Impact of climate change on extreme rainfall events and flood risk in India

Guhathakurta, Pulak; Sreejith, O. P.; Menon, Preetha

doi:10.1007/s12040-011-0082-5

Cited by 466 publications

(185 citation statements)

References 16 publications

Supporting

Mentioning

172

Contrasting

Unclassified

Order By: Relevance

“…Increases are in general larger for the DC method; the multipliers of the LS method may reduce the change signal. These projections are in line with the study of Guhathakurta et al (2011), Lal et al (2000, May (2011), Rupakumar et al (2006) and Menon et al (2013) who also reported increases for monsoon rainfall in east and north east India.…”

Section: Mean Seasonal Rainfallsupporting

confidence: 89%

Downscaling GCM data for climate change impact assessments on rainfall: a practical application for the Brahmani-Baitarani river basin

Dahm

Singh

Lal

et al. 2016

Preprint

View full text Add to dashboard Cite

The delta of the Brahmani-Baitarani river basin, located in the eastern part of India, frequently experiences severe floods. For flood risk analysis and water system design, insights in the possible future changes in extreme rainfall events caused by climate change are of major importance. There is a wide range of statistical and dynamical 5 downscaling and bias-correction methods available to generate local climate projections that also consider changes in rainfall extremes. Yet the applicability of these methods highly depends on availability of meteorological observations at local level. In the developing countries data and model availability may be limited, either due to the lack of actual existence of these data or because political data sensitivity hampers 10 open sharing.We here present the climate change analysis we performed for the BrahmaniBaitarani river basin focusing on changes in four selected indices for rainfall extremes using data from three performance-based selected GCMs that are part of the 5th Coupled Model Intercomparison Project (CMIP5). We apply and compare two widely used 15 and easy to implement bias correction approaches. These methods were selected as best suited due to the absence of reliable long historic meteorological data. We present the main changes -likely increases in monsoon rainfall especially in the Mountainous regions and a likely increase of the number of heavy rain days. In addition, we discuss the gap between state-of-the-art downscaling techniques and the actual options one is 20 faced with in local scale climate change assessments.

show abstract

Section: Mean Seasonal Rainfallsupporting

confidence: 89%

Downscaling GCM data for climate change impact assessments on rainfall: a practical application for the Brahmani-Baitarani river basin

Dahm

Singh

Lal

et al. 2016

Preprint

View full text Add to dashboard Cite

show abstract

“…The severe rains have a substantial socio-economic impact in tropical areas which are dependent on agriculture and prone to natural hazards such as flooding and mass movements. Thus, in recent decades in India, many authors have analysed extreme rainfall series for periods of different lengths, using data from different rain-gauge networks and a variety of methods (Rakhecha and Soman 1994;Dhar and Nandargi 1995;Roy and Balling 2004;Goswami et al 2006;Rajeevan et al 2008;Guhathakurta et al 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Northeast India, where the Meghalaya Hills are located, can be treated as a relatively separate region, with summer monsoon rainfall weakly correlated or out of phase with that of peninsular India (Mooley and Shukla 1987;Parthasarathy et al 1987;Sontakee and Singh 1996;Guhathakurta and Rajeevan 2008;Guhathakurta et al 2011). The area receives high rainfall (the annual mean approximately 2,066 mm with a coefficient of variation of 8.6 %), but its large spatiotemporal variation, related to multiscale interaction with topography, results in difficulties in the detection of trends in extreme rain events (Parthasarathy et al 1995;Goswami et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Variation in the orographic extreme rain events over the Meghalaya Hills in northeast India in the two halves of the twentieth century

Prokop

Walanus

2014

Theor Appl Climatol

View full text Add to dashboard Cite

The daily rainfall data for the twentieth century, from three stations across the region, constitute the basis for statistical analysis. However, the low signal-to-noise ratio makes it difficult to find any significant departure from the simplest null hypothesis of the stability of the rain record at individual stations in northeast India. Only the coarsest possible view, i.e. comparing the two halves of the century, provided strongly significant results in the numbers of days with extreme rain. Using a more general approach, the number of Fourier transform extreme amplitudes also differed significantly. Increasingly heavy events during the summer monsoon season, and partly in the pre-and post-monsoon seasons, are offset by a weakening in the winter monsoon season, so that the annual mean rainfall does not show a significant trend over the Meghalaya Hills. Apart from a greater number of years with noticeable extreme rainfall events in the second half of the twentieth century, we can also observe a more pronounced quasi-periodicity of 10-20 and 30-60 days during the same period. The detection of the latter periodicity indicates that the Madden-Julian oscillation plays an important role in the formation of extreme rainfall events over the Meghalaya Hills during extreme monsoon years.

show abstract

“…Based on the available literatures, most of the previous studies are mainly focused on the mean flows [24,25]. For better disaster management and mitigation in general, it is important to be aware that understanding the changes in flow extremes is more important than understanding the changes in the mean pattern [26].…”

Section: Study Area and Data Descriptionmentioning

confidence: 99%

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

Wang

Zhao

et al. 2016

Water

View full text Add to dashboard Cite

Statistical modeling of hydrological extremes is significant to the construction of hydraulic engineering. This paper, taking the Yingluoxia watershed as the study area, compares the annual maximum (AM) series and the peaks over a threshold (POT) series in order to study the hydrological extremes, examines the stationarity and independence assumptions for the two series, and discusses the estimations and uncertainties of return levels from the two series using the Generalized Extreme Value (GEV) and Generalized Pareto distribution (GPD) models. For comparison, the return levels from all threshold excesses with considering the extremal index are also estimated. For the POT series, the threshold is selected by examining the mean excess plot and the stability of the parameter estimates and by using common-sense. The serial correlation is reduced by filtering out a set of dependent threshold excesses. Results show that both series are approximately stationary and independent. The GEV model fits the AM series well and the GPD model fits the POT series well. The estimated return levels are fairly comparable for the AM series, the POT series, and all threshold excesses with considering the extremal index, with the difference being less than 10% for return periods longer than 10 years. The uncertainties of the estimated return levels are the highest for the AM series, and next for the POT series and then for all threshold excesses series in turn.

show abstract

Impact of climate change on extreme rainfall events and flood risk in India

Cited by 466 publications

References 16 publications

Downscaling GCM data for climate change impact assessments on rainfall: a practical application for the Brahmani-Baitarani river basin

Downscaling GCM data for climate change impact assessments on rainfall: a practical application for the Brahmani-Baitarani river basin

Variation in the orographic extreme rain events over the Meghalaya Hills in northeast India in the two halves of the twentieth century

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

Contact Info

Product

Resources

About