Using the PILOTE Model to Improve Water Productivity for Rice in Rasht, North of Iran

Subject Areas : Farm Management

Maryam Shadpour ¹ , Mohammadreza Khaledian ² , MohammadHassan Biglouei ³ , Mojtaba Rezaei ⁴

1 - MSc Student, University of Guilan
2 - University of Guilan
3 - University of Guilan
4 - Rice Research Ins

Received: 2016-11-26 Accepted : 2017-01-01 Published : 2017-12-01

Keywords: simulation, Irrigation Management, Rasht, Hashemi variety,

Abstract :

In order to calibrate and validate the PILOTE model for rice in a humid climate, this study was carried in a randomized complete block design with three replications on a popular local variety, Hashemi, during 2001, 2002, 2005, 2006 and 2007 crop seasons. This research was done at the Rice Research Institute of Rasht, Iran. Evaluation of simulated and measured grain yield and dry matter values was done using Nash-Sutcliffe efficiency (EF), Root Mean Square Errors (RMSE) and normalized root mean square errors (NRMSE) indices. The results revealed that RMSE for validation and calibration were 0.69 and 0.72 Mg.ha-1, respectively. NRMSE for calibration was 9.5% and for validation was 14.1%. NRMSE for grain yield and dry matter were 8.74 and 13.37%, respectively. EF values were between 0.84 and 0.98. The results showed that the PILOTE model can be used to manage properly rice irrigation in different regimes. Scenario analysis showed that the best irrigation regime was intermittent irrigation with 8-day interval.

References:

Allen, R.G., Periera, L.S., Raes, D., & Smith, M. (1998). Crop evapotranspiration guidelines for computing crop water requirement. The 56^th report on the irrigation and drainage (FAO), Rome.

Amiri, A., Razavipoor, T., & Banayan, M. (2011a).  Evaluation of rice water productivity in different irrigation condition and cultivation distance by using ORYZA 2000 model. Electronical Field Crop Production, 4(3), 1-19.

Amiri, A., Rezaei, M., Motamed, K., & Emami, S. (2011b). Evaluation of WOFOST plant growth model in condition of irrigation management. Agronomy: Research and Building,90, 9-17.

Amiri, E., Rezaei, M., Bannayan, M., & Soufizadeh, S. (2013). Calibration and evaluation of CERES-Rice model under different N and water management options in semi-Mediterranean climate condition, Communication in Soil Science and Plant Analysis, 44(12), 1814-1830.

Belder, P., Bouman, B.A.M., Cabangon, R., Guoan, L., Quilang, E.J.P., Li, Y., Spiertz, J.H.J., & Tuong T.P. (2004). Effect of water saving irrigation on rice yield and water use in typical lowland conditions in Asia. Agricultural Water Management, 65, 193–210.

Bannayan, M., & Hoogenboom, C. (2009). Using pattern recognition for estimating cultivar coefficients of a crop simulation model. Field Crops Research, 111(3), 290-302.  

Bouman, B.A.M., Kropff, M.J., Tuong, T.P., Wopereis, M.C.S., Ten-Berge, H.F.M., & Vanlaar, H.H. (2001). ORYZA2000: modeling low land rice. Los Banos (Philippines): International Rice Research Institute, and Wageningen: Wageningen University and Research Center, pp. 235.

Bouman, B.A.M., & Tuong, T.P. (2001). Field water management to save water and increase its productivity in irrigated lowland rice. Agricultural Water Management, 49(1), 11-30.                        

Confalonieri, R., Acutis, M., Bellocci, G., & Donatelli, M. (2009). Multi- metric evaluation of the model WARM, CropSyst, and WOFOST for Rice. Ecological Modelling, 220(11), 1395-1410.

Confalonieri, R., & Bocchi, S. (2005). Evaluation of CropSyst for simulating the yield of                                                    flooded rice in northern Italy. European Journal of Agronomy, 23, 315-326.

Hsiao, T.C., Heng, L., Steduto, P., Rojas-Larra, B., Raes, D., & Fereres, E. (2009). AquaCrop: the FAO crop model to simulate yield response to water: parameterization and testing for maize. Agronomy Journal, 101, 448-459.

Jamieson, P.D., Porter, J.R., & Wilson, D.R. (1991). A test of the computer simulation model ARC-WHEAT on wheat crops grown in New Zealand. Field Crops Research, 27(4), 337-350.

Khaledian, M.R., Mailhol, J.C., Ruelle, P., & Dejean, C. (2013). Effect of cropping strategies on the irrigation water productivity of durum wheat. Plant, Soil and Environment, 59(1), 29-36.

Khaledian, M.R., Mailhol, J.C., Ruelle, P., Mubarak, I., & Maraux, F. (2011). Nitrogen balance and irrigation water productivity for corn, sorghum and durum wheat under direct seeding into mulch when compared with conventional tillage in the southeastern France. Irrigation Science, 29(5), 413-422.

Khaledian, M.R., Mailhol, J.C., Ruelle, P., Rosique, P. (2009). Adapting PILOTE model for water and yield management under seeding system: The case of corn and durum wheat in a Mediterranean context. Agricultural Water Management, 96(6), 757-770.

Mailhol, J.C. (2005). Contribution to the control of irrigation and its impacts. Unpublished dissertation Irrigation Deptment, Faculty of Agricultural Sciences, University of Montpellier 2. France.

Mailhol, C., Olofayo, A.A., & Ruelle, P. (1997). Sorgum and sunflower evapotranspiration and yield from simulated leaf area index. Agricultural Water Management, 35(1-2), 167-182.

Mailhol, J. C., Ruelle, P., Walser, S., Schutze, N., & Dejean, D. (2011). Analysis of AET and yield predictions under surface and buried drip irrigation systems using the crop model PILOTE and
Hydrus-2D. Agricultural Water Management, 98, 1033-1044.

Ng, N., & Loomis, R.S. (1984). Simulation of growth and yield for the potato crop. Simulation Monographs. Agricultural Publishing and Documentation Center, Wageningen, Pp.147.

Page, A.L. (1982). Methods of soil analysis. American Society of Agronomy, Inc. and Soil Science Society of America, Inc. Madison, Wisconsin, USA.

Rezaei, M., Davatgar, N., Khaledian, M.R., & Pirmoradian, N. (2013). Using intermittent irrigation to use saline water in rice production. Acta Agriculturae Slovenica, 101(1), 49-57.

Rezaei, M., & Nahvi, M.( 2007). Effect of different irrigation management in clay soils on water efficiency and some features of local rice cultivars at Guilan. Agricultural Sciences Research, 9, 15-25.

Rodrigues, G.C., & Pereira, L.S. (2009). Assessing economic impacts of deficit irrigation as related to water productivity and water costs. Biosystem Engineering, 103(4), 536–551.

Saadati, Z. (2011). Assessment of aquacrop, cropsyst and WOFOST models in yield simulating of two rice varieties, Binam and Hasani, under different irrigation regimes. Unpublished thesis Water Engineering Deptment, Faculty of Agricultural Sciences, University of Guilan, Iran.

Saadati, Z., Pirmoradian, N., Amiri, A., & Rezaei, M. (2011). Evaluation WOFOST model in simulating two yields varieties rice under different irrigation regimes. Water Research in Agriculture, 3, 324-337.

Singh, A.K., Goyal, V., Mishra, A.K., & Parihar, S.S. (2013). Validation of CropSyst simulation model for direct seeded rice-wheat cropping system. Current Science, 104(10), 1324-1331.

Stokle, C.O., Williams, J.R., Rosenberg, N.J.,  & Jones, C.A. (1992). A method for estimating the direct and climatic effects of rising atmospheric carbon dioxide on growth and yield of crops: Part I. modification of the EPIC model for climate change analysis. Agricultural  System. 38(3), 225-238.

Van Dam, J.C. (1977). Field-scale water flow and solute transport. SWAP model concepts, parameter estimation, and case studies. Unpublished dissertation Netherlands: Faculty of Agricultural Sciences, University of Wageningen.

Viets, F.G. Jr. (1962). Fertilizers and the efficient use of water. Advances in Agronomy,14, 223–264.

Wohling, T. (2005). Physically based modeling of furrow irrigation system during a growing season. Unpublished dissertation Dresden: Faculty of Agricultural Sciences, University of Dresden. Pp. 209.

Xiong, W., Ian, H., Declan, C., & Erdalin, Y. (2008). A crop model cross calibration for use in regional climate impact studies. Ecological Modeling, 213, 365-380.