Satellite-based crop coefficient and evapotranspiration using surface soil moisture and vegetation indices in Northeast Asia

Catena

Volumn 156, Issue , 2017, Pages 305-314

  Park, Jongmin ^a   Baik, Jongjin ^b   Choi, Minha ^b  

^a UNIVERSITY OF MARYLAND   (United States)

^b Sungkyunkwan University   (South Korea)

Author keywords

Crop coefficient; ESA CCI soil moisture; Evapotranspiration; Remote sensing; Vegetation indices

Indexed keywords

ACCURACY ASSESSMENT; AGRICULTURAL MANAGEMENT; CROP YIELD; EVAPOTRANSPIRATION; LATENT HEAT FLUX; MODEL VALIDATION; NDVI; PADDY FIELD; REMOTE SENSING; RICE; SATELLITE DATA; SOIL MOISTURE;

NORTHEAST ASIA;

EID: 85018275473     PISSN: 03418162     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.catena.2017.04.013     Document Type: Article

References (78)

1. Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay, P., Isaksen, L., Brocca, L., de Jeu, R., Wagner, W., Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses. Remote Sens. Environ. 138 (2013), 77–89.
2. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., Crop evapotranspiration-guidelines for computing crop water requirements-FA O irrigation and drainage paper 56. FAO, Rome, 300, 1998, 6541.
3. Al-Yaari, A., Wigneron, J.P., Ducharne, A., Kerr, Y., de Rosnay, P., de Jeu, R., Govind, A., Al Bitar, A., Albergel, C., Munoz-Sabater, J., Richaume, P., Mialon, A., Merging two passive microwave remote sensing (SMOS and AMSR_E) datasets to produce a long term record of soil moisture. Geoscience and Remote Sensing Symposium (IGARSS), 2014, Canada, Quebec City.
4. Baik, J.J., Choi, M., Evaluation of geostationary satellite (COMS) based Priestley–Taylor evapotranspiration. Agr. Water. Manage. 159 (2015), 77–91.
5. Baker, I., Prihodko, L., Denning, A., Goulden, M., Miller, S., Da Rocha, H., Seasonal drought stress in the Amazon: reconciling models and observations. J. Geophys. Res. Biogeosci., 113(G1), 2008.
6. Bausch, W.C., Remote sensing of crop coefficients for improving the irrigation scheduling of corn. Agr. Water. Manage. 27:1 (1995), 55–68.
7. Boonjung, H., Fukai, S., Effects of soil water deficit at different growth stages on rice growth and yield under upland conditions. 2. Phenology, biomass production and yield. Field. Crop. Res. 48:1 (1996), 47–55.
8. Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martínez-Fernández, J., Llorens, P., Latron, J., Martin, C., Bittelli, M., Soil moisture estimation through ASCAT and AMSR-E sensors: an intercomparison and validation study across Europe. Remote Sens. Environ. 115:12 (2011), 3390–3408.
9. Bunce, J.A., Does transpiration control stomatal responses to water vapour pressure deficit?. Plant Cell Environ. 20:1 (1997), 131–135.
10. Campos, I., Neale, C.M.U., Calera, A., Balbontín, C., González-Piqueras, J., Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.). Agr. Water. Manage. 98:1 (2010), 45–54.
11. Choi, M., Parameterizing daytime downward longwave radiation in two Korean regional flux monitoring network sites. J. Hydrol. 476 (2013), 257–264.
12. Choudhury, B.J., Ahmed, N.U., Idso, S.B., Reginato, R.J., Daughtry, C.S.T., Relations between evaporation coefficients and vegetation indices studied by model simulations. Remote Sens. Environ. 50:1 (1994), 1–17.
13. Doorenbos, J., Kassam, A.H., Yield response to water Rome, Italy. Irrigation and Drainage Paper 33, 1979.
14. Duchemin, B., Hadria, R., Erraki, S., Boulet, G., Maisongrande, P., Chehbouni, A., Escadafal, R., Ezzahar, J., Hoedjes, J.C.B., Kharrou, M.H., Khabba, S., Mougenot, B., Olioso, A., Rodriguez, J.C., Simonneaux, V., Monitoring wheat phenology and irrigation in Central Morocco: on the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices. Agr. Water. Manage. 79:1 (2006), 1–27.
15. Earnshaw, K.M., Orr, B., Soil moisture, field-scale toposequential position, and slope effects on yields in irrigated rice (Oryza sativa L.) fields in Honduras. Agric. Sci. 4:8A (2013), 1–8, 10.4236/as.2013.48A001.
16. Er-Raki, S., Chehbouni, A., Boulet, G., Williams, D., Using the dual approach of FAO-56 for partitioning ET into soil and plant components for olive orchards in a semi-arid region. Agr. Water. Manage. 97:11 (2010), 1769–1778.
17. Fung, A.K., Eom, H.J., A comparison between active and passive sensing of soil moisture from vegetated terrains. IEEE. T. Geosci. Remote. GE-23:5 (1985), 768–775.
18. Glenn, E.P., Neale, C.M.U., Hunsaker, D.J., Nagler, P.L., Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems. Hydrol. Process. 25:26 (2011), 4050–4062.
19. Gontia, N.K., Tiwari, K.N., Estimation of crop coefficient and evapotranspiration of wheat (Triticum aestivum) in an irrigation command using remote sensing and GIS. Water Resour. Manag. 24:7 (2010), 1399–1414.
20. Gonzalez-Dugo, M.P., Neale, C.M.U., Mateos, L., Kustas, W.P., Prueger, J.H., Anderson, M.C., Li, F., A comparison of operational remote sensing-based models for estimating crop evapotranspiration. Agric. For. Meteorol. 149:11 (2009), 1843–1853.
21. Gruhier, C., de Rosnay, P., Hasenauer, S., Holmes, T., de Jeu, R., Kerr, Y., Mougin, E., Njoku, E., Timouk, F., Wagner, W., Soil moisture active and passive microwave products: intercomparison and evaluation over a Sahelian site. Hydrol. Earth Syst. Sci. Discuss. 14 (2010), 141–156, 10.5194/hess-14-141-2010.
22. Guerschman, J.P., Van Dijk, A.I.J.M., Mattersdorf, G., Beringer, J., Hutley, L.B., Leuning, R., Pipunic, R.C., Sherman, B.S., Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia. J. Hydrol. 369:1–2 (2009), 107–119.
23. Hagan, R.M., Factors affecting soil moisture-plant growth relations. Report of the XIV International Horticultural Congress, Scheveningen, Netherlands, 1955 Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.499.8192&rep=rep1&type=pdf.
24. Hagemann, S., Stacke, T., Impact of the soil hydrology scheme on simulated soil moisture memory. Clim. Dyn. 44:7 (2014), 1731–1750.
25. Hatfield, J.L., Asrar, G., Kanemasu, E.T., Intercepted photosynthetically active radiation estimated by spectral reflectance. Remote Sens. Environ. 14:1–3 (1984), 65–75.
26. Hengl, T., Heuvelink, G.B., Tadić, M.P., Pebesma, E.J., Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images. Theor. Appl. Climatol. 107:1–2 (2012), 265–277.
27. Hunsaker, D., Pinter, P. Jr., Barnes, E., Kimball, B., Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index. Irrig. Sci. 22:2 (2003), 95–104.
28. Hunsaker, D.J., Fitzgerald, G.J., French, A.N., Clarke, T.R., Ottman, M.J., Pinter, P.J. Jr., Wheat irrigation management using multispectral crop coefficients: I. Crop evapotranspiration prediction. T. ASABE. 50:6 (2007), 2017–2033.
29. Hwang, K., Choi, M., Seasonal trends of satellite-based evapotranspiration algorithms over a complex ecosystem in East Asia. Remote Sens. Environ. 137 (2013), 244–263.
30. Jang, K., Kang, S., Kim, J., Lee, C.B., Kim, T., Kim, J., Hirata, R., Saigusa, N., Mapping evapotranspiration using MODIS and MM5 four-dimensional data assimilation. Remote Sens. Environ. 114:3 (2010), 657–673.
31. Jang, K., Kang, S., Lim, Y.-J., Jeong, S., Kim, J., Kimball, J.S., Hong, S.Y., Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System. J. Geophys. Res. - Atmos., 118(23), 2013 (2013JD020639).
32. Jiang, X., Kang, S., Tong, L., Li, F., Li, D., Ding, R., Qiu, R., Crop coefficient and evapotranspiration of grain maize modified by planting density in an arid region of northwest China. Agr. Water. Manage. 142 (2014), 135–143.
33. Kamble, B., Kilic, A., Hubbard, K., Estimating crop coefficients using remote sensing-based vegetation index. Remote Sens. 5:4 (2013), 1588–1602.
34. Kim, J., Hogue, T.S., Evaluation of a MODIS-based potential evapotranspiration product at the point scale. J. Hydrometeorol. 9:3 (2008), 444–460.
35. Kim, J., Guo, Q., Baldocchi, D.D., Leclerc, M.Y., Xu, L., Schmid, H.P., Upscaling fluxes from tower to landscape: overlaying flux footprints on high-resolution (IKONOS) images of vegetation cover. Agric. For. Meteorol. 136:3–4 (2006), 132–146.
36. Kim, H., Hwang, K., Mu, Q., Lee, S., Choi, M., Validation of MODIS 16 global terrestrial evapotranspiration products in various climates and land cover types in Asia. KSCE J. Civ. Eng. 16:2 (2012), 229–238.
37. Klemas, V., Finkl, C.W., Kabbara, N., Remote sensing of soil moisture: an overview in relation to coastal soils. J. Coast. Res. 30:4 (2014), 685–696.
38. Kljun, N., Calanca, P., Rotach, M.W., Schmid, H.P., A simple two-dimensional parameterization for flux footprint prediction (FFP). Geosci. Model Dev. 8 (2015), 3695–3713.
39. Kwon, H., Park, S., Kang, M., Yoo, J., Yuan, R., Kim, J., Quality control and assurance of eddy covariance data at the two KoFlux sites. Korea J Agric. For. Meterol. 9:4 (2007), 260–267.
40. Lee, S.M., Byun, H.R., Tanaka, H.L., Spatiotemporal characteristics of drought occurrences over Japan. J. Appl. Meteorol. 51:6 (2012), 1087–1098.
41. Lei, H., Yang, D., Combining the crop coefficient of winter wheat and summer maize with a remotely sensed vegetation index for estimating evapotranspiration in the North China plain. J. Hydrol. Eng. 19:1 (2014), 243–251.
42. Li, X., Liang, S., Yuan, W., Yu, G., Cheng, X., Chen, Y., Zhao, T., Feng, J., Ma, Z., Ma, M., Liu, S., Chen, J., Shao, C., Li, S., Zhang, X., Zhang, Z., Sun, G., Chen, S., Ohta, T., Varlagin, A., Miyata, A., Takagi, K., Saiqusa, N., Kato, T., Estimation of evapotranspiration over the terrestrial ecosystems in China. Ecohydrology 7:1 (2014), 139–149.
43. Liu, Y., Parinussa, R., Dorigo, W., De Jeu, R., Wagner, W., Van Dijk, A., McCabe, M., Evans, J., Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrol. Earth Syst. Sci. 15:2 (2011), 425–436.
44. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M., 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.
45. Loew, A., Stacke, T., Dorigo, W., Jeu, R.d., Hagemann, S., Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies. Hydrol. Earth Syst. Sci. 17:9 (2013), 3523–3542.
46. Marsal, J., Johnson, S., Casadesus, J., Lopez, G., Girona, J., Stöckle, C., Fraction of canopy intercepted radiation relates differently with crop coefficient depending on the season and the fruit tree species. Agric. For. Meteorol. 184 (2014), 1–11.
47. McCabe, M.F., Wood, E.F., Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors. Remote Sens. Environ. 105:4 (2006), 271–285.
48. Miralles, D.G., Gash, J.H., Holmes, T.R.H., de Jeu, R.A.M., Dolman, A.J., Global canopy interception from satellite observations. J. Geophys. Res. - Atmos., 115(D16), 2010 (D16122).
49. Moormann, F.R., Breemen, N.v., Rice: soil, water, land. Rice: Soil, Water, Land, 1978, International Rice Research Institute.
50. Motohka, T., Nasahara, K.N., Murakami, K., Nagai, S., Evaluation of sub-pixel cloud noises on MODIS daily spectral indices based on in situ measurements. Remote Sens. 3:8 (2011), 1644–1662.
51. Mu, Q., Heinsch, F.A., Zhao, M., Running, S.W., Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sens. Environ. 111:4 (2007), 519–536.
52. Neale, C.M.U., Bausch, W.C., Heermann, D.F., Development of reflectance-based crop coefficients for corn. T. ASAE. 32:6 (1989), 1891–1899.
53. Odhiambo, L.O., Irmak, S., Evaluation of the impact of surface residue cover on single and dual crop coefficient for estimating soybean actual evapotranspiration. Agr. Water. Manage. 104 (2012), 221–234.
54. Park, J.M., Byun, K.H., Choi, M., Jang, E., Lee, J.H., Lee, Y.K., Jung, S.W., Evaluation of statistical gap fillings for continuous energy flux (evapotranspiration) measurements for two different land cover types. Stoch. Env. Res. Risk A. 29:8 (2015), 2021–2035, 10.1007/s00477-015-1101-x.
55. Pereira, L.S., Allen, R.G., Smith, M., Raes, D., Crop evapotranspiration estimation with FAO56: past and future. Agr. Water. Manage. 147 (2015), 4–20.
56. Piao, S., Mohammat, A., Fang, J., Cai, Q., Feng, J., NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China. Glob. Environ. Chang. 16:4 (2006), 340–348.
57. Pratola, C., Barrett, B., Gruber, A., Kiely, G., Dwyer, E., Evaluation of a global soil moisture product from finer spatial resolution SAR data and ground measurements at Irish sites. Remote Sens. 6:9 (2014), 8190–8219.
58. Saito, M., Miyata, A., Nagai, H., Yamada, T., Seasonal variation of carbon dioxide exchange in rice paddy field in Japan. Agric. For. Meteorol. 135:1–4 (2005), 93–109.
59. Serbin, S.P., Ahl, D.E., Gower, S.T., Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence. Remote Sens. Envion. 133:15 (2013), 71–84.
60. Shrestha, N.K., Shukla, S., Support vector machine based modeling of evapotranspiration using hydro-climatic variables in a sub-tropical environment. Agric. For. Meteorol. 200 (2015), 172–184.
61. Singh, R.K., Irmak, A., Estimation of crop coefficients using satellite remote sensing. J. Irrig. Drain. Eng. 135:5 (2009), 597–608.
62. Sur, C.Y., Hur, J.W., Kim, K.J., Choi, W.J., Choi, M.H., An evaluation of satellite-based drought indices on a regional scale. Int. J. Remote Sens. 36:22 (2015), 5593–5612.
63. Thanyapraneedkul, J., Muramatsu, K., Daigo, M., Furumi, S., Soyama, N., Improvement of terrestrial GPP estimation algorithm using satellite and flux data. International Archives of the Photogrammetry, Remote Sensing, and Spatial Information Science, Vol. XXXVIII, 2010 (Part 8, Kyoto Japan).
64. Tian, Y., Dickinson, R.E., Zhou, L., Zeng, X., Dai, Y., Myneni, R.B., Knyazikhin, Y., Zhang, X., Friedl, M., Yu, H., Wu, W., Shaikh, M., Comparison of seasonal and spatial variations of leaf area index and fraction of absorbed photosynthetically active radiation from Moderate Resolution Imaging Spectroradiometer (MODIS) and Common Land Model. J. Geophys. Res. - Atmos., 109(D1), 2004 (D01103).
65. Twine, T.E., Kustas, W.P., Norman, J.M., Cook, D.R., Houser, P.R., Meyers, T.P., Prueger, J.H., Starks, P.J., Wesley, M.L., Correcting eddy-covariance flux underestimates over a grassland. Agric. For. Meteorol. 100 (2000), 279–300.
66. Veihmeyer, F., Hendrickson, A., Soil moisture in relation to plant growth. Annu. Rev. Plant Physiol. 1:1 (1950), 285–304.
67. Vischel, T., Pegram, G., Sinclair, S., Wagner, W., Bartsch, A., Comparison of soil moisture fields estimated by catchment modelling and remote sensing: a case study in South Africa. Hydrol. Earth Syst. Sci. 12:3 (2008), 751–767.
68. Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, 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, I-7, 2012 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia.
69. Wang, X., Xie, H., Guan, H., Zhou, X., Different responses of MODIS-derived NDVI to root-zone soil moisture in semi-arid and humid regions. J. Hydrol. 340:1–2 (2007), 12–24.
70. Waring, R.H., Running, S.W., Forest Ecosystems: Analysis at Multiple Scales. third ed., 2007, Academic Press, San Diago.
71. Willmott, C.J., Robeson, S.M., Matsuura, K., A refined index of model performance. Int. J. Climatol. 32:13 (2012), 2088–2094.
72. Wu, J., Guan, D., Han, S., Shi, T., Jin, C., Pei, T., Yu, G., Energy budget above a temperate mixed forest in northeastern China. Hydrol. Process. 21:18 (2007), 2425–2434, 10.1002/hyp.6395.
73. Xu, L., Samanta, A., Costa, M.H., Ganguly, S., Nemani, R.R., Myneni, R.B., Widespread decline in greenness of Amazonian vegetation due to the 2010 drought. Geophys. Res. Lett., 38(7), 2011, L07402.
74. Yan, K., Park, T., Yan, G., Chen, C., Yang, B., Liu, Z., Nemani, R.R., Knyazikhin, Y., Myneni, R.B., Evaluation of MODIS LAI/FPAR Product Collection 6. Part 1: Consistency and Improvements. Remote Sens., 8(5), 2016, 359.
75. Yang, W., Shabanov, N.V., Huang, D., Wang, W., Dickinson, R.E., Nemani, R.R., Knyazikhin, Y., Myneni, R.B., Analysis of leaf area index products from combination of MODIS Terra and Aqua data. Remote Sens. Environ. 104:3 (2006), 297–312.
76. Yang, Y., Feng, Z., Huang, H.Q., Lin, Y., Climate-induced changes in crop water balance during 1960-2001 in Northwest China. Agric. Ecosyst. Environ. 127:1–2 (2008), 107–118.
77. Yu, G., Fu, Y., Sun, X., Wen, X., Zhang, L., Recent progress and future directions of ChinaFLUX. Sci. China. Ser. D. 49:2 (2006), 1–23.
78. Yu, Q., Wang, S., Mickler, R.A., Huang, K., Zhou, L., Yan, H., Chen, D., Han, S., Narrowband bio-indicator monitoring of temperate Forest carbon fluxes in northeastern China. Remote Sens. 6 (2014), 8986–9013.