PROBABILISTIC SEISMIC HAZARD ASSESSMENT FOR THE TRANH RIVER HYDROPOWER PLANT NO2 SITE, QUANG NAM PROVINCE

In this paper, the results of probabilistic seismic hazard assessment (PSHA) for the Tranh river hydropower plant No2 site, Quang Nam province, are presented. A regional earthquake catalog updated until 2014 and most recent data on active faulting in the area with a radial extent of 100 km from the HPP site were used. Applied modern techniques in the PSHA methodology including logic tree and hazard disaggregation allow to adopt different models of seismicity, seismic sources and ground motions for the study area. A set of the probabilistic seismic hazard maps showing distribution of the median peak ground acceleration (PGA) and intensity I (according to the MSK-64 scale) predicted for the periods of approximately 200, 500, 1000 and 10.000 years, respectively was compiled for the region. For the HPP site, the calculated hazard is presented in terms of the hazard curves and the seismic hazard disaggregation graphics at the site. For the 500 year period, maximum shaking in the area with a radial extent of 100 km from the HPP site reaches the level VIII-IX of the MSK-64 scale (in the Tam Ky-Phuoc Son fault zone). At the HPP site, the maximum PGA value ranges between 0.1g and 0.13 g (VII-VIII levels in the MSK-64 scale). The PGA maps present both short - term and long - term forecasts of seismic hazard in Quang Nam province. Calculated shakings at the HPP’s site can be used for seismic safety evaluation and antiseismic design for the HPP’s facilities during its operational time. References Budnitz, R.J., Apostolakis G., Boore D. M., Cluff L. S., Coppersmith K. J., Cornell C. A., Morris P. A., 1997. Recommendation for Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and Use of Experts. NUREG/CR-6732, 1. Cornell, C.A., 1968. Engineering Seismic Risk Analysis, Bull. Seim. Soc. Am., 58, 1583-1606. Crowley, H., D. Monelli, M. Pagani, V. Silva, G. Weatherill, 2011. OpenQuake Book. The GEM Foundation, Pavia, Italy. Esteva, L., 1968. Bases para la formulacion de decisiones de diseno sismico. PhD thesis, Universidad Autonoma Nacional de Mexico. Gumbel, E. J., 1958. Statistics of Extremes, Columbia University Press. Nguyen Hong Phuong (Editor), 2013. Assessment of earthquake and tsunami hazards in the Ninh Thuan province for site approval of the NPPs”.  Final report of the 2013 National Scentific Research Project, Institute of Geophysics, Hanoi, 2013 (in Vietnamese). Nguyen Hong Phuong , Que Cong Bui, Xuyen Dinh Nguyen, 2012. Investigation of tsunami sources, capable of affecting the Vietnamese coast. Natural Hazards, 64(1), 311-327. DOI: 10.1007/s11069-012-0240-3, Nguyen Hong Phuong, 2004. Seismic Hazard Maps of Vietnam and the East Vietnam Sea. Journal of Earth’s Sciences, 26(2), 97-111, 2004 (in Vietnamese). Nguyen Hong Phuong, Bui Cong Que, Vu Ha Phuong and Pham The Truyen, 2014. Scenario-based Tsunami Hazard Assessment for the coast of Vietnam from the Manila Trench source. Physics of the Earth and Planetary Interiors. DOI: 10.1016/j.pepi.2014.07.003. Nguyen Hong Phuong, Pham The Truyen, 2015. Probabilistic Seismic Hazard Maps of Vietnam and the East Vietnam Sea. Journal of Marine Science and Technology, 15(1), 77-90. DOI: 10.15625/1859-3097/15/1/6083 (in Vietnamese). Nguyen Ngoc Thuy et al., 2003. Assessment of seismic hazard for the Tranh River hydropower plant No2. A pre-feasebility report, Institute of Geophysics, Hanoi, October 2003, 75 p. (in Vietnamese). Nguyen, L. M., et al, 2012. The first peak ground motion attenuation relationships for North of Vietnam, Journal of Asian Earth Sciences, doi: 10.1016/j.jseaes.2011.09.012. OYO corporation, 2013. Research, Detailed Review of Geological Condition, Geodynamics and Geological Activities in Song Tranh 2 Hydropower Area (Bac Tra My District, Quang Nam Province). Draft Final Report No.: 01/2013/SACQI-OYO,  101 pp. Pacific Earthquake Engineering Research Center, 2008. NGA model for average horizontal component of peak ground motion and response spectra. Earthquake Spectra, 24(1), Petersen Mark D., James Dewey, Stephan Hartzell, Charles Mueller, Stephan Harmsen, Arthur D. Frankel, Ken Rukstales, 2004. Probabilistic seismic hazard analysis for Sumatra, Indonesia and across the Southern Malaysian Peninsula. Tectonophysics, 390, 141-158. Toro, G. R., 2002. modification of the Toro et al. (1997) attenuation equations for large magnitudes and short distances. Risk Engineering Incl., June. Toro, G. R., Abrahamson, N. A., and Schneider, J. F., 1997. Engineering model of strong ground motions from earthquakes in the central and eastern United States. Seismological Research Letters, 68(1): 41-57. Tran Viet Hung and Kiyomiya, O., 2012. Ground motion attenuation relationship for shallow strike-slip earthquakes in northern Vietnam based on strong motion records from Japan, Vietnam and adjacent regions, Structural Eng./Earthquake Eng., JSCE, 29, 23-39. Vu Van Chinh (Editor), 2015. Study and detailed evaluation of the regional seismotectonic characteristics and their impact to the stability of the Tranh River hydropower plant No2 and Northern Tra My area, Quang Nam province. A Thematic report of the 2013 National Scentific Research Project ” Study of the seismotectonic impact to the stability of the Tranh River hydropower plant No2 in Northern Tra My area, Quang Nam province”, Institute of Geophysics, Hanoi, 2015 (in Vietnamese). Wieland M., 2010. Selecting seismic parameters for large dames - Guidelines. ICOLD Bulletin 72, 2010 Revision

Development of a Web-GIS based Decision Support System for earthquake warning service in Vietnam

This paper describes the development of a Decision support system (DSS) for earthquake warning service in Vietnam using Web GIS technology. The system consists of two main components: (1) an on-line database of earthquakes recorded from the national seismic network of Vietnam, and (2) a set of tools for rapid seismic hazard assessment. Using an online earthquake database, the system allows creating a shake map caused by a newly recorded earthquake. In addition, the Web GIS environment allows any user, including non-professional to get useful information about a just-occurred event and the possible impact caused by the earthquake shortly after its occurrence. A fault-source model developed for Vietnam was used as a part of the hazard calculation and mapping procedure. All information and results obtained from the system are automatically included in the earthquake bulletins, which will be disseminated national wide afterward by the Vietnam earthquake information and tsunami warning Center.The shake maps produced by the DSS in terms of both Peak Ground Acceleration and intensity values are rapidly available via the Web and can be used for emergency response, public information, loss estimation, earthquake planning, and post-earthquake engineering and scientific analyses. Application of the online decision support system in earthquake warning service can mitigate the earthquake risk and reduce the losses and damages due to earthquakes in Vietnam in future.ReferencesBoore D.M., Joyner W.B. and Fumal T.E., 1994. Estimation of Response Spectra and Peak Acceleration from Wester North American earthquakes: an interim report, USGS open file report, 94-127, Menlo Park, California, United States Geological Survey.Boore D.M. and Atkinson G.M., 2008. Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods between 0.01 s and 10.0 s. Earthquake Spectra, 24(1), 1-341.Bui Van Duan, Nguyen Anh Duong, 2017.  The relation between fault movement potential and seismic activity of major faults in Northwestern Vietnam. Vietnam J. Earth Sci., 39, 240-255.Campbell K.W. and Bozorgnia Y., 1994. Near-Source Attenuation of Peak Horizontal Acceleration from Worldwide Accelerograms Recorded from 1957 to 1993, Proceedings, Fifth U.S. National Conference on Earthquake Engineering, Chicago, Illinois, July 10-14: V(III), 283-292.Campbell K.W. and Bozorgnia Y., 2008. NGA Ground Motion Model for the Geometric Mean Horizontal Component of PGA, PGV, PGD and 5% Damped Linear Elastic Response Spectra for Periods Ranging from 0.01 to 10s. Earthquake Spectra, 24(1), 1-341.Cauzzi C., Edwards B., Fäh D., Clinton J., Wiemer S., Kastli F., Cua G. and Giardini D., 2014. On the customisation of shakemap for optimised use in Switzerland, 2014. Proceedings of the 2nd European Conference on Earthquake Engineering and Seismology, Istanbul, August 25-29, 1-10.Center for International Earth Science Information Network - CIESIN - Columbia University, 2016. Documentation for the Gridded Population of the World, Version 4 (GPWv4). Palisades NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4D50JX4 Accessed April 2018.Chiou B.S.-J. and Youngs R.R., 2008. An NGA Model for the Average Horizontal Component of Peak Ground Motion and Response Spectra. Earthquake Spectra, 24(1), 1-341.Cornell, C.A., 1968. Engineering seismic risk analysis. Bull. Seis. Soc. Amer., 58(5), 1583-1606.Der Kiureghian and A. S-H. Ang, 1977. A fault rupture model for seismic risk analysis, Bull. Seim. Soc. Am., 67(4), 233-241.Douglas B.M. and Ryall A., 1977. Seismic risk in linear source regions, with application to the San Adreas fault, Bull. Seis. Soc. Amer., 67, 729-754.Marreiros, C. and Carrilho, F., 2012. The ShakeMap at the Instituto de Meteorologia. The proceedings of the 15th World Conference on Earthquake Engineering, Lisbon, Portugal September 24-28.Nguyen Le Minh, et al., 2012. The first peak ground motion attenuation relationships for North of Vietnam. Journal of Asian Earth Sciences. Doi: 10.1016/j.jseaes.2011.09.012.Nguyen Dinh Xuyen and Tran Thi My Thanh, 1999. To find a formula for computing ground acceleration in strong earthquake in Vietnam, J. Sci. of the Earth, 21, 207-213 (in Vietnamese).Pacific Earthquake Engineering Research Center, 2008. NGA model for average horizontal component of peak ground motion and response spectra. Earthquake Spectra, 24(1), 1-341.Tran V.H. and Kiyomiya O., 2012. Ground motion attenuation relationship for shallow strike-slip earthquakes in northern Vietnam based on strong motion records from Japan, Vietnam and adjacent regions, Structural Eng./Earthquake Eng., JSCE, 29, 23-39.Toro G.R., Abrahamson N.A. and Schneider J.F., 1997. Engineering Model of Strong Ground Motions from Earthquakes in the Central and Eastern United States, Seismological Research Letters, January/February.Wald D.J., Worden B.C., Quitoriano V. and Pankow K.L., 2006. ShakeMap Manual. Technical manual, users guide, and software guide.Wald D.L., Wald B. Worden and Goltz J., 2003. ShakeMap - a tool for earthquake response. U.S. Geological Survey Fact Sheet 087-03.Wells D.L. and Coppersmith K.J., 1994. New Empirical Relationships Among Magnitude, Rupture Length, Rupture Width, and Surface Displacement, Bulletin of the Seismological Society of America, 84, 974-1002.

Assessment of earthquake-induced liquefaction hazard in urban areas of Hanoi city using LPI-based method

Liquefaction Potential Index (LPI) is used as an assessing tool of liquefaction potential. In this study, the LPI-based method was applied to evaluate the earthquake-induced liquefaction potential for the urban area of Hanoi city. The data used includes 120 boreholes logs, containing necessary geomechanical information such as fine contents, specific gravity, dry density, porosity, N (SPT) values and the groundwater depth Z(w) of subsoil layers in every borehole. The “simplified procedure” proposed by Seed and Idriss was applied to evaluate the liquefaction of all subsoil layers in each borehole point. Then, the Liquefaction Potential Index was calculated for the whole soil column at al boreholes points using the method proposed by Iwasaki. Finally, the obtained LPI values were used to assess the liquefaction probability for an urban area of Hanoi city, using the empirical formula proposed by Papathanassiou and two earthquake scenarios originated on the Chay river fault with magnitudes of 5.3 and 6.5, respectively.For entire study area, the first scenario earthquake (Mw=5.3) is not capable of causing liquefaction (PG0.1). This means that the downtown area of Hanoi city is non-liquefiable to the medium magnitude events. Results of the second scenario (Mw=6.5) show in worst cases, an earthquake with magnitude, maximum expected for Hanoi region can produce liquefaction throughout the downtown area of Hanoi city. The highest liquefaction probability of 0.7PG≤0.9 is distributed in two large areas, where the first one is observed in Thanh Tri district, eastern part of Ha Dong, a smaller areas of the Thanh Xuan, Tu Liem and Cau Giay districts, while the second area covers Hoan Kiem district, a northern part of Hai Ba Trung district and northwestern part of Long Bien district.This is the first time the LPI based method was applied for evaluation of earthquake-induced liquefaction for Hanoi city. The most advantage of the method is that it can be easy to use, although the reliability of the results depends very much on number and distribution of the borehole data. Nevertheless, the combination of this method with other available methods can help effectively solving the problem of urban seismic risk assessment for the mega-cities in Vietnam.References Bui Cong Que, 1983. The new results in study of the crustal Structure for the territory of Vietnam. J. Sci. of the Earth, 5(1), 17-24 (in Vietnamese).Bui Van Duan, Nguyen Cong Thang, Nguyen Van Vuong, Phạm Dinh Nguyen, 2013. The magnitude of the largest possible earthquake in the Muong La- Bac Yen fault zone. J. Sci. of the Earth, 35, 49-53 (in Vietnamese).Day R.W., 2002. Geotechnical Earthquake engineering Handbook. McGRaw-Hill New York Chicago San Francisco Lisbon London Madrid Mexico City Milan New Delhi San Juan Seoul Singapore Sydney Toronro. Printed and bound by R.R. Donnelley Sons Company.Dixit J., Dewaikar D.M.and Jangid R.S., 2012. Assesment of liquefaction potential index for Mumbai city. Nat. Hazards Earth Syst. Sci., 12, 2759-2768.Federal Emergency Management Agency, 1999. NEHRP recommended Provisions for Seismic Regulations for New Buildings, Washington, D. C., Developed by the Building Seismic Safety Council (BSSC) for the Federal Emergency Management Agency (FEMA).Gillins D.T., 2016. Probabilistic Liquefaction Potential and Lateral Spread Hazard Maps for Utah County, Utah: Collaborative Research with Brigham Young University and Oregon State University. USGS Award Numbers: G14AP00118 G14AP00119.Term of Award: 08/01/2014 - 01/31/2016.Tran Dinh Hoa and Bui Manh Duy, 2013. Earthquake-induced liquefaction foudation and the methods of assessment for liquefaction foundation for Kinh Lo barrier Ho Chi Minh City. Journal of Water Resources Science and Technology, 15(4), 21-29.Ishihara K., 1985. Stability of natural deposits during earthquakes. Proceedings of the 11th International Conference on Soil Mechanics and Foundation Engineering, 1. A.A. Balkema, Rotterdam, The Nertherlands, 321-376.Iwasaki T., Tatsuoka F., Tokida K. and Yasuda S., 1978. A practicalmethod for assessing soil liquefaction potential based oncase studies at various sites in Japan, In Proceedings of the 2nd International Conference on Microzonation for Safer Construction-Research and Application, San Francisco, Calif., 26 November-1 December. American Society of Civil Engineers, New York, 2, 885-896.Iwasaki T., Arakawa T. and Tokida K., 1982. Simplified proceduresfor assessing soil liquefaction during earthquakes. InProceedingsof the Conference on Soil Dynamics and EarthquakeEngineering, Southampton, UK, 13-15 July 1982. Balkema,Rotterdam, the Netherlands, 925-939.Kircher C.A., Whitman R.V., Holmes W.T., 2006. HAZUS earthquake loss estimation methods. Nat Hazards Rev, 7(2), 45-59.Kongar I., Rossetto T., Giovinazzi S., 2016. Evaluating Simplified Methods for Liquefaction Assessment for Loss Estimation. Nat. Hazards Earth Syst. Sci. Discuss. Doi:10.5194/nhess-2016-281.Li D.K., Juang C.H. and Andrus R.D., 2006. Liquefaction potentialindex: a critical assessment, Journal of GeoEngineering,Taiwan Geotechnical Society, 1(1), 11-24.Liu F., Li Z., Jiang M., Frattini P. and Crosta G., 2016. Quantitative - induced lateral spead hazard mapping. Engineering Geology, 207, 36-47. Doi: 10.1016/j.enggeo.2016.04.001.Mustafa Erdik, K. S˘es˘etyan, M.B. Demirciog˘lu, C. Zu¨lfikar, U. Hancılar, C. Tu¨zu¨n, and E. Harmandar., 2014. Rapid Earthquake Loss Assessment After Damaging Earthquakes. Perspectives on European Earthquake Engineering and Seismology, 1, 53-95.Nguyen Hong Phuong, 2000. An algorithm for seismic risk assessment in Vietnam using a GIS. J. Sci. of the Earth, 22(3), 210-222 (in Vietnamese).Nguyen Hong Phuong (Project Manager), 2002. Study of seismic risk of Hanoi city. Project code 01C-04/09-2001-2. Institute for Marine Geology and Geophysics, VAST.Nguyen Hong Phuong, 2003. Development of a DSS for seismic risk assessment and Loss reduction using GIS technology. Contributions of the Marine Geophysics and Geology, VII, 62-78 (in Vietnamese).Nguyen Hong Phuong (Project Manager), 2003. Study of seismic risk of Hanoi city. Final report of the National scientific research Project 01C-04/09-2001-2, Hanoi (in Vietnamese).Nguyen Hong Phuong (Project Manager), 2007.  Application of GIS technology to Development of a model for seismic risk analysis for Hanoi city. Final Report of Research Project, Institute for Marine Geology and Geophysics, VAST.Nguyen Hong Phuong, 2008. Assessment of earthquake risk for Ho Chi Minh city using GIS and mathematical models. Final Report of Research Project, Institute of Geophysics, VAST (in Vietnamese).Nguyen Hong Phuong, 2009. Integrated Spatial decision support Systems for Urban Emergencies (ISSUE), Final Report of Vietnam-French Research Project, Hanoi.Nguyen Huy Phuong (Project Manager), 2010.  Study on the phenomenon of coherent action and changes reliability of   Hanoi bottom land under the impact of dynamic load in order to improve the geotechnical information system for sustainable development and disaster prevention. Hanoi University of Mining and Geology.Nguyen Hong Phuong (Project Manager), 2014.  Estimation of Site Effects and Assessment of Urban Seismic Risk for Hanoi city. National Scientific Research Project Final report. Institute of Geophysics, VAST.Papathanassiou G., 2008. LPI-based approach for calibrating theseverity of liquefaction-induced failures and for assessing theprobability of liquefaction surface evidence. Engineering Geology, 96(1-2), 94-104. Doi:10.1016/j.enggeo.2007.10.005.Phan Trong Trinh, Hoang Quang Vinh, Leloup Philippe Hervé, Giuliani G., Vincent Garnier., Tapponnier P., 2004. Cenozoic deformation, thermodynamic evolution, slip mechanism of Red River shear zone and ruby formation. Science and Technics Publishing House, Hanoi, 5-72 (In Vietnamese with English abstract).Phan Trong Trinh, Ngo Van Liem, Nguyen Van Huong, Hoang Quang Vinh, Bui Van Thom, Bui Thi Thao, Mai Thanh Tan, Nguyen Hoang, 2012. Late Quaternary tectonics and seismotectonics along the Red River fault zone, North Vietnam. Earth-Science Reviews, 114, 224-235.Phan Trong Trinh, Hoang Quang Vinh, Nguyen Van Huong, Ngo Van Liem, 2013. Active fault segmentation and seismic hazard in Hoa Binh reservoir, Vietnam. Cent. Eur. J. Geosci., 5(2), 223-235.Jaimes M.A, Niño M., Reinoso E., 2015. Regional map of earthquake-induced liquefaction hazard using the lateral spreading displacement index DLL, 77, 1595-1618.Juang C.H., et al., 2002. Assessing Probability-based Methodsfor Liquefaction Potential Evaluation. Journal of geotechnical and Geoenvironmental Engineering, 128(7), 580-589.Juang C.H., Yang S.H., Yuan H., Fang S.Y., 2005. Liquefaction inthe Chi-Chi earthquake: effect of fines and capping non-liquefiablelayers. Soils and Foundations, 45(6), 89-101.Juang C.H., Li D.K., 2007. Assessment of liquefaction hazards in Charleston quadrangle South Carolina. Engineering Geology, 92, 59-72. Doi:10.1016/j.enggeo.2007.03.003.Juang C.H., Chang Y.O., Lu C.C., Luo Z., 2010. Probabilistic framework for assessing liquefactionhazard at a given site in a specified exposure timeusing standard penetration testing. Canadian Geotechnical Journal, 47(6), 674-687. https://doi.org/10.1139/T09-127.Seed H.B., and  Idriss I.M., 1971. Simplified procedure for evaluatingsoil liquefaction potential. Journal of the Soil Mechanics andFoundations Division, ASCE, 97(9), 1249-1273.Vu Thanh Tam (Project Manager), 2014. Study and propose a reasonable threshold for preventing the subsidence caused by ground water exploitation, pilot application for downtown area of the Hanoi city. Final report of the Scientific research and technology development Project, National Center for water resource planning and investigation. Ministry of Natural Resources and Environment.Nguyen Ngoc Thuy (Project manager), 2004. “Study, supplement and enhancement of the 1:25,000 scale seismic microzonning map of the expanded Hanoi city, development of the ground motion characteristics database in Hanoi in accordance with the map”. Final report of the scientific research project, The Hanoi Institute of Building Technology. Hanoi Construction Department.Whitman R.V., Anagnos T., Kircher C.A., Lagorio H.J., Lawson R.S., Schneider P., 1997. Development of a national earthquake loss estimation methodology. Earthquake Spectra, 13(4), 643-661.Nguyen Dinh Xuyen, 1987. Manifestation of strong earthquake activity in the territory of Vietnam, J. Sci. of the Earth, 9(2), 14-20 (in Vietnamese).Nguyen Dinh Xuyen, Nguyen Ngoc Thuy et al., 1996. Completion of the seismic microzoning map of 1:25 000 scale for Hanoi region. Final report of the City’s level project. Institute of Geophysics, Hanoi (in Vietnamese).Nguyen Dinh Xuyen (Project Manager) 2004. Final report of the National scientific research project on “Study of earthquake prediction and ground motion in Vietnam”, Institute of Geophysics, Hanoi (in Vietnamese).Youd T.L., Idriss I.M., Andrus R.D., Arango I., Castro G., Christian J.T., Dobry R., Finn W.D.L., Harder L.F., Hynes M.E., Ishihara K., Koester J.P., Liao S.S.C., Marcurson III W.F., Marti G.R.,Mitchell J.K., Moriwaki Y., Power M.S., Robertson P.K., Seed R.B., Stokoe II K.H., 2001. Liquefaction resistance of soils: summary report from the 1996 NCEER and 1998 NCEER/NSFworkshops on evaluation of liquefaction resistance of soils. Journalof Geotechnical and Geoenvironmental Engineering, ASCE, 127(10), 817-833.Yuan H., Yang S.H., Andrus R.D., Juang C.H., 2004. Liquefaction-inducedground failure: A study of the Chi-Chi earthquake cases. Engineering Geology, 71(1-2), 141-155

Probabilistic seismic hazard assessment for the South Central Vietnam

In this paper, the probabilistic seismic hazard maps for the South Central Vietnam are presented. An earthquakes catalog updated until 2014 and most recent seismotectonic and geodynamic information were used for delineation of 14seismic source zones in the study area. The Toro et al. (1997) attenuation equation was used for the PSHA. The hazard maps show distribution of the mean peak ground acceleration (PGA) with a 10%, 5%, 2% and 0.5% probability of exceedance in 50 years. The highest values of PGA are observed in the continental shelf of the South Central Vietnam, in the 1090 meridian source zone, where the maximum PGA values are 0.12, 0.15, 0.2 and 0.28 g corresponding to the return times of about 500, 1000, 2500 and 10 000 years, respectively. In addition, two seismic source zones that can produce strong ground shaking off-shore South Central coast are Cuu Long -Con Son and Thuan Hai -Minh Hai. For the time period of about 1000 years, the highest shaking intensity within these source zones reaches the value of VIII (I=VIII by MSK-64 scale).In the territory of South Central Vietnam, the strongest shaking are observed in the Quang Nam and Quang Ngai provinces, in the Hung Nhuong -Ta Vi seismic source zone. For the return times of about 500, 1000, 2500 and 10 000 years, the highest PGA values in this zone are  0.1, 0.12, 0.14 và 0.17 g, respectively.Strong ground shakings are also observed in some other seismic source zones as Tuy Hoa -Cu Chi, Hau river and Nha Trang -Tanh Linh.ThePGA maps present both short-term and long-term forecasts of seismic hazard in the South Central Vietnam and can be used as a reference for antiseismic design and many engineering applications.References Cornell, C. A., 1968: Engineering Seismic Risk Analysis, Bull. Seim. Soc. Am.,58, pp. 1583 - 1606. Department of Science and Technology of the Ho Chi Minh City, People Committee of Ho Chi Minh city, 2008: 1 Report of the 1st Stage of implementation of the Project “Seismic Microzoning of the Ho Chi Minh city”, Ho Chi Minh City (in Vietnamese). International Atomic Energy Agency, 2003: Site Evaluation for Nuclear Installations. IAEA Safety Standards Series No. NS-R-3, IAEA, Vienna. Institute of Energy, EVN, Ministry of Industry and Trade, 2003: Feasibility report of investment and construction of NPP in Ninh Thuan, Vol. 3, Appendix, Book 2/2 (in Vietnamese). Keilis-Borok, V.I., Knopoff, L., Rotwain, I.M., 1980: Burst of aftershocks, long-term precursors of strong earthquakes, Nature, Vol. 283, 259-263. L. T. Son et al., 2006: Investigation of the Phan Thiet - Vung Tau earthquake of November 8, 2005. Field trip report, Dept. of earthquake observation, Institute of Geophysics, Hanoi. McGuire, R.K., 1976: FORTRAN computer program for seismic risk analysis, U.S. Geol. Survey Open - File Rept. 76-67, 89. N. K. Mao, 1974: Seismic zoning of South Vietnam. Bulletins of Universities. N. L. Minh et al, 2012: The first peak ground motion attenuation relationships for North of Vietnam, Journal of Asian Earth Sciences, doi: 10.1016/j.jseaes.2011.09.012. N. H. Phuong, 1991: Probabilistic Assessment of  Earthquake Hazard in Vietnam based on Seismotectonic Regionalization, Tectonophysics, 198, 81-93, Elsevier Publisher. N. H. Phuong, 1993: Probabilistic earthquake hazard assessment for the territory of Vietnam, Ph.D. thesis, Smith Institute of Physics of the Earth, Academy of Sciences of Russian Federation, Moscow (In Russian). N. H. Phuong, 1999: Investigation of the Relation between Seismicity and Elements of Geodynamics along the Southeastern Coast of Vietnam. Proceedings of the International Workshop on Tectonics, Geodynamics and Natural Hazards in West Pacific-Asia. Journal of Geology, Series B, No13-14/99, pp.179-193. N. H. Phuong, 2004: Probabilistic seismic hazard maps of Vietnam and the East Vietnam Sea. Vietnam Journal of Earth Sciences, 26(2), 97-111 (in Vietnamese). N. H. Phuong, 2010: Chapter V. Seismic hazard and seismic risk in the coastal zones and islands of Vietnam. In: B. C. Que (editor). “Earthquakes and tsunamis hazards in the coastal zones of Vietnam”, Natural Science and Technology Publ. House, Hanoi, 312 pp. (in Vietnamese). N. H. Phuong, B. C. Que, N. D. Xuyen, 2012: Investigation of tsunami sources, capable of affecting the Vietnamese coast. Natural Hazards, 64(1) pp 311-327. DOI: 10.1007/s11069-012-0240-3, October 2012. N. H. Phuong et al., 2014: Assessment of earthquake and tsunami hazards in the Ninh Thuan province for site approval of the NPPs. Final report of the National Scientific Research Project No 02-2012/HĐ-ĐTĐL, Hanoi. N. D. Xuyen et al., 1981: Additional earthquakes data from questionnaires. Field trip report on earthquakes during 1979 - 1981. Department of Physics of the Earth - Vietnam Institute of Sciences, Hanoi (in Vietnamese). N. D. Xuyen et al., 2004: Final report of the National scientific research project on “Study of earthquake prediction and ground motion in Vietnam. Final report of the National scientific research project on “Study of earthquake prediction and ground motion in Vietnam”, Institute of Geophysics, Hanoi, (in Vietnamese). Ordaz M., Aguilar A., Arboleda J. CRISISS99. University of Mexico (UNAM). Petersen, M. D. Dewey, J., Hartzell, S., Mueller, C., Harmsen, S., Frankel, A.D., Rukstales K., 2004: Probabilistic seismic hazard analysis for Sumatra, Indonesia and across the Southern Malaysian Peninsula. Tectonophysics,390 (2004) 141-158. T. V. Hung and Kiyomiya, O., 2012: Ground motion attenuation relationship for shallow strike-slip earthquakes in northern Vietnam based on strong motion records from Japan, Vietnam and adjacent regions, Structural Eng./Earthquake Eng., JSCE, 29: 23-39. P. V. Thuc, 2008: Relationship of earthquakes and volcanoes activities in the South Central Coast, Journal of Marine Science and Technology, No 2(8), Hanoi. Toro, G. R., Abrahamson, N. A. and Schneider, J. F., 1997: Engineering Model of Strong Ground Motions from Earthquakes in the Central and Eastern United States, Seismological Research Letters, January/February. V. M. Giang, 2000: Earthquakes and other natural disasters through the historical data.  Institute report, Institute of Geophysics.

Eksperymentalne i mezoskopowe badanie numeryczne sieci krystalicznej wzrostu współczynnika dyfuzyjności chlorków podczas jednoosiowego modelu obciążenia

This paper presents experimental and simulation results of the change in the chloride diffusion coefficient of concrete C40 (f’c=40 MPa) during axial loading. Test Method for Electrical Indication was used to measure the chloride diffusivity of the concrete sample during the axial loading. A mesoscopic lattice model is proposed to describe the variation of chloride diffusion coefficient versus damage variable. In such a model, the domain of material is discretized randomly by using Voronoi tessellation for the transport element and Delaunay triangulation for a mechanical element. At the mesoscale, the concrete is constituted by three phases: aggregate, cement paste and ITZ, in which aggregate is assumed to be elastic while cement matrix and ITZ are represented by a damage model with softening. The experimental and numerical results show that in the first stage, without crack (s < 40%smax), the chloride diffusion coefficient remains almost constant, however in the crack initiation and propagation stage (s = 60-80%smax) chloride diffusion coefficient increases significantly. An empirical power model is also proposed to describe the increase of the chloride diffusion coefficient versus stress level and damage variable.W artykule przedstawiono wyniki doświadczalne i symulacyjne zmiany współczynnika dyfuzji chlorków betonu C40 (f’c = 40 MPa) podczas obciążenia osiowego. Do pomiaru dyfuzyjności chlorków próbki betonu podczas obciążenia osiowego wykorzystano metodę badania wskazań elektrycznych. Zaproponowano mezoskopowy model sieci krystalicznej w celu opisania zmiany współczynnika dyfuzji chlorków w funkcji zmiennej uszkodzenia. W takim modelu domena materiału jest dyskretyzowana losowo przy użyciu teselacji Voronoia dla elementu transportowego i triangulacji Delaunaya dla elementu mechanicznego. W mezoskali beton składa się z trzech faz: kruszywa, zaczynu cementowego i ITZ, w których zakłada się, że kruszywo jest elastyczne, natomiast osnowa cementowa i ITZ są reprezentowane przez model uszkodzenia ze zmiękczeniem. Wyniki eksperymentalne i numeryczne pokazują, że w pierwszym etapie, bez pęknięcia ((σ<40%σmax), współczynnik dyfuzji chlorków pozostaje prawie stały, natomiast w fazie inicjacji i propagacji pęknięcia (σ=60-80% σmax) współczynnik dyfuzji chlorków znacznie wzrasta. Zaproponowano również empiryczny model mocy opisujący wzrost współczynnika dyfuzji chlorków w funkcji poziomu naprężenia i zmiennej uszkodzenia

Landslide susceptibility mapping at sin Ho, Lai Chau province, Vietnam using ensemble models based on fuzzy unordered rules induction algorithm

Landslide susceptibility map is considered as one of the important steps in assessing vulnerability of an area to landslide hazard. In this study, the main objective is to propose ensemble machine learning models: BF, DF and RSSF which are a combination of Fuzzy Unordered Rules Induction algorithm (F) and three optimization techniques namely Bagging, Decorate, and Random Subspace, respectively for landslide susceptibility mapping. In addition, two other single models namely F and Support Vector Machines (SVM) were also applied for the comparison of performance of the proposed models. For this purpose, the Sin Ho district, Lao Cai Province, Vietnam was selected as the study area. For the development of models, database of 850 present and historical landslides of this province including ten landslide affecting input parameters namely slope, curvature, elevation, aspect, Topographic Wetness Index (TWI), deep division, river density, fault density, aquifer, and geology were used. Validation of the models was done using various popular statistical indicators including Area Under the Receiver Operating Characteristics (AUC) curve. The results show that the BF model (AUC = 0.923) is the best model for accurate landslide susceptibility mapping (LSM) in comparison to other models namely DF (AUC = 0.899), RSSF (AUC = 0.893), SVM (AUC = 0.840), and F (AUC = 0.862). The study revealed that LSM map constructed using BF model can be used for better land use planning and proper landslide hazard management

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. FundingBill & Melinda Gates Foundation

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundEstimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.Methods22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsGlobal all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.InterpretationGlobal adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.</p