A high-performance distributed fine-grained hydrological forecast simulation method

Abstract

The present invention discloses a high-performance distributed fine hydrological forecast simulation method, comprising the following steps: obtaining a hydrological forecast study area, dividing the study area into M triangular sub-units, and obtaining the boundary and boundary length L of each sub-unit m. m A hydrological data equation is constructed to calculate the hydrological forecast data for each subunit m. The hydrological data equation includes a precipitation equation, an evaporation equation, a soil moisture movement equation, and a slope runoff and confluence equation. Hydrological data variables within subunit m are obtained and input into the hydrological data equation to calculate the hydrological forecast data for subunit m, thereby calculating the confluence data of the river network within the study area. The trough storage capacity of the river network is calculated based on the confluence data of the river network, thereby simulating the evolution of floods within the study area. The present invention fully considers the changes and evolution of hydrological processes in space and time, more accurately simulates the hydrological evolution phenomenon of a local area, and improves the spatial accuracy of hydrological forecasts.

Description

Technical Field

[0001] The present invention relates to the field of hydrological research, and in particular to a high-performance distributed fine hydrological forecast simulation method. Background Art

[0002] As global climate and human activities increasingly impact the hydrological cycle, basin-wide hydrological variability is increasing. Traditional conceptual lumped hydrological models simulate the basin as a whole, making it difficult to accurately account for the spatiotemporal distribution of basin hydrology. Furthermore, because conceptual hydrological models lack rigorous physical mechanisms, model parameters require extensive field data for fitting and determination. Furthermore, such models are generally applied to large river basins, limiting their applicability. Existing distributed hydrological models also suffer from deficiencies in computational efficiency and adaptability to complex terrain and underlying surface conditions. Furthermore, effective methods are often lacking for merging large amounts of hydrological data, making it difficult to achieve accurate and rapid hydrological forecasting and simulation. Summary of the Invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a high-performance distributed fine hydrological forecast simulation method, which can accurately simulate the hydrological change process and achieve high-performance distributed fine hydrological forecasting in the study area.

[0004] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0005] A high-performance distributed fine hydrological forecast simulation method is provided, which includes the following steps:

[0006] S1: Obtain the study area for hydrological forecast, split the study area into M triangular sub-units, and obtain the boundary and boundary length L of each sub-unit m m ;

[0007] S2: Constructing hydrological data equations to calculate the hydrological forecast data for each subunit m. The hydrological data equations include precipitation equation, evaporation equation, soil moisture movement equation, and slope runoff generation and confluence equation;

[0008] S3: Obtain the hydrological data variables in subunit m, input the hydrological data variables into the hydrological data equation, calculate the hydrological forecast data of subunit m, and then calculate the confluence data of the river network in the study area;

[0009] S4: Calculate the channel storage of the river network based on the confluence data of the river network and simulate the flood evolution in the study area.

[0010] Furthermore, the precipitation equation is:

[0011]

[0012] Where k is the number of the rainfall monitoring station in the study area, K is the number of rainfall monitoring stations, and p k (t) is the rainfall data reported by the kth rainfall monitoring station at time t, is the influence weight of the rainfall data reported by the kth rain gauge station on the precipitation calculation of subunit m, P m (t) is the total rainfall of subunit m at time t; if the rainfall monitoring station k is located in subunit m, then If the rainfall monitoring station k is located on the boundary of subunit m, then If the rain gauge station k is located on the boundary vertex of the subunit m, then according to the number n of subunits adjacent to the boundary vertex where the rain gauge station k is located,

[0013] The evaporation equation is:

[0014]

[0015] Among them, E m (t) is the potential evaporation of subunit m, Q is the runoff during the snowmelt process, α is the relationship coefficient between snowmelt runoff and evaporation, DDF is the degree-day factor of ice and snow, T is the snowmelt threshold temperature, T t is the actual temperature, P′ is the natural melting amount, Δl is the slope of the saturated water vapor pressure-temperature curve, R m is the net radiation received by subunit m, G m is the heat flux of the soil in subunit m, ρ is the air density, c is the specific heat of air at constant pressure, e0 is the saturated water vapor pressure, e1 is the actual water vapor pressure, r1 is the aerodynamic resistance, r0 is the surface resistance, and γ is the psychrometric constant.

[0016] Furthermore, the soil water movement equation is:

[0017]

[0018] Where θ is the volumetric water content of the soil, z is the vertical coordinate of the soil layer downward, K(θ) is the soil hydraulic conductivity, and h is the soil water pressure head;

[0019] The soil water movement equation is discretely solved, and the soil layer on the soil profile is defined as J layer, and the thickness of each layer j is Z j , defining the time step of water movement in the soil as Δt, then the soil moisture content of the soil layer at time step t+1 is

[0020]

[0021] Where Δz j is the vertical coordinate of water movement in soil layer j, are the average hydraulic conductivity of water at the interface between the upper and lower layers of soil layer j, h j is the water pressure head of soil layer j;

[0022] The slope runoff generation and confluence equations include the slope runoff generation equation and the slope confluence motion equation;

[0023]

[0024] Among them, K0 is the saturated hydraulic conductivity, Q m (t) is the slope discharge, ψ is the wetting front suction, Δθ is the difference between the initial soil moisture content and the saturated soil moisture content, F m (t) is the cumulative infiltration area, Am is the water-passing cross-sectional area in subunit m;

[0025] According to the calculated slope runoff Q m (t) Establish the equation of motion for slope flow;

[0026]

[0027] Where H is the water depth on the slope, q m is the lateral inflow on the slope, x is the slope distance, S m1 S is the slope that produces friction resistance to water flow, m0 is the bottom slope, v m is the slope convergence velocity.

[0028] Furthermore, step S3 includes:

[0029] S31: Obtain rainfall data reported by the rainfall monitoring station in subunit m, which includes rainfall and / or snowfall, and calculate the actual rainfall P in subunit m using the precipitation equation m ;

[0030] S32: Calculate the potential evaporation E in subunit m according to the evaporation equation m , and then calculate the soil water pressure head h;

[0031]

[0032] S33: Calculate the water pressure head h0 of the surface soil at the saturated water content based on the saturated water content of the surface soil on the slope, and calculate the water depth H=h-h0 on the slope during rainfall based on the water pressure head h;

[0033] S34: Substitute the water depth H on the slope into the slope flow equation to calculate the slope flow Q m (t) and slope flow velocity v, according to the slope flow Q in subunit m m(t) and slope flow velocity v are used to calculate the confluence data of the river network in the study area. The confluence data include confluence flow P and confluence velocity V;

[0034]

[0035] Furthermore, step S4 includes:

[0036] S41: Calculate the storage capacity S″ that the current river network needs to bear using the confluence flow P;

[0037] S″=K″[x″P+(1-x″)Q″];

[0038] Among them, K″ is the storage constant of the river network, x″ is the flow weighting factor of the river network, and Q″ is the ideal flood discharge capacity of the river network;

[0039] S42: According to the maximum storage capacity of the river network S max , assess whether flood disasters occur in the river network of the study area;

[0040] If S max ≤S″, it is determined that the river network in the study area will suffer from flood disasters. The time of flood disasters is after the time t′ when the rainfall monitoring station starts reporting rainfall data. L is the average length of the slope in the study area;

[0041] If S max If ≤S″, it is determined that the river network in the study area will not suffer from flood disasters.

[0042] The beneficial effects of the present invention are as follows: the present invention fully considers the changes and evolution of hydrological processes in space and time, and by dividing the study area into multiple sub-units, the spatial distribution differences of hydrological processes in different sub-units in the study area can be discussed separately, and accurate hydrological evolution simulation equations are established in each sub-unit, thereby realizing high-performance distributed fine hydrological simulation and forecasting of the entire river basin, more accurately simulating the hydrological evolution phenomena in local areas, and improving the spatial accuracy of hydrological forecasting. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Flowchart of the high-performance distributed fine-grained hydrological forecast simulation method. DETAILED DESCRIPTION

[0044] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0045] like Figure 1 As shown, a high-performance distributed fine hydrological forecast simulation method includes the following steps:

[0046] S1: Obtain the study area for hydrological forecast, split the study area into M triangular sub-units, and obtain the boundary and boundary length L of each sub-unit m m ; Can better adapt to complex basin terrain.

[0047] S2: Constructing hydrological data equations to calculate the hydrological forecast data for each subunit m. The hydrological data equations include precipitation equation, evaporation equation, soil moisture movement equation, and slope runoff generation and confluence equation;

[0048] The precipitation equation is:

[0049]

[0050] Where k is the number of the rainfall monitoring station in the study area, K is the number of rainfall monitoring stations, and p k (t) is the rainfall data reported by the kth rainfall monitoring station at time t, is the influence weight of the rainfall data reported by the kth rain gauge station on the precipitation calculation of subunit m, P m (t) is the total rainfall of subunit m at time t; if the rainfall monitoring station k is located in subunit m, then If the rainfall monitoring station k is located on the boundary of subunit m, then If the rain gauge station k is located on the boundary vertex of the subunit m, then according to the number n of subunits adjacent to the boundary vertex where the rain gauge station k is located,

[0051] The evaporation equation is:

[0052]

[0053] Among them, E m (t) is the potential evaporation of subunit m, Q is the runoff during the snowmelt process, α is the relationship coefficient between snowmelt runoff and evaporation, which is related to the current temperature. The higher the temperature, the larger the relationship coefficient α, and vice versa. DDF is the degree-day factor of ice and snow, T is the snowmelt threshold temperature, T t is the actual temperature, P′ is the natural melting amount, Δl is the slope of the saturated water vapor pressure-temperature curve, R m is the net radiation received by subunit m, G m is the heat flux of the soil in subunit m, ρ is the air density, c is the specific heat of air at constant pressure, e0 is the saturated water vapor pressure, e1 is the actual water vapor pressure, r1 is the aerodynamic resistance, r0 is the surface resistance, and γ is the psychrometric constant.

[0054] The soil water movement equation is:

[0055]

[0056] Where θ is the volumetric water content of the soil, z is the vertical coordinate of the soil layer downward, K(θ) is the soil hydraulic conductivity, and h is the soil water pressure head;

[0057] The soil water movement equation is discretely solved, and the soil layer on the soil profile is defined as J layer, and the thickness of each layer j is Z j , defining the time step of water movement in the soil as Δt, then the soil moisture content of the soil layer at time step t+1 is

[0058]

[0059] Where Δz j is the vertical coordinate of water movement in soil layer j, are the average hydraulic conductivity of water at the interface between the upper and lower layers of soil layer j, h j is the water pressure head of soil layer j;

[0060] The slope runoff generation and confluence equations include the slope runoff generation equation and the slope confluence motion equation;

[0061]

[0062] Among them, K0 is the saturated hydraulic conductivity, Q m (t) is the slope discharge, ψ is the wetting front suction, Δθ is the difference between the initial soil moisture content and the saturated soil moisture content, F m (t) is the cumulative infiltration area, Am is the water-passing cross-sectional area in subunit m;

[0063] According to the calculated slope runoff Q m (t) Establish the equation of motion for slope flow;

[0064]

[0065] Where H is the water depth on the slope, q m is the lateral inflow on the slope, x is the slope distance, S m1 S is the slope that produces friction resistance to water flow, m0 is the bottom slope, v m is the slope convergence velocity.

[0066] S3: Obtain the hydrological data variables within subunit m and input them into the hydrological data equation to calculate the hydrological forecast data for subunit m. This, in turn, calculates the runoff data for the river network within the study area. By continuously updating the hydrological data variables for each subunit, a simulation and forecast of the hydrological processes for the entire study area is achieved.

[0067] Step S3 specifically includes:

[0068] S31: Obtain rainfall data reported by the rainfall monitoring station in subunit m, which includes rainfall and / or snowfall, and calculate the actual rainfall P in subunit m using the precipitation equation m ;

[0069] S32: Calculate the potential evaporation E in subunit m according to the evaporation equation m , and then calculate the soil water pressure head h;

[0070]

[0071] S33: Calculate the water pressure head h0 of the surface soil at the saturated water content based on the saturated water content of the surface soil on the slope, and calculate the water depth H=h-h0 on the slope during rainfall based on the water pressure head h;

[0072] S34: Substitute the water depth H on the slope into the slope flow equation to calculate the slope flow Q m (t) and slope flow velocity v, according to the slope flow Q in subunit m m (t) and slope flow velocity v are used to calculate the confluence data of the river network in the study area. The confluence data include confluence flow P and confluence velocity V;

[0073]

[0074] S4: Calculate the river network's channel storage capacity based on the river network's confluence data and simulate the flood evolution in the study area. Step S4 specifically includes:

[0075] S41: Calculate the storage capacity S″ that the current river network needs to bear using the confluence flow P;

[0076] S″=K″[x″P+(1-x″)Q″];

[0077] Among them, K″ is the storage constant of the river network, x″ is the flow weighting factor of the river network, and Q″ is the ideal flood discharge capacity of the river network;

[0078] S42: According to the maximum storage capacity of the river network S max , assess whether flood disasters occur in the river network of the study area;

[0079] If S max≤S″, it is determined that the river network in the study area will suffer from flood disasters. The time of flood disasters is after the time t′ when the rainfall monitoring station starts reporting rainfall data. L is the average length of the slope in the study area;

[0080] If S max If ≤S″, it is determined that the river network in the study area will not suffer from flood disasters.

[0081] The present invention fully considers the changes and evolution of hydrological processes in space and time. By dividing the study area into multiple sub-units, the spatial distribution differences of hydrological processes in different sub-units within the study area can be discussed separately, and accurate hydrological evolution simulation equations are established in each sub-unit, thereby realizing high-performance distributed fine hydrological simulation and forecasting of the entire basin, more accurately simulating the hydrological evolution phenomena in local areas, and improving the spatial accuracy of hydrological forecasting.

Claims

1. A high-performance distributed fine hydrological forecast simulation method, characterized in that: The following steps are involved: S1: Obtain the study area for hydrological forecast and split the study area into M triangular subunits, And get each subunit m The boundary and boundary length L m ; S2: Construct and calculate each subunit m Hydrological data equations for hydrological forecast data, including precipitation equation, evaporation equation, soil moisture movement equation, slope runoff and confluence equation; S3: Get subunits m The hydrological data variables in the subunit are input into the hydrological data equation to calculate the hydrological data variables. m The hydrological forecast data of the study area are used to calculate the runoff data of the river network in the study area; S4: Calculate the river network's channel storage capacity based on the river network's confluence data and simulate the flood evolution in the study area; The precipitation equation is: ； in, k is the number of the rainfall monitoring station in the study area, K is the number of rain gauge stations, For the k Rain gauge stations at the time t Reported rainfall data, For the first k Rainfall data reported by rainfall monitoring stations for subunits m The influence weight of precipitation calculation, For subunits m At the moment t The total rainfall at the rainfall monitoring station k Located in subunit m Inside, then , if the rainfall monitoring station k Located in subunit m On the boundary of , if the rainfall monitoring station k Located in subunit m At the boundary vertex, according to the rainfall detection station k The number of adjacent subunits at the boundary vertex n , ; The evaporation equation is: ； in, For subunits m The potential evaporation Q is the runoff during snowmelt, is the relationship coefficient between snowmelt runoff and evaporation, DDF The factor of ice and snow, T is the snowmelt threshold temperature, T t is the actual temperature, is the natural melting amount, is the slope of the saturated water vapor pressure-temperature curve, R m For subunits m The net radiation received, G m For subunits m The heat flux of the inner soil, is the air density, c is the specific heat of air at constant pressure, e 0 is the saturated water vapor pressure, e 1 is the actual water vapor pressure, r 1 is the aerodynamic resistance, r 0 is the surface resistance, is the psychrometric constant.

2. The high-performance distributed fine hydrological forecast simulation method according to claim 1 is characterized in that: The soil moisture movement equation is: ； in, is the volumetric water content of the soil, z is the vertical coordinate of the soil layer downward, is the soil hydraulic conductivity, h is the soil water pressure head; The soil water movement equation is solved discretely, and the soil layers on the soil profile are defined as J Layer, each layer of soil j The thickness is Z j , the time step of water movement in the soil is defined as , then the soil layer in time step t The soil moisture content on +1 is ; ； in, Soil layer j The vertical coordinate of internal water movement, Water in the soil j The average hydraulic conductivity at the interface between the upper and lower layers is h j Soil layer j Water pressure head; The slope runoff generation and confluence equations include the slope runoff generation equation and the slope confluence motion equation; ； in, K 0 is the saturated hydraulic conductivity, is the slope runoff, For the moist front suction, is the difference between the initial soil moisture content and the saturated soil moisture content. is the cumulative infiltration area, A m For subunits m Internal water flow cross-sectional area; According to the calculated slope flow Establish the slope confluence motion equation; ； in, H is the water depth on the slope, q m is the lateral inflow on the slope, x is the slope distance, The slope that creates frictional resistance to water flow, is the bottom slope, v m is the slope convergence velocity.

3. The high-performance distributed fine hydrological forecast simulation method according to claim 2 is characterized in that: The step S3 comprises: S31: Get subunit m Rainfall data reported by internal rain gauge stations, including rainfall and / or snowfall, is calculated using the precipitation equation subunit m Actual rainfall in P m ; S32: Calculation subunit based on evaporation equation m Potential evaporation within E m , and then calculate the soil water pressure head h ; ； S33: Calculate the water pressure head of the surface soil at saturated water content based on the saturated water content of the surface soil on the slope h 0, according to water pressure head h Calculate the water depth on a slope during rainfall ; S34: The water depth on the slope H Substitute into the slope flow equation to calculate the slope flow yield and slope convergence velocity v m , according to the subunit m Slope flow within and slope convergence velocity v m Calculate the confluence data of the river network in the study area, including the confluence flow P and confluence velocity V ; 。 4. The high-performance distributed fine hydrological forecast simulation method according to claim 3 is characterized by In, The step S4 comprises: S41: Using Confluence Flow P Calculate the storage capacity that the current river network needs to bear ; ； in, is the storage constant of the river network, is the flow weighting factor of the river network, is the ideal flood discharge capacity of the river network; S42: Based on the maximum storage capacity of the river network , assess whether flood disasters occur in the river network of the study area; like , it is determined that the river network in the study area will suffer from flood disasters. The time when the flood disaster occurs is the time when the rainfall monitoring station starts reporting rainfall data. after, , L is the average length of the slope in the study area; like , it is determined that the river network in the study area will not suffer from flood disasters.

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