ASSESSMENT OF THE USSURI RIVER FLOOD REGIME CHANGES REGARDING TO CLIMATE PROJECTIONS TO THE END OF THE XXI CENTURY
Detecting reaction of river systems to climate changes is one of the key problems in modern hydrology. Moreover, this is the case of the Far East of Russia, where moisture regime variability is well known. The presented article deals with the assessment results of changes in the flood characteristics of the Ussuri rivers basins under the expected climate changes, linked with global warming. The estimates are based on dynamic–stochastic modeling scheme, in which numerous synthetic precipitation series are input to the hydrological model for searching of all kinds of humidification conditions at the investigated catchments. There was used a regional hydrological Flood Cycle Model of small river basin that focuses on the description of runoff formation processes in the summer–autumn flood period. Climate changes input is based on the integration of the regional stochastic rainfall model and General Circulation Models (GCM) data to the end of XXI century (2071–2100).
It is shown that an increase in precipitation sum leads to an unproportional response of the evaluated flood flow characteristics. The relative increase in the mean values of the maximum flow reaches 4–5 times and 2–3 times for the seasonal runoff depth depending on applied GCM and climate scenarios. The obtained results are consistent with the analysis of observational data using the “elasticity coefficient” and previous investigations. Therefore, flood risks could be expected at the investigated territory due to climate changes.
Bales R., Molotch N., Painter Th., Dettinger M., Rice R., Dozier J. Mountain hydrology of the western United States. Water Resources Re-search, 2006, vol. 42, iss. 8, W08432. DOI: 10.1029/2005WR004387
Belyakova P.A. Gartsman B.I. Possibilities of Flood Forecasting in the West Caucasian Rivers Based on FCM Model. Water Resources, 2018, vol. 45, suppl. 1, pp. 50-58. DOI: 10.1134/S0097807818050317
Bentsen M. et al. The Norwegian Earth system model, NorESM1-M - Part 1: Description and basic evaluation of the physical climate. Geoscien-tific Model Development, 2013, vol. 6, pp. 687-720. DOI: 10.5194/gmdd-5-2843-2012
Chen N.Ch. Lee K.T. Gartsman B.I. Application of Flood Cycle Model for daily flow simulating in different climate area. Taiwan Water Conservan-cy, 2008, vol. 56, no 2, pp. 1-13.
Dufresne J.-L. et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Climate Dynamics, 2013, vol. 40, iss. 9-10, pp. 2123-2165. DOI: 10.1007/s00382-012-1636-1
Dunne J. et al. GFDL’s ESM2 Global Coupled Climate-Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics. Journal of Climate, 2012, vol. 25, no. 19, pp. 6646-6665. DOI: 10.1175/JCLI-D-11-00560.1
Gartsman B.I. Dozhdevye navodneniya na rekah Dalnego Vostoka: metody raschetov, prognozov, otsenki riska [Rainfall Floods in the Rivers of the Far East: Calculation, Forecasting, and Risk As-sessment Methods]. Vladivostok: Publ. Dalnauka, 2008. 421 p. (In Russian)
Gartsman B.I. Gubareva T.S. Prognoz gidrografa dozhdevyh pavodkov na rekah Dal'nego Vostoka [Forecast of the rainfall flood hydrograph on the Far East rivers] // Meteorologija i gidrologija [Me-teorology and hydrology (Russia)], 2007, no. 5, p. 70-80. (In Russian; abstract in English)
Gartsman B.I. Lupakov S.Yu. Effect of climate changes on the maximal runoff in the Amur Basin: Estimation based on dynamic-stochastic simula-tion. Water Resources, 2017, vol. 44, iss. 5, pp. 697-706. DOI: 10.1134/S0097807817050062
Gartsman B.I. Lupakov S.Yu. Changes in the maximum runoff regime in the Ussuri River basin: the methodological aspects of forecasting based on dynamic-stochastic simulation. Water Re-sources, 2018, vol. 45, suppl. 1, pp. S79-S89. DOI: 10.1134/S0097807818050342
Gartsman I.N. Lylo V.M. Chernenko V.G. Pa-vodochnyj stok rek Dal'nego Vostoka [Flood flow of the Far Eastern rivers]. Leningrad, Publ. Gidrometeoizdat, 1971. 264 p. (In Russian)
Gelfan A.N. Dinamiko-stohasticheskoye mod-elirovaniye formirovaniya talogo stoka [Dynam-ic—Stochastic Simulation of Snowmelt Runoff Formation]. Moscow: Publ. of Institute of Water Problems RAS, 2007. 294 p. (In Russian)
Gelfan A.N. Moreydo V.M. Opisanie makromasshtabnoj struktury polja snezhnogo pokrova ravninnoj territorii s pomoshh'ju dina-miko-stohasticheskoj modeli ego formirovanija [Describing macro-scale structure of the snow cover by a dynamic-stochastic model]. Led i sneg [Ice and snow (Russia)], 2015, vol. 55, no. 4, pp. 61-72. (In Russian; abstract in English)
IPCC: Climate Change 2013: The Physical Sci-ence Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovern-mental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge, United Kingdom and New York, Cambridge University Press, 2013. 1535 p.
Jones C.D. et al. The HadGEM2-ES implementa-tion of CMIP5 centennial simulations. Geoscien-tific Model Development, 2011, vol. 4, iss. 3, pp. 543-570. DOI: 10.5194/gmd-4-543-2011
Oudin L., Hervieu F., Michel C., Perrin C., An-dreassian V., Anctil F., Loumagne C. Which po-tential evapotranspiration input for a lumped rain-fall-runoff model? Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling. Jornal of Hydrology, 2005a, vol. 303, no. 1-4. pp. 290-306. DOI: 10.1016/j.jhydrol.2004.08.026
Oudin L. Michel C. Anctil F. Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 1 - Can rainfall-runoff models effectively handle detailed potential evapotranspi-ration inputs? Jornal of Hydrology, 2005b, vol. 303, no. 1-4, pp. 275-289. DOI: 10.1016/j.jhydrol.2004.08.025
Sankarasubramanian A., Vogel R.M., Limbrunner J.F. Climate elasticity of streamflow in the United States. Water Resources Research, 2001, vol. 37, iss. 6, pp. 1771-1781. DOI: 10.1029/2000WR900330
Trzaska S. Schnarr E. A review of downscaling methods for climate change projections (Technical report, United States Agency for International De-velopment). Burlington, Vermont, Tetra Tech ARD, 2014. 56 p.
van Vuuren D.P. et al. The representative concen-tration pathways: an overview. Climatic Change, 2011, vol. 109, pp. 5-31. DOI: 10.1007/s10584-011-0148-z
Vinogradov Yu.B. Matematicheskoye modeliro-vaniye protsessov formirovaniya stoka [Mathemat-ical Modeling of River Runoff Formation Process-es]. Leningrad, Publ. Gidrometeoizdat, 1988. 311 p. (In Russian)
Warszawski L., Frieler K., Huber V., Piontek F., Serdeczny O., Schewe J. The Inter-Sectoral Im-pact Model Intercomparison Project (ISI-MIP): project framework. Proceedings of the National Academy of Sciences, 2014, vol. 111, iss. 9, pp. 3228-3232. DOI: 10.1073/pnas.1312330110.
Watanabe S. et al. MIROC-ESM 2010: model description and basic results of CMIP5 experi-ments. Geoscientific Model Development, 2011, vol. 4, pp. 845-872. DOI: 10.5194/gmdd-4-1063-2011
Wu Y., Zhang G., Shen H., Jun Xu Y. Nonlinear Response of Streamflow to Climate Change in High-Latitude Regions: A Case Study in Head-waters of Nenjiang River Basin in China’s Far Northeast. Water, 2018, vol. 10, no. 3, pp. 294-311. DOI: 10.3390/w10030294
Zhang A., Liu W., Yin Zh., Fu G., Zheng Ch. How will climate change affect the water availa-bility in the Heihe River basin, northwest China? Journal of Hydrometeorology, 2016, vol. 17, no. 5, pp. 1517-1542. DOI: 10.1175/JHM-D-15-0058.1
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract views: 36 PDF Downloads: 15