Performance assessment of AquaCrop model for estimating maize (Zea mays L.) evapotranspiration and its components in micro irrigation systems under mulch conditions

Document Type : Original Article

Authors

1 Associate Professor, Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization, Karaj, Alborz, Iran

2 Assistant Professor, Department of Water Engineering, College of Agriculture, Bu-Ali Sina University., Hamedan., Iran

3 Associate Professor, Department of Water Engineering, Imam Khomeini International University, Qazvin, Iran

4 Ph.D. Student, Department of Water Engineering, Imam Khomeini International University, Qazvin, Iran

5 Assistant Professor of Irrigation and Drainage Engineering, Agricultural Engineering Research Institute (AERI), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

Abstract

The aim of this study was to simulate the effect of micro irrigation systems under mulch conditions on evapotranspiration, soil surface evaporation and plant transpiration of forage maize using AquaCrop model. In this study, the AquaCrop model’s performance was tested using data for silage maize (Zea mays L.) under surface drip, subsurface drip and permeability clay pipe irrigation systems with mulch conditions in the semiarid environment of Karaj, Alborz during 2014. According to the NRMSE index, in the calibration and validation stage (7.74% and 10.7%), the accuracy of this model to simulating forage maize biomass was acceptable, and AquaCrop simulated well the biomass yield (B-yield) of silage maize. The model had moderate efficiency for simulating corn evapotranspiration.The performance of the model in maze evapotranspiration simulation was better in PCI-M1 treatment than other treatments. So that, it had the lowest value of nRMSE and the highest value of R2. There was no good correlation between the observed and simulated values in estimating soil surface evaporation and high nRMSE values in these treatments (2.96 and 3.23%) indicate the inefficiency of the AquaCrop model in estimating soil surface evaporation. The positive MBE index in both DI-M1 and SDI-M1 treatments indicates that the model overestimates the soil surface evaporation and does not estimate close to the observed values. Statistical evaluations between observational values and plant transpiration simulation showed a moderate correlation between observed and simulated values. The value of NRMSE index for canopy cover was calculated to be more than 30% in all treatments, which indicates the poor performance of the model. In these treatments, the maximum amount of canopy cover simulated using the AquaCrop model is more than the observed values.

Keywords


ابراهیمی، م.، رضاوردی­نژاد، و.، مجنونی هریس، ا. 1394. شبیه­سازی رشد ذرت تحت مدیریت­های مختلف آب و نیتروژن با مدل AquaCrop. تحقیقات آب و خاک ایران. 46 (2): 220-207.
قربانیان کرد­آبادی، م.، لیاقت، ع.م.، وطن­خواه، ا.، و نوری، ح. 1393. شبیه­سازی عملکرد و تبخیر-تعرق ذرت علوفه­ای با استفاده از مدل AquaCrop. نشریه حفاظت منابع آب و خاک. 4 (2): 64-47.
Abi Saab, M.T., Albirizio, R., Nangia, V., Karam, F. and Rouphael, Y. 2014. Deeloping scenarios to assess sunflower and aoybean yield under different sowing dates and water regimes in the bekaa valley (Lebanon): simulation with AquaCrop. International Journal of Plant Production. 8(4): 457-482.
Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. 1998. Crop Evapotranspiration–Guidelines for Computing Crop Water Requirements. FAO, Rome.
Anjum Iqbal, M., Shen Y., Stricevic R., Pei H., Sun H., Amiri E., Penas A. and Rio S. 2014. Evaluation of the FAO AquaCropmodel for winter wheat on the north china plain under deficit irrigation from field experiment to regional yield simulation. Agricaultural Water Management. 135: 61-72
Ayars, J.E., Fulton, A. and Taylor, B. 2015. Subsurface drip irrigation in California-Here to stay?. Agric Water Manage. 157: 39-47.
Díaz-Pérez, J.C. and Eaton, T.E. 2015. Eggplant (Solanum melongena L.) plant growth and fruit yield as affected by drip irrigation rate. Horticultural Science. 50 (11): 1709–1714.
Farahani, H.J., Izzi, G. and Oweis, T.Y. 2009. Parameterization and evaluation of the AquaCrop model for full and deficit irrigated cotton. Agronomy jJournal. 101(3): 469–476.
Filipovic, ´ V., Romic, ´ D., Romic, ´ M., Borosi ˇ c, ´ J., Filipovic, ´ L., Mallmann, F.J.K., and Robinson, D.A. 2016. Plastic mulch and nitrogen fertigation in growing vegetables modify soil temperature, water and nitrate dynamics: experimental results and a modeling study. Agricaultural Water Management. 176: 100–110.
García García, J., Martínez-Cutillas, A. and Romero, P. 2012. Financial analysis of wine grape production using regulated deficit irrigation and partial-root zone drying strategies. Irrigation Science. 30: 179–188.
Greaves, G.E. and Wang, Y.M., 2016. Assessment of FAO AquaCrop model for simulating maize growth and productivity under deficit irrigation in a tropical environment. Water. 8(12): 557.
Heng, L.K., Hsiao, T., Evett, S., Howell, T. and Steduto, P. 2009. Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agronomy Journal. 101(3): 488–498.
Hsiao, T.C., Heng, L., Steduto, P., Rojas-Lara, B., Raes, D. and Fereres, E. 2009. AquaCrop—the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal. 101(3): 448–459.
Jamieson, P.D., Porter, J.R. and Wilson, D.R. 1991. A test of computer simulation model ARCWHEAT1 on wheat cropsgrown in New Zealand. Field Crops Research. 27: 337-350
Jones, J.W., Hoogenboom, G., Porter, C.H., Boote, K.J., Batchelor, W.D., Hunt, L.A., Wilkens, P.W., Singh, U., Gijsman, A.J. and Ritchie, J.T. 2003. The DSSAT cropping system model. European Journal of Agronomy. 18(3): 235–265.
Masasi, B., Taghvaeian, S., Gowda, P.H., Warren, J. and Marek, G., 2019. Simulating soil water content, evapotranspiration, and yield of variably irrigated grain sorghum using AquaCrop. JAWRA Journal of the American Water Resources Association. 55(4): 976-993.
Mebane, V.J., Day, R.L., Hamlett, J.M., Watson, J.E. and Roth G.W. 2013. Validating the FAO AquaCrop Model for Rainfed Maize in Pennsylvania. Agronomy Journal. 105 (2): 419–27.
Moran, M.S., Scott, R.L., Keefer, T.O., Emmerich, W.E., Hernandez, M., Nearing, G.S., Paige, G.B., Cosh, M.H. and O’Neill, P.E. 2009. Partitioning evapotranspiration in semiarid grassland and shrubland ecosystems using time series of soil surface temperature. Agricultural and Forest Meteorology. 149: 59-72.
Newman, B.D., Wilcox, B.P., Archer, S.R., Breshears, D.D., Dahm, C.N., Duffy, C.J., McDowell, N.G., Phillips, F.M., Scanlon, B.R. and Vivoni, E.R. 2006. Ecohydrologyof water-limited environments. A scientific vision. Water Resources Research. 42: 1–15.
Paul, J.C., Mishra, J.N., Pradhan, P.L. and Panigrahi, B. 2013. Effect of drip and surface irrigation on yield, water-use-efficiency and economics of capsicum (Capsicum annum L.) Grown under mulch and no mulch conditions in eastern coastal India. Indian Journal of Sustainable Development. 2(1): 99-108.
Panigrahi, H.K., Agrawal, N., Agrawal, R., Dubey, S. and Tiwari, S.P. 2016. Effect of drip irrigation and polythene mulch on the fruit yield and quality parameters of mango (Mangifera indica L.). Journal of Horticultural Science and Biotechnology. 5(2): 140-143.
Reddy, M., Ayyanagowdar, M.S., Patil, M.G., Polisgowdar, B.S., Nemichandrappa, M. and Patil, JR., 2018. Performance of Water Melon under Mulching, Subsurface and Surface Drip Irrigation Systems in Semi-Arid Region. International Journal of Pure & Applied Bioscience. 6(1): 488-496.
Smith, M. 1992. CROPWAT: A computer program for irrigation planning and management. In: FAO Irrigation and Drainage Paper No. 46. FAO, Rome, Italy.
 Steduto, P., Hsiao, T.C., Raes, D. and Fereres, E. 2009. AquaCrop—the FAO crop model to simulate yield response to water: i. Concepts and underlying principles. Agronomy Journal. 101(3): 426–437.
 Stöckle, C.O., Donatelli, M. and Nelson, R. 2003. CropSyst, a cropping systems simulation model. Eur. J. Agron. 18(3–4): 289–307.
Tiwari, K.N., Kumar, M., Santosh, D.T., Singh, V.K., Maji, M.K. and Karan, A.K. 2014. Influence of drip irrigation and plastic mulch on yield of sapota (achraszapota) and soil nutrients. Irrigation & Drainage Systems Engineering. 3: 116.
Van Diepen, C.A., Wolf, J., van Keulen, H. and Rappoldt, C. 1989. WOFOST: a simulation model of crop production. Soil Use and Management. 5(1): 16–24.
Van Halsema, G.E. and Vincent, L. 2012. Efficiency and productivity terms for water management: a matter of contextual relativism versus general absolutism. Agric. Water Manage. 108: 9–15.
Voloudakis, D., Karamanos, A., Economou, G., Kalivas, D., Vahamidis, P., Kotoulas, V., Kapsomenakis, J. and Zerefos, C. 2015. Prediction of climate change impacts on cotton yields in Greece under eight climatic models using the AquaCrop crop simulation model and discriminant function analysis. Agricaultural Water Management. 147: 116-128.
Wang, L., Caylor, K.K., Villegas, J.C., Barron-Gafford, G.A., Breshears, D.D. and Huxman, T.E. 2010. Partitioning evapotranspiration across gradients of woody plant cover: assessment of a stable isotope technique. Geophys. Res. Lett. 37: L09401.
Wang, X., Wang, Q., Fan, J. and Fu, Q. 2013. Evaluation of the AquaCrop model for simulating the impact of water deficits and different irrigation regimes on the biomass and yield of winter wheat grown on China’s Loess Plateau. Agricaultural Water Management. 129: 95–104.
Wilcox, B.P., Breshears, D.D. and Seyfried, M.S. 2003. Water balance on rangelands. In: Stewart, B.A., Howell, T.A. (Eds.), Encyclopedia of Water Science. Marcel Dekker, Inc., New York, pp. 791–794.
Yang, P., Hu, H., Tian, F., Zhang, Z. and Dai, C. 2016. Crop coefficient for cotton under plastic mulch and drip irrigation based on eddy covariance observation in an arid area of northwestern China. Agricaultural Water Management. 171: 21–30