Document Type : Research Paper
Authors
1 PhD Student of Irrigation and Drainage, Sari Agricultural Sciences and Natural Resources University.
2 Associate Professor, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University.
3 Professor, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University.
Abstract
Water demand is one of the most effective factors in irrigation scheduling. In evapotranspiration formulas, crop coefficient (Kc), as a representative of different plants characteristics, is of great importance. Calculating this coefficient using the existing methods and formulas is costly and time-consuming, and results are point-specific. However, nowadays, calculation methods that provide large- scale Kc values are of interest. The methods based on remote sensing have been welcomed by many researchers. The objective of the present study was calculating crop coefficient (Kc) and leaf area index (LAI) of rice in different growing stages, using OLI sensor. In this regard, data LAI of two rice fields (areas of 15 and 65 hectares) located in north part of Sari, Iran, were used in two growing seasons (2014-2015 and 2015-2016). The average Kc at transplantation, tillering, heading, and maturity stages was, respectively, 0.92, 1.24, 1.19, and 1.12, showing that Kc had a good correlation with NDVI at different stages (r>0.97). According to the results, NDVI is a good estimator for rice Kc. In addition, Rice Growth Vegetation Index (RGVI) in all growing stages had a correlation coefficient r>0.93. RGVI is considered as a good estimator of LAI. Approximately at all growing stages, except heading, more than 93% of LAI changes were predicted by RGVI. Generally, it can be concluded that the most suitable indices for estimating Kc and LAI of rice are NDVI and RGVI, respectively.
Keywords
- امینی بازیانی، س.، اکبری، م. و زارع ابیانه، ح. (1392). برآورد سطح و تراکم کشت با استفاده از سنجش از دور در دشت همدان- بهار. نشریه آبیاری و زهکشی ایران. 7 (1). 48-36.
- بخت فیروز، ع. (1390). بررسی اثر سامانههای زهکشی بر گسیل گاز متان و دی اکسید کربن از شالیزارها. پایاننامه کارشناسی ارشد دانشگاه علوم کشاورزی و منابع طبیعی ساری، ص 50.
- پیرمرادیان، ن.، ذکری، ف.، رضایی، م. و عبدالهی، و. (1392). استخراج ضرایب گیاهی سه رقم برنج بر پایه روش برآورد تبخیر- تعرق مرجع در منطقه رشت. تحقیقات غلات. 3(2). 95-106.
- جعفری صیادی، ف. 1395. کاربرد سنجش از دور در براورد سطح زیر کشت و مقدار آب مصرفی برنج. پایاننامه کارشناسیارشد. دانشکده مهندسی زراعی. دانشگاه علوم کشاورزی و منابع طبیعی ساری.
- درویشصفت ع ا.، پیرباوقار م. و رجبپور رحمتی م. (1391). سنجش از دور برای مدیران GIS. چاپ دوم. دانشگاه تهران.
- غلامی سفیدکوهی، م ع.، میرلطیفی، س م.، محمدی، ک. و علیمحمدی، ع. (1389). برآورد ضریب گیاهی و تبخیر- تعرق واقعی گندم با استفاده از سنجش از دور، مطالعه موردی حوضه گرگانرود. نشریه آبیاری و زهکشی ایران. 2(4). 222-231.
- مدبری، ه.، میرلطیفی، س م. و غلامی، م ع. (1393). تعیین تبخیر- تعرق و ضریب گیاهی ارقام هاشمی و خزر برنج در دشت مرداب- گیلان. مجله علوم و فنون کشاورزی و منابع طبیعی، علوم آب و خاک. 18(69). 97- 107.
- Aboelghar, M., Arafat, S., Abo Yousef, M., El-Shirbeny, M., Naeem, S., Massoud, A. and Saleh, N. (2011). Using SPOT data and leaf area index for rice yield estimating in Egyptian Nile Delta. The Egyptian Journal of Remote Sensing and Space. 14. 81-89.
- Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. Irrigation and Drainage paper 56. United Nations FAO, Rome. Italy, 300p.
- Department of the Interior U.S. Geological Survey (USGS). (2015). LANDSAT 8 (L8) DATA USER HANDBOOK. Version 1.
- 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. and Simonneaux, V. (2006). Monitoring wheat phenology and irrigation in Central Morocco: on the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely sensed vegetation index. Agricultural Water Management. 79. 1-27.
- Kamble, B., Kilic, A. and Hubbaed, K. (2013). Estimating Crop Coefficient Using Remote Sensing-Based Vegetation Index. Sensor. 5: 1588-1602.
- Mosleh, M.K., Hassan, Q.K. and Chowdhury, E.H. (2015). Application of Remote Sensing in Mapping Rice Rea and Forecasting Its Production. Sensor. 15: 769-791.
- Russo, A.L., Simoniello, T., Greco, M., Squicciarrino, G., Lanfredi, M. and Macchiato, M. (2010). Correlation between satellite vegetation indeces and crop coefficients. Geophysical Research Abstracts. 12.
- Sari, DK., Isullah, I.H., Sulasdi, W.N. and Harto, A.B. (2013). Estimation of water consumption of lowland rice in tropical area based on heterogeneous cropping calendar using remote sensing technology. Procedia Environmental Sciences. 17. 298-307.
- Yoshida, S. 1981. Fundamentals of Rice Crop Science. The International Rice Research Institute. Philippines.
- Zhang, Y., Qu, Y., Wang, J., Liang, S. and Liu, Y. (2012) Estimating Leaf Area Index from MODIS and surface meteorological data using dynamic Bayesian network. Remote Sensing of Environment. (127). 30-43.
)