260
Brown JF, Wardlow BD, Tadesse T, Hayes MJ, Reed BC (2008) The vegetation drought response
index (VegDRI): a new integrated approach for monitoring drought stress in vegetation. GISci
Remote Sens 45:16–46. https://doi.org/10.2747/1548-1603.45.1.16
Chatterjee S, Khan A, Akbari H, Wang Y (2016) Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901–2002), West Bengal, India. Atmos Res
182:54–75. https://doi.org/10.1016/j.atmosres.2016.07.010
Cornish PS, Avijit C, Ashok K, Sudipta D, Kuntalika K, Shane N, Shivendra K (2015) Improving
crop production for food security and improved livelihoods on the East India Plateau II. Crop
options, alternative cropping systems and capacity building. Agric Syst 137:180–190. https://
doi.org/10.1016/j.agsy.2015.02.011
Dash SS, Sahoo B, Raghuwanshi NS (2019) A SWAT-Copula based approach for monitoring and
assessment of drought propagation in an irrigation command. Ecol Eng 127:417–430. https://
doi.org/10.1016/j.ecoleng.2018.11.021
Datta P, Das S (2018) Analysis of long-term precipitation changes in West Bengal, India: an
approach to detect monotonic trends influenced by autocorrelations. Dyn Atmos Oceans 88.
https://doi.org/10.1016/j.dynatmoce.2019.101118
Dunn JA, Dey AK (1942) The geology and petrology of eastern Singhbhum and surrounding areas.
Geol Surv India Mem (Hyderabad) 69:281–456
Dutta D, Patel NR, Kundu A (2011) Analyzing the performance of auto regressive integrated moving average (ARIMA) model for predicting agricultural productivity in eastern Rajasthan. Res
J Agric Sci 2:555–559
Dutta D, Kundu A, Patel NR (2013) Predicting agricultural drought in eastern Rajasthan of India
using NDVI and standardized precipitation index. Geocarto Int 28(3):192–209. https://doi.
org/10.1080/10106049.2012.679975
Dutta D, Kundu A, Patel NR, Saha SK, Siddiqui AR (2015) Assessment of agricultural drought
in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and
Standardized Precipitation Index (SPI). Egypt J Remote Sens Space Sci 18(1):53–63. https://
doi.org/10.1016/j.ejrs.2015.03.006
Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison
L, Hoell A, Michaelsen J (2015) The climate hazards infrared precipitation with stations—a
new environmental record for monitoring extremes. http://www.nature.com/sdata/, https://doi.
org/10.1038/sdata.2015.66
Ganapuram S, Nagarajan R, Sehkar GC, Balaji V (2014) Spatiotemporal analysis of droughts in
the semi-arid Pedda Vagu and Ookacheti Vagu watersheds, Mahabubnagar District, India. Arab
J Geosci 8:6911–6929. https://doi.org/10.1007/s12517-014-1696-70
Ghosh KG (2018) Geo-statistical assessment of the intensity, duration, frequency and trend of
drought over Gangetic West Bengal, Eastern India. Top Hydrometerol:64–81. https://doi.
org/10.5772/intechopen.80037
Gu Y, Brown JF, Verdin JP, Wardlow B (2007) A five-year analysis of MODIS NDVI and NDWI
for grassland drought assessment over the central great plains of the United States. Geophys
Res Lett 34(6):186–192. https://doi.org/10.1029/2006GL029127
Haldar S, Saha P (2015) Identifying the causes of water scarcity in Purulia, West Bengal, India – a
geographical perspective. IOSR J Environ Sci Toxicol Food Technol 9(8)I:41–51
Jha S, Das J, Sharma A, Hazra B, Goyal MK (2019) Probabilistic evaluation of vegetation drought
likelihood and its implications to resilience across India. Glob Planet Chang 176:23–25. https://
doi.org/10.1016/j.gloplacha.2019.01.014
Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15:91–100. https://doi.org/10.1016/0273-1177(95)00079-T
Kundu A, Denis DM, Dutta D (2016) Spatial pattern of agricultural drought using NOAA-AVHRR
derived vegetation indices, remote sensing for natural resources monitoring and management,
Gaur M, Pandey CB, Goyal RK (eds). Scientific Publishers (India)
Lu J, Carbone GJ, Gao P (2017) Detrending crop yield data for spatial visualization of drought
impacts in the United States, 1895–2014. Agric For Meteorol 237–238:196–208. https://doi.
org/10.1016/j.agrformet.2017.02.001
NADAMS (1989). https://farmer.gov.in
M. Dey et al.
Brown JF, Wardlow BD, Tadesse T, Hayes MJ, Reed BC (2008) The vegetation drought response
index (VegDRI): a new integrated approach for monitoring drought stress in vegetation. GISci
Remote Sens 45:16–46. https://doi.org/10.2747/1548-1603.45.1.16
Chatterjee S, Khan A, Akbari H, Wang Y (2016) Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901–2002), West Bengal, India. Atmos Res
182:54–75. https://doi.org/10.1016/j.atmosres.2016.07.010
Cornish PS, Avijit C, Ashok K, Sudipta D, Kuntalika K, Shane N, Shivendra K (2015) Improving
crop production for food security and improved livelihoods on the East India Plateau II. Crop
options, alternative cropping systems and capacity building. Agric Syst 137:180–190. https://
doi.org/10.1016/j.agsy.2015.02.011
Dash SS, Sahoo B, Raghuwanshi NS (2019) A SWAT-Copula based approach for monitoring and
assessment of drought propagation in an irrigation command. Ecol Eng 127:417–430. https://
doi.org/10.1016/j.ecoleng.2018.11.021
Datta P, Das S (2018) Analysis of long-term precipitation changes in West Bengal, India: an
approach to detect monotonic trends influenced by autocorrelations. Dyn Atmos Oceans 88.
https://doi.org/10.1016/j.dynatmoce.2019.101118
Dunn JA, Dey AK (1942) The geology and petrology of eastern Singhbhum and surrounding areas.
Geol Surv India Mem (Hyderabad) 69:281–456
Dutta D, Patel NR, Kundu A (2011) Analyzing the performance of auto regressive integrated moving average (ARIMA) model for predicting agricultural productivity in eastern Rajasthan. Res
J Agric Sci 2:555–559
Dutta D, Kundu A, Patel NR (2013) Predicting agricultural drought in eastern Rajasthan of India
using NDVI and standardized precipitation index. Geocarto Int 28(3):192–209. https://doi.
org/10.1080/10106049.2012.679975
Dutta D, Kundu A, Patel NR, Saha SK, Siddiqui AR (2015) Assessment of agricultural drought
in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and
Standardized Precipitation Index (SPI). Egypt J Remote Sens Space Sci 18(1):53–63. https://
doi.org/10.1016/j.ejrs.2015.03.006
Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison
L, Hoell A, Michaelsen J (2015) The climate hazards infrared precipitation with stations—a
new environmental record for monitoring extremes. http://www.nature.com/sdata/, https://doi.
org/10.1038/sdata.2015.66
Ganapuram S, Nagarajan R, Sehkar GC, Balaji V (2014) Spatiotemporal analysis of droughts in
the semi-arid Pedda Vagu and Ookacheti Vagu watersheds, Mahabubnagar District, India. Arab
J Geosci 8:6911–6929. https://doi.org/10.1007/s12517-014-1696-70
Ghosh KG (2018) Geo-statistical assessment of the intensity, duration, frequency and trend of
drought over Gangetic West Bengal, Eastern India. Top Hydrometerol:64–81. https://doi.
org/10.5772/intechopen.80037
Gu Y, Brown JF, Verdin JP, Wardlow B (2007) A five-year analysis of MODIS NDVI and NDWI
for grassland drought assessment over the central great plains of the United States. Geophys
Res Lett 34(6):186–192. https://doi.org/10.1029/2006GL029127
Haldar S, Saha P (2015) Identifying the causes of water scarcity in Purulia, West Bengal, India – a
geographical perspective. IOSR J Environ Sci Toxicol Food Technol 9(8)I:41–51
Jha S, Das J, Sharma A, Hazra B, Goyal MK (2019) Probabilistic evaluation of vegetation drought
likelihood and its implications to resilience across India. Glob Planet Chang 176:23–25. https://
doi.org/10.1016/j.gloplacha.2019.01.014
Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15:91–100. https://doi.org/10.1016/0273-1177(95)00079-T
Kundu A, Denis DM, Dutta D (2016) Spatial pattern of agricultural drought using NOAA-AVHRR
derived vegetation indices, remote sensing for natural resources monitoring and management,
Gaur M, Pandey CB, Goyal RK (eds). Scientific Publishers (India)
Lu J, Carbone GJ, Gao P (2017) Detrending crop yield data for spatial visualization of drought
impacts in the United States, 1895–2014. Agric For Meteorol 237–238:196–208. https://doi.
org/10.1016/j.agrformet.2017.02.001
NADAMS (1989). https://farmer.gov.in
M. Dey et al.