Global-scale analysis on future changes in flow regimes using Gini and Lorenz asymmetry coefficients

Water Resources Research

Volumn 50, Issue 5, 2014, Pages 4054-4078

  Masaki, Yoshimitsu ^a   Hanasaki, Naota ^a   Takahashi, Kiyoshi ^a   Hijioka, Yasuaki ^a  

^a NATIONAL INSTITUTE FOR ENVIRONMENTAL STUDIES   (Japan)

Author keywords

climate change; Gini coefficient; Lorenz asymmetry coefficient; river discharge; seasonal inequality

Indexed keywords

CLIMATE MODELS; RIVERS;

FUTURE CLIMATE SCENARIOS; GENERAL CIRCULATION MODEL; GINI COEFFICIENTS; LORENZ ASYMMETRY COEFFICIENT; PICTORIAL REPRESENTATION; RIVER DISCHARGE; SEASONAL INEQUALITY; STATISTICAL CHARACTERISTICS;

CLIMATE CHANGE;

ASYMMETRY; CLIMATE CHANGE; CLIMATE EFFECT; DISCHARGE; FLOW PATTERN; GENERAL CIRCULATION MODEL; GLOBAL CHANGE; HYDROLOGICAL MODELING; RIVER FLOW; SIMULATION;

EID: 84900970243     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2013WR014266     Document Type: Article

References (47)

1. Arnell, N. W., (2004), Climate change and global water resources: SRES emissions and socio-economic scenarios, Global Environ. Change, 14, 31-52, doi: 10.1016/j.gloenvcha.2003.10.006. (Pubitemid 38215126)
2. Arnell, N. W., and, S. N. Gosling, (2013), The impacts of climate change on river flow regimes at the global scale, J. Hydrol., 486, 351-364.
3. Arora, V. K., and, G. J. Boer, (2001), Effects of simulated climate change on the hydrology of major river basins, J. Geophys. Res., 106 (D4), 3335-3348.
4. Center for International Earth Science Information Network (CIESIN) and Centro Internacional de Agricultura Tropical (CIAT) (2005), Gridded Population of the World, Version 3. [Available at http://sedac.ciesin.columbia.edu/gpw/ index.jsp.]
5. Christensen, J. H., et al. (2007), Regional climate projections, in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by, S. Solomon, et al., pp. 847-940, Cambridge Univ. Press, Cambridge, U. K.
6. Christensen, J. H., et al. (2013), Chapter 14: Climate phenomena and their relevance for future regional climate change, in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, edited by, T. F. Stocker, et al., pp. 1217-1308, Cambridge Univ. Press, Cambridge, U. K.
7. Dagum, C., (1980), The generation and distribution of income, the Lorenz curve and the Gini ratio, Écon. Appl., 33 (2), 327-367.
8. Damgaard, C., and, J. Weiner, (2000), Describing inequality in plant size or fecundity, Ecology, 81 (4), 1139-1142. (Pubitemid 30442013)
9. Dingman, S. L., (2008), Physical Hydrology, 2nd ed., pp. 646, Waveland Press, Long Grove, Ill.
10. Döll, P., and, H. M. Schmied, (2012), How is the impact of climate change on river flow regimes related to the impact on mean annual runoff? A global-scale analysis, Environ. Res. Lett., 7, 014037, doi: 10.1088/1748-9326/7/ 1/014037.
11. Drǎgulescu, A., and, V. M. Yakovenko, (2001), Exponential and power-law probability distributions of wealth and income in the United Kingdom and the United States, Physica A, 299, 213-221. (Pubitemid 33018371)
12. Etchevers, P., et al. (2002), SnowMIP, an intercomparison of snow models: First results, in Proceedings of the International Snow Science Workshop, pp. 353-360, International Snow Science Workshop, Penticton, Canada, 29 Sept-4 Oct.
13. Foster, J., G. Liston, R. Koster, R. Essery, H. Behr, L. Dumenil, D. Verseghy, S. Thompson, D. Pollard, and, J. Cohen, (1996), Snow cover and snow mass intercomparisons of general circulation models and remotely sensed datasets, J. Clim., 9, 409-426.
14. Giorgi, F., and, R. Francisco, (2000), Uncertainties in regional climate change prediction: A regional analysis of ensemble simulations with the HADCM2 coupled AOGCM, Clim. Dyn., 16, 169-182. (Pubitemid 30192428)
15. Haddeland, I., et al. (2011), Multimodel estimate of the global terrestrial water balance: Setup and first results, J. Hydrometeorol., 12, 869-884, doi: 10.1175/2011JHM1324.1.
16. Haines, A. T., B. L. Finlayson, and, T. A. McMahon, (1988), A global classification of river regimes, Appl. Geogr., 8, 255-272. (Pubitemid 19298450)
17. Hanasaki, N., S. Kanae, T. Oki, K. Masuda, K. Motoya, N. Shirakawa, Y. Shen, and, K. Tanaka, (2008a), An integrated model for the assessment of global water resources-Part 1: Model description and input meteorological forcing, Hydrol. Earth Syst. Sci., 12, 1007-1025.
18. Hanasaki, N., S. Kanae, T. Oki, K. Masuda, K. Motoya, N. Shirakawa, Y. Shen, and, K. Tanaka, (2008b), An integrated model for the assessment of global water resources-Part 2: Applications and assessments, Hydrol. Earth Syst. Sci., 12, 1027-1037.
19. Hempel, S., K. Frieler, L. Warszawski, J. Schewe, and, F. Piontek, (2013), A trend-preserving bias correction-The ISI-MIP approach, Earth Syst. Dyn. Discuss., 4, 49-92.
20. Hosking, J. R. M., and, J. R. Wallis, (1997), Regional Frequency Analysis, An Approach Based on L-Moments, pp. 224, Cambridge Univ. Press, Cambridge, U. K.
21. Jawitz, J. W., and, J. Mitchell, (2011), Temporal inequality in catchment discharge and solute export, Water Resour. Res., 47, W00J14, doi: 10.1029/2010WR010197.
22. Kotz, S., and, N. L. Johnson, (Eds.) (1985), Encyclopedia of Statistical Sciences, vol. 5 (9), John Wiley, N. Y.
23. Krause, M., (2013), Parametric Lorenz curves and the modality of the income density function, Rev. Income Wealth, doi: 10.1111/roiw.12047.
24. Kundzewicz, Z. W., L. J. Mata, N. W. Arnell, P. Döll, P. Kabat, B. Jiménez, K. A. Miller, T. Oki, Z. Şen, and, I. A. Shiklomanov, (2007), Freshwater resources and their management, in Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by, M. L. Parry, et al., pp. 173-210, Cambridge Univ. Press, Cambridge, U. K.
25. Mastin, M. C., K. J. Chase, and, R. W. Dudley, (2011), Changes in spring snowpack for selected basins in the United States for different climate-change scenarios, Earth Interact., 15 (23), 1-18, doi: 10.1175/2010EI368.1.
26. Meehl, G. A., et al. (2007), Global climate projections, in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by, S. Solomon, et al., pp. 747-845, Cambridge Univ. Press, Cambridge, U. K.
27. Metsaranta, J. M., and, V. J. Lieffers, (2008), Inequality of size and size increment in Pinus banksiana in relation to stand dynamics and annual growth rate, Ann. Bot., 101, 561-571, doi: 10.1093/aob/mcm320. (Pubitemid 351301896)
28. Milanovic, B., (1997), A simple way to calculate the Gini coefficient, and some implications, Econ. Lett., 56, 45-49. (Pubitemid 127163375)
29. Moss, R. H., et al. (2010), The next generation of scenarios for climate change research and assessment, Nature, 463, 747-756, doi: 10.1038/nature08823.
30. Nijssen, B., G. M. O'Donnell, A. F. Hamlet, and, D. P. Lettenmaier, (2001), Hydrologic sensitivity of global rivers to climate change, Clim. Change, 50, 143-175. (Pubitemid 32665128)
31. Nilsson, C., C. A. Reidy, M. Dynesius, and, C. Revenga, (2005), Fragmentation and flow regulation of the world's large river systems, Science, 308, 405-408, doi: 10.1126/science.1107887. (Pubitemid 40530076)
32. Nohara, D., A. Kitoh, M. Hosaka, and, T. Oki, (2006), Impact of climate change on river discharge projected by multimodel ensemble, J. Hydrometeorol., 7, 1076-1089. (Pubitemid 44734315)
33. Oja, H., (1981), On location, scale, skewness and kurtosis of univariate distributions, Scand. J. Stat., 8, 154-168.
34. Oki, T., and, Y. C. Sud, (1998), Design of total runoff integrating pathways (TRIP)-A global river channel network, Earth Interact., 2 (1), 1-36.
35. Özdoǧan, M., (2011), Climate change impacts on snow water availability in the Euphrates-Tigris basin, Hydrol. Earth Syst. Sci., 15, 2789-2803, doi: 10.5194/hess-15-2789-2011.
36. Piani, C., J. O. Haerter, and, E. Coppola, (2010a), Statistical bias correction for daily precipitation in regional climate models over Europe, Theor. Appl. Climatol., 99, 187-192, doi: 10.1007/s00704-009-0134-9.
37. Piani, C., G. P. Weedon, M. Best, S. M. Gomes, P. Viterbo, S. Hagemann, and, J. O. Haerter, (2010b), Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models, J. Hydrol., 395, 199-215, doi: 10.1016/j.jhydrol.2010.10.024.
38. Raskin, P., P. Gleick, P. Kirshen, G. Pontius, and, K. Strzepek, (1997), Water futures: Assessment of long-range patterns and problems, in Comprehensive Assessment of the Freshwater Resources of the World, edited by, K. Hultcrantz, et al., pp. 77, Stockholm Environ. Inst., Stockholm, Sweden.
39. Searcy, J. K., (1959), Flow-duration curves, Geol. Surv. Water Supply Pap. 1542-A, pp. 1-33, U.S. Gov. Print. Off., Wash.
40. Seekell, D. A., P. D'Odorico, and, M. L. Pace, (2011), Virtual water transfers unlikely to redress inequality in global water use, Environ. Res. Lett., 6, 024017, doi: 10.1088/1748-9326/6/2/024017.
41. Siebert, S., P. Döll, J. Hoogeveen, J.-M. Faures, K. Frenken, and, S. Feick, (2005), Development and validation of the global map of irrigation areas, Hydrol. Earth Syst. Sci., 9, 535-547.
42. Sperna Weiland, F. C., L. P. H. van Beek, J. C. J. Kwadijk, and, M. F. P. Bierkens, (2012), Global patterns of change in discharge regimes for 2100, Hydrol. Earth Syst. Sci., 16, 1047-1062, doi: 10.5194/hess-16-1047-2012.
43. The Inter-sectoral Impact Model Intercomparison Project (ISI-MIP) (2012), Project Design and Simulation Protocol, Version 1.3, Potsdam Inst. for Clim. Impact Res., Potsdam, Germany.
44. Wada, Y., et al. (2013), Multimodel projections and uncertainties of irrigation water demand under climate change, Geophys. Res. Lett., 40, 4626-4632, doi: 10.1002/grl.50686.
45. Weiner, J., and, O. T. Solbrig, (1984), The meaning and measurement of size hierarchies in plant populations, Oecologia, 61, 334-336. (Pubitemid 16276736)
46. Yaeger, M., E. Coopersmith, S. Ye, L. Cheng, A. Viglione, and, M. Sivapalan, (2012), Exploring the physical controls of regional patterns of flow duration curves-Part 4: A synthesis of empirical analysis, process modeling and catchment classification, Hydrol. Earth Syst. Sci., 16, 4483-4498, doi: 10.5194/hess-16-4483-2012.
47. Yevjevich, V., and, J. T. B. Obeysekera, (1984), Estimation of skewness of hydrologic variables, Water Resour. Res., 20 (7), 935-943.