The Effect of Different Probability Levels in Estimating the Net Water Requirement of Rice in the Northern Provinces of Iran

Document Type : Research Article

Authors

• E. Asadi Oskouei ¹
• S. Kouzegaran ²
• M.R. Yazdani ³
• A. Rahmani ⁴

¹ Assistant Professor, Climatological Research Institut, ASMERC, Mashhad, Iran

² Ph.D. in Agrometeorology, Applied Meteorological Research Center, Mashhad, Iran

³ Assistant Professor, Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization, Rasht, Iran

⁴ Ph.D. Student of Soil Science, University of Tehran, Tehran, Iran

https://doi.org/10.22067/jsw.2021.71370.1064

Abstract

Introduction: Correct assessment of evapotranspiration fluctuations in different meteorological scenarios plays an important role in the optimal management of water resources. Probability analyzes with different probabilities of occurrence can increase flexibility in decision making and increase the reliability of decisions. Rice (Oryza sativa L.) is one of the most important agricultural products in the world. Although rice is cultivated in a wide range of climatic and geographical conditions, it is vulnerable to changes in environmental conditions. Planting management, design of irrigation systems, and suitable irrigation cycle for optimal production are important issues for sustainable production.
Materials and Methods: The study area includes the northern region of Iran, i.e. the provinces of Gilan, Mazandaran and Golestan, which is the main rice-growing area in Iran. Changes in rice evapotranspiration in three different cultivation dates with four different occurrence probabilities of 75, 50, 25 and 10%, was calculated using the FAO Penman-Monteith equation and meteorological data with a statistical period of 30 years (2020- 1990). Also, the average rice crop coefficient at different stages of growth in 10-day periods was estimated based on the Weibull model. These probabilities represent the probable limits of the expected values of evapotranspiration in different scenarios of low, normal, high, and very high evapotranspiration years.
Results and Discussion: The results showed a relatively constant difference of 1 to 2 mm between different rice cultivation histories in the major rice cultivation areas of Gilan and Mazandaran in normal to very high evapotranspiration years. In the years of low evapotranspiration, the water requirement was significantly different from the normal, high and very high evapotranspiration years, which decreased from east to west. This difference was approximately 30% higher in Golestan province as compared with other areas. In the early planting situation relative to the late planting situation in the major western and central coastal areas, there was a 10% decrease in water consumption. At the scale of the whole growing season in Gorgan, evapotranspiration in different conditions of planting date was on average 20% (1300 cubic meters) more than the main regions of Gilan and Mazandaran. In case of timely planting, the net irrigation requirement in very high evapotranspiration years was about 2000 cubic meters per hectare more than the normal years. In years with high evapotranspiration, late planting increased the net irrigation requirement by more than 210 mm compared to different planting dates in Gorgan. According to the obtained results, the largest difference between evapotranspiration values during normal and very high evapotranspiration years was in the late planting situation. Therefore, it seems that late planting causes a significant increase in water consumption in the high evapotranspiration years. Consequently, it is better to avoid rice cultivation when the rice growing season is anticipated to be warm.
Conclusion: Evapotranspiration, as one of the main components of the hydrological cycle, had a significant role in proper irrigation planning and water resources management. The results underline the importance of estimating the rice evapotranspiration to avoid appreciable yield loss under extreme conditions.

Keywords

• Evapotranspiration
• Probabilistic analysis
• Rice plant
• Water requirement

20.1001.1.20084757.1400.35.5.4.7

Main Subjects

• Irrigation

References

1. 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), p.D05109.
2. AsadiOskouei E., Yazdani M.R., and Alizadeh A. 2017. The effect of submergence depth on evaporation losses in paddy fields. Journal of Water and Soil Conservation 24(1): 221-235. (In Persian with English abstract)
3. Asadi Oskouei E., Mousavi Baygi M., Yazdany M.R., Alizadeh A., and Zohd Ghodsi M.J. 2017. The effect of submergence depth on water and soil temperature in paddy field (Case study: Rasht). Journal of Agricultural Meteorology 5(1): 48-56. (In Persian with English abstract)
4. Heydari M., Marofi M., Sabziparvar A.A., Mirmasoudi S.S., and Ghiyami F. 2009. Investigation of impact of plant water requirement calculation method, length of maximum water requirement period and probability level on optimal estimation of crop water requirement (Case Study: Hamedan), Water and Soil Conservation 16(3): 123-140. (In Persian with English abstract)
5. Jensen M.E., Burman R.D., and Allen R.G. 1990. Evapotranspiration and irrigation water requirements. ASCE.
6. Jensen M.E. 1983. Design and Operation of Farm Irrigation System. The American Society of Agricultural Engineering, USA. 2950 Niles Road St. Joseph Michigan 1-11.
7. Kar G., and Verma H.N. 2005. Climatic water balance, probable rainfall, rice crop water requirements and cold periods in AER 12.0 in India. Agricultural Water Management 72(1): 15-32 .
8. Mehdizadeh S., Behmanesh J., and Nikbakht J. 2011. Estimation of Reference Evapotranspiration with Various Occurrence Probability Levels (Case Study: Urmia), Water and Soil Scienc 20(4): 171-183. (In Persian with English abstract)
9. Mohammad F.S. 1998. Calibration and use of evapotranspiration equations under arid climatic conditions. Agricultural Engineering Journal 7(3&4): 185-200.
10. Nikbakht J., Mohammadi K., and Ehteshami M. 2007. Estimation of actual evapotranspiration of the plant at different probability levels: A case study in Maragheh, East Azerbaijan. Agricultural Sciences 13(1): 95-106. (In Persian with English abstract)
11. Nikbakht J., and MirLatifi M. 2002. The effect of ETo calculation method, probability of occurrence and duration of maximum water consumption on evapotranspiration of reference plant potential. Soil and Water Science 16(2): 223-231. (In Persian with English abstract)
12. Nixon P.R., Lawless G.P., and Richardson G.V. 1972. Coastal California evapotranspiration frequencies. Journal of the Irrigation and Drainage Division 98(2): 185-191.
13. Razavipour T., and Yazdani M. 2000. Determination of Evapotranspiration, plant coefficient, and Pan coefficient of rice, Binam and Caspian cultivars using lysimeter and controlled plots in Rasht region. Journal of Agroecology 6(2): 238-249. (In Persian with English abstract)
14. Pruitt W.O., von Oettingen S., and Morgan D.L. 1972. Central California evapotranspiration frequencies. Journal of the irrigation and drainage Division 98(2): 177-184.
15. Sharifi Bonab S.S., Nazemi A.H., Ashraf Sadraddini A., Fakheri Fard A., and Salmasi F. 2016. Estimation of Irrigation Water Requirement using Probability Distribution Functions (PDF) Case study: (Triticum aestivum), Iranian Journal of Irrigation & Drainage 9(5): 720-730. (In Persian with English abstract)
16. Sharifan H., and Alizadeh A. 2008. Investigating the trend of changes in the frequency curves of evapotranspiration, Journal of Water and Soil 22(1): 7-20. (In Persian with English abstract)
17. Wright J.L., and Jensen M.E. 1972. Peak water requirements in Southern Idaho. Proceeding of the American Society of Civil Engineers, Journal of the Irrigation and Drainage Division 98(2): 193-201.
18. Yoo S.H., Choi J.Y., and Jang M.W. 2008. Estimation of design water requirement using FAO Penman–Monteith and optimal probability distribution function in South Korea. Agricultural Water Management 95(7): 845-853.