Water Resources Management

, Volume 33, Issue 3, pp 1123–1145 | Cite as

Groundwater Remediation through Pump-Treat-Inject Technology Using Optimum Control by Artificial Intelligence (OCAI)

  • Sina SadeghfamEmail author
  • Yousef Hassanzadeh
  • Rahman Khatibi
  • Ata Allah Nadiri
  • Marjan Moazamnia


Optimum Control by Artificial Intelligence (OCAI) is presented in this paper as a dynamic decision making algorithm for optimising pumpage schedule to remediate a contaminated aquifer using the Pump, Treat and Inject (PTI) method. OCAI integrates three modules to control contaminants, to reduce runtime and to meet water quality constraints and discharge capacity at the wells. There is no bespoke capability for the strategy presented by the paper, which formulates: (i) Module 1 comprises models of physics-based flow and transport for simulating heads and contamination; (ii) Module 2 serves as the “surrogate” of Module 1 by transforming the simulation outputs of Module 1 into two fast forecasting Sugeno Fuzzy Logic (SFL) models; and (iii) Module 3 is a user-defined unit to implement OCAI, to run Genetic Algorithm (GA) and to interrogate Module 2, where Modules 2 and 1 are pre-processed. The OCAI strategy resolves two barriers: (i) the information created in the past time step is passed on to new time step for an efficient control; and (ii) the ‘hunger’ of GA for function evaluation is met by the fast Module 2 but not by the slow Module 1. The novelty in OCAI includes: an optimum PTI schedule to control contaminants and to remediate contaminated plumes. The results show that the maximum Total Dissolved Matter is reduced from a range of 3500 to 8000 to a range from 1490 to 3450. The results provide “proof-of-concept” for OCAI.


Contaminant control Dynamic decision making Genetic algorithm Groundwater remediation Pump-treat-inject 



The authors would like to thank the East Azerbaijan Association of Environmental Protection and East Azerbaijan Regional Water Authority for their cooperation in data preparation. In particular, our gratitude is expressed to Dr. Dehganzadeh of Tabriz University of Medical Sciences and to Mr. Rahim Oglu of the East Azerbaijan Association of Environmental Protection for their kind helps and cooperation.

Compliance with Ethical Standards

We assure that the paper incorporates the following statements:

• Disclosure of potential conflicts of interest

• Research involving Human Participants and/or Animals

• Informed consent


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Sina Sadeghfam
    • 1
    Email author
  • Yousef Hassanzadeh
    • 2
  • Rahman Khatibi
    • 3
  • Ata Allah Nadiri
    • 4
  • Marjan Moazamnia
    • 2
  1. 1.Department of Civil EngineeringFaculty of Engineering, University of MaraghehMaraghehIran
  2. 2.Faculty of Civil EngineeringUniversity of TabrizTabrizIran
  3. 3.GTEV-ReX LimitedSwindonUK
  4. 4.Department of Earth SciencesFaculty of Natural Sciences, University of TabrizTabrizIran

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