Multi-model projections of future climate and climate change impacts uncertainty assessment for cotton production in Pakistan

Habib-ur-Rahman, Muhammad; Ahmad, Ashfaq; Wang, Xuechun; Wajid, Aftab; Nasim, Wajid; Hussain, Muhammad Arshad; Ahmad, Bashir; Ahmad, Ishfaq; Ali, Zulfiqar; Ishaque, Wajid; Awais, Muhammad; Shelia, Vakhtang; Ahmad, Shakeel; Fahd, Shah; Alam, Mukhtar; Ullah, Hidayat; Hoogenboom, Gerrit

doi:10.1016/j.agrformet.2018.02.008

Cited by 207 publications

(81 citation statements)

References 70 publications

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“…The impact of climate change is becoming harsh due to frequent extreme weather events [23,24]. It is imperative to evaluate crops for resilience against harsh climatic conditions by sustaining yields and soil fertility with efficient nutrient management [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan

et al. 2020

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Low planting density and deficient nitrogen application are factors that significantly decrease the yield of pearl millet in Pakistan. Optimizing their management is imperative in increasing millet production efficiency, especially with N fertilization, which can strongly affect hybrid millet response. Therefore, a field experiment was conducted at the Agronomic Research Area, University of Agriculture, Faisalabad (semi-arid) and the Agronomic Research Station, Karor Lal Eason, District Layyah (arid) over two summer seasons (2015 and 2016). The experiment consisted of three intra-row spacings (10, 15, and 20 cm) as main plots, while four nitrogen rates (0, 150, 200, and 250 kg ha−1) were randomized in subplots. The treatments were triplicated each year at both locations. The results depicted a significant change in millet crop development with a change in planting density and nitrogen rate in semi-arid and arid environments. The decrease in planting density resulted 1–2 day(s) delay in 50% flowering, milking, and maturity in semi-arid and arid region during both years of study. Higher dry matter accumulation was observed at medium planting density (15 cm intra-row spacing) and higher levels of nitrogen (250 kg ha−1) at both locations and growing seasons. The yield and attributed yield performed well with 15-cm plant spacing coupled with N application from 150–200 kg ha−1, and resulted in high nitrogen use efficiency (NUE). The results of the quadratic relationship and economic analysis linked with yield and nitrogen levels at 15-cm spacing showed 176 and 181 kg N ha−1 optimum levels (mean of years) against the economic N levels of 138 and 137 kg N ha−1 for Faisalabad and Layyah, respectively. The benefit–cost ratio (BCR) showed 31% and 45% mean excessive N at 200 and 250 kg N ha−1, in Faisalabad and Layyah, respectively. So, it is concluded that the optimum economic level of N should be sought out according to the soil and climate of an area for the production of hybrid pearl millet on a sustainable basis.

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Section: Introductionmentioning

confidence: 99%

Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan

et al. 2020

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“…The study was conducted for data sparse region of Pakistan, located in subtropical zone of southern Asia. Climatic conditions of Pakistan are semiarid with hot summers and mild winters (Ahmad et al, 2018). The entire region of Pakistan was divided into 10 km × 10 km grids with a total 8188 grids to take into account the soil and climatic spatial heterogeneity.…”

Section: Description Of Study Areamentioning

confidence: 99%

“…Climate change is threatening agriculture and food security globally ( Lipper et al, 2014;Lobell and Gourdji, 2012;Moorhead, 2009). Variations in temperature and uneven distribution of precipitation, negatively impact the crop production (Ahmed et al, 2018;Asseng et al, 2015a;Rahman et al, 2018;Ullah et al, 2019a). Future climate projections indicate that the global surface temperature is expected to increase by 0.8°C to 1.2°C between 2030 to 2052, resulting in decrease in agriculture productivity (IPCC, 2013).…”

Section: Introductionmentioning

confidence: 99%

Implications of 1.5 and 2.0 ºC additional warming for wheat yield using a gridded modeling approach

Fahad

Ahmad

Athar

2020

ATM

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The goal of limiting the increasing global mean temperature below 2.0°C and possibly to 1.5°C, was decided in Paris Agreement in 2015. It is therefore important to understand the climate risk and impacts associated with 1.5°C and 2.0°C additional warming scenarios. The current study investigates the impacts of 1.5°C and 2.0°C additional warming on wheat yield in Pakistan using a gridded modeling approach. The generated climate data by four GCMs under 1.5°C and 2.0°C were acquired from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) scenarios group. The CERES-Wheat model was calibrated and evaluated using the field data and then applied to the entire region of Pakistan. Model calibration results showed a close association between observed and simulated wheat yield with an error ranging from 0.52 to 1.36%. Climate change projections indicated that the mean temperature is expected to rise by 0.46°C in 1.5°C and 1.44°C in 2.0°C additional warming scenarios in the GCMs. The spatial variations of precipitation ranges from-22.4 to 42.6% and 4.6 to 34.1% under 1.5°C and 2.0°C HAPPI scenarios, respectively. Higher precipitation was recorded in northern Pakistan as compared to central and southern Pakistan. The projected changes in temperature and precipitation will decrease the wheat yield by 3.2% and 4.7% in Punjab, 17.8% and 13.8% in Sindh province under 1.5°C and 2.0°C additional warming, respectively. However, the wheat yield will increase by 4.7% and 13% in KP, 9.4% and 15.3% in Baluchistan under 1.5°C and 2.0°C additional warming, respectively.

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“…The increase in temperature altered the phenology of crop i.e. leaf development, anthesis, harvest, fruit production and in asynchrony between anthesis and pollinators [7]. The rise in temperature also resulted in high respiration rates, reduction in pollen germination, shorter grain filling period, lesser biomass production and low yields.…”

Section: Climate Change Profile Of Pakistanmentioning

confidence: 99%

“…Climate resilience is quite resemblance to vulnerability and commonly defined as "the ability to bounce back after an external shock or stress". Resilience of a system can also be illustrated through its components including system disturbance, maintaining system & control and returning to stable state [6,7]. Agriculture system is affected by extreme weather events associate with climate change, therefore adaptative measures are needed to mitigate the negative impacts of climate change.…”

Section: Introductionmentioning

confidence: 99%

Climate Smart Interventions of Small-Holder Farming Systems

Ullah¹,

Ahmad²,

Habib-ur-Rehman³

et al. 2019

Climate Change and Agriculture

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Agriculture is very vulnerable to temperature and drought in semi-arid and arid regions. Farming communities are especially vulnerable to the potential impact of climate change on crop and livestock. For Pakistan, a potential increase of 2.8°C for the maximum day temperature and 2.2°C decrease in night temperature by the midcentury has been reported. The goal of this chapter is to introduce climate-smart interventions as mitigation and adaptation strategies coupled with crop diversification through the introduction of climate resilient crops in existing cropping systems. Firstly, it describes the impacts of climate change in context to current food security situation in Pakistan and, secondly, potential climate smart interventions to combat changes in the country. Crop models, their application for developing adaptations, modeling technique and its integration with breeding, remote sensing and its application, policy interventions and resource smart interventions in context to changing climate are imperative means to favor the farming community in future farming. Introducing climate resilient crops can be rescued and recognized in dry and hot areas of Pakistan using climate smart interventions and resource use efficiency may be determined with the aid of computer and decision support IT tools in resource inefficient areas.

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Multi-model projections of future climate and climate change impacts uncertainty assessment for cotton production in Pakistan

Cited by 207 publications

References 70 publications

Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan

Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan

Implications of 1.5 and 2.0 ºC additional warming for wheat yield using a gridded modeling approach

Climate Smart Interventions of Small-Holder Farming Systems

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