Sponge park hydrological efficiency dynamic analysis method based on multi-source spatio-temporal data

Abstract

The invention relates to the technical field of data processing, in particular to a sponge park hydrological efficiency dynamic analysis method based on multi-source spatiotemporal data, and the method comprises the steps: obtaining a surface runoff coefficient reference value and a soil steady-state infiltration rate reference value of a target sponge park at the current moment; according to the change rate of the soil moisture content of the target sponge park at the current moment, the strength of the hydrological event, the sediment concentration and the operation duration, the soil steady-state infiltration rate reference value is adjusted, and the dynamic infiltration rate is obtained; adjusting the reference value of the surface runoff coefficient according to the initial soil moisture content, the rainfall intensity, the duration time and the maximum confluence length of the target sponge park at the current moment to obtain a dynamic runoff coefficient; and inputting the dynamic infiltration rate and the dynamic runoff coefficient into the distributed hydrological model, and carrying out real-time monitoring and early warning on the hydrological efficiency of the target sponge park according to an output result of the model, so that the accuracy of analyzing the hydrological efficiency of the sponge park is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data. Background Technology

[0002] In the current context of the coordinated development of smart cities and ecological water conservancy, sponge parks, as a key component of urban ecological infrastructure, shoulder the important mission of rainwater regulation, purification, and infiltration. Their hydrological efficiency directly affects the health of the urban water cycle and the effectiveness of urban flood control. Among these parameters, the runoff coefficient directly reflects the surface runoff generation capacity, and the differences in runoff generation across different underlying surfaces make it a key indicator for measuring the formation and flow of surface rainwater in sponge parks. Infiltration rate (especially the steady-state soil infiltration rate), as a core functional parameter of sponge facilities, determines the soil's ability to absorb rainwater and is crucial to the rainwater infiltration effect. Both provide key evidence for assessing the capacity of sponge parks to absorb, retain, purify, and release rainwater during rainfall, and are indispensable parameters for accurately simulating runoff generation and confluence processes, scientifically analyzing hydrological efficiency, and rationally optimizing the design of sponge facilities. Therefore, obtaining accurate runoff coefficients and infiltration rates is a prerequisite for the dynamic analysis of the hydrological efficiency of sponge parks.

[0003] Traditional sponge park hydrological analysis relies heavily on monitoring data from a single time period and local scale to obtain hydrological parameters (runoff coefficient and soil steady-state infiltration rate), making it difficult to comprehensively depict the spatiotemporal dynamic characteristics of processes such as rainfall, runoff, and storage and infiltration. In particular, it is insufficient in capturing changes in hydrological response caused by extreme weather events or facility performance degradation. At the same time, existing assessment methods lack the collaborative use of multi-source spatiotemporal data (such as real-time monitoring by the Internet of Things, high-resolution remote sensing images, and weather forecasts), resulting in low accuracy of hydrological parameter inversion and an inability to support the dynamic optimization and adaptive design of sponge parks.

[0004] Therefore, improving the accuracy of hydrological performance analysis of sponge parks has become an urgent problem to be solved. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a dynamic analysis method for the hydrological performance of sponge parks based on multi-source spatiotemporal data, in order to solve the problem of how to improve the accuracy of analyzing the hydrological performance of sponge parks.

[0006] This invention provides a method for dynamic analysis of the hydrological effectiveness of sponge parks based on multi-source spatiotemporal data. The method includes the following steps: Based on the runoff coefficients of various underlying surfaces of the target sponge park and the area of ​​each underlying surface at the current time, obtain the benchmark value of the surface runoff coefficient at the current time. Based on the soil saturated hydraulic conductivity of the target sponge park and the soil moisture content at the current time, obtain the benchmark value of the soil steady-state infiltration rate at the current time. Based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park, the benchmark value of soil steady-state infiltration rate is adjusted to obtain the dynamic infiltration rate at the current moment. The rainfall status of the target sponge park at the current moment is detected. If the target sponge park is in a rainfall state at the current moment, the surface runoff coefficient benchmark value is adjusted according to the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment to obtain the dynamic runoff coefficient at the current moment. The dynamic infiltration rate and the dynamic runoff coefficient are input into the distributed hydrological model, and the hydrological performance of the target sponge park is monitored and warned in real time based on the output of the distributed hydrological model.

[0007] Preferably, obtaining the benchmark value of the surface runoff coefficient at the current moment based on the runoff coefficients of various underlying surfaces of the target sponge park and the area of ​​each underlying surface at the current moment includes: For any type of underlying surface of the target sponge park, obtain the area of ​​the underlying surface at the current time and the park area of ​​the target sponge park, calculate the proportion of the area of ​​the underlying surface at the current time in the park area, and obtain the area proportion of the underlying surface at the current time. The area proportion of each type of underlying surface of the target sponge park at the current time is obtained. The area proportion of each type of underlying surface at the current time is used as the weight of the runoff coefficient of each type of underlying surface. The runoff coefficients of each type of underlying surface are weighted and summed to obtain the benchmark value of the surface runoff coefficient at the current time.

[0008] Preferably, obtaining the benchmark value of the steady-state soil infiltration rate at the current moment based on the soil saturated hydraulic conductivity of the target sponge park and the soil moisture content at the current moment includes: Obtain the soil moisture content of the target sponge park at the current moment, as well as the soil saturation moisture content of the target sponge park, calculate the proportion of the soil moisture content in the soil saturation moisture content, and obtain the soil moisture level at the current moment. Subtracting the soil moisture level from the constant 1 yields the target difference. The saturated hydraulic conductivity of the target sponge park is then obtained. The product of the target difference and the saturated hydraulic conductivity is calculated to obtain the benchmark value of the steady-state soil infiltration rate at the current moment.

[0009] Preferably, the step of adjusting the soil steady-state infiltration rate benchmark value based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park to obtain the dynamic infiltration rate at the current moment includes: Based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park, a dynamic adjustment factor is obtained to adjust the benchmark value of the soil steady-state infiltration rate. Subtract the dynamic adjustment factor from the constant 1 to obtain the adjustment coefficient. Calculate the product between the adjustment coefficient and the soil steady-state infiltration rate benchmark value to obtain the dynamic infiltration rate at the current moment.

[0010] Preferably, the step of obtaining a dynamic adjustment factor for adjusting the soil steady-state infiltration rate benchmark value based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park includes: The soil moisture content of the target sponge park at the end of the most recent rainfall is obtained and recorded as the soil moisture content after the rain stops. The soil moisture content after a preset time period following the end of the most recent rainfall is obtained and recorded as the soil moisture content after the rain stops. The preset time period is used as the denominator, and the difference between the soil moisture content after the rain stops and the soil moisture content after the rain stops is used as the numerator to obtain the rate of change of soil moisture content. The rate of change of soil moisture content is normalized to obtain a normalized value. The normalized value is then subtracted from the constant 1 to obtain the characteristic value of soil permeability resistance at the current moment. Obtain the runoff and surface sediment concentration of a preset number of historical rainfall events prior to the current time for the target sponge park. Calculate the product between the runoff and surface sediment concentration for each historical rainfall event to obtain the degree of siltation for each event. Normalize the cumulative value of all siltation degrees to obtain the characteristic value of the infiltration rate attenuation at the current time. The current rainfall of the target sponge park within a preset time period up to the current moment is obtained, as well as the critical rainfall that would cause the soil moisture content of the target sponge park to reach the soil saturation moisture content. The proportion of the current rainfall in the critical rainfall is calculated, and the proportion is normalized to obtain the intensity characteristic value of the previous hydrological event. Obtain the start time of the most recent rainfall event in the target sponge park, obtain the time interval between the start time and the current time, normalize the reciprocal of the time interval, and obtain the characteristic value of the impact of previous hydrological events. Obtain the number of days since the target sponge park was built, normalize the number of days, and obtain the operating time characteristic value of the target sponge park; The sum of the soil seepage resistance characteristic value, the infiltration rate attenuation characteristic value, the previous hydrological event intensity characteristic value, and the previous hydrological event impact characteristic value is calculated to obtain the sum result. The product of the sum result and the running time characteristic value is normalized to obtain the dynamic adjustment factor for adjusting the soil steady-state infiltration rate benchmark value.

[0011] Preferably, the step of adjusting the benchmark value of the surface runoff coefficient based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment to obtain the dynamic runoff coefficient at the current moment includes: Based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment, a dynamic adjustment factor is obtained to adjust the benchmark value of the surface runoff coefficient. The sum of constant 1 and the dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient is calculated to obtain the adjustment coefficient for adjusting the benchmark value of the surface runoff coefficient. The product between the adjustment coefficient for adjusting the benchmark value of the surface runoff coefficient and the benchmark value of the surface runoff coefficient is calculated to obtain the candidate runoff coefficient. Obtain the runoff coefficients of various underlying surfaces of the target sponge park, select the maximum value among all runoff coefficients and record it as the maximum runoff coefficient, and select the minimum value between the maximum runoff coefficient and the candidate runoff coefficients as the dynamic runoff coefficient at the current moment.

[0012] Preferably, the step of obtaining the dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment includes: Get the minute-level rainfall intensity of the target sponge park at the current moment, and record it as the real-time rainfall intensity. Get the average rainfall intensity of the target sponge park in a preset historical period, calculate the proportion of the real-time rainfall intensity in the average rainfall intensity, and obtain the rainfall intensity coefficient at the current moment. The minute-level rainfall intensity of the target sponge park at the previous moment is obtained and recorded as the historical rainfall intensity. The difference between the real-time rainfall intensity and the historical rainfall intensity is normalized to obtain the rainfall intensity change rate at the current moment. The product between the rainfall intensity change rate and the rainfall intensity coefficient is normalized to obtain the rainfall intensity characteristic value at the current moment. Based on the real-time rainfall intensity, the time required for the soil moisture content of the target sponge park to reach the soil saturation moisture content is obtained and recorded as the reference time. The time interval between the start time of this rainfall and the current time is obtained and recorded as the rainfall duration. The proportion of the rainfall duration in the reference time is calculated, and the minimum value is obtained between the constant 1 and the proportion to obtain the runoff transformation characteristic value at the current time. Obtain the initial soil moisture content of the target sponge park at the current time, and normalize the initial soil moisture content to obtain the normalized value of the initial moisture content; Obtain the maximum runoff length of the target sponge park at the current moment, and normalize the reciprocal of the maximum runoff length to obtain the runoff velocity characteristic value; The sum between the rainfall intensity characteristic value and the runoff transformation characteristic value is calculated to obtain the sum result. The product between the sum result, the normalized value of the initial water content, and the runoff velocity characteristic value is normalized to obtain a dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient.

[0013] Preferably, if the target sponge park is in a state of no rainfall at the current moment, the benchmark value of the surface runoff coefficient at the current moment shall be used as the dynamic runoff coefficient.

[0014] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows: This invention first obtains benchmark values ​​for surface runoff coefficient and soil steady-state infiltration rate, which reflect the initial hydrological characteristics of the target sponge park, to provide a basis for subsequent hydrological simulation and analysis. Then, it comprehensively and meticulously quantifies the impact of performance degradation caused by long-term operation of the sponge facilities on the infiltration rate from multiple dimensions, including the facility's own operational status (i.e., the rate of change in soil moisture content), sediment accumulation, operating time, and the influence of previous hydrological events. The benchmark value for soil steady-state infiltration rate is adjusted to better reflect the actual hydrological conditions, yielding the dynamic infiltration rate at the current moment. Secondly, it combines the hydrological processes of the target sponge park area, i.e., from rainfall intensity... From the perspectives of intensity, duration, and runoff length, the dynamic runoff coefficient is fully reflected, taking into account external dynamic factors such as rainfall and topography. The benchmark value of the surface runoff coefficient is adjusted to obtain the dynamic runoff coefficient at the current moment. The dynamic infiltration rate and dynamic runoff coefficient take into account the comprehensive influence of multiple factors, which can more accurately simulate the runoff generation and runoff process of the park and provide reliable data support for the effectiveness assessment and early warning of sponge facilities. Finally, the dynamic infiltration rate and dynamic runoff coefficient are input into the distributed hydrological model to obtain key hydrological response indicators and make early warnings based on them, providing a scientific basis for the maintenance and management of sponge facilities and improving the accuracy of the analysis of the hydrological effectiveness of sponge parks. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a dynamic analysis method for the hydrological efficiency of sponge parks based on multi-source spatiotemporal data, provided in Embodiment 1 of the present invention. Detailed Implementation

[0017] Embodiments of this disclosure are described in detail below, with examples of these embodiments illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting it.

[0018] It should be noted that the terms "first," "second," etc., used in this disclosure and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure.

[0019] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0020] See Figure 1 This is a flowchart of a method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data, provided in Embodiment 1 of the present invention. Figure 1 As shown, the method may include: Step S101: Based on the runoff coefficients of various underlying surfaces of the target sponge park and the area of ​​each underlying surface at the current time, obtain the benchmark value of the surface runoff coefficient at the current time; based on the soil saturated hydraulic conductivity of the target sponge park and the soil moisture content at the current time, obtain the benchmark value of the soil steady-state infiltration rate at the current time.

[0021] The hydrological performance analysis of sponge parks focuses particularly on runoff coefficient and infiltration rate (especially soil steady-state infiltration rate). The runoff coefficient directly reflects the surface runoff generation capacity, and the differences in runoff generation across different underlying surfaces make it a key indicator for measuring the formation and flow of rainwater on the park's surface. Infiltration rate (especially soil steady-state infiltration rate), as a core functional parameter of sponge facilities, determines the soil's ability to absorb rainwater and is crucial to the effectiveness of rainwater infiltration. Runoff coefficient and infiltration rate provide key evidence for evaluating the capacity of sponge parks to absorb, retain, purify, and release rainwater during rainfall. They are indispensable parameters for accurately simulating runoff generation and confluence processes, scientifically analyzing hydrological performance, and rationally optimizing the design of sponge facilities. Therefore, obtaining accurate runoff coefficient and infiltration rate is a prerequisite for the dynamic analysis of the hydrological performance of sponge parks.

[0022] In this embodiment of the invention, a dynamic response sponge park hydrological performance analysis is achieved through multi-source spatiotemporal data fusion and dynamic modeling technology: First, baseline values ​​of surface runoff coefficient and soil steady-state infiltration rate are obtained; then, the baseline values ​​are corrected from the perspectives of facility health and rainfall process to obtain dynamic runoff coefficient and dynamic infiltration rate; finally, the dynamic runoff coefficient and dynamic infiltration rate are input into a distributed hydrological model to simulate runoff generation and confluence in the park in real time, obtain key hydrological response indicators, realize dynamic response sponge park hydrological performance analysis, and provide early warning based on key hydrological response indicators, providing a scientific basis for the maintenance and management of sponge facilities.

[0023] Any sponge park to be analyzed is designated as the target sponge park. Before analyzing the hydrological efficiency of the target sponge park, relevant data collection needs to be completed: (1) The area of ​​various underlying surfaces. The spatial distribution of various underlying surfaces of the target sponge park is extracted by supervised classification or deep learning semantic segmentation using high-resolution remote sensing images (such as drone aerial photography or satellite images with a resolution better than 0.5 meters). The area of ​​various underlying surfaces is counted in GIS software. The collection frequency depends on the changes in the underlying surfaces of the target sponge park. If the changes are frequent, they can be collected quarterly. If the changes are slow, they can be collected annually. In this embodiment of the invention, they are collected quarterly; (2) The runoff coefficient of various underlying surfaces. Refer to the "Outdoor Drainage Design Standard" (GB (50014) or typical values ​​in local hydrological manuals; (3) Soil saturated hydraulic conductivity, which refers to the amount of water passing through a unit area per unit time under a unit water potential gradient when the soil pores are completely filled with water. It is determined by laboratory sampling in the field (such as the constant head method) or by looking up empirical values ​​in tables according to soil texture type (sand, loam, clay); (4) Soil saturated water content, which refers to the ratio of the mass of water to the mass of solid particles when the soil pores are completely filled with water. It is obtained by gravimetric method, capacitance method, soil moisture tensiometer method or time domain reflection method, etc.; (5) Soil initial water content: refers to the proportion of water contained in the soil before rainfall or irrigation. It is obtained by real-time monitoring of soil moisture sensor through Internet of Things, with a sampling frequency of once per minute; (6) Soil water content: obtained by soil moisture sensor, with a sampling frequency of once per minute. (7) Historical rainfall runoff: obtained from the historical rainfall event record table. The basic formula for runoff is Q=C×I×A, where Q is the runoff (cubic meters), C is the runoff coefficient, I is the rainfall (millimeters), and A is the catchment area (square meters); (8) Surface sediment concentration corresponding to each historical rainfall: estimated by referring to local rainwater quality monitoring data or according to the catchment type; (9) Rainfall: obtained from meteorological forecasts or on-site rain gauges, with a collection frequency of once per minute; (10) Maximum runoff length: extracted through a high-precision digital elevation model (DEM). Using GIS hydrological analysis tools, the DEM is used to fill depressions, analyze flow direction, and calculate the cumulative runoff volume, automatically generating the catchment area boundary and surface runoff path, from which the path length from the farthest point in the catchment area along the water flow direction to the outlet is obtained. The above data collection methods are all existing technologies and will not be elaborated here. It is worth noting that when acquiring data at the current moment, if the current moment is not the time when a certain piece of information was collected, then based on the collection frequency of that piece of information, the data collected at times prior to the current moment will be used as the data at the current moment.

[0024] After collecting the required data, the baseline values ​​of the surface runoff coefficient and soil steady-state infiltration rate of the target sponge park at the current moment are first obtained. Regarding the baseline value of the surface runoff coefficient, since the surface runoff coefficient reflects the surface runoff generation capacity, its value is significantly affected by the impermeability of the underlying surface. Different types of underlying surfaces (such as roofs, green spaces, etc.) have large differences in runoff generation capacity. Remote sensing imagery can accurately obtain the spatial distribution and area proportion of various underlying surfaces. Therefore, in this embodiment of the invention, the baseline value of the surface runoff coefficient of the target sponge park at the current moment is obtained by combining the runoff coefficients of various underlying surfaces of the target sponge park and the area of ​​each underlying surface at the current moment. This baseline value is used to characterize the overall runoff generation characteristics of the target sponge park. Specifically: For any type of underlying surface of the target sponge park, obtain the area of ​​the underlying surface at the current time and the park area of ​​the target sponge park, calculate the proportion of the area of ​​the underlying surface at the current time in the park area, and obtain the area proportion of the underlying surface at the current time. The area proportion of each type of underlying surface of the target sponge park at the current time is obtained. The area proportion of each type of underlying surface at the current time is used as the weight of the runoff coefficient of each type of underlying surface. The runoff coefficients of each type of underlying surface are weighted and summed to obtain the benchmark value of the surface runoff coefficient at the current time.

[0025] In one embodiment, the formula for calculating the baseline value of the surface runoff coefficient at the current time is: in, This represents the baseline value of the surface runoff coefficient at the current time, where t represents the current time and n represents the total number of underlying surface types for the target sponge park. This represents the area percentage of the j-th type of underlying surface at the current moment. This represents the runoff coefficient of the j-th type of underlying surface.

[0026] Regarding the benchmark value of soil steady-state infiltration rate, considering that soil saturated hydraulic conductivity is an inherent physical property of soil, determining its potential maximum infiltration capacity, and that soil moisture content is a dynamic variable that directly affects the actual infiltration rate, in this embodiment of the invention, the benchmark value of soil steady-state infiltration rate at the current moment is obtained based on the soil saturated hydraulic conductivity of the target sponge park and the soil moisture content at the current moment. Specifically: Obtain the soil moisture content of the target sponge park at the current moment, as well as the soil saturation moisture content of the target sponge park, calculate the proportion of the soil moisture content in the soil saturation moisture content, and obtain the soil moisture level at the current moment. Subtracting the soil moisture level from the constant 1 yields the target difference. The saturated hydraulic conductivity of the target sponge park is then obtained. The product of the target difference and the saturated hydraulic conductivity is calculated to obtain the benchmark value of the steady-state soil infiltration rate at the current moment.

[0027] In one embodiment, the formula for calculating the benchmark value of soil steady-state infiltration rate at the current moment is: in, This represents the baseline value of the soil steady-state infiltration rate at the current moment. Indicates the saturated hydraulic conductivity of the soil. This indicates the soil moisture content of the target sponge park at the current moment. This indicates the soil saturation moisture content.

[0028] It should be noted that, The larger the value, the wetter the soil in the target sponge park at that moment, and the lower the soil infiltration rate at that moment. The smaller; conversely, The smaller the value, the drier the soil in the target sponge park at the current moment, and the higher the soil infiltration rate at the current moment. The larger.

[0029] Thus, the baseline values ​​of the surface runoff coefficient and the soil steady-state infiltration rate of the target sponge park at the current moment have been obtained.

[0030] It is worth noting that in this embodiment of the invention, the benchmark values ​​of surface runoff coefficient and soil steady-state infiltration rate are updated every half hour, which means that the hydrological performance analysis of the target sponge park is performed every half hour. There are no restrictions here, and implementers can set them according to specific scenarios.

[0031] Step S102: Based on the rate of change of soil moisture content of the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park, adjust the benchmark value of the soil steady-state infiltration rate to obtain the dynamic infiltration rate at the current moment.

[0032] Since the benchmark values ​​for surface runoff coefficient and soil steady-state infiltration rate are calculated based on ideal or average conditions, in actual operation, sponge city facilities are affected by various factors, leading to changes in their performance. Long-term operation can result in performance degradation, such as material aging and structural deformation. Simultaneously, sediment and pollutants carried by rainwater can deposit on the surface of the facilities, clogging soil pores, all of which affect the infiltration capacity of the sponge city facilities. Furthermore, the characteristics of rainfall processes, such as rainfall intensity, duration, and terrain slope, also influence surface runoff. Therefore, in this embodiment of the invention, from the perspectives of facility health and rainfall processes, a multivariate weighted fusion method is used to correct the benchmark values ​​for surface runoff coefficient and soil steady-state infiltration rate according to actual conditions. This yields the dynamic infiltration rate and dynamic runoff coefficient of the target sponge park at the current moment, making them more consistent with actual hydrological conditions. This provides reliable data support for the effectiveness assessment and early warning of sponge city facilities, thereby improving the accuracy of hydrological performance analysis of the target sponge park.

[0033] The dynamic infiltration rate is obtained as follows: (1) Based on the rate of change of soil moisture content of the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park, obtain the dynamic adjustment factor for adjusting the benchmark value of soil steady-state infiltration rate.

[0034] Specifically: Obtain the soil moisture content of the target sponge park at the end of the most recent rainfall, denoted as the "rain-stopped soil moisture content," and use... This means obtaining the soil moisture content after a preset time elapsed since the end of the most recent rainfall, denoted as the post-rain soil moisture content, and using... It means that, among them, In this embodiment of the invention, a preset duration is set. The timeframe is not limited here; the implementer can set it according to the actual rainfall conditions of the target sponge park. Using the preset duration as the denominator and the difference between the soil moisture content after rain and the soil moisture content after rain as the numerator, the rate of change of soil moisture content is obtained. This rate is used to capture the real-time dynamics of the sponge facility's operating status, reflecting the immediate trend of facility performance changes. The rate of change of soil moisture content is normalized to obtain a normalized value. Subtracting the normalized value from a constant 1 yields the characteristic value of soil infiltration resistance at the current moment, denoted as [value missing]. ,Right now , Represents the normalization function. The smaller the value, the slower the rate of soil moisture loss after the most recent rainfall, and the weaker the soil's permeability. The larger the value, the greater the soil permeability resistance of the target sponge park at the current moment; Considering that long-term deposition of historical sediments can clog soil pores and affect the performance of sponge facilities, the five rainfalls preceding the current moment in the target sponge park are recorded as historical rainfall (the number of historical rainfalls is not limited; implementers can set it according to the actual rainfall situation of the target sponge park. If the rainfall is low, the number of historical rainfalls should be appropriately reduced; conversely, if the rainfall is frequent, the number of historical rainfalls should be appropriately increased). The runoff and surface sediment concentration of each historical rainfall are obtained. The product between the runoff and surface sediment concentration of each historical rainfall is calculated to obtain the degree of siltation for each historical rainfall. The cumulative value of all siltation degrees is normalized to obtain the characteristic value of the infiltration rate at the current moment, denoted as... ,Right now Where M represents the historical rainfall amount before the current moment, and in this embodiment of the invention, M=5. This represents the runoff volume of the k-th historical rainfall event. This represents the surface sediment concentration of the k-th historical rainfall event. Represents the normalization function. The larger, or The larger the value, the greater the historical rainfall, the higher the sediment concentration, the more severe the soil siltation in the target sponge park, and the more severe the decline in soil infiltration capacity. The larger; Considering that the intensity and interval of previous hydrological events can affect soil saturation and thus the soil's infiltration capacity at the current moment, the current rainfall in the target sponge park within the past 24 hours (this is not limited and can be set by the implementer according to the actual rainfall situation of the target sponge park) is obtained and denoted as [missing information]. And the critical rainfall amount required to bring the soil moisture content of the target sponge park to the soil saturation level, denoted as The current rainfall is calculated as a percentage of the critical rainfall, and this percentage is normalized to obtain the intensity characteristic value of the previous hydrological event at the current moment, denoted as... ,Right now ,in, Represents the normalization function. The larger the value, the closer the rainfall within 24 hours is to soil saturation rainfall, or even higher, indicating a greater intensity of the preceding hydrological event. The larger the value, the more severe the decrease in the soil infiltration capacity of the target sponge park at the current moment. It is worth noting that if the target sponge park has not received rainfall in the 24 hours leading up to the current moment, then... ; Obtain the start time of the most recent rainfall event at the target sponge park, and obtain the time interval between the start time and the current time, denoted as . The reciprocal of the time interval is normalized to obtain the characteristic value of the impact of previous hydrological events, denoted as . ,Right now ,in, The smaller the value, the closer the current time is to the last rainfall, and the greater the influence of previous hydrological events on the soil infiltration rate of the target sponge park at the current moment. The larger the value, the more severe the decrease in the soil infiltration capacity of the target sponge park at the current moment. Represents the normalization function; The macro-level indicator of facility operation time cannot be ignored. As time goes on, issues such as material aging inevitably affect the soil's infiltration capacity. Therefore, we obtain the number of days since the target sponge park was built, and then normalize this number using the `norm()` function to obtain the characteristic value of the target sponge park's operation time, denoted as... This is used to characterize the health of facilities. The longer a target sponge park has been built, the greater the decline in its facility performance, and consequently... The larger the value, the more severe the decrease in the soil infiltration capacity of the target sponge park at the current moment; The sum of the soil seepage resistance characteristic value, the infiltration rate attenuation characteristic value, the previous hydrological event intensity characteristic value, and the previous hydrological event impact characteristic value is calculated to obtain the sum result. The product of the sum result and the running time characteristic value is normalized to obtain the dynamic adjustment factor for adjusting the soil steady-state infiltration rate benchmark value.

[0035] In one embodiment, the formula for calculating the dynamic adjustment factor that adjusts the benchmark value of soil steady-state infiltration rate is as follows: in, This represents a dynamic adjustment factor used to adjust the baseline value of steady-state soil infiltration rate. This represents the characteristic value of the target sponge park's operating time. This represents the characteristic value of soil seepage resistance at the current moment. This represents a characteristic value indicating the degree of infiltration rate decay at the current moment. This represents the intensity characteristic value of previous hydrological events. This indicates the characteristic value of the impact of previous hydrological events. This represents the normalization function.

[0036] It should be noted that, The larger the value, the longer the target sponge park has been built, and the more severe the decline in facility performance, i.e., the more severe the decline in soil permeability. In this case, the larger the adjustment range for the soil steady-state infiltration rate benchmark value, and consequently... The larger; The larger the value, the greater the soil permeability resistance of the target sponge park at the current moment, and the more severe the decline in soil permeability. In this case, the adjustment range for the soil steady-state infiltration rate benchmark value should be larger, and thus... The larger; The larger the value, the more severe the soil siltation and the more severe the decline in soil permeability in the target sponge park. In this case, the adjustment range for the soil steady-state infiltration rate benchmark value should be larger, and thus... The larger; The larger the value, the closer the rainfall within 24 hours is to, or even exceeds, the soil saturation rainfall. This indicates a greater intensity of previous hydrological events and a more severe decline in the soil infiltration capacity of the target sponge park at the current moment. Consequently, the adjustment range for the soil steady-state infiltration rate benchmark value will be larger. The larger; The larger the value, the closer the current time is to the last rainfall, the greater the impact of previous hydrological events on the soil infiltration rate of the target sponge park at the current moment, and the more severe the decline in the soil infiltration capacity of the target sponge park at the current moment. Therefore, the adjustment range for the soil steady-state infiltration rate benchmark value should be larger. The larger.

[0037] (2) Adjust the soil steady-state infiltration rate benchmark value according to the dynamic adjustment factor that adjusts the soil steady-state infiltration rate benchmark value to obtain the dynamic infiltration rate of the target sponge park at the current moment.

[0038] Specifically: Subtract the dynamic adjustment factor from the constant 1 to obtain the adjustment coefficient, calculate the product between the adjustment coefficient and the soil steady-state infiltration rate benchmark value, and obtain the dynamic infiltration rate of the target sponge park at the current moment.

[0039] In one embodiment, the formula for calculating the dynamic infiltration rate of the target sponge park at the current moment is: in, This represents the dynamic infiltration rate of the target sponge park at the current moment. This represents the baseline value of the soil steady-state infiltration rate at the current moment. This represents the dynamic adjustment factor used to adjust the benchmark value of soil steady-state infiltration rate.

[0040] It should be noted that, The larger the value, the more severe the decline in the soil infiltration capacity of the target sponge park at the current moment, and the lower the actual infiltration rate of the soil at the current moment. The smaller.

[0041] Thus, by considering multiple dimensions such as the target sponge park's own operational status, sediment accumulation, operating time, and the impact of previous hydrological events, the benchmark value of the soil steady-state infiltration rate was adjusted, resulting in a dynamic infiltration rate that better reflects the actual situation of the target sponge park at the current moment.

[0042] Step S103: Detect the rainfall status of the target sponge park at the current moment. If the target sponge park is in a rainfall state at the current moment, adjust the benchmark value of the surface runoff coefficient according to the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment to obtain the dynamic runoff coefficient at the current moment.

[0043] After correcting the benchmark value of soil steady-state infiltration rate based on actual conditions, the benchmark value of surface runoff coefficient is then corrected to obtain the dynamic runoff coefficient of the target sponge park at the current moment. The specific implementation method is as follows: Since real-time rainfall is a key dynamic factor affecting the runoff coefficient, the rainfall status of the target sponge park at the current moment is first obtained from the meteorological platform. If the target sponge park is detected to be in a state of no rainfall at the current moment, the baseline value of the surface runoff coefficient is not adjusted; that is, the baseline value of the surface runoff coefficient at the current moment is directly used as the dynamic runoff coefficient of the target sponge park at the current moment. Conversely, if the target sponge park is detected to be in a state of rainfall at the current moment, the baseline value of the surface runoff coefficient needs to be dynamically adjusted according to the specific rainfall status to obtain the dynamic runoff coefficient of the target sponge park at the current moment. The method for obtaining the dynamic runoff coefficient is as follows: (1) Based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment, obtain the dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient.

[0044] Specifically: Since real-time rainfall intensity changes are crucial, and the magnitude and trend of rainfall directly affect runoff, the runoff coefficient increases when rainfall intensity exceeds the soil infiltration capacity. Therefore, the minute-level rainfall intensity of the target sponge park at the current moment is obtained and recorded as the real-time rainfall intensity. This means that rainfall intensity = rainfall amount / rainfall duration. The minute-level rainfall intensity of the target sponge park at the current moment is the average rainfall amount per minute from the start of this rainfall to the current moment. The average rainfall intensity of the target sponge park over the past two years (this is not limited and can be set by the implementer according to the specific scenario) is obtained. This means that the proportion of the real-time rainfall intensity in the average rainfall intensity is calculated to obtain the rainfall intensity coefficient at the current moment; Obtain the minute-level rainfall intensity of the target sponge park at the time preceding the current moment, denoted as historical rainfall intensity, and use... This means that the difference between the real-time rainfall intensity and the historical rainfall intensity is normalized to obtain the rainfall intensity change rate at the current moment. The product of the rainfall intensity change rate and the rainfall intensity coefficient is then normalized to obtain the rainfall intensity characteristic value at the current moment, denoted as... ,Right now , Represents the normalization function. The larger, and The larger the value, the greater the rainfall intensity at the current moment, and the greater the rate of change in rainfall intensity, resulting in a faster increase in the runoff coefficient. The larger; Considering that the duration of rainfall also has a significant impact on the runoff coefficient, and that soil moisture increases with the duration of rainfall, leading to a rise in the runoff coefficient, the time required for the soil moisture content of the target sponge park to reach soil saturation was obtained based on the real-time rainfall intensity and recorded as a reference time. This indicates that the time interval between the start time of this rainfall and the current time is recorded as the rainfall duration. This means that the proportion of the rainfall duration in the reference time is calculated, and the minimum value between the constant 1 and the proportion is obtained to obtain the runoff transformation characteristic value at the current moment, denoted as . ,Right now , The larger the value, the longer the rainfall duration, the greater the increase in soil moisture content, and the lower the infiltration rate, resulting in more rainfall being converted into runoff. A higher runoff coefficient further... The larger, This indicates that when continuous rainfall leads to soil saturation, It will no longer increase, that is The maximum value is 1; Furthermore, considering that the initial soil moisture level determines the magnitude of the initial rainfall loss (the amount of loss from the start of rainfall to the start of runoff), the more moist the soil, the smaller the initial loss, the earlier the runoff occurs, and the higher the runoff coefficient. Therefore, the initial soil moisture content of the target sponge park at the current moment is obtained and denoted as... The initial soil moisture content is normalized to obtain the normalized value of the initial moisture content; Topographical factors such as the slope of the catchment area, the length of the surface runoff path, and surface roughness affect the water flow velocity and catchment time, thus altering the runoff coefficient. Shorter paths result in faster catchment and a generally higher runoff coefficient, while longer paths lead to slower catchment and a generally lower runoff coefficient. Therefore, the maximum catchment length of the target sponge park at the current moment is obtained and denoted as... The reciprocal of the maximum flow length is normalized to obtain the flow velocity characteristic value; The sum between the rainfall intensity characteristic value and the runoff transformation characteristic value is calculated to obtain the sum result. The product between the sum result, the normalized value of the initial water content, and the runoff velocity characteristic value is normalized to obtain a dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient.

[0045] In one embodiment, the formula for calculating the dynamic adjustment factor for adjusting the baseline value of the surface runoff coefficient is as follows: in, This represents the dynamic adjustment factor used to adjust the baseline value of the surface runoff coefficient. This represents the initial soil moisture content at the current moment. This represents the maximum runoff length of the target sponge park at the current moment. This represents the characteristic value of rainfall intensity at the current moment. This represents the characteristic value of runoff transformation at the current moment. This represents the normalization function.

[0046] It should be noted that, The larger the value, the higher the soil moisture content of the target sponge park before this rainfall, and the earlier the runoff generation. At this time, the runoff coefficient should be significantly increased, thus... The larger; The smaller the value, the shorter the maximum runoff length and the faster the runoff velocity. In this case, the runoff coefficient should be significantly increased, and thus... The larger; The larger the value, the greater the rainfall intensity at the current moment, and the greater the rate of change in rainfall intensity. This leads to a faster increase in the runoff coefficient, at which point the runoff coefficient should increase significantly. The larger; The larger the value, the greater the degree to which rainfall is converted into runoff; in this case, the runoff coefficient should increase significantly, and thus... The larger.

[0047] (2) Adjust the benchmark value of the surface runoff coefficient according to the dynamic adjustment factor that adjusts the benchmark value of the surface runoff coefficient, and obtain the dynamic runoff coefficient of the target sponge park at the current time.

[0048] Specifically: the sum of constant 1 and the dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient is calculated to obtain the adjustment coefficient for adjusting the benchmark value of the surface runoff coefficient; the product between the adjustment coefficient for adjusting the benchmark value of the surface runoff coefficient and the benchmark value of the surface runoff coefficient is calculated to obtain the candidate runoff coefficient. Obtain the runoff coefficients of various underlying surfaces of the target sponge park, select the maximum value among all runoff coefficients and record it as the maximum runoff coefficient, and select the minimum value between the maximum runoff coefficient and the candidate runoff coefficients as the dynamic runoff coefficient of the target sponge park at the current moment.

[0049] In one embodiment, the formula for calculating the dynamic runoff coefficient of the target sponge park at the current moment is: in, This represents the dynamic runoff coefficient of the target sponge park at the current moment. This represents the baseline value for the surface runoff coefficient. This represents the dynamic adjustment factor used to adjust the baseline value of the surface runoff coefficient. This represents the maximum runoff coefficient among various underlying surface types, i.e., the maximum runoff coefficient. This represents the minimum value function.

[0050] It should be noted that, The larger the value, the higher the soil moisture content of the target sponge park before this rainfall, and the greater the rainfall intensity of this rainfall. This indicates a higher proportion of rainfall at the target sponge park being converted into surface runoff at the current moment, and thus... The larger.

[0051] Thus, by taking into account factors such as rainfall process and topography, the benchmark for surface runoff coefficient was adjusted to obtain a dynamic runoff coefficient that better reflects the actual situation of the target sponge park at the current moment.

[0052] Step S104: Input the dynamic infiltration rate and the dynamic runoff coefficient into the distributed hydrological model, and monitor and warn of the hydrological performance of the target sponge park in real time based on the output results of the distributed hydrological model.

[0053] After obtaining the dynamic infiltration rate and dynamic runoff coefficient of the target sponge park at the current moment, these parameters are input into a distributed hydrological model (such as SWMM or a gridded runoff generation and collection model). Based on the output of the distributed hydrological model, the hydrological efficiency of the target sponge park is monitored and warned in real time. The general process is as follows: The distributed hydrological model dynamically updates the runoff generation calculation module of the catchment area within the target sponge park based on minute-level meteorological forecast data (such as rainfall intensity and duration) and high-precision topographic and pipeline network data. The dynamic runoff coefficient is used to adjust the proportion of rainfall converted into surface runoff, directly affecting the amount of runoff generated. The dynamic infiltration rate, by controlling the soil infiltration rate, determines the start time and peak shape of runoff generation. The dynamic infiltration rate and dynamic runoff coefficient work together to accurately simulate the runoff generation process, surface runoff path, and facility infiltration capacity within the catchment area of ​​the target sponge park, and to deduce the spatiotemporal distribution of pipeline drainage load. After the distributed hydrological model outputs key hydrological response indicators (such as the flow process line at the outlet section, water depth distribution, and total runoff reduction rate), the system will compare them with the design thresholds in real time. For example, when the runoff reduction rate is lower than 90% of the design threshold and lasts for more than 30 minutes, or when the water depth exceeds the standard and the receding time exceeds the limit, the system will automatically trigger an early warning mechanism.

[0054] It is worth noting that the focus of this invention is on how to obtain more accurate dynamic infiltration rate and dynamic runoff coefficient in real time, so as to provide reliable data support for the performance evaluation and early warning of sponge facilities, thereby improving the accuracy of hydrological performance analysis of sponge parks. Real-time monitoring and early warning of the hydrological performance of target sponge parks based on the output results of distributed hydrological models is an existing technology, which will not be elaborated here.

[0055] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data, characterized in that, The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data includes: Based on the runoff coefficients of various underlying surfaces of the target sponge park and the area of ​​each underlying surface at the current time, obtain the benchmark value of the surface runoff coefficient at the current time. Based on the soil saturated hydraulic conductivity of the target sponge park and the soil moisture content at the current time, obtain the benchmark value of the soil steady-state infiltration rate at the current time. Based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park, the benchmark value of soil steady-state infiltration rate is adjusted to obtain the dynamic infiltration rate at the current moment. The rainfall status of the target sponge park at the current moment is detected. If the target sponge park is in a rainfall state at the current moment, the surface runoff coefficient benchmark value is adjusted according to the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment to obtain the dynamic runoff coefficient at the current moment. The dynamic infiltration rate and the dynamic runoff coefficient are input into the distributed hydrological model, and the hydrological performance of the target sponge park is monitored and warned in real time based on the output of the distributed hydrological model.

2. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 1, characterized in that, The process of obtaining the benchmark value of the surface runoff coefficient at the current moment based on the runoff coefficients of various underlying surfaces of the target sponge park and the area of ​​each underlying surface at the current moment includes: For any type of underlying surface of the target sponge park, obtain the area of ​​the underlying surface at the current time and the park area of ​​the target sponge park, calculate the proportion of the area of ​​the underlying surface at the current time in the park area, and obtain the area proportion of the underlying surface at the current time. The area proportion of each type of underlying surface of the target sponge park at the current time is obtained. The area proportion of each type of underlying surface at the current time is used as the weight of the runoff coefficient of each type of underlying surface. The runoff coefficients of each type of underlying surface are weighted and summed to obtain the benchmark value of the surface runoff coefficient at the current time.

3. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 1, characterized in that, The process of obtaining the benchmark value of soil steady-state infiltration rate at the current moment based on the soil saturated hydraulic conductivity of the target sponge park and the soil moisture content at the current moment includes: Obtain the soil moisture content of the target sponge park at the current moment, as well as the soil saturation moisture content of the target sponge park, calculate the proportion of the soil moisture content in the soil saturation moisture content, and obtain the soil moisture level at the current moment. Subtracting the soil moisture level from the constant 1 yields the target difference. The saturated hydraulic conductivity of the target sponge park is then obtained. The product of the target difference and the saturated hydraulic conductivity is calculated to obtain the benchmark value of the steady-state soil infiltration rate at the current moment.

4. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 1, characterized in that, The process of adjusting the soil steady-state infiltration rate benchmark value based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall prior to the current moment, and the operating time of the target sponge park to obtain the dynamic infiltration rate at the current moment includes: Based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park, a dynamic adjustment factor is obtained to adjust the benchmark value of the soil steady-state infiltration rate. Subtract the dynamic adjustment factor from the constant 1 to obtain the adjustment coefficient. Calculate the product between the adjustment coefficient and the soil steady-state infiltration rate benchmark value to obtain the dynamic infiltration rate at the current moment.

5. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 4, characterized in that, The dynamic adjustment factor for adjusting the soil steady-state infiltration rate benchmark value is obtained based on the rate of change of soil moisture content in the target sponge park at the current moment, the intensity of the hydrological event, the surface sediment concentration of historical rainfall before the current moment, and the operating time of the target sponge park. This adjustment includes: The soil moisture content of the target sponge park at the end of the most recent rainfall is obtained and recorded as the soil moisture content after the rain stops. The soil moisture content after a preset time period following the end of the most recent rainfall is obtained and recorded as the soil moisture content after the rain stops. The preset time period is used as the denominator, and the difference between the soil moisture content after the rain stops and the soil moisture content after the rain stops is used as the numerator to obtain the rate of change of soil moisture content. The rate of change of soil moisture content is normalized to obtain a normalized value. The normalized value is then subtracted from the constant 1 to obtain the characteristic value of soil permeability resistance at the current moment. Obtain the runoff and surface sediment concentration of a preset number of historical rainfall events prior to the current time for the target sponge park. Calculate the product between the runoff and surface sediment concentration for each historical rainfall event to obtain the degree of siltation for each event. Normalize the cumulative value of all siltation degrees to obtain the characteristic value of the infiltration rate attenuation at the current time. The current rainfall of the target sponge park within a preset time period up to the current moment is obtained, as well as the critical rainfall that would cause the soil moisture content of the target sponge park to reach the soil saturation moisture content. The proportion of the current rainfall in the critical rainfall is calculated, and the proportion is normalized to obtain the intensity characteristic value of the previous hydrological event. Obtain the start time of the most recent rainfall event in the target sponge park, obtain the time interval between the start time and the current time, normalize the reciprocal of the time interval, and obtain the characteristic value of the impact of previous hydrological events. Obtain the number of days since the target sponge park was built, normalize the number of days, and obtain the operating time characteristic value of the target sponge park; The sum of the soil seepage resistance characteristic value, the infiltration rate attenuation characteristic value, the previous hydrological event intensity characteristic value, and the previous hydrological event impact characteristic value is calculated to obtain the sum result. The product of the sum result and the running time characteristic value is normalized to obtain the dynamic adjustment factor for adjusting the soil steady-state infiltration rate benchmark value.

6. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 1, characterized in that, The process of adjusting the baseline value of the surface runoff coefficient based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment to obtain the dynamic runoff coefficient at the current moment includes: Based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment, a dynamic adjustment factor is obtained to adjust the benchmark value of the surface runoff coefficient. The sum of constant 1 and the dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient is calculated to obtain the adjustment coefficient for adjusting the benchmark value of the surface runoff coefficient. The product between the adjustment coefficient for adjusting the benchmark value of the surface runoff coefficient and the benchmark value of the surface runoff coefficient is calculated to obtain the candidate runoff coefficient. Obtain the runoff coefficients of various underlying surfaces of the target sponge park, select the maximum value among all runoff coefficients and record it as the maximum runoff coefficient, and select the minimum value between the maximum runoff coefficient and the candidate runoff coefficients as the dynamic runoff coefficient at the current moment.

7. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 6, characterized in that, The dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient, obtained based on the initial soil moisture content, rainfall intensity and duration, and maximum runoff length of the target sponge park at the current moment, includes: Get the minute-level rainfall intensity of the target sponge park at the current moment, and record it as the real-time rainfall intensity. Get the average rainfall intensity of the target sponge park in a preset historical period, calculate the proportion of the real-time rainfall intensity in the average rainfall intensity, and obtain the rainfall intensity coefficient at the current moment. The minute-level rainfall intensity of the target sponge park at the previous moment is obtained and recorded as the historical rainfall intensity. The difference between the real-time rainfall intensity and the historical rainfall intensity is normalized to obtain the rainfall intensity change rate at the current moment. The product between the rainfall intensity change rate and the rainfall intensity coefficient is normalized to obtain the rainfall intensity characteristic value at the current moment. Based on the real-time rainfall intensity, the time required for the soil moisture content of the target sponge park to reach the soil saturation moisture content is obtained and recorded as the reference time. The time interval between the start time of this rainfall and the current time is obtained and recorded as the rainfall duration. The proportion of the rainfall duration in the reference time is calculated, and the minimum value is obtained between the constant 1 and the proportion to obtain the runoff transformation characteristic value at the current time. Obtain the initial soil moisture content of the target sponge park at the current time, and normalize the initial soil moisture content to obtain the normalized value of the initial moisture content; Obtain the maximum runoff length of the target sponge park at the current moment, and normalize the reciprocal of the maximum runoff length to obtain the runoff velocity characteristic value; The sum between the rainfall intensity characteristic value and the runoff transformation characteristic value is calculated to obtain the sum result. The product between the sum result, the normalized value of the initial water content, and the runoff velocity characteristic value is normalized to obtain a dynamic adjustment factor for adjusting the benchmark value of the surface runoff coefficient.

8. The method for dynamic analysis of the hydrological efficiency of sponge parks based on multi-source spatiotemporal data according to claim 1, characterized in that, If the target sponge park is in a state of no rainfall at the current moment, the benchmark value of the surface runoff coefficient at the current moment will be used as the dynamic runoff coefficient.

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