Examining the Impacts of Recent Water Availability on the Future Food Security Risks in Pakistan Using Machine Learning Approaches DOI Open Access
Wilayat Shah, Junfei Chen, Irfan Ullah

et al.

Water, Journal Year: 2024, Volume and Issue: 17(1), P. 55 - 55

Published: Dec. 28, 2024

Food and water security are critical challenges in Pakistan, exacerbated by rapid population growth, climate variability, limited resources. This study explores the application of machine learning techniques to address these issues. We specifically examine dimensions food employing data-driven methods enhance crop yield predictions, production forecasting, resource management. Using secondary data, we refine models, such as random forest linear regression, analyze availability, yield, production. These models aim optimize distribution, improve irrigation efficiency, minimize waste. propose developing AI-based predictions crises proactively. Our findings indicate that insecurity persists worsened uneven distribution. Given country’s high dependence on for production, impact growth demand. recommend a comprehensive strategy includes infrastructure development, improved use efficiency agriculture, policy adjustments balance imports exports.

Language: Английский

Attributing rainfall and drought variability across climate vulnerable area of Pakistan: Perspective from different satellite and ground-based datasets DOI
Mohammad Ilyas Abro, Ehsan Elahi,

Murad Ali Khaskheli

et al.

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(2)

Published: Jan. 10, 2025

Language: Английский

Citations

1

Comparative study of multiple algorithms classification for Land Use and Land Cover Change Detection and its impact on local climate of Mardan District, Pakistan DOI Creative Commons

Farnaz,

Narissara Nuthammachot, Muhammad Ali

et al.

Environmental Challenges, Journal Year: 2024, Volume and Issue: unknown, P. 101069 - 101069

Published: Dec. 1, 2024

Language: Английский

Citations

4

How Significant is Projected Drought Risk in Pakistan Under a Warmer Climate? DOI
Irfan Ullah, Xin‐Min Zeng, Sidra Syed

et al.

Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Language: Английский

Citations

0

Agricultural productivity under climate change vulnerability: does carbon reduction paths matter for sustainable agriculture? DOI
Syed Rashid Ali, Nooreen Mujahid

Environment Development and Sustainability, Journal Year: 2025, Volume and Issue: unknown

Published: March 8, 2025

Language: Английский

Citations

0

Elevation‐dependent warming and possible‐driving mechanisms over global highlands DOI
Haider Abbas, Mojolaoluwa Toluwalase Daramola,

Ming Xu

et al.

International Journal of Climatology, Journal Year: 2024, Volume and Issue: 44(12), P. 4157 - 4177

Published: Sept. 7, 2024

Abstract Elevation‐dependent warming (EDW) has been a topic of intense debate due to limited observed data in global highland areas. This study aims fill this gap by utilizing CRU and ERA5 datasets from 1981 2021 explore the trends climate change its elevation dependency. The anomalies temperature indicators ( T mean , max min ) both showed significant over highlands. Moreover, response across highlands is not spatially uniform. linear regression model based on signals for at various elevations On regional scale, predominantly EDW EU highlands, while Asian exhibited 4–5 km. 2.5–5.5 km with 3–5 CRU. In Andes, was prominent 2.5–4 Overall, are evident all studied regions but vary them. While assessing driving factors, results indicate that total column water vapour (TCWV), snow depth (SD), albedo, normalized difference vegetation index (NDVI) correlated positively indicators. These findings emphasize significance elevation‐specific interactions between environmental factors forecasting changes mountainous Additionally, coherence teleconnection indices Atlantic Pacific Oceans. European (EU) interzonal Oceans, North American (NA) coherence, followed South (SA) provide comprehensive understanding implications globally, including potential more severe depletion snow/ice resources warmer future.

Language: Английский

Citations

1

Examining the Impacts of Recent Water Availability on the Future Food Security Risks in Pakistan Using Machine Learning Approaches DOI Open Access
Wilayat Shah, Junfei Chen, Irfan Ullah

et al.

Water, Journal Year: 2024, Volume and Issue: 17(1), P. 55 - 55

Published: Dec. 28, 2024

Food and water security are critical challenges in Pakistan, exacerbated by rapid population growth, climate variability, limited resources. This study explores the application of machine learning techniques to address these issues. We specifically examine dimensions food employing data-driven methods enhance crop yield predictions, production forecasting, resource management. Using secondary data, we refine models, such as random forest linear regression, analyze availability, yield, production. These models aim optimize distribution, improve irrigation efficiency, minimize waste. propose developing AI-based predictions crises proactively. Our findings indicate that insecurity persists worsened uneven distribution. Given country’s high dependence on for production, impact growth demand. recommend a comprehensive strategy includes infrastructure development, improved use efficiency agriculture, policy adjustments balance imports exports.

Language: Английский

Citations

0