Agricultural Drought Indices - US Department of Agriculture

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The 2004-2005 drought that affected most of the Iberian peninsula caused losses of more than 2,500 million euros (two-thirds of it corresponding to the agricultural sector, and one-third to the cattle producing sector). Conclusions Drought is a recurrent climate hazard that affects Spain. Precipitation deficits occur in cycles of highly variable duration and spatial distribution. From a strictly climatic point of view, the SPI is very useful for its capacity of establishing, operationally and in a simple and objective way, the start of a drought period, as well as its end and intensity level. By the application of a meteorological drought monitoring scheme, based on the SPI and developed at AEMET, to two recent droughts episodes (with quite different characteristics), the system's capacity of diagnosis has been made clear, especially in long-lasting episodes ending in hydrological droughts. In addition, using observational data from different meteorological stations with precipitation volumes averaged for river basins was found useful for characterizing drought. Nevertheless, there is a need to extend this drought monitoring system to explicitly include other drought indices aimed at the specific needs of the agricultural sector and to produce drought predictions under a probabilistic approach, taking advantage of the recent developments in monthly and seasonal prediction. This chapter highlights the need to plan and develop an integrated management system of water resources in order to prevent and mitigate the negative effects of drought. References Heim, R. 2000. Drought Indices: A review. Pages 159-168 in Drought: A Global Assessment (D. Wilhite, ed.). Routledge, London. McKee, T.B., N.J. Doesken, and J. Kleist. 1995. Drought monitoring with multiple time scales. Preprints, 9th Conference on Applied Climatology, pp. 233-236. January 5-20, Dallas,Texas. McKee, T.B.; N.J. Doesken, and J. Kleist. 1993. The relationship of drought frequency and duration to time scales. Preprints, 8th Conference on Applied Climatology, pp. 179- 184.January 17-22, Anaheim, California. Mestre, A. 2005. El año hidrometeorológico 2004-2005. Revista Ambienta, MIMAM. Madrid, Noviembre 2005. Mestre, A. and V. Moreno. 2004. The operational water balance of the INM: A climate tool for the Spanish agrarian sector. 5th European Conference on Applied Climatology (ECAC). Nice, September 26-30, 2004. Mestre, A. and V. Moreno. 2008. El seguimiento de la sequía en estaciones y sobre grandes cuencas a través del uso del índice SPI. Proceedings of the XXX Scientific Meeting of the Spanish Meteorological Society (Zaragoza, 6-8 May 2008). Navarro, J.A. and J.R. Picatoste. 1998. Desarrollo de una nueva metodología para estimar de forma operativa la humedad del suelo mediante un balance hídrico. Calendario Meteorológico 1998, pages 141-152, Ministerio de Medio Ambiente. INM 1998. Peral, C., A. Mestre, and J.L. Garcia-Merayo. 2000. The drought of 1991-95 in southern Spain: Analysis, economic repercussions and response measures. Pages 367-381 in Drought: A Global Assessment (D. Wilhite, ed.). Routledge, London. 105
Agricultural Drought Indices in the Greater Horn of Africa (GHA) Countries P.A. Omondi IGAD Climate Prediction and Applications Centre (ICPAC), Nairobi, Kenya Abstract This chapter highlights some of the practical applications of agricultural drought monitoring over the Greater Horn of Africa based on the experiences gained and lessons learned on regional and national scales. The paper draws upon the longstanding and sustained efforts by the IGAD Climate Prediction and Applications Centre (ICPAC) with the drought monitoring system that has been in operation since 1989, when the Centre was established. ICPAC is a specialized institution of the Intergovernmental Authority for Development (IGAD), dealing in climate applications and disaster-related issues in the Greater Horn of Africa region. This drought monitoring system helps in detecting, early and easily, where and when a drought has occurred, and how the drought situation is slowly creeping into the sub-region. The onset and withdrawal dates of a drought can be defined clearly by this system. Also, it is useful for detecting changes in the rainfall regime. The Standardized Precipitation Index (SPI), which is an intensive measure that considers rainfall accumulation with the weighting function of time, is used on operational basis in the IGAD subregion. Introduction The Horn of Africa is prone to extreme climatic events such as droughts and floods, with severe negative impacts on the key socio-economic sectors. Natural resources (such as water, vegetation, wildlife, general flora and fauna, and biodiversity) that determine the livelihood of communities are impacted by temperature and rainfall. Thus climate variability has far-reaching implications for the livelihoods of most of the rural communities in the region. The IPCC Fourth Assessment Report (IPCC 2007a) has shown that any change in climate will have more adverse socio-economic impacts in Africa than in other parts of the world, because of the vulnerability of society and the sensitivity of the environment. Hazards such as floods, droughts, desertification, locust infestation, infectious diseases, epidemics, and resources-based armed conflicts continue to inflict loss of property, injury, death, food insecurity, health hazards, environmental degradation, poor economic performance, displacement of people, environmental refugees, and other miseries. In comparison to weather-related natural hazards such as floods and windstorm events, droughts develop slowly (Wilhite 2000). However, they are often more widespread and cause more extensive damage to the Greater Horn of Africa’s population than any other hazard. Climate change is projected to increase the risk of drought over many parts of Africa in the 21st century (IPCC 2007b), partly through altering the frequency of El Niño events. Drought impacts are often aggravated by poor policies, or, alternatively, conflicts over limited water, food, and grazing resources. Therefore, drought particularly affects societies that have little resilience and preparedness. Here, the effects can linger for years after the drought event. The Intergovernmental Authority on Development (IGAD) Climate Prediction and Applications Centre (ICPAC) is a specialized institution of the seven IGAD countries (Figure 1a) in the Greater Horn of Africa plus Tanzania, Burundi, and Rwanda (Figure 1b). ICPAC is charged with the responsibility of climate monitoring, prediction, early warning, and applications for the reduction of climate-related risks in its member countries. This is in support of specific sector applications for the mitigation of climate variability impacts, alleviation of poverty, management of the environment, and sustainable development over the IGAD sub-region. 106
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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
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Palmer Drought Severity Index (PDSI
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PDSI as an operational index since
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WAOB, GIS has become an important t
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USDM as the official criteria for F
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Monitoring Drought Risks in India w
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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
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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.
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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: adverse climatic impacts on agricul
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
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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
Page 149 and 150: a model for cassava and potato (Tsu
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Page 161 and 162: 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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