ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, Vol. 14, No. 1, pp. 50-57

Identification of pollution sources in the Sea of Azov using the adjoint equation method

V.S. Kochergin 1 , S.V. Kochergin 1 , S.V. Stanichny 1 
1 Marine Hydrophysical Institute RAS, Sevastopol, Russia
Accepted: 16.12.2016
DOI: 10.21046/2070-7401-2017-14-1-50-57
Successive satellite images provide information about the changes in spatial structures measured in the optical range, especially by tracking the scattering suspended matter concentration. The joint use of the satellite data and passive admixtures transfer models is of interest in identifying the sources of suspended matter. The test example demonstrates the efficiency of variational identification algorithm and outlines a comparison between numerical simulation and successive satellite images taken by the MODIS scanner. The variational pollution source identification algorithm is implemented for the region of the Dolgaya Spit. The measurement data assimilation algorithm in the passive admixture transfer model is implemented using gradient methods for optimal estimate retrieval. The retrieval is carried out by means of minimizing a quadratic function of prediction quality. The linked problem solving is used in the gradient of quality functional construction. On the basis of the variational method of data assimilation, the optimal estimate retrieval algorithm for pollution source power identification is constructed. In application of the algorithm, the integration of the main, linked and variational problems is implemented. The latter is solved to determine an iteration parameter when performing gradient descent. Integration problems are solved using TVD approximations. For the application of the procedure, the Sea of Azov flow fields and turbulent diffusion coefficients are obtained using the sigma coordinate ocean model (POM) under the eastern wind stress conditions being dominant at the observed period of time. For that period the satellite image series characterizing the surface concentration of suspended matter in the Sea of Azov gives an idea of dynamic processes occurring in the basin. The linked problem solving and influence functions measurement allow for defining the coastal zones having an effect on higher loads of suspended matter in the region of the Dolgaya Spit observed in the satellite images. The model estimation and the satellite data on the loads of suspended matter were brought into comparison. The analysis of the obtained data shows a positive correlation between the numerical simulation results and the satellite data based on a specified pollution source located along the northern coastal line of the Dolgaya Spit, where turbidity generally occurs under given dynamic conditions. Furthermore, the results can be used to perform numerical data assimilation on loads of suspended matter.
Keywords: satellite data, concentration of passive admixture, transport model, Azov Sea, the adjoint equation
Full text


  1. Ivanov V.A., Fomin V.V., Matematicheskoe modelirovanie dinamicheskih protsessov v zone morya-susha (Mathematical modeling of dynamic processes in the area of the Sea-Earth), Sevastopol: EKOSI–gidrofizika, 2008, 363 p.
  2. Kochergin S.V., Kochergin V.S., Fomin V.V., Opredelenie kontsentratsii passivnoy primesi v Azovskom more na osnove resheniya serii sopryazhennyih zadach (Determination of passive admixture concentration in the Azov Sea based on a solutions series of adjoint tasks), Ekologicheskaya bezopasnost pribrezhnoy i shelfovoy zon i kompleksnoe ispolzovanie resursov shelfa, Sevastopol: MGI NANU, 2012, Issue 26, Vol. 2, pp. 112–118.
  3. Kochergin V.S., Identifikatsiya nachalnogo polya kontsentratsii dlya modeli perenosa passivnoy primesi v Azovskom more (Identification of the initial concentration field for the passive admixture transport model in the Azov Sea), Ekologicheskaya bezopasnost pribrezhnoy i shelfovoy zon i kompleksnoe ispolzovanie resursov shelfa, Sevastopol: MGI NANU, 2012, Issue 26, Vol. 2, pp. 123–125.
  4. Kochergin V.S., Kochergin S.V., Identifikatsiya moschnosti istochnika zagryazneniya v Kazantipskom zalive na osnove primeneniya variatsionnogo algoritma (Identification of power source pollution in the Kazantip bay by applying a variational algorithm), Morskoy gidrofizicheskiy zhurnal, 2015, No. 2, pp. 79–88.
  5. Marchuk G.I., Matematicheskoe modelirovanie v probleme okruzhayuschey sredyi (Mathematical modeling in environmental problem), Moskow: Nauka, 1982, 320 p.
  6. Fomin V.V., Chislennaya model tsirkulyatsii vod Azovskogo morya (Numerical circulation model of the Azov Sea water), Nauchnyie trudyi UkrNIGMI, 2002, Vol. 249, pp. 246–255.
  7. Blumberg A.F., Mellor G.L., A description of the three-dimensional coastal ocean circulation model, In: Three-dimensional coastal ocean models, Heaps N. (ed.), Am. Geoph. Union, 1987, Vol. 4, pp. 1–16.
  8. Marchuk G.I., Penenko V.V., Application of optimization methods to the problem of mathematical simulation of atmospheric processes and environment, Modelling and Optimization of Complex Systems, Proc. IFIP-TC7 Working conf., New-York, Springer 1978, pp. 240–252.