Agricultural Drought Indices - US Department of Agriculture

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Figure 3. Example of the evolution over time of LST-NDVI spaces. Time period: January 1, 2005, to June 27, 2005. Figure 4 represents the time evolution of the spatial distribution of the WDI indicator, for the time period 2004-2006. From this figure, it can be observed that this index, with variation from 0 to 1, is inversely correlated with soil moisture. The driest areas will present the highest values of WDI. Figure 4. Example of time evolution of spatial distribution of WDI, for 2004-2006. 153
Conclusions and Discussion Several authors have applied methodologies based on remote sensing and climate data for monitoring drought conditions at the regional scale, generally showing that indicators based only on meteorological data are not enough to describe the spatial patterns of droughts (Bhuiyan et al. 2006). The time monitoring of spatial distributions of indicators correlated with soil moisture and vegetation water stress, such as VTCI, TDVI, and WDI, given the strong theoretical base on which they are founded, has been shown to provide a good approximation for conditions of water stress or drought at the regional level. In the present work, it has been demonstrated that during dry conditions (less availability of soil moisture), the increase in surface temperature (involving temperature of vegetation as well as soil temperature, according to the cell) serves as a good indicator of vegetation water stress preceding the onset of drought. The response of vegetation to conditions of high temperature can occur even when the vegetation is green, because of stomatal regulation to minimize water loss through transpiration (Wan et al. 2004). This leads to a reduction in latent heat flux and, consequently, to a noticeable increase in heat flux, resulting in a rise in leaf temperature with respect to the air temperature. This increase in leaf temperature is often used to identify stress in crops. The increasingly widespread availability of satellite images allows evaluation studies to address drought conditions and impacts from remote sensing, either based on indicators correlated with soil moisture, or directly on estimates of actual evapotranspiration. Acknowledgments This work was developed in the framework of the agreement between the UPCT and the CHS, “Development of indicators of water scarcity and droughts, in the context of climate change”, and the agreement “Development of early warning system for Jucar River and Segura River Basins”, between UPCT and the General Deputy of Water, of the Ministry for the Environment, Marine and Rural Affairs. The financial support, as well as the support of Project CGL, are acknowledged. References Bhuiyan, C., R.P. Singh, and F.N. Kogan. 2006. Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data. International Journal of Applied Earth Observation and Geoinformation 8:289-302. Cihlar, J., L. St. Laurent, and J. Dyer. 1991. Relation between the Normalized Difference Vegetation Index and ecological variables. Remote Sensing of Environment 35:279-298. EC. 2009. Common Implementation Strategy for the Water Framework Directive (2000/60/EC). Technical Report – 2009 – 040, European Communities, 52 pp. Fensholt, R. and I. Sandholt. 2003. Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment. Remote Sensing of Environment 87(1):111-121. García, S.G., A. Baille, M.M. González, V. Martínez, M. Urrea, Z. Hernández, P. Nortes, and M. Tanguy. 2007. Desarrollo y aplicación de indicadores de alerta temprana frente a sequías a escala regional desde MODIS. Pages 223-229 in Proceedings Congreso de la Asociación Española de Teledetección. Hacia un mejor entendimiento de la dinámica global y regional. Moran, M.S., T.R. Clarke, Y. Inoue, and A. Vidal. 1994. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment 49:246-263. Ranjan Parida, B. 2006. Analysing the Effect of Severity and Duration of Agricultural Drought on Crop Performance Using Terra/MODIS Satellite Data and Meteorological Data. International Institute for Geo-Information Science and Earth Observation Enschede, The 154
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Agricultural Drought Indices Procee
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© World Meteorological Organizatio
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Agricultural Drought Indices Procee
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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
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The analysis revealed that out of 1
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Figure 3. Aridity anomaly chart of
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Figure 5. Progression of surface we
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Agricultural Drought Indices in Cur
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Meteorological and Agricultural Dro
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Palmer Drought Severity Index Adapt
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Accumulated WD and WS April 2010 Ac
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Soil Water Storage (SWS) September
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hydrological characteristics, and c
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Agricultural Drought Indices in Cur
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application of drought indices has
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The Value of Crop and Pasture Simul
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To assist, many agriculturally-spec
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change in Australia. The PDSI provi
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Mpelasoka, F.S., M.A. Collier, R. S
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supply and demand are fully taken i
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In Germany, the Deutsche Wetterdien
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creation of a system of European su
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The second index is extracted from
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Figure 7. Standardized Soil Water I
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References Durand, Y., E. Brun, L.
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Europe around the Iberian Peninsula
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The incoming rainwater and the atmo
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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
Page 149 and 150: a model for cassava and potato (Tsu
Page 151 and 152: ackground. The system’s most impo
Page 153 and 154: management. In research, however, p
Page 155 and 156: Smajstrla, A.G. 1990. Technical Man
Page 157 and 158: Monitoring Regional Drought Conditi
Page 159: Figure 2 represents the regression
Page 163 and 164: Experiences During the Drought Peri
Page 165 and 166: During the years 2007 and 2008, for
Page 167 and 168: Figure 6. Management simulation mod
Page 169 and 170: Figure 9. Irrigation diversions in
Page 171 and 172: References Andreu, J., Ferrer Polo,
Page 173 and 174: Table 2. MERIS spectral bands MDS N
Page 175 and 176: Figure 6. Spanish NSDIE during 2008
Page 177 and 178: References Gu, Y., J. F. Brown, J.
Page 179 and 180: Agricultural Drought Indices: Summa
Page 181 and 182: Table 1. Agricultural drought indic
Page 183 and 184: Accumulated Rainfall Deficits In an
Page 185 and 186: Heim (2002) notes that as recently
Page 187 and 188: each calendar day in the base perio
Page 189 and 190: The purpose of the climatic charact
Page 191 and 192: to compare moisture conditions at d
Page 193 and 194: Table 6. Overview of different drou
Page 195 and 196: have been adopted because of the av
Page 197 and 198: TCI = 100 (T max - T) / (T max - T
Page 199 and 200: Figure 1. The February 8, 2011, US
Page 201 and 202: 8) There is a universal interest in
Page 203 and 204: Mavromatis, T. 2007. Drought index
Page 205: Agricultural Drought Indices Procee
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