Assessing Severe Drought and Wet Events over India in a Future Climate Using a Nested Bias-Correction Approach

被引:53
作者
Ojha, Richa [1 ]
Kumar, D. Nagesh [1 ,2 ]
Sharma, A. [3 ]
Mehrotra, R. [3 ]
机构
[1] Indian Inst Sci, Dept Civil Engn, Bangalore 560012, Karnataka, India
[2] Indian Inst Sci, Ctr Earth Sci, Bangalore 560012, Karnataka, India
[3] Univ New S Wales, Sch Civil & Environm Engn, Sydney, NSW 2052, Australia
关键词
Droughts; India; Climates; Hydrologic models; Nested bias correction; General circulation model; Drought; Wet; Standardized Precipitation Index; Climate; Precipitation; STANDARDIZED PRECIPITATION INDEX; REGION; BASIN;
D O I
10.1061/(ASCE)HE.1943-5584.0000585
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
General circulation models (GCMs) are routinely used to simulate future climatic conditions. However, rainfall outputs from GCMs are highly uncertain in preserving temporal correlations, frequencies, and intensity distributions, which limits their direct application for downscaling and hydrological modeling studies. To address these limitations, raw outputs of GCMs or regional climate models are often bias corrected using past observations. In this paper, a methodology is presented for using a nested bias-correction approach to predict the frequencies and occurrences of severe droughts and wet conditions across India for a 48-year period (2050-2099) centered at 2075. Specifically, monthly time series of rainfall from 17 GCMs are used to draw conclusions for extreme events. An increasing trend in the frequencies of droughts and wet events is observed. The northern part of India and coastal regions show maximum increase in the frequency of wet events. Drought events are expected to increase in the west central, peninsular, and central northeast regions of India. (C) 2013 American Society of Civil Engineers.
引用
收藏
页码:760 / 772
页数:13
相关论文
共 35 条
[1]   Downscaling precipitation to river basin in India for IPCCSRES scenarios using support vector machine [J].
Anandhi, Aavudai ;
Srinivas, V. V. ;
Nanjundiah, Ravi S. ;
Kumar, D. Nagesh .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2008, 28 (03) :401-420
[2]  
[Anonymous], CLIMATE CHANGE 2007
[3]   Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data [J].
Bhuiyan, C. ;
Singh, R. P. ;
Kogan, F. N. .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2006, 8 (04) :289-302
[4]   Observed drought and wetness trends in Europe: an update [J].
Bordi, I. ;
Fraedrich, K. ;
Sutera, A. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2009, 13 (08) :1519-1530
[5]   Evaluating uncertainties in the projection of future drought [J].
Burke, Eleanor J. ;
Brown, Simon J. .
JOURNAL OF HYDROMETEOROLOGY, 2008, 9 (02) :292-299
[6]  
Bussay A., 1999, Investigation and Measurements of Droughts in Hungary
[7]   Data mining for evolution of association rules for droughts and floods in India using climate inputs [J].
Dhanya, C. T. ;
Kumar, D. Nagesh .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2009, 114
[8]   Nonparametric methods for modeling GCM and scenario uncertainty in drought assessment [J].
Ghosh, Subimal ;
Mujumdar, P. P. .
WATER RESOURCES RESEARCH, 2007, 43 (07)
[9]   Accepting the standardized precipitation index: A calculation algorithm [J].
Guttman, NB .
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 1999, 35 (02) :311-322
[10]   Evaluation of bias-correction methods for ensemble streamflow volume forecasts [J].
Hashino, T. ;
Bradley, A. A. ;
Schwartz, S. S. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2007, 11 (02) :939-950