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Monitoring Drought in Brazil by Remote Sensing

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Remote Sensing of Hydrological Extremes

Part of the book series: Springer Remote Sensing/Photogrammetry ((SPRINGERREMO))

Abstract

Drought is a natural phenomena responsible for significant socioeconomic and environmental damage worldwide. Remote sensing techniques can provide high resolution and multitemporal images for drought monitoring and warning systems. In this review, we depict drought definition and its different types and we also demonstrate a set of sensors for global terrestrial monitoring and how they contribute for mapping hydrological variables. Finally, we present a practical example on the use of remote sensing technologies to detect and quantify a recent drought event in Brazil during 2012–2015. Soil moisture data derived from Advanced Microwave Scanning Radiometer (AMSR), vegetation index from Moderate Resolution Imaging Spectroradiometer (MODIS), and total water storage retrieved from Gravimetry Recovery and Climate Experiment (GRACE) was used to estimate impacted areas and region-specific water deficits over Southeastern and Northeastern Brazil. Drought has impacted significantly all of the three remotely sensed variables mentioned above in different degrees for the two studied regions. It was also observed that a positive correlation between monthly time series of GRACE and 16 reservoirs located within Southeastern Brazil varied from 0.42 to 0.82. Differences are mainly explained by reservoir sizes and proximity to the drought nucleus.

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References

  • AghaKouchak A (2015) A multivariate approach for persistence-based drought prediction: application to the 2010–2011 east Africa drought. J Hydrol 526:127–135. doi:10.1016/j.jhydrol.2014.09.063

    Article  Google Scholar 

  • AghaKouchak A, Farahmand A, Melton FS, Teixeira J, Anderson MC, Wardlow BD, Hain CR (2015) Remote sensing of drought: progress, challenges and opportunities. Rev Geophys 53(2):452–480. doi:10.1002/2014rg000456

    Article  Google Scholar 

  • Allen RG, Tasumi M, Morse A, Trezza R, Wright JL, Bastiaanssen W, Kramber W, Lorite I, Robison CW (2007) Satellite-based energy balance for mapping Evapotranspiration with internalized calibration (METRIC)—applications. J Irri Drain Eng 133(4):395–406. doi:10.1061/(asce)0733-9437(2007)133:4(395)

    Article  Google Scholar 

  • Alsdorf D, Bates P, Melack J, Wilson M, Dunne T (2007) Spatial and temporal complexity of the Amazon flood measured from space. Geophys Res Lett 34(8), L08402. doi:10.1029/2007gl029447

    Article  Google Scholar 

  • Anderson LO, Malhi Y, Aragão LEOC, Ladle R, Arai E, Barbier N, Phillips O (2010) Remote sensing detection of droughts in Amazonian forest canopies. New Phytol 187(3):733–750. doi:10.1111/j.1469-8137.2010.03355.x

    Article  Google Scholar 

  • Anderson M (1997) A Two-Source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens Environ 60(2):195–216. doi:10.1016/s0034-4257(96)00215-5

    Article  Google Scholar 

  • Anderson MC, Hain C, Wardlow B, Pimstein A, Mecikalski JR, Kustas WP (2011) Evaluation of drought indices based on thermal remote sensing of Evapotranspiration over the continental United States. J Climate 24(8):2025–2044. doi:10.1175/2010jcli3812.1

    Article  Google Scholar 

  • Anderson MC, Zolin CA, Sentelhas PC, Hain CR, Semmens K, Tugrul Yilmaz M, Gao F, Otkin JA, Tetrault R (2016) The evaporative stress index as an indicator of agricultural drought in brazil: an assessment based on crop yield impacts. Remote Sens Environ 174:82–99. doi:10.1016/j.rse.2015.11.034

    Article  Google Scholar 

  • Anderson WB, Zaitchik BF, Hain CR, Anderson MC, Yilmaz MT, Mecikalski J, Schultz L (2012) Towards an integrated soil moisture drought monitor for east Africa. Hydrol Earth Syst Sci 16(8):2893–2913. doi:10.5194/hess-16-2893-2012

    Article  Google Scholar 

  • Barbosa HA, Lakshmi Kumar TV (2016) Influence of rainfall variability on the vegetation dynamics over northeastern brazil. J Arid Environ 124:377–387. doi:10.1016/j.jaridenv.2015.08.015

    Article  Google Scholar 

  • Bastiaanssen WGM, Pelgrum H, Wang J, Ma Y, Moreno JF, Roerink GJ, van der Wal T (1998) A remote sensing surface energy balance algorithm for land (SEBAL). J Hydrol 212–213:213–229. doi:10.1016/s0022-1694(98)00254-6

    Article  Google Scholar 

  • Björnsson H, Venegas SA (1997) A manual for EOF and SVD analyses of climatic data

    Google Scholar 

  • Bolten JD, Crow WT, Zhan X, Jackson TJ, Reynolds CA (2010) Evaluating the utility of remotely sensed soil moisture Retrievals for operational agricultural drought monitoring. IEEE J Sel Top Appl Earth Obs Remote Sens 3(1):57–66. doi:10.1109/jstars.2009.2037163

    Article  Google Scholar 

  • Brown JF, Wardlow BD, Tadesse T, Hayes MJ, Reed BC (2008) The vegetation drought response index (VegDRI): a new integrated approach for monitoring drought stress in vegetation. GISci Remote Sens 45(1):16–46. doi:10.2747/1548-1603.45.1.16

    Article  Google Scholar 

  • Cai W, Cowan T, Briggs P, Raupach M (2009) Rising temperature depletes soil moisture and exacerbates severe drought conditions across southeast Australia. Geophys Res Lett 36(21), L21709. doi:10.1029/2009gl040334

    Article  Google Scholar 

  • Carlson T (2007) An overview of the “triangle method” for estimating surface Evapotranspiration and soil moisture from satellite imagery. Sensors 7(8):1612–1629. doi:10.3390/s7081612

    Article  Google Scholar 

  • Carlson TN, Gillies RR, Schmugge TJ (1995) An interpretation of methodologies for indirect measurement of soil water content. Agric For Meteorol 77(3–4):191–205. doi:10.1016/0168-1923(95)02261-u

    Article  Google Scholar 

  • Carrão H, Russo S, Sepulcre-Canto G, Barbosa P (2016) An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data. Int J Appl Earth Obs Geoinfo 48:74–84. doi:10.1016/j.jag.2015.06.011

    Article  Google Scholar 

  • Coelho CAS, Cardoso DHF, Firpo MAF (2015a) Precipitation diagnostics of an exceptionally dry event in São Paulo, brazil. Theor Appl Climatol. doi:10.1007/s00704-015-1540-9

    Google Scholar 

  • Coelho CAS, de Oliveira CP, Ambrizzi T, Reboita MS, Carpenedo CB, Campos JLPS, Tomaziello ACN, Pampuch LA, Custódio M de S, Dutra LMM, Da Rocha RP, Rehbein A (2015b) The 2014 southeast brazil austral summer drought: regional scale mechanisms and teleconnections. Climate Dynam 46(11–12):3737–3752. doi:10.1007/s00382-015-2800-1

    Google Scholar 

  • Cunha APM, Alvalá RC, Nobre CA, Carvalho MA (2015) Monitoring vegetative drought dynamics in the Brazilian semiarid region. Agric For Meteorol 214–215:494–505. doi:10.1016/j.agrformet.2015.09.010

    Article  Google Scholar 

  • Dracup JA, Lee KS, Paulson EG (1980) On the definition of droughts. Water Resour Res 16(2):297–302. doi:10.1029/wr016i002p00297

    Article  Google Scholar 

  • Draper CS, Walker JP, Steinle PJ, de Jeu RAM, Holmes TRH (2009) An evaluation of AMSR–E derived soil moisture over Australia. Remote Sens Environ 113(4):703–710. doi:10.1016/j.rse.2008.11.011

    Article  Google Scholar 

  • Escobar H (2015) Drought triggers alarms in brazil’s biggest metropolis. Science 347(6224):812. doi:10.1126/science.347.6224.812

    Article  Google Scholar 

  • Espinoza JC, Ronchail J, Frappart F, Lavado W, Santini W, Guyot JL (2013) The major floods in the Amazonas river and Tributaries (western Amazon basin) during the 1970–2012 period: a focus on the 2012 flood. J Hydrometeorol 14(3):1000–1008. doi:10.1175/jhm-d-12-0100.1

    Article  Google Scholar 

  • Famiglietti JS, Rodell M (2013) Water in the balance. Science 340(6138):1300–1301. doi:10.1126/science.1236460

    Article  Google Scholar 

  • Fang B, Lakshmi V, Bindlish R et al (2013) Passive microwave soil moisture downscaling using vegetation index and skin surface temperature. Vadose Zone J 12(3). doi:10.2136/vzj2013.05.0089

  • Frappart F, Papa F, Güntner A, Werth S, Santos da Silva J, Tomasella J, Seyler F, Prigent C, Rossow WB, Calmant S, Bonnet M-P (2011) Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains. Remote Sens Environ 115(6):1588–1594. doi:10.1016/j.rse.2011.02.003

    Article  Google Scholar 

  • Gao B (1996) NDWI—a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens Environ 58(3):257–266. doi:10.1016/s0034-4257(96)00067-3

    Article  Google Scholar 

  • Getirana A (2016) Extreme water deficit in brazil detected from space. J Hydrometeorol 17(2):591–599. doi:10.1175/jhm-d-15-0096.1

    Article  Google Scholar 

  • Getirana ACV, Dutra E, Guimberteau M, Kam J, Li H-Y, Decharme B, Zhang Z, Ducharne A, Boone A, Balsamo G, Rodell M, Toure AM, Xue Y, Peters-Lidard CD, Kumar SV, Arsenault K, Drapeau G, Ruby Leung L, Ronchail J, Sheffield J (2014) Water balance in the Amazon basin from a land surface model ensemble. J Hydrometeorol 15(6):2586–2614. doi:10.1175/jhm-d-14-0068.1

    Article  Google Scholar 

  • Getirana ACV, Peters-Lidard C (2013) Estimating water discharge from large radar altimetry datasets. Hydrol Earth Syst Sci 17(3):923–933. doi:10.5194/hess-17-923-2013

    Article  Google Scholar 

  • González J, Valdés JB (2004) The mean frequency of recurrence of in-time-multidimensional events for drought analyses. Nat Hazards Earth Syst Sci 4(1):17–28. doi:10.5194/nhess-4-17-2004

    Article  Google Scholar 

  • Gruber A, Su C, Zwieback S, Crow W, Dorigo W, Wagner W (2016) Recent advances in (soil moisture) triple collocation analysis. Int J Appl Earth Obs Geoinfo 45:200–211. doi:10.1016/j.jag.2015.09.002

    Article  Google Scholar 

  • Gu Y, Brown JF, Verdin JP, Wardlow B (2007) A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central great plains of the United States. Geophys Res Lett 34(6), L06407. doi:10.1029/2006gl029127

    Article  Google Scholar 

  • Hayes MJ, Svoboda MD, Wilhite DA, Vanyarkho OV (1999) Monitoring the 1996 drought using the standardized precipitation index. Bull Am Meteorol Soc 80(3):429–438. doi:10.1175/1520-0477(1999)080<0429:mtduts>2.0.co;2

    Article  Google Scholar 

  • Hirschi M, Mueller B, Dorigo W, Seneviratne SI (2014) Using remotely sensed soil moisture for land–atmosphere coupling diagnostics: the role of surface vs. Root-zone soil moisture variability. Remote Sens Environ 154:246–252. doi:10.1016/j.rse.2014.08.030

    Article  Google Scholar 

  • Hong Y, Adler RF, Hossain F et al (2007) A first approach to global runoff simulation using satellite rainfall estimation. Water Resour Res 43(8). doi:10.1029/2006wr005739

  • Hubert P, Carbonnel JP, Chaouche A (1989) Segmentation des séries hydrométéorologiques—application à des séries de précipitations et de débits de l’afrique de l’ouest. J Hydrol 110(3–4):349–367. doi:10.1016/0022-1694(89)90197-2

    Article  Google Scholar 

  • Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83(1–2):195–213. doi:10.1016/s0034-4257(02)00096-2

    Article  Google Scholar 

  • Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF (2007) The TRMM Multisatellite Precipitation analysis (TMPA): Quasi-Global, multiyear, combined-sensor Precipitation estimates at fine scales. J Hydrometeorol 8(1):38–55. doi:10.1175/jhm560.1

    Article  Google Scholar 

  • de Jeu R, Dorigo W (2016) On the importance of satellite observed soil moisture. Int J Appl Earth Obs Geoinfo 45:107–109. doi:10.1016/j.jag.2015.10.007

    Article  Google Scholar 

  • Junquas C, Vera C, Li L, Le Treut H (2011) Summer precipitation variability over southeastern South America in a global warming scenario. Climate Dynam 38(9–10):1867–1883. doi:10.1007/s00382-011-1141-y

    Google Scholar 

  • Justice CO, Townshend JRG, Vermote EF, Masuoka E, Wolfe RE, Saleous N, Roy DP, Morisette JT (2002) An overview of MODIS land data processing and product status. Remote Sens Environ 83(1–2):3–15. doi:10.1016/s0034-4257(02)00084-6

    Article  Google Scholar 

  • Karnieli A, Agam N, Pinker RT, Anderson M, Imhoff ML, Gutman GG, Panov N, Goldberg A (2010) Use of NDVI and land surface temperature for drought assessment: merits and limitations. J Climate 23(3):618–633. doi:10.1175/2009jcli2900.1

    Article  Google Scholar 

  • Kim T-W, Valdés JB, Aparicio J (2002) Frequency and spatial characteristics of droughts in the Conchos river basin, Mexico. Water Int 27(3):420–430. doi:10.1080/02508060208687021

    Article  Google Scholar 

  • Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15(11):91–100. doi:10.1016/0273-1177(95)00079-t

    Article  Google Scholar 

  • Kohler MA, Linsley RK (2008) Predicting the runoff from storm rainfall. http://www.nrc.gov/docs/ML0819/ML081900279.pdf. Accessed 18 June 2016

  • Kumar 2014 Multivariate satellite data assimilation in NLDAS. AMS Annual meeting, 95th AMS annual meeting, Phoenix

    Google Scholar 

  • Lakshmi V, Piechota T, Narayan U, Tang C (2004) Soil moisture as an indicator of weather extremes. Geophys Res Lett 31(11), L11401. doi:10.1029/2004gl019930

    Article  Google Scholar 

  • Landerer FW, Swenson SC (2012) Accuracy of scaled GRACE terrestrial water storage estimates. Water Resour Res 48(4), W04531. doi:10.1029/2011wr011453

    Article  Google Scholar 

  • Li B, Rodell M (2015) Evaluation of a model-based groundwater drought indicator in the conterminous U.S. J Hydrol 526:78–88. doi:10.1016/j.jhydrol.2014.09.027

    Article  Google Scholar 

  • Li B, Rodell M, Zaitchik BF, Reichle RH, Koster RD, van Dam TM (2012) Assimilation of GRACE terrestrial water storage into a land surface model: evaluation and potential value for drought monitoring in western and central Europe. Journal of Hydrology 446–447:103–115. doi:10.1016/j.jhydrol.2012.04.035

    Article  Google Scholar 

  • Liu J, Rambal S, Mouillot F (2015) Soil drought anomalies in MODIS GPP of a Mediterranean Broadleaved evergreen forest. Remote Sens 7(1):1154–1180. doi:10.3390/rs70101154

    Article  Google Scholar 

  • Liu WT, Juárez RIN (2001) ENSO drought onset prediction in northeast brazil using NDVI. Int J Remote Sens 22(17):3483–3501. doi:10.1080/01431160010006430

    Article  Google Scholar 

  • Lyon B (2004) The strength of El Niño and the spatial extent of tropical drought. Geophys Res Lett 31(21), L21204. doi:10.1029/2004gl020901

    Article  Google Scholar 

  • Marengo JA, Alves LM, Soares WR, Rodriguez DA, Camargo H, Riveros MP, Pabló AD (2013) Two contrasting severe seasonal extremes in tropical south America in 2012: flood in Amazonia and drought in northeast brazil. J Climate 26(22):9137–9154. doi:10.1175/jcli-d-12-00642.1

    Article  Google Scholar 

  • Marengo JA, Bernasconi M (2014) Regional differences in aridity/drought conditions over northeast brazil: present state and future projections. Clim Change 129(1–2):103–115. doi:10.1007/s10584-014-1310-1

    Google Scholar 

  • Marengo JA, Soares WR, Saulo C, Nicolini M (2004) Climatology of the low-level jet east of the Andes as derived from the NCEP–NCAR Reanalyses: characteristics and temporal variability. J Climate 17(12):2261–2280. doi:10.1175/1520-0442(2004)017<2261:cotlje>2.0.co;2

    Article  Google Scholar 

  • Merlin O, Walker J, Chehnbouni A, Kerr Y (2008) Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency. Remote Sens Environ 112(10):3935–3946. doi:10.1016/j.rse.2008.06.012

    Article  Google Scholar 

  • Mishra AK, Desai VR (2005) Spatial and temporal drought analysis in the Kansabati river basin, India. Int J River Basin Manage 3(1):31–41. doi:10.1080/15715124.2005.9635243

    Article  Google Scholar 

  • Mishra AK, Ines AVM, Das NN, Prakash Khedun C, Singh VP, Sivakumar B, Hansen JW (2015) Anatomy of a local-scale drought: application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study. J Hydrol 526:15–29. doi:10.1016/j.jhydrol.2014.10.038

    Article  Google Scholar 

  • Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391(1–2):202–216. doi:10.1016/j.jhydrol.2010.07.012

    Article  Google Scholar 

  • Mishra AK, Singh VP (2011) Drought modeling—a review. J Hydrol 403(1–2):157–175. doi:10.1016/j.jhydrol.2011.03.049

    Article  Google Scholar 

  • Moura F de BP, Mendes Malhado AC, Ladle RJ (2013) Nursing the caatinga back to health. J Arid Environ 90:67–68. doi:10.1016/j.jaridenv.2012.10.010

    Article  Google Scholar 

  • Mu Q, Zhao M, Kimball JS, McDowell NG, Running SW (2013) A remotely sensed global terrestrial drought severity index. Bull Am Meteorol Soc 94(1):83–98. doi:10.1175/bams-d-11-00213.1

    Article  Google Scholar 

  • Mu Q, Zhao M, Running SW (2011) Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ 115(8):1781–1800. doi:10.1016/j.rse.2011.02.019

    Article  Google Scholar 

  • Narasimhan B, Srinivasan R (2005) Development and evaluation of soil moisture deficit index (SMDI) and Evapotranspiration deficit index (ETDI) for agricultural drought monitoring. Agric For Meteorol 133(1–4):69–88. doi:10.1016/j.agrformet.2005.07.012

    Article  Google Scholar 

  • Nazareno AG, Laurance WF (2015) Brazil’s drought: beware deforestation. Science 347(6229):1427–1427. doi:10.1126/science.347.6229.1427-a

    Article  Google Scholar 

  • Otkin JA, Anderson MC, Hain C, Svoboda M (2014) Examining the relationship between drought development and rapid changes in the evaporative stress index. J Hydrometeorol 15(3):938–956. doi:10.1175/jhm-d-13-0110.1

    Article  Google Scholar 

  • Palmer WC (1968) Keeping track of crop moisture conditions, nationwide: the new crop moisture index. Weatherwise 21(4):156–161. doi:10.1080/00431672.1968.9932814

    Article  Google Scholar 

  • Papa F, Frappart F, Güntner A, Prigent C, Aires F, Getirana ACV, Maurer R (2013) Surface freshwater storage and variability in the Amazon basin from multi-satellite observations, 1993-2007. J Geophys Res Atmos 118(21):11951–11965. doi:10.1002/2013jd020500

    Article  Google Scholar 

  • Petropoulos G, Carlson TN, Wooster MJ, Islam S (2009) A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Prog Phys Geo 33(2):224–250. doi:10.1177/0309133309338997

    Article  Google Scholar 

  • Pettitt AN (1979) A non-parametric approach to the change-point problem. Appl Stat 28(2):126. doi:10.2307/2346729

    Article  Google Scholar 

  • Piles M, Camps A, Vall-llossera M, Corbella I, Panciera R, Rudiger C, Kerr YH, Walker J (2011) Downscaling SMOS-Derived soil moisture using MODIS visible/infrared data. IEEE Trans Geosci Remote Sens 49(9):3156–3166. doi:10.1109/tgrs.2011.2120615

    Article  Google Scholar 

  • Poveda G, Jaramillo L, Vallejo LF (2014) Seasonal precipitation patterns along pathways of south American low-level jets and aerial rivers. Water Resour Res 50(1):98–118. doi:10.1002/2013wr014087

    Article  Google Scholar 

  • Privette JL, Myneni RB, Knyazikhin Y, Mukelabai M, Roberts G, Tian Y, Wang Y, Leblanc SG (2002) Early spatial and temporal validation of MODIS LAI product in the southern Africa Kalahari. Remote Sens Environ 83(1–2):232–243. doi:10.1016/s0034-4257(02)00075-5

    Article  Google Scholar 

  • Rahmani A, Golian S, Brocca L (2016) Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products. Int J Appl Earth Obs Geoinf 48:85–95. doi:10.1016/j.jag.2015.06.009

    Article  Google Scholar 

  • Ramillien G, Frappart F, Güntner A, Ngo-Duc T, Cazenave A, Laval K (2006) Time variations of the regional evapotranspiration rate from gravity recovery and climate experiment (GRACE) satellite gravimetry. Water Resour Res 42(10), W10403. doi:10.1029/2005wr004331

    Article  Google Scholar 

  • Rees G (2012) Electromagnetic waves in free space. In: Physical principles of remote sensing. Cambridge University Press, Cambridge

    Chapter  Google Scholar 

  • Rodell M, McWilliams EB, Famiglietti JS, Beaudoing HK, Nigro J (2011) Estimating evapotranspiration using an observation based terrestrial water budget. Hydrol Process 25(26):4082–4092. doi:10.1002/hyp.8369

    Article  Google Scholar 

  • Rodell M, Velicogna I, Famiglietti JS (2009) Satellite-based estimates of groundwater depletion in India. Nature 460(7258):999–1002. doi:10.1038/nature08238

    Article  Google Scholar 

  • Running SW, Nemani RR, Heinsch FA, Zhao M, Reeves M, Hashimoto H (2004) A continuous satellite-derived measure of global terrestrial primary production. BioScience 54(6):547. doi:10.1641/0006-3568(2004)054[0547:acsmog]2.0.co;2

    Article  Google Scholar 

  • Sandholt I, Rasmussen K, Andersen J (2002) A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sens Environ 79(2–3):213–224. doi:10.1016/s0034-4257(01)00274-7

    Article  Google Scholar 

  • Santos JF, Pulido-Calvo I, Portela MM (2010) Spatial and temporal variability of droughts in Portugal. Water Resour Res 46(3), W03503. doi:10.1029/2009wr008071

    Article  Google Scholar 

  • van der Schrier G, Barichivich J, Briffa KR, Jones PD (2013) A scPDSI-based global data set of dry and wet spells for 1901–2009. J Geophys Res Atmos 118(10):4025–4048. doi:10.1002/jgrd.50355

    Article  Google Scholar 

  • Seth A, Fernandes K, Camargo SJ (2015) Two summers of São Paulo drought: origins in the western tropical pacific. Geophys Res Lett 42(24):10816–10823. doi:10.1002/2015gl066314

    Article  Google Scholar 

  • Sheffield J (2004) A simulated soil moisture based drought analysis for the United States. J Geophys Res 109(D24), D24108. doi:10.1029/2004jd005182

    Article  Google Scholar 

  • Silva ACS, Galvão CO, Silva GNS (2015) Droughts and governance impacts on water scarcity: an analysis in the Brazilian semi-arid. Proc Int Assoc Hydrol Sci 369:129–134. doi:10.5194/piahs-369-129-2015

    Google Scholar 

  • Singh RP, Roy S, Kogan F (2003) Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India. Int J Remote Sens 24(22):4393–4402. doi:10.1080/0143116031000084323

    Article  Google Scholar 

  • Stoffelen A (1998) Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. J Geophy Res Oceans 103(C4):7755–7766. doi:10.1029/97jc03180

    Article  Google Scholar 

  • Su Z (2002) The surface energy balance system (SEBS) for estimation of turbulent heat fluxes. Hydrol Earth Syst Sci 6(1):85–100. doi:10.5194/hess-6-85-2002

    Article  Google Scholar 

  • Sun D, Kafatos M (2007) Note on the NDVI-LST relationship and the use of temperature-related drought indices over north America. Geophys Res Lett 34(24), L24406. doi:10.1029/2007gl031485

    Article  Google Scholar 

  • Syed TH, Lakshmi V, Paleologos E, Lohmann D, Mitchell K, Famiglietti JS (2004) Analysis of process controls in land surface hydrological cycle over the continental United States. J Geophys Res Atmos 109(D22), D22105. doi:10.1029/2004jd004640

    Article  Google Scholar 

  • Tang C, Piechota TC (2009) Spatial and temporal soil moisture and drought variability in the upper Colorado river basin. J Hydrol 379(1–2):122–135. doi:10.1016/j.jhydrol.2009.09.052

    Article  Google Scholar 

  • Tapley BD (2004) GRACE measurements of mass variability in the earth system. Science 305(5683):503–505. doi:10.1126/science.1099192

    Article  Google Scholar 

  • Tatli H, Türkeş M (2011) Empirical Orthogonal function analysis of the palmer drought indices. Agric For Meteorol 151(7):981–991. doi:10.1016/j.agrformet.2011.03.004

    Article  Google Scholar 

  • Thomas AC, Reager JT, Famiglietti JS, Rodell M (2014) A gRACE-based water storage deficit approach for hydrological drought characterization. Geophys Res Lett 41(5):1537–1545. doi:10.1002/2014gl059323

    Article  Google Scholar 

  • Toumazou V, Cretaux J-F (2001) Using a Lanczos Eigensolver in the computation of empirical Orthogonal functions. Mon Weather Rev 129(5):1243–1250. doi:10.1175/1520-0493(2001)129<1243:ualeit>2.0.co;2

    Article  Google Scholar 

  • Tsakiris G, Pangalou D, Vangelis H (2006) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21(5):821–833. doi:10.1007/s11269-006-9105-4

    Article  Google Scholar 

  • Tsakiris G, Vangelis H (2005) Establishing a drought index incorporating evapotranspiration. Eur Water 9:3–11

    Google Scholar 

  • Vermote E, Vermeulen A (1999) Atmospheric correction algorithm: spectral reflectances (MOD09), Algorithm Theoretical Basis Documents (ATBD) Version 4.0. Tech Report April, EOS Project Science Office. NASA Goddard Space Flight Center, Greenbelt

    Google Scholar 

  • Wagner W, Lemoine G, Rott H (1999) A method for estimating soil moisture from ERS Scatterometer and soil data. Remote Sens Environ 70(2):191–207. doi:10.1016/s0034-4257(99)00036-x

    Article  Google Scholar 

  • Wan, Z. (1999) Land-surface temperature algorithm theoretical basis document (LST ATBD). Technical Report April. Institute for Computational Earth System Science, University of California

    Google Scholar 

  • Werth S, Güntner A, Petrovic S, Schmidt R (2009) Integration of GRACE mass variations into a global hydrological model. Earth Planet Sci Lett 277(1–2):166–173. doi:10.1016/j.epsl.2008.10.021

    Article  Google Scholar 

  • Wilhite DA (1993) The enigma of drought. In: Wilhite DA (ed) Drought assessment, management, and planning: theory and case studies. Kluwer Academic, Berlin

    Chapter  Google Scholar 

  • Wu D, Qu JJ, Hao X (2015) Agricultural drought monitoring using MODIS-based drought indices over the USA corn belt. Int J Remote Sens 36(21):5403–5425. doi:10.1080/01431161.2015.1093190

    Article  Google Scholar 

  • Yao Y, Liang S, Qin Q, Wang K (2010) Monitoring drought over the Conterminous United States using MODIS and NCEP Reanalysis-2 data. J Appl Meteorol Climatol 49(8):1665–1680. doi:10.1175/2010jamc2328.1

    Article  Google Scholar 

  • Yao Y, Liang S, Qin Q, Wang K, Zhao S (2011) Monitoring global land surface drought based on a hybrid evapotranspiration model. Int J Appl Earth Obs Geoinf 13(3):447–457. doi:10.1016/j.jag.2010.09.009

    Article  Google Scholar 

  • Zaitchik BF, Rodell M, Reichle RH (2008) Assimilation of GRACE terrestrial water storage data into a land surface model: results for the Mississippi river basin. J Hydrometeorol 9(3):535–548. doi:10.1175/2007jhm951.1

    Article  Google Scholar 

  • Zhang F, Zhang L, Wang X, Hung J (2013) Detecting agro-droughts in southwest of china using MODIS satellite data. J Integr Agric 12(1):159–168. doi:10.1016/s2095-3119(13)60216-6

    Article  Google Scholar 

  • Zhang L, Xiao J, Li J, Wang K, Lei L, Guo H (2012) The 2010 spring drought reduced primary productivity in southwestern china. Environ Res Lett 7(4):045706. doi:10.1088/1748-9326/7/4/045706

    Article  Google Scholar 

  • Zhang X, Susan Moran M, Zhao X, Liu S, Zhou T, Ponce-Campos GE, Liu F (2014) Impact of prolonged drought on rainfall use efficiency using MODIS data across china in the early 21st century. Remote Sens Environ 150:188–197. doi:10.1016/j.rse.2014.05.003

    Article  Google Scholar 

  • Zhao W, Li A (2013) A downscaling method for improving the spatial resolution of AMSR-E derived soil moisture product based on MSG-SEVIRI data. Remote Sens 5(12):6790–6811. doi:10.3390/rs5126790

    Article  Google Scholar 

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Authors and Affiliations

  1. Laboratório de Recursos Hídricos e Meio Ambiente (LABH2O), Programa de Engenharia Civil, Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa em Engenharia—COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil

    Vitor Paiva Alcoforado Rebello & Otto Corrêa Rotunno Filho

  2. Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Augusto Getirana

  3. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA

    Augusto Getirana

  4. Department of Geophysics, Stanford University, Stanford, CA, USA

    Venkat Lakshmi

  5. School of Earth, Ocean and Environment, University of South Carolina, Columbia, SC, USA

    Venkat Lakshmi

Authors
  1. Vitor Paiva Alcoforado Rebello
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  2. Augusto Getirana
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  3. Venkat Lakshmi
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  4. Otto Corrêa Rotunno Filho
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Correspondence to Vitor Paiva Alcoforado Rebello .

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  1. Department of Geophysics, Stanford University, Stanford, California, USA

    Venkat Lakshmi

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Paiva Alcoforado Rebello, V., Getirana, A., Lakshmi, V., Corrêa Rotunno Filho, O. (2017). Monitoring Drought in Brazil by Remote Sensing. In: Lakshmi, V. (eds) Remote Sensing of Hydrological Extremes. Springer Remote Sensing/Photogrammetry. Springer, Cham. https://doi.org/10.1007/978-3-319-43744-6_10

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