Your search found 3 records
1 Khan, N. A.. 1998. Environmental management of water pollution. In Khan, A. F. (Ed.), Water resource management: Thrust and challenges. New Delhi, India: Anmol Publications Pvt. Ltd. pp.151-156.
(Location: IWMI-HQ Call no: 333.91 G635 KHA Record No: H022556)
2 Khan, N. A.. 1998. Controlling water pollution in India. In Khan, A. F. (Ed.), Water resource management: Thrust and challenges. New Delhi, India: Anmol Publications Pvt. Ltd. pp.219-223.
(Location: IWMI-HQ Call no: 333.91 G635 KHA Record No: H022560)
3 Khan, N. A.; Qiao, J.; Abid, M.; Gao, Q. 2021. Understanding farm-level cognition of and autonomous adaptation to climate variability and associated factors: evidence from the rice-growing zone of Pakistan. Land Use Policy, 105:105427. (Online first) [doi: https://doi.org/10.1016/j.landusepol.2021.105427]
Climate change adaptation ; Strategies ; Farmers' attitudes ; Climate-smart agriculture ; Rice ; Nonfarm income ; Access to information ; Temperature ; Rainfall patterns ; Risk ; Tube wells ; Irrigation canals ; Socioeconomic environment ; Models / Pakistan / Punjab
(Location: IWMI HQ Call no: e-copy only Record No: H050303)
(2.05 MB)
This study was conducted in the rice-growing zone of Punjab province, where rice production is affected by climate variabilities. The study aimed to assess farmers' perception of and adaptation to climate variability and its associated factors. Cross-sectional data of 480 rice growers was collected from the four rice-growing districts in Punjab using a multi-stage sampling approach. A multivariate probit model is used to analyze the determinants of farmers' adaptation decisions, and an ordered probit model is employed to estimate the factors affecting adaptation intensity. We find that farmers perceived significant changes in local climate, i.e., increase in summer temperature, decrease in summer rainfall, and changing pattern of rainfall and winter cropping season. Rice growers applied supplementary irrigation, changed rice cultivation dates, considered fertilizer management and crop diversification, and changed crop varieties as adaptation strategies to cope with climatic variability. The results of the multivariate probit model indicate farmers' age, farm size, availability of water resources, livestock ownership, off-farm income, and access to farm advisory services, credit, and climate information as significant determinants of adaptation strategies. The ordered probit model shows a positive and significant effect of farmers' education level and availability of irrigation water, farm labor, credit, farm advisory services, and climate information on adaptation intensity. The findings identify lack of water resources, financial constraints, and limited advisory services as key barriers to adaptation. This study suggests that the government should adopt a proactive approach to support farming communities to adapt to climate variability through improved access to water resources, advisory services, and credit services.
Powered by DB/Text WebPublisher, from
