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Analyzing the long-term variability and trend of aridity in India using non-parametric approach.

Authors :
Choudhary, Akshita
Mahato, Susanta
Roy, P. S.
Pandey, Deep Narayan
Joshi, P. K.
Source :
Stochastic Environmental Research & Risk Assessment. Oct2023, Vol. 37 Issue 10, p3837-3854. 18p.
Publication Year :
2023

Abstract

Aridity is a climatic phenomenon characterized by shortage of water availability in a given time and space resulting in low moisture and reduced carrying capacity of ecosystems. It is represented by a numerical indicator known as Aridity Index (AI), a function of rainfall and temperature. Aridification is a slow and steady effect of climate change and assessing its spread and change is vital in context of global climatic variations. Aridity is predominantly significant for agrarian countries like India, where a slight rise in drylands area can have a significant impact on the economy and community sustenance. AI is an inclusive indicator of climatic conditions in most arid and semi-arid regions. It helps in identifying and interpreting large scale trend in temperature and precipitation; and thus, classifying region into different climatic classes. The present study assessed long-term AI based on precipitation and temperature data obtained from the India Meteorological Department at the resolution of 1 × 1 degree for years 1969–2017. AI is estimated as a ratio of mean precipitation to mean potential evapotranspiration, calculated using Thornthwaite method. The results highlight the trend of aridity over pan-India with Innovative Trend Analysis and Mann–Kendall test. The study concludes that there is a relatively slow, however steadily progressive drier conditions being established in most of the regions. A shift from 'Semi-arid' towards 'Arid' class appeared in central mainland. The north-eastern Himalaya showed decrease in humid conditions ('Humid' to 'Sub-humid'). The study implies that there is a rising aridity trend over the years due to changing climatic conditions. The shifts in aridity can have serious implications on agriculture, long-term water resource utilization and land use management plans. Our results have scope for future landscape management studies in drylands and better adaptation methods in arid regions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14363240
Volume :
37
Issue :
10
Database :
Academic Search Index
Journal :
Stochastic Environmental Research & Risk Assessment
Publication Type :
Academic Journal
Accession number :
172020317
Full Text :
https://doi.org/10.1007/s00477-023-02483-4