Agricultural Drought Indices - US Department of Agriculture

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In Australia, an approach was developed that would capture a multitude of agricultural drought assessment methods to assist drought declarations, especially drought exceptional circumstances. This approach was pursued through the National Agricultural Monitoring System (NAMS) and appeared to contain all the requirements that would deliver scientific objectivity into the agricultural drought assessment process. Indeed, a science advisory group was included which would oversee that the “best indices and production models in Australia” (whether for rainfed cereals, pastures, or irrigated systems) were employed in order to help overcome disputes within the scientific community and between various scientific institutions regarding drought status. It is not known why NAMS has recently been discontinued. Valuable assessments have been made in Australia that show that when various drought indices are compared, especially for grazing enterprise purposes, in respect to rainfall, soil moisture, pasture growth, animal liveweight, and generated income, they will generally all identify the major droughts in the relevant regions of Australia (Stafford-Smith and McKeon 1998). However, Stafford-Smith and McKeon (1998) point out these measures may well differ in respect to ranking the more contentious droughts in which affected farmers may be very sensitive in eligibility for associated “exceptional drought” assistance (severe droughts of a 1 in 20 to 25 year occurrence). As individual grazing properties in Australia can be relatively large, these assessments on drought status will be also “dependent on assumptions about soil types and pasture condition which are quite specific to individual properties” (Stafford-Smith 2003). On the other hand, more straightforward, easily calculated drought indices and measures that are based on just rainfall or soil moisture and which can be calculated on a more universal manner appear, unfortunately, to be less closely aligned with issues of farmer hardship in Australia and maybe less relevant to application for assessment of exceptional drought assistance, to which drought indices in Australia are inexorably applied. Indeed, it has been noted that a single national measure (index) of exceptional and extreme drought is “likely to create inequity between regions” (Stafford-Smith 2003). This is especially the case of a country as large as Australia in that the timing and pattern of drought declarations is likely to differ between regions and types of agricultural land use (Stafford- Smith 2003, White and Walcott 2009). In a similar manner to that employed by Keating and Meinke (1998) in respect to assessment of agricultural drought for cereal cropping enterprises, Stafford-Smith and McKeon (1998) emphasize the need for an integrated index for application but focused on pastoral enterprise drought assessment. They applied 100-year pasture growth and animal liveweight-gain simulations (using the GRASP simulation model for pasture production) in relation to the monitoring, assessment, and declaration of droughts in Australia and recommended a form of an integrative index since information on soil moisture and pasture growth noticeably give differing results from a rainfall index alone (Stafford-Smith and McKeon 1998, White and Walcott 2009). Utilization of “Common” Single Agricultural Drought Indices To an Australian agronomist, drought tends to be defined as below-average rainfall that restricts typical plant growth for agricultural production. On the other hand, measurements of amounts of rainfall expressed as deciles are rarely questioned by drought relief agencies in terms of recognition of meteorological drought, unless a dispute on the density of rainfall gauges is raised. However, because of the widely varying nature of soils, crops, and pasture species, disputes may be initiated by farmers or different assessment agencies (usually state agencies) with other drought assessment agencies (usually federal agencies) over “which is the more reliable crop or pasture model to apply as an index in agricultural drought assessment,” especially if state governments provide their own scientific inputs, which may be at odds or even in competition for notoriety with federally produced scientific inputs—such has been the nature of state-federal politics in Australia and competition or even jealousy between scientific agencies and individuals. 77
To assist, many agriculturally-specific drought indices have been developed and proposed, based on rainfall data, soil moisture models, crop simulation models, and so forth, although, in the main, they have been found limiting for the purposes of ranking agricultural droughts for the very needs of government policy intervention, which could be a prime purpose in Australia. To assist in the identification of potential agricultural drought indices, White and Walcott (2009) compiled a remarkably useful listing of indices together with their positive attributes, weaknesses, and limitations for Australia (Table 1). Table 1. A listing of agricultural drought indices that have some application in Australia—drawn from White and Walcott 2009. Index Description Strengths Weaknesses and limitations Palmer Drought Water balance for Widely used internationally— Value questioned in Severity Index (PDSI) (Palmer 1965, 1968) droughts— potentially high value for agricultural droughts. comparisons between PDSI and soil moisture quite promising— relevance under climate change (Burke and regions with high climate variability such as Australia. Prescott (ratio) index (Prescott 1949) Hutchison Drought Severity Index (HDSI) (Smith et al. 1992) Plant growth index (McDonald 1994) Enhanced vegetation index (EVI) (Huete et al. 2002) Temperature Condition Index (TCI) (Kogan 1995) Normalized Difference Vegetation Index (NDVI) Soil moisture anomaly and recharge levels (SMA) (e.g., Potgieter et al. 2005) Vegetation Condition Index (VCI) (Kogan 1990) Periods of plant stress. Progressive index aimed at targeting agricultural droughts. Estimates the duration of the pasture growing season. Improved monitoring— less atmospheric influence. Rising leaf temperatures with plant moisture stress. Monitoring vegetation using NOAA/AVHRR data. Soil moisture index To assess the impact of changing weather on NDVI signals. Brown 2008). It’s simple— includes evaporation losses. Uses only rainfall data. An intermediate level index. Remote sensed MODIS data. Remotely sensed by NOAA AVHRR data. Remotely sensed repeatable and synoptic measurement. Highly relevant for vegetative health and agricultural production. Remotely sensed repeatable and synoptic scale measurements. Excludes transpiration losses —may be unsuited for accurately monitoring crops and losses. Omits rainfall effectiveness and temperature. Requires further evaluation— including across a wider range of agricultural ecosystems. Limited dataset— launched in 2000 as a scientific rather than operational sensor. No ability to normalize for variation in daily and seasonal meteorological conditions. Current data are best compared with long-term NDVI dataset “limited to 29 years” Limited observations of soil moisture mean that operationally it may not always be practical. The emphasis is on seasonal dryness rather than ranking extended droughts (from White and Walcott 2009) The indices listed by White and Walcott (2009) provide a remarkably useful assessment of agricultural drought indices that may lead to application for Australian needs. However, as White and Walcott (2009) note, ‘it is unlikely that a single index will be suitable for use under all conditions in Australia’. It is therefore interesting that, to a considerable extent, crop and pasture simulation modelling has overtaken application of use of agricultural drought indices due to the 78
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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)
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 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: The Value of Crop and Pasture Simul
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
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
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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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Agricultural Drought Indices - US Department of Agriculture

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