شبیه‌سازی عملکرد و کارایی مصرف آب ارقام مختلف برنج تحت شرایط مختلف کاشت با استفاده از دو مدل AquaCrop و SWAP

نویسندگان

1 دانشجوی کارشناسی ارشد آبیاری و زهکشی، گروه علوم و مهندسی آب، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران.

2 استادیار، گروه علوم و مهندسی آب، واحد اهواز، دانشگاه آزاد اسلامی، اهواز، ایران.

3 استادیار، بخش تحقیقات اصلاح و تهیه نهال و بذر، مرکز تحقیقات کشاورزی و منابع طبیعی استان خوزستان، سازمان تحقیقات، آموزش و ترویج‌کشاورزی، اهواز، ایران.

چکیده

به منظور شبیه‌سازی عملکرد و کارایی مصرف آب برنج توسط دو مدل AquaCrop و SWAP، تحقیقی در مرکز تحقیقات کشاورزی و منابع طبیعی استان خوزستان (ایستگاه شاوور) انجام شد. در این تحقیق، دو عامل روش کاشت (D1: نشایی، D2: مستقیم رایج در منطقه و D3: خشکه‌کاری) و رقم برنج (V1: عنبوری قرمز، V2: چمپا و  V3: دانیال) مورد مطالعه قرار گرفتند. نتایج نشان داد که دقت مدل AquaCrop برای تعیین عملکرد براساس آماره‌های MBE (36/0 تن بر هکتار)، RSME (07/1 تن بر هکتار) و NRMSE (14/0) قابل قبول بود. مقادیر این آماره‌ها برای مدل SWAP به ترتیب برابر با 54/0 تن بر هکتار، 09/1 تن بر هکتار و 15/0 بود که نشان داد دقت این مدل نیز قابل قبول بود. مقادیر آماره‌های MBE، RMSE و NRMSE برای کارایی مصرف آب توسط مدل AquaCrop به ترتیب برابر با 11/0- کیلوگرم بر مترمکعب، 40/0 کیلوگرم بر مترمکعب و 15/0 و توسط مدل SWAP به ترتیب برابر با 10/0- کیلوگرم بر مترمکعب، 40/0 کیلوگرم بر مترمکعب و 15/0 بود. متوسط اختلاف عملکرد برای مدل‌های AquaCrop و SWAP به ترتیب برابر با 64/0 و 67/0 تن بر هکتار و متوسط اختلاف بین مقادیر مشاهداتی و شبیه‌سازی شده کارایی مصرف آب توسط مدل‌های AquaCrop و SWAP به ترتیب برابر با 02/0 و 025/0 کیلوگرم بر متر مکعب تعیین شد. مجموع نتایج نشان داد که که هر دو مدل AquaCrop و SWAP دقت مناسبی برای شبیه‌سازی عملکرد و کارایی مصرف آب برنج تحت شرایط مختلف کاشت  برای ارقام گوناگون داشتند؛ لیکن دقت مدل AquaCrop از عملکرد بهتری برخوردادر بود.

کلیدواژه‌ها


عنوان مقاله [English]

Yield and Water Use Efficiency Simulation of Different Rice Cultivars under Various Cultivation Methods Using AquaCrop and SWAP

نویسندگان [English]

  • Seyed Amir Hossein Mousavi 1
  • Aslan Egdernezhad 2
  • Abdolali Gilani 3
1 M.Sc. Student of Irrigation and drainage, Department of Water Sciences and Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.
2 Assistant Professor, Department of Water Sciences and Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.
3 Assistant Professor, Seed and Plant Improvement Research Department, Khuzestan Agricultural and Natural Resources Research Center, AREEO, Ahvaz, Iran.
چکیده [English]

So as to simulate rice yield and water use efficiency using AquaCrop and SWAP models, a research study was conducted at Khuzistan Agricultrual Research Station. In this study, three types of cultivation (D1: transplanting, D2: current directs seeding consorted seeding, and D3: dry bed seeding) and rice cultivars (V1: Red-Anbori, V2: Champa, V3: Danial) were considered. Results of MBE (0.36 ton.ha-1), RMSE (0.1.07 ton.ha-1) and NRMSE (0.14 ton.ha-1) showed that AquaCrop had good accuracy for simulation of rice yield. Mentioned statistical criteria for yield simulated by SWAP were 0.54 ton.ha-1, 1.09 ton.ha-1 and 0.15, respectively, which showed a good accuracy for this model. MBE, RMSE and NRMSE values for water use efficiency calculated by AquaCrop were -0.11 kg.m-3, 0.40 kg.m-3 and 0.15, respectively, and by AquaCrop were -0.10 kg.m-3, 0.40 kg.m-3 and 0.15, respectively. Average difference between observed and simulated yield by AquaCrop and SWAP were 0.64 ton.ha-1 and 0.67 ton.ha-1, respectively. Those values for water use efficiency were 0.02 kg.m-3 and 0.025 kg.m-3, respectively. The results revealed that both AquaCrop and SWAP had acceptable accuracy for simulation of different rice cultivars yield and water use efficiency under various cultivation types, however, AquaCrop had a bit better accuracy.
 

کلیدواژه‌ها [English]

  • Champa Variety
  • Crop Modeling
  • Danial Variety
  • Dry Bed Seeding
  • Red-Anbori Variety
  • Rice Transplanting
Amiri. E. 2017. Evaluation of water schemes for maize under arid are in Iran using the SWAP model. Communications in Soil Science and Plant Analysis. 48(16): 1963-1976.

Bonefante, A., Basile, A., Acutis, M., Mascellis, R. De., Manna, P., Perego, A., 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.

Bonefante, A., Bouma, J. 2015. The role of soil series in quantitative land evaluation when expressing effects of climate change and crop breeding on future land use. Geroderma. 250-260: 187-195.

FAO, 2017. FAOSTAT. Statistical Databases. Food and Agriculture Organization of the United Nations. http:/ www.fao.org.

Farahani H. J., Izzi G., Steduto P. and Oweis T Y 2009. Parameterization and evaluation of AquaCrop for full and deficit irrigated cotton. Agronomy. 101: 469-476.

Garcia-Vila M., Fereres E., Mateos L., Orgaz F and Steduto P 2009. Deficit irrigation optimization of cotton with AquaCrop. Agronomy. 101: 477-487.

Geerts S., Raes D., Garcia M., Miranda R and Cusicanqui J A 2009. Simulating yield response to water of quinoa (Chenopodium quinoaWilld.) with FAO-AquaCrop. Agronomy. 101: 499-508.

Geerts, S., and Raes, D. 2009. Defecit irrigation as on-farm strategy to maximize crop water productivity in dry areas. Agricultural Water Management. 96: 1275-1284.

Heng, L.k., Hsiao, T.C., 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. Agron.J. 101(3), 448-459.

IRRI 2008. Background Paper: The Rice Crisis: What Needs to Be Done? IRRI, Los Baños, Philippines, www.irri.org/12pp

Jonubi, R., Rezaverdinejad, V., Salemi, H. 2017. Enhancing field scale water productivity for several rice cultivars under limited water supply. Paddy and Water Environment. 16(1): 125-141.

Ma, Y., Feng, Sh., Huo, Z., Song, X. 2011. Application of the SWAP model to simulate the field water cycle under deficit irrigation in Beijing, China. Mathematical and Computer Modeling. 54(3-4): 1044-1052.

Raes, D., Steduto, P., Hsiao, T.C., Fereres, E. 2009. AquaCrop— the FAO crop model to simulate yield response to water II. Main algorithms and software description. Agronomy Journal. 101:438–447.

Saadati, Z.,N. Pirmoradianand M. Rezaei. 2011. Calibration and evaluation of AquaCrop model in rice growth simulation under different irrigation managements. 21th International Congress on Irrigation and Drainage, October19-23,2011,Tehran,Iran,589-600.

Sharma, P. K., Ladha, J. K. and Bhushan, L. 2003. Soil physical effects of puddling in rice-wheat cropping systems. In “Improving the Productivity and Sustainability of Rice-Wheat Systems: Issues and Impacts” (J. K. Ladha, J. E. Hill, J. M. Duxbury, R. K. Gupta, and R. J. Buresh, Eds.), pp. 97–113. ASA, CSSA, SSSA, Madison, WI, ASA Special Publication 65.

Stricevic R., Cosic M., Djurovic N., Pejic B and Maksimovic L 2011. Assessment of the FAO AquaCrop model in the simulation of rainfed and supplementally irrigated maize, sugar beet and sunflower. Agricultural Water Management. 98: 1615-1621.

Todorovic M., Albrizio R., Zivotic L., Abisaab M and Stwckle C 2009. Assessment of AquaCrop, CropSyst and WOFOST models in the simulation of sunflower growth under different water regimes. Agronomy. 101: 509-521.

Van Dam, J.C., Huygen, J., Wesseling, J.G., Feddes, R.A., Kabat, P., van Walsum, P.E.V., Groenendijk, P. van Diepen, C. A. 1997. Theory of SWAP Version 2.0, Report #71. Department of Water Resources, Wageningen Agricultural University, 167 pp.

Yung, K., Anan, M., Hamada, K. 2016. Evaluation of drainage ability of a shallow subsurface drain in a rotational rice paddy field. CIGR-AgEng Conference, 26-29 June 2016, Aarhus, Denmark. Pp. 1-9.