Inverse Modeling for Aquatic Source and Transport Parameters Identification and its Application to Fukushima Nuclear Accident.

Sharma, L.; Ghosh, A.; Nair, R.; Chopra, Manish; Sunny, Faby; Puranik, V.

Inverse modeling technique based on nonlinear least square regression method (LSRM) is developed for the identification of aquatic source and transport parameters. Instantaneous line source release model in two-dimensional domain and continuous point source release model in three-dimensional domain are used for the purpose. Case studies have been carried out for both types of releases to illustrate their application. Error analysis has been carried out to identify the maximum error that can be tolerated in the input concentration data used in the inverse model and to specify the minimum number of sampling points to generate such input data. The LSRM is compared with the well-established correlation coefficient optimization method for instantaneous line source release model, and good comparison is observed between them. The LSRM is used to quantitatively estimate the releases of different radionuclides into the Pacific Ocean which has resulted due to the discharge of highly radioactive liquid effluent from the affected Daiichi Nuclear Power Station at Fukushima in Japan. The measured concentrations of these radionuclides in seawater samples collected from two sampling points near Fukushima are used for the estimation. The average release works out to be 1.09 × 10 for I, 3.4 × 10 Bq for Cs, and 3.57 × 10 Bq for Cs. Very good agreement is observed between the releases estimated in this study and those estimated by other different agencies.

PACIFIC Ocean; FUKUSHIMA Nuclear Accident, Fukushima, Japan, 2011; RADIOACTIVE pollution of the sea; RADIOISOTOPES; REGRESSION analysis

Environmental Modeling & Assessment, 2014, Vol 19, Issue 3, p193

1420-2026

Academic Journal

10.1007/s10666-013-9391-1