China Institute of Water Resources and Hydropower Research

Shaohui Zhang

Di Xu

Fuxiang Li

Meijian Bai

Yinong Li

Wei Dai

Qunchang Liu

A method for acquiring a canal flow rate, comprising: measuring an actual measure value of an upstream water depth and an actual measure value of a downstream water depth of a target canal; presetting the upstream canal flow rate and surface water infiltration rate of the target canal, and respectively acquiring preset values of each; substituting the actual measured value of the upstream water depth, the preset value of the upstream canal flow rate, and the preset value of the surface water infiltration rate into Saint-Venant equations, so as to solve the equations and obtain a downstream water depth simulation value of the target canal; when the relative error between the downstream water depth simulation value and the actual measured value of the downstream water depth is less than or equal to the preset threshold value, acquiring a viable upstream canal flow rate and a viable surface water infiltration rate; otherwise, optimizing the preset value of the upstream canal flow rate and the preset value of the surface water infiltration rate, and repeating the described process until the relative error between the two is less than or equal to the preset threshold value, so as to acquire the two viable results and acquire the canal flow rate at any measurement point of the target canal.

Method for irrigating farmland

A simulation method of a surface water movement process in surface irrigation, comprising: acquiring surface relative elevation data, border surface roughness coefficient data and surface water infiltration rate data of a target border check; substituting surface relative elevation data, border surface roughness coefficient data and surface water infiltration rate data into improved full hydrodynamic equations, and performing numerical solution on improved full hydrodynamic equations to obtain a simulated surface water depth value and simulated values of vertical integral average velocities of an irrigation water flow in x-coordinate and y-coordinate directions of a certain measurement site in the target border check at a certain time; and obtaining simulated values of unit width discharge of the irrigation water flow in x-coordinate and y-coordinate directions, respectively according to simulated surface water depth value and simulated values of the vertical integral average velocities of the irrigation water flow in x-coordinate and y-coordinate directions.

Simulation method of surface water flow movement process in surface irrigation

The present invention belongs to the technical field of irrigation and water conservancy, and discloses a method for acquiring anisotropic basin surface roughness and use thereof. The method includes: preselecting two experimental strip fields respectively parallel to length direction and width direction of a target basin, to respectively acquire first surface water flow advancing process data of the two experimental strip fields, where the target basin may be regarded as a square-shaped field; acquiring two pieces of isotropic basin surface roughness respectively by using one-dimensional complete hydrodynamic model for basin irrigation according to the surface water flow advancing process data; and substituting the isotropic basin surface roughness into an elliptic equation that anisotropic basin surface roughness satisfies, to solve anisotropic basin surface roughness of the target basin, the anisotropic basin surface roughness including basin surface roughness components parallel to and perpendicular to shallow furrows on basin surface and crop planting direction in the target basin. The anisotropic basin surface roughness can truly reflect the resistance of the basin surface against the water flow, thereby improving simulation precision of surface irrigation hydrodynamics, and acquiring more accurate irrigation performance indexes.

Method for acquiring anisotropic basin surface roughness and use thereof

A method for irrigating terrain comprising the following steps: generating field surface relative elevation data set using Monte-Carlo simulation; adjusting the simulation data set to ensure it falls in a reasonable numerical range; adjusting the data set to establish certain spatial dependence using Kriging interpolation method; and making further statistical characteristics parameter modification to the data set, so that the final corrected field surface relative elevation data shares the same or similar statistics characteristics parameters as the initial simulation. The method factors in both the randomness and spatial dependence of the field relative elevation distribution, which brings the simulation result closer to the actual micro-topography.

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Beijing, China

Shaohui Zhang