Improving Crop Yield Estimation through SWAP Model Using Satellite Data

Document Type : Research Paper

Authors

1 Master science of irrigation and drainage , Department of Irrigation and Reclamation Eng., College of Agriculture and Natural Resources, University of Tehran

2 Assistance professor, Department of Irrigation and Reclamation Eng., College of Agriculture and Natural Resources, University of Tehran

3 Assistance professor, Water Engineering Department, University of Guilan

Abstract

Updating the satellite data in crop growth models is a useful technique to estimate the crop yield on some large scale farms. Throughout the present study, the improvement of SWAP model simulation was investigated using this technique for crop yield estimation. The study was conducted during 2012 growing season at some three center- pivot farms, covered by fodder maize and sugar beet as the main crops in Qazvin Irrigation Network. SWAP model was run by two methods, namely through either non-updated or updated satellite Leaf Area Index (LAI) data. Results indicated that sugar beet and fodder maize yields estimated through updated SWAP model were improved by about 13.7 and 14.5 (%) in absolute percent error while they amounted to 3.321 and 1.621 (ton/ha) in RMSE.
The obtained results indicated that the LAI assimilation technique (using satellite data) can greatly reduce errors related to model input parameters. It can reduce the uncertainty as well as estimate fairly accurately the crop yield in a large area and on any individual farm.

Keywords

Main Subjects

References

Aggarwal, P. K., Kalra, N., Singh, A. K., and Sinha, S. K. (1994). Analyzing the limitations set by climatic factors, geotype, water and nitrogen availability on productivity of wheat I. The model description, parameterization and validation, Field Crops Research. 38(12), 73-91.
Badieneshin, A. R. and Noory, H. (2013). Comparison investigations that done with the SWAP simulation model and determine the performance of this model. In: The 1st national conference on solutions to access sustainable development in agriculture,natural resources and the environment (sdconf), 10 March, Department of the Interior, Tehran, Iran, pp. 853-858. (In Farsi)
Badieneshin, A. R. and Noory, H. (2014). Calibration of leaf area index estimating equations in maize and sugar beet based on MODIS sensor satellite data (Qazvin irrigation network), Iranian Journal of Soil and Water Research, 44(1), 25-39. (in Farsi)
Bonfante, A., Basile, A., Acutis, M., Mascellis, R., Manna, D., Perego, P., and Terribile F. (2010). SWAP, CropSyst and MACRO comparison in two contrasting soils cropped with maize in Northern Italy, Agricultural Water Management, 97(7), 1051-1062.
Curnela, Y., Allard, J. W., Duveillerc, G., and Defourny, P. (2011). Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS Experiment. Agricultural and Forest Meteorology, 151(12), 1843– 1855.
Dente, L., Satalino, G., Mattia, F., and Rinaldi, M. (2008). Assimilation of leaf area index derived from ASAR and MERIS data into CERES-Wheat model to map wheat yield. Remote Sensing of Environment, 112(4), 1395–1407.
Diepen, C. A., van Wolf, J., and van Keulen, H., (1989). WOFOST: a simulation model of crop production. Soil Use Manage. 5(1), 16–24.
Droogers, P., Akbari, M., Torabi, M., and Pazira, E. (2000). Exploring field scale salinity using simulation modeling, example for Rodasht area, Esfahan Province, Iran. IAERIIWMI: Research Reports 2. [word11] 
Eitzinger, J., Trnka, M., Hosch, J., Zalud, Z., and Dubrovsky, M. (2004). Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions. Ecological Modelling 171(3), 223–246.
Ferencz, Cs., Bognar, P., Lichtenberger, J., Hamar, D., Tarcsai, Gy., Timar, G., and Molnar, G. (2004). Crop yield estimation by satellite remote sensing. International Journal of Remote Sensing 25(20), 4113-4149.
Godwin, D. C. and Jones, C. A. (1991). Nitrogen dynamics in soil–plant systems, In: R. J. Hanks, J. T. Ritchie (Eds.). Modelling plant and soil systems, Agron. Monog. 31, ASA, CSSA, SSSA, Madison, WI, USA.
Khani, M., Davari, K., Alizadeh, A., Hashminia, H., and Zolfagharan, A. (2007). SWAP model assessment for simulating Sugar beet yield under different irrigation water quantities and qualities. Water and Soil Science, 1(2), 107-118. (In Farsi)
Kroes, J. G. and Van Dam, J. C. (2003). Reference Manual SWAP version 3.03. (Ed). Alterra- report: Alterra Green WorldResearch (Vol. 773). (pp.1-211). MI: Wageningen University and Research Centre.
Mo, X. and Liu, S. (2001). Simulating evapotranspiration and photosynthesis of winter wheat over the growing season. Agricultural and Forest Meteorology, 109(10), 203–222.
Mo, X., Liu, S., Lin, Z., Xu, Y., Xiang, Y., and McVicar, T. R. (2005). Prediction of crop yield, water consumption and water use efficiency with a SVAT-crop growth model using remotely sensed data on the North China Plain. Ecological Modelling, 183(2), 301–322.
Mokhtari, J. (2012). Development and application of a simple model (VSM) to estimate regional rice yield using satellite data. M. Sc. Irrigation and Drainage, University of Gilan, Iran. (In Farsi)
Mostafazadeh-fard, B., Mansouri Mousavi, H., and SF Feyzi, M., (2009). Effects of different levels of irrigation water salinity and leaching on yield and yield components of wheat in an arid region. Journal of irrigation and drainage engineering. 135(1): 32-38.
Mualem, Y. (1976). A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resource Research. 12: 513-522.
Nahvinia, M. J., Shahidi, A., Parsinejad, M., and Karimi, B. (2011). Assessing the performance of SWAP model in estimating the production of wheat under salinity and water stress (case study: Birjand, Iran).  Iranian Water Research Journal, 4(6), 43-58. (In Farsi)
Navabian, M., Aghajani, M., Vazifehdost, M., and Rezaei, M. (2012). Optimal irrigation regime of rice under salinity using SWAP model. Journal of Water and Soil, 25(6), 1413-1420. (In Farsi)[word12] 
Noory, H., Liaghat, A. M., Parsinejad, M., and Vazifedoust, M. (2011). Evaluation of SWAP model in simulating yield of Wheat and Fodder Maize in simultaneous condition of water and salinity limitations (Case study: Voshmgir network, Golestan provinc). Journal of Water and Soil, 24(6), 1224-1235. (In Farsi)
Noory, H., van der Zee, S. E. A. T. M., Liaghat, A. M., Parsinejad, M., and van Dam, J. C. (2011). Distributed agro-hydrological modeling with SWAP to improve water and salt management of the Voshmgir Irrigation and Drainage Network in Northern Iran. Agricultural Water Management, 98(6), 1062-1070.
Ruiz, M. E. and Utset, A. (2003) Models for predicting water use and crop yields. Report of college on soil Physics. 323-328.
Sehgal, V. (2002). Remote sensing for crop growth and crop simulation modeling.I.A.R.I: New Dehli.
Singh, R., Van Dam, J. C., and Feddes, R. A. (2006). Water Productivity analysis of irrigated crops in Sirsa district, India, Agricultural Water Management, 82(3), 253-278.
Singh, U. K., Ren, L., and Kang, S. (2010). Simulation of soil water in space and time using an agrohydrological model and remote sensing techniques, Agricultural Water Management, 97(8), 1210-1220.
Utset, A., Velicia, H., Delrio, B., Morillo, R., Centenio, J. A., and Martinez, J. C. (2007) Calibrating and validating an agrohidlogical model to simulate sugar beet water use under Mediterranean conditions. Agricultural Water Management, 94(3), 11-21.
Van Dam, J. C., Groenendijk, P., Hendriks, R. F. A., and Kroes, J. G. (2008). Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone Journal, 7(2), 640-653.[word13] 
Van Genuchten, M. Th. (1980). A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society American Journal. 44: 892-898.
Vazifedoust, M., van Dam, J. C., Bastiaanssen, W. G. M., and Feddes, R. A. (2009) Assimilation of satellite data into agrohydrological models to improve crop yield forecasts, International Journal of Remote Sensing, 30(10), 2523-2545.
Vazifedoust, M., van Dam, J. C., Feddes, R. A., and Feizi, M. (2008). Increasing water productivity of irrigated crops under limited water supply at field scale. Agricultural Water Management, 95(2), 89-102.
Verdinejad, V. R, Sohrabi, T., Feizi, M., Heydari, N., and Araghinejad, SH. (2010). Patterning different crops yield with saline water irrigation condition using SWAP model. Water and Soil Science, 1(4), 11-97. (In Farsi)
Wosten, J. H. M., Lilly, A., Nemes, A., and Le Bas, C. (1998). Using existing soil data to derive hydraulic parameters for simulations models in environmental studies and in land use planning. Report 156. DLO Winand Staring Centre, the Netherlands.
 
Iranian Journal of Soil and Water Research
Volume 45, Issue 4 - Serial Number 4
January 2015
Pages 379-388

Files

Share

How to cite

Statistics