Agricultural Drought Indices - US Department of Agriculture

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Further, a year is considered a “drought year” when the area affected by moderate and severe drought either individually or together is 20-40% of the total area of the country and seasonal rainfall deficiency during the southwest monsoon season for the country as a whole is at least 10% or more. When the spatial coverage of drought is more than 40% then it is called an all-India severe drought year (www.imd.gov.in). Based on the index of percentage departure of rainfall from normal, IMD has delineated drought by subdivision since 1875. The droughts over a period of 135 years (1875-2009) have been identified and classified so far. Further, the drought-prone areas have been identified and probabilities of moderate and severe drought occurrences have also been computed by subdivision over the country (Table 1). Table 1. Subdivision frequencies of moderate and severe drought during 1875-2009 and probabilities of drought years. Sl.No. Name of subdivision Moderate Severe Total Drought probabilities (Total) % 1. Andaman & Nicobar Islands 17 0 17 13 2. Arunachal Pradsh 7 1 8 6 3. Assam & Meghalaya 5 0 5 4 4. Nagaland, Manipur, Mizoram & Tripura 12 0 12 9 5. Sub-Himalayan West Bengal 7 0 7 5 6. Gangetic West Bengal 2 0 2 1 7. Orissa 5 0 5 4 8. Bihar 12 0 12 9 9. Jharkhand 6 0 6 4 10. East Uttar Pradesh 13 1 14 10 11. West Uttar Pradesh 13 1 14 10 12. Uttarakhand 16 2 18 13 13. Haryana, Delhi & Chandigarh 21 4 25 19 14. Punjab 20 4 24 18 15. Himachal Pradesh 20 3 23 17 16. Jammu & Kashmir 21 6 27 20 17. West Rajasthan 22 12 34 25 18. East Rajasthan 18 5 23 17 19. West Madhya Pradesh 14 0 14 10 20 East Madhya Pradesh (including 12 0 12 9 Chhattisgarh) 21. Gujarat Region 17 11 28 21 22. Saurashtra & Kutch 16 15 31 23 23. Konkan & Goa 9 0 9 7 24. Madhya Maharashtra 7 2 9 7 25. Marathwada 17 1 18 13 26. Vidarbha 16 1 17 13 27. Coastal Andhra Pradesh 13 0 13 10 28. Telangana 18 0 18 13 29. Rayalaseema 20 2 22 16 30. Tamil Nadu & Pondicherry 12 0 12 9 31. Coastal Karnataka 5 0 5 4 32. North Interior Karnataka 10 0 10 7 33. South Interior Karnataka 9 0 9 7 34. Kerala 10 0 10 7 35. Lakshdweep 10 3 13 10 Data in Table 1 reveal that the arid west, namely West Rajasthan (34 cases) and Saurashtra and Kutch (31 cases), have the highest occurrences of drought. The adjoining Gujarat region, which mostly belongs to a semiarid climate, also experiences high incidences of drought (28). Other 51
areas recording large incidences of drought are Haryana, Delhi and Chandigarh, Punjab, Himachal Pradesh, and East Rajasthan in northwest India and Rayalaseema in the southern peninsula. The subhumid and humid areas of east and northeast India (Arunachal Pradesh, Assam and Meghalaya, Orissa, Gangetic West Bengal, and Jharkhand), for obvious reasons, have the lowest occurrences of drought. Based on the probabilities of occurrence of drought (percentage), the entire country has been divided (Figure 1) into chronically drought-prone areas (probability of occurrence of drought more than 20%), frequently drought-prone areas (probability of occurrence of drought 10-20%), and least drought-prone areas (probability of occurrence of drought less than 10%) (IMD 2005). Figure 1. Probability of occurrence of drought (%) and drought prone areas, 1875-2004. Figure 1 shows that West Rajasthan and the entire Gujarat State fall in the category of chronically drought-prone areas. Therefore, these areas deserve special attention for drought proofing, like evolving crop varieties resistant to moisture stress, better water management, and effective land management. East Uttar Pradesh, Uttarakhand, Haryana, Punjab, Himachal Pradesh, East Rajasthan, West Madhya Pradesh, Marathwada, Vidarbha, Telangana, Coastal Andhra Pradesh, and Rayalaseema fall in the category of frequently drought-prone areas, which can expect drought once in 6-10 years. These areas generally belong to the subhumid climate zone (IMD 2005). 52
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Agricultural Drought Indices Procee
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© World Meteorological Organizatio
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Page 7 and 8: Preface With the world population p
Page 9 and 10: Segura River Basin: Spanish Pilot R
Page 11 and 12: Table 3. Segura River Basin resourc
Page 13 and 14: Figure 5. Segura River Basin water
Page 15 and 16: Drought Indicator Expression After
Page 17 and 18: Table 5. Analysis of drought impact
Page 19 and 20: Even with this drought action plan
Page 21 and 22: that complicates water management b
Page 23 and 24: Understanding the nature of the haz
Page 25 and 26: Figure 2. U.S. Drought Monitor for
Page 27 and 28: Summary Drought is a creeping pheno
Page 29 and 30: Agricultural Drought—WMO Perspect
Page 31 and 32: c) CAgM-VI (Washington, USA, 1974)
Page 33 and 34: an unusually large moisture demand.
Page 35 and 36: the-clock nature of WIGOS, the anal
Page 37 and 38: and temporal variations in drought
Page 39 and 40: Support to Regional Institutions WM
Page 41 and 42: Williams, M.A.J. and R.C. Balling,
Page 43 and 44: The day after Black Sunday, an Asso
Page 45 and 46: Meteorological research at these in
Page 47 and 48: United States is sent to the Secret
Page 49 and 50: Palmer Drought Severity Index (PDSI
Page 51 and 52: PDSI as an operational index since
Page 53 and 54: WAOB, GIS has become an important t
Page 55 and 56: USDM as the official criteria for F
Page 57: Monitoring Drought Risks in India w
Page 61 and 62: The analysis revealed that out of 1
Page 63 and 64: Figure 3. Aridity anomaly chart of
Page 65 and 66: Figure 5. Progression of surface we
Page 67 and 68: Agricultural Drought Indices in Cur
Page 69 and 70: Meteorological and Agricultural Dro
Page 71 and 72: Palmer Drought Severity Index Adapt
Page 73 and 74: Accumulated WD and WS April 2010 Ac
Page 75 and 76: Soil Water Storage (SWS) September
Page 77 and 78: hydrological characteristics, and c
Page 79 and 80: Agricultural Drought Indices in Cur
Page 81 and 82: application of drought indices has
Page 83 and 84: The Value of Crop and Pasture Simul
Page 85 and 86: To assist, many agriculturally-spec
Page 87 and 88: change in Australia. The PDSI provi
Page 89 and 90: Mpelasoka, F.S., M.A. Collier, R. S
Page 91 and 92: supply and demand are fully taken i
Page 93 and 94: In Germany, the Deutsche Wetterdien
Page 95 and 96: creation of a system of European su
Page 97 and 98: The second index is extracted from
Page 99 and 100: Figure 7. Standardized Soil Water I
Page 101 and 102: References Durand, Y., E. Brun, L.
Page 103 and 104: Europe around the Iberian Peninsula
Page 105 and 106: The incoming rainwater and the atmo
Page 107 and 108: Figure 6. Example of SPI map for a
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The 1991-95 Drought Episode A long-
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adverse climatic impacts on agricul
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Agricultural Drought Indices in the
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efers to deficiencies in surface an
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Figure 5. Time series of standardiz
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Limitations of Agricultural Drought
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Incorporating a Composite Approach
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Figure 3. Daily gridded SPI by regi
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The North American Drought Monitor:
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process (a) emulates natural cycles
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Summary Given the complexity that d
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alance models cannot be applied for
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60 50 40 Error 30 20 Systematic Err
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In Figure 4, examples of the normal
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Figure 7. Water balance for Brazil,
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The soil water balance module in th
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Water Balance as a Tool for Agricul
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Conclusions The topics discussed pr
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Use of Crop Models for Drought Anal
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The parameters used in crop simulat
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a model for cassava and potato (Tsu
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ackground. The system’s most impo
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management. In research, however, p
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Smajstrla, A.G. 1990. Technical Man
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Monitoring Regional Drought Conditi
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Figure 2 represents the regression
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Conclusions and Discussion Several
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Experiences During the Drought Peri
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During the years 2007 and 2008, for
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Figure 6. Management simulation mod
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Figure 9. Irrigation diversions in
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References Andreu, J., Ferrer Polo,
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Table 2. MERIS spectral bands MDS N
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Figure 6. Spanish NSDIE during 2008
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References Gu, Y., J. F. Brown, J.
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Agricultural Drought Indices: Summa
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Table 1. Agricultural drought indic
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Accumulated Rainfall Deficits In an
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Heim (2002) notes that as recently
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each calendar day in the base perio
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The purpose of the climatic charact
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to compare moisture conditions at d
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Table 6. Overview of different drou
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have been adopted because of the av
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TCI = 100 (T max - T) / (T max - T
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Figure 1. The February 8, 2011, US
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8) There is a universal interest in
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Mavromatis, T. 2007. Drought index
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