Assessing climate change impacts with downscaling techniques: A case study

Imran Hussain Mahdy 1, *, Partha Protim Roy 2 and Rafiqul Bari Kabir 3

1 Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Alurtol Road, Sylhet-3100, Bangladesh.
2 Department of Irrigation and Water Management, Sylhet Agricultural University, Alurtol Road, Sylhet-3100, Bangladesh.
3 Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Alurtol Road, Sylhet-3100, Bangladesh.
 
Review
International Journal of Science and Research Archive, 2024, 12(02), 1645–1652.
Article DOI: 10.30574/ijsra.2024.12.2.1424
Publication history: 
Received on 24 June 2024; revised on 02 August 2024; accepted on 05 August 2024
 
Abstract: 
The review focuses on the intersection of climate change, water resources, and downscaling techniques. It covers various studies that examine the impact of climate change on hydrological models, agricultural productivity, and socio-economic conditions, particularly in regions like Bangladesh and India. Key studies include the evaluation of different downscaling techniques, such as Statistical Down Scaling Model (SDSM) and Artificial Neural Networks (ANNs), to project climate variables and their effects on water resources. The review also highlights the importance of downscaling methods in providing high-resolution climate data necessary for impact assessments. Additionally, it discusses the statistical analysis of climate trends, including temperature and rainfall variability, and their implications for water management and agricultural adaptation strategies. Through a comprehensive examination of past research, the review underscores the critical need for accurate climate modeling and downscaling to mitigate adverse climate impacts and inform sustainable resource management practices. This synthesis of existing literature provides a foundation for future research and policy development aimed at enhancing climate resilience in vulnerable regions.
 
Keywords: 
Surface Air temperature; Environment; Climate Analysis; Global Climate
 
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