High-performance distributed fine hydrological forecast simulation method

Abstract

The invention discloses a high-performance distributed fine hydrological forecast simulation method, which comprises the following steps of: acquiring a research area of hydrological forecast, splitting the research area into M triangular subunits, and acquiring the boundary and the boundary length Lm of each subunit m; constructing a hydrological data equation for calculating hydrological forecast data of each subunit m, wherein the hydrological data equation comprises a precipitation equation, an evaporation equation, a soil moisture motion equation and a slope runoff and confluence equation; hydrological data variables in the subunit m are obtained, the hydrological data variables are input into the hydrological data equation, hydrological forecast data of the subunit m are calculated, and then confluence data of the river network in the research area are calculated; and calculating the tank storage capacity of the river network according to the convergence data of the river network, and simulating the flood routing condition in the research area. According to the method, the change and evolution of the hydrological process in space and time are fully considered, the hydrological evolution phenomenon of a local area is more accurately simulated, and the spatial precision of hydrological forecasting is improved.

Description

Technical Field

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

[0002] As the impact of global climate and human activities on the hydrological cycle intensifies, the hydrological differences in river basins are increasing. The traditional conceptual lumped hydrological model simulates the river basin as a whole, which makes it difficult to consider the spatiotemporal distribution of river basin hydrology in detail. At the same time, since the conceptual hydrological model lacks a strict physical mechanism, the model parameters require a large amount of measured data to fit and determine. Moreover, this type of model is generally applied to large river basins, and its applicability has certain limitations. Existing distributed hydrological models also have shortcomings in terms of computational efficiency and adaptability to complex terrain and underlying surface conditions. In addition, when dealing with a large amount of hydrological data fusion, there is often a lack of effective methods, 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 forecasting simulation method, which can accurately simulate the hydrological change process and realize 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 comprises the following steps:

[0006] S1: Obtain the study area for hydrological forecasting, 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: Construct the hydrological data equation for calculating the hydrological forecast data of each subunit m. The hydrological data equation includes 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 capacity 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 rainfall monitoring station on the precipitation calculation of subunit m, P m (t) is the total rainfall of subunit m at time t; if 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 rainfall detection station k is located on the boundary vertex of the subunit m, then according to the number n of other subunits adjacent to the boundary vertex where the rainfall detection 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 snowmelt, 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 moisture movement equation is:

[0017]

[0018] Among them, θ is the soil volume water content, 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 moisture movement equation is discretely solved, and the soil layer on the soil profile is defined as J layer, and the thickness of each soil layer j is Z j , the time step of water movement in the soil is defined 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 flow generation and confluence equations include the slope flow generation equation and the slope confluence motion equation;

[0023]

[0024] Where K0 is the saturated hydraulic conductivity, Q m (t) is the slope flow, 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 cross-sectional area of ​​water flow in subunit m;

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

[0026]

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

[0028] Further, step S3 includes:

[0029] S31: Obtain the rainfall data reported by the rainfall monitoring station in the subunit m, the rainfall data includes rainfall and / or snowfall, and use the precipitation equation to calculate the actual rainfall P in the subunit m. 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 according to the saturated water content of the surface soil on the slope, and calculate the water depth H=h-h0 on the slope during rainfall according to the water pressure head h;

[0033] S34: Substitute the water depth H on the slope into the slope confluence motion 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] Further, step S4 includes:

[0036] S41: Calculate the tank 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 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 experience flood disasters. The flood disaster will occur after the rainfall monitoring station starts reporting rainfall data, time t′. L is the average length of the slope in the study area;

[0041] If S max ≤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 divides the study area into multiple sub-units so that the spatial distribution differences of hydrological processes in different sub-units in the study area can be discussed separately, and an accurate hydrological evolution simulation equation is established on each sub-unit, thereby achieving 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 implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept 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 forecasting, 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 river basin topography.

[0047] S2: Construct the hydrological data equation for calculating the hydrological forecast data of each subunit m. The hydrological data equation includes 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 rainfall monitoring station on the precipitation calculation of subunit m, P m (t) is the total rainfall of subunit m at time t; if 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 rainfall detection station k is located on the boundary vertex of the subunit m, then according to the number n of other subunits adjacent to the boundary vertex where the rainfall detection 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 of snowmelt, 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] Among them, θ is the soil volume water content, 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 moisture movement equation is discretely solved, and the soil layer on the soil profile is defined as J layer, and the thickness of each soil layer j is Z j , the time step of water movement in the soil is defined 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 flow generation and confluence equations include the slope flow generation equation and the slope confluence motion equation;

[0061]

[0062] Where K0 is the saturated hydraulic conductivity, Q m (t) is the slope flow, 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 cross-sectional area of ​​water flow in subunit m;

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

[0064]

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

[0066] 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. By continuously updating the hydrological data variables of each subunit, the simulation forecast of the hydrological process in the entire study area can be achieved.

[0067] Step S3 specifically includes:

[0068] S31: Obtain the rainfall data reported by the rainfall monitoring station in the subunit m, the rainfall data includes rainfall and / or snowfall, and use the precipitation equation to calculate the actual rainfall P in the subunit m. 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 according to the saturated water content of the surface soil on the slope, and calculate the water depth H=h-h0 on the slope during rainfall according to the water pressure head h;

[0072] S34: Substitute the water depth H on the slope into the slope confluence motion 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 tank 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 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 experience flood disasters. The flood disaster will occur after the rainfall monitoring station starts reporting rainfall data, time t′. L is the average length of the slope in the study area;

[0080] If S max ≤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 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.

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 forecasting, split the study area into M triangular sub-units, and obtain the boundary and boundary length L of each sub-unit m m ; S2: Construct the hydrological data equation for calculating the hydrological forecast data of each subunit m. The hydrological data equation includes precipitation equation, evaporation equation, soil moisture movement equation, and slope runoff generation and confluence equation; 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; S4: Calculate the channel storage capacity of the river network based on the confluence data of the river network and simulate the flood evolution in the study area.

2. The high-performance distributed fine hydrological forecast simulation method according to claim 1 is characterized in that: The precipitation equation is: 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 rainfall monitoring station on the precipitation calculation of subunit m, P m (t) is the total rainfall of subunit m at time t; if 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 rainfall detection station k is located on the boundary vertex of the subunit m, then according to the number n of other subunits adjacent to the boundary vertex where the rainfall detection station k is located, The evaporation equation is: Among them, E m (t) is the potential evaporation of subunit m, Q is the runoff during snowmelt, 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.

3. The high-performance distributed fine hydrological forecast simulation method according to claim 2 is characterized in that: The soil moisture movement equation is: Among them, θ is the soil volume water content, 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; The soil moisture movement equation is discretely solved, and the soil layer on the soil profile is defined as J layer, and the thickness of each soil layer j is Z j , the time step of water movement in the soil is defined as Δt, then the soil moisture content of the soil layer at time step t+1 is 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; The slope flow generation and confluence equations include the slope flow generation equation and the slope confluence motion equation; Where K0 is the saturated hydraulic conductivity, Q m (t) is the slope flow, 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 cross-sectional area of ​​water flow in subunit m; According to the calculated slope flow Q m (t) Establish the equation of motion for slope confluence; Where H is the water depth on the slope, q m is the lateral inflow on the slope, x is the distance from the slope, S m1 S is the slope that produces friction resistance to water flow, m0 is the bottom slope, v m is the slope flow velocity.

4. The high-performance distributed fine hydrological forecast simulation method according to claim 3 is characterized in that: The step S3 comprises: S31: Obtain the rainfall data reported by the rainfall monitoring station in the subunit m, the rainfall data includes rainfall and / or snowfall, and use the precipitation equation to calculate the actual rainfall P in the subunit m. m ; S32: Calculate the potential evaporation E in subunit m according to the evaporation equation m , and then calculate the soil water pressure head h; S33: Calculate the water pressure head h0 of the surface soil at the saturated water content according to the saturated water content of the surface soil on the slope, and calculate the water depth H=h-h0 on the slope during rainfall according to the water pressure head h; S34: Substitute the water depth H on the slope into the slope confluence motion 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; 5. The high-performance distributed fine hydrological forecast simulation method according to claim 4 is characterized in that: The step S4 comprises: S41: Calculate the tank storage capacity S″ that the current river network needs to bear using the confluence flow P; S″=K″[x″P+(1-x″)Q″]; 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 of the river network; 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; If S max ≤S″, it is determined that the river network in the study area will experience flood disasters. The flood disaster will occur after the rainfall monitoring station starts reporting rainfall data, time t′. L is the average length of the slope in the study area; If S max ≤S″, it is determined that the river network in the study area will not suffer from flood disasters.

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