On prediction of droughts in the Indian arid region

Autor: Y. S. RAMA KRISHNA, A. S. R. A. S. SASTRI, G. G. S. N. RAO, B. V. RAMANA RAO
Rok vydání: 1984
Předmět:
Zdroj: MAUSAM. 35:349-354
ISSN: 0252-9416
1901-1970
Popis: Drought is a recurring feature in the arid regions and prediction of droughts has got great relevance with respect to planning for afforestation, sand dune stabilisation, establishment of grasslands etc. Some attempts have been made at the Central Arid Zone Research Institute, Jodhpur to develop techniques for prognostication of droughts in the Indian arid region on the basis of climatic fluctuation., and variability. The climatic spectrum of the Indian arid region extends from extremely arid to semi-arid conditions. Through application of the theory of conditional probabilities based on first order Markov chain model, the climatic fluctuations during the years 1901-1970 were studied. It was observed that the occurrence of extreme arid conditions in the succeeding year could be predicted with 92 per cent confidence while climatic types can be predicted with 83 per cent confidence. Drought incidence may not be affecting whole of the region simultaneously and some parts might experience localised droughts. However, in some years the whole region experienced drought conditions and studies reveal that even In such years the drought intensity and its time of occurrence varied from region to region. Studies on the incidence and spread of droughts over western Rajasthan indicate that drought condition originate first in the northeastern region, during the month of July spread in a south-westerly direction during the month of August and dissipate with an easterly movement in the month of September. This pattern is observed to repeat during the years of. severe drought. In the present paper, the applicability of the above techniques have been discussed. Long range prediction of droughts is not yet possible with 100 per cent confidence. Therefore, a combination approach using different techniques might provide the necessary confidence in prediction of droughts.
Databáze: OpenAIRE
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