Comparison of methods for determining the layer of daily precitation for calculation of the maximum expenses of rain floods (on the example of the Kaliningrad region)

Introduction. To prepare territorial planning documents, during design and construction it is necessary to take into account the requirements for organizing a safe living environment, assess the risks of negative impact of surface waters, including the possibility of flooding of the development area. For this purpose, engineering and hydrometeorological surveys are carried out, the maximum estimated flow rates and water levels in the nearest water bodies are determined. When performing hydrological calculations, an important role is given to quantitative indicators of precipitation, including maximum daily precipitation. The article considers a method of increasing the accuracy of modelling the maximum daily rainfall on the example of meteorological stations in the Kaliningrad region.

Materials and methods. Data arrays of the results of precipitation observations at four weather stations — Sovetsk (26614), Baltiysk (26701), Kaliningrad (26702), Zheleznodorozhny (26706) were processed in Mathcad. The main source of observational results is specialized datasets for climate research for the period from 1977 to 2021.

Results. A significant stochastic relationship between the annual precipitation amounts for the indicated meteorological stations and a weak one between the maximum values of 24-hour precipitation amounts for the year were determined. Numerical parameters of the series of maximum precipitation amounts at four meteorological stations in the Kaliningrad region for 1977–2021 years are calculated. The relative excess of the values of the maximum 24-hour precipitation over the values of the maximum daily amounts at the weather stations Sovetsk, Baltiysk, Kaliningrad, Zheleznodorozhny was calculated.

Conclusions. It has been established that with the help of 8-term observations of precipitation, it is possible to increase the accuracy of calculation of the maximum amounts of daily (24-hour) precipitation. The results obtained can be used in the analysis of precipitation and calculation of the maximum discharges of rain floods on rivers with a catchment area of less than 200 km2.

1. Gelfan A.N., Gusev E.M., Kalugin A.S., Krylenko I.N., Motovilov Y.G., Nasonova O.N. et al. Runoff of Russian rivers under current and projected climate change: A review 2. Climate change impact on the water regime of Russian rivers in the XXI century. Water Resources. 2022; 49(3):270-285. DOI: 10.31857/S0321059622030051. EDN FBYFJJ. (rus.).

2. Bormann H., Diekkruger B. Possibilities and limitations of regional hydrological models applied within an environmental change study in Benin (West Africa). Physics and Chemistry of the Earth, Parts A/B/C. 2003; 28(33-36):1323-1332. DOI: 10.1016/ j.pce.2003.09.008

3. Golian S., Murphy C., Meresa H. Regionalization of hydrological models for flow estimation in ungauged catchments in Ireland. Journal of Hydrology: Regional Studies. 2021; 36:100859. DOI: 10.1016/ j.ejrh.2021.100859

4. Horton P., Schaefli B., Kauzlaric M. Why do we have so many different hydrological models? A review based on the case of Switzerland. WIREs Water. 2022; 9(1). DOI: 10.1002/wat2.1574

5. Jiang C., Parteli E.J.R., Xia Q., Yin X., Shao Y. A regional hydrological model for arid and semi-arid river basins with consideration of irrigation. Environmental Modelling & Software. 2022; 157:105531. DOI: 10.1016/j.envsoft.2022.105531

6. Naumov V.A., Nelyubina E.A. Interannual variability of elements of the water balance of the basin of the transboundary river Angrapa. Environmental Engineering. 2022; 3:95-100. DOI: 10.26897/1997-6011-2022-3-95-100. EDN ACBMSN. (rus.).

7. Naumov V.A. Maximum annual water discharges of small rivers in Slavsky district Kaliningrad region. Land Reclamation and Hydraulic Engineering. 2022; 12(4). DOI: 10.31774/2712-9357-2022-12-4-367-383. EDN HQBZOW. (rus.).

8. Klimenko D.E., Korepanov E.P. Mapping of daily layer precipitation security P = 1 % for territories activity Urals management of hydrometeorology at calculations of the drain rain high waters for the formula of limiting intensity. Geographical Bulletin. 2012; 3(22):54-63. (rus.).

9. Klimenko D.E., Cherepanova E.S., Kuz’-minykh A.Y. Evaluating parameters of the distributions of extreme storms with several events per year taken into account. Water Resources. 2019; 46(4):438-446. DOI: 10.31857/S0321-0596464438-446. EDN ONRVGP. (rus.).

10. Coles S., Pericchi L.R., Sisson S. A fully probabilistic approach to extreme rainfall modeling. Journal of Hydrology. 2003; 273(1-4):35-50. DOI: 10.1016/s0022-1694(02)00353-0

11. De Michele C. Advances in deriving the exact distribution of maximum annual daily precipitation. Water. 2019; 11(11):2322. DOI: 10.3390/w11112322

12. Ma H.-Y., Klein S.A., Lee J., Ahn M.-S., Tao C., Gleckler P.J. Superior daily and sub-daily precipitation statistics for intense and long-lived storms in global storm-resolving models. Geophysical Research Letters. 2022; 49(8). DOI: 10.1029/2021GL096759

13. Miró J.J., Lemus-Canovas M., Serrano-Notivoli R., Cantos J.O., Estrela M.J., Martin-Vide J. et al. A component-based approximation for trend detection of intense rainfall in the Spanish Mediterranean coast. Weather and Climate Extremes. 2022; 38:100513. DOI: 10.1016/j.wace.2022.100513

14. Morales J., García-Barrón L., Aguilar-Alba M., Sousa A. Hazard characterization of the annual maximum daily precipitation in the southwestern Iberian peninsula (1851–2021). Water. 2022; 14(9):1504. DOI: 10.3390/w14091504

15. Palagin E.D., Strelkov A.K., Pavluhin A.A. Rain precipitation parameters for the design of surface effluent treatment facilities from the territory of industrial enterprises. IOP Conference Series: Earth and Environmental Science. 2021; 720(1):012021. DOI: 10.1088/1755-1315/720/1/012021

16. Papalexiou S.M., Koutsoyiannis D. Battle of extreme value distributions: A global survey on extreme daily rainfall. Water Resources Research. 2013; 49(1):187-201. DOI: 10.1029/2012wr012557

17. Veneziano D., Langousis A., Lepore C. New asymptotic and preasymptotic results on rainfall maxima from multifractal theory. Water Resources Research. 2009; 45(11). DOI: 10.1029/2009wr008257

18. Naumov V.A. Using specialized data sets for climate research. Bulletin of the Scientific and Methodological Council for Environmental Engineering and Water Use. 2020; (18):52-59. EDN DMCZOE. (rus.).

19. Barinova G.M. Kaliningrad region. Climate. Kaliningrad, Amber Tale, 2002; 194. (rus.).

20. Rozhdestvensky A.V., Chebotarev A.I. Statistical Methods in Hydrology. Leningrad, Gidrometeoizdat, 2009; 424. (rus.).

21. Sikan A.V. Methods of statistical processing of hydrometeorological information. St. Petersburg, Publishing House of the Russian State Humanitarian University, 2007; 279. (rus.).