Application of Bayesian Model Averaging (BMA) Approach to Estimating Wheat Yield in Golestan Province

Document Type : Research Paper

Authors

1 Irrigation & Reclamation Engineering Deptpartment University of Tehran Karaj, Iran.

2 Assistant Prof., Irrigation & Reclamation Engrg. Dept. University of Tehran Karaj, Iran.

Abstract

Wheat is a strategic crop for food security, so accurate forecasting of its performance is important for planning and adopting appropriate policies for import or export. Crop models use climatic, soil, cultivar type and crop management data to predict crop growth, development and yield. The purpose of this study was to improve the accuracy of estimating wheat yield using a combination of recommended crop models in Golestan province using Bayesian model averaging (BMA). In this study, first, the ability of DSSAT, CropSyst and SSM-Wheat models was evaluated to estimate wheat yield in Golestan province. According to the results, the DSSAT model with root mean square error (RMSE) equal to 290 kg ha-1, coefficient of determination (R2) equal to 96%, mean square root of normalized error (NRMSE) equal to 6.34 and the efficiency of the model (EF) equal to 0.9 has the most accurate estimation as compared to two other models. In the next step, using the BMA approach, binary and ternary combinations were taken from three crop models, which led to the production of four new models. Comparing the performance of BMA models with individual models, showed that the combination of models improves the accuracy of estimation. Thus, the amount of RMSE in the C23 model (which is the result of combining DSSAT and SSM-Wheat models (was reduced by 30% compared to the amount of yield calculated by the best single model (DSSAT) and reached 202 kg ha-1. Also, the value of R2 in the C23 model reached 97%. Therefore, the combination of models improves the accuracy, estimating wheat yield.

Keywords

References

Abdalla, E. M. H., Alfredsen, K. and Muthanna, T. M. (2022). Towards improving the calibration practice of conceptual hydrological models of extensive green roofs. Journal of Hydrology, 607, 127548. https://doi.org/10.1016/j.jhydrol.2022.127548
Agyekum, J., Annor, T., Quansah, E., Lamptey, B. and Okafor, G. (2022). Extreme Precipitation Indices over the Volta Basin: CMIP6 model evaluation. Scientific African, e01181.
Ahmadi, K., Ebadzadeh, H., Hatami, F., Afruzi, SH., Esfandiari-Pur, E. and Abbas-Taghani, R. (2021). Agricultural statistics 2019 first volume: crops. Tehran: Ministry of agriculture.
 AhmadiAlipour, H., Soltani, a., Kazemi, H. and Nehbandani, A. (2018). zoning golestan province in terms of the ability and the wheat production gap using a simulation model (SSM). journal of crops improvement (journal of agriculture), 20(1), 129-144. https://www.sid.ir/en/journal/ViewPaper.aspx?id=610238 . (In Farsi)
Alimagham, S.M., Soltani, A., Vadez, V., Zeinali, E. and Zand, E. (2020). Irrigated Wheat (Triticum aestivum L.) Traits Effects on Potential Yield under Current and Future Climates in Iran, Agroecology journal, 12(3), 413-431. (In Farsi)
Aslani, P., Davari, M., Mahmoodi, M., Hosseinpanahi, F., Khaleghpanah, N. (2021). Effect of zeolite and nitrogen on some basic soil properties and wheat yield in potato-wheat rotation. Journal of Agricultural Engineering Soil Science and Agricultural Mechanization, (Scientific Journal of Agriculture), 44(1). (In Farsi)
Chen, S., He, L., Cao, Y., Wang, R., Wu, L., Wang, Z., ... and He, J. (2021). Comparisons among four different upscaling strategies for cultivar genetic parameters in rainfed spring wheat phenology simulations with the DSSAT-CERES-Wheat model. Agricultural Water Management, 258, 107181.
Dahmardeh, A., Shahriari, A., Pahlavan Rad, M., Shabani, A., GHOEBANI, M. (2021). Modeling wheat yield using some soil properties at the field scale (Case study: Sistan dam research farm, university of Zabol). Journal of Agricultural Engineering Soil Science and Agricultural Mechanization, (Scientific Journal of Agriculture), 44(1). (In Farsi)
Dastmalchi, A. (2010). Simulating wheat growth and development using CropSyst model under Golestan province Condition. M.Sc. thesis, Gorgan University of agricultural sciences and natural resources. (In Farsi)
 Ebrahimipak, N.A. and Egdernezhad, A. (2019). Assessment of AquaCrop, WOFOST and CropSyst models for Estimating Sugar Beet Yield under Water Deficit Conditions, Journal of Hydrology and Soil Science, 23(1), 199-207. (In Farsi)
Fallah, M.H., Nezami, A., Khazaie, H.R. and Nassiri Mahallati, M. (2021). Evaluation of DSSAT-Nwheat Model across a Wide Range of Climate Conditions in Iran. Agroecology journal, 12(4), 561-580. (In Farsi)
Ghadiryan, R. (2011). Growth analysis of wheat cultivars of Golestan province. M.Sc. thesis, Gorgan University of agricultural sciences and natural resources. (In Farsi)
Hao, Y., Baik, J. and Choi, M. (2019). Combining generalized complementary relationship models with the Bayesian Model Averaging method to estimate actual evapotranspiration over China. Agricultural and Forest Meteorology, 279, 107759.
Jing, Q., McConkey, B., Qian, B., Smith, W., Grant, B., Shang, J., ... and Luce, M. S. (2021). Assessing water management effects on spring wheat yield in the Canadian Prairies using DSSAT wheat models. Agricultural Water Management, 244, 106591.
Kazemi, A., Ghahreman, N., Ghamghami, M. and Ghameshloo, A. (2021). Application of Bayesian Model Averaging (BMA) Approach for Estimating Evapotranspiration in Gorganrood-Gharesoo Basin, Iran. Journal of Agricultural Science and Technology, 2021; 23 (6) :1395-1409. http://jast.modares.ac.ir/article-23-45031-en.html . (In Farsi)
Kumar, R., Yadav, R. S., Kumawat, A., Yadava, N. D., Rathore, V. S., Nangia, V. and Pareek, N. K. (2021). Evaluation of CropSyst model for soil moisture and water productivity of wheat. Journal of Soil and Water Conservation, 20(3), 330-334.
lotfi, M., Kamali, G., Meshkatee, A., Varshavian, V. (2021). Evaluation of Yield Changes and Length of Dryland Wheat Phenological Stages under RCP Scenario Using DSSAT and AquaCrop Models in Western Iran. Iranian Journal of Soil and Water Research, 52(10), 2665-2677. (In Farsi)
MahrouKashani, A., Soltani, A., Galeshi, S. and KalatehArabi, M. (2010). Estimates of genetic coefficients and evaluation of model DSSAT for Golestan province. Journal of Crop Production, 3(2), 229-153. (In Farsi)
Manschadi, A. M., Palka, M., Fuchs, W., Neubauer, T., Eitzinger, J., Oberforster, M. and Soltani, A. (2022). Performance of the SSM-iCrop model for predicting growth and nitrogen dynamics in winter wheat. European Journal of Agronomy, 135, 126487.
Ouda, S., Noreldin, T., Alarcón, J. J., Ragab, R., Caruso, G., Sekara, A. and Abdelhamid, M. T. (2021). Response of Spring Wheat (Triticum aestivum) to Deficit Irrigation Management under the Semi-Arid Environment of Egypt: Field and Modeling Study. Agriculture 2021, 11, 90.
Panahi, M.H., Soltani, A., Zeynali, E., KalatehArabi, M. and Nehbandani, A.R. (2020). Estimation of phenological parameters in SSM-Wheat model for bread wheat (Triticum aestivum L.) genotypes in Golestan province of Iran, Iranian Journal of Crop Sciences, 21(4), 302-314. (In Farsi)
Prakash, G. and Balomenos, G. P. (2021). A Bayesian approach to model selection and averaging of hydrostatic-season-temperature-time model. Elsevier, 33, 4359-4370.
Salarieh, P., Khoshravesh, M., Norooz Valashedi, R., Kiani, A. (2021). Investigation the Effect of Climate Change and Planting Date on Maize Yield using WOFOST Model. Iranian Journal of Soil and Water Research, 52(10), 2515-2527. (In Farsi)
Seifi, S., Khodashenas, S., Mosaedi, A. (2021). Prediction of Changes in Inflow Suspended to the Dam Reservoir using IHACRES Rainfall-runoff Model under the Influence of Climate Change Phenomenon (Case Study: Torogh Dam). Iranian Journal of Soil and Water Research, 52(10), 2539-2553. (In Farsi)
  Soltani, A. and Sinclair, T. R. (2015). A comparison of four wheat models with respect to robustness and transparency: Simulation in a temperate, sub-humid environment. Field Crops Research, 175, 37-46.
Soltani, A., Maddah, V. and Sinclair, T. R. (2013). SSM-wheat: a simulation model for wheat development, growth and yield. International Journal of Plant Production, 7(4), 711-740.
Sun, H., Yang, Y., Wu, R., Gui, D., Xue, J., Liu, Y. and Yan, D. (2019). Improving estimation of cropland evapotranspiration by the Bayesian model averaging method with surface energy balance models. Atmosphere, 10(4), 188.
Tofigh, S., Rahimi, D. and Yazadnpanah H. (2020). Simulation of Yield, Evapotranspiration, Water Requirement and Water Use Efficiency of Wheat Using CERES-WHEAT-DSSAT Model in Shahrekord Plain, Journal of water and soil, 34(3), 579-592. (In Farsi)
Zou, Y., Lin, B., Yang, X., Wu, L., Muneeb Abid, M. and Tang, J. (2021). Application of the bayesian model averaging in analyzing freeway traffic incident clearance time for emergency management. Journal of advanced transportation, vol. 2021. https://doi.org/10.1155/2021/6671983
Torabi, B., Soltani, A., Galeshi, S., Zeinali, E. (2020). Yield Gap Analysis: quantifying the gap between actual yield and potential yields of wheat in Gorgan. Journal of Crop Production, 13(1), 1-24.
Iranian Journal of Soil and Water Research
Volume 53, Issue 9
November 2023
Pages 2045-2059

Files

Share

How to cite

Statistics