Probabilistic models of water resources management on urbanized areas
DOI:
https://doi.org/10.17721/1812-5409.2020/4.3Keywords:
water quality, global climate change, mathematical modeling, probabilistic modelsAbstract
Gradual global climate change poses new challenges to the mathematical sciences, which are related to forecasting of meteorological conditions, preparing the infrastructure for possible rains, storms, droughts, and other climatic disasters. One of the most common approaches is synthetic regression-probability models, which use the spatio-temporal probability density functions of precipitation level. This approach is applied to the statistics of precipitation in the Kharkiv region, which shows the tendency to a gradual increase in air temperature, high indices of basic water stress, indices of drought and riverside flood threats. Open data on temperature distributions and precipitation were processed using various probability statistics. It is shown that the lognormal distribution most accurately describes the measurement data and allows making more accurate prognoses. Estimates of drought and flood probabilities in Kharkiv region under different scenarios of climate change dynamics have been carried out. The results of the study can be used for management of water resources on urban territories at global climate warming.
Pages of the article in the issue: 22 - 27
Language of the article: Ukrainian
References
Causes, Impacts and Solutions to Global Warming (2013) / I. DINCER, C.O. COLPAN, F. KADIOGLU (eds.), Springer.
KIZILOVA N.N., RYCHAK N.L., CHEBUKIN D.S., LUKIJENKO M.V. (2020) Ecological assessment of surface water quality in the rainless period in the conditions of urban catchment. Visnyk of V.N. Karazin Kharkov National University, Ser. «Geology. Geography. Ecology». Vol. 53. p.
KIZILOVA N.N., RYCHAK N.L., RUDNEV Y.I. (2019) The system dynamics approach to water quality control in urban areas. Systems of information treatment. Vol. 4(159). p.87–92. doi:10.30748/soi.2019.159.10
MAMMAN M.J., MARTINS O.Y., IBRAHIM J., SHABA M.I. (2017) Evaluation of Best-Fit Probability Distribution Models for the Prediction of Inflows of Kainji Reservoir, Niger State, Nigeria. Air, Soil and Water Research. Vol.10. Р. 1–7 doi:201710.1177/1178
LANGAT P.K., KUMAR L., KOECH R. (2019) Identification of the Most Suitable Probability Distribution Models for Maximum, Minimum, and Mean Streamflow. Water. Vol. 11. p. 734-741. doi:10.3390/w11040734
SORDO-WARD Á., GRANADOS I., MARTÍN-CARRASCO F., GARROTE L. (2016) Impact of Hydrological Uncertainty on Water Management Decisions. Water Resourses Management. Vol. 30(14). p. 323-339. doi:10.1007/s11269-016-1505-5
BALABUKH V., LAVRYNENKO O., BILANIUK V., et al. Extreme Weather Events in Ukraine: Occurrence and Change. / P.J. Sallis, ed. Intech Open, 2018. – 228 p. doi:10.5772/intechopen.77306
BULDYGIN V.V., KOZACHENKO Y.V. (1998) Metric characteristics of random variables and processes, К.: ТВіМС. 290 p.
NATHAN R., JORDAN P., SCORAH M., et al. (2016) Estimating the exceedance probability of extreme rainfalls up to the probable maximum precipitation. Journal of Hydrology. Vol. 543. p. 706–720. doi: 10.1016/j.jhydrol. 2016.10.044
FOUFOULA-GEORGIOU E. A. (1989) probabilistic storm transposition for estimating exceedance probabilities of extreme precipitation depths. Water Resourses Research. Vol. 25(5). p. 799–815. doi: 10.1029/WR025i005p00799
SCHAEFER M.G. (1990) Regional analysis of precipitation annual maxima in Washington State. Water Resourses Research. Vol. 26. p. 119–131. doi: 10.1029/WR026i001p
YEVJEVICH V. (1984) Probability and Statistics in Hydrology. Water resources Publ., Colorado, USA. 312 p.
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