Impact of Climate Change on the Rice–Wheat Cropping System of Pakistan

Ahmad, Ashfaq; Ashfaq, Muhammad; Wajid, Syed Aftab; Rasul, Ghulam; AftabWajid, Syed; Khaliq, Tasneem; Rasul, Fahd; Saeed, Umer; Habib-ur-Rahman, Muhammad; Hussain, Jasmin; Baig, Irfan Ahmad; Naqvi, Syed Asif Ali; Bokhari, Syed Ahsan Ali; Ahmad, Shakeel; Naseem, Wajid; Hoogenboom, Gerrit; Valdivia, Roberto O.

doi:10.1142/9781783265640_0019

Cited by 123 publications

(81 citation statements)

References 17 publications

(21 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The Rice-Wheat systems of the Punjab in Pakistan, for example, are famously productive in utilizing monsoon rains during the wet (Kharif; May-October) season and harnessing the power of irrigation in the dry (Rabi; November-April) season (Ahmad et al 2015). The economics of this rice-wheat system is better assessed using a single driving climate model rather than attempting to stitch together rice impacts simulated with one GCM and wheat impacts simulated by another.…”

Section: Limitations and Areas For Continuing Developmentmentioning

confidence: 99%

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

Ruane

McDermid

2017

Earth Perspectives

View full text Add to dashboard Cite

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

show abstract

Section: Limitations and Areas For Continuing Developmentmentioning

confidence: 99%

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

Ruane

McDermid

2017

Earth Perspectives

View full text Add to dashboard Cite

show abstract

“…In terms of crop yields, many projections for Pakistan show that there may be declines in the yields of staple crops such as rice and wheat Zhu et al, 2013;Ahmad et al, 2015;Shakoor et al, 2015) due to a range of factors such as changed length of the growing season, though the wheat may be affected positively or negatively in different climate zones in Pakistan (Sultana et al, 2009). Adaptations such as changed sowing dates, more efficient use of water and greater research and development for higher yielding crop varieties may offset the negative impacts of climate change (Sultana et al, 2009;Yu et al, 2013;Zhu et al, 2013;Ahmad et al, 2015;Gorst et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Adaptations such as changed sowing dates, more efficient use of water and greater research and development for higher yielding crop varieties may offset the negative impacts of climate change (Sultana et al, 2009;Yu et al, 2013;Zhu et al, 2013;Ahmad et al, 2015;Gorst et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Agricultural production, water use and food availability in Pakistan: Historical trends, and projections to 2050

Kirby

Ahmad

Mainuddin

et al. 2017

Agricultural Water Management

Self Cite

117

View full text Add to dashboard Cite

“…(Bacillus thuringiensis) genotypes has caused a hesitation among farmers whether to sow it or not owing to the controversial debates regarding it's sowing windows and some other complications. It is a well-known fact that crop growth, and development are weather dependent and it is considered as the most limiting factor in crop production (Hoogenboom, 2000;Yucel and Gormus, 2002;Hussain et al, 2015). Among environmental factors temperature affects cotton growth, developmental rate and yield.…”

Section: Introductionmentioning

confidence: 99%

“…Environmental stresses mainly temperature is the main cause of yield variability among years; high day temperature followed by the higher night temperature may exacerbate this harmful effect (Lewis, 2000;Brown et al, 2003). Unforeseen periodic incidents of heat stress are projected to happen more frequently in the region (Ahmad et al, 2015). The consequence of changing weather affects the phenology, growth and development which threatens sustainable cotton production become writing on the wall.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Temporal Variation Resilience in Cotton Varieties Using Statistical Models

Habib-ur-Rahman¹

2016

PAKJAS

View full text Add to dashboard Cite

Suitable cotton variety selection is imperative to cope with temporal variations for yield enhancement and sustainability under unpredictable climatic conditions. Cotton varieties including transgenic (Bacillus thuringiensis) and non-transgenic (non Bt.) were sown from 10-March to 21-June with 20 days interval for two growing seasons (2012 and 2013) consecutively while cotton sowing after wheat harvest is normal practice at farmers' field in Cotton-Wheat cropping system of Punjab-Pakistan. Phenology, growth indices, seed cotton yield (SCY) and its heat use efficiency of varieties were estimated on daily basis by using statistical models. Seed cotton yield (SCY) was significantly correlated with crop duration exhibiting delays in planting (21-June) impact on shortening of phenophases i.e. first square, flower, boll initiation and boll opening by 8, 7, 4 and 6 days, respectively compared with 10-May planting in first season while second season advanced 0-3 days owing to deviation in frequency of cold shock <11 °C and heat stress >35 °C. Long crop cycle varieties AA-802 and IR-3701 took 6-9 days more compared to short season NIAB-112. More heat units accretion 46, 33, 20 and 13 % to switch into next phenophase (first square, flower, boll initiation and boll opening) was computed in 10-May planting than 10-March due to excessive heat stress (>40 °C) during early phenophases while reduced variations observed in later phases. Reproductive stage initiation and accumulated higher thermal time delayed in late mature varieties compared to short one with lower root mean square error (RMSE) and higher coefficient of determination (R 2 ). Significant reduction in days after planting to attain maximum LAI, CGR, TDM and SCY-heat use efficiency (HUESCY) decreased with delay in planting with good statistical indices. Less impact of cold shock and heat stress on 21-April and 10-May plantings noted while 10-March and 21-June planting had higher incidence during early growth phases. Cotton varieties MNH-886 and NIAB-9811 (NIAB-Kiran) planted 30-March to 10-May exhibited higher resilience to variable weather conditions with fostered growth potential and yield. Variety NIAB-112 seemed heat tolerant and it can be recommend for early and especially for late plating while MNH-886 and NIAB-Kiran can be adopted at farmer's field in the region for maximizing cotton production under variable environment.

show abstract

Impact of Climate Change on the Rice–Wheat Cropping System of Pakistan

Cited by 123 publications

References 17 publications

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

Agricultural production, water use and food availability in Pakistan: Historical trends, and projections to 2050

Estimation of Temporal Variation Resilience in Cotton Varieties Using Statistical Models

Contact Info

Product

Resources

About