Strip mine area daily soil water content production method and system based on hydrological model

Abstract

The invention discloses a hydrological model-based strip mine area daily soil water content production method and system, and the method comprises the steps: firstly adding a strip mine area dynamic terrain generation module, and obtaining a strip mine area dynamic terrain DEM data set based on an unmanned plane oblique photogrammetry technology in combination with static basic digital elevation model (DEM) data; secondly, based on river flow direction data, cumulative flow data, rainfall data, potential evapotranspiration data, hydrological stations and runoff data, a drainage basin range determination module determines a drainage basin range where the strip mine area is located, and a CREST model is calibrated through a CREST model calibration module to obtain model parameters suitable for a target drainage basin; the conceptualized expression of the water circulation physical process of the target drainage basin is realized; and finally, a soil water content data set with daily scale, long time sequence and high resolution of 0-2m from the ground surface in the target strip mine area is obtained through simulation of a soil water content simulation module. According to the method, a daily-scale, long-time-sequence and high-resolution soil water content data product which is 0-2 m away from the ground surface and adapts to a strip mine area scene can be obtained, long-time-sequence monitoring of the soil water content of the strip mine area can be achieved, and data support is provided for excavating an ecological environment evolution mechanism of the strip mine area, achieving precise management of reclamation vegetation of the strip mine area and the like.

Description

Technical Field

[0001] The present invention relates to the fields of mining, hydrology, ecology, remote sensing and geographic information, and particularly to a daily soil water content production method and system for open-pit mining areas based on a hydrological model. Background Art

[0002] The large-scale exploitation of coal resources in open-pit mining areas has a negative impact on their ecological environment, hindering the green and sustainable development of mining areas. The soil water content in mining areas plays a very important role in the water cycle, energy cycle, and carbon cycle. It is one of the main ecological parameters affected by coal mining and also a restrictive factor for ecological restoration in arid and semi-arid mining areas in the northwest, the main coal-producing areas in China. Monitoring it has important practical significance. Currently, for the monitoring of soil water content, although the traditional ground monitoring method has relatively accurate monitoring results, it is time-consuming and laborious and cannot obtain areal data of mining areas. At the same time, open-pit mining areas have a long resource exploitation life cycle, and traditional methods cannot obtain historical data, so they cannot meet the monitoring requirements of soil water content in open-pit mining areas. Although the rise of remote sensing technology can conduct rapid and areal monitoring of open-pit mining areas, optical / thermal infrared remote sensing is easily affected by weather, and its temporal resolution is mostly greater than 5 days, making it difficult to continuously and effectively monitor the soil water content in open-pit mining areas; active microwave also cannot meet the high-frequency monitoring requirements of open-pit mining area scenarios due to its temporal resolution; passive microwave remote sensing has a rough spatial resolution (20 - 40 kilometers) of its monitoring data because of the long wavelength of the electromagnetic waves it uses, and is not applicable to small-scale scenarios in open-pit mining areas; in addition, remote sensing monitoring technology is limited by the wavelength of electromagnetic waves, and it can only monitor the surface soil water content within 0 - 5 cm from the ground surface. Therefore, the currently common methods cannot obtain long-time series, high spatio-temporal resolution soil water content monitoring data applicable to open-pit mining area scenarios. Summary of the Invention

[0003] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a daily soil water content production method and system for open-pit mining areas based on a hydrological model, add a dynamic terrain generation module for open-pit mining areas, and based on the unmanned aerial vehicle (UAV) oblique photogrammetry technology, combined with static basic digital elevation model (DEM) data, obtain a dynamic terrain DEM dataset for open-pit mining areas. Determine the watershed range where the open-pit mining area is located through a watershed range determination module based on river flow direction data, cumulative flow data, rainfall data, potential evapotranspiration data, hydrological station and runoff data, and calibrate the CREST model through a CREST model calibration module to obtain model parameters applicable to the target watershed, realizing a conceptual expression of the physical process of the water cycle in the target watershed. Further simulate through a soil water content simulation module to obtain a soil water content dataset with daily scale, long-time series, and high resolution at 0 - 2 m from the ground surface for the target open-pit mining area.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] In a first aspect, a method for producing daily soil water content in an open-pit mining area based on a hydrological model is as follows:

[0006] S10. Determine the target open-pit mining area and its watershed, collect the watershed data and basic geographic data of the target open-pit mining area, determine the outlet position based on the watershed data, and determine the minimum watershed area of the target open-pit mining area based on the basic geographic data;

[0007] S20. Obtain the basic watershed hydrological data of the minimum watershed area;

[0008] S30. Add a dynamic terrain data module for the open-pit mining area to the CREST hydrological model to obtain an improved CREST model, and couple the unmanned aerial vehicle oblique photogrammetry technology and the improved CREST model to generate a dynamic change terrain data set of the open-pit mining area;

[0009] S40. Calibrate the improved CREST model based on the observed data of the watershed hydrological station, and adjust and optimize the model parameters to match the target watershed;

[0010] S50. Simulate the physical process of the water cycle in the target open-pit mining area based on the basic watershed hydrological data and the parameters of the adjusted and optimized model, and obtain a long-time series, daily-scale, and high-resolution soil water content data set of the target open-pit mining area at a height of 0-2 m from the ground surface.

[0011] Furthermore, the method for producing daily soil water content in an open-pit mining area based on a hydrological model of the present invention further includes the following method:

[0012] The following steps are further included in step S10 of the present invention:

[0013] S101. The watershed data includes the mining right boundary data, regional cumulative flow data, and basic information of the watershed where the target open-pit mining area is located, and the basic geographic data includes regional digital elevation model (DEM) data;

[0014] S102. According to the regional cumulative flow data, based on the principle that the cumulative flow per square meter greater than 24 is set as surface runoff, use the Raster Calculator tool in the Arcmap software to extract runoff and obtain regional runoff data;

[0015] S103. Determine the outlet position according to the mining right boundary data, regional runoff data, and basic information of the watershed where the target open-pit mining area is located, and the outlet position is within the spatial range of the regional runoff;

[0016] S104. According to the regional digital elevation model (DEM) data and the outlet position, extract the watershed range by using the Watershed tool in the Arcmap software.

[0017] S105. Determine whether the watershed range obtained in step S103 includes the target open-pit mining area range according to the mining right boundary data of the open-pit mining area. If it includes, this range is the final range of the watershed; if it does not include, repeat steps S103 and S104 until the condition that the watershed range includes the target open-pit mining area range is met.

[0018] S106. The regional cumulative flow data is collected from the HydroSHEDS platform, the regional digital elevation model DEM data is static data collected from the Google Earth Engine platform, the mining right boundary data is collected from the national mining right holders' exploration and mining information publicity system platform of the Ministry of Natural Resources, and the basic information of the watershed is obtained from the official websites of local governments.

[0019] The following steps are also included in step S20 of the present invention:

[0020] The watershed hydrological basic data includes river flow direction data, cumulative flow data, daily-scale historical rainfall data, daily-scale historical potential evapotranspiration data, hydrological stations and runoff number observation data. The river flow direction data and the cumulative flow data are collected from the HydroSHEDS platform; the daily-scale historical rainfall data is collected from the NASA Earth Science Data Platform Earthdata; the daily-scale historical potential evapotranspiration data is collected from the open data platform of the University of Bristol; the hydrological stations and runoff number observation data are collected from hydrological statistical yearbooks.

[0021] The following steps are also included in step S30 of the present invention:

[0022] S301. Use the unmanned aerial vehicle (UAV) oblique photogrammetry technology to obtain images of the target open-pit mining area. That is, according to the specific situation of the target open-pit mining area, select a weather suitable for UAV flight with no cloud and rain and small wind speed, plan the flight route, altitude and shooting angle of the UAV, and the UAV flies according to the planned route to shoot multi-angle images of the target open-pit mining area.

[0023] S302. Import the photos taken by the UAV into the Context Capture platform and automatically process the photos, extract feature points and generate three-dimensional point cloud data, and optimize the generated point cloud data to remove noise and unnecessary points.

[0024] S303. Collect ground remote sensing images of the target open-pit mining area. The remote sensing images include satellite images and aerial photography images. Use image processing technology to extract ground points from the remote sensing images, and fuse the extracted ground points with the optimized three-dimensional point cloud data to obtain elevation accuracy fusion data.

[0025] S304. Use the tools built in the Context Capture platform to convert the elevation accuracy fusion data into the initial digital elevation model (DEM) data;

[0026] S305. Obtain the static digital elevation model (DEM) data of the watershed area of the target open-pit mining area, compare and analyze the initial digital elevation model (DEM) data and the static digital elevation model (DEM) data of the watershed to identify the terrain change areas of the target open-pit mining area. According to the terrain change areas, update the static digital elevation model (DEM) data of the watershed in real time and construct a dynamic terrain data module for the open-pit mining area. Obtain the dynamic digital elevation model (DEM) data of the watershed from the dynamic terrain data module for the open-pit mining area;

[0027] S306. Regularly use an unmanned aerial vehicle (UAV) for oblique photography to obtain the latest real-time photos of the target open-pit mining area. Repeat steps S301 to S305, and integrate all the updated static digital elevation model (DEM) data of the watershed to generate a dynamic digital elevation model (DEM) dataset for the watershed. The dynamic digital elevation model (DEM) dataset for the watershed is the dynamic change terrain dataset for the open-pit mining area.

[0028] The steps in step S40 of the present invention further include the following steps:

[0029] S401. Extract the hydrological station location data and flow observation data based on the observation data of the watershed hydrological stations. The hydrological station location data includes the longitude and latitude information of the hydrological stations, and the flow observation data includes the runoff flow data on a daily scale;

[0030] S402. Set the initial parameters of the improved CREST model according to experience or previous research, run the improved CREST model using the initial parameters to generate the initial simulated runoff flow data, and calculate the target evaluation indicators using a calibration model. The target evaluation indicators include the Nash efficiency coefficient log-NSCE, the Pearson correlation coefficient CC, and the relative bias Bias. The mathematical expression of the calibration model is:

[0031] The mathematical expression of the Nash efficiency coefficient log-NSCE is:

[0032]

[0033] The mathematical expression of the Pearson correlation coefficient CC is:

[0034]

[0035] The mathematical expression of the relative bias Bias is:

[0036]

[0037] where Q t,oDenote the observed runoff flow value at time t as Q t,s Denote the simulated runoff flow value at time t as Denote the average value of the observed runoff flow value at time t as Denote the average value of the simulated runoff flow value at time t;

[0038] S403. Determine the model effect according to the Nash efficiency coefficient log-NSCE, the Pearson correlation coefficient CC and the relative bias Bias. Ideally, log-NSCE approaches 1 infinitely, CC approaches 1 infinitely, and Bias approaches 0 infinitely. When log-NSCE is greater than 0.36, CC is greater than 0.6, and Bias is between ±40%, the simulation effect of the model is acceptable.

[0039] The steps in step S50 of the present invention further include the following steps:

[0040] S501. Input the basin hydrological basic data and the model parameters calibrated in step S40 into the improved CREST model, and set the time step of the model, and the time step is on a daily scale;

[0041] S502. Run the improved CREST model to simulate the water cycle process of the open-pit mining area, and obtain a long-time series, daily-scale and high-resolution soil moisture content dataset with a depth of 0-2m from the surface of the target open-pit mine.

[0042] In a second aspect, a daily soil moisture content production system for an open-pit mining area based on a hydrological model includes:

[0043] A basin range determination module, configured to determine the target open-pit mining area and its basin range, collect basin data and basic geographic data of the target open-pit mining area, determine the outlet position based on the basin data, and determine the basin area of the target open-pit mining area based on the basic geographic data;

[0044] A data acquisition and processing module, configured to obtain the basin hydrological basic data of the basin area;

[0045] An open-pit mining area dynamic terrain generation module, configured to obtain an improved CREST model by adding an open-pit mining area dynamic terrain data module based on the CREST hydrological model, and couple the unmanned aerial vehicle oblique photogrammetry technology and the improved CREST model to generate a dynamic change terrain dataset of the open-pit mining area;

[0046] A CREST model calibration module, configured to calibrate the improved CREST model based on the basin hydrological basic data, and adjust and optimize the model parameters to match the target basin;

[0047] A soil water content simulation module, which is used to simulate the physical process of the water cycle in the target open-pit mining area based on the basin hydrological basic data and the parameters of the adjusted and optimized model, and obtain a high-resolution soil water content dataset with long time series, daily scale and 0-2m above the ground surface in the target open-pit mining area.

[0048] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0049] (1) The present invention solves a number of problems in traditional soil water content monitoring methods, improves the monitoring range and frequency of the soil water content dataset, has important value for fields such as the mining field, the hydrological field, the ecological field, remote sensing and geographic information, etc., can effectively obtain the soil water content data in the open-pit mining area, and thus provides strong support for the management and maintenance work of the reclaimed vegetation in the open-pit mining area.

[0050] (2) Aiming at the characteristics of the dynamic terrain change in the target open-pit mining area, the present invention first couples the dynamic terrain of the open-pit mining area based on the unmanned aerial vehicle (UAV) oblique photogrammetry technology with the CREST hydrological model, enables the CREST hydrological model to be applied to the open-pit mining area scene with dynamic terrain changes, realizes the simulation of the physical process of the water cycle in the open-pit mining area scene, and provides theoretical and technical support for exploring the evolution mechanism of the ecological environment in the open-pit mining area.

[0051] (3) Based on the mining right boundary data, static basic digital elevation model (DEM) data, river flow direction data, cumulative flow data, daily scale historical rainfall data, daily scale historical potential evapotranspiration data, hydrological station and runoff observation data of the target open-pit mining area, the present invention improves the CREST model to add a dynamic terrain data module of the open-pit mining area, calibrates the model parameters applicable to the basin where the target open-pit mining area is located, and simulates and obtains a 0-2m soil water content dataset with daily scale, long time series and high resolution in the open-pit mining area, providing data support for exploring the evolution mechanism of the ecological environment in the open-pit mining area and realizing the precise management of the reclaimed vegetation in the open-pit mining area, etc.

[0052] (4) Based on the unmanned aerial vehicle (UAV) oblique photogrammetry technology and combined with the static digital elevation model (DEM) data, the present invention realizes the production of the DEM dataset of the dynamic terrain change in the open-pit mining area, providing basic data support for the simulation of the physical process of the water cycle in the target basin and the simulation of the high-resolution soil water content data.

[0053] (5) Based on the dynamic digital elevation model (DEM) data, river flow data, accumulated flow data, rainfall data, potential evapotranspiration data, hydrological stations and runoff data of the watershed where the target open-pit mine is located, the present invention obtains a parameter model suitable for the target watershed by improving the CREST model calibration, thereby simulating the physical process of water circulation in the open-pit mine scene. Based on this, the long-term and daily-scale surface soil moisture data products of the open-pit mine are further simulated to provide scientific data for the ecological environment protection of the mining area. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the principle flow of the method of the present invention;

[0055] Figure 2 This is a process diagram of a dynamic terrain data generation module added in this embodiment;

[0056] Figure 3 It is a principle structure block diagram of the system of the present invention. DETAILED DESCRIPTION

[0057] The present invention is further described in detail below in conjunction with embodiments:

[0058] Embodiment 1

[0059] like Figures 1 to 2 As shown, the method for producing daily soil moisture content in open-pit mines based on the hydrological model is as follows:

[0060] S10, determining the target open-pit mine area and its watershed, collecting watershed data and basic geographic data of the target open-pit mine area, determining the outlet location based on the watershed data, and determining the minimum watershed area of ​​the target open-pit mine area based on the basic geographic data;

[0061] S20, obtaining basic watershed hydrological data of the smallest watershed area;

[0062] S30. Based on the CREST hydrological model, a dynamic terrain data module for open-pit mines is added to obtain an improved CREST model. The UAV oblique photogrammetry technology and the improved CREST model are coupled to generate a dynamically changing terrain data set for open-pit mines.

[0063] S40, calibrate the improved CREST model based on the observation data of the basin hydrological stations, adjust and optimize the model parameters to match the target basin;

[0064] S50. Based on the basic hydrological data of the watershed and the parameters of the adjusted and optimized model, the physical process of water cycle in the target open-pit mine area is simulated to obtain a soil moisture data set of the target open-pit mine area with a long time series, daily scale and high resolution of 0-2m from the surface.

[0065] Step S10 of this embodiment includes the following steps:

[0066] S101. The basin data includes the mining right boundary data, regional cumulative flow data, and basic information of the basin where the target open-pit mining area is located. The basic geographic data includes regional digital elevation model (DEM) data;

[0067] S102. According to the regional cumulative flow data, based on the principle that the cumulative flow per square meter greater than 24 is set as surface runoff, use the Raster Calculator tool in Arcmap software to extract runoff and obtain regional runoff data;

[0068] S103. Determine the outlet position according to the mining right boundary data, regional runoff data, and basic information of the basin where it is located. The outlet position is within the spatial range of the regional runoff;

[0069] S104. According to the regional digital elevation model (DEM) data and the outlet position, use the Watershed tool in Arcmap software to extract the basin range.

[0070] S105. According to the mining right boundary data of the open-pit mining area, judge whether the basin range obtained in step S103 includes the target open-pit mining area range. If it includes, this range is the final range of the basin. If it does not include, repeat steps S103 and S104 until the condition that the basin range includes the target open-pit mining area range is met.

[0071] S106. The regional cumulative flow data is collected from the HydroSHEDS platform. The regional digital elevation model (DEM) data is static data collected from the Google Earth Engine platform. The mining right boundary data is collected from the National Mining Rights Exploration and Exploitation Information Publicity System platform of the Ministry of Natural Resources. The basic information of the basin where it is located is obtained from the official website of the local government.

[0072] Step S20 of this embodiment includes the following steps:

[0073] The basic hydrological data of the basin includes river flow direction data, cumulative flow data, daily-scale historical rainfall data, daily-scale historical potential evapotranspiration data, hydrological stations, and runoff observation data. The river flow direction data and the cumulative flow data are collected from the HydroSHEDS platform; the daily-scale historical rainfall data is collected from the NASA Earth Science Data Platform Earthdata; the daily-scale historical potential evapotranspiration data is collected from the open data platform of the University of Bristol; the hydrological stations and runoff observation data are collected from the hydrological statistics yearbook.

[0074] Step S30 of this embodiment includes the following steps:

[0075] S301, using the UAV oblique photogrammetry technology to obtain images of the target open-pit mine area, that is, according to the specific conditions of the target open-pit mine area, selecting weather suitable for UAV flight with no clouds or rain and low wind speed, planning the flight route, altitude and shooting angle of the UAV, and the UAV flies according to the planned route to shoot multi-angle images of the target open-pit mine area;

[0076] S302, importing the photos taken by the drone into the Context Capture platform and automatically processing the photos, extracting feature points and generating three-dimensional point cloud data, optimizing the generated point cloud data, and removing noise and unnecessary points;

[0077] S303, collecting ground remote sensing images of the target open-pit mine area, wherein the remote sensing images include satellite images and aerial photography images, extracting ground points from the remote sensing images using image processing technology, and fusing the extracted ground points with the optimized three-dimensional point cloud data to obtain elevation precision fused data;

[0078] S304. Use the tools provided by the Context Capture platform to convert the elevation accuracy fusion data into the initial digital elevation model DEM data;

[0079] S305, obtaining the static digital elevation model DEM data of the watershed area of ​​the target open-pit mine area, comparing and analyzing the initial digital elevation model DEM data and the static digital elevation model DEM data of the watershed to identify the terrain change area of ​​the target open-pit mine area, updating the static digital elevation model DEM data of the watershed in real time according to the terrain change area and constructing a dynamic terrain data module of the open-pit mine area, and obtaining the dynamic digital elevation model DEM data of the watershed from the dynamic terrain data module of the open-pit mine area;

[0080] S306. Regularly use drone oblique photography to obtain the latest real-time photos of the target open-pit mining area, repeat steps S301 to S305, integrate all updated watershed static digital elevation model DEM data, and generate a watershed dynamic digital elevation model DEM dataset, which is the dynamically changing terrain dataset of the open-pit mining area.

[0081] In this embodiment, step S40 includes the following steps:

[0082] S401, extracting hydrological station location data and flow observation data based on the basin hydrological station observation data, wherein the hydrological station location data includes the latitude and longitude information of the hydrological station, and the flow observation data includes the runoff flow data on a daily scale;

[0083] S402. Set the initial parameters for improving the CREST model based on experience or previous research. Run the improved CREST model using the initial parameters to generate initial simulated runoff flow data. Calculate the target evaluation indicators using the calibration model. The target evaluation indicators include the Nash efficiency coefficient log-NSCE, the Pearson correlation coefficient CC, and the relative bias Bias. The mathematical expression of the calibration model is:

[0084] The mathematical expression of the Nash efficiency coefficient log-NSCE is:

[0085]

[0086] The mathematical expression of the Pearson correlation coefficient CC is:

[0087]

[0088] The mathematical expression of the relative bias Bias is:

[0089]

[0090] Where, Q t,o represents the observed runoff flow value at time t, and Q t,s represents the simulated runoff flow value at time t, represents the average value of the observed runoff flow values at time t, represents the average value of the simulated runoff flow values at time t;

[0091] S403. Determine the model effect based on the Nash efficiency coefficient log-NSCE, the Pearson correlation coefficient CC, and the relative bias Bias. Ideally, log-NSCE approaches 1 infinitely, CC approaches 1 infinitely, and Bias approaches 0 infinitely. When log-NSCE is greater than 0.36, CC is greater than 0.6, and Bias is between ±40%, the simulation effect of the model is acceptable.

[0092] In this embodiment, step S50 includes the following steps:

[0093] S501. Input the basin hydrological basic data and the model parameters calibrated in step S40 into the improved CREST model, and set the time step of the model. The time step is on a daily scale;

[0094] S502. Run the improved CREST model to simulate the water cycle process in the open-pit mining area, and obtain a dataset of soil moisture content with long time series, daily scale, and high resolution at a depth of 0 - 2 m from the ground surface in the target open-pit mine.

[0095] As Figure 3 shown, the daily soil moisture content production system in the open-pit mining area based on the hydrological model is characterized by including:

[0096] A basin scope determination module, configured to determine a target open-pit mining area and its basin scope, collect basin data and basic geographic data of the target open-pit mining area, determine the outlet position based on the basin data, and determine the basin area of the target open-pit mining area based on the basic geographic data;

[0097] A data acquisition and processing module, configured to obtain the basic basin hydrological data of the basin area;

[0098] An open-pit mining area dynamic terrain generation module, configured to obtain an improved CREST model by adding an open-pit mining area dynamic terrain data module to the CREST hydrological model, and couple the UAV oblique photogrammetry technology and the improved CREST model to generate a dynamic change terrain data set of the open-pit mining area;

[0099] A CREST model calibration module, configured to calibrate the improved CREST model based on the basic basin hydrological data, and adjust and optimize the model parameters to match the target basin;

[0100] A soil water content simulation module, configured to simulate the physical process of the water cycle in the target open-pit mining area based on the basic basin hydrological data and the parameters of the adjusted and optimized model, and obtain a long time series, daily scale and high-resolution soil water content data set with a depth of 0-2 m from the ground surface in the target open-pit mining area.

[0101] Embodiment 2

[0102] As Figures 1 to 2 shown, a method and system for producing daily soil water content in an open-pit mining area based on a hydrological model are as follows:

[0103] A. Determine the target open-pit mining area and its basin, collect the mining rights boundary data of the target open-pit mining area, collect the regional static basic digital elevation model DEM data, river data, river flow data, cumulative flow data, rainfall data, potential evapotranspiration data, hydrological stations and runoff observation data of the target basin. The mining rights boundary data of the target open-pit mining area in this embodiment is collected and obtained through the National Mining Rights Exploration and Exploitation Information Publicity System Platform of the Ministry of Natural Resources, the static basic digital elevation model DEM data and rainfall data are obtained through the NASA Earth Science Data Platform Earthdata, the river flow data, cumulative flow data and runoff data of the study area are obtained through the HydroSHEDS project website (https: / / www.hydrosheds.org / ), the daily scale historical rainfall data is obtained through the National Meteorological Science Data Center (https: / / data.cma.cn / ), the daily scale historical potential evapotranspiration data is obtained through the Bristol University data platform (https: / / data.bris.ac.uk / data / dataset), and the hydrological station and runoff data are obtained through the hydrological yearbook. The collected data is used to simulate the soil moisture content in the open-pit mining area.

[0104] A1. Determination of watershed scope: Combined with regional cumulative flow data, based on the principle that cumulative flow per square meter greater than 24 is set as surface runoff, the Raster Calculator tool in Arcmap software is used to extract runoff and obtain regional runoff data; combined with basic watershed information, the outlet position is set on the surface runoff data; on the ArcGIS platform, the watershed is extracted through the Watershed tool to ensure that the watershed scope completely includes the target open-pit mining area.

[0105] A2. Preprocessing of hydrological data: For daily historical rainfall data, use Python to analyze its longitude and latitude changes and convert it into tif format; for daily historical potential evapotranspiration data, use Python to read its daily data and convert it into tif format; for hydrological sites, create their location point shp data through ArcGIS platform; for runoff observation data, convert its text and image data into csv table data.

[0106] A3. UAV oblique photogrammetry: Determine the time for UAV to perform oblique photogrammetry according to weather conditions, plan the UAV flight route in the mining rights area of ​​the open-pit mine, perform UAV field flight data collection, set the lateral overlap to 60°, the heading overlap to 70°, and the gimbal angle to -45°.

[0107] A4. Import the ground photos taken by the drone into this platform based on the Context Capture platform, construct a three-dimensional point cloud, extract ground points by combining ground remote sensing images, obtain accurate ground point elevation information, and further generate a digital elevation model (DEM) of the open-pit mining area.

[0108] A5. Update the DEM of the open-pit mining area obtained in step A4 into the static basic digital elevation model DEM to obtain the DEM of the watershed.

[0109] A6. Repeat steps A3, A4, and A5 until the production of the monthly dynamic change DEM dataset of the watershed where the open-pit mining area is located during the research period is completed.

[0110] A7. Calibration of CREST model parameters: Based on the rainfall data, potential evapotranspiration data, hydrological station and runoff observation data processed in step A2, as well as the dynamic change DEM dataset production of the watershed, river data, river flow direction data, and cumulative flow data of the open-pit mining area, perform calibration of the CREST model of the watershed to obtain model parameters suitable for the watershed where the open-pit mining area is located. The three accuracy indicators of its log-Nash-Sutcliffe coefficient of efficiency (log-NSCE), Pearson Correlation Coefficient (CC), and relative bias ratio (R) are 0.604, 0.788, and -10.636% respectively, and the calibration effect of the model is acceptable.

[0111] A8. Simulation of long-term soil moisture content in the open-pit mine based on the improved CREST model: According to the virtual outlet position determined in step A1, the rainfall data and potential evapotranspiration data processed in step A2, the dynamic terrain dataset of the open-pit mining area obtained in step A6, and the CREST model parameters suitable for the watershed where the open-pit mining area is located obtained in step A7, perform soil moisture content simulation to obtain a soil moisture content dataset with daily scale, long-term sequence, and high resolution at a depth of 0-2m from the ground surface in the open-pit mining area.

[0112] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for producing daily soil moisture content in an open-pit mine based on a hydrological model, characterized in that: include: S10, determining the target open-pit mine area and its watershed, collecting watershed data and basic geographic data of the target open-pit mine area, determining the location of the water outlet based on the watershed data, and determining the minimum watershed area of ​​the target open-pit mine area based on the basic geographic data; S20, obtaining basic watershed hydrological data of the smallest watershed area; S30. Based on the CREST hydrological model, a dynamic terrain data module for open-pit mines is added to obtain an improved CREST model. The UAV oblique photogrammetry technology and the improved CREST model are coupled to generate a dynamically changing terrain data set for open-pit mines. S40, calibrate the improved CREST model based on the observation data of the basin hydrological stations, adjust and optimize the model parameters to match the target basin; S50. Based on the basic hydrological data of the watershed and the parameters of the adjusted and optimized model, the physical process of water cycle in the target open-pit mine area is simulated to obtain a soil moisture data set of the target open-pit mine area with a long time series, daily scale and high resolution of 0-2m from the surface.

2. The method for producing daily soil moisture content in an open-pit mine based on a hydrological model according to claim 1, characterized in that: The step S10 comprises the following steps: S101, the watershed data includes the mining rights boundary data of the target open-pit mine area, the regional cumulative flow data and the basic information of the watershed where the target open-pit mine is located, and the basic geographic data includes the regional digital elevation model DEM data; S102, according to the regional cumulative flow data, based on the principle that the cumulative flow per square meter is greater than 24 and is set as surface runoff, the runoff is extracted using the Raster Calculator tool in the Arcmap software to obtain regional runoff data; S103, determining the location of the water outlet according to the mining rights boundary data, the regional runoff data and the basic information of the watershed, wherein the location of the water outlet is within the spatial range of the regional runoff; S104. Based on the regional digital elevation model (DEM) data and the location of the water outlet, the watershed range is extracted by using the Watershed tool in Arcmap software. S105: Based on the mining rights boundary data of the open-pit mine area, determine whether the watershed range obtained in step S103 includes the target open-pit mine area. If it does, this range is the final range of the watershed; if it does not, repeat steps S103 and S104 until the watershed range includes the target open-pit mine area. S106. The regional cumulative flow data is collected from the HydroSHEDS platform, the regional digital elevation model DEM data is static data collected from the Google Earth Engine platform, the mining right boundary data is collected from the National Mining Right Holder Exploration and Exploitation Information Publicity System Platform of the Ministry of Natural Resources, and the basic information of the watershed is obtained from the official website of the local government.

3. The method for producing daily soil moisture content in an open-pit mine based on a hydrological model according to claim 1, characterized in that: The step S20 comprises the following steps: The basin hydrological basic data include river flow direction data, cumulative flow data, daily historical rainfall data, daily historical potential evapotranspiration data, hydrological station and runoff number observation data. The river flow direction data and the cumulative flow data are collected from the HydroSHEDS platform; the daily historical rainfall data are collected from NASA's earth science data platform Earthdata; the daily historical potential evapotranspiration data are collected from the Bristol University open data platform; the hydrological station and runoff number observation data are collected from the Hydrological Statistical Yearbook.

4. The method for producing daily soil moisture content in an open-pit mine based on a hydrological model according to claim 1, characterized in that: The step S30 comprises the following steps: S301, using the UAV oblique photogrammetry technology to obtain images of the target open-pit mine area, that is, according to the specific conditions of the target open-pit mine area, selecting weather suitable for UAV flight with no clouds or rain and low wind speed, planning the flight route, altitude and shooting angle of the UAV, and the UAV flies according to the planned route to shoot multi-angle images of the target open-pit mine area; S302, importing the photos taken by the drone into the Context Capture platform and automatically processing the photos, extracting feature points and generating three-dimensional point cloud data, optimizing the generated point cloud data, and removing noise and unnecessary points; S303, collecting ground remote sensing images of the target open-pit mine area, wherein the remote sensing images include satellite images and aerial photography images, extracting ground points from the remote sensing images using image processing technology, and fusing the extracted ground points with the optimized three-dimensional point cloud data to obtain elevation precision fused data; S304. Use the tools provided by the Context Capture platform to convert the elevation accuracy fusion data into the initial digital elevation model DEM data; S305, obtaining the static digital elevation model DEM data of the watershed area of ​​the target open-pit mine area, comparing and analyzing the initial digital elevation model DEM data and the static digital elevation model DEM data of the watershed to identify the terrain change area of ​​the target open-pit mine area, updating the static digital elevation model DEM data of the watershed in real time according to the terrain change area and constructing a dynamic terrain data module of the open-pit mine area, and obtaining the dynamic digital elevation model DEM data of the watershed from the dynamic terrain data module of the open-pit mine area; S306. Regularly use drone oblique photography to obtain the latest real-time photos of the target open-pit mining area, repeat steps S301 to S305, integrate all updated watershed static digital elevation model DEM data, and generate a watershed dynamic digital elevation model DEM dataset, which is the dynamically changing terrain dataset of the open-pit mining area.

5. The method for producing daily soil moisture content in an open-pit mine based on a hydrological model according to claim 1, characterized in that: The step S40 comprises the following steps: S401, extracting hydrological station location data and flow observation data based on the basin hydrological station observation data, wherein the hydrological station location data includes the latitude and longitude information of the hydrological station, and the flow observation data includes the runoff flow data on a daily scale; S402, setting initial parameters of the improved CREST model based on experience or previous research, running the improved CREST model using the initial parameters, generating initial simulated runoff flow data, and using the calibration model to calculate target evaluation indicators, the target evaluation indicators include Nash efficiency coefficient log-NSCE, Pearson correlation coefficient CC and relative deviation Bias, and the mathematical expression of the calibration model is: The mathematical expression of Nash efficiency coefficient log-NSCE is: The mathematical expression of Pearson correlation coefficient CC is: The mathematical expression of relative deviation Bias is: Among them, Q t,o represents the observed value of runoff flow at time t, Q t,s represents the simulated value of runoff flow at time t, represents the average value of the runoff flow observation at time t, It represents the average value of the simulated runoff flow at time t; S403. Determine the model effect based on the Nash efficiency coefficient log-NSCE, the Pearson correlation coefficient CC and the relative deviation Bias. Ideally, log-NSCE infinitely approaches 1, CC infinitely approaches 1, and Bias infinitely approaches 0. When log-NSCE is greater than 0.36, CC is greater than 0.6, and Bias is between ±40%, the simulation effect of the model is acceptable.

6. The method and system for producing daily soil moisture content in an open-pit mine based on a hydrological model according to claim 1, characterized in that: The step S50 comprises the following steps: S501, inputting the basin hydrological basic data and the model parameters calibrated in step S40 into the improved CREST model, setting the time step of the model, wherein the time step is on a daily scale; S502. Run the improved CREST model to simulate the water cycle process in the open-pit mine area, and obtain a soil moisture data set of the target open-pit mine area with a long time series, daily scale, and a high resolution of 0-2 m from the surface.

7. The daily soil moisture production system in open-pit mines based on the hydrological model is characterized by: include: A watershed range determination module is used to determine the target open-pit mine area and its watershed range, collect watershed data and basic geographic data of the target open-pit mine area, determine the outlet location based on the watershed data, and determine the watershed area of ​​the target open-pit mine area based on the basic geographic data; Data acquisition and processing module, used to obtain basic hydrological data of the watershed area; The open-pit mine dynamic terrain generation module is used to add the open-pit mine dynamic terrain data module based on the CREST hydrological model to obtain the improved CREST model, and couple the UAV oblique photogrammetry technology with the improved CREST model to generate a dynamic terrain data set for the open-pit mine; CREST model calibration module, used to calibrate the improved CREST model based on the basic hydrological data of the basin, and adjust and optimize the model parameters to match the target basin; The soil moisture simulation module is used to simulate the physical process of water cycle in the target open-pit mine area based on the basic hydrological data of the watershed and the parameters of the adjusted and optimized model, and obtain a soil moisture data set of the target open-pit mine area with a long time series, daily scale and high resolution of 0-2m from the surface.

Images