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Detection of pollutant source in groundwater using hybrid optimization model

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Abstract

Detection of groundwater pollution source is an inverse problem. To solve this inverse problem, it has been posed into an optimization problem. In this study, a hybrid optimization model has been developed for detection of groundwater pollution sources in terms of its source characteristics, namely, source location, source strength and duration of activity of pollution source. In this hybrid optimization model, the Genetic Algorithm model has been linked with the Gradient Descent optimization model. The global convergence property of Genetic Algorithm has been utilized to find the optimal solution near global minima. This solution is then used as an initial guess to the Gradient Descent optimization model to find the global minima. The performance of developed hybrid model has been evaluated for two-dimensional case for error free and erroneous concentration data. Performance results show a significant improvement in the prediction error of groundwater pollution source parameters. The prediction error using GA model was found to be equal to 10.806%, 13.930% and 25.211% in source location, duration of activity and source strength, respectively, while using hybrid optimization model the prediction error were improved to 0.461%, 7.178% and 9.999%. The novelty of the present work is that it requires the observed concentration data of one observation well only for complete identification of pollution source. Also, a prior knowledge of probable locations of potential pollution sources is not required in this model.

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Fig. 7

source parameters with error free concentration data

Fig. 8

source parameters for run no. 5 with error level 5%

Fig. 9

source parameters for run no. 5 with error level 10%

Fig. 10
Fig. 11

source parameters for run no. 3 with error level 5%

Fig. 12

source parameters for run no. 9 with error level 10%

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Abbreviations

t :

Time

C :

Concentration of the dissolved pollutant

D x :

Coefficient of hydrodynamic dispersion in x-direction

D z :

Coefficient of hydrodynamic dispersion in z-direction

U :

Groundwater velocity in x-direction

R d :

Retardation factor

ν :

Decay constant

T o :

Duration of disposal period

C 0 :

Pollution source strength

n:

Total number of concentration observation reading at an observation well

\({\mathrm{C}}_{\mathrm{obs}}^{\mathrm{i}}\) :

Observed concentration at the observation well at ith reading

\({\mathrm{C}}_{\mathrm{est}}^{\mathrm{i}}\) :

Estimated concentration corresponding to the observation well at ith reading

q :

Vector of model parameters (source location and release period)

C :

Vector of simulated concentrations

h(q):

Simulation model which transform q into C

q l :

Lower bound on vector q

q u :

Upper bound on vector

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Acknowledgments

The authors wish to thank all who assisted in conducting this work.

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The authors have no relevant financial or non-financial interests to disclose.

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Authors and Affiliations

  1. Civil Engineering Section, University Polytechnic, Aligarh Muslim University Aligarh, Aligarh, 202002, India

    M. Ayaz

  2. Department of Civil Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, 202002, India

    S. A. Ansari

  3. Department of Civil Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, 202002, India

    O. K. Singh

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  1. M. Ayaz
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Correspondence to M. Ayaz.

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Ayaz, M., Ansari, S.A. & Singh, O.K. Detection of pollutant source in groundwater using hybrid optimization model. Int J Energ Water Res 6, 81–93 (2022). https://doi.org/10.1007/s42108-021-00118-4

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