Agricultural Drought Indices - US Department of Agriculture

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Figure 8 shows the combination of mean area, mean duration, and mean severity. Similar mean severities have been reached for different events, but with different combinations of mean area and mean duration. The 1988-1990 drought stands out for this specific drought index and threshold. Figure 9 shows the evolution of the area affected by droughts, defined here by a threshold of 5% on 3-month indices. Different drought periods like the 1976 drought, autumn 1978 drought, multiyear 1989-1990 drought, and recent 2003 drought can be identified in this chart. There are differences between the three types of droughts. For example, the soil moisture deficits were much more severe in 2003 than the precipitation deficits. Standardized drought indices are undoubtedly powerful analytical tools for characterizing events in space and time. Drought reanalysis offers identification and description of past drought events at both the local and national scale in France (Vidal et al. 2010). Figure 9. Evolution of the area affected by droughts, defined here by a threshold of 5% on 3-month indices (from Vidal et al. 2009). Conclusions There is no universal drought index and there is no uniform approach for drought monitoring in Europe. The complexity of drought indices depends on the number of parameters taken into account, and different levels of complexity can be considered. However, a focus on drought indices that offer a consistent estimation of soil water content through a realistic calculation of evapotranspiration is recommended. Rainfall-based indices are unable to estimate severe soil moisture deficits when precipitation deficit is not the only driver (2003 drought, for example). The land surface scheme approach allows explicit snowpack modeling through the computation of water and energy budgets with soil and vegetation databases. This approach is undoubtedly the way forward and is nearly mandatory in mountainous areas where snowpack modeling is a key issue. Lastly, we showed that the SPI normalization approach is not restricted to rainfall and can be applied to soil moisture. Standardized drought indices are undoubtedly powerful analytical tools for characterizing events in space and time. Drought reanalysis offers identification and description of past drought events at both the local and national scale in France. 93
References Durand, Y., E. Brun, L. Mérindol, G. Guyomarc'h, B. Lesaffre, and E. Martin. 1993. A meteorological estimation of relevant parameters for snow models. Annals of Glaciology 18:65-71. Durand, Y., G. Giraud, E. Brun, L. Merindol, and E. Martin. 1999. A computer-based system simulating snowpack structure as a tool for regional avalanche forecasting. Journal of Glaciology 45:469-484. Habets, F., A. Boone, and J.L. Champeaux. 2008. The SAFRAN-ISBA-MODCOU hydrometeorological model applied over France. Journal of Geophysical Research D06113, doi:10.1029/2007JD008548. Hahne, F. 2008. Les indices de sécheresse sur la France: recherche bibliographique et application. Météo-France. McKee, T.B., N.J. Doesken, and J. Kleist. 1993. The relationship of drought frequency and duration to time scales. Eighth Conference on Applied Climatology. American Meteorological Society, Boston. Noilhan, J. and J.F. Mahfouf. 1996. The ISBA land surface parameterisation scheme. Global and Planetary Change 13:145-159. Quintana-Seguí, P., P. Le Moigne, and Y. Durand. 2008. Analysis of near-surface atmospheric variables: Validation of the SAFRAN analysis over France. Journal of Applied Meteorology and Climatology 47:92-107. Vidal, J.-P., E. Martin, M. Baillon, L. Franchistéguy, and J.-M. Soubeyroux. 2009a. A 50-year highresolution atmospheric reanalysis over France with the Safran system. International Journal of Climatology, http://onlinelibrary.wiley.com/doi/10.1002/joc.2003/full. Vidal, J.-P., E. Martin, L. Franchistéguy, F. Habets, J.-M. Soubeyroux, M. Blanchard, and M. Baillon. 2010. Multilevel and multiscale drought reanalysis over France with the Safran- Isba-Modcou hydrometeorological suite. Hydrology and Earth System Sciences 14:459– 478. Wilhite, D.A. and M.H. Glantz. 1985. Understanding the drought phenomenon: The role of definitions. Water International 10(3):111–120. WMO. 2006. Drought monitoring and early warning: Concepts, progress and future challenges. WMO No. 1006, Geneva, Switzerland. 94
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Agricultural Drought Indices Procee
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© World Meteorological Organizatio
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Preface With the world population p
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Segura River Basin: Spanish Pilot R
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Table 3. Segura River Basin resourc
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Figure 5. Segura River Basin water
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Drought Indicator Expression After
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Table 5. Analysis of drought impact
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Even with this drought action plan
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that complicates water management b
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Understanding the nature of the haz
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Figure 2. U.S. Drought Monitor for
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Summary Drought is a creeping pheno
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Agricultural Drought—WMO Perspect
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c) CAgM-VI (Washington, USA, 1974)
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an unusually large moisture demand.
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the-clock nature of WIGOS, the anal
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and temporal variations in drought
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Support to Regional Institutions WM
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Williams, M.A.J. and R.C. Balling,
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The day after Black Sunday, an Asso
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Meteorological research at these in
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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 and 58: Monitoring Drought Risks in India w
Page 59 and 60: areas recording large incidences of
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: Figure 7. Standardized Soil Water I
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
Page 109 and 110: The 1991-95 Drought Episode A long-
Page 111 and 112: adverse climatic impacts on agricul
Page 113 and 114: Agricultural Drought Indices in the
Page 115 and 116: efers to deficiencies in surface an
Page 117 and 118: Figure 5. Time series of standardiz
Page 119 and 120: Limitations of Agricultural Drought
Page 121 and 122: Incorporating a Composite Approach
Page 123 and 124: Figure 3. Daily gridded SPI by regi
Page 125 and 126: The North American Drought Monitor:
Page 127 and 128: process (a) emulates natural cycles
Page 129 and 130: Summary Given the complexity that d
Page 131 and 132: alance models cannot be applied for
Page 133 and 134: 60 50 40 Error 30 20 Systematic Err
Page 135 and 136: In Figure 4, examples of the normal
Page 137 and 138: Figure 7. Water balance for Brazil,
Page 139 and 140: The soil water balance module in th
Page 141 and 142: Water Balance as a Tool for Agricul
Page 143 and 144: Conclusions The topics discussed pr
Page 145 and 146: Use of Crop Models for Drought Anal
Page 147 and 148: The parameters used in crop simulat
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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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