4.6 Article

Long-term agricultural performance and climate variability for drought assessment: a regional study from Telangana and Andhra Pradesh states, India

期刊

GEOMATICS NATURAL HAZARDS & RISK
卷 8, 期 2, 页码 822-840

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/19475705.2016.1271831

关键词

Agriculture drought; NDVI; crop area; crop growth; precipitation; irrigation

资金

  1. Department of Science and Technology (Government of India) [NRDMS/11/1717/010]
  2. National Academy of Sciences, India, Government of India
  3. NASI, Senior Platinum Jubliee Fellow Program [NAS/597/12/2012-13]

向作者/读者索取更多资源

A novel approach is presented to assess the agriculture performance in the states of Telangana and Andhra Pradesh using long-term fortnightly satellite, meteorological and irrigation data-sets. National Oceanic and Atmospheric Administration (NOAA), Global Inventory Modeling and Mapping Studies (GIMMS) and Normalized Difference Vegetation Index (NDVI) data for the period 1982-2000 were used to study the pattern of anomalies in the NDVI anomalies and Standardized Precipitation Index (SPI) in the agriculture areas to capture the drought events. After hierarchical image classification and field observations, the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI product was used to generate the cropped area. The deviation of the NDVI (NDVIDev) was used to understand the agricultural growth/stress, variations in the cropped area and per cent fluctuation in space and time. The SPI, derived from the rainfall data pertaining to 2000-2015, was used to determine the distribution of precipitation. The crop area (%) and growth conditions during the different cropping seasons agree well with the prevailing drought conditions. A significant (p < 0.05) relation was found between the NDVI and precipitation in the summer monsoon each year except during excellent summer monsoon year. The seasonal precipitation, residual soil moisture and source of irrigation were also found to have significant (p < 0.05) impacts on the winter and summer crops.

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