Abstract
Problem statement: Water is a major natural resource for all the livi ng beings in the world. People's lives and livelihood depends on water. Mos t of the human beings in this world use ground water for drinking purpose. The reason behind that is the ground water is pollution less or less polluted when compared with the surface water. The need for clean water increases continually with the world population growth. People in different ar eas in this world are lack of fresh drinkable water which is important for their survival. Maintaining secure water supplies for drinking, industry and agriculture is not possible without ground water. S o it is necessary to explore the potential ground w ater area to dig a well for the utilization of ground wa ter. Approach: In this study, we have used some parameters to identify the level of water in a part icular area. Then, the ground water identification system is designed with the help of Histogram Equalization , Neural Network and PCA. The collected data is given as input to data normalization and the featur e is computed for every data using PCA. The presence of ground water in particular location is identifie d using the trained neural network. Results: Finally, the experimentation is carried out using the synthetic data to show the performance of the ground water identification system. Conclusion: The potential zones of ground water can be identifi ed if the specified parameters of the particular location can be given as input to the neural network.
Highlights
The utility of the Geographic Information System (GIS) (Morales et al, 2002; Sudiana and Arbain, 2011; Carpio, 2011; Nouri et al, 2006) in groundwater management and research has been increased in large number
If the estimation of the rainfall in the target area comes under fifth category, the possibility of the ground water in the target area is less than 10% or there will not be any possibility of ground water in the target area
We identify some of the attributes for identifying the ground water and we apply the following preprocessing steps. (a) Data transformation: At first, the input data is converted into MxN format in which every row represents the number of locations and every column represents the attributes taken for identification of ground water. (b) Normalization using Histogram: System for ground water identification: This section presents the ground water identification system developed based on Principal Component Analysis (PCA)
Summary
The utility of the Geographic Information System (GIS) (Morales et al, 2002; Sudiana and Arbain, 2011; Carpio, 2011; Nouri et al, 2006) in groundwater management and research has been increased in large number. GIS is commonly used to create the digital geographic databases to influence and prepare the data as input for various model parameters and to display the model output. These functions allows primarily overlay or index operations, but latest GIS functions that exists or under development can further helps the necessity of process based approaches. A GIS controlled hydro geological database has been generated in order to aid data used in vulnerability assessment systems and numerical modeling for groundwater flow and contaminant transport studies. Coupling between the database and process based numerical systems were implemented. Data and information is complex which is necessary for the hydro geological studies. Data are collected from existing databases and maps and from field measurements
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