Probability analysis of monthly rainfall on seasonal monsoon in Pakistan

Ahmad, Ishfaq; Mahmood, Iram; Malik, Imran Riaz; Arshad, Irshad Ahmad; Haq, Ehtasham ul; Iqbal, Zahid

doi:10.1002/joc.3725

Cited by 9 publications

(8 citation statements)

References 11 publications

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“…The climate ranges from arid subtropical with an average temperature of 17.5–30.4°C and rainfall 150–200 mm in southern Punjab to semi‐arid tropical with an average temperature of 10.5–24.4 °C and rainfall 315–600 mm in central Punjab. The majority of the rain occurs during the monsoon season (July–September) in Punjab (Ahmad et al., ).…”

Section: Introductionmentioning

confidence: 99%

Quantification of the impacts of climate warming and crop management on canola phenology in Punjab, Pakistan

Ahmad

Abbas

Fatima

et al. 2017

J Agronomy Crop Science

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Yield is influenced by the length of the growing season, which is affected by weather conditions and management practices of a crop, including sowing dates and shifting of cultivars. It is necessary to understand the effects of agronomic management practices and weather variables on phenological stages and crop phases in order to develop strategies for adaptation of agricultural systems to changes in climatic conditions. The goal of this study was to determine the impact of warming trends on phenology of canola from 1980 to 2014 for central and southern Punjab, Pakistan. Sowing, emergence, anthesis and physiological maturity dates were delayed by an average of 6.02, 3.14, 3.31 and 1.89 days per decade, respectively.The duration of sowing to anthesis, sowing to physiological maturity and anthesis to physiological maturity phases decreased an average 2.71, 4.13 and 1.42 days per decade, respectively, for all 10 locations that were analysed in this study. The sowing, emergence, anthesis and physiological maturity dates were positively correlated with an increase in temperature by an average 2.71, 1.41, 1.49 and 0.85 days per°C , respectively. However, the phenological phases such as sowing to anthesis, anthesis to maturity and sowing to maturity were negatively correlated with an increase in temperature by an average of 1.22, 0.64 and 1.86 days per°C, respectively, for all 10 locations. Applying a process-based CSM-CROPGRO-Canola model using a standard cultivar (field tested) for all locations and years indicated that the simulated phenological stages occurred earlier due to the warming trend compared to the observed phenological stages. One-quarter of the negative effects of this thermal trend was compensated by growing new cultivars that had higher thermal time requirements. Therefore, new canola genotypes with a higher number of growing degree day requirement and high temperature tolerance should be a priority for evolving new cultivars. K E Y W O R D S anthesis date, Brassica napus L., climate change, CSM-CROPGRO-Canola model, cultivar shift,

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Section: Introductionmentioning

confidence: 99%

Quantification of the impacts of climate warming and crop management on canola phenology in Punjab, Pakistan

Ahmad

Abbas

Fatima

et al. 2017

J Agronomy Crop Science

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“…Krishnamurti 1985;Webster and Lukas 1992;Lau et al 2000;Ding and Chan 2005;Bhat et al 2002;Johnson et al 2004;Webster 2005;Singh and Ranade 2010;Saeed et al 2011;Imran et al 2014;Rasul and Chaudhry 2010). The summer monsoon rainfall over the subcontinent has great social, agricultural, and economic value (Ahmad et al 2014). The summer monsoon contributes 65-75% of the total annual rainfall in Pakistan (Ahmad et al 2014).…”

Section: Introductionmentioning

confidence: 99%

“…The summer monsoon rainfall over the subcontinent has great social, agricultural, and economic value (Ahmad et al 2014). The summer monsoon contributes 65-75% of the total annual rainfall in Pakistan (Ahmad et al 2014). The summer monsoon rainfall in Pakistan provides water replenishment which allows the water requirements to be fulfilled during the transition period until the onset of winter rainfall (Imran et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan

Ali

Khalid

Kiani

et al. 2019

Asia-Pacific J Atmos Sci

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Pakistan receives huge amount of rainfall during summer monsoon season that provides water replenishment for transition periods, helps in maintaining natural and anthropogenic ecosystems, and increased crop productivity. In this changing world, shifts in summer monsoon onset in Pakistan have been observed that seems to affect the society in general. Therefore, it is vital to address these summer monsoon onset shifts to help policy makings and implementation. The study was carried out to analyse the spatio-temporal variability in summer monsoon onset in four objectively defined regions covering all Pakistan. A total of 35 meteorological stations spreading over four regions (i.e., northern, central east, central west, and southern) were taken in to account and shifts in summer monsoon onset have been calculated for the period of 1971-2010. The analysis is based on the observational data of daily precipitation from 20th Jun-20th July for 40 years. The onset for each year and mean onset for each decade has been calculated for all stations. The data was analysed for homogeneity, spatial and temporal variability of monsoon rainfall has been calculated for all four regions, and station wise monsoon onset has been discussed in detail. The temporal analysis shows that the onset of monsoon has shift towards earlier onset from first week of July to last week of June at most of the stations in which the investigation was carried out during the studied period. The spatial analysis shows that the amount of monsoon precipitation during the onset period has decreased after 1970's in almost all regions. This variability in monsoon onset can have major impacts on rain fed agriculture and cultivation of crops like maize, soybean, rice and sugarcane etc. and will have to revisit the cropping calendar. Keywords Monsoon onset. Spatial variability. Temporal variability. Asian summer monsoon. Monsoon shifts Highlights 1-Observations at 35 meteorological stations were processed for summer monsoon onset in Pakistan 2-Temporal analysis of four decades i.e., 1971-2010 3-Mean monsoon onset has observed a shift over 40 years to an earlier time in Pakistan 4-Total amount of precipitation has decreased over the studied period 5-North eastern region of Pakistan received highest amount of precipitation among all others Responsible Editor: Ashok Karumuri.

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“…Because of their suitability to modelling of extreme value, these probability distributions have numerous applications for environmental data (e.g., An and Pandey, 2005;Furrer and Katz, 2008;Chikobvu and Sigauke, 2013;Jonathan and Ewans, 2013;Diriba et al, 2015;Ahmad et al, 2016). Several studies based on frequentist approaches have been conducted for finding the best fit distribution and modelling the AMDR data in Pakistan by Rasul et al (2004), Haroon and Rasul (2009), Rasul et al (2009) and Ahmad et al (2014Ahmad et al ( , 2016. Ahmad et al (2016) suggested that the (GEV) and (GP) are the most suitable distribution for the AMDR series in the different regions of Pakistan.…”

Section: Introductionmentioning

confidence: 99%

Modelling of Extreme Rainfall in Punjab: Pakistan Using Bayesian and Frequentist Approach

Ahmad¹

2019

Appl. Ecol. Env. Res.

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In this study we compared the efficiency of frequentist approach with Bayesian approach by carrying out extreme value analysis of Annual Maximum Daily Rainfall (AMDR). For frequentist frequency analysis of AMDR, we used the data of one station i.e. Lahore in Punjab province, Pakistan while for Bayesian analysis we used the data of three other neighboring stations as prior information. During frequentist approach, Generalized Extreme Value (GEV) was found to be a best-fit distribution on the data. In frequentist method, the parameters of GEV distribution were estimated using Maximum Likelihood Estimation (MLE), while in the Bayesian framework the Markov Chain Monte Carlo (MCMC) simulation technique along with Metropolis-Hasting algorithm and Gibbs sampler were implemented. Findings of this study indicate that despite the asymptotic requirements of the MLE, its performance can be enhanced by adopting the Bayesian MCMC paradigm. In order to acquire the posterior densities of GEV parameters, non-informative and informative priors based on the historical data of surrounding weather stations were employed. The result of Bayesian MCMC might be affected by the choice of priors. In addition, the performance of the parameters estimation methods was verified by employing several robustness measures. Robustness measures results proved that the Bayesian MCMC method performed better than MLE in estimating GEV parameters and future return levels. Therefore, the findings of these analyses could be helpful in adopting proper flood protection measures and designing infrastructures of culverts, buildings, bridges and dams in the region.

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Probability analysis of monthly rainfall on seasonal monsoon in Pakistan

Cited by 9 publications

References 11 publications

Quantification of the impacts of climate warming and crop management on canola phenology in Punjab, Pakistan

Quantification of the impacts of climate warming and crop management on canola phenology in Punjab, Pakistan

Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan

Modelling of Extreme Rainfall in Punjab: Pakistan Using Bayesian and Frequentist Approach

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