Monitoring and Managing Agricultural Drought in India - Monitoring and Predicting Agricultural Drought: A Global Study - page 303

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are sent to the Ministry of Agriculture, and the Planning Commission, Gov-
ernment of India (De et al., 1997).
In addition, computer models such as the SPAW (soil-plant-air-water;
Saxton, 1989) model, CERES-millet (Ramakrishna et al., 1994), and
RANGETEK (Ross Wight, 1987) have been used in India to forecast crop
yields and droughts. The SPAW model explained up to 89% of the varia-
tion in pearl millet yields of Jodhpur district, Rajasthan:

( R 2 Y =− 45 . 38 WSI + 526 . 18 = 0 . 89 ) [23.1]

where Y is pearl millet grain yields (kg/ha). The water stress index (WSI)
varied from 0 (for a nonstressed crop) to 15 (for a crop with severe water
stress) (Rao and Saxton, 1995; Rao et al., 2000).
The RANGETEK model, based on a yield index (ratio of transpiration to
potential transpiration), could estimate moisture stress and pasture yields
within 1-13% in the case of C. ciliaris and up to 88% in the case of L.
sindicus (Rao et al., 1996; Singh and Rao, 1996). The CERES-millet model
explained 99% of variation in pearl millet grain yield (Ramakrishna et al.,
1994).

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W eather Forecasting

Short range (less than 3 days), medium range (3-10 days), and long range
(10-30 days) weather forecasts (DST, 1999) are issued by the IMD and
the National Centre for Medium Range Weather Forecast at New Delhi,
which can be used to monitor the development and persistence of drought
conditions in the country.

[303

U se of Satellite Data

Under a centrally sponsored scheme on Remote Sensing Application
Mission for Agriculture, Department of Agriculture and Cooperation, in
the Ministry of Agriculture, and the Indian Space Research Organization,
Department of Space, initiated in 1987 (Chakraborti, 2000) a national
program called the National Agricultural Drought Assessment and Moni-
toring System (NADAMS). The NADAMS was established at the National
Remote Sensing Agency, Hyderabad, in Andhra Pradesh State. Under this
system, Advanced Very High Resolution Radiometer (AVHRR) daily data
have been used since 1989 to generate biweekly composites of the nor-
malized difference vegetation index (NDVI) during the kharif season for
11 agriculturally sensitive states of India (Andhra Pradesh, Bihar, Gujarat,
Haryana, Karanataka, Maharashtra, Madhya Pradesh, Orissa, Rajasthan,
Tamil Nadu, and Uttar Pradesh).
The NDVI is a transformation of reflected radiation in the visible (0.58-
0.68 µ m) and near infrared (0.725-1.10 µ m) bands of AVHRR data and is
a function of green biomass (Thiruvengadachari, 1990; chapters 5 and 6).
These composites are included in the biweekly drought bulletins that are