Method and system for simulating hydrological processes of base flow and surface runoff of gate-controlled rivers under changing environment

Abstract

The invention discloses a method and system for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment. The method comprises the following steps: simulating base flow data and surface runoff data of a gate-controlled river based on a SWAT gate-controlled river hydrological model; comparing and analyzing the base flow data and surface runoff data obtained by segmentation using a digital filtering method with the base flow data and surface runoff data obtained by simulation using the SWAT gate-controlled river hydrological model; performing cross-wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulation using the SWAT gate-controlled river hydrological model and meteorological data, respectively, to obtain cross-wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and meteorological data, so as to determine the coherence degree between the base flow and surface runoff and meteorological elements in the time-frequency domain; and inputting land use type data of different scenarios of the gate-controlled river into the SWAT gate-controlled river hydrological model to obtain the influence results of the land use type elements on the base flow and surface runoff.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrological model design, and in particular to a hydrological process simulation method and system for base flow and surface runoff of a gate-controlled river under a changing environment. Background Art

[0002] Hydrological models are simulations and generalizations of hydrological processes in nature. They play an important supporting role in many aspects, including water resources development and utilization, regional resource planning, ecological environmental water needs, flood prevention and disaster reduction, reservoir scheduling, point source and non-point source pollution assessment, and the impact of climate change and human activities on river basin ecosystems.

[0003] Meteorological factors and land use type factors will have an important impact on the base flow and surface runoff hydrological process of gate-controlled rivers. Assessing their potential impact can provide scientific theoretical support for the water resources allocation plan of gate-controlled rivers. Therefore, providing a method and system for simulating the hydrological process of base flow and surface runoff of gate-controlled rivers under a changing environment that can obtain the response laws between the base flow and surface runoff hydrological process and meteorological factors and land use type factors is a technical problem that needs to be solved urgently. Summary of the invention

[0004] Based on this, it is necessary to provide a method and system for simulating the hydrological processes of base flow and surface runoff of gated rivers under a changing environment, which can obtain the response laws between the base flow and surface runoff hydrological processes and meteorological elements and land use type elements.

[0005] A method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment comprises the following steps:

[0006] Acquire various basic data and measured runoff data of the gate-controlled river, wherein the various basic data include DEM data, soil type data, land use type data and meteorological data;

[0007] On the basis of the original SWAT hydrological model, the nonlinear reservoir and dam modules are introduced simultaneously, and the SWAT gate-controlled river hydrological model is established according to various basic data of the gate-controlled river;

[0008] Based on the SWAT gate-controlled river hydrological model, base flow data and surface runoff data of the gate-controlled river are simulated;

[0009] Based on the measured runoff data of the gate-controlled river, the measured runoff data of the gate-controlled river is divided into base flow and surface runoff by using a digital filtering method;

[0010] The base flow data and surface runoff data obtained by segmentation using the digital filtering method are compared with the base flow data and surface runoff data obtained by simulation using the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data obtained by simulation using the SWAT gate-controlled river hydrological model;

[0011] Respectively performing cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model and the meteorological data to obtain cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and the meteorological data;

[0012] Determine the coherence degree between the base flow and the surface runoff and the meteorological elements in the time-frequency domain according to the cross wavelet transform and / or wavelet coherence transform results of the obtained base flow data and the surface runoff data and the meteorological data;

[0013] The land use type data of different scenarios of the gate-controlled river are input into the established SWAT gate-controlled river hydrological model to obtain the impact results of land use type elements on the base flow and the surface runoff.

[0014] In one embodiment, the hydrological cycle stage of the SWAT gated river hydrological model is described by the following equation:

[0015]

[0016] Among them, SW0 and SW t are the soil moisture content at the beginning and end of the time period, mm; t is the time step, d; R day is the precipitation in the time step, mm; Q surf is the surface runoff generated within the time step, mm; E a is the evapotranspiration within the time step, mm; W seep is the amount of water infiltrating and lateral flowing in the soil profile within the time step, mm; Q gw is the amount of groundwater that flows into the river during the time step, mm.

[0017] In one embodiment, the SWAT gate-controlled river hydrological model uses the SCS-CN method when estimating surface runoff, and the SCS curve number equation is:

[0018]

[0019] Among them, Q surf Indicates surface runoff, mm; P day Indicates the rain depth on a certain day, mm; I a represents the initial loss, mm; S represents the retention, mm;

[0020] The calculation formula of S is:

[0021]

[0022] Among them, CN represents the number of curves on a certain day.

[0023] In one embodiment, the calculation formula involved in the step of dividing the measured runoff data of the gate-controlled river into base flow and surface runoff based on the measured runoff data of the gate-controlled river by using a digital filtering method is as follows:

[0024]

[0025] Q b(i) =Q i -Q d(i)

[0026] Among them, Q d(i) is the surface runoff on the i-th day, m 3 / s;Q d(i-1) is the surface runoff on day i-1, m 3 / s;Q i is the runoff on the i-th day, m 3 / s;Q i-1 is the runoff on day i-1, m 3 / s;Q b(i) is the base flow of the ith day, α is the filter coefficient.

[0027] In one of the embodiments, the coherence degree between the base flow and surface runoff and the meteorological elements in the time-frequency domain includes the resonance period and phase relationship between the base flow and surface runoff and the meteorological elements.

[0028] In one embodiment, the meteorological data includes precipitation and temperature, and the steps of performing cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model and the meteorological data to obtain the cross wavelet transform and / or wavelet coherence transform results of the base flow data and the surface runoff data and the meteorological data include:

[0029] Draw cross wavelet graphs and wavelet coherence graphs of surface runoff data-precipitation data, surface runoff data-temperature data, base flow data-precipitation data, and base flow data-temperature data respectively;

[0030] The regions of each cross wavelet map and wavelet coherence map that passed the 95% significance test were analyzed to determine the resonance period and phase relationship between two variables, where the two variables refer to surface runoff data and precipitation data, surface runoff data and temperature data, baseflow data and precipitation data, and baseflow data and temperature data.

[0031] In one embodiment, the step of inputting the land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the impact results of land use type elements on the base flow and the surface runoff includes:

[0032] Inputting early land use type data into the SWAT gate-controlled river hydrological model, and then driving the SWAT gate-controlled river hydrological model to simulate base flow and surface runoff in the reference period;

[0033] Adjusting the land use type data of the base period, setting an extreme land use scenario, and then driving the SWAT gate-controlled river hydrological model to simulate the base flow and surface runoff after the land use type data is adjusted;

[0034] The simulation results of base flow and surface runoff after the land use type data is adjusted are compared and analyzed with the simulation results of base flow and surface runoff in the reference period to obtain the impact results of land use type factors on the base flow and the surface runoff.

[0035] In one embodiment, the land use type data includes cultivated land, forest land, grassland and urban land, and the step of inputting the land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the influence of land use type elements on the base flow and the surface runoff includes:

[0036] Inputting data of various land use types in a certain year into the SWAT gate-controlled river hydrological model, and then driving the SWAT gate-controlled river hydrological model to simulate base flow and surface runoff in a reference period;

[0037] The steps of adjusting the land use type data of the base period, setting the extreme land use scenario, and then driving the SWAT gate-controlled river hydrological model to simulate the base flow and surface runoff after the land use type data is adjusted include:

[0038] All cultivated land in the baseline period is converted into forest land, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the cultivated land is converted into forest land;

[0039] All cultivated land in the baseline period is converted into grassland, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the cultivated land is adjusted to grassland;

[0040] All cultivated land in the baseline period is converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the cultivated land is converted into urban land;

[0041] All forest lands in the baseline period are converted into grasslands, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the forest lands are converted into grasslands;

[0042] All forest lands in the baseline period are converted into urban lands, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the forest lands are adjusted to urban lands;

[0043] All grasslands in the baseline period are converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the grasslands are adjusted to urban land;

[0044] The step of comparing and analyzing the simulation results of the base flow and surface runoff after the land use type data is adjusted and the simulation results of the base flow and surface runoff in the reference period to obtain the influence of the land use type elements on the base flow and the surface runoff includes:

[0045] The simulation results of base flow and surface runoff after the cultivated land was converted into forest land were compared with those of the base flow and surface runoff in the baseline period to obtain the effects of cultivated land and forest land on base flow and surface runoff.

[0046] Compare and analyze the simulation results of base flow and surface runoff after the cultivated land is converted to grassland with the simulation results of base flow and surface runoff in the baseline period, and obtain the results of the impact of land use of cultivated land and grassland on base flow and surface runoff;

[0047] Compare and analyze the simulation results after the cultivated land is converted to urban land with the simulation results of base flow and surface runoff in the reference period, and obtain the impact of cultivated land and urban land on base flow and surface runoff;

[0048] Compare and analyze the simulation results of base flow and surface runoff after the forest land is converted into grassland with the simulation results of base flow and surface runoff in the baseline period, and obtain the results of the impact of forest land and grassland on base flow and surface runoff;

[0049] Compare and analyze the simulation results of base flow and surface runoff after the forest land is converted into urban land with the simulation results of base flow and surface runoff in the baseline period, and obtain the impact of forest land and urban land on base flow and surface runoff;

[0050] The simulation results of base flow and surface runoff after grassland was converted into urban land were compared with those of base flow and surface runoff in the baseline period to obtain the impact of grassland and urban land on base flow and surface runoff.

[0051] In one embodiment, it also includes:

[0052] The established SWAT gate-controlled river hydrological model was calibrated and verified.

[0053] A hydrological process simulation system for base flow and surface runoff of a gated river under a changing environment, comprising:

[0054] The first module is used to obtain various basic data and measured runoff data of the gate-controlled river, wherein the various basic data include DEM data, soil type data, land use type data and meteorological data;

[0055] The second module is used to simultaneously introduce the nonlinear reservoir and dam modules on the basis of the original SWAT hydrological model, and establish the SWAT gate-controlled river hydrological model according to various basic data of the gate-controlled river;

[0056] The third module is used to simulate and obtain the base flow data and surface runoff data of the gate-controlled river based on the SWAT gate-controlled river hydrological model;

[0057] The fourth module is used for dividing the measured runoff data of the gate-controlled river into base flow and surface runoff based on the measured runoff data of the gate-controlled river by using a digital filtering method;

[0058] The fifth module is used to compare the base flow data and surface runoff data obtained by segmentation by the digital filtering method with the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model;

[0059] The sixth module is used to perform cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model and the meteorological data, respectively, to obtain cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and the meteorological data;

[0060] The seventh module is used to determine the coherence degree between the base flow and the surface runoff and the meteorological elements in the time-frequency domain according to the cross wavelet transform and / or wavelet coherence transform results of the obtained base flow data and the surface runoff data and the meteorological data;

[0061] The eighth module is used to input the land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the impact results of land use type elements on the base flow and the surface runoff.

[0062] The present application provides a method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment. The established SWAT gate-controlled river hydrological model can better simulate the changing process of surface runoff and base flow of a river under the control of a dam, and introduces a "nonlinear reservoir", taking into account the nonlinear relationship between the water storage capacity and outflow of a groundwater reservoir. At the same time, the base flow data and surface runoff data obtained by segmentation by a digital filtering method are compared with the base flow data and surface runoff data simulated by the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data simulated by the SWAT gate-controlled river hydrological model;

[0063] Secondly, by performing cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by SWAT gate-controlled river hydrological model simulation and meteorological data, the cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and meteorological data are obtained, and the coherence degree between the base flow and surface runoff and meteorological elements in the time-frequency domain is determined according to the results, so as to obtain the response law between the base flow and surface runoff hydrological process and meteorological elements;

[0064] In addition, the present invention obtains the influence of land use type elements on the base flow and the surface runoff by inputting land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model, thereby obtaining the response law between the base flow and the surface runoff hydrological process and the land use type elements;

[0065] In summary, the present invention can provide data support and decision-making support for water resource management and efficient utilization of gate-controlled rivers and construction of water ecological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A flowchart of a method for simulating hydrological processes of base flow and surface runoff of a gate-controlled river under a changing environment in one embodiment;

[0067] Figure 2 A cross wavelet diagram of the Yellow River runoff into the sea and the Yellow River sediment transport into the sea in one embodiment;

[0068] Figure 3 It is a wavelet coherence graph of the Yellow River runoff data into the sea and the Yellow River sediment transport data into the sea in one embodiment. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0071] refer to Figure 1 The present application provides a method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment, comprising the following steps:

[0072] S100, obtaining various basic data and measured runoff data of the gate-controlled river, wherein the various basic data include DEM data, soil type data, land use type data and meteorological data.

[0073] S200, based on the original SWAT hydrological model, simultaneously introduces nonlinear reservoir and sluice dam modules, and establishes a SWAT sluice-controlled river hydrological model based on a variety of basic data of sluice-controlled rivers.

[0074] S300, based on the SWAT hydrological model of gate-controlled rivers, simulates the base flow data and surface runoff data of gate-controlled rivers.

[0075] S400, based on the measured runoff data of the gate-controlled river, the measured runoff data of the gate-controlled river is divided into two parts: base flow and surface runoff by using a digital filtering method.

[0076] S500, comparing the base flow data and surface runoff data obtained by segmentation using the digital filtering method with the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model.

[0077] S600, performing cross wavelet transform and / or wavelet coherence transform on base flow data and surface runoff data obtained by SWAT gate-controlled river hydrological model simulation and meteorological data, respectively, to obtain cross wavelet transform and / or wavelet coherence transform results of base flow data and surface runoff data and meteorological data.

[0078] S700, determining the coherence degree between the base flow and surface runoff and meteorological elements in the time-frequency domain according to the obtained cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and meteorological data.

[0079] S800, inputting land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model, and obtaining the influence results of land use type elements on base flow and surface runoff.

[0080] The present application provides a method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment. The established SWAT gate-controlled river hydrological model can better simulate the changing process of surface runoff and base flow of a river under the control of a dam, and introduces a "nonlinear reservoir", taking into account the nonlinear relationship between the water storage capacity and outflow of a groundwater reservoir. At the same time, the base flow data and surface runoff data obtained by segmentation by a digital filtering method are compared with the base flow data and surface runoff data simulated by the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data simulated by the SWAT gate-controlled river hydrological model;

[0081] Secondly, by performing cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by SWAT gate-controlled river hydrological model simulation and meteorological data, the cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and meteorological data are obtained. According to the results, the coherence degree between the base flow and surface runoff and meteorological elements in the time-frequency domain is determined, so as to obtain the response law between the base flow and surface runoff hydrological process and meteorological elements;

[0082] In addition, the present invention obtains the influence of land use type elements on the base flow and the surface runoff by inputting land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model, thereby obtaining the response law between the base flow and the surface runoff hydrological process and the land use type elements;

[0083] In summary, the present invention can provide data support and decision-making support for water resource management and efficient utilization of gate-controlled rivers and construction of water ecological environment.

[0084] Dams are an important means for humans to rationally develop and utilize rivers. Dams play an important role in flood control and water supply by intercepting and storing water to reduce peak flow and increase available water in the dry season. However, the regulation and storage function of dams has changed the natural hydrological process. Dams and reservoirs divide rivers in plain areas into several independent watershed units. There is no clear hydraulic connection between the surface runoff between the watershed units, which changes the movement state of water flow in the natural river network and will affect the simulation of hydrological processes. Changes in the hydrological situation will further lead to the destruction of the river's ecological environment. Constructing the SWAT gate-controlled river hydrological model is the basic premise for quantifying the hydrological and environmental effects of water conservancy projects such as dams, and thus provides an important basis for formulating dam scheduling plans.

[0085] Specifically, the SWAT (Soil and Water Assessment Tool) hydrological model was developed by the Agricultural Research Service (ARS) of the United States Department of Agriculture (USDA) and is more suitable for long-term distributed hydrological process simulation for water resources management.

[0086] In order to reduce the impact of the temporal and spatial variation of underlying surface and climate factors on the model, the SWAT hydrological model usually divides the basin into multiple subbasins according to the river network, and realizes topological connectivity through paths such as rivers or canals. The subbasins are further divided into multiple hydrological response units (HRUs) according to different combinations of surface cover type, soil type, slope and other characteristics, and each hydrological unit calculates the water cycle process separately. The water migration process of the hydrological response unit is divided into vertical migration and horizontal migration. Vertical migration refers to the migration of water between the vegetation layer, unsaturated soil layer, shallow aquifer, and deep aquifer, including precipitation and irrigation infiltration, unsaturated soil water redistribution, seepage to shallow aquifers and deep aquifers, phreatic evaporation, root water absorption, soil evaporation and other processes; horizontal migration mainly refers to the lateral output of the hydrological unit, including surface runoff, soil flow, base flow and other processes.

[0087] Extracting basin features based on the digital elevation model (DEM) is the premise and key to building the SWAT hydrological model. The SWAT hydrological model processes the DEM based on the principle of the steepest slope and the minimum area threshold to generate river networks and sub-basins, and uses the valley line as the confluence path and the watershed as the boundary of the sub-basin. Users can set the minimum area threshold for generating rivers, and the SWAT hydrological model determines the density of the river network and the number of sub-basins based on the threshold.

[0088] The rivers extracted by the SWAT hydrological model based on DEM are usually not completely consistent with the actual situation, such as the extracted rivers are discontinuous and the artificial canal system cannot be extracted. To address this problem, the "burn-in" function is used to perform concave processing on the DEM according to the spatial distribution of the gate-controlled rivers, so as to obtain the distribution of the gate-controlled rivers. The principle of the "burn-in" function is to first convert the digital river network of the gate-controlled rivers into a grid form, and then superimpose it on the original DEM after projection conversion. On the basis of maintaining the elevation value of the grid unit of the modified river system unchanged, the grid elevation value of the non-river channel perpendicular to the river direction is slightly increased, so that the river channel grid elevation value is lower than the coastal elevation. Then reprocess the modified DEM to generate a new river network.

[0089] Digital elevation model (DEM) data comes from ASTER (Advanced Spacebome Thermal Emission and Reflection Radiometer) with a resolution of 30m. DEM data can include but is not limited to height, slope and slope length.

[0090] Soil type data comes from the Harmonized World Soil Database (HWSD) (version 1.2) jointly released by FAO and the International Institute for Applied Systems Analysis (IIASA) in February 2012, with a spatial resolution of 1000m×1000m. Soil physical parameters were calculated using MATLAB and SPAW software, and a soil database suitable for the SWAT hydrological model was established.

[0091] Soil type data may include, but are not limited to, clay soil (NT), clay loam (NRT), sandy clay loam (SNRT), sandy loam (SRT), silt sandy loam (FSRT), silt sandy clay loam (FSNRT), and silt sandy soil (FST). Hydrological data may include, but are not limited to, flow.

[0092] Specifically, based on the SWAT gate-controlled river hydrological model, the principle of simulating the base flow data and surface runoff data of the gate-controlled river is as follows:

[0093] The SWAT gate-controlled river hydrological model is mainly divided into the hydrological cycle stage and the confluence stage during simulation. Among them, water balance is an important basis and basis for driving the SWAT gate-controlled river hydrological model to simulate the hydrological cycle process. The hydrological cycle stage of the SWAT gate-controlled river hydrological model is described by the following formula:

[0094]

[0095] Among them, SW0 and SW t are the soil moisture content at the beginning and end of the time period, mm; t is the time step, d; Rday is the precipitation in the time step, mm; Q surf is the surface runoff generated within the time step, mm; E a is the evapotranspiration within the time step, mm; W seep is the amount of water infiltrating and lateral flowing in the soil profile within the time step, mm; Q gw is the amount of groundwater that flows into the river during the time step, mm.

[0096] The SWAT gate-controlled river hydrological model uses the SCS-CN (Soil Conservation Service curve number) method to estimate surface runoff. The SCS curve number equation is:

[0097]

[0098] Among them, Q surf Indicates surface runoff, mm; P day Indicates the rain depth on a certain day, mm; I a represents the initial loss, mm; S represents the retention, mm; the calculation formula of S is:

[0099]

[0100] Among them, CN represents the curve number of a certain day; the initial loss amount I a Usually approximately 0.2S. day >I a When the water level rises, surface runoff is generated.

[0101] Shallow aquifers are the main source of recharge for base flow in the main channel or river section of a gate-controlled river, and their water balance equation is:

[0102] aq sh，i =aq sh,i-1 +w rchrg，sh -Q gw -w revap -w pump，sh

[0103] Among them, aq sh,i , aq sh,i-1 are the water storage of the shallow aquifer on the i-th and i-1-th day, mm; w rchrg.sh is the recharge of the shallow aquifer on day i, mm; Q gw is the underground runoff or base flow entering the river on the i-th day, mm; w revap is the amount of water that returns to the root zone from the shallow aquifer due to soil water shortage on the i-th day, mm; w pump，sh is the water withdrawal of the shallow aquifer on the i-th day, mm.

[0104] The calculation formula involved in the steady-state response of groundwater runoff to recharge is as follows:

[0105]

[0106] Among them, K sat Indicates the permeability coefficient of the aquifer, mm / d; L gw Indicates the distance from the groundwater watershed of the sub-basin to the main river channel, m; h wtbl Indicates the depth of the water table, m.

[0107] The water table fluctuations are caused by the non-steady-state response of groundwater runoff to periodic recharge and involve the following calculation formula:

[0108]

[0109] in, It represents the change of the depth of the water table over time, mm / d; μ represents the water supply degree of the shallow aquifer, m / m.

[0110] In the SWAT gate-controlled river hydrological model, it is assumed that there is a linear relationship between the change in groundwater runoff and the rate of change in the depth of the water table. Combining the above two calculation formulas, we can get:

[0111]

[0112] Among them, α gw represents the base flow retreat constant or proportional constant. Integrating the above formula yields:

[0113] Q gw，i =Q gw，i-1 ·exp(-α gw ·Δt)+w rchrg，sh [1-exp(-α gw ·Δt)],aq sh >aq shthr，q

[0114] Q gw，i =0, aq sh ≤aq shthr，q

[0115] Among them, △t represents the time step, that is, 1d; aq shthr，q It indicates the water level threshold of the shallow aquifer when groundwater flows into the main river channel, mm.

[0116] In the simulation of groundwater processes in the SWAT gate-controlled river hydrological model, the nonlinear relationship between the storage capacity and outflow of the groundwater reservoir is considered, and the nonlinear reservoir relationship is introduced into the original SWAT hydrological model, namely the “nonlinear reservoir” method.

[0117] The recession curve of the base flow is:

[0118] Q t =Q0exp(-αt)

[0119] Where: Q t is the flow at time t, Q0 is the flow at the initial time, and α is the water withdrawal coefficient. The exponential formula of the water withdrawal curve shows that the water storage capacity and outflow of the groundwater reservoir are in a linear relationship, which is a conceptualized "linear single reservoir" method:

[0120] S=kQ

[0121] Where: S is the water storage capacity of the groundwater aquifer, m 3 ; Q is the water flow rate, m 3 / s.

[0122] Theory and extensive analysis have shown that the relationship between storage and discharge is nonlinear. In order to obtain the nonlinear relationship between groundwater storage and outflow, Wittenberg added a dimensionless exponent b and modified the above formula to:

[0123] S=aQ b

[0124] The nonlinear reservoir relationship is introduced into the original SWAT hydrological model, namely the "nonlinear reservoir" method. The flow rate of the groundwater recharge channel is:

[0125]

[0126] Parameters a and b are calibrated using the flow data observed during the river's receding period. Different adjacent flows on the receding curve will result in different estimated values ​​of a. Different combinations of a and b will result in different simulated values. When the sum of squared errors between the simulated value and the measured value is minimized, the a and b values ​​at this time are selected as the optimal values ​​of the parameters.

[0127] In terms of dam treatment, the SWAT gate-controlled river hydrological model provides a simulation control function for reservoirs. By adding reservoirs as independent units at the outlet of the corresponding sub-basin, the impact of reservoirs on the water cycle of the basin can be simulated. The sluice gate can be regarded as a river-type reservoir, which has both river evolution and weak reservoir regulation and storage functions. Therefore, the simulation of water flow regulation by the sluice gate can refer to the regulation and storage concept of the reservoir: that is, the water flow is first calculated in the river channel, and the calculated water flow enters a virtual reservoir, and then forms the outflow of the gate through the regulation and storage of the virtual reservoir.

[0128] A reservoir is a water storage body located on a river network. Its water balance is composed of storage, inflow, rainfall, outflow, evaporation and leakage. The water balance equation can be expressed as:

[0129] V=V0+V in +Vp -V out -V e -V s

[0130] Where: V is the water storage capacity of the reservoir at the end of the simulation, m 3 ; V0 is the water storage capacity of the reservoir at the beginning of simulation, m 3 ; V in is the amount of water entering the reservoir during the simulation period, m 3 ; V p is the rainfall in the reservoir simulation period, m 3 ; V out is the outflow of water from the reservoir during the simulation period, m 3 ; V e is the evaporation of the reservoir during the simulation period, m 3 ; V s is the leakage loss during the reservoir simulation period, m 3 .

[0131] For the reservoir V p 、V e and V s Parameters such as water level and water volume are calculated by the model, and the determination of these parameters is inseparable from the water surface area of ​​the reservoir. For a specific reservoir, different water storage capacities correspond to different water surface areas. If each reservoir is processed separately, a large amount of measured data is required, which consumes a lot of time and effort. Therefore, the model uses the following equation to assume the relationship between water surface area and water storage capacity:

[0132] S=β*V e

[0133] In the formula, S represents the surface area of ​​the reservoir; β represents the coefficient; V represents the water storage capacity of the reservoir, m 3 ; e represents exponent.

[0134] For the outflow V out , using the measured outflow method and the target discharge method. The target discharge method assumes that the discharge of the reservoir is a function of the target water storage capacity. It simulates the general discharge rules that reservoir managers may use, with the normal spillway water volume corresponding to the water volume when the maximum flood control reserve is reached, and the emergency spillway water volume corresponding to the water volume when there is no flood control reserve.

[0135] In one embodiment, the method further includes: step S220, calibrating and verifying the established SWAT gate-controlled river hydrological model.

[0136] Different basic data have different impacts on surface runoff and base flow, that is, different sensitivities. Therefore, it is necessary to calibrate and verify the established SWAT gate-controlled river hydrological model in order to quantitatively evaluate the simulation effect of the SWAT gate-controlled river hydrological model.

[0137] In one embodiment, the step S220 of calibrating and validating the established SWAT gate-controlled river hydrological model includes:

[0138] In step S221, three evaluation indicators, namely, efficiency coefficient NSE (Nash-Sutcliffe), percentage deviation PBIAS (PercentBias) and determination coefficient R2, are used to evaluate the simulation effect of the SWAT gate-controlled river hydrological model.

[0139] Specifically, the calculation formulas of the three evaluation indicators are as follows:

[0140]

[0141]

[0142]

[0143] Among them, Q m，i is the measured runoff of the gate-controlled river, Q s，i is the simulated runoff of the gated river, Q m，avg is the measured average runoff of the gate-controlled river over many years, Q s，avg is the multi-year simulated average runoff of the gate-controlled river, and n is the length of the measured time series.

[0144] The NSE value range is from -∞ to 1.0. When NSE = 1, the simulation value is optimal. When 0.75<NSE≤1.00, the simulation effect is very good; when 0.65<NSE≤0.75, the simulation effect is good; when 0.50<NSE≤0.65, the simulation effect is satisfactory; when NSE≤0.5, the simulation effect is unsatisfactory.

[0145] When PBIAS = 0.0, the simulation value is the optimal value, and the smaller the magnitude, the better the simulation effect. When PBIAS < ±10, the simulation effect is very good; when ±10 ≤ PBIAS < ±15, the simulation effect is good; when ±15 ≤ PBIAS < ±25, the simulation effect is satisfactory; when PBIAS ≥ ±25, the simulation effect is unsatisfactory.

[0146] R 2 Also called goodness of fit, it describes the degree to which the model explains the observed data. 2 The value range is 0 to 1. 2 The closer it is to 1, the better the model fit is. 2 When >0.5, the model simulation effect is considered acceptable.

[0147] Digital filtering method (Lyne-Hollick) is the most widely used baseflow segmentation method by scholars at home and abroad in recent years. It has the characteristics of strong operability and fast calculation speed. This method originated from signal analysis and processing. Its principle is similar to filtering high-frequency signals. It uses digital filters to divide signals into high-frequency signals (surface runoff) and low-frequency signals (baseflow), thereby separating the corresponding surface runoff and baseflow from the runoff process.

[0148] In one embodiment, based on the measured runoff data of the gate-controlled river, the calculation formula involved in step S300 of using a digital filtering method to divide the measured runoff data of the gate-controlled river into two parts: base flow and surface runoff is as follows:

[0149]

[0150] Q b(i) =Q i -Q d(i)

[0151] Among them, Q d(i) is the surface runoff on the i-th day, m 3 / s;Q d(i-1) is the surface runoff on day i-1, m 3 / s;Q i is the runoff on the i-th day, m 3 / s;Q i-1 is the runoff on day i-1, m 3 / s;Q b(i) is the base flow of the ith day, α is the filter coefficient, and the value range of α is 0.9 to 0.95. In this embodiment, the value of α is 0.925.

[0152] Specifically, land use type data include cultivated land, forest land, grassland and urban land, and meteorological data include precipitation and temperature.

[0153] Crossed wavelet transform (XWT) has strong signal coupling and resolution capabilities, and can analyze the resonant periods with higher resonance energy and their phase relationship in two time series.

[0154] Specifically, cross wavelet transform (XWT) is a signal analysis method that combines cross spectrum analysis and wavelet transform, and can analyze the intrinsic connection between two time series with a certain relationship in the time-frequency domain from multiple time scales.

[0155] Define W X(s) , W Y(s) are the cross wavelet transforms of the two given time series X and Y, then define W X(s) , W Y(s) The cross wavelet spectrum of in, The corresponding cross wavelet power spectral density is The larger the value, the higher the W X(s) , W Y(s) The two have a common high energy area and are significantly correlated with each other.

[0156] The test of the continuous cross wavelet power spectrum is also compared with the red noise standard spectrum, assuming that the expected spectra of the two time series X and Y are both red noise power spectra. and The cross wavelet power spectrum distribution has the following relationship:

[0157]

[0158] Among them, σ X and σ Y are the standard deviations of the time series X and Y, Morlet wavelet transform, the degree of freedom v is 2, Zv(P) is the confidence level related to the probability P, when the significance level α = 0.05, Z2(95%) = 3.999. Specifically, first calculate the red noise power spectrum and At the upper confidence limit of significance level α = 0.05 (i.e. probability P = 95%), when When the confidence limit is exceeded, it is considered that W X(s) , W Y(s) The red noise standard spectrum was tested at a significance level of α=0.05, and the correlation between the two was significant.

[0159] The complex angle can describe the local relative phase relationship between time series X and Y in the time-frequency domain. To calculate the phase difference between the scale components of two time series X and Y, it is necessary to estimate the mean and confidence interval of each phase difference. In the area with a confidence level of more than 95%, that is, within the wavelet influence cone (COI), the circular average phase angle is used to quantitatively describe the phase relationship between time series X and Y. Suppose there are n phase angles α i (i=l,...,n), let It represents the sample mean of n phase angles, referred to as the average angle, and its calculation formula is:

[0160]

[0161] It can be called circular standard deviation or angular deviation, which represents the measure of discrete trend, and its range is 0 to +∞; It represents the angle central tendency measure, which ranges from 0 to 1. It should be pointed out that q and r are essentially the same. iWhen they are all equal to the same value, there is no variation in this set of data, q=0 and r=1; when the αi in a set of data are uniformly distributed on the circumference, then r=0, and q cannot be calculated because the average angle does not exist, but when r approaches 0, q approaches +∞.

[0162] Wavelet coherence (WTC) characterizes the coherence degree of wavelet transform of two time series in the time-frequency domain. It can make up for the deficiency of cross-wavelet energy spectrum in identifying low-energy areas and analyze the significant correlation of low-energy areas of two time series.

[0163] Wavelet coherence spectrum (WTC) is used to measure the closeness of the local correlation between two time series in the time-frequency space. Even if the corresponding low energy value area in the cross wavelet power spectrum, the correlation between the two in the wavelet coherence spectrum may be significant. Define the wavelet coherence spectrum of two time series X and Y as:

[0164]

[0165] Where: S is the smoothing operator, It is the cross product of the wave amplitudes of two time series X and Y at a certain frequency; is the amplitude of the vibration wave.

[0166] S(W)=S scale (S time (W n (s))

[0167]

[0168] S scale (w)| n =(W n (s)×c2∏(0.6s))| n

[0169] Where: S scale represents smoothing along the wavelet scaling axis; S time Indicates smoothing along the wavelet time translation axis. c1 and c2 are normalization constants, Π is a rectangular function, and the parameter 0.6 is an empirically determined scale that is decorrelated with the wavelength of the Morlet wavelet. The significance test of the wavelet coherence spectrum uses the Monte Carlo method. Both the cross wavelet power spectrum and the wavelet coherence spectrum can determine the phase angle. The main difference between the two is that the wavelet coherence spectrum uses a smoothing function.

[0170] Specifically, the high and low energy areas represent the dependence of the correlation between the two variables on time and frequency, that is, the high and low energy reflect the degree of correlation. The high energy area of ​​the cross wavelet power spectrum (XWT) coincides with the low energy area of ​​the cross wavelet condensation spectrum (WTC), and the significant correlation intensity between the two in the low energy area is greater than that in the high energy area.

[0171] The step S600 of performing cross wavelet transform and / or wavelet coherence transform on the base flow data and the surface runoff data and the meteorological data obtained by the SWAT gate-controlled river hydrological model simulation to obtain the cross wavelet transform and / or wavelet coherence transform results of the base flow data and the surface runoff data and the meteorological data comprises:

[0172] S610, performing cross-wavelet transform and / or wavelet coherence transform on the baseflow data and the surface runoff data and the precipitation data obtained by simulating the SWAT gate-controlled river hydrological model, and obtaining the cross-wavelet transform and / or wavelet coherence transform results of the baseflow data and the surface runoff data and the precipitation data; S620, performing cross-wavelet transform and / or wavelet coherence transform on the baseflow data and the surface runoff data and the temperature data obtained by simulating the SWAT gate-controlled river hydrological model, and obtaining the cross-wavelet transform and / or wavelet coherence transform results of the baseflow data and the surface runoff data and the temperature data.

[0173] According to the obtained cross wavelet transform and / or wavelet coherence transform results of the base flow data and the surface runoff data and the meteorological data, the step S700 of determining the coherence degree between the base flow and the surface runoff and the meteorological elements in the time-frequency domain comprises:

[0174] S710, determining the degree of coherence between the base flow and the surface runoff and precipitation elements in the time-frequency domain based on the obtained base flow data and the cross wavelet transform and / or wavelet coherence transform results of the surface runoff data and precipitation data; S720, determining the degree of coherence between the base flow and the surface runoff and temperature elements in the time-frequency domain based on the obtained base flow data and the cross wavelet transform and / or wavelet coherence transform results of the surface runoff data and temperature data.

[0175] In one embodiment, the step S600 of performing cross wavelet transform and / or wavelet coherence transform on the base flow data and the surface runoff data and the meteorological data obtained by the SWAT gate-controlled river hydrological model simulation to obtain the cross wavelet transform and / or wavelet coherence transform results of the base flow data and the surface runoff data and the meteorological data comprises:

[0176] S601, respectively draw cross wavelet graphs and wavelet coherence graphs of surface runoff data-precipitation data, surface runoff data-temperature data, base flow data-precipitation data, and base flow data-temperature data.

[0177] In one embodiment, MATLAB is used to draw cross wavelet graphs and wavelet coherence graphs of surface runoff data-precipitation data, surface runoff data-air temperature data, base flow data-precipitation data, and base flow data-air temperature data.

[0178] S602, analyzing the regions of each cross wavelet map and wavelet coherence map that pass the 95% significance test (ie, the black thick solid line region) to determine the resonance period and phase relationship between the two variables.

[0179] Specifically, between two variables refers to between surface runoff data and precipitation data, surface runoff data and temperature data, baseflow data and precipitation data, and baseflow data and temperature data. Determining the resonance period between two variables includes determining the resonance period between the two variables and the duration of the resonance period.

[0180] The phase relationship indicates the positive or negative correlation between two variables, which is represented by arrows. → indicates that the two variables are in phase, indicating that they are positively correlated. ← indicates that the two variables are in opposite phases, indicating that they are negatively correlated. The specific calculation formulas for the phase relationship of Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) are described in detail above.

[0181] Regarding the cross wavelet diagram and wavelet coherence diagram of surface runoff data-precipitation data, surface runoff data-temperature data, baseflow data-precipitation data, and baseflow data-temperature data, the horizontal axis represents time, the vertical axis represents the resonance period between the two, the direction of the arrow represents the phase relationship between the two, from left to right represents that the two are in phase, and from right to left represents that the two are in anti-phase. The thick black solid line indicates that the red noise test of 95% is reached between the two, and the thin black solid line is the wavelet influence cone curve (COI). The area outside the wavelet influence cone curve (COI) is not considered due to the edge effect.

[0182] refer to Figure 2 and Figure 3 , using the cross wavelet graph and wavelet coherence graph of the Yellow River runoff data and the Yellow River sediment transport data for the past 70 years as an example:

[0183] Figure 2 is a cross wavelet diagram of the Yellow River runoff into the sea and the Yellow River sediment transport into the sea in an embodiment, Figure 2 It can be seen that the high-energy periods of the Yellow River runoff data and the Yellow River sediment transport data are 1 to 6 years and 6 to 15 years, and the period scale of 1 to 6 years from 1960 to 1972 passed the 95% red noise test, and the Yellow River runoff data and the Yellow River sediment transport data showed a positive phase relationship.

[0184] refer to Figure 3 , Figure 3is a wavelet coherence graph of the Yellow River runoff data into the sea and the Yellow River sediment transport data into the sea in an embodiment, Figure 3 It can be seen that the Yellow River runoff data and the Yellow River sediment transport data have significant resonance periods in the low energy area of ​​the entire time-frequency space, and the significant correlation in the low energy area is much greater than that in the high energy area. The time scale of 8 to 16 years passed the 95% significance test in the entire time period (the time at both ends was affected by the boundary), and the Yellow River runoff data and the Yellow River sediment transport data into the sea are mainly in positive phase, indicating that the evolution characteristics of the Yellow River runoff and the Yellow River sediment transport into the sea are highly consistent.

[0185] Step S800 of inputting land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the impact of land use type elements on base flow and surface runoff includes:

[0186] S810, inputting early land use type data into the SWAT gate-controlled river hydrological model, and then driving the SWAT gate-controlled river hydrological model to run, so as to simulate the base flow and surface runoff in the reference period.

[0187] Specifically, the land use type data includes cultivated land, forest land, grassland and urban land; through the remote sensing images of the gate-controlled rivers, the land use type data of the gate-controlled rivers in different periods (for example, 1980, 2000, 2020, that is, the period is 20 years. It can be understood that in other embodiments, the period can be 5 years, 10 years, or 15 years).

[0188] Step S810 specifically includes: Step S812, [Scenario 1] Inputting land use type data of a certain year (for example, 2000) into the SWAT gate-controlled river hydrological model, and then driving the SWAT gate-controlled river hydrological model to run to simulate the base flow and surface runoff of the reference period.

[0189] S820, adjusts the land use type data of the baseline period, sets extreme land use scenarios, and then drives the SWAT gate-controlled river hydrological model to simulate the base flow and surface runoff after the land use type data is adjusted.

[0190] It can be understood that step S820 may include but is not limited to the following 6 steps, which are as follows:

[0191] Step S821, [Scenario 2] All cultivated land in the baseline period is converted into forest land, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the cultivated land is adjusted to forest land.

[0192] Step S822, [Scenario 3] All cultivated land in the baseline period is converted into grassland, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the cultivated land is adjusted to grassland.

[0193] Step S823, [Scenario 4] All cultivated land in the baseline period is converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the cultivated land is adjusted to urban land.

[0194] Step S824, [Scenario 5] All forest land in the baseline period is converted into grassland, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the forest land is adjusted to grassland.

[0195] Step S825, [Scenario 6] All forest land in the baseline period is converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the forest land is adjusted to urban land.

[0196] Step S826, [Scenario 7] All grasslands in the baseline period are converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the grassland is adjusted to urban land.

[0197] S830, comparing and analyzing the simulation results of base flow and surface runoff after the land use type data is adjusted with the simulation results of base flow and surface runoff in the reference period, and obtaining the results of the influence of land use type factors on base flow and surface runoff.

[0198] It can be understood that based on the six sub-steps (scenario 2 to scenario 7) included in step S820, step S830 specifically includes:

[0199] Step S831, comparing and analyzing the simulation results of base flow and surface runoff after the cultivated land is converted into forest land and the simulation results of base flow and surface runoff in the reference period, and obtaining the impact results of cultivated land and forest land on base flow and surface runoff.

[0200] Step S832, comparing and analyzing the simulation results of base flow and surface runoff after the cultivated land is converted into grassland and the simulation results of base flow and surface runoff in the reference period, to obtain the impact results of land use of cultivated land and grassland on base flow and surface runoff.

[0201] Step S833, comparing and analyzing the simulation results after the cultivated land is adjusted to urban land and the simulation results of base flow and surface runoff in the reference period, to obtain the impact results of cultivated land and urban land on base flow and surface runoff.

[0202] Step S834, comparing and analyzing the simulation results of base flow and surface runoff after the forest land is converted into grassland and the simulation results of base flow and surface runoff in the reference period, to obtain the impact results of the forest land and grassland on the base flow and surface runoff.

[0203] Step S835, comparing and analyzing the simulation results of base flow and surface runoff after the forest land is adjusted to urban land and the simulation results of base flow and surface runoff in the reference period, to obtain the impact results of forest land and urban land on base flow and surface runoff.

[0204] Step S836, comparing and analyzing the simulation results of base flow and surface runoff after the grassland is adjusted to urban land and the simulation results of base flow and surface runoff in the reference period, to obtain the impact results of grassland and urban land on base flow and surface runoff.

[0205] The present application also provides a hydrological process simulation system for base flow and surface runoff of a gate-controlled river under a changing environment, comprising: a first module, a second module, a third module, a fourth module, a fifth module, a sixth module, a seventh module and an eighth module;

[0206] The first module is used to obtain various basic data and measured runoff data of gate-controlled rivers. The various basic data include DEM data, soil type data, land use type data and meteorological data.

[0207] The second module is used to introduce nonlinear reservoir and dam modules simultaneously on the basis of the original SWAT hydrological model, and to establish a SWAT gate-controlled river hydrological model based on a variety of basic data of the gate-controlled river.

[0208] The third module is used to simulate the base flow data and surface runoff data of the gate-controlled river based on the SWAT gate-controlled river hydrological model.

[0209] The fourth module is used to divide the measured runoff data of the gate-controlled river into base flow and surface runoff based on the measured runoff data of the gate-controlled river by digital filtering method.

[0210] The fifth module is used to compare the base flow data and surface runoff data obtained by digital filtering with the base flow data and surface runoff data simulated by the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data simulated by the SWAT gate-controlled river hydrological model.

[0211] The sixth module is used to perform cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data and meteorological data obtained by SWAT gate-controlled river hydrological model simulation, and obtain cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and meteorological data.

[0212] The seventh module is used to determine the coherence degree between base flow and surface runoff and meteorological elements in the time-frequency domain according to the cross wavelet transform and / or wavelet coherence transform results of the obtained base flow data and surface runoff data and meteorological data.

[0213] The eighth module is used to input the land use type data of different scenarios of gate-controlled rivers into the established SWAT gate-controlled river hydrological model to obtain the impact of land use type elements on base flow and surface runoff.

[0214] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. All equivalent structural changes made using the contents of the present invention's specification and drawings, or directly / indirectly applied in other related technical fields, are included in the patent protection scope of the present invention.

Claims

1. A method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment, characterized in that: The following steps are involved: Acquire various basic data and measured runoff data of the gate-controlled river, wherein the various basic data include DEM data, soil type data, land use type data and meteorological data; On the basis of the original SWAT hydrological model, the nonlinear reservoir and dam modules are introduced simultaneously, and the SWAT gate-controlled river hydrological model is established according to various basic data of the gate-controlled river; Based on the SWAT gate-controlled river hydrological model, base flow data and surface runoff data of the gate-controlled river are simulated; Based on the measured runoff data of the gate-controlled river, the measured runoff data of the gate-controlled river is divided into base flow and surface runoff by using a digital filtering method; The base flow data and surface runoff data obtained by segmentation using the digital filtering method are compared with the base flow data and surface runoff data obtained by simulation using the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data obtained by simulation using the SWAT gate-controlled river hydrological model; Respectively performing cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model and the meteorological data to obtain cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and the meteorological data; Determine the coherence degree between the base flow and the surface runoff and the meteorological elements in the time-frequency domain according to the cross wavelet transform and / or wavelet coherence transform results of the obtained base flow data and the surface runoff data and the meteorological data; The land use type data of different scenarios of the gate-controlled river are input into the established SWAT gate-controlled river hydrological model to obtain the impact results of land use type elements on the base flow and the surface runoff.

2. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 1, characterized in that: The hydrological cycle phase of the SWAT gated river hydrological model is described by the following equation: Among them, SW0 and SW t are the soil moisture content at the beginning and end of the time period, mm; t is the time step, d; R day is the precipitation in the time step, mm; Q surf is the surface runoff generated within the time step, mm; E a is the evapotranspiration within the time step, mm; W seep is the amount of water infiltrating and lateral flowing in the soil profile within the time step, mm; Q gw is the amount of groundwater that flows into the river during the time step, mm.

3. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 1, characterized in that: The SWAT gate-controlled river hydrological model uses the SCS-CN method to estimate surface runoff, and the SCS curve number equation is: Among them, Q surf Indicates surface runoff, mm; P day Indicates the rain depth on a certain day, mm; I a represents the initial loss, mm; S represents the retention, mm; The calculation formula of S is: Among them, CN represents the number of curves on a certain day.

4. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 1, characterized in that: The calculation formula involved in the step of dividing the measured runoff data of the gate-controlled river into base flow and surface runoff based on the measured runoff data of the gate-controlled river by using a digital filtering method is as follows: Q b(i) =Q i -Q d(i) Among them, Q d(i) is the surface runoff on the i-th day, m 3 / s;Q d(i-1) is the surface runoff on day i-1, m 3 / s;Q i is the runoff on the i-th day, m 3 / s;Q i-1 is the runoff on day i-1, m 3 / s;Q b(i) is the base flow of the ith day, and α is the filter coefficient.

5. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 1, characterized in that: The coherence degree between the base flow and surface runoff and the meteorological elements in the time-frequency domain includes the resonance period and phase relationship between the base flow and surface runoff and the meteorological elements.

6. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 5, characterized in that: The meteorological data includes precipitation and temperature. The steps of performing cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model and the meteorological data to obtain the cross wavelet transform and / or wavelet coherence transform results of the base flow data and the surface runoff data and the meteorological data include: Draw cross wavelet graphs and wavelet coherence graphs of surface runoff data-precipitation data, surface runoff data-temperature data, base flow data-precipitation data, and base flow data-temperature data respectively; The regions of each cross wavelet map and wavelet coherence map that passed the 95% significance test were analyzed to determine the resonance period and phase relationship between two variables, where the two variables refer to surface runoff data and precipitation data, surface runoff data and temperature data, baseflow data and precipitation data, and baseflow data and temperature data.

7. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 1, characterized in that: The step of inputting the land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the influence results of land use type elements on the base flow and the surface runoff includes: Inputting early land use type data into the SWAT gate-controlled river hydrological model, and then driving the SWAT gate-controlled river hydrological model to simulate base flow and surface runoff in the reference period; Adjusting the land use type data of the base period, setting an extreme land use scenario, and then driving the SWAT gate-controlled river hydrological model to simulate the base flow and surface runoff after the land use type data is adjusted; The simulation results of base flow and surface runoff after the land use type data is adjusted are compared and analyzed with the simulation results of base flow and surface runoff in the reference period to obtain the impact results of land use type factors on the base flow and the surface runoff.

8. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 7, characterized in that: The land use type data includes cultivated land, forest land, grassland and urban land. The step of inputting the land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the influence results of the land use type elements on the base flow and the surface runoff includes: Inputting data of various land use types in a certain year into the SWAT gate-controlled river hydrological model, and then driving the SWAT gate-controlled river hydrological model to run, so as to simulate the base flow and surface runoff in the reference period; The steps of adjusting the land use type data of the base period, setting the extreme land use scenario, and then driving the SWAT gate-controlled river hydrological model to simulate the base flow and surface runoff after the land use type data is adjusted include: All cultivated land in the baseline period is converted into forest land, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the cultivated land is converted into forest land; All cultivated land in the baseline period is converted into grassland, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the cultivated land is adjusted to grassland; All cultivated land in the baseline period is converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the cultivated land is converted into urban land; All forest lands in the baseline period are converted into grasslands, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the forest lands are converted into grasslands; All forest lands in the baseline period are converted into urban lands, and then the SWAT gate-controlled river hydrological model is driven to simulate the base flow and surface runoff after the forest lands are adjusted to urban lands; All grasslands in the baseline period are converted into urban land, and then the SWAT gate-controlled river hydrological model is driven to run to simulate the base flow and surface runoff after the grasslands are adjusted to urban land; The step of comparing and analyzing the simulation results of the base flow and surface runoff after the land use type data is adjusted and the simulation results of the base flow and surface runoff in the reference period to obtain the influence of the land use type elements on the base flow and the surface runoff includes: The simulation results of base flow and surface runoff after the cultivated land was converted into forest land were compared with those of the base flow and surface runoff in the baseline period to obtain the effects of cultivated land and forest land on base flow and surface runoff. Compare and analyze the simulation results of base flow and surface runoff after the cultivated land is converted to grassland with the simulation results of base flow and surface runoff in the baseline period, and obtain the results of the impact of land use of cultivated land and grassland on base flow and surface runoff; Compare and analyze the simulation results after the cultivated land is converted to urban land with the simulation results of base flow and surface runoff in the reference period, and obtain the impact of cultivated land and urban land on base flow and surface runoff; Compare and analyze the simulation results of base flow and surface runoff after the forest land is converted into grassland with the simulation results of base flow and surface runoff in the baseline period, and obtain the results of the impact of forest land and grassland on base flow and surface runoff; Compare and analyze the simulation results of base flow and surface runoff after the forest land is converted into urban land with the simulation results of base flow and surface runoff in the baseline period, and obtain the impact of forest land and urban land on base flow and surface runoff; The simulation results of base flow and surface runoff after grassland was converted into urban land were compared with those of base flow and surface runoff in the baseline period to obtain the impact of grassland and urban land on base flow and surface runoff.

9. The method for simulating the hydrological process of base flow and surface runoff of a gate-controlled river under a changing environment according to claim 1, characterized in that: Also includes: The established SWAT gate-controlled river hydrological model was calibrated and verified.

10. A hydrological process simulation system for base flow and surface runoff of a gate-controlled river under a changing environment, characterized in that: include: The first module is used to obtain various basic data and measured runoff data of the gate-controlled river, wherein the various basic data include DEM data, soil type data, land use type data and meteorological data; The second module is used to simultaneously introduce the nonlinear reservoir and dam modules on the basis of the original SWAT hydrological model, and establish the SWAT gate-controlled river hydrological model according to various basic data of the gate-controlled river; The third module is used to simulate and obtain the base flow data and surface runoff data of the gate-controlled river based on the SWAT gate-controlled river hydrological model; The fourth module is used for dividing the measured runoff data of the gate-controlled river into base flow and surface runoff based on the measured runoff data of the gate-controlled river by using a digital filtering method; The fifth module is used to compare the base flow data and surface runoff data obtained by segmentation by the digital filtering method with the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model, so as to achieve comparison and verification of the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model; The sixth module is used to perform cross wavelet transform and / or wavelet coherence transform on the base flow data and surface runoff data obtained by simulating the SWAT gate-controlled river hydrological model and the meteorological data, respectively, to obtain cross wavelet transform and / or wavelet coherence transform results of the base flow data and surface runoff data and the meteorological data; The seventh module is used to determine the coherence degree between the base flow and the surface runoff and the meteorological elements in the time-frequency domain according to the cross wavelet transform and / or wavelet coherence transform results of the obtained base flow data and the surface runoff data and the meteorological data; The eighth module is used to input the land use type data of different scenarios of the gate-controlled river into the established SWAT gate-controlled river hydrological model to obtain the impact results of land use type elements on the base flow and the surface runoff.

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