Decadal frequency and trends of extreme excess/deficit rainfall during the monsoon season over different meteorological sub-divisions of India

Subash, N.; Mohan, H. S. Ram; Sikka, A. K.

doi:10.1080/02626667.2011.608677

Cited by 30 publications

(12 citation statements)

References 38 publications

(36 reference statements)

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“…2000 a , b ; Kundzewicz & Robson 2000; Chiew & Sirivardena 2005; Subash & Ram Mohan 2011, 2012; Subash et al . 2011 a , b ). The averages of monthly, seasonal (rice season: June–October, wheat season: Novermber–April) and annual values for all weather variables and their sd and coefficients of variation (CV) (CV=( sd /mean)×100) were calculated in order to find out the variability during the study period.…”

Section: Methodsmentioning

confidence: 99%

Long-term yield variability and detection of site-specific climate-smart nutrient management practices for rice–wheat systems: an empirical approach

et al. 2014

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Identification of climate-smart nutrient management practices will overcome the ill effects of extreme climate variability on agricultural production under projected climate change scenarios. The rice-wheat cropping system is the major system used in India: using long-term yield data from Integrated Nutrient Management experiments on this system, the present study analysed trends in weather parameters and grain yield under different nutrient management practices. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure (FYM), green manure (GM) and crop residue) sources of nutrients were compared with farmers' conventional practices. A significant increasing trend was noticed for rainfall during the rice season at Kalyani and Navsari, of the order of 137·7 and 154·2 mm/decade, respectively. The highest increase in maximum temperature was seen at Palampur (1·62°C/decade) followed by Ludhiana (1·14°C/decade). At all the sites except Ludhiana and Kanpur, the yield of the rice-wheat system showed an increasing trend ranging from 0·08 t/ha/year in Jabalpur to 0·011 t/ha/year in Navsari, under the recommended dose of inorganic fertilizer application. A significant decreasing trend of 0·055 t/ha was found in Ludhiana. For most of the sites, a combination of half the recommended dose of inorganic fertilizer and either FYM or GM to provide the remainder of the N required was sufficient to maintain productivity. The top three climate-resilient integrated nutrient management practices were identified for all the study sites. Thus, the present study highlights the adaptive capacity of different integrated nutrient management practices to rainfall and temperature extremes under rice-wheat cropping system in distinctive agro-ecological zones of India.

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Section: Methodsmentioning

confidence: 99%

Long-term yield variability and detection of site-specific climate-smart nutrient management practices for rice–wheat systems: an empirical approach

et al. 2014

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“…The magnitude of the trends was estimated using Sen Slope (Sen, 1968) and according to Hirsch et al (1982) Sen's method was robust against extreme outliers. The procedures and equations for Mann-Kendall test statistic and Sen's methodology were described by Bandyopadhyay et al (2009) andSubash et al (2011).…”

Section: Trends Methodologymentioning

confidence: 99%

“…The link between ENSO and the monsoon is realized through vertical and horizontal addictions associated with the stationary waves in the upper troposphere set up by the tropical ENSO heating (Xavier et al , ). The year‐to‐year variability in monsoon rainfall causes severe droughts and floods in one or other places in India (Kripalani et al , ; Subash et al , ). Frequent occurrence of the fluctuating nature of the Indian monsoon affects the agriculture, power generation, water resources and even in financial sectors.…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis of Indian rainfall and rice productivity anomalies over the last decades

Subash

Gangwar

2013

Intl Journal of Climatology

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Monsoon fluctuations have a reflective influence on rice productivity, which is the main foodgrain in India. The impact of El Niño on spatial variability of summer monsoon rainfall and thereby kharif rice productivity was analysed for the period 1974-2009. It was clear from the analysis that the delayed onset of monsoon along with El Niño has varied influences on rice productivity over different rice growing states as well as over India. Out of eight El Niño years, 6 years received deficit rainfall during monsoon season. But, the quantity of deficit varies from −20.3% in 2002 to −5.5% in 1991. The monthly distribution of monsoon rainfall shows higher frequency of deficit occurred during July and September. Interestingly, all El Niño years, except in 1997, September received deficit in rainfall which indicate the early withdrawal of monsoon. During 8 moderate and strong El Niño years, 5 years the kharif rice productivity falls below the technological trend ranging by between −4.3% in 1986 and −13.8% in 2002 over India. There exists a wide spatial variability of normalized kharif rice productivity anomaly during moderate El Niño event, with a maximum of −21.9% over Gujarat followed by −15.9% at Maharashtra. However, during the strong El Niño event, there is a maximum of −14.2% at Bihar to −6.6% over Maharashtra. The correlation between normalized monthly rainfall anomaly and rice productivity anomaly during the El Niño years indicated that July rainfall contributed 71% of the variations in rice productivity. Analysis of El Niño impact on spatial rice productivity may be useful for formulating farm-level site specific management planning and policy decisions.

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“…A wide literature exists for trend assessments on both national and international scales for many parts of the world, viz. Gautam and Acharya (2012), Lorenzo-Lacruz et al (2012), Subash et al (2011), Burn et al (2010, Brabets andWavvoord (2009), Birsan et al (2005), Douglas et al (2000), Genta et al (1998), Giakoumakis and Baloutsos (1997), Hyvarinen (2003), Jiang et al (2007), Johnston and Shmagin (2008), Kahya and Kalayci (2004), Lindstrom and Bergstrom (2004) and Wilson et al (2010). There have been few studies of river basins in China and India (Gautam and Acharya 2012), and none of studies had reported the trend of climate variables in the Tapi Basin at local scales.…”

Section: Introductionmentioning

confidence: 92%

Identification of trend and probability distribution for time series of annual peak flow in Tapi Basin, India

Timbadiya

Mirajkar

Patel

et al. 2013

ISH Journal of Hydraulic Engineering

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This study deals with trend analysis of observed annual peak flow time series data at four stream gauging stations in the Tapi Basin. Innovative trend analysis, recently proposed by S°en, and Mann Kendall test are used to ascertain the trend in extreme annual flow (flood) at aforesaid gauging stations in the Tapi Basin. Also, the time series of extreme flow data have been checked for their serial correlation and, subsequently, flood frequency analysis is undertaken to obtain floods of different return periods. The fitted probability distributions are also used to predict extreme flow into the Ukai Reservoir on the basis of information from upstream gauging stations. The methodology has also been used to predict runoff into the reservoir from the unguaged catchments.

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Decadal frequency and trends of extreme excess/deficit rainfall during the monsoon season over different meteorological sub-divisions of India

Cited by 30 publications

References 38 publications

Long-term yield variability and detection of site-specific climate-smart nutrient management practices for rice–wheat systems: an empirical approach

Long-term yield variability and detection of site-specific climate-smart nutrient management practices for rice–wheat systems: an empirical approach

Statistical analysis of Indian rainfall and rice productivity anomalies over the last decades

Identification of trend and probability distribution for time series of annual peak flow in Tapi Basin, India

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