Chapter 4
Application of Artificial Intelligence
in Predicting Groundwater Contaminants
Sushant K. Singh, Ataollah Shirzadi, and Binh Thai Pham
4.1 Introduction
Groundwater constitutes 95% of all global freshwater, and more than 7 billion
individuals depend on it for their domestic needs (NGWA 2020). Groundwater is
naturally characterized by certain physical, chemical, and biological properties. Its
major chemical constituents, whose concentrations may range between 1 mg/L and
1000 mg/L, are sodium, calcium, magnesium, bicarbonate, sulfate, chloride, and
silica (Chapman 1996; Şen 2014). Secondary and elemental constituents of groundwater include iron, aluminum, potassium, carbonate, nitrate, fluoride, boron, and
selenium, which may be found in concentrations between 0.01 mg/L and 10 mg/L
(Chapman 1996). Several other elements occur in slight levels (0.0001 mg/L to
0.1 mg/L) and form the minor elemental constituents of groundwater; these include
arsenic, barium, bromide, cadmium, chromium, cobalt, copper, iodide, lead, lithium,
manganese, nickel, phosphate, strontium, uranium, and zinc (Chapman 1996;
Schwarzenbach et al. 2010; Şen 2014). These natural groundwater constituents
may be altered by processes that are physical (dispersion and filtration), geochemical
(complexation, ionic strength, acid-base, oxidation–reduction, precipitation solution, and adsorption–desorption), or biochemical (decay, respiration, and cell synthesis) (Chapman 1996; Schwarzenbach et al. 2010). These processes are influenced
by a variety of anthropogenic activities that lead to groundwater pollution, including
S. K. Singh (*)
Artificial Intelligence & Analytics | Health Care and Life Sciences, Virtusa Corporation,
New York, NY, USA
A. Shirzadi
Department of Rangeland and Watershed Management, Faculty of Natural Resources,
University of Kurdistan, Sanandaj, Iran
B. T. Pham
Institute of Research and Development, Duy Tan University, Da Nang, Vietnam
© Springer Nature Singapore Pte Ltd. 2021
A. Singh et al. (eds.), Water Pollution and Management Practices,
https://doi.org/10.1007/978-981-15-8358-2_4
71
Application of Artificial Intelligence
in Predicting Groundwater Contaminants
Sushant K. Singh, Ataollah Shirzadi, and Binh Thai Pham
4.1 Introduction
Groundwater constitutes 95% of all global freshwater, and more than 7 billion
individuals depend on it for their domestic needs (NGWA 2020). Groundwater is
naturally characterized by certain physical, chemical, and biological properties. Its
major chemical constituents, whose concentrations may range between 1 mg/L and
1000 mg/L, are sodium, calcium, magnesium, bicarbonate, sulfate, chloride, and
silica (Chapman 1996; Şen 2014). Secondary and elemental constituents of groundwater include iron, aluminum, potassium, carbonate, nitrate, fluoride, boron, and
selenium, which may be found in concentrations between 0.01 mg/L and 10 mg/L
(Chapman 1996). Several other elements occur in slight levels (0.0001 mg/L to
0.1 mg/L) and form the minor elemental constituents of groundwater; these include
arsenic, barium, bromide, cadmium, chromium, cobalt, copper, iodide, lead, lithium,
manganese, nickel, phosphate, strontium, uranium, and zinc (Chapman 1996;
Schwarzenbach et al. 2010; Şen 2014). These natural groundwater constituents
may be altered by processes that are physical (dispersion and filtration), geochemical
(complexation, ionic strength, acid-base, oxidation–reduction, precipitation solution, and adsorption–desorption), or biochemical (decay, respiration, and cell synthesis) (Chapman 1996; Schwarzenbach et al. 2010). These processes are influenced
by a variety of anthropogenic activities that lead to groundwater pollution, including
S. K. Singh (*)
Artificial Intelligence & Analytics | Health Care and Life Sciences, Virtusa Corporation,
New York, NY, USA
A. Shirzadi
Department of Rangeland and Watershed Management, Faculty of Natural Resources,
University of Kurdistan, Sanandaj, Iran
B. T. Pham
Institute of Research and Development, Duy Tan University, Da Nang, Vietnam
© Springer Nature Singapore Pte Ltd. 2021
A. Singh et al. (eds.), Water Pollution and Management Practices,
https://doi.org/10.1007/978-981-15-8358-2_4
71