MODELING STEADY STATE GROUNDWATER DISTRIBUTION ON FRACTURED FLOW MEDIA CASE STUDY OPEN PIT GRASBERG - SITUMORANG - NIM: 22715001, SYAIFUL
The condition of the area in the complex geological structure causes the groundwater level between several points to have a very significant difference, so that a research is needed to find out the groundwater level in the complex geological condition, especially on the flow media flow. This study aims to determine the distribution of groundwater in the flow media berkekar using soft computing and geostatistics method. The soft computing method of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) use coordinates (x, y, z), rock quality designation (RQD), hydraulic conductivity (K) and groundwater level in the pizometer as input of ANFIS and ANN in order to predict the groundwater level. Meanwhile, the Kriging method uses the coordinate (x, y, z) and groundwater level in the pizometer. Groundwater distribution modeling is based on 49 groundwater level data in pizometer and 90 other groundwater level data, where 41 groundwater level data is the addition of clustering data. Predicted groundwater level based on 49 data and 90 data shows that ANFIS can predict the distribution of groundwater level in fractured media with high accuracy that is validated by the result on groundwater level distribution map which indicates good prediction.