Agricultural Drought Indices - US Department of Agriculture

More documents

Recommendations

Info

where Dη is the hydraulic diffusivity; Kη the hydraulic conductivity; z the depth of layer; and Sη the water uptake by roots, estimated as a functional relation among soil moisture in the layer, its field capacity and wilting point, and ETP. ETP is calculated by the Thornthwaite (1948) method. This water balance model also takes into account the effective rainfall estimated by satellite; variation of SWHC for different types of soil, classified by texture classes; leaf area index from satellite images; and runoff. The performance of this model was tested with data from the ABRACOS/LBA project, for pastures and forests in the Amazon region of Brazil. The results obtained by Gevaerd and Freitas (2006) showed moderate accuracy and high precision, as can be seen in the regression analyses presented below: a) for pasture: SWS est = 0.65 SWS obs + 186 and R 2 = 0.82 b) for forest : SWS est = 0.87 SWS obs + 52 and R 2 = 0.90 where SWS est is the estimated soil water storage and SWS obs the observed soil water storage, during the ABRACOS field experiment. An example of the maps produced with this kind of technique is presented for two different soil layers, from 0 to 19 cm and from 0 to 75 cm (Figure 10). The results are impressive since this model allows determining soil moisture for all South America, with a resolution of 5 km, giving a general view of the availability of water in different regions of the country, based on surface and satellite information. Figure 10. Soil moisture for different soil depths (19 cm – left side and 75 cm – right side) as determined by the Gevaerd and Freitas (2006) model. Source: http://agricultura.cptec.inpe.br/. 133
Water Balance as a Tool for Agricultural Drought Monitoring Several agricultural drought indices in current use are based on information provided by the water balance models. Some of these indices are listed below, showing how the water balance outputs are used as inputs for them. Accumulated Water Deficiency Index (AWDI): This index is simply the sum of the water deficiency during the drought period. Water deficiency is calculated as the difference between ETP and ETa. The method to estimate these two variables can vary, and the results will vary proportionally. The most common procedure to determine water deficiency is through Thornthwaite and Mather’s water balance model, with ETP calculated by Thornthwaite (1948). However, the ETP method can be changed to produce more reliable results, since the Thornthwaite model used to underestimate ETP during the dry periods (Sentelhas et al. 2008). Relative soil moisture index (RSMI): This index is given by the relationship between actual soil water storage (SWS) and soil water holding capacity (SWHC), in percentage: RSMI = SWS / SWHC (17) Relative Water Deficiency Index (RWDI): This index is the water deficiency expressed in percentage, in relation to ETP: WDI = (1 – ETa/ETP) * 100 (18) Crop Moisture Index (CMI): This index is based on the difference between the observed ETa (ETa obs ) and the expected ETa (ETa exp ) for the period and was proposed by Palmer (1968) as a simple way for monitoring crop conditions: CMI = ETa obs – ETa exp (19) Observed ETa is provided by the serial climatological water balance of Thornthwaite and Mather (1955), whereas expected ETa is the climatological value for the period. Crop Water Development Index (CWDI): This index is based on soil moisture calculated by the water balance, according to the following calculations: • Crop water deficit factor (CWDF): CWDF = SWS/SWHC (20) • Crop water development index (CWDI): CWDI = (CWDF/0.4) – 1 (21) • Accumulated CWDI (ACWDI): ACWDI = ∑ [CWDI / (n * 1.5)] (22) The classes of ACWDI are presented in Table 1, showing the relationship between ACWDI and crop development conditions. 134
Page 1 and 2:
Agricultural Drought Indices Procee
Page 3 and 4:
© World Meteorological Organizatio
Page 5 and 6:
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 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 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
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: The soil water balance module in th
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 and 160: Figure 2 represents the regression
Page 161 and 162: Conclusions and Discussion Several
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:
show all

Agricultural Drought Indices - US Department of Agriculture

Create successful ePaper yourself

Delete template?

Save as template?