Calibration, validation and application of AquaCrop model in irrigation scheduling for rice under northwest India
Article Main
Abstract
A lot of research work regarding irrigation scheduling in rice has been carried out at global level with the objective of increasing irrigation water productivity (IWP) and sustaining grain yield. Under natural conditions rain disturb the planned irrigation treatments. One way to overcome this problem is to use rain shelters which is a costly affair, crop growth simulation models offer a good scope to conduct such studies by excluding the effect of rain. Very limited studies are available where FAO’s AquaCrop model has been used to develop irrigation schedule for crops. Therefore, a study was conducted using FAO AquaCrop model to develop irrigation schedule for rice having higher IWP. The model was calibrated and validated using the experimental data of field experiments conducting during 2009 and 2010, respectively. The model underestimated the above ground dry biomass at 30 days after transplanting (DAT) in the range of 21.60 to 24.85 %. At the time of harvest the model overestimated the above ground dry biomass within the range 11.58 to 14.34 %. At harvest the values of normalized root mean square error (15.54%) suggested a good fit for the above ground dry biomass and an excellent agreement (3.34%) between observed and model predicted grain yield. The model suggested to irrigate rice transplanted in puddled loamy sand soil on every 5th day to get higher IWP coupled with statistically similar grain yield as obtained with daily irrigation schedule.
Article Details
Article Details
Keywords
Above ground dry biomass, Grain yield, Puddled rice, Water productivity
References
Abedinpour, M., Sarangi, A., Rajput, T.B.S., Singh, M., Pathak, H. and Ahmed, T. (2012). Performance evalua-tion of AquaCrop model for maize crop in a semi-arid environment. Agric. Water Manag., 110: 55-66.
Alizadeh, H.A., Nazari, B., Parsinezhad, M., Ramazani, E.H. and Janbaz, H.R. (2010). Evaluation of AquaCrop model on wheat deficit irrigation in Karaj area. Iranian J. Irri. Drain, 4: 273-283.
Andarzian, B., Bannayan, M., Steduto, P., Mazraeh, H., Barati, M.E., Barati, M.A. and Rahnama, A. (2011). Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Ag-ric.Water Manag.,100: 1–8.
Araya, A., Habtub, S., Hadguc, K.M., Kebedea, A. and De-jened, T. (2010a). Test of AquaCrop model in simulat-ing biomass and yield of water deficient and irrigated barley (Hordeum vulgare). Agric. Water Manag., 97: 1838–1846.
Araya, A., Keesstra, S.D. and Stroosnijder, L. (2010b). Simulating yield response to water of Teff (Eragrostis tef) with FAO’s AquaCrop model. Fld. Crops Res., 116: 196–204.
Bali, A.S. and Uppal, H.S. (1999). Growth and yield dynam-ics of basmati rice in relation to intervals and cut-off dates of irrigations on loamy sand soils of Punjab. Appl.Biol.Res., 1: 63-66.
Baumhardt, R.L., Staggenborg, S.A., Gowda, P.H., Colaizzi, P.D. and Howell, T.A. (2009). Modelling irrigation management strategies to maximize cotton lint yield and water use efficiency. Agron. J., 101: 460–468.
Benli, B., Pala, M., Stockle, C. and Oweis, T. (2007). As-sessment of winter wheat production under early sow-ing with supplemental irrigation in a cold high land environment using CropSyst simulation model. Agric. Water Manag., 93: 45–53.
Blum, F A. (2009). Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress. Fld. Crops Res.,112: 119–123.
Doorenbos, J. and Kassam, A.H. (1979). Yield response to water. FAO irrigation and drainage paper no. 33. FAO, Rome, Italy, 193 pp.
Edwin, L. and Anal, P.S.M. (2008). Effect of irrigation re-gimes and nitrogen management practices on uptake of nutrients and grain yield in hybrid rice (Oryza sativa L.). Envir. Eco., 26: 1146-1148.
Geerts, S. and Raes, D. (2009). Deficit irrigation as on-farm strategy to maximize crop water productivity in dry areas. Agric. Water Manag., 96:1275–1284.
Geerts, S., Raes, D., Garcia, M., Miranda, R., Cusicanqui, J.A., Taboada, C., Mendoza, J., Huanca, R., Mamani, A., Condori, O., Mamani, J., Morales, B., Osco, V. and Steduto, P. (2009). Simulating yield response of Quinoa to water availability with AquaCrop. Agron. J., 101: 499–508.
Heng, L.K., Asseng, S., Mejahed, K., and Rusan, M. (2007). Optimizing wheat productivity in two rainfed environ-ments of the west Asia-North Africa region using a simulation model. European Journal of Agronomy, 26: 121–129.
Heng, L.K., Hsiao, T., Evett, S., Howell, T. and Steduto, P. (2009). Validating the FAO AquaCrop model for irri-gated and water deficient field maize. Agron. J., 101: 488–498.
Husain, M.F., Mohd Shamim and Pal, S. (2008). Influence of irrigation schedule on yield and water use efficiency of rice (Oryza sativa) in kharif season. Int. J. Agric.Sci., 4: 332-334.
Jamieson, P.D., Porter, J.R. and Wilson, D.R. (1991). A test of computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Fld. Crops Res., 27: 337–350.
Katozi, M., Khoei, F.R. and Sabouri, H. (2009). Effect of irrigation management on grain filling rate, grain filling duration and leaf relative water content on three rice (Oryza sativa L.) cultivars. J. Sci. Tech. Agric. Nat. Res., 13: 623-638.
Khalifa, A.A.A., Salem, A.K.M., and El Refaee, I.S. (2005). Effect of irrigation intervals and nitrogen sources on yield, sugar and starch content of rice. Egyptian J. Agron., 27: 113-123.
Lin, L., Zhang, B. and Xiong, L. (2012). Evaluating yield response of paddy rice to irrigation and soil manage-ment with application of the AquaCrop model. Transac-tions of the ASABE, 55: 839-848.
Luikham, E., Krishnarajan, J. and Premsekhar, M. (2004). Irrigation and nitrogen application schedules for hybrid 'ADTRH 1' rice (Oryza sativa) in Tamil Nadu. Indian J. Agron., 49: 37-39.
Merwin, H.D. and Peech, M. (1950). Exchangeability of soil potassium in the sand, silt and clay fractions as influ-enced by the nature of the complementary exchangeable cations. Pro. Soil Sci. Soc. America, 15: 125-128.
Mkhabela, M.S. and Bullock, P.R. (2012). Performance of the FAO AquaCrop model for wheat grain yield and soil moisture simulation in Western Canada. Agric. Water Manag., 110: 16-24.
Olsen, S.R., Cole, C.V., Waternabe, F.S. and Dean, L.A. (1954). Estimation of available phosphorus in soils by extraction with sodium bicarbonate. USDA Circular, 939: 19.
Parihar, S.S. (2004). Effect of crop-establishment method, tillage, irrigation and nitrogen on production potential of rice (Oryza sativa)-wheat (Triticum aestivum) crop-ping system. Indian J. Agron., 49: 1-5.
Pereira, L.S., Paredes, P., Sholpankulov, E.D., Inchenkova, O.P., Teodor, P.R. and Horst, M.G. (2009). Irrigation scheduling strategies for cotton to cope with water scar-city in the Fergana Valley, Central Asia. Agric. Water Manag., 96: 723–735.
Raes, D., Steduto, P., Hsiao, T.C. and Fereres, E. (2009). Reference Manual, Chapter 1 – AquaCrop, January 2009 available at http://www.fao.org/NR/water/docs/AquaCropChapter1.pdf, cited on 1-2-2013.
Ramakrishna, Y., Singh, S. and Parihar, S.S. (2007). Influ-ence of irrigation regime and nitrogen management on productivity, nitrogen uptake and water use by rice (Oryza sativa). Indian J. Agron., 52: 102-106.
Sandhu, B.S., Khera, K.L., Prihar, S.S. and Singh, B. (1980). Irrigation needs and yield of rice on a sandy loam soil as affected by continuous and intermittent submergence. Indian J. Agric. Sci., 50: 492-496.
Sandhu, S.S., Mahal, S.S., Vashist, K.K., Buttar, G.S., Brar, A.S., and Maninder Singh (2012). Crop and water pro-ductivity of bed transplanted rice as influenced by vari-ous levels of nitrogen and irrigation in northwest India. Agric. Water Manag., 104: 32-39.
Sharma, P.K., Bhushan, L., Ladha, J.K., Naresh, R.K., Gupta, R.K., Balasubramanian, B.V. and Bouman, B.A.M. (2002). Crop-water relations in rice-wheat crop-ping under different tillage systems and water management practices in a marginally sodic, medium textured soil, Water-Wise Rice Pro-duction. I.R.R.I., Los Banos, Philippines, pp. 223-35.
Singh, A.K., Choudhury, B.U. and Bouman, B.A.M. (2002). Effects of rice establishment methods on crop performance, water use and mineral nitrogen,Water-Wise Rice Production. I.R.R.I., Los Banos, Philippines, pp. 237–46.
Singh, R., Kumar, A., Kumar, S. and Chand, R. (2008). Al-ternative crop establishment tillage technologies in rice. Indian Res. J. Ext. Edu., 8: 13-15.
Singh, K. (2006). Fall in water table in central Punjab how serious? Tech. bull. The Punjab State Farmers Commis-sion. Government of Punjab, Mohali, Punjab, India, pp. 10.
Steduto, P., Hsiao, T.C., Raes, D., and Ferereset, E. (2009). AquaCrop – the FAO crop model to simulate yield re-sponse to water: I. Concepts and underlying principles. Agron. J., 101: 426–437.
Stricevic, R., Cosic, M., Djurovic, N., Pejic, B. and Maksi-movic,L.(2011). Assessment of the FAO AquaCrop model in the simulation of rainfed and supplementally irrigated maize, sugar beet and sunflower. Agric. Water Manag., 98: 1615-1621.
Subbiah, B.V. and Asija, G.L. (1956). A rapid procedure for the estimation of available nitrogen in soils. Curr. Sci., 25: 259-260.
Tuong, T.P. and Bouman, B.A.M. (2003). Rice production in water scare environments, in: Kijne, J.W., Barker, R., Molden, D. (Eds.), Water Productivity in Agriculture: Limits and Opportunities for Improvement, C.A.B.I. Publishing, Wallingford, U.K., pp. 53-67.
Walkley, A. and Black, C.A. (1934). An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci., 37: 27-38.
Zeleke, K.T., Luckett, D. and Cowley, R. (2011). Calibration and testing of the FAO AquaCrop model for canola. Agron. J., 103: 1610–1618.
Zinyengere, N., Mhizha, T., Mashonjowa, E., Chipindu, B., Geerts, S. and Raes, D. (2011). Using seasonal climate forecasts to improve maize production decision support in Zimbabwe. Agric. Forest Met., 151: 1792–1799.
Alizadeh, H.A., Nazari, B., Parsinezhad, M., Ramazani, E.H. and Janbaz, H.R. (2010). Evaluation of AquaCrop model on wheat deficit irrigation in Karaj area. Iranian J. Irri. Drain, 4: 273-283.
Andarzian, B., Bannayan, M., Steduto, P., Mazraeh, H., Barati, M.E., Barati, M.A. and Rahnama, A. (2011). Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Ag-ric.Water Manag.,100: 1–8.
Araya, A., Habtub, S., Hadguc, K.M., Kebedea, A. and De-jened, T. (2010a). Test of AquaCrop model in simulat-ing biomass and yield of water deficient and irrigated barley (Hordeum vulgare). Agric. Water Manag., 97: 1838–1846.
Araya, A., Keesstra, S.D. and Stroosnijder, L. (2010b). Simulating yield response to water of Teff (Eragrostis tef) with FAO’s AquaCrop model. Fld. Crops Res., 116: 196–204.
Bali, A.S. and Uppal, H.S. (1999). Growth and yield dynam-ics of basmati rice in relation to intervals and cut-off dates of irrigations on loamy sand soils of Punjab. Appl.Biol.Res., 1: 63-66.
Baumhardt, R.L., Staggenborg, S.A., Gowda, P.H., Colaizzi, P.D. and Howell, T.A. (2009). Modelling irrigation management strategies to maximize cotton lint yield and water use efficiency. Agron. J., 101: 460–468.
Benli, B., Pala, M., Stockle, C. and Oweis, T. (2007). As-sessment of winter wheat production under early sow-ing with supplemental irrigation in a cold high land environment using CropSyst simulation model. Agric. Water Manag., 93: 45–53.
Blum, F A. (2009). Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress. Fld. Crops Res.,112: 119–123.
Doorenbos, J. and Kassam, A.H. (1979). Yield response to water. FAO irrigation and drainage paper no. 33. FAO, Rome, Italy, 193 pp.
Edwin, L. and Anal, P.S.M. (2008). Effect of irrigation re-gimes and nitrogen management practices on uptake of nutrients and grain yield in hybrid rice (Oryza sativa L.). Envir. Eco., 26: 1146-1148.
Geerts, S. and Raes, D. (2009). Deficit irrigation as on-farm strategy to maximize crop water productivity in dry areas. Agric. Water Manag., 96:1275–1284.
Geerts, S., Raes, D., Garcia, M., Miranda, R., Cusicanqui, J.A., Taboada, C., Mendoza, J., Huanca, R., Mamani, A., Condori, O., Mamani, J., Morales, B., Osco, V. and Steduto, P. (2009). Simulating yield response of Quinoa to water availability with AquaCrop. Agron. J., 101: 499–508.
Heng, L.K., Asseng, S., Mejahed, K., and Rusan, M. (2007). Optimizing wheat productivity in two rainfed environ-ments of the west Asia-North Africa region using a simulation model. European Journal of Agronomy, 26: 121–129.
Heng, L.K., Hsiao, T., Evett, S., Howell, T. and Steduto, P. (2009). Validating the FAO AquaCrop model for irri-gated and water deficient field maize. Agron. J., 101: 488–498.
Husain, M.F., Mohd Shamim and Pal, S. (2008). Influence of irrigation schedule on yield and water use efficiency of rice (Oryza sativa) in kharif season. Int. J. Agric.Sci., 4: 332-334.
Jamieson, P.D., Porter, J.R. and Wilson, D.R. (1991). A test of computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Fld. Crops Res., 27: 337–350.
Katozi, M., Khoei, F.R. and Sabouri, H. (2009). Effect of irrigation management on grain filling rate, grain filling duration and leaf relative water content on three rice (Oryza sativa L.) cultivars. J. Sci. Tech. Agric. Nat. Res., 13: 623-638.
Khalifa, A.A.A., Salem, A.K.M., and El Refaee, I.S. (2005). Effect of irrigation intervals and nitrogen sources on yield, sugar and starch content of rice. Egyptian J. Agron., 27: 113-123.
Lin, L., Zhang, B. and Xiong, L. (2012). Evaluating yield response of paddy rice to irrigation and soil manage-ment with application of the AquaCrop model. Transac-tions of the ASABE, 55: 839-848.
Luikham, E., Krishnarajan, J. and Premsekhar, M. (2004). Irrigation and nitrogen application schedules for hybrid 'ADTRH 1' rice (Oryza sativa) in Tamil Nadu. Indian J. Agron., 49: 37-39.
Merwin, H.D. and Peech, M. (1950). Exchangeability of soil potassium in the sand, silt and clay fractions as influ-enced by the nature of the complementary exchangeable cations. Pro. Soil Sci. Soc. America, 15: 125-128.
Mkhabela, M.S. and Bullock, P.R. (2012). Performance of the FAO AquaCrop model for wheat grain yield and soil moisture simulation in Western Canada. Agric. Water Manag., 110: 16-24.
Olsen, S.R., Cole, C.V., Waternabe, F.S. and Dean, L.A. (1954). Estimation of available phosphorus in soils by extraction with sodium bicarbonate. USDA Circular, 939: 19.
Parihar, S.S. (2004). Effect of crop-establishment method, tillage, irrigation and nitrogen on production potential of rice (Oryza sativa)-wheat (Triticum aestivum) crop-ping system. Indian J. Agron., 49: 1-5.
Pereira, L.S., Paredes, P., Sholpankulov, E.D., Inchenkova, O.P., Teodor, P.R. and Horst, M.G. (2009). Irrigation scheduling strategies for cotton to cope with water scar-city in the Fergana Valley, Central Asia. Agric. Water Manag., 96: 723–735.
Raes, D., Steduto, P., Hsiao, T.C. and Fereres, E. (2009). Reference Manual, Chapter 1 – AquaCrop, January 2009 available at http://www.fao.org/NR/water/docs/AquaCropChapter1.pdf, cited on 1-2-2013.
Ramakrishna, Y., Singh, S. and Parihar, S.S. (2007). Influ-ence of irrigation regime and nitrogen management on productivity, nitrogen uptake and water use by rice (Oryza sativa). Indian J. Agron., 52: 102-106.
Sandhu, B.S., Khera, K.L., Prihar, S.S. and Singh, B. (1980). Irrigation needs and yield of rice on a sandy loam soil as affected by continuous and intermittent submergence. Indian J. Agric. Sci., 50: 492-496.
Sandhu, S.S., Mahal, S.S., Vashist, K.K., Buttar, G.S., Brar, A.S., and Maninder Singh (2012). Crop and water pro-ductivity of bed transplanted rice as influenced by vari-ous levels of nitrogen and irrigation in northwest India. Agric. Water Manag., 104: 32-39.
Sharma, P.K., Bhushan, L., Ladha, J.K., Naresh, R.K., Gupta, R.K., Balasubramanian, B.V. and Bouman, B.A.M. (2002). Crop-water relations in rice-wheat crop-ping under different tillage systems and water management practices in a marginally sodic, medium textured soil, Water-Wise Rice Pro-duction. I.R.R.I., Los Banos, Philippines, pp. 223-35.
Singh, A.K., Choudhury, B.U. and Bouman, B.A.M. (2002). Effects of rice establishment methods on crop performance, water use and mineral nitrogen,Water-Wise Rice Production. I.R.R.I., Los Banos, Philippines, pp. 237–46.
Singh, R., Kumar, A., Kumar, S. and Chand, R. (2008). Al-ternative crop establishment tillage technologies in rice. Indian Res. J. Ext. Edu., 8: 13-15.
Singh, K. (2006). Fall in water table in central Punjab how serious? Tech. bull. The Punjab State Farmers Commis-sion. Government of Punjab, Mohali, Punjab, India, pp. 10.
Steduto, P., Hsiao, T.C., Raes, D., and Ferereset, E. (2009). AquaCrop – the FAO crop model to simulate yield re-sponse to water: I. Concepts and underlying principles. Agron. J., 101: 426–437.
Stricevic, R., Cosic, M., Djurovic, N., Pejic, B. and Maksi-movic,L.(2011). Assessment of the FAO AquaCrop model in the simulation of rainfed and supplementally irrigated maize, sugar beet and sunflower. Agric. Water Manag., 98: 1615-1621.
Subbiah, B.V. and Asija, G.L. (1956). A rapid procedure for the estimation of available nitrogen in soils. Curr. Sci., 25: 259-260.
Tuong, T.P. and Bouman, B.A.M. (2003). Rice production in water scare environments, in: Kijne, J.W., Barker, R., Molden, D. (Eds.), Water Productivity in Agriculture: Limits and Opportunities for Improvement, C.A.B.I. Publishing, Wallingford, U.K., pp. 53-67.
Walkley, A. and Black, C.A. (1934). An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci., 37: 27-38.
Zeleke, K.T., Luckett, D. and Cowley, R. (2011). Calibration and testing of the FAO AquaCrop model for canola. Agron. J., 103: 1610–1618.
Zinyengere, N., Mhizha, T., Mashonjowa, E., Chipindu, B., Geerts, S. and Raes, D. (2011). Using seasonal climate forecasts to improve maize production decision support in Zimbabwe. Agric. Forest Met., 151: 1792–1799.
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Calibration, validation and application of AquaCrop model in irrigation scheduling for rice under northwest India. (2015). Journal of Applied and Natural Science, 7(2), 691-699. https://doi.org/10.31018/jans.v7i2.668
