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SULAMA SUYU YÖNETİMİNDE UZAKTAN ALGILAMA TEKNİKLERİNİN KULLANIMI

Yıl 2007, Cilt: 22 Sayı: 3, 306 - 315, 31.12.2007

Öz

Sulama suyu yönetimi bitki, toprak ve iklim faktörlerini kapsayan oldukça karmaşık bir temele dayanır. Herhangi bir bitkinin ne zaman ve ne kadar sulama suyuna gereksinim duyduğunun ve / veya bir yetişme döneminde ne kadar bitki su tüketimi (ETc) gerçekleştiğinin belirlenmesi veya tahmin edilmesi amacı ile bir çok yöntem geliştirilmiştir. Son zamanlarda bitki izlemeye dayalı yöntemlerden, uzaktan algılama teknikleri öne çıkmaktadır ve bu konudaki araştırmalar 1960’ lı yıllara dayanmaktadır. Ülkemizde uzaktan algılama tekniklerinin sulama suyu yönetiminde kullanım olanaklarını ortaya koymayı hedefleyen az sayıda çalışma bulunmaktadır. Hazırlanan bu makale ile amaçlanan, son kırk yılda konu ile ilgili yapılmış çalışmalardan önde gelenlerini sonuçları ile birlikte derlemektir.

Kaynakça

  • Abdul-Jabbar, A.S, Lugg, D.G., Sammis, T.W., Gay, L.W. 1985. Relationships between crop water stress index and Alfalfa yield and evapotranspiration. Trans. ASAE. Pp:454-461.
  • Alderfasi, A.A., Nielsen, D.C. 2001. Use of crop water stress index for monitoring water status and scheduling irrigation in whet. Agricultural Water Management, 47:69–75.
  • Allen, R. G. Tasumi, M., Morse, A., Trezza, R., 2005. A Landsat-based energy balance and evapotrapiration model in Western US water rights regulation and planning. Irriggation and Drainage Sysytms, 19:251268.
  • Allen, R.G., Pereira, L.S., Raes, D., Smith, M. 1998. Crop evapotranspiration, FAO, 300, Rome.
  • Allen, R.G., Tasumi, M., Morse, A., Trezza, R., Kramber, W., Lorite, I. and Robison, W. 2006. Water management applications using evapotranpiration maps from satellite – based energy balance. International Symposium on Water and Land Management for Sustainable Irrigated Agriculture. Adana. Turkey.
  • Alves, I., Pereira, L.S. 2000. Non-water-stressed baselines for irrigation scheduling with infrared thermometers: A new approach. Irrigation Science, 19:101-106.
  • Aparicio, N., Viellegas, D., Royo, C., Casadesus, J., Araus, J.L. 2004. Effect of sensor view angle on the assessment of agronomic traits by ground level hyper-spectral reflectance measurements in durum wheat under contrasting Mediterranean conditions. Int. J. Remote sensing, 25(6):1131-1152.
  • ASCE – EWRI., 2005. The ASCE Standardized reference evapotranspiration equation. ASCE-EWRI Standardization of Reference Evapotranspiration Task Comm. Report. Available from URL: http://www.kimberly.uidaho.edu/water/asceewri/
  • Asrar, G., Myneni, R.B., Li, Y., Kanemasu, E.T. 1989. Measuring and modeling spectral characteristics of tall grass prairie. Remote Sens. Environ., 27:143-155.
  • Bastiaanssen, W. G. M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F. Roerink, G. J., van der Wal, T., 1998a. A remote sensing surface energy balance algorithm for land (SEBAL) 1.Formulation. Journal of Hydrology 212-213:213-229.
  • Bastiaanssen, W. G. M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F. Roerink, G. J., van der Wal, T., 1998b. A remote sensing surface energy balance algorithm for land (SEBAL) 2.Validation. Journal of Hydrology 212213:213-229.
  • Blad, B. L., Rosenberg, N. J. 1975. Measurement of crop temperature by leaf thermocouple, infrared thermometry and remotely sensed thermal imagery, Agronomy J.l, 65:635-641.
  • Boegh, E., Soegaard, H., Broge, A., Hasager, C.B., Jensne, N.O., Schelde, K., Thomsen, A. 2002. Airborne multispectral data for quantifying leaf area index, nitrogen concentration and photosynthetic efficiency in agriculture. Remote Sens. Environ., 81:179-193.
  • Bowman, W.D. 1989. The relationship between leaf water status, gas exchange, and spectral reflectance in cotton leaves. Remote Sens. Environ. 30:249-255.
  • Brown, K.W., Rosenberg, N.J. 1973. A resistance model to predict evapotranspiration and its application to a sugar beet field. Agronomy J., 65(3):341-347.
  • Carter, G. A. 1993. Responses of leaf reflectance to plant stress. American J. Botany, 80:239-243.
  • Carter, G. A.. 1991. Primary and secondary effects of water content on the spectral reflectance of leaves. American J. Botany, 78:916-924.
  • Ceccato, P., Flasse, S., Tarantola, S., Jacquemoud, S., Gregoire, J.M. 2001. Detecting vegetation leaf water content using reflectance in the optical domain, Remote Sens. Environ., 77:22-33.
  • Chenbouni, A., Nouvellon, Y, Kerr, Y.H., Moran, M.S., Watts, C., Prevot, L., Goodrich, D.C., Rembal, S. 2001. Directional effect on radiative surface temperature measurements over a semiarid grassland site. Remote Sens. Environ., 76:360-372.
  • Choudhury, B.J., Idso, S.B. 1984. Simulating sunflower canopy temperatures to infer root-zone soil water potential. Agricultural and Forest Meteorology, 31:6978.
  • Choudhury, B.J., Idso, S.B., Reginato, R.J. 1986 Analysis of a resistance-energy balance method for estimating daily evaporation from wheat plots using one-time-of-day infrared temperature observations. Remote Sens. Environ., 19:253-268.
  • Cohen, W.B. 1991. Temporal versus spatial variation in leaf reflectance under changing water stress conditions. Int. J. Remote Sens. 12:1865-1876.
  • Cure, W. W., Flagler, R., B., Heagle, A.S. 1989. Correlations between canopy reflectance and leaf temperature in irrigated and droughted soybeans. Remote Sens. Environ. 29:273-280.
  • Danson, M., Steven M. D., Malthus, T. J., Clark, J.A. 1992. High-spectral resolution data for determining leaf water content, Int. J. Remote Sensing, 13:461-470.
  • Ehrler, W.L., Idso, S.B., Jackson, R.D., Reginato, R.J. 1978. Diurnal changes in plant water potential and canopy temperature of wheat as affected by drought. Agronomy J.,70:999-1009.
  • Fitzgerald, G.J., Hunsaker, D.J., Barnes, E.M., Clarke, T.R., Lesch, S.M., Roth, R., Pinter Jr, P.J. 2003. Estimating Cotton Crop Water Use From Multispectral Aerial Imagery. In Irrigation Associations Exposition And Technical Conference, San Diego, Ca, Nov. 18-20. PP.138-148.
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  • Fucs, M., Kanemasu, E.T., Kerr, J.P., Tanner, C.B. 1967. Effect of viewing angle on canopy temperature measurements with infrared thermometers. Agronomy J., 59:494-496.
  • Hatfield, J.L. 1979. Canopy temperatures: The usefulness and reliability of remote measurements. Agronomy J,71:889-892.
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  • Hatfield, J.L., Reginato, R.J., Idso, S.B. 1984. Evaluation of canopy temperature-evapotranspiration models over various crops. Agriculural and Forest Meteorology, 32:41-53.
  • Hattendorf, M.J., Carlson, R.E., Halim, R.A., Buxton, D.R. 1988. Crop water stress index and yield of water-deficitstressed alfalfa. Agronomy Journal, 80:871-875.
  • Howell, T.A., Hatfield, J.L., Yamada, H., Davis, K.R. 1984. Evaluation of cotton canopy temperature to detect crop water stress. Transact. ASAE.Pp:84-88.
  • Howell, T.A., Musick, J.T., Tolk, J.A. 1986. Canopy temperature of irrigated winter wheat. Transact. ASAE. Pp:1692-1698.
  • Hunsaker, D. J., Pinter Jr, P.J., Kimball, B.A., 2005. Wheat Basal Crop Coefficients Determined By Normalized Difference Vegetation Index. Irrigation Science. 24:114.
  • Hunsaker, D.J., Pinter Jr, P.J., Fitzgerald, G.J., Clarke, T.R., Kimball, B.A., Barnes, E.M. 2003b. Tracking Spatial And Temporal Cotton Dt Patterns With A Normalized Difference Vegetation Index. Irrigation Associations Exposition And Technical Conference Proceedings. Pp. 126-137.
  • Hunsaker, D.J., Pinter, Jr. P.J., Barnes E. M., Kimball, B.A. 2003a. Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index. Irrig. Sci.22: 95-104.
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  • Nielsen, D.C., Clawson, K.L., Blad, B.L. 1983. Effect of solar azimuth and Infrared thermometer view direction on measured soybean canopy temperature. Agronomy J, 76:607-610.
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SULAMA SUYU YÖNETİMİNDE UZAKTAN ALGILAMA TEKNİKLERİNİN KULLANIMI

Yıl 2007, Cilt: 22 Sayı: 3, 306 - 315, 31.12.2007

Öz

Sulama suyu yönetimi bitki, toprak ve iklim faktörlerini kapsayan oldukça karmaşık bir temele dayanır. Herhangi bir bitkinin ne zaman ve ne kadar sulama suyuna gereksinim duyduğunun ve / veya bir yetişme döneminde ne kadar bitki su tüketimi (ETc) gerçekleştiğinin belirlenmesi veya tahmin edilmesi amacı ile bir çok yöntem geliştirilmiştir. Son zamanlarda bitki izlemeye dayalı yöntemlerden, uzaktan algılama teknikleri öne çıkmaktadır ve bu konudaki araştırmalar 1960’ lı yıllara dayanmaktadır. Ülkemizde uzaktan algılama tekniklerinin sulama suyu yönetiminde kullanım olanaklarını ortaya koymayı hedefleyen az sayıda çalışma bulunmaktadır. Hazırlanan bu makale ile amaçlanan, son kırk yılda konu ile ilgili yapılmış çalışmalardan önde gelenlerini sonuçları ile birlikte derlemektir

Kaynakça

  • Abdul-Jabbar, A.S, Lugg, D.G., Sammis, T.W., Gay, L.W. 1985. Relationships between crop water stress index and Alfalfa yield and evapotranspiration. Trans. ASAE. Pp:454-461.
  • Alderfasi, A.A., Nielsen, D.C. 2001. Use of crop water stress index for monitoring water status and scheduling irrigation in whet. Agricultural Water Management, 47:69–75.
  • Allen, R. G. Tasumi, M., Morse, A., Trezza, R., 2005. A Landsat-based energy balance and evapotrapiration model in Western US water rights regulation and planning. Irriggation and Drainage Sysytms, 19:251268.
  • Allen, R.G., Pereira, L.S., Raes, D., Smith, M. 1998. Crop evapotranspiration, FAO, 300, Rome.
  • Allen, R.G., Tasumi, M., Morse, A., Trezza, R., Kramber, W., Lorite, I. and Robison, W. 2006. Water management applications using evapotranpiration maps from satellite – based energy balance. International Symposium on Water and Land Management for Sustainable Irrigated Agriculture. Adana. Turkey.
  • Alves, I., Pereira, L.S. 2000. Non-water-stressed baselines for irrigation scheduling with infrared thermometers: A new approach. Irrigation Science, 19:101-106.
  • Aparicio, N., Viellegas, D., Royo, C., Casadesus, J., Araus, J.L. 2004. Effect of sensor view angle on the assessment of agronomic traits by ground level hyper-spectral reflectance measurements in durum wheat under contrasting Mediterranean conditions. Int. J. Remote sensing, 25(6):1131-1152.
  • ASCE – EWRI., 2005. The ASCE Standardized reference evapotranspiration equation. ASCE-EWRI Standardization of Reference Evapotranspiration Task Comm. Report. Available from URL: http://www.kimberly.uidaho.edu/water/asceewri/
  • Asrar, G., Myneni, R.B., Li, Y., Kanemasu, E.T. 1989. Measuring and modeling spectral characteristics of tall grass prairie. Remote Sens. Environ., 27:143-155.
  • Bastiaanssen, W. G. M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F. Roerink, G. J., van der Wal, T., 1998a. A remote sensing surface energy balance algorithm for land (SEBAL) 1.Formulation. Journal of Hydrology 212-213:213-229.
  • Bastiaanssen, W. G. M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F. Roerink, G. J., van der Wal, T., 1998b. A remote sensing surface energy balance algorithm for land (SEBAL) 2.Validation. Journal of Hydrology 212213:213-229.
  • Blad, B. L., Rosenberg, N. J. 1975. Measurement of crop temperature by leaf thermocouple, infrared thermometry and remotely sensed thermal imagery, Agronomy J.l, 65:635-641.
  • Boegh, E., Soegaard, H., Broge, A., Hasager, C.B., Jensne, N.O., Schelde, K., Thomsen, A. 2002. Airborne multispectral data for quantifying leaf area index, nitrogen concentration and photosynthetic efficiency in agriculture. Remote Sens. Environ., 81:179-193.
  • Bowman, W.D. 1989. The relationship between leaf water status, gas exchange, and spectral reflectance in cotton leaves. Remote Sens. Environ. 30:249-255.
  • Brown, K.W., Rosenberg, N.J. 1973. A resistance model to predict evapotranspiration and its application to a sugar beet field. Agronomy J., 65(3):341-347.
  • Carter, G. A. 1993. Responses of leaf reflectance to plant stress. American J. Botany, 80:239-243.
  • Carter, G. A.. 1991. Primary and secondary effects of water content on the spectral reflectance of leaves. American J. Botany, 78:916-924.
  • Ceccato, P., Flasse, S., Tarantola, S., Jacquemoud, S., Gregoire, J.M. 2001. Detecting vegetation leaf water content using reflectance in the optical domain, Remote Sens. Environ., 77:22-33.
  • Chenbouni, A., Nouvellon, Y, Kerr, Y.H., Moran, M.S., Watts, C., Prevot, L., Goodrich, D.C., Rembal, S. 2001. Directional effect on radiative surface temperature measurements over a semiarid grassland site. Remote Sens. Environ., 76:360-372.
  • Choudhury, B.J., Idso, S.B. 1984. Simulating sunflower canopy temperatures to infer root-zone soil water potential. Agricultural and Forest Meteorology, 31:6978.
  • Choudhury, B.J., Idso, S.B., Reginato, R.J. 1986 Analysis of a resistance-energy balance method for estimating daily evaporation from wheat plots using one-time-of-day infrared temperature observations. Remote Sens. Environ., 19:253-268.
  • Cohen, W.B. 1991. Temporal versus spatial variation in leaf reflectance under changing water stress conditions. Int. J. Remote Sens. 12:1865-1876.
  • Cure, W. W., Flagler, R., B., Heagle, A.S. 1989. Correlations between canopy reflectance and leaf temperature in irrigated and droughted soybeans. Remote Sens. Environ. 29:273-280.
  • Danson, M., Steven M. D., Malthus, T. J., Clark, J.A. 1992. High-spectral resolution data for determining leaf water content, Int. J. Remote Sensing, 13:461-470.
  • Ehrler, W.L., Idso, S.B., Jackson, R.D., Reginato, R.J. 1978. Diurnal changes in plant water potential and canopy temperature of wheat as affected by drought. Agronomy J.,70:999-1009.
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  • Kustas, W.P., Daughtry, C.S.T., 1990. Estimation of the soil heat flux/net radiation ratio from spectral data. Agricultural and Forest Meteorology. 49:205-223.
  • Luquet, D., Begue, A., Vidal, A., Clouvel, P., Dauzat, J., Olioso, A., Gu, X.F., Tao, Y. 2003. Using multidirectional thermography to characterize water status of cotton. Remote Sens. Environ., 84:411-421.
  • Monteith J. L., Unsworth M. H., 1990. Principles of Environmental Physics. Second edition. 291 p. Moran, M.S., Clarke, T.R., Inoue, Y., Vidal, A. 1994. Estimating crop water deficit using the relation between surface – air temperature and spectral vegetation index. Remote Sens. Environ., 49:246-263.
  • Moran, M.S., Inou, Y., Barnes, E.M. 1997. Opportunities and limitations for image-based remote sensing in precision crop management. Remote Sens. Environ., 61:319-346.
  • Moran, M.S., Pinter, P.Jr., Clothier, B.E., Allen, S.G. 1989. Effect of water stres on the canopy architecture and spectral indices of irrigated alfalfa. Remote Sens. Environ., 29:251-261.
  • Moran, M.S., Rahman, A.F., Washburne, J.C., Goodrich, D.C:, Waltz, M.A., Kustas, W.P. 1996. Combining the Penman-Monteith equation with measurements of surface temperature and reflectance to estimate evaporation rates of semiarid grassland. Agricultural and Forest Meteorology, 80:87-109.
  • Nielsen, D.C. 1990. Scheduling irrigation for soybeans with the crop water stress index (CWSI). Field Crops Res. 23:103-116.
  • Nielsen, D.C., Anderson, R.L. 1989. Infrared thermometry to measure single leaf temperatures for quantification of water stress in sunflower. Agronomy Journal. 81:840842.
  • Nielsen, D.C., Clawson, K.L., Blad, B.L. 1983. Effect of solar azimuth and Infrared thermometer view direction on measured soybean canopy temperature. Agronomy J, 76:607-610.
  • Olufayo, A., Baldy, C., Ruelle, P. 1996. Sorghum yield, water use and canopy temperatures under different levels of irrigation. Agricultural Water Management. 30:77-90.
  • Orta, A.H., Erdem, T. ve Erdem, Y. 2001. İnfrared termometre tekniği ile ayçiçeğinde bitki su stresi indeksi (CWSI) ve sulama zamanının belirlenmesi. Birinci ulusal sulama kogresi bildirileri., s. 145-153, 8-11 Kasım 2001, Antalya.
  • Penuelas, J., Filella, I., Biel, C., Serrano, L., Save, R., 1993, The reflectance at the 950-970 nm region as an indicator of plant water status. Int. J. Remote Sensing, 14(10):1887-1905.
  • Penuelas, J., Gamon, J.A., Fredeen, A.L., Merino, J., Field, C.B. 1994. Reflectance Indices Associated with physiological changes in nitrogen-and water – limited sunflower leaves. Remote Sens. Environ., 48:135-146.
  • Penuelas, J., Pinol, J., Ogaya, R.,, Fiella, I. 1997. Estimation of plant water concentration by the reflectance Water Index WI (R900/R970), Int. J. Remote Sensing 18:28692875.
  • Pinol, J., Filella, I., Ogaya, R., Penuelas, J. 1998. Groundbased spectroradiometric estimation of live fine fuel moisture of Mediterranean plants. Agricultural and Forest Meteorology., 90:173-186.
  • Pinter, P.J. JR. 1983. Monitoring the effect of water stress on the growth of alfalfa via remotely sensed observations of canopy reflectance and temperature. 18th Conference on Agriculture and Forest Meteorology, April 26-28, 1983. Boston Pp:91-94.
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  • Shibayama, M., Takahashi, W., Morinaga, S., Akiyama, T., 1993. Canopy water deficit detection in paddy rice using a high resolution field spectroradiometer. Remote Sens. Environ., 45:117-126.
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Toplam 92 adet kaynakça vardır.

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Yayımlanma Tarihi 31 Aralık 2007
Yayımlandığı Sayı Yıl 2007 Cilt: 22 Sayı: 3

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APA Köksal, E. (2007). SULAMA SUYU YÖNETİMİNDE UZAKTAN ALGILAMA TEKNİKLERİNİN KULLANIMI. Anadolu Tarım Bilimleri Dergisi, 22(3), 306-315. https://doi.org/10.7161/anajas.2007.22.3.306-315
Online ISSN: 1308-8769