农业地下水硝酸盐含量预测模型数据

可以用于农业地下水位预测,输入为农业中地下水的灌溉用水，降雨量，化学需氧量，地下水位，磷酸盐，土壤湿度，土壤类型，肥料用量。输出为地下水硝酸盐含量。该模型帮助解决了地下水硝酸盐含量和农业气候以及地下水理化指标的关系建模的问题。使用理化实验以及温度计等采集地下水理化指标以及气候因素，将采集的地下水理化指标以及气候数据使用传统算法，多元线性回归算法等方式以预测地下水硝酸盐含量。该模型通过输入地下水的灌溉用水，降雨量，化学需氧量，地下水位，磷酸盐，土壤湿度，土壤类型，肥料用量，来输出预测的硝酸盐含量。

This dataset can be used for agricultural groundwater nitrate content prediction. Its inputs include irrigation water for agricultural groundwater, rainfall, Chemical Oxygen Demand (COD), groundwater level, phosphate, soil moisture, soil type and fertilizer application rate, while the output is the nitrate content in groundwater. This model addresses the challenge of modeling the relationships between groundwater nitrate content, agricultural climatic factors and physiochemical indicators of groundwater. Physiochemical indicators of groundwater and climatic factors are collected via physicochemical experiments, thermometers and other relevant instruments. Then, traditional algorithms such as multiple linear regression are applied to the collected data to predict groundwater nitrate content. This model takes the above-mentioned inputs to output the predicted nitrate content in groundwater.