A multi-scale base flow monitoring method and device, electronic equipment and storage medium

Abstract

The present application relates to river monitoring technical field, disclose a kind of multi-scale base flow monitoring method, device, electronic equipment and storage medium, the present application is by non-contact multi-source collaborative monitoring, including satellite remote sensing, synthetic aperture radar, microwave radar etc., effectively overcome the defect that traditional contact type measurement is easily destroyed by flood, affected by silt accumulation in hilly and mountainous area, on this basis, with water level this continuity strong and with cross-scale representative key parameter as core, it realizes site millimeter level resolution, river section centimeter level inversion accuracy and watershed ten-meter level satellite coverage Multi-scale collaborative continuous observation.Simultaneously, through long-term monitoring and algorithm optimization, based on the improved digital filtering method to form the complete technical closed loop from water level observation, flow calculation to base flow, provide efficient, accurate and generalizable systematic solution for base flow monitoring.

Description

Technical Field

[0001] This invention relates to the field of river monitoring technology, specifically to a multi-scale baseflow monitoring method, device, electronic equipment, and storage medium. Background Technology

[0002] Base flow is the stable runoff portion of a river channel formed by groundwater recharge. As a key parameter for groundwater resource assessment, watershed water resource management, ecological flow determination, drought prediction, and water pollution control, its accurate monitoring is of great scientific value for revealing the dynamic changes in watershed groundwater level and volume, analyzing the interaction process between surface water and groundwater, and supporting the sustainable use of water resources.

[0003] However, unlike conventional surface water flow monitoring, baseflow is groundwater, and it is currently difficult to accurately measure baseflow experimentally. Furthermore, its uncertainty is further increased by factors such as river and landform morphology, hydraulic gradient dynamics, and hydrogeological conditions, compounded by the profound impacts of climate change and human activities. Simultaneously, due to the complexity and high spatiotemporal variability of baseflow, monitoring faces challenges such as high data acquisition costs, poor reliability of single observation methods, and significant cross-scale effects, making continuous monitoring and large-scale deployment difficult.

[0004] Currently, traditional baseflow monitoring stations mainly rely on manual sampling and contact measuring instruments such as weirs, current meters, and level gauges, but these methods have significant limitations: they are susceptible to siltation and flood damage, with equipment failure rates exceeding 30% in extreme environments; mountain stations are scattered, resulting in low frequency and high cost of manual surveys, making it difficult to obtain continuous data and achieve remote real-time transmission and processing, thus failing to meet the real-time needs of modern hydrological forecasting and emergency management; and inadequate municipal power supply and wired network coverage in remote mountainous areas pose technical bottlenecks for equipment power supply and communication. Although radar or ultrasonic-based remote monitoring instruments can achieve non-contact measurement, these devices are expensive and mostly used in monitoring stations along major rivers, and suffer from insufficient accuracy (errors exceeding 10%) or data delays (exceeding 30 minutes). Furthermore, baseflow exhibits highly complex spatiotemporal variability, with significant scale effects during monitoring, making continuous monitoring and large-scale deployment particularly difficult in hilly and mountainous areas. Summary of the Invention

[0005] This invention provides a multi-scale baseflow monitoring method, device, electronic equipment, and storage medium to address the limitations of traditional methods, the high cost and insufficient accuracy and timeliness of existing remote monitoring instruments, and the difficulty in continuous monitoring in small watersheds in hilly and mountainous areas due to complex terrain and other factors. While ensuring monitoring accuracy, it achieves the goals of non-contact, multi-scale, low-cost, and low-complexity baseflow monitoring, thereby improving the efficiency of baseflow monitoring.

[0006] In a first aspect, the present invention provides a multi-scale baseflow monitoring method, comprising: acquiring multi-scale monitoring data and GNSS observation data of a target watershed, wherein the multi-scale monitoring data includes satellite data at the watershed scale, synthetic aperture radar data at the river section scale, and microwave radar data at the monitoring station scale; calculating the runoff at the watershed scale and river section scale by means of water level inversion based on the multi-scale monitoring data and GNSS observation data, and calculating the runoff at the monitoring station by means of basic hydraulic principles; and dividing the runoff at each scale into baseflows to obtain the baseflow at each scale.

[0007] This invention utilizes non-contact, multi-source collaborative monitoring, including satellite remote sensing, synthetic aperture radar, and microwave radar, to effectively overcome the shortcomings of traditional contact-based measurements, which are susceptible to flooding and siltation in hilly and mountainous areas. While improving equipment reliability and measurement accuracy, it significantly enhances adaptability and monitoring security in complex terrain conditions such as remoteness, narrow spaces, and vegetation obstruction. Based on this, the invention focuses on "water level," a key parameter with strong continuity and cross-scale representativeness, achieving multi-scale collaborative continuous observation with millimeter-level resolution at stations, centimeter-level inversion accuracy for river sections, and ten-meter-level satellite coverage of the watershed. Furthermore, through long-term monitoring and algorithm optimization, based on an improved digital filtering method, a complete technical closed loop is formed, encompassing water level observation, flow calculation, and baseflow conversion, providing an efficient, accurate, and scalable systematic solution for baseflow monitoring.

[0008] In one optional implementation, the synthetic aperture radar data is obtained by aerial surveying using a synthetic aperture radar mounted on an unmanned aerial vehicle; the microwave radar data is obtained by measurement using a microwave radar installed at a monitoring station located at a cross-section of the target watershed.

[0009] In this embodiment, a drone equipped with synthetic aperture radar is used to acquire river section data, which can flexibly cover complex terrain, reduce costs, and ensure data accuracy with its high resolution. Monitoring stations are built on the river cross-section and measured with microwave radar, which can acquire data accurately and at fixed points for a long time, efficiently and comprehensively acquire multi-scale data, and ensure the accuracy and efficiency of baseflow monitoring while reducing costs.

[0010] In one optional implementation, the step of calculating the runoff at the basin-scale and river section-scale using water level inversion based on the multi-scale monitoring data and GNSS observation data, and calculating the runoff at the monitoring station using basic hydraulic principles, includes: performing water level inversion based on satellite data at the basin-scale and synthetic aperture radar data at the river section-scale, respectively, and calculating the runoff at the basin-scale and river section-scale in combination with GNSS observation data; and calculating the runoff at the monitoring station using microwave radar data at the monitoring station-scale using basic hydraulic principles.

[0011] In one optional implementation, the step of performing water level inversion based on watershed-scale satellite data and river segment-scale synthetic aperture radar data, and calculating runoff at the watershed-scale and river segment-scale in conjunction with GNSS observation data, includes: obtaining the phase difference between two echo images from watershed-scale satellite data and river segment-scale synthetic aperture radar data, respectively, to obtain the watershed-scale satellite data phase difference and the river segment-scale synthetic aperture radar data phase difference; calculating the watershed-scale water level elevation change value and the river segment-scale water level elevation change value based on the watershed-scale satellite data phase difference and the river segment-scale synthetic aperture radar data phase difference using geometric principles; obtaining the watershed-scale water level calibration value and the river segment-scale water level calibration value based on the watershed-scale water level elevation change value and the river segment-scale water level elevation change value, respectively, in conjunction with the absolute water level value in the GNSS observation data; and calculating the watershed-scale and river segment-scale runoff using the hydraulic gradient method based on the watershed-scale water level calibration value and the river segment-scale water level calibration value.

[0012] In one optional implementation, the step of calculating the runoff at the watershed scale and the river section scale respectively using the hydraulic gradient method based on the water level calibration values ​​at the watershed scale and the river section scale includes: determining the rate of change of water level along the flow direction at the watershed scale and the rate of change of water level along the flow direction at the river section scale respectively using gradient calculation based on the water level calibration values ​​at the watershed scale and the river section scale respectively; and calculating the runoff at the watershed scale and the river section scale respectively based on the rate of change of water level along the flow direction at the watershed scale and the rate of change of water level along the flow direction at the river section scale, combined with a preset hydraulic conductivity.

[0013] In this embodiment, basin-scale satellite data can cover a wide area, providing macroscopic overall basin information, while river segment-scale synthetic aperture radar (SAR) data can focus on local areas, acquiring more detailed topographic and flow characteristics. GNSS observation data provides crucial absolute water level references, thus enabling accurate runoff data. The phase difference between two echo images is precisely extracted from satellite and SAR data to capture minute changes in river water level, laying a solid foundation for subsequent accurate calculation of water level elevation changes and effectively avoiding water level inversion deviations caused by data errors. This embodiment utilizes geometric principles to calculate the phase difference, transforming abstract phase information into intuitive water level change data. It fully considers the influence of topography and flow on water level, ensuring a high degree of scientific accuracy in the calculation of water level elevation changes. Based on this, water level calibration is performed using absolute water level values ​​from GNSS observation data, successfully solving the problem of determining accurate water levels solely based on remote sensing or GNSS data. This yields more accurate water level calibration values, providing precise water level data for subsequent runoff calculations and significantly improving the overall accuracy of the monitoring system. In the runoff calculation stage, the hydraulic gradient method is used to calculate runoff at both the basin-scale and river section-scale based on water level calibration values. This method fully considers the hydraulic characteristics of water flow at different scales and can reliably calculate runoff provided that water level inversion is accurate. Moreover, by performing water level inversion and runoff calculation at different scales, comprehensive monitoring at multiple scales is achieved. This allows for a macroscopic understanding of the overall hydrological conditions of the basin and a microscopic understanding of the local water flow characteristics of the river section, comprehensively meeting the needs of water resource management and research at different levels and effectively improving the comprehensiveness, practicality, and overall efficiency of baseflow monitoring.

[0014] In one optional implementation, the step of calculating the runoff of the monitoring station based on microwave radar data at the monitoring station scale using basic hydraulic principles includes: obtaining the frequency change of two echo signals from the microwave radar data at the monitoring station scale; calculating the water velocity at the monitoring station location based on the Doppler effect according to the frequency change; obtaining the river cross-sectional area at the monitoring station location; and calculating the runoff of the monitoring station using basic hydraulic principles based on the water velocity and river cross-sectional area at the monitoring station location.

[0015] In this embodiment, by acquiring the frequency changes of two echo signals from microwave radar data at the monitoring station, and accurately calculating the water flow velocity based on the Doppler effect, and then combining the acquired river cross-sectional area, the runoff is calculated based on the basic principles of hydraulics. This method can efficiently and accurately acquire key data using microwave radar, and realize the rapid and accurate calculation of the runoff at the monitoring station, providing reliable and timely data support for water resource monitoring and management.

[0016] In one optional implementation, the step of dividing the runoff at each scale into baseflows to obtain the baseflows at each scale includes: using a digital filtering method with preset filtering parameters to separate the low-frequency baseflows from the runoffs at each scale. This can efficiently and accurately complete the baseflow division, avoid complex and tedious manual analysis, and effectively improve data processing efficiency and accuracy.

[0017] Secondly, the present invention provides a multi-scale baseflow monitoring device, comprising: a data acquisition module for acquiring multi-scale monitoring data and GNSS observation data of a target watershed, wherein the multi-scale monitoring data includes satellite data at the watershed scale, synthetic aperture radar data at the river section scale, and microwave radar data at the monitoring station scale; a runoff calculation module for calculating runoff at the watershed scale and river section scale based on the multi-scale monitoring data and GNSS observation data by means of water level inversion, and calculating runoff at the monitoring station by means of basic hydraulic principles; and a baseflow segmentation module for dividing the runoff at each scale into baseflows to obtain the baseflow at each scale.

[0018] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the multi-scale base current monitoring method described in the first aspect or any corresponding embodiment thereof.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the multi-scale base current monitoring method described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the first process of a multi-scale baseflow monitoring method according to an embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of the second process of the multi-scale baseflow monitoring method according to an embodiment of the present invention;

[0023] Figure 3 This is a layout diagram of the monitoring equipment for a multi-scale baseflow monitoring method according to an embodiment of the present invention;

[0024] Figure 4 This is a microwave radar structure diagram of a monitoring station for a multi-scale base current monitoring method according to an embodiment of the present invention;

[0025] Figure 5 This is a baseflow segmentation map of a watershed in a specific scenario of the multi-scale baseflow monitoring method according to an embodiment of the present invention;

[0026] Figure 6 This is a structural block diagram of a multi-scale base current monitoring device according to an embodiment of the present invention;

[0027] Figure 7 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0030] Baseflow is a key parameter in groundwater research and water resource management, and its accurate monitoring is of great significance. However, due to its inherent characteristics and the influence of various factors, baseflow monitoring faces numerous challenges. Traditional monitoring stations rely on manual sampling and contact instruments, which have limitations such as equipment fragility, difficulty in data acquisition, and inability to transmit and process data in real time. While remote monitoring instruments can perform non-contact measurements, they are costly, lack accuracy and timeliness, and the strong spatiotemporal variability and significant scale effects of baseflow make monitoring particularly challenging in small watersheds in hilly and mountainous areas. Therefore, this invention provides a multi-scale baseflow monitoring method, device, electronic equipment, and storage medium to address the limitations of traditional methods, the high cost and insufficient accuracy and timeliness of existing remote monitoring instruments, and the difficulty in continuous monitoring in small watersheds in hilly and mountainous areas due to complex terrain. This invention achieves non-contact, multi-scale, low-cost, and low-complexity baseflow monitoring while ensuring monitoring accuracy, thus improving baseflow monitoring efficiency.

[0031] According to an embodiment of the present invention, a multi-scale base current monitoring method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] This embodiment provides a multi-scale base current monitoring method. Figure 1 This is a flowchart of a multi-scale baseflow monitoring method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0033] Step S101: Acquire multi-scale monitoring data and GNSS observation data of the target watershed. The multi-scale monitoring data includes satellite data at the watershed scale, synthetic aperture radar data at the river section scale, and microwave radar data at the monitoring station scale.

[0034] Watershed-scale refers to the research scope of the entire watershed, while river segment-scale focuses on a specific section of a river, paying attention to the unique topography and flow characteristics of that section. Monitoring stations are fixed points set up in specific locations to monitor hydrological and other data, such as stations at river cross-sections to monitor water level and flow velocity. Synthetic Aperture Radar (SAR) is an active microwave remote sensing device that can penetrate clouds and fog to acquire high-resolution ground images under different lighting conditions. Microwave radar uses microwave bands to detect targets and is used at monitoring stations to accurately measure parameters such as water flow velocity, providing data for runoff calculation. GNSS, or Global Navigation Satellite System, provides location, altitude, and time information by receiving satellite signals. In baseflow monitoring, GNSS observation data can provide accurate absolute position and water level reference information.

[0035] This step is fundamental to the multi-scale baseflow monitoring method. Its purpose is to collect comprehensive and accurate data to provide a basis for subsequent runoff calculation and baseflow classification.

[0036] Step S102: Based on multi-scale monitoring data and GNSS observation data, calculate the runoff at the basin scale and river section scale by water level inversion, and calculate the runoff at the monitoring station by the basic principles of hydraulics.

[0037] Runoff refers to the volume of water passing through a specific cross-section of a river per unit time. Accurately calculating runoff at different scales allows for a clear understanding of the dynamic changes in water resources within a watershed. In this step, the runoff calculations at the watershed and river section scales are performed using water level inversion. This involves using acquired monitoring data and GNSS observation data to deduce the water level information of the watershed or river section, and then calculating the corresponding runoff based on the relationship between water level and runoff. Runoff at monitoring stations is calculated based on fundamental principles of hydraulics. These principles involve the relationships between parameters such as water velocity, cross-sectional area, and flow rate. By measuring the water velocity and river cross-sectional area at the monitoring station location, the runoff can be obtained using the flow rate calculation formula.

[0038] Step S103: Divide the runoff at each scale into baseflows to obtain the baseflow at each scale.

[0039] In this step, the runoff sequence is regarded as a signal composed of different frequency components. Baseflow usually manifests as a low-frequency signal, while surface runoff and the like manifest as a high-frequency signal. By selecting appropriate filtering parameters, a digital filter is used to separate the low-frequency baseflow signal from the runoff sequence.

[0040] The multi-scale baseflow monitoring method provided in this embodiment combines satellite and GNSS at the watershed scale. Satellite remote sensing technology, with its unique advantage of wide-area coverage, allows a single satellite to comprehensively monitor a large watershed in a short time, eliminating the need for extensive ground monitoring station deployments as in traditional methods. This not only saves significant equipment purchase costs but also reduces subsequent equipment maintenance and personnel operation costs. GNSS provides precise absolute position and water level reference information, which, combined, yields accurate water level information. This combination achieves high-precision monitoring of the macroscopic watershed at a lower cost, avoiding the need for large-scale deployment of high-precision but expensive monitoring equipment. At the river segment scale, synthetic aperture radar (SAR) is used in conjunction with GNSS. SAR, which can be mounted on aircraft or UAVs, enables flexible and efficient monitoring of specific river segments. It has high spatial resolution and can clearly capture detailed information such as topographic relief and water flow velocity within the river segment, providing crucial data support for accurate runoff calculation and baseflow classification. Compared to the large-scale construction of fixed monitoring facilities along river sections, this mobile monitoring method allows for flexible adjustment of the monitoring range and frequency according to actual needs, avoiding equipment idleness and waste, and reducing monitoring costs. GNSS provides precise absolute location and water level reference information, which, combined with other methods, yields accurate water level information, thereby improving the accuracy of runoff calculation. This achieves high-precision monitoring at the river section scale at a lower cost, eliminating the need for extensive deployment of complex and costly monitoring equipment along the river. The monitoring stations utilize a combination of microwave radar and GNSS. Microwave radar offers advantages such as high measurement accuracy, fast response speed, and strong anti-interference capabilities. At the monitoring stations, it can measure parameters such as flow velocity at the river cross-section in real time and accurately, providing high-precision data for runoff calculation.

[0041] Deploying microwave radars across a large area of ​​the monitoring region would not only result in high equipment purchase costs but also significantly increase the difficulty and cost of subsequent maintenance and management. This invention, however, deploys microwave radars only at key monitoring sites, while using other equipment in combination with GNSS at a broader scale, effectively controlling costs and avoiding unnecessary large-scale equipment deployment. By rationally selecting combinations of satellites, synthetic aperture radar, microwave radar, and GNSS at different scales, this invention successfully reduces overall monitoring costs while ensuring monitoring accuracy at each scale, avoiding the need for large-scale deployment of high-cost equipment within the monitoring area, and achieving efficient and economical monitoring objectives.

[0042] This embodiment provides a multi-scale base current monitoring method. Figure 2 This is a flowchart of a multi-scale baseflow monitoring method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0043] Step S201: Acquire multi-scale monitoring data and GNSS observation data for the target watershed. The multi-scale monitoring data includes watershed-scale satellite data, river section-scale synthetic aperture radar data, and monitoring station-scale microwave radar data. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0044] Specifically, synthetic aperture radar data is obtained by aerial surveying using synthetic aperture radar carried by UAVs; microwave radar data is obtained by measurements taken by microwave radar installed at monitoring stations located at the cross-section of the target watershed.

[0045] In some alternative implementations, see [link to implementation details]. Figure 3 For watershed-scale satellite data, Sentinel-1 satellite data was used, with an image resolution of 10m and a revisit period of 6 days. Water level inversion was performed by combining PS-InSAR technology, DEM data, and GNSS-IR data, with an inversion error of <10cm, enabling large-scale, all-weather, and full-watershed monitoring capabilities. For river segment-scale data, a UAV equipped with synthetic aperture radar (SAR) in the L-band was used, with an image resolution of 0.5m and a revisit period of 1 hour. Periodic aerial surveys were conducted, and D-InSAR technology and GNSS-R data were integrated to perform river segment water level inversion, with an inversion error of <5cm, achieving continuous observation at the river segment scale. In hilly and mountainous areas, representative small watersheds were selected, stable river channels were identified, and monitoring stations were established at the river cross-sections. Low-cost microwave radar sensors with an IP68 protection rating were employed, adaptable to environments ranging from -20℃ to 60℃, enabling non-contact, precise measurements. The water level measurement range was 0-20m, with a resolution of 1mm, a monitoring error of <2%, and a data reuse rate of 60%. Power was supplied by solar panels and batteries, achieving real-time monitoring at individual stations. (See [link to relevant documentation]). Figure 4 .

[0046] In some optional implementations, the data collected by the above-mentioned devices or apparatus is transmitted using a low-power LoRa and 4G / 5G dual-mode communication module. LoRa networking is preferred, with a transmission distance of 3km and a power consumption of 0.1W. In areas without network coverage, the system automatically switches to 4G / 5G signals to ensure that the monitoring data is accurately transmitted to the processor.

[0047] Step S202: Based on multi-scale monitoring data and GNSS observation data, calculate the runoff at the watershed scale and river section scale by water level inversion, and calculate the runoff at the monitoring stations by basic hydraulic principles.

[0048] Specifically, step S202 above includes:

[0049] Step S2021: Water level inversion is performed based on satellite data at the watershed scale and synthetic aperture radar data at the river section scale, respectively, and runoff at the watershed scale and river section scale is calculated in combination with GNSS observation data.

[0050] In some optional implementations, step S2021 above includes:

[0051] Step a1: Obtain the phase difference between the two echo images from satellite data at the watershed scale and synthetic aperture radar data at the river section scale, respectively, to obtain the phase difference between satellite data at the watershed scale and synthetic aperture radar data at the river section scale.

[0052] Step a2: Using geometric principles, calculate the water level elevation changes at the watershed scale and the river segment scale using the phase difference of satellite data at the watershed scale and the phase difference of synthetic aperture radar data at the river segment scale, respectively.

[0053]

[0054] In the formula, For water level, The wavelength of satellite data or synthetic aperture radar data. Let be the angle of incidence of the wave. This represents the phase difference between the two echoes.

[0055] Step a3: Based on the water level elevation change values ​​at the basin scale and the river section scale, respectively, and combined with the absolute water level values ​​in the GNSS observation data, obtain the water level calibration values ​​at the basin scale and the river section scale.

[0056] Step a4: Based on the water level calibration values ​​at the watershed scale and the water level calibration values ​​at the river section scale, calculate the runoff at the watershed scale and the river section scale respectively using the hydraulic gradient method.

[0057] Specifically, based on the water level calibration values ​​at the watershed scale and the river reach scale, respectively, the rate of change of water level along the flow direction at both the watershed and river reach scales is determined through gradient calculation. Then, based on these rates of change, and in conjunction with preset hydraulic conductivity, the runoff at both the watershed and river reach scales is calculated using the following formulas:

[0058]

[0059] In the formula, h is the water level calibration value, i.e., the water head, and x represents the distance in the river direction. This represents the hydraulic gradient along the direction of water flow, where Q is the runoff volume. is the hydraulic conductivity.

[0060] Step S2022: Calculate the runoff at the monitoring station based on the microwave radar data at the monitoring station scale using basic hydraulic principles.

[0061] In some optional implementations, step S2022 above includes:

[0062] Step b1: Obtain the frequency changes of the two echo signals from microwave radar data at the monitoring station scale, and calculate the water flow velocity at the monitoring station location based on the Doppler effect according to the frequency changes.

[0063]

[0064] In the formula, For flow rate, The speed at which radar waves propagate in water. For Doppler frequency shift, The carrier frequency of the radar. The angle between the radar wave and the direction of water flow.

[0065] Step b2: Obtain the cross-sectional area of ​​the river at the location of the monitoring station.

[0066] Step b3: Based on the water flow velocity and river cross-sectional area at the monitoring station location, calculate the runoff at the monitoring station using basic hydraulic principles.

[0067]

[0068] In the formula, For runoff, This represents the cross-sectional area.

[0069] Step S203: Divide the runoff at each scale into baseflows to obtain the baseflow at each scale.

[0070] Specifically, low-frequency base flow rates are separated from runoff at various scales using digital filtering with preset filtering parameters:

[0071]

[0072]

[0073] In the formula, These are the filter parameters. , Let be the runoff volume at times t and t-1, in m³ / s; , Let m be the surface runoff at times t and t-1. 3 / s; Let m be the basic flux at time t. 3 / s.

[0074] Preferably, the filtering parameters used in this step are selected as follows: =0.90 is the optimal parameter for base current segmentation, with a segmentation accuracy of 98.5%.

[0075] In some optional implementations, a flow time series is formed in chronological order, with a flow error of <8%. The baseflow segmentation module, based on an improved digital filtering method, automatically segments the continuous daily flow series, automatically calculating the daily baseflow flow and baseflow index (BFI) for each monitoring station-river segment-basin, achieving a segmentation accuracy of 98.5%. Users can access relevant data at any time via computer or mobile terminal, view real-time water levels, flow process lines, baseflow segmentation result charts, data anomalies or equipment malfunctions, and obtain historical data reports.

[0076] The multi-scale base current monitoring method provided in this embodiment has the following beneficial effects:

[0077] 1. Non-contact multi-source collaborative monitoring: Integrating technologies such as satellite remote sensing, drones and microwave radar, it realizes all-time, non-contact monitoring, avoiding the problems of traditional contact equipment being easily damaged in extreme environments such as floods and silt and water flow disturbance, and adapting to complex terrains such as remote, narrow, and vegetated areas.

[0078] 2. Multi-scale fusion observation based on water level: Using water level as the key parameter, multi-scale monitoring is constructed to realize continuous observation of single station (millimeter level), river section (centimeter level), and watershed (10m resolution). The data reuse rate is increased by 60%, and the station deployment cost and maintenance difficulty are significantly reduced.

[0079] 3. High-frequency and high-precision integrated monitoring system: The space-based Sentinel-1 satellite updates every 6 days with a resolution of 10m; the UAV-equipped synthetic aperture radar cruises every hour with a resolution of 0.5m; the microwave radar collects data every 5 minutes with a resolution of 1mm, and the water level monitoring error is <2%; multi-scale collaboration enables all-time, high-precision water level monitoring in hilly and mountainous watersheds.

[0080] 4. Automatic baseflow segmentation and intelligent analysis: An improved digital filtering method is used to achieve automatic baseflow segmentation with an accuracy of 98.5%. The time for a single watershed analysis is reduced from several days of manual work to 15 minutes, reducing labor costs by more than 90%.

[0081] The method of the present invention will be explained and illustrated below using specific scenarios.

[0082] Scenario 1: In a watershed area of ​​2.90 km² 2In a small watershed with an elevation of 80-560m and a main channel length of 22.7km, a straight and stable section of the river was selected. A concrete foundation was poured on the bank, and a monitoring bracket was erected. A DX-WLX-2 microwave radar water level gauge was fixedly installed facing the water surface at a 45° angle. The solar panel was installed tilted to the south. The battery box, main controller, and communication module were fixed in a safe position above the bracket.

[0083] Repeatedly adjust the filter parameters in the digital filtering method The values ​​of the base current value and the filtering time T' are used to obtain the optimal parameters and accuracy for base current segmentation. The debugging results are shown in Table 1. When T'=2 and T'=0.90, the BFI value is closest to that of the basecurrent index method, and the basecurrent segmentation accuracy reaches 98.5%. Therefore, =0.90, T'=2 are the optimal parameters for baseflow separation using the digital filtering method in the Pengchongjian small watershed.

[0084] The water level data is collected every 5 minutes, and the data is packaged every hour and sent to the processor for storage and analysis via a communication device. Every morning at 8:00 AM, the previous day's flow sequence data is retrieved, and baseflow segmentation calculations are performed; a single watershed analysis takes only 15 minutes. This processor can be configured on a cloud platform, allowing administrators to log in via computer or mobile phone to view water level, flow process lines, and baseflow segmentation charts in real time.

[0085] Table 1 Comparison of BFI values ​​using the two methods

[0086]

[0087] Scenario 2: In a drainage area of ​​485 km² 2 In a watershed with an elevation of 10–1084 m and a main channel length of 57.3 km, 14 straight and stable study sections were selected. Monitoring stations were established along the riverbanks, and ONSET HOBO U20-001 water level gauges (IP68 protection rating, adaptable to environments from -20℃ to 60℃, with a range of 0–20 m and a resolution of 1 mm) were used to achieve real-time continuous water level observation at a single station scale. The water level monitoring error was <2%, and the equipment failure rate was <5%. Once a month, a UAV equipped with synthetic aperture radar (SAP) in the L-band was used to collect hydrological information at the river section scale with an image resolution of 0.5 m and a revisit period of 1 hour. Water level inversion was performed using D-InSAR technology and GNSS-R data, with an inversion error of <5 cm, to retrieve the base flow at the river section scale.

[0088] Data is uploaded to the processor via a low-power LoRa and 4G / 5G dual-mode communication module to ensure data accuracy. Basestream segmentation, data analysis, and data export are performed based on an improved digital filtering method. Monitoring results are as follows: Figure 5 As shown, this embodiment efficiently identified the baseflow proportion of the watershed through baseflow segmentation. In 2023, the baseflow proportion of the watershed was 58.8%, and the number of days with a baseflow index (BFI) > 0.90 reached 89.6%, indicating that the groundwater recharge of the watershed was stable and the baseflow contribution was significant.

[0089] This embodiment also provides a multi-scale base current monitoring device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0090] This embodiment provides a multi-scale base current monitoring device, such as... Figure 6 As shown, it includes:

[0091] The data acquisition module 601 is used to acquire multi-scale monitoring data and GNSS observation data of the target watershed. The multi-scale monitoring data includes satellite data at the watershed scale, synthetic aperture radar data at the river section scale, and microwave radar data at the monitoring station scale.

[0092] The runoff calculation module 602 is used to calculate the runoff at the watershed scale and river section scale by means of water level inversion based on multi-scale monitoring data and GNSS observation data, and to calculate the runoff at monitoring stations by means of basic hydraulic principles.

[0093] The baseflow segmentation module 603 is used to segment the runoff at each scale into baseflows to obtain the baseflow at each scale.

[0094] The multi-scale baseflow monitoring device provided in this embodiment of the invention can execute the multi-scale baseflow monitoring method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0095] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0096] The following is a detailed reference. Figure 7This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 701, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 702 or a program loaded from memory 708 into random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the electronic device. The processor 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0097] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows electronic devices to exchange data via wireless or wired communication with other devices. Although Figure 7 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0098] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 709, or installed from a memory 708, or installed from a ROM 702. When the computer program is executed by the processor 701, it performs the functions defined in the multi-scale basestream monitoring method of the embodiments of the present invention.

[0099] Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0100] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the multi-scale basecurrent monitoring method shown in the above embodiments is implemented.

[0101] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0102] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A multi-scale baseflow monitoring method, characterized in that, The method includes: Acquire multi-scale monitoring data and GNSS observation data of the target watershed, including satellite data at the watershed scale, synthetic aperture radar data at the river section scale, and microwave radar data at the monitoring station scale. Based on the multi-scale monitoring data and GNSS observation data, the runoff at the basin scale and river section scale is calculated by water level inversion, and the runoff at the monitoring stations is calculated by the basic principles of hydraulics. The runoff at each scale is divided into baseflows to obtain the baseflow at each scale.

2. The multi-scale baseflow monitoring method according to claim 1, characterized in that, The synthetic aperture radar data is obtained by aerial surveying using a synthetic aperture radar mounted on an unmanned aerial vehicle; the microwave radar data is obtained by measurement using microwave radar installed at a monitoring station located at the cross-section of the target watershed.

3. The multi-scale baseflow monitoring method according to claim 1, characterized in that, The steps of calculating runoff at the watershed and river reach scales using water level inversion based on the multi-scale monitoring data and GNSS observation data, and calculating runoff at monitoring stations using basic hydraulic principles, include: Water level inversion was performed based on satellite data at the watershed scale and synthetic aperture radar data at the river section scale, and runoff at the watershed scale and river section scale was calculated by combining GNSS observation data. The runoff at the monitoring station is calculated based on microwave radar data at the monitoring station scale using basic hydraulic principles.

4. The multi-scale baseflow monitoring method according to claim 3, characterized in that, The steps of performing water level inversion based on satellite data at the watershed scale and synthetic aperture radar data at the river reach scale, and calculating runoff at the watershed scale and river reach scale in conjunction with GNSS observation data, include: The phase difference between the two echo images was obtained from satellite data at the watershed scale and synthetic aperture radar data at the river section scale, respectively, to obtain the phase difference between satellite data at the watershed scale and synthetic aperture radar data at the river section scale. The water level elevation changes at the watershed scale and the river segment scale are calculated using geometric principles based on the phase difference of satellite data at the watershed scale and the phase difference of synthetic aperture radar data at the river segment scale, respectively. Based on the water level elevation changes at the basin scale and the river section scale, respectively, and combined with the absolute water level values ​​in the GNSS observation data, the water level calibration values ​​at the basin scale and the river section scale are obtained. Based on the water level calibration values ​​at the basin scale and the river section scale, the runoff at the basin scale and the river section scale are calculated respectively using the hydraulic gradient method.

5. The multi-scale baseflow monitoring method according to claim 4, characterized in that, The steps of calculating runoff at the watershed and river reach scales respectively using the hydraulic gradient method based on the water level calibration values ​​at the watershed and river reach scales include: Based on the water level calibration values ​​at the watershed scale and the water level calibration values ​​at the river section scale, the rate of change of water level along the flow direction at the watershed scale and the rate of change of water level along the flow direction at the river section scale are determined by gradient calculation. Based on the rate of change of water level along the flow direction at the basin scale and the rate of change of water level along the flow direction at the river section scale, and in conjunction with the preset hydraulic conductivity, the runoff at the basin scale and river section scale are calculated respectively.

6. The multi-scale baseflow monitoring method according to claim 3, characterized in that, The step of calculating the runoff at a monitoring station based on microwave radar data at the monitoring station scale using basic hydraulic principles includes: The frequency changes of two echo signals are obtained from microwave radar data at the monitoring station scale, and the water flow velocity at the monitoring station location is calculated based on the Doppler effect according to the frequency changes. Obtain the cross-sectional area of ​​the river at the location of the monitoring station; Based on the water flow velocity and river cross-sectional area at the monitoring station location, the runoff at the monitoring station is calculated using basic hydraulic principles.

7. The multi-scale baseflow monitoring method according to claim 1, characterized in that, The step of dividing runoff at each scale into baseflows to obtain the baseflow at each scale includes: The low-frequency base flow rate is separated from the runoff at various scales using a digital filtering method with preset filtering parameters.

8. A multi-scale base current monitoring device, characterized in that, The device includes: The data acquisition module is used to acquire multi-scale monitoring data and GNSS observation data of the target watershed. The multi-scale monitoring data includes satellite data at the watershed scale, synthetic aperture radar data at the river section scale, and microwave radar data at the monitoring station scale. The runoff calculation module is used to calculate the runoff at the watershed scale and river section scale by means of water level inversion based on the multi-scale monitoring data and GNSS observation data, and to calculate the runoff at the monitoring station by means of basic hydraulic principles. The baseflow segmentation module is used to segment the runoff at various scales into baseflows to obtain the baseflow at each scale.

9. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the multi-scale base current monitoring method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the multi-scale baseflow monitoring method according to any one of claims 1 to 7.

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