Modeling of standardized groundwater index of Bihar using machine learning techniques

• Main Authors: Kumari S., Kumar D., Kumar M., Pande C.B.
• Other Authors: 58164893400
• Format: Article
• Published: Elsevier Ltd 2024
• Subjects: Artificial neural network and random forest; GRACE satellite; Groundwater drought; Standardized groundwater index; Bihar; India; Drought; Forestry; Geodetic satellites; Groundwater resources; Learning algorithms; Machine learning; Mean square error; Neural networks; Rain; Artificial neural network modeling; Correlation coefficient; Gravity recovery and climate experiment satellites; Machine learning techniques; Means square errors; Random forests; Water equivalent; artificial neural network; GRACE; groundwater; modeling; rainfall; Groundwater

Groundwater is the most preferred source of water resource for the human needs. Over-exploitation of the groundwater has been led to the tremendous effect on the groundwater drought. Assessment of groundwater drought is difficult to understand due to its complexity, non-linearity feature. In this st...