Spatio-temporal trends of rainfall across Indian river basins

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, N. S.; Sridhar, Venkataramana

doi:10.1007/s00704-017-2095-8

Cited by 132 publications

(64 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over all major river basins except the Ganges and the Brahmaputra, these changes correspond to an increase in the magnitude of intense rainfall (>95th percentile and daily maxima) in the latter part of the 20th century (Bisht et al, ; Deshpande et al, ). Although there are no significant changes in the magnitude or frequency of extreme rainfall in the Ganges basin, the area under extremes of this basin has increased along with increases in the Narmada–Tapi, and Godavari river basins in central and peninsular India (Deshpande et al, ).…”

Section: Observations Changes In Precipitation Processes and Their Atmentioning

confidence: 99%

“…Studies attributing the trends in extremes to anthropogenic activities are rather limited. A few recent studies have attributed the changes in extremes in certain regions to urbanization effects based on the reversal of long‐term trends in the 1970s when urbanization intensified in India (Bisht et al, ; Vittal et al, ). Recently, Mukherjee et al () demonstrated the role of anthropogenic forcings in increasing the frequency of heavy precipitation events across parts of western‐central and peninsular India relative to natural forcings using the CMIP5 suite of experiments, corroborating the results of Krishnan et al () using a single high‐resolution model.…”

Section: Observations Changes In Precipitation Processes and Their Atmentioning

confidence: 99%

See 1 more Smart Citation

Indian summer monsoon: Extreme events, historical changes, and role of anthropogenic forcings

Singh

Ghosh

Roxy

et al. 2019

WIREs Climate Change

160

111

View full text Add to dashboard Cite

The South Asian summer monsoon is a complex coupled human-natural system that poses unique challenges for understanding its evolution alongside increasing anthropogenic activities. Rapid and substantial changes in land-use, landmanagement and industrial activities over the subcontinent, and warming in the Indian Ocean, have influenced the South Asian summer monsoon. These might continue to be significant drivers in the near-term along with rising global greenhouse gas emissions. Deciphering the region's vulnerability to climate change requires an understanding of how these anthropogenic activities, acting on a range of spatial scales, have shaped the monsoon spatially and temporally. This review summarizes historical changes in monsoon rainfall characteristics, associated mechanisms, and the role of anthropogenic forcings, focusing on subseasonal variability and extreme events. Several studies have found intensified subseasonal extremes across parts of India and an increase in spatial variability of rainfall despite an overall weakening of seasonal rainfall in the monsoon core. However, understanding these changes remains challenging because of uncertainties in observations and climate models. The mechanisms and relative influences of various anthropogenic activities, particularly on subseasonal extremes, remain relatively underexplored. Large biases in the representation of relevant processes in global climate models limit the ability to attribute historical changes and make reliable projections. Nevertheless, recent advances in modeling these processes using higher-resolution modeling frameworks provide new tools to investigate the Indian summer monsoon's response to various anthropogenic forcings. There is an urgent need to understand how these forcings interact to shape climate variability and change in this vulnerable region. This article is categorized under:Paleoclimates and Current Trends > Earth System Behavioranthropogenic forcings, climate change attribution, extreme events, South Asian monsoon, subseasonal variability | INTRODUCTIONSouth Asia is one of the world's most densely populated regions, with a large fraction of people dependent on monsoonrelated activities for their livelihood. The summer monsoon season is the prime agricultural season for most of South Asia and the yields of the major cereal crops are highly sensitive to seasonal temperature and precipitation variability (DeFries et al., 2016). Recent studies have also highlighted the substantial impacts that subseasonal precipitation variability has on crop yields

show abstract

Section: Observations Changes In Precipitation Processes and Their Atmentioning

confidence: 99%

Section: Observations Changes In Precipitation Processes and Their Atmentioning

confidence: 99%

Indian summer monsoon: Extreme events, historical changes, and role of anthropogenic forcings

Singh

Ghosh

Roxy

et al. 2019

WIREs Climate Change

160

111

View full text Add to dashboard Cite

show abstract

“…The Spearman′s rank correlation coefficient test result at the Rolla station indicated a decreasing annual rainfall trend at a confidence interval of 90% (−7.1 mm/year), while the Mann-Kendall test does not indicate any significant trend. The IMD gridded rainfall data analysis at river basin scale by Bisht et al [8] and climate projections used in Jaspers et al [90] showed an increasing annual rainfall trend. It is to be noted that, although the interpolated and projected climate data showed an increasing trend, the trend analysis using station level data, as in Rao et al [8], indicated a similar increasing annual rainfall trend at the Guntakal station and decreasing annual rainfall trend at the Pedapappuru station, as in this study.…”

Section: Rainfall Trend Analysismentioning

confidence: 99%

“…India is quite vulnerable to climate change and its impact on various sectors such as water resources, agriculture, forestry, and the health sector, etc. are well documented by several researchers [3][4][5][6][7][8][9][10]. Detailed analysis of rainfall trend is useful to rainfall forecasting, planning water resources development and management, designing water storage structures, irrigation practices and crop choices, drinking water supply, industrial development, and disaster management for current and future climatic conditions [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Long-Term Homogeneity, Trend, and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

Patakamuri

Muthiah

Sridhar

2020

Water

Self Cite

View full text Add to dashboard Cite

The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the subdistrict level and aggregated to monthly, annual, seasonal rainfall totals, and the number of rainy days. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. NonParametric Mann–Kendall test and Spearman’s rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen’s slope method. For the data influenced by serial correlation, various modified versions of Mann–Kendall tests (pre-whitening, trend-free pre-whitening, bias-corrected pre-whitening, and two variants of variance correction approaches) were applied. A significant increasing summer rainfall trend is observed in six out of 27 stations. Significant decreasing trends are observed at two stations during the southwest monsoon season and at two stations during the northeast monsoon season. To identify the trend change points in the time series, distribution−free cumulative sum test, and sequential Mann–Kendall tests were applied. Two open−source library packages were developed in R language namely, ”modifiedmk” and ”trendchange” to implement the statistical tests mentioned in this paper. The study results benefit water resource management, drought mitigation, socio−economic development, and sustainable agricultural planning in the region.

show abstract

“…It provides a clear signal of the utility of the satellite precipitation products at the required spatial resolution for water managers working at a basin scale. Also, at a basin scale, the statistical and hydrologic results are more complementary (Bisht et al, 2017;Kneis et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale

Beria¹,

Nanda²,

Bisht³

et al. 2017

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Abstract. The last couple of decades have seen the outburst of a number of satellite-based precipitation products with Tropical Rainfall Measuring Mission (TRMM) as the most widely used for hydrologic applications. Transition of TRMM into the Global Precipitation Measurement (GPM) promises enhanced spatio-temporal resolution along with upgrades to sensors and rainfall estimation techniques. The dependence of systematic error components in rainfall estimates of the Integrated Multi-satellitE Retrievals for GPM (IMERG), and their variation with climatology and topography, was evaluated over 86 basins in India for year 2014 and compared with the corresponding (2014) and retrospective (1998-2013) TRMM estimates. IMERG outperformed TRMM for all rainfall intensities across a majority of Indian basins, with significant improvement in low rainfall estimates showing smaller negative biases in 75 out of 86 basins. Low rainfall estimates in TRMM showed a systematic dependence on basin climatology, with significant overprediction in semiarid basins, which gradually improved in the higher rainfall basins. Medium and high rainfall estimates of TRMM exhibited a strong dependence on basin topography, with declining skill in higher elevation basins. The systematic dependence of error components on basin climatology and topography was reduced in IMERG, especially in terms of topography. Rainfall-runoff modeling using the Variable Infiltration Capacity (VIC) model over two flood-prone basins (Mahanadi and Wainganga) revealed that improvement in rainfall estimates in IMERG did not translate into improvement in runoff simulations. More studies are required over basins in different hydroclimatic zones to evaluate the hydrologic significance of IMERG.

show abstract

Spatio-temporal trends of rainfall across Indian river basins

Cited by 132 publications

References 49 publications

Indian summer monsoon: Extreme events, historical changes, and role of anthropogenic forcings

Indian summer monsoon: Extreme events, historical changes, and role of anthropogenic forcings

Long-Term Homogeneity, Trend, and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale

Contact Info

Product

Resources

About