Assessing socio-economic drought evolution characteristics and their possible meteorological driving force

References

• Arab D, Elyasi A, Far HT, Karamouz M. 2010. Developing an integrated drought monitoring system based on socioeconomic drought in a transboundary river basin: a case study. World Environmental and Water Resources Congress in Providence, Rhode Island, May 16-20, 2010: Challenges of Change; p. 2754–2761.
   Google Scholar
• Bai T, Wu L, Chang J, Huang Q. 2015. Multi-objective optimal operation model of cascade reservoirs and its application on water and sediment regulation. Water Resour Manage. 29(8):2751–2770.
   Google Scholar
• Barker LJ, Hannaford J, Chiverton A, Svensson C. 2016. From meteorological to hydrological drought using standardised indicators. Hydrol Earth Syst Sci. 20(6):2483–2505.
   Google Scholar
• Cayan DR, Maurer EP, Dettinger MD, Tyree M, Hayhoe K. 2008. Climate change scenarios for the California region. Climatic Change. 87(S1):21–42.
   Google Scholar
• Chang F, Chang Y. 2006. Adaptive neuro-fuzzy inference system for prediction of water level in reservoir. Adv in Water Resourc. 29(1):1–10.
   Google Scholar
• Charlier JB, Ladouche B, Maréchal JC. 2015. Identifying the impact of climate and anthropic pressures on karst aquifers using wavelet analysis. J Hydrol. 523:610–623.
   Google Scholar
• Chen J, Fu T. 2011. Application of water poverty index to socioeconomic drought assessment. Water Resources and Power. 29(9):130–133.
   Google Scholar
• Connell-Buck CR, Medellín-Azuara J, Lund JR, Madani K. 2011. Adapting California’s water system to warm vs. dry climates. Climatic Change. 109(S1):133–149.
   Google Scholar
• Cronin TM, Dwyer GS, Schwede SB, Vann CD, Dowsett H. 2002. Climate variability from the Florida Bay sedimentary record: possible teleconnections to ENSO, PNA and CNP. Clim Res. 19:233–245.
   Google Scholar
• Dessai S, Hulme M. 2004. Does climate adaptation policy need probabilities? Climate Policy. 4(2):107–128.
   Google Scholar
• Dinar A, Mendelsohn RO. (Eds). 2011. Handbook on climate change and agriculture. Edward Elgar Publishing, Cheltenham, Gloucestershire, U. K. p:384-389
   Google Scholar
• Fang W, Huang Q, Huang S, Yang J, Meng E, Li Y. 2017. Optimal sizing of utility-scale photovoltaic power generation complementarily operating with hydropower: a case study of the world’s largest hydro-photovoltaic plant. Energy Convers Manage. 136:161–172.
   Google Scholar
• Fang W, Huang S, Huang G, Huang Q, Wang H, Wangal L, Zhang Y, Li P, Ma L. 2019a. Copulas-based risk analysis for inter-seasonal combinations of wet and dry conditions under a changing climate. Int J Climatol. doi: 10.1002/joc.5929.
   Google Scholar
• Fang W, Huang S, Ren K, Huang Q, Huang G, Cheng G, Li K. 2019b. Examining the applicability of different sampling techniques in the development of decomposition-based streamflow forecasting models. J Hydrol. 568, 534–580.
   Google Scholar
• Farahmand A, AghaKouchak A, Teixeira J. 2015. A vantage from space can detect earlier drought onset: an approach using relative humidity. Sci Rep. 5: 8553; doi: 10.1038/srep08553.
   Google Scholar
• Gan TY, Ito M, Hulsmann S, Qin X, Lu X, Liong SY, Rutschman P, Disse M, Koivusalo H. 2016. Possible climate change/variability and human impacts, vulnerability of drought-prone regions, water resources and capacity building for Africa. Int Assoc Scient Hydrol Bull. 61(7):1209–1226.
   Google Scholar
• Gong Z, Feng G, Wan S, Li J. 2006. Analysis of features of climate change of Huabei area and the global climate change based on heuristic segmentation algorithm. Acta Phys Sin. 55(1):477–484.
   Google Scholar
• Grinsted A, Moore JC, Jevrejeva S. 2004. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlin Processes Geophys. 11(5/6):561–566.
   Google Scholar
• Guttman NB. 1998. Comparing the Palmer Drought index and the standardized precipitation index. J Am Water Resourc Assoc. 34(1):113–121.
   Google Scholar
• Hamed KH, Rao AR. 1998. A modified Mann–Kendall trend test for autocorrelated data. J Hydrol. 204(1–4):182–196.
   Google Scholar
• Hao Z, AghaKouchak A. 2014. A nonparametric multivariate multi-index drought monitoring framework. J Hydrometeor. 15(1):89–101.
   Google Scholar
• Hao Z, Singh VP. 2015. Drought characterization from a multivariate perspective: a review. J Hydrol. 527:668–678.
   Google Scholar
• Heim RR. 2002. A review of twentieth-century drought indices used in the United States. Bull Amer Meteor Soc. 83(8):1149–1166.
   Google Scholar
• Hirsch RM, Slack JR. 1984. Non-parametric trend test for seasonal data with serial dependence. Water Resour Res. 20(6):727–732.
   Google Scholar
• Hirsch RM, Slack JR, Smith RA. 1982. Techniques of trend analysis for monthly water quality data. Water Resour Res. 18(1):107–121.
   Google Scholar
• Huang S, Chang J, Huang Q, Chen Y. 2014a. Monthly streamflow prediction using modified EMD-based support vector machine. J Hydrol. 511:764–775.
   Google Scholar
• Huang S, Chang J, Huang Q, Chen Y. 2014b. Spatio-temporal changes and frequency analysis of drought in the Wei River Basin, China. Water Resour Manage. 28(10):3095–3110.
   Google Scholar
• Huang S, Huang Q, Chang J, Leng G, Xing L. 2015. The response of agricultural drought to meteorological drought and the influencing factors: a case study in the Wei River Basin, China. Agr Water Manage. 159:45–54.
   Google Scholar
• Huang S, Huang Q, Chang J, Leng G. 2016. Linkages between hydrological drought, climate indices and human activities: a case study in the Columbia River basin. Int J Climatol. 36(1):280–290.
   Google Scholar
• Huang S, Li P, Huang Q, Leng G, Hou B, Ma L. 2017. The propagation from meteorological to hydrological drought and its potential influence factors. J Hydrol. 547:184–195.
   Google Scholar
• Kendall MG. 1948. Rank correlation methods. Oxford: Griffin.
   Google Scholar
• Kumar MN, Murthy CS, Sai MVRS, Roy PS. 2009. On the use of Standardized Precipitation Index (SPI) for drought intensity assessment. Met Apps. 16(3):381–389.
   Google Scholar
• Li Y, Li J, Feng J. 2013. Boreal summer convection oscillation over the Indo-Western Pacific and its relationship with the East Asian summer monsoon. Atmos Sci Lett. 14(2):66–71.
   Google Scholar
• Lin Q, Wu Z, Singh VP, Sadeghi SHR, He H, Lu G. 2017. Correlation between hydrological drought, climatic factors, reservoir operation, and vegetation cover in the Xijiang Basin, South China. J of Hydrol. 549:512–524.
   Google Scholar
• Liu S, Huang S, Xie Y, Wang H, Huang Q, Leng G, Li P, Wang L. 2019a. Spatial-temporal changes in vegetation cover in a typical semi-humid and semi-arid region in China: Changing patterns, causes and implications. Ecol Indicator, 98, 462–475.
   Google Scholar
• Liu S, Huang S, Xie Y, Wang H, Leng G, Huang Q, Wei X, Wang L. 2019b. Identification of the non-stationarity of floods: Changing patterns, causes, and implications. Water Resourc Manage. doi: 10.1007/s11269-018-2150-y.
   Google Scholar
• Lorenzolacruz J, Vicente-Serrano SM, GonzálezHidalgo JC, López-Moreno JI, Cortesi N. 2013. Hydrological drought response to meteorological drought in the Iberian Peninsula. Clim Res. 58(2):117–131.
   Google Scholar
• Madani K. 2014. Water management in Iran: what is causing the looming crisis?. J Environ Stud Sci. 4(4):315–328.
   Google Scholar
• Mann HB. 1945. Nonparametric tests against trend. Econometrica: J Econometr Soc. 13(3):245–259.
   Google Scholar
• Mastrandrea MD, Heller NE, Root TL, Schneider SH. 2010. Bridging the gap: linking climate-impacts research with adaptation planning and management. Climatic Change. 100(1):87–101.
   Google Scholar
• McKee TB, Doesken NJ, Kleist J. 1993. The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology, January 17–22, p. 179–183. Boston, MA: American Meteorological Society.
   Google Scholar
• Mehran A, Mazdiyasni O, AghaKouchak A. 2015. A hybrid framework for assessing socioeconomic drought: Linking climate variability, local resilience, and demand. J Geophys Res Atmos. 120(15):7520–7533.
   Google Scholar
• Meng E, Huang S, Huang Q, Fang W, Wu L, Wang L. 2019. A robust method for non-stationary streamflow prediction based on improved EMD-SVM model. J Hydrol. 568, 462–478.
   Google Scholar
• Mitchell JJM, Dzerdzeevskii B, Flohn H, Hofmeyr WL, Lamb HH, Rao KN, Wallén CC. 1966. Climatic change. WMO Technical Note 79 (WMO-No. 195/TP. 100). Geneva: World Meteorological Organization.
   Google Scholar
• Montanari A. 2015. Debates–perspectives on socio-hydrology: introduction. Water Resour Res. 51(6):4768–4769.
   Google Scholar
• MoránTejeda E, Ceglar A, Medvedcvikl B, Vicente-Serrano SM, López-Moreno JI, González-Hidalgo JC, Revuelto J, Lorenzo-Lacruz J, Camarero J, Pasho E. 2013. Assessing the capability of multi-scale drought datasets to quantify drought severity and to identify drought impacts: an example in the Ebro Basin. Int J Climatol. 33(8):1884–1897.
   Google Scholar
• Palmer WC. 1965. Meteorological drought. Washington, DC: Department of Commerce Weather Bureau.
   Google Scholar
• Palmer WC. 1968. Keeping track of crop moisture conditions, nation-wide: the new crop moisture index. Weatherwise. 21(4):156–161.
   Google Scholar
• Pedro BG, Plamen CI, Luís ANA, Eugene HS. 2001. Scale invariance in the nonstationary of human heart rate. Phys Rev Lett. 87(16):160815.
   Google Scholar
• Seager R, Vecchi GA. 2010. Greenhouse warming and the 21st century hydroclimate of southwestern North America. Proc Nat Acad Sci USA. 107(50):21277–21282.
   Google Scholar
• Shafer BA. 1982. Development of a surface water supply index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. Proceedings of the 50th Annual Western Snow Conference, Colorado State University, Fort Collins. p. 164–175.
   Google Scholar
• Shiklomanov IA, Shiklomanov AI, Lammers RB, Peterson BJ, Vorosmarty CJ. 2000. The dynamics of river water inflow to the Arctic Ocean. In: E.L. Lewis et al. (eds.), The freshwater budget of the Arctic Ocean. Dordrecht: Springer; p.281–296.
   Google Scholar
• Shukla S, Wood AW. 2008. Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett. 35, L02405, doi: 10.1029/2007GL032487.
   Google Scholar
• Sivapalan M. 2015. Debates-Perspectives on socio-hydrology: Changing water systems and the “tyranny of small problems”-Socio-hydrology. Water Resour Res. 51(6):4795–4805.
   Google Scholar
• Tan X, Gan TY, Shao D. 2016. Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large-scale climate anomalies. J Geophys Res: Atmos. 121(24):14469-14486
   Google Scholar
• Vicente-Serrano SM, Beguería S, López-Moreno JI. 2010. A multi-scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Climate. 23(7):1696–1718.
   Google Scholar
• Vicente-Serrano SM, López-Moreno JI, Beguería S, Lorenzo-Lacruz J, Azorin-Molina C, Morán-Tejeda E. 2012. Accurate computation of a streamflow drought index. J Hydrol Eng. 17(2):318–332.
   Google Scholar
• Vogel RM, Lall U, Cai X, Rajagopalan B, Weiskel PK, Hooper RP, Matalas NC. 2015. Hydrology: The interdisciplinary science of water. Water Resour Res. 51(6):4409–4430.
   Google Scholar
• Wada Y, Van Beek LPH, Viviroli D, Dürr HH, Weingartner R, Bierkens MF. 2011. Global monthly water stress: 2. Water demand and severity of water stress. Water Resour Res. 47, W07518, doi: 10.1029/2010WR009792
   Google Scholar
• Wan X, Han Y, Zhang P. 1997. Study on the droughts and soil moisture in Gansu Province in 1995. Gansu Agric Sci Technol. 6:24–25. (in Chinese)
   Google Scholar
• Wang Q, Li F, Liu B, Ling H. 2015. Variation in drought and its response to climate warming in Qinghai plateau in recent 50 years. Arid Zone Res. 32(1):65–72.
   Google Scholar
• Wheater HS, Gober P. 2015. Water security and the science agenda. Water Resour Res. 51(7):5406–5424.
   Google Scholar
• Wilhite DA. 2000. Drought as a natural hazard: concepts and definitions. In: Drought A Global Assessment. Vol. 1; edited by Donald A. Wilhite, London: Routledge, chap. 1; p. 3–18.
   Google Scholar
• Wilhite DA, Glantz MH. 1985. Understanding: the drought phenomenon: the role of definitions. Water Int. 10(3):111–120.
   Google Scholar
• Wu Z, Wang B, Li J, Jin F. 2009. An empirical seasonal prediction model of the East Asian summer monsoon using ENSO and NAO. J Geophys Res: Atmos. 114, D18120, doi: 10.1029/2009JD011733.
   Google Scholar
• Xie Y, Huang Q, Chang J, Liu S, Wang Y. 2016. Period analysis of hydrologic series through moving-window correlation analysis method. J Hydrol. 538:278–292.
   Google Scholar
• Yang X, Lu X. 2014. Drastic change in China's lakes and reservoirs over the past decades. Sci Rep. 4:6041
   Google Scholar
• Yue S, Ouarda TBMJ, Bobée B, Legendre P, Bruneau P. 1999. The Gumbel mixed model for flood frequency analysis. J Hydrol. 226(1/2):88–100.
   Google Scholar
• Zetterqvist L. 1991. Statistical estimation and interpretation of trends in water quality time series. Water Resour Res. 27(7):1637–1648.
   Google Scholar
• Zhang S, Gao H, Naz BS. 2014. Monitoring reservoir storage in South Asia from multisatellite remote sensing. Water Resour Res. 50(11):8927–8943.
   Google Scholar
• Zseleczky L, Yosef S. 2014. Are shocks really increasing? A selective review of the global frequency, severity, scope, and impact of five types of shocks (Vol. 5). International Food Policy Research Institute, Addis Ababa, Ethiopia
   Google Scholar