Spatial distribution method and device for rural domestic surface source load

Abstract

The invention provides a spatial distribution method and device for rural domestic surface source load. The method comprises the following steps: performing river network digitalization on a digital evaluation model by using a GIS (Geographic Information System) tool, and performing 'computing element' encoding according to a Pfafstetter drainage basin encoding method; establishing a nonlinear relation among a rural population size, a terrain factor and the load capacity under a time-space scale to realize spatial distribution characteristic prediction of the surface source load. A computing result is dynamic and stable, and has high simulation accuracy; the method is an effective method for identifying the type of surface source pollution, and has the characteristics of convenience in use, operability and the like; guidance about 'where the pollution is', 'where the pollution is severe' and 'where the pollution needs to be treated in time' can be provided for the water environment protection department, and rapid and effective responses can be made.

Description

technical field [0001] The invention belongs to the technical field of water environment, and in particular relates to a method and device for spatially distributing non-point source loads of rural life. Background technique [0002] The non-point source load of rural life generally refers to the pollutants produced by the domestic garbage and feces of the rural population. Such pollutants mainly include organic matter, nitrogen, phosphorus, etc. Rural life non-point source load is usually studied by empirical value method or non-physical mechanism methods such as mathematical statistics. The former is macroscopic and needs to be determined by empirical formulas or partial experimental data, and is restricted by the caliber of administrative units (such as cities, counties and other administrative units); the latter relies on complete and continuous environmental statistical data, and the calculation range is limited by administrative units. and data continuity limitations,...

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Problems solved by technology

The former is macroscopic and needs to be determined by empirical formulas or partial experimental data, and is restricted by the caliber of administrative units (such as cities, counties and other administrative units); the latter relies on complete and continuous environmental statistical data, and the calculation range is limited by administrative units. and data continuity limitations, and the prediction of non-point source load for rural life cannot be realized. Use mathematical statistics (such as: artificial neural network method) to analyze the connection between the data of rural population non-point source load, and analyze the physical mechanism of the results Weak

The prediction of non-point source load of rural population through the above two methods needs to rely on complete and continuous environmental statistical data. Once the data is missing, the prediction results will have large deviations

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