Estimating water requirement of forage maize and sugar beet using remote sensing (case study: Qazvin plain)
Subject Areas : Farm water management with the aim of improving irrigation management indicatorsحمیده نوری 1 , ALI Mokhtari 2 , Alireza Badiyeneshin 3
1 - استاد دانشگاه/دانشگاه تهران
2 - Department of Irrigation and Reclamation Eng., College of Agriculture and Natural Resources, University of Tehran
3 - Department of Irrigation and Reclamation Eng., College of Agriculture and Natural Resources, University of Tehran
Keywords: SWAP, vegetation indices, potential evapotranspiration, Crop coefficient, Priestly-Taylor,
Abstract :
In this study, Kc curves of early- and late-planted fodder maize and sugar beet were obtained based on two main satellite-based methods: (1) ratio approach (2) vegetation indices (VIs) approach. In the ratio approach, basal crop coefficient (Kcb) and single crop coefficient (Kc) was directly calculated from the ratio of potential transpiration (Tp) to ET0 (using SWAP) and ETp to ET0 (using SWAP and the Priestly-Taylor equation), respectively. The VI approach makes use of Landsat 7 (ETM+) and 8 (OLI) and also MODIS imagery in order to extract soil adjusted vegetation index (SAVI). The Kcb curves were evaluated against field measured leaf area index (LAI) in 2012 growing season. After each Kc curve was modeled, net irrigation requirement (NIR) was calculated on daily and season basis. Results showed that the SWAP approach was weak in estimating the Kcb and Kc curves especially at late-season stage. The VI approach could properly detect changes in vegetation cover during an entire growing season. But, when it came to Kc curve modelling, the VI approach was limited to the values given in FAO 56. However, the Priestly-Taylor approach compensated for the aforesaid limitation; therefore, yielded more sensible trends in Kc curves. Therefore satellite-based approaches derived from more realistic Kc curves during the entire growing season. Overall, making use of the satellite-based approaches could improve water management on regional scales.
Agam, N., Kustas, W. P., Anderson, M. C., Li, F., and Neale, C. M. 2007. A vegetation index based technique for spatial sharpening of thermal imagery. Remote Sensing of Environment, 107(4), 545-558.
Agron. J., 81, 650-662.
Allen, R. G. 1995. Evaluation of procedures for estimating mean monthly solar radiation from air temperature.
Allen, R. G., and Pruitt, W. O. 1986. Rational use of the FAO Blaney-Criddle formula. Journal of Irrigation and Drainage Engineering, 112(2), 139-155.
Allen, R. G., Jensen, M. E., Wright, J. L., and Burman, R. D. 1989. Operational estimates of reference evapotranspiration. Agronomy journal, 81(4), 650-662.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. 1998. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9), D05109.
Allen, R. G., Pereira, L. S., Smith, M., Raes, D., and Wright, J. L. 2005. FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions. Journal of irrigation and drainage engineering, 131(1), 2-13.
Allen, R. G., Walter, I. A., Elliott, R. L., Howell, T. A., Itenfisu, D., Jensen, M. E., and Snyder, R. L., eds. 2005b. The ASCE standardized reference evapotranspiration equation, American Society of Civil Engineers, Reston, Va.Rosenberg, N. J., Blad, B. L., and Verma, S. B. 1983. Microclimate: the biological environment. John Wiley and Sons.
Allen, R. G., Pruitt, W. O., Raes, D., Smith, M., and Pereira, L. S. 2005a. Estimating evaporation from bare soil and the crop coefficient for the initial period using common soils information. Journal of irrigation and drainage engineering, 131(1), 14-23.
Allen, R. G., and Pereira, L. S. 2009. Estimating crop coefficients from fraction of ground cover and height. Irrigation Science, 28(1), 17-34.
Andrieu, B., Allirand, J. M., and Jaggard, K. 1997. Ground cover and leaf area index of maize and sugar beet crops. Agronomie, 17(6-7), 315-321.
Bastiaanssen, W. G., Ahmad, M. U. D., and Chemin, Y. 2002. Satellite surveillance of evaporative depletion across the Indus Basin. Water Resources Research, 38(12).
Bastiaanssen, W. G. M., Menenti, M., Feddes R. A., and Holtslag, A. A. M.. 1998. A remote sensing surface energy balance algorithm for land SEBAL: 1. Formulation. Journal of Hydrology, 212–213, 198–212
Bausch, W.C., Neale, C.M.U., 1987. Crop coefficients derived from reflected canopy radiation: a concept. Transactions of the ASAE 30, 703–709.Beständen. Schriftenreihe des DVWK 57, 1-53.
Bouyoucos, G. J. 1962. Hydrometer method improved for making particle size analyses of soils. Agronomy journal, 54(5), 464-465
Braden, H., 1985. Ein Energiehaushalts- und Verdunstungsmodell for Wasser und
Choudhury, B. J., Ahmed, N. U., Idso, S. B., Reginato, R. J., and Daughtry, C. S. 1994. Relations between evaporation coefficients and vegetation indices studied by model simulations. Remote sensing of environment, 50(1), 1-17.
Buckman, H. O., and Brady, N. C. 1960. The nature and properties of soils. Soil Science, 90(3), 212.
Clevers, J. G. P. W. 1988. The derivation of a simplified reflectance model for the estimation of leaf area index. Remote Sensing of Environment, 25(1), 53-69.
Deutsche Bodenkundliche Geselschaft, 42, 294-299.
Doherty, J. 2002. PEST: Model-Independent Parameter Estimation, 4 ed, Watermark Numerical Computing, Brisbane, Queensland.
González-Dugo, M. P., and Mateos, L. 2008. Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops. Agricultural water management, 95(1), 48-58.
González-Dugo, M. P., Escuin, S., Cano, F., Cifuentes, V., Padilla, F. L. M., Tirado, J. L., and Mateos, L. 2013. Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. II. Application on basin scale. Agricultural water management, 125, 92-104.
Gonzalez-Dugo, M. P., Neale, C. M. U., Mateos, L., Kustas, W. P., Prueger, J. H., Anderson, M. C., and Li, F. 2009. A comparison of operational remote sensing-based models for estimating crop evapotranspiration. Agricultural and Forest Meteorology, 149(11), 1843-1853.
Heilman, J. L., Heilman, W. E., and Moore, D. G. 1982. Evaluating the crop coefficient using spectral reflectance. Agronomy Journal, 74(6), 967-971.
Huete, A. R., Jackson, R. D., and Post, D. F. 1985. Spectral response of a plant canopy with different soil backgrounds. Remote sensing of environment, 17(1), 37-53.
Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote sensing of environment, 25(3), 295-309.
Iqbal M., (1983). "An Introduction to Solar Radiation". Iqbal, M. Editorial: Academic Press, Toronto, Canada.
Irmak, S., Djaman, K., and Sharma, V. 2015. Winter Wheat (Triticum aestivum L.) Evapotranspiration and Single (Normal) and Basal Crop Coefficients. Transactions of the ASABE, 58(4), 1047-1066.
Jackson, R. D., and Huete, A. R. 1991. Interpreting vegetation indices. Preventive veterinary medicine, 11(34), 185-200.
Jackson, R. D., Idao, S. B., Reginato, R. J., and Pinter, P. J. (1980). Remotely sensed crop temperatures and reflectances as inputs to irrigtion scheduling.
Jensen, M. E., and Haise, H. R. 1963. Estimating evapotranspiration from solar radiation. Proceedings of the American Society of Civil Engineers, Journal of the Irrigation and Drainage Division, 89, 15-41.
Jensen, M. E., Burman, R. D., and Allen, R. G. 1990 Evapotranspiration and irrigation water requirements. ASCE.
Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., and Baret, F. (2004). Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agricultural and forest meteorology, 121(1), 19-35.
Kamble, B., Kilic, A., and Hubbard, K. 2013. Estimating crop coefficients using remote sensing-based vegetation index. Remote Sensing, 5(4), 1588-1602.
Kroes, J. G., Van Dam, J. C., Groenendijk, P., Hendriks, R. F. A., and Jacobs, C. M. J. 2008. SWAP version 3.2. Theory description and user manual. Alterra report, 1649.
Kustas, W. P., Norman, J. M., Anderson, M. C., and French, A. N. 2003. Estimating subpixel surface temperatures and energy fluxes from the vegetation index–radiometric temperature relationship. Remote sensing of Environment, 85(4), 429-440.
Martínez-Ferri, E., Muriel-Fernández, J. L., and Díaz, J. A. 2013. Soil water balance modelling using SWAP: an application for irrigation water management and climate change adaptation in citrus. Outlook on AGRICULTURE, 42(2), 93-102.
Mateos, L., González-Dugo, M. P., Testi, L., and Villalobos, F. J. 2013. Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. I. Method validation. Agricultural water management, 125, 81-91.
McMahon, T. A., Peel, M. C., Lowe, L., Srikanthan, R., and McVicar, T. R. 2013. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences, 17(4), 1331-1363.
Melton, F. S., Johnson, L. F., Lund, C. P., Pierce, L. L., Michaelis, A. R., Hiatt, S. H., and Votava, P. 2012. Satellite irrigation management support with the terrestrial observation and prediction system: a framework for integration of satellite and surface observations to support improvements in agricultural water resource management. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(6), 1709-1721.
Monteith, J. L. 1965. Light distribution and photosynthesis in field crops. Annals of Botany, 29(1), 17-37.
Monteith, J. L. 1981. Evaporation and surface temperature. Quarterly Journal of the Royal Meteorological Society, 107(451), 1-27.
Moran, M. S., Maas, S. J., and Pinter Jr, P. J. 1995. Combining remote sensing and modeling for estimating surface evaporation and biomass production. Remote Sensing Reviews, 12(3-4), 335-353.
Neale, C. M., Bausch, W. C., and Heermann, D. F. 1990. Development of reflectance-based crop coefficients for corn. Transactions of the ASAE, 32(6), 1891-1900.
Paço, T. A., Ferreira, M. I., Rosa, R. D., Paredes, P., Rodrigues, G. C., Conceição, N., and Pereira, L. S. 2012. The dual crop coefficient approach using a density factor to simulate the evapotranspiration of a peach orchard: SIMDualKc model versus eddy covariance measurements. Irrigation Science, 30(2), 115-126.
Parodi, N., and Gabriel, Ir. 2002. AHVRR Hydrological Analysis System Algorithms and theory - Version 1.3. John Wiley and Sons, NewYork.
Priestley, C. H. B., and Taylor R.J. 1972. On the assessment of surface heat flux and evaporation using large scale parameters. In Mon. Weather Rev.
Rouse, J. W., Haas, R. H., Jr., Schell, J. A., and Deering, D. W. 1974. Monitoring vegetation systems in the Great Plains with ERTS. Third ERTS-1 Symposium (pp. 309–317). Washington, DC: NASA.
Samani, Z. 2000. Estimating solar radiation and evapotranspiration using minimum climatological data. Journal of Irrigation and Drainage Engineering, 126(4), 265-267.
Shao, L. W., Zhang, X. Y., Sun, H. Y., Chen, S. Y., and Wang, Y. M. 2011. Yield and water use response of winter wheat to winter irrigation in the North China Plain. Journal of Soil and Water Conservation, 66(2), 104-113.
Sobrino, J. A., Jiménez-Muñoz, J. C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J., and Martínez, P. 2008. Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscience and Remote Sensing, 46(2), 316-327.
Steduto, P., Hsiao, T. C., Fereres, E., and Raes, D. 2012. Crop yield response to water. Roma: FAO.
Sun, D., and Kafatos, M. 2007. Note on the NDVI‐ LST relationship and the use of temperature‐ related drought indices over North America. Geophysical Research Letters, 34(24).
Vazifedoust, M., Van Dam, J. C., Bastiaanssen, W. G. M., Feddes, R. A., 2009. Assimilation of satellite data into agrohydrological models to improve crop yield forecasts. International Journal of Remote Sensing. 30(10), 2523-2545.
Viña, A., Gitelson, A. A., Nguy-Robertson, A. L., and Peng, Y. 2011. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sensing of Environment, 115(12), 3468-3478.
Von Hoyningen-Hüne, J., 1983. Die Interception des Niederschlags in landwirtschaftlichen
Waters, R., Allen, R., Tasumi, M., Trezza, R., and Bastiaanssen, W. G. M. 2002. SEBAL (Surface Energy Balance Algorithms for Land): advanced training and user’s manual. Department of Water Resources, University of Idaho, Kimberly, 98P.
Zhang, X., Pei, D., and Chen, S. 2004. Root growth and soil water utilization of winter wheat in the North China Plain. Hydrol. Proc., 18(12), 2275-2287. http://dx.doi.org/10.1002/hyp.5533.
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