Prediction flooding zones of the Amga River floodplain using geoinformation technologies

Natural emergencies have a significant impact on the surrounding areas and real-world objects. Due to the large scale of the territory, climatic conditions, landscape and geographical characteristics, in Russia, the most dangerous emergencies are natural. For the Northern regions of the country, one of these situations is flooding. In the northern territories, severe climatic conditions prevail, and the average temperature growth rate is twice as high as in other regions of the country, which can lead to the retreat of permafrost, which in turn entails dangerous hydrometeorological phenomena. The goal of this work is to determine the flooded zones of the Amga river during the spring flood using geoinformation technology. The object of the study is the Amga river in the middle course, which was flooded in 2018. The subject of the study is the prediction of flooded zones of the Amga river based on satellite observations. Satellite images with a thick layer of clouds were used to determine the flooded zones. A mathematical method (based on the vegetation index), a geoinformation method (raster), and a geometric approach (DEM) were applied. Methodologies have been developed for determining flooded zones using multispectral images, radar images, and a digital terrain model. By comparing the results obtained, you can determine which zones are affected and which are at risk in the future.

1. Istomina M. N., Kocharyan A. G., Lebedeva I. P., Nikitskaya K. E. Ecological consequences of floods. Inzhenernaya ekologiya. 2004;4:3-21. (In Russ)

2. Ovchinnikova I. S., Seryakov P. S., Kobzeva N. A. On the problem of flooded impact (on the example of foreign publications). Molodoy ucheniy. 2015;11:550-552. (In Russ)

3. Cherepanov A. S., Druzhinina E. G. Spectral properties of vegetation and vegetation index. Geomatics. Available at: https://sovzond.ru (In Russ), (accessed 10.03.2020)

4. Kataev M. Yu., Bekerov A. A. Method of detecting water objects by multispectral satellite measurements. Doklady TUSURa. 2017;4(20):105-108. (In Russ)

5. Terekhov A. G., Kauazov A. M. Subsatellite MODIS-oriented analysis of the informativeness of vegetation indices in the problem of describing the state of spring wheat in Northern Kazakhstan. Sovremennyye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2007;2(4):352-357. (In Russ)

6. Arkhipkin O. P., Sagatdinova G. N. Use of polarimetric radar data in space monitoring of floods and floods. Sovremennyye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 2017;14(2):175-184. (In Russ)

7. Savvinov G. N. Features of the hydrothermal regime of permafrost chernozems and meadow-chernozem soils during autumn water-charging irrigation (on the example of the Amga River valley). Avtoreferat dis. … kan. biol. nauk. Akademiya nauk Respubliki Sakha (Yakutiya) institut prikladnoy ekologii Severa. 1997:21. (In Russ)

8. Alabyan A. M., Zelentsov V. A., Krylenko I. N., Potryasayev S. A., Sokolov B. V., Yusupov R. M. Rapid flood forecasting based on comprehensive proactive modeling and integration of heterogeneous data. Trudy SPIIRAN. 2015;4(41):5-33. Available at: www.proceedings.spiiras.nw.ru (In Russ)

9. Tananaev N. I., Efremova V. A., Gavrilyeva T. N., Parfenova O. T. Assessment of the community vulnerability to extreme spring floods: the case of the Amga River, central Yakutia, Siberia. Hydrology Research. 2020;52(1):125-141. Available at: https://iwaponline.com. DOI: 10.2166/nh.2020.124

10. Nikiforov S. L., Koshel S. M., Sorokhtin N. O., Kozlov N. E. Digital models of the bottom relief and some possibilities of their morphometric analysis. Vestnik MGTU. 2015;18(2):287-294. (In Russ)