An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data

International Journal of Applied Earth Observation and Geoinformation

Volumn 48, Issue , 2016, Pages 74-84

  Carrão, Hugo ^a   Russo, Simone ^a   Sepulcre Canto, Guadalupe ^a,b   Barbosa, Paulo ^a  

^a JOINT RESEARCH CENTRE   (Italy)

^b UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

Author keywords

Agricultural drought; Crop yield; Remote sensing based index; Soil moisture; South Central America

Indexed keywords

CROP YIELD; DROUGHT; EMPIRICAL ANALYSIS; PROBABILITY DENSITY FUNCTION; REMOTE SENSING; SATELLITE DATA; SOIL MOISTURE;

CENTRAL AMERICA; SOUTH AMERICA;

GLYCINE MAX; TRITICUM AESTIVUM; ZEA MAYS;

EID: 85015897968     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2015.06.011     Document Type: Article

References (88)

1. Albergel, C., Dorigo, W., Reichle, R.H., Balsamo, G., de Rosnay, P., Muoz-Sabater, J., Isaksen, L., de Jeu, R., Wagner, W., Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing. J. Hydrometeor. 14 (2013), 1259–1277.
2. Bacour, C., Bron, F.-M., Maignan, F., Normalization of the directional effects in NOAA–AVHRR reflectance measurements for an improved monitoring of vegetation cycles. Remote Sens. Environ. 102 (2006), 402–413.
3. Beck, P.S., Atzberger, C., Hgda, K.A., Johansen, B., Skidmore, A.K., Improved monitoring of vegetation dynamics at very high latitudes: a new method using {MODIS} {NDVI}. Remote Sens. Environ. 100 (2006), 321–334.
4. Bouezmarni, T., Ghouch, A.E., Mesfioui, M., Gamma kernel estimators for density and hazard rate of right-censored data. J. Prob. Stat., 2011 Article ID 937574.
5. Brown, J., Wardlow, B., Tadesse, T., Hayes, M., Reed, B., The vegetation drought response index (VegDRI): a new integrated approach for monitoring drought stress in vegetation. GISci. Remote Sens. 45 (2008), 16–46.
6. Caccamo, G., Chisholm, L.A., Bradstock, R.A., Puotinen, M.L., Assessing the sensitivity of MODIS to monitor drought in high biomass ecosystems. Remote Sens. Environ. 115 (2011), 2626–2639.
7. Calviño, P., Monzon, J., Farming systems in Argentina: yield constraints and risk management. Sadras, V.O., Calderini, D.F., (eds.) Crop Physiology, 2009, Elsevier, Amsterdam, 55–70.
8. Carrão, H., Gonalves, P., Caetano, M., Contribution of multispectral and multitemporal information from modis images to land cover classification. Remote Sens. Environ. 112 (2008), 986–997.
9. Carrão, H., Gonalves, P., Caetano, M., A nonlinear harmonic model for fitting satellite image time series: analysis and prediction of land cover dynamics. IEEE Trans. Geosci. Remote Sens. 48 (2010), 1919–1930.
10. Carrão, H., Sepulcre, G., Horion, S., Barbosa, P., A multitemporal and non-parametric approach for assessing the impacts of drought on vegetation greenness: a case study for Latin America. EARSeL eProc. 12 (2013), 8–24.
11. Carrão, H., Singleton, A., Naumann, G., Barbosa, P., Vogt, J., An optimized system for the classification of meteorological drought intensity with applications in frequency analysis. J. Appl. Meteor. Climatol. 53 (2014), 1943–1960.
12. Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais (CPTEC-INPE), Evolution of ENSO regimes during 1970–2012. 2013 Available online at http://www.cptec.inpe.br/ cited 06.09.13.
13. Chen, S.X., Probability density function estimation using gamma kernels. Ann. Inst. Stat. Math. 52 (2000), 471–480.
14. Chiang, J.C.H., Kushnir, Y., Giannini, A., Deconstructing Atlantic ITCZ variability: influence of the local crossequatorial SST gradient, and remote forcing from the eastern equatorial pacific. J. Geophys. Res., 107, 2002, 4004.
15. Chung, D., de Jeu, R.A.M., Dorigo, W., Hahn, S., Melzer, T., Parinussa, R.M., Paulik, C., Reimer, C., Vreugdenhil, M., Wagner, W., ESA CCI Soil Moisture. Algorithm Theoretical Baseline Document (ATBD) Version 0.3. 2012, European Space Agency (ESA), ESRIN, Italy.
16. Dorigo, W.A., Gruber, A., De Jeu, R.A.M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R.M., Kidd, R., Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sens. Environ. 162 (2015), 380–395.
17. Dorigo, W.A., de Jeu, R.A.M., Chung, D., Parinussa, R.M., Liu, Y.Y., Wagner, W., Fernandez-Prieto, D., Evaluating global trends (1988–2010) in harmonized multi-satellite surface soil moisture. Geophys. Res. Lett., 39, 2010, L18405.
18. Dracup, J.A., Lee, K.S. Jr., Paulson, E.G., On the definition of droughts. Water Resour. Res. 16 (1980), 297–302.
19. Dutra, E., Viterbo, P., Miranda, P.M.A., Era-40 reanalysis hydrological applications in the characterization of regional drought. Geophys. Res. Lett., 35, 2008, L19402.
20. FAO, Aquastat Database – Food and Agriculture Organization of the United Nations (FAO). 2014 Available online at http://www.fao.org/nr/water/aquastat/main/index.stm cited 18/11/2014.
21. Farahmand, A., AghaKouchak, A., A generalized framework for deriving nonparametric standardized drought indicators. Adv. Water Resour. 76 (2015), 140–145.
22. Gutirrez, A.P.A., Engle, N.L., Nys, E.D., Molejn, C., Martins, E.S., Drought preparedness in brazil. Weather Clim. Extremes 3 (2014), 95–106.
23. Guttman, N.B., Accepting the standardized precipitation index: a calculation algorithm. JAWRA 35 (1999), 311–322.
24. Hannaford, J., Lloyd-Hughes, B., Keef, C., Parry, S., Prudhomme, C., Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit. Hydrol. Process 25 (2011), 1146–1162.
25. Hayes, M.J., Svoboda, M.D., Wilhite, D.A., Vanyarkho, O.V., Monitoring the 1996 drought using the standardized precipitation index. Bull. Am. Meteorol. Soc. 80 (1999), 429–438.
26. Heim, R.R., A review of twentieth-century drought indices used in the United States. Bull. Am. Meteorol. Soc. 83 (2002), 1149–1165.
27. Hofer, B., Carrão, H., McInerney, D., Multi-disciplinary forest fire danger assessment in Europe: the potential to integrate long-term drought information. IJSDIR 7 (2012), 300–322.
28. Hunt, E.D., Hubbard, K.G., Wilhite, D.A., Arkebauer, T.J., Dutcher, A.L., The development and evaluation of a soil moisture index. Int. J. Climatol. 29 (2009), 747–759.
29. IPCC, Summary for policymakers. Field, C.B., Barros, V., Stocker, T.F., Qin, D., Dokken, D.J., Ebi, K.L., Mastrandrea, M.D., Mach, K.J., Plattner, G.-K., Allen, S.K., Tignor, M., Midgley, P., (eds.) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, 2012, Cambridge University Press, 1–19.
30. Jones, M.C., Simple boundary correction for kernel density estimation. Stat. Comput. 3 (1993), 135–146.
31. Kayano, K.T., Capistrano, V.B., How the Atlantic multidecadal oscillation (AMO) modifies the ENSO influence on the South American rainfall. Int. J. Climatol. 34 (2013), 162–178.
32. Keyantash, J., Dracup, J.A., The quantification of drought: an evaluation of drought indices. Bull. Am. Meteorol. Soc. 83 (2002), 1167–1180.
33. Kumar, M.N., Murthy, C.S., Sai, M.V.R.S., Roy, P.S., On the use of standardized precipitation index (SPI) for drought intensity assessment. Meteorol. Appl. 16 (2009), 381–389.
34. Kuncheva, L., Combining Pattern Classifiers: Methods and Algorithms. 2004, John Wiley & Sons.
35. Liao, J.G., Wu, Y., Lin, Y., Improving Sheather and Jones’ bandwidth selector for difficult densities in kernel density estimation. J. Nonparametr. Stat. 22 (2010), 105–114.
36. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., Jeu, R.A.M.D., Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M., Trend-preserving blending of passive and active microwave soil moisture retrievals. Remote Sens. Environ. 123 (2012), 280–297.
37. Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., Jeu, R.A.M.D., Wagner, W., van Dijk, A.I.J.M., McCabe, M.F., Evans, J.P., Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrol. Earth Syst. Sci. 15 (2011), 425–436.
38. Llano, M.P., Vargas, W., Naumann, G., Climate variability in areas of the world with high production of soya beans and corn: its relationship to crop yields. Meteorol. Appl. 19 (2012), 385–396.
39. Lloyd-Hughes, B., A spatio-temporal structure-based approach to drought characterisation. Int. J. Climatol. 32 (2012), 406–418.
40. Lloyd-Hughes, B., Saunders, M.A., A drought climatology for Europe. Int. J. Climatol. 22 (2002), 1571–1592.
41. Magrin, G., Garca, C.G., Choque, D.C., Gimnez, J.C., Moreno, A.R., Nagy, G.J., Nobre, C., Villamizar, A., Climate change 2007: impacts, adaptation and vulnerability. Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J., Hanson, C.E., (eds.) Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007, Cambridge University Press, 581–615.
42. Marengo, J.A., Alves, L.M., Soares, W.R., Rodriguez, D.A., Camargo, H., Riveros, M.P., Pabl, A.D., Two contrasting severe seasonal extremes in tropical South America in 2012: flood in Amazonia and drought in Northeast Brazil. J. Clim. 26 (2013), 9137–9154.
43. Marron, J.S., Ruppert, D., Transformations to reduce boundary bias in kernel density estimation. J. R. Stat. Soc. 56 (1994), 653–671.
44. Martnez-Fernndez, J., Gonzlez-Zamora, A., Snchez, N., Gumuzzio, A., A soil water based index as a suitable agricultural drought indicator. J. Hydrol. 522 (2015), 265–273.
45. McKee, T.B., Doeskin, N.J., Kleist, J., The relationship of drought frequency and duration to time scales. 8th Conf. on Applied Climatology. Amer. Meteor. Soc., Anaheim, Canada, 1993, 179–184.
46. Mishra, A.K., Singh, V.P., A review of drought concepts. J. Hydrol. 391 (2010), 202–216.
47. Mishra, A.K., Singh, V.P., Desai, V.R., Drought characterization: a probabilistic approach. Stoch. Environ. Res. Risk Assess. 23 (2007), 41–55.
48. Nagarajan, R., Drought: Assessment, Monitoring, Management and Resources Conservation. 2003, Capital Publishing Company, New Delhi.
49. Narasimhan, B., Srinivasan, R., Development and evaluation of soil moisture deficit index (SMDI) and evapotranspiration deficit index (ETDI) for agricultural drought monitoring. Agric. For. Meteorol. 133 (2005), 69–88.
50. Naumann, G., Barbosa, P., Carrão, H., Singleton, A., Vogt, J., Monitoring drought conditions and their uncertainties in Africa using TRMM data. J. Appl. Meteor. Climatol. 51 (2012), 1867–1874.
51. Ntale, H.K., Gan, T.Y., Drought indices and their application to East Africa. Int. J. Climatol. 23 (2003), 1335–1357.
52. Palmer, W., Meteorological Drought. 1965, U.S. Weather Bureau, Washington, DC Research Paper 45.
53. Palmer, W.C., Keeping track of crop moisture conditions, nationwide: the new crop moisture index. Weatherwise 21 (1968), 156–161.
54. Paulo, A.A., Ferreira, E., Coelho, C., Pereira, L.S., Drought class transition analysis through Markov and loglinear models, an approach to early warning. Agric. Water Manag. 77 (2005), 59–81.
55. Peled, E., Dutra, E., Viterbo, P., Angert, A., Technical note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation. Hydrol. Earth Syst. Sci. 14 (2010), 271–277.
56. Penalba, O.C., Bettolli, M.L., Vargas, W.M., The impact of climate variability on soybean yields in Argentina. Multivariate regression. Meteorol. Appl. 14 (2007), 3–14.
57. Pereira, M.P.S., Justino, F., Malhado, A.C.M., Barbosa, H., Marengo, J., The influence of oceanic basins on drought and ecosystem dynamics in northeast Brazil. Environ. Res. Lett., 9, 2014, 124013.
58. Phillips, O.L., Arago, L.E.O.C., Lewis, S.L., Fisher, J.B., Lloyd, J., Lpez-Gonzlez, G., Malhi, Y., Monteagudo, A., Peacock, J., Quesada, C.A., van der Heijden, G., Almeida, S., Amaral, I., Arroyo, L., Aymard, G., Baker, T.R., Bnki, O., Blanc, L., Bonal, D., Brando, P., Chave, J., de Oliveira, C.A., Cardozo, N.D., Czimczik, C.I., Feldpauschand, T.R., Freitas, M.A., Gloor, E., Higuchi, N., Jimnez, E., Lloyd, G., Meir, P., Mendoza, C., Morel, A., Neill, D.A., Nepstad, D., Patio, S., Peuela, M.C., Prieto, A., Ramrez, F., Schwarz, M., Silva, J., Silveira, M., Thomas, A.S., Steege, H., Stropp, J., Vsquez, R., Zelazowski, P., Dvila, E.A., Andelman, S., Andrade, A., Chao, K.-J., Erwin, T., Fiore, A.D.C.E.H., Keeling, H., Killeen, T., Laurance, W.F., Cruz, A.P., Pitman, N.C.A., Vargas, P.N., Ramrez-Angulo, H., Rudas, A., Salamo, R., Silva, N., Terborgh, J., Torres-Lezama, A., Drought sensitivity of the Amazon rainforest. Science 323 (2009), 1344–1347.
59. Rao, V.B., Hada, K., Herdies, D.L., On the severe drought of 1993 in north-east Brazil. Int. J. Climatol. 15 (1995), 697–704.
60. Rhee, J., Im, J., Carbone, G.J., Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sens. Environ. 114 (2010), 2875–2887.
61. Rodrigues, R.R., McPhaden, M.J., Why did the 2011–2012 La Nia cause a severe drought in the Brazilian Northeast. Geophys. Res. Lett. 41 (2014), 1012–1018.
62. Russo, S., Carrão, H., Singleton, A., Barbosa, P., Dosio, A., Vogt, J., European dryness and wetness in the last decade with the empirical standardized precipitation index. Maia, R., de Brito, A.G., Teixeira, A.S., Valente, J.T., Pêgo, J.P., (eds.) Water Resources Management in an Interdisciplinary and Changing Context, 2013, FEUP, Porto, Portugal, 296–308.
63. Sacks, W.J., Deryng, D., Foley, J.A., Ramankutty, N., Crop planting dates: an analysis of global patterns. Glob. Ecol. Biogeogr. 19 (2010), 607–620.
64. Schuster, E.F., Incorporating support constraints into nonparametric estimators of densities. Commun. Stat. Theory Methods 14 (1985), 1123–1136.
65. Sepulcre-Canto, G., Horion, S., Singleton, A., Carrão, H., Vogt, J., Development of a combined drought indicator to detect agricultural drought in Europe. Nat. Hazards Earth Syst. Sci. 12 (2012), 3519–3531.
66. Sheather, S.J., Jones, M.C., A reliable data-based bandwidth selection method for kernel density estimation. J. R. Stat. Soc. B 53 (1991), 683–690.
67. Sheffield, J., Andreadis, K.M., Wood, E.F., Lettenmaier, D.P., Global and continental drought in the second half of the twentieth century: severity-area-duration analysis and temporal variability of large-scale events. J. Clim. 22 (2009), 1962–1981.
68. Sheffield, J., Goteti, G., Wen, F., Wood, E.F., A simulated soil moisture based drought analysis for the United States. J. Geophys. Res., 109, 2004, D24108.
69. Sienz, F., Bothe, O., Fraederich, K., Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias. Hydrol. Earth Syst. Sci. 16 (2012), 2143–2157.
70. Silverman, B.W., Density Estimation for Statistics and Data Analysis. 1986, Chapman & Hall.
71. Smakhtin, V.U., Schipper, E.L.F., Droughts: the impact of semantics and perceptions. Water Pol. 10 (2008), 131–143.
72. Sridhar, V., Hubbard, K.G., You, J., Hunt, E.D., Development of the soil moisture index to quantify agricultural drought and its “user friendliness” in severity-area-duration assessment. J. Hydrometeorol. 9 (2008), 660–676.
73. Svoboda, M., Hayes, M., Wood, D., Standardized Precipitation Index User Guide. 2012, World Meteorological Organization, Geneva, Switzerland Tech. Rep. WMO-No. 1090.
74. Trenberth, K.E., Stepaniak, D., Indices of el Niño evolution. J. Clim. 14 (2011), 1697–1701.
75. van Bussel, L.G., Grassini, P., Wart, J.V., Wolf, J., Claessens, L., Yang, H., Boogaard, H., de Groot, H., Saito, K., Cassman, K.G., van Ittersum, M.K., From field to atlas: upscaling of location-specific yield gap estimates. Field Crops Res. 177 (2015), 98–108.
76. van Ittersum, M.K., Cassman, K.G., Grassini, P., Wolf, J., Tittonell, P., Hochman, Z., Yield gap analysis with local to global relevance – a review. Field Crops Res 143 (2013), 4–17.
77. van Wart, J., Kersebaum, K.C., Peng, S., Milner, M., Cassman, K.G., Estimating crop yield potential at regional to national scales. Field Crops Res. 143 (2013), 34–43.
78. van Wart, J., van Bussel, L.G., Wolf, J., Licker, R., Grassini, P., Nelson, A., Boogaard, H., Gerber, J., Mueller, N.D., Claessens, L., van Ittersum, M.K., Cassman, K.G., Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Res. 143 (2013), 44–55.
79. Vargas, W.M., Naumann, G., Minetti, J.L., Dry spells in the River Plata Basin: an approximation of the diagnosis of droughts using daily data. Theor. Appl. Climatol. 104 (2011), 159–173.
80. Vyas, S.S., Bhattacharya, B.K., Nigam, R., Guhathakurta, P., Ghosh, K., Chattopadhyay, N., Gairola, R., A combined deficit index for regional agricultural drought assessment over semi-arid tract of India using geostationary meteorological satellite data. Int. J. Geogr. Inf. Sci. 39 (2015), 28–39.
81. Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Haas, J.B.E., Ertl, M., Fusion of active and passive microwave observations to create an essential climate variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. I-7, 2012, ISPRS, Melbourne, Australia, 315–321 xXII ISPRS Congress.
82. Wilhite, D.A., Glantz, M.H., Understanding the drought phenomenon: the role of definitions. Water Int. 10 (1985), 111–120.
83. Wilks, D.S., Statistical Methods in the Atmospheric Sciences. 2nd ed., 2005, Academic Press, San Diego, California, USA.
84. WMO, Guide to climatological practices. 3rd ed., 2011, World Meteorological Organization (WMO), Geneva, Switzerland Tech. Rep. WMO No. 100.
85. Wu, H., Hayes, M.J., Wilhite, D.A., Svoboda, M.D., The effect of the length of record on the standardized precipitation index calculation. Int. J. Climatol. 25 (2005), 505–520.
86. Yadav, S., Redden, R., Hatfield, J., Lotze-Campen, H., Hall, A., Crop Adaptation to Climate Change. 2011, Wiley.
87. Zambom, A.Z., Dias, R., A review of kernel density estimation with applications to econometrics. IER 5 (2013), 20–42.
88. Zhao, M., Running, S.W., Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329 (2010), 940–943.