流域面源污染监测及动态扩散模型训练数据集

基于对面源污染源（如农业活动、城镇地表径流等）的实时监测数据，包括污染物的种类、浓度、排放位置等信息，以及流域内的气象、水文条件等影响因素，运用统计学方法或机理模型等算法，对数据进行分析和处理，从而训练出能够模拟污染物在流域内形成、迁移、转化及扩散过程的模型，为流域面源污染的预警、防控和水质管理提供科学依据

Based on real-time monitoring data of non-point source pollution sources (such as agricultural activities, urban surface runoff, etc.), including information such as pollutant types, concentrations, discharge locations and other related details, as well as influencing factors like meteorological and hydrological conditions within the watershed, this dataset uses algorithms including statistical methods and mechanistic models to analyze and process the data, thereby training models that can simulate the formation, migration, transformation and diffusion processes of pollutants in the watershed, providing a scientific basis for early warning, prevention and control, and water quality management of watershed non-point source pollution.

搜集汇总

数据集介绍

特点

该数据集主要用于流域环境管理，通过实时监测和机器学习算法训练模型，预测污染物扩散趋势，实现预警和防控。数据规模为10.3GB，无更新周期。