农业地下水位预测模型数据

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，硝酸盐，磷酸盐，土壤湿度，土壤类型，肥料用量。输出为地下水地下水位。该模型帮助解决了地下水位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位。该模型通过输入地下水的灌溉用水，降雨量，化学需氧量，硝酸盐，磷酸盐，土壤湿度，土壤类型，肥料用量，来输出预测的地下水位。

This dataset is intended for agricultural groundwater level prediction. Its input features consist of agricultural groundwater irrigation water, rainfall, chemical oxygen demand (COD), nitrate, phosphate, soil moisture, soil type, and fertilizer application rate, with the output being the predicted groundwater level. This model addresses the challenge of modeling the relationship between groundwater levels, agricultural climatic factors, and physicochemical indices of groundwater. Physicochemical indicators of groundwater and climatic factors were collected through physicochemical experiments, thermometers and other monitoring instruments. Then, the collected groundwater physicochemical indicators and climatic data were utilized with traditional algorithms including multiple linear regression to predict groundwater levels. Specifically, this model takes the aforementioned input parameters (irrigation water, rainfall, COD, nitrate, phosphate, soil moisture, soil type, fertilizer application rate) to generate the predicted groundwater level.