeological conditions and water resource utilization characteristics of the study area, the weight coefficients of the surface water level change rate and the groundwater level change rate are determined. Generally speaking, in areas with abundant surface water resources, the weight of the surface water level change rate is relatively large; while in areas where groundwater exploitation is the main focus, the weight of the groundwater level change rate is correspondingly increased. For example, if the rate of change of surface water level in a certain area is -0.04 m / day and the rate of change of groundwater level is -0.02 m / day, considering that the utilization ratio of surface water to groundwater in the area is about 6:4, the weight of the rate of change of surface water level can be set to 0.6, and the weight of the rate of change of groundwater level can be set to 0.4. The calculated rate of change of water level is -0.032 m / day. This weighted calculation method not only takes into account the change rate of different water bodies, but also reflects their relative importance in the regional water resources system. By real-time monitoring of the rate of change of water level, the overall consumption of regional water resources can be dynamically evaluated, providing a more comprehensive basis for drought early warning.

[0046] Step 203: Calculate soil saturation according to the soil moisture content in the soil monitoring data.

[0047] Among them, soil moisture content refers to the ratio of the volume of water in the soil to the total volume of the soil, indicating the amount of water contained in a unit volume of soil, usually expressed in the form of volumetric moisture content. Its value is collected in real time by soil monitoring equipment such as soil moisture sensors and time domain reflectometers, and can directly reflect the absolute content of water in the soil. For example, if the volumetric moisture content of a soil sample is 30%, it means that the volume proportion of water in the total volume of the soil sample is 30%.

[0048] Soil saturation refers to the ratio of the actual water volume in the soil to the maximum water volume that the soil can hold, indicating the degree of fullness of the soil water content relative to its maximum water holding capacity. It is a dimensionless value between 0 and 1. It is calculated by dividing the measured soil water content by the soil porosity. For example, when the soil saturation is 0.8, it means that the actual water volume in the soil accounts for 80% of its maximum possible water volume, which is close to saturation; when the soil saturation is 0.2, it means that the soil is in a relatively dry state.

[0049] Specifically, in order to accurately assess the moisture status of the soil in the monitored area, it is necessary to convert the soil moisture content in the soil monitoring data into a standardized indicator, soil saturation. This is because soil saturation can intuitively reflect the relative fullness of soil moisture, exclude the influence of porosity differences among different soil types, and is an important basic parameter for determining meteorological-soil response characteristics. Specifically, the calculation of soil saturation is based on soil moisture content and soil physical property parameters, and is obtained by calculating the ratio of measured soil moisture content to soil porosity. The calculation formula is: soil saturation is equal to the measured soil moisture content divided by soil porosity, where soil porosity represents the ratio of pore volume to total volume in the soil, which is an inherent physical property of the soil. In order to improve the calculation accuracy, multiple soil monitoring points can be arranged in the monitoring area to obtain soil moisture data at different depths, and a more representative soil saturation value can be obtained by stratified weighted averaging. The soil saturation calculated in this way is a dimensionless ratio with a numerical range between 0 and 1. The closer the value is to 1, the closer the soil is to a saturated state, and the closer the value is to 0, the drier the soil is. This calculation result will be used as an important parameter to establish a corresponding relationship with rainfall intensity and evaporation, and then determine the second rainfall critical value and the second evaporation critical value. This soil saturation-based assessment method not only eliminates the interference of different soil types on the comparison results, but also provides a standardized basis for accurate early warning. Through dynamic monitoring of soil saturation, the soil's ability to regulate water can be grasped in a timely manner.

[0050] Based on the above embodiment, as an optional embodiment, in step 203: calculating soil saturation according to soil water content in soil monitoring data, this step may also include the following steps: Step 213: Obtain the soil type in the area to be monitored; and determine the field water holding capacity corresponding to the soil type in the area to be monitored based on a preset soil type mapping table.

[0051] Soil type refers to the basic property category of soil classified according to soil particle composition, mechanical structure and physical and chemical properties. It reflects the basic physical characteristics and hydrological characteristics of the soil, including different types such as sandy soil, loam and clay. For example, sandy soil refers to soil with a sand content of more than 85%, which has the characteristics of strong water permeability and poor water retention; clay refers to soil with a clay content of more than 30%, which has the characteristics of strong water retention and poor water permeability.

[0052] The preset soil type mapping table is a table that establishes a comparison between soil types and their corresponding field water holding capacity. This mapping relationship is a standardized parameter table established based on a large amount of experimental data and field observation results. For example, the field water holding capacity of sandy soil ranges from 15-20%, sandy loam is 20-25%, clay loam is 25-35%, clay is 35-40%, etc. These values ​​are recorded in the mapping table for easy query and use.

[0053] Field water holding capacity refers to the maximum water content that the soil can retain after removing excess gravity water under the action of natural gravity, usually expressed as a percentage of soil water content. This physical quantity reflects the maximum practical water holding capacity of the soil, and its size is affected by factors such as soil texture, structure and organic matter content. For example, the field water holding capacity of clay can reach 35-40%, while sandy soil may only be 15-20%, indicating that clay has a stronger water holding capacity.

[0054] Specifically, first, the soil type information of the monitored area is obtained through soil survey data or remote sensing image interpretation, such as sandy soil, loam, clay, etc. Then, according to the pre-established soil type mapping table, the field water holding capacity value of the corresponding soil type is found and determined. For example, for sandy soil, its field water holding capacity may be between 15-20%; while for clay soil, the field water holding capacity may reach 35-40%. The preset soil type mapping table is a control relationship established on the basis of a large amount of experimental data, covering the moisture characteristic parameters of the main soil types. This parameter determination method based on soil classification effectively solves the problem of difficulty in field determination of field water holding capacity, and provides a feasible technical path for large-scale drought monitoring. By determining the field water holding capacity through the soil type mapping table, the soil moisture characteristic parameters of the monitored area can be quickly obtained, providing basic data support for subsequent drought determination.

[0055] Step 223: Divide the soil water content by the field capacity to obtain soil saturation.

[0056] Specifically, in order to quantitatively evaluate the soil moisture status and achieve comparability between different soil types, it is necessary to standardize the soil moisture content and characterize the degree of soil moisture deficit by calculating the soil saturation. This is because there are significant differences in the water holding capacity of different types of soil, and it is difficult to accurately reflect the soil moisture status based solely on the absolute value of the soil moisture content. Specifically, the measured soil moisture content is divided by the field water holding capacity corresponding to this type of soil, and the ratio obtained is the soil saturation. This dimensionless indicator reflects the percentage of the actual soil moisture content relative to the maximum water holding capacity. For example, if the soil moisture content in a clay area is 28% and its field water holding capacity is 35%, the calculated soil saturation is 0.8, indicating that the current soil moisture has reached 80% of the maximum water holding capacity. This standardized processing method eliminates the impact of differences in water holding capacity of different soil types, making the soil moisture status of different regions comparable. By real-time monitoring of soil saturation, the degree of soil moisture deficit can be dynamically evaluated, providing a quantitative basis for drought early warning.

[0057] Step 204: Determine the first rainfall critical value that causes the water level to rise and the first evaporation critical value that causes the water level to drop by statistically analyzing the mapping relationship between rainfall intensity, evaporation and water level change rate.

[0058] Among them, the first rainfall critical value that causes water level rise refers to the minimum rainfall intensity value determined by statistical analysis that can cause the water level change rate to turn from negative to positive or begin to rise significantly. This critical value reflects the sensitivity of the hydrological system in the monitored area to rainfall input and is an important characteristic value of the mapping relationship between rainfall intensity and water level change rate. For example, if statistical analysis shows that when the rainfall intensity reaches 15 mm per hour, the water level begins to show a clear upward trend, then millimeters per hour can be determined as the first rainfall critical value of the area.

[0059] The first evaporation critical value that triggers a drop in water level refers to the minimum evaporation value determined by statistical analysis that can cause the water level change rate to turn from positive to negative or begin to drop significantly. This critical value reflects the sensitivity of the hydrological system in the monitored area to evaporation losses and is an important characteristic value of the mapping relationship between evaporation and water level change rate. For example, if statistical analysis shows that when the evaporation reaches 6 mm per day, the water level begins to show a clear downward trend, then 6 mm per day can be determined as the first evaporation critical value of the area.

[0060] Specifically, it is necessary to first construct a scatter plot of rainfall intensity and water level change rate, as well as a scatter plot of evaporation and water level change rate, and obtain the quantitative relationship between the two groups of variables through data fitting. For the rainfall process, the focus is on the rainfall intensity when the water level begins to rise significantly, and this value is defined as the first rainfall critical value; for the evaporation process, the focus is on the evaporation when the water level begins to drop significantly, and this value is defined as the first evaporation critical value. In actual calculations, a linear or nonlinear regression method can be used to establish a hydrological response model, and a reasonable range of critical values ​​can be determined by confidence interval analysis. At the same time, considering that the meteorological-hydrological response characteristics of different seasons may be different, a mapping relationship can be established according to seasonal classification to obtain a more targeted critical value. This critical value determination method based on statistical analysis not only takes into account the hysteresis effect of the hydrological system on meteorological changes, but also reflects the integrity of regional hydrological characteristics. By setting the first rainfall critical value and the first evaporation critical value, the meteorological conditions that may cause significant changes in water levels can be effectively identified, providing a quantitative basis for flood control and drought warning. When the measured rainfall intensity exceeds the first rainfall critical value, it indicates that the rainfall process may cause the water level to rise significantly; when the measured evaporation exceeds the first evaporation critical value, it indicates that the water level may continue to drop. This early warning method based on response characteristics breaks through the limitations of traditional empirical judgment and can more accurately assess the risk of water level changes.

[0061] Step 205: Determine the second rainfall critical value that causes soil saturation and the second evaporation critical value that causes soil dehydration by statistically analyzing the mapping relationship among rainfall intensity, evaporation and soil saturation; use the first rainfall critical value and the first evaporation critical value as meteorological-hydrological response characteristics, and use the second rainfall critical value and the second evaporation critical value as meteorological-soil response characteristics.

[0062] Among them, the second rainfall critical value that causes soil saturation refers to the minimum rainfall intensity value determined by statistical analysis that can cause soil saturation to approach the saturation state. This critical value reflects the response characteristics of the soil in the monitored area to rainfall infiltration and is a key parameter in the mapping relationship between rainfall intensity and soil saturation. For example, if statistical analysis shows that when the rainfall intensity reaches 20 mm per hour, the soil saturation quickly approaches 1 (fully saturated state), then 20 mm per hour can be determined as the second rainfall critical value of the area.

[0063] The second critical value of evaporation that causes soil water loss refers to the minimum evaporation value determined by statistical analysis that can cause a significant decrease in soil saturation. This critical value reflects the response characteristics of the soil in the monitored area to evaporation loss and is a key parameter in the mapping relationship between evaporation and soil saturation. For example, if statistical analysis shows that when evaporation reaches 8 mm per day, soil saturation begins to decline rapidly and tends to a lower level, 8 mm per day can be determined as the second critical value of evaporation in the area.

[0064] Specifically, it is necessary to first construct a scatter plot of rainfall intensity and soil saturation, as well as a scatter plot of evaporation and soil saturation, and obtain the quantitative relationship between the variables through data fitting. For the rainfall process, the focus is on the rainfall intensity when the soil saturation is close to the saturated state, and this value is defined as the second rainfall critical value; for the evaporation process, the focus is on the evaporation when the soil saturation begins to decrease significantly, and this value is defined as the second evaporation critical value. In actual calculations, a variety of statistical regression methods can be used to establish a soil moisture response model, and the reasonable range of critical values ​​can be determined by confidence interval analysis. Considering that soil moisture characteristics may differ in different seasons, a mapping relationship can be established according to seasonal classification to obtain more targeted critical values. The determined critical values ​​are classified into meteorological-hydrological response characteristics and meteorological-soil response characteristics, respectively, and a complete dual judgment system is constructed. Among them, the first rainfall critical value and the first evaporation critical value reflect the direct response of the hydrological system to meteorological changes, as meteorological-hydrological response characteristics; the second rainfall critical value and the second evaporation critical value reflect the sensitivity of the soil system to meteorological changes, as meteorological-soil response characteristics. This classification method not only reflects the relative independence of hydrological processes and soil processes, but also highlights the different roles of the two types of response characteristics in flood and drought early warning. By simultaneously monitoring these two types of response characteristics, the state changes of the regional hydrological cycle system can be comprehensively evaluated.

[0065] Step 103: Determine the flood risk index and drought risk index of the area to be monitored by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics.

[0066] Among them, the flood risk index and drought risk index refer to dimensionless indicators that quantitatively characterize the possibility of flood and drought disasters in a region by comprehensively considering the meteorological-hydrological response characteristics and the meteorological-soil response characteristics. The flood risk index mainly reflects the risk level of flood disasters in a region, while the drought risk index characterizes the risk level of drought disasters in a region. For example, the flood risk index may vary between 0 and 1, and the closer the value is to 1, the higher the risk of flood disasters; the drought risk index may also adopt similar quantitative standards, and the larger the value, the higher the risk of drought.

[0067] Specifically, the relationship between the indicators such as rainfall intensity and water level change rate in the meteorological-hydrological response characteristics and flood control risk, and the relationship between the indicators such as soil saturation and evapotranspiration intensity in the meteorological-soil response characteristics and drought resistance risk are first analyzed. Then, a multi-index comprehensive evaluation method is adopted to weight and integrate the various response characteristic indicators by setting reasonable weight coefficients to obtain the flood control risk index and drought resistance risk index. For example, when calculating the flood control risk index, more attention may be paid to the influence of rainfall intensity and water level change rate; while when calculating the drought resistance risk index, more attention may be paid to the changes in soil saturation and evapotranspiration intensity. Through this comprehensive integration method, the driving effect of meteorological factors is considered, and the response characteristics of the hydrological system and soil system are reflected. When the flood control risk index or the drought resistance risk index exceeds the preset threshold, it indicates that the region faces a high risk of flood and drought disasters and needs to initiate the corresponding emergency response in time. This risk assessment method based on multi-system response characteristics improves the comprehensiveness and reliability of disaster warning. Especially in the context of climate change, the causes of flood and drought disasters are more complicated, and this comprehensive assessment method can better reflect the dynamic changes of regional disaster risks. At the same time, by analyzing the spatiotemporal evolution characteristics of the flood risk index and drought risk index, the development law of regional water and drought disasters can be revealed, providing a scientific basis for the formulation of disaster prevention and mitigation strategies. This risk assessment method based on multi-system response realizes the dynamic monitoring and early warning of regional water and drought disaster risks.

[0068] Based on the above embodiment, as an optional embodiment, in step 103: combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics to determine the flood risk index and drought risk index of the area to be monitored, this step may also include the following steps: Step 301: When the rainfall intensity is greater than a first rainfall critical value causing a water level rise, and the soil saturation is greater than a second rainfall critical value causing soil saturation, it is determined that the risk type of the monitored area is a flood type.

[0069] Specifically, in order to accurately identify the flood risk in the monitored area, it is necessary to consider the critical states of the two key indicators, rainfall intensity and soil saturation, at the same time. This is because the occurrence of flood disasters is not only directly related to rainfall intensity, but also significantly affected by the soil water storage status. When the rainfall intensity exceeds the first rainfall critical value that causes the water level to rise, it indicates that the rainfall has exceeded the flood discharge capacity of the surface water system, which may cause the water level to rise rapidly; at the same time, when the soil saturation exceeds the second rainfall critical value that causes soil saturation, it indicates that the soil has approached or reached a saturated state and has lost its buffering effect on rainfall. For example, if the rainfall intensity in a certain area exceeds 50 mm / h (the first rainfall critical value) and the soil saturation exceeds 0.9 (the second rainfall critical value), the dual discrimination conditions for flood risk are met. This discrimination method based on dual critical values ​​reflects the potential for surface runoff through rainfall intensity and characterizes the water storage state of the underlying surface through soil saturation. When these two conditions are met at the same time, it indicates that the area is very prone to flood disasters. This discrimination method can effectively reduce the false alarm rate and improve the accuracy of flood risk identification. Especially in heavy rainfall events, the change of soil saturation often lags behind the rainfall process. This discrimination method considering double critical values ​​can better reflect the breeding process of flood disasters. By real-time monitoring of rainfall intensity and soil saturation changes, regional flood risks can be dynamically assessed and timely warnings can be provided for flood prevention and rescue.

[0070] Step 302: When the evaporation amount is greater than the first evaporation critical value causing the water level to drop, and the soil saturation is less than the second evaporation critical value causing soil water loss, it is determined that the risk type of the monitored area is a drought type.

[0071] Specifically, in order to accurately identify the drought risk in the monitored area, it is necessary to consider the critical states of the two key indicators, evaporation and soil saturation, at the same time. This is because the occurrence of drought disasters is related to both the atmospheric water loss process and the soil water storage status. When the evaporation exceeds the first evaporation critical value that causes the water level to drop, it indicates that the atmospheric evaporation demand is strong, which may cause the surface water level to continue to drop; at the same time, when the soil saturation is lower than the second evaporation critical value that causes soil water loss, it indicates that the soil moisture is already in a deficit state and the vegetation may face water shortage stress. For example, if the evaporation in a certain area exceeds 8 mm / day (the first evaporation critical value) and the soil saturation is lower than 0.4 (the second evaporation critical value), the dual discrimination conditions of drought risk are met. This discrimination method based on dual critical values ​​reflects the intensity of atmospheric water demand through evaporation and characterizes the degree of soil moisture deficit through soil saturation. When these two conditions are met at the same time, it indicates that the region is very prone to drought disasters. This discrimination method can effectively reduce the misjudgment rate and improve the accuracy of drought risk identification. Especially in the case of continuous high temperature and little rainfall, the loss of soil moisture often shows a cumulative effect. This discrimination method considering double critical values ​​can better reflect the development process of drought disasters. By real-time monitoring of changes in evaporation and soil saturation, regional drought risks can be dynamically assessed to provide timely warnings for drought relief.

[0072] Step 303: Calculate the flood risk index and drought risk index of the area to be monitored based on the risk type, rainfall intensity, evaporation and soil saturation of the area to be monitored.

[0073] Specifically, in order to quantitatively assess the risk level of flood and drought disasters in the monitored area, it is necessary to establish a risk index calculation model based on the determined risk type, combined with key indicators such as rainfall intensity, evaporation and soil saturation. This is because the severity of flood and drought disaster risks is not only related to the risk type, but also affected by the comprehensive influence of various hydrological and meteorological elements. When the regional risk type is flood, the flood risk index is calculated, and the ratio of rainfall intensity to the first rainfall critical value and the ratio of soil saturation to the second rainfall critical value are used as basic indicators. By setting reasonable weight coefficients for weighted integration, a quantitative indicator reflecting the degree of flood risk is obtained. For example, if the rainfall intensity in a certain area is 75 mm / h (1.5 times the first rainfall critical value of 50 mm / h) and the soil saturation is 0.95 (1.06 times the second rainfall critical value of 0.9), a higher flood risk index may be obtained, indicating that the area is facing a serious flood threat. Similarly, when the regional risk type is drought type, the drought risk index is calculated, and the ratio of evaporation to the first evaporation critical value and the ratio of the second evaporation critical value to soil saturation are used as basic indicators. Through weighted integration, a quantitative indicator reflecting the degree of drought risk is obtained. This calculation method based on multi-indicator integration not only takes into account the intensity of disaster factors, but also reflects the vulnerability of disaster-bearing bodies, and can more accurately characterize the severity of regional water and drought disaster risks. By real-time calculation and dynamic updating of flood control risk index and drought risk index, the evolution trend of regional water and drought disaster risks can be grasped in a timely manner, providing a quantitative basis for disaster prevention and mitigation decisions.

[0074] Based on the above embodiment, as an optional embodiment, in step 303: according to the risk type, rainfall intensity, evaporation and soil saturation of the monitored area, the flood control risk index and drought resistance risk index of the monitored area are calculated. This step may also include the following steps: Step 313: respectively compare the rainfall intensity with the rainfall intensity threshold, the evaporation with the evaporation threshold, and the soil saturation with the saturation threshold to obtain the rainfall intensity difference, the evaporation difference, and the saturation difference; if the risk type of the area to be monitored is a flood type, then based on the preset risk weight combination corresponding to the flood type, the rainfall intensity difference, the evaporation difference, and the saturation difference are weighted and summed to obtain the flood risk index of the area to be monitored.

[0075] Among them, the preset risk weight combination refers to a set of normalized weight coefficients pre-set according to the importance and contribution of different hydrological and meteorological elements in the formation of flood and drought disasters. This set of weight coefficients reflects the relative impact of factors such as rainfall intensity, evaporation and soil saturation on flood or drought risks. The sum of their weight values ​​is equal to 1, which is used to realize the differentiated contribution of each factor to the risk.

[0076] Specifically, the difference between rainfall intensity and rainfall intensity threshold is first calculated to reflect the extent to which rainfall intensity exceeds the safety threshold; the difference between evaporation and evaporation threshold is calculated to reflect the impact of atmospheric water loss; the difference between soil saturation and saturation threshold is also calculated to reflect the impact of soil water storage status on flood control. For example, if the rainfall intensity in a certain area is 80 mm / hour and the rainfall intensity threshold is 50 mm / hour, the rainfall intensity difference is 30 mm / hour; the evaporation is 2 mm / day and the evaporation threshold is 5 mm / day, the evaporation difference is -3 mm / day; the soil saturation is 0.95 and the saturation threshold is 0.9, then the saturation difference is 0.05. When the regional risk type is determined to be a flood type, the pre-set flood type risk weight combination is used to weight these differences. Among them, the rainfall intensity difference may obtain a higher weight (such as 0.5) because it directly reflects the intensity of the disaster-causing factor; the soil saturation difference may obtain the second highest weight (such as 0.3) because it reflects the regulation and storage capacity of the underlying surface; the evaporation difference may obtain a relatively low weight (such as 0.2) because its impact is relatively small in flood disasters. This calculation method based on difference and weight can accurately reflect the contribution of each factor to flood control risk and obtain a more reasonable flood control risk index. The flood control risk index calculated in this way not only takes into account the degree to which each factor exceeds the threshold, but also reflects the relative importance of different factors, which improves the accuracy and reliability of risk assessment. At the same time, this calculation method has good adaptability. By adjusting the weight combination, it can adapt to the characteristics of different regions and different types of flood disasters. This risk assessment method based on difference and weight provides a quantitative basis for flood control decision-making.

[0077] Step 323: If the risk type of the monitored area is drought type, based on the preset risk weight combination corresponding to the drought type, the rainfall intensity difference, evaporation difference and saturation difference are weighted and summed to obtain the drought risk index of the monitored area.

[0078] Specifically, when the regional risk type is determined to be a drought type, a pre-set drought type risk weight combination is used to weight these differences. Among them, the evaporation difference may obtain a higher weight (such as 0.5) because it directly reflects the intensity of atmospheric drought; the soil saturation difference may obtain the second highest weight (such as 0.3) because it reflects the degree of agricultural drought; the rainfall intensity difference may obtain a relatively low weight (such as 0.2) because it has a relatively small impact on the drought state that has been formed. This calculation method based on differences and weights can accurately reflect the contribution of each factor to the drought risk and obtain a more reasonable drought risk index. The drought risk index calculated in this way not only takes into account the degree of deviation of each factor from the threshold, but also reflects the relative importance of different factors, thereby improving the accuracy of drought risk assessment.

[0079] Step 104: When the flood risk index is greater than or equal to the flood threshold, a flood warning is issued to the monitored area; when the drought risk index is greater than or equal to the drought threshold, a drought warning is issued to the monitored area.

[0080] Among them, the flood control threshold and drought resistance threshold refer to the critical values ​​for triggering flood and drought disaster warnings that are predetermined by analyzing historical disaster data and expert experience. These thresholds reflect the critical state of the region's exposure to flood and drought disasters. When the risk index exceeds these thresholds, it indicates that the region faces a greater disaster risk and needs to activate the corresponding early warning mechanism.

[0081] Specifically, in order to prevent and respond to water and drought disasters in a timely manner, it is necessary to compare the calculated flood risk index and drought resistance risk index with the corresponding warning threshold to achieve early warning of the risk of water and drought disasters in the monitored area. This early warning mechanism is necessary because only when the risk index exceeds a specific threshold can the occurrence and spread of disasters be effectively prevented by issuing early warning signals in a timely manner. When the flood risk index is greater than or equal to the flood control threshold, it indicates that the region faces a greater risk of flooding and the flood early warning mechanism needs to be activated immediately. For example, if the flood risk index of a certain area is 0.85 and the flood control threshold is 0.8, it means that the area has reached the early warning conditions, and it is necessary to issue flood warning information in a timely manner and activate the corresponding flood emergency plan. Similarly, when the drought resistance risk index is greater than or equal to the drought resistance threshold, it indicates that the area faces a more serious drought threat and needs to activate the drought resistance early warning mechanism. If the drought resistance risk index of a certain area is 0.75 and the drought resistance threshold is 0.7, it means that the area has reached the drought warning conditions, and it is necessary to issue drought resistance early warning information in a timely manner and deploy relevant drought resistance measures. This threshold-based early warning mechanism can effectively achieve early identification and early warning of risks, and win precious preparation time for disaster prevention and mitigation work. Through the timely release of early warning information, relevant departments and the public can be guided to make preventive preparations and take necessary protective measures. This early warning method not only takes into account the quantitative degree of risk, but also establishes a clear early warning trigger mechanism, which improves the initiative and pertinence of disaster prevention and mitigation work. At the same time, the establishment of the early warning mechanism can also set differentiated early warning thresholds according to the actual conditions of different regions, so as to achieve more accurate risk warning. This threshold-based early warning system provides important decision-making support for the prevention and control of water and drought disasters, and effectively improves the regional disaster prevention and mitigation capabilities.

[0082] Reference Figure 2 , is a flood control and drought relief early warning system provided in an embodiment of the present application, the system comprises: a data acquisition module, a feature determination module, an index calculation module, and a risk early warning module, wherein: A data acquisition module is used to acquire meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored; A feature determination module, for determining a meteorological-hydrological response feature based on the meteorological monitoring data and the hydrological monitoring data, and for determining a meteorological-soil response feature based on the meteorological monitoring data and the soil monitoring data; An index calculation module is used to determine the flood risk index and drought risk index of the monitored area by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics; The risk warning module is used to issue flood warnings to the monitored area when the flood risk index is greater than or equal to the flood threshold, and to issue drought warnings to the monitored area when the drought risk index is greater than or equal to the drought threshold.

[0083] On the basis of the above embodiments, the feature determination module is also used to calculate the rainfall intensity and evaporation according to the rainfall, temperature and humidity in the meteorological monitoring data; calculate the water level change rate according to the surface water level and groundwater level in the hydrological monitoring data; calculate the soil saturation according to the soil moisture content in the soil monitoring data; determine the first rainfall critical value that causes the water level to rise and the first evaporation critical value that causes the water level to drop by statistically analyzing the mapping relationship between rainfall intensity, evaporation and water level change rate; determine the second rainfall critical value that causes soil saturation and the second evaporation critical value that causes soil dehydration by statistically analyzing the mapping relationship between rainfall intensity, evaporation and soil saturation; use the first rainfall critical value and the first evaporation critical value as meteorological-hydrological response characteristics, and use the second rainfall critical value and the second evaporation critical value as meteorological-soil response characteristics.

[0084] On the basis of the above embodiment, the feature determination module is also used to calculate the rainfall change value within a preset unit time, and use the rainfall change value as the rainfall intensity; determine the saturated water vapor pressure according to the temperature, and determine the actual water vapor pressure according to the humidity and the saturated water vapor pressure; multiply the pressure difference between the saturated water vapor pressure and the actual water vapor pressure by the preset water vapor diffusion coefficient to obtain the water vapor flux, and use the product of the water vapor flux and the preset evaporation coefficient as the evaporation amount.

[0085] Based on the above embodiment, the feature determination module is also used to calculate the change in the surface water level within a preset time interval to obtain the surface water level change rate, and calculate the change in the groundwater level within a preset time interval to obtain the groundwater level change rate; the surface water level change rate and the groundwater level change rate are weightedly summed to obtain the water level change rate.

[0086] Based on the above embodiment, the feature determination module is also used to obtain the soil type in the monitored area; based on a preset soil type mapping table, determine the field water holding capacity corresponding to the soil type in the monitored area; divide the soil moisture content by the field water holding capacity to obtain the soil saturation.

[0087] On the basis of the above embodiment, the index calculation module is also used to determine that the risk type of the monitored area is a flood type when the rainfall intensity is greater than the first rainfall critical value that causes the water level to rise, and the soil saturation is greater than the second rainfall critical value that causes soil saturation; when the evaporation is greater than the first evaporation critical value that causes the water level to drop, and the soil saturation is less than the second evaporation critical value that causes soil water loss, the risk type of the monitored area is determined to be a drought type; according to the risk type, rainfall intensity, evaporation and soil saturation of the monitored area, the flood control risk index and drought resistance risk index of the monitored area are calculated.

[0088] On the basis of the above embodiment, the index calculation module is also used to compare the rainfall intensity with the rainfall intensity threshold, the evaporation with the evaporation threshold, and the soil saturation with the saturation threshold, respectively, to obtain the rainfall intensity difference, the evaporation difference and the saturation difference; if the risk type of the area to be monitored is a flood type, then based on the preset risk weight combination corresponding to the flood type, the rainfall intensity difference, the evaporation difference and the saturation difference are weighted and summed to obtain the flood risk index of the area to be monitored; if the risk type of the area to be monitored is a drought type, then based on the preset risk weight combination corresponding to the drought type, the rainfall intensity difference, the evaporation difference and the saturation difference are weighted and summed to obtain the drought risk index of the area to be monitored.

[0089] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0090] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0091] The communication bus 302 is used to realize the connection and communication between these components.

[0092] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0093] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0094] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface diagrams and applications, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0095] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a flood control and drought relief early warning method.

[0096] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call an application program storing a flood control and drought relief early warning method in the memory 305, and when executed by one or more processors 301, the electronic device 300 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0097] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0098] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0099] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0100] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0101] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0102] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0103] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not recorded in the present disclosure. The description and examples are to be regarded as exemplary only.

Claims

1. A flood control and drought relief early warning method, characterized in that: include: Obtain meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored; Determining meteorological-hydrological response characteristics based on the meteorological monitoring data and the hydrological monitoring data, and determining meteorological-soil response characteristics based on the meteorological monitoring data and the soil monitoring data; Determine the flood risk index and drought risk index of the area to be monitored by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics; When the flood risk index is greater than or equal to the flood threshold, a flood warning is issued to the area to be monitored; when the drought risk index is greater than or equal to the drought threshold, a drought warning is issued to the area to be monitored.

2. The flood control and drought relief early warning method according to claim 1, characterized in that: The determining of meteorological-hydrological response characteristics based on the meteorological monitoring data and the hydrological monitoring data, and the determining of meteorological-soil response characteristics based on the meteorological monitoring data and the soil monitoring data, comprises: Calculating rainfall intensity and evaporation according to the rainfall, temperature and humidity in the meteorological monitoring data; Calculating the water level change rate based on the surface water level and groundwater level in the hydrological monitoring data; Calculating soil saturation according to the soil moisture content in the soil monitoring data; Determine a first rainfall critical value causing a water level rise and a first evaporation critical value causing a water level drop by statistically analyzing the mapping relationship between the rainfall intensity, the evaporation amount and the water level change rate; Determine a second rainfall critical value causing soil saturation and a second evaporation critical value causing soil water loss by statistically analyzing the mapping relationship between the rainfall intensity, the evaporation amount and the soil saturation; The first rainfall critical value and the first evaporation critical value are used as meteorological-hydrological response characteristics, and the second rainfall critical value and the second evaporation critical value are used as meteorological-soil response characteristics.

3. The flood control and drought relief early warning method according to claim 2, characterized in that: The step of calculating rainfall intensity and evaporation according to the rainfall, temperature and humidity in the meteorological monitoring data comprises: Calculating a rainfall change value within a preset unit time, and using the rainfall change value as rainfall intensity; determining a saturated water vapor pressure according to the temperature, and determining an actual water vapor pressure according to the humidity and the saturated water vapor pressure; The pressure difference between the saturated water vapor pressure and the actual water vapor pressure is multiplied by a preset water vapor diffusion coefficient to obtain a water vapor flux, and the product of the water vapor flux and a preset evaporation coefficient is used as the evaporation amount.

4. The flood control and drought relief early warning method according to claim 2, characterized in that: The calculating the water level change rate according to the surface water level and the groundwater level in the hydrological monitoring data comprises: Calculating the change of the surface water level within a preset time interval to obtain the surface water level change rate, and calculating the change of the groundwater level within the preset time interval to obtain the groundwater level change rate; The surface water level change rate and the groundwater level change rate are weightedly summed to obtain the water level change rate.

5. The flood control and drought relief early warning method according to claim 2, characterized in that: The step of calculating soil saturation according to the soil moisture content in the soil monitoring data comprises: Obtaining the soil type in the area to be monitored; Based on a preset soil type mapping table, determining the field water holding capacity corresponding to the soil type in the area to be monitored; The soil saturation was obtained by dividing the soil water content by the field capacity.

6. The flood control and drought relief early warning method according to claim 2, characterized in that: The step of determining the flood risk index and drought risk index of the area to be monitored by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics includes: When the rainfall intensity is greater than the first rainfall critical value causing the water level to rise, and the soil saturation is greater than the second rainfall critical value causing soil saturation, it is determined that the risk type of the monitored area is a flood type; When the evaporation amount is greater than the first evaporation critical value that causes the water level to drop, and the soil saturation is less than the second evaporation critical value that causes soil water loss, the risk type of the monitored area is determined to be a drought type; The flood control risk index and drought resistance risk index of the area to be monitored are calculated according to the risk type, rainfall intensity, evaporation and soil saturation of the area to be monitored.

7. The flood control and drought relief early warning method according to claim 6, characterized in that: The method of calculating the flood risk index and drought risk index of the area to be monitored according to the risk type, rainfall intensity, evaporation and soil saturation of the area to be monitored includes: Respectively comparing the rainfall intensity with the rainfall intensity threshold, the evaporation with the evaporation threshold, and the soil saturation with the saturation threshold to obtain a rainfall intensity difference, an evaporation difference, and a saturation difference; If the risk type of the area to be monitored is a flood type, then based on the preset risk weight combination corresponding to the flood type, the rainfall intensity difference, the evaporation difference and the saturation difference are weighted and summed to obtain the flood control risk index of the area to be monitored; If the risk type of the area to be monitored is drought type, then based on the preset risk weight combination corresponding to the drought type, the rainfall intensity difference, the evaporation difference and the saturation difference are weighted and summed to obtain the drought risk index of the area to be monitored.

8. A flood and drought relief early warning system, characterized in that: The system comprises: A data acquisition module is used to acquire meteorological monitoring data, hydrological monitoring data and soil monitoring data in the area to be monitored; a feature determination module, configured to determine a meteorological-hydrological response feature based on the meteorological monitoring data and the hydrological monitoring data, and to determine a meteorological-soil response feature based on the meteorological monitoring data and the soil monitoring data; An index calculation module, used to determine the flood risk index and drought risk index of the monitored area by combining the meteorological-hydrological response characteristics and the meteorological-soil response characteristics; The risk warning module is used to issue a flood warning to the monitored area when the flood risk index is greater than or equal to the flood threshold, and to issue a drought warning to the monitored area when the drought risk index is greater than or equal to the drought threshold.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the flood control and drought relief early warning method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the flood control and drought relief early warning method according to any one of claims 1 to 7 is executed.

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