شبیه‌سازی رشد و نمو گوجه‌فرنگی (Lycopersicon esculentum Mill.) در شرایط تنش خشکی: 1- محتوای رطوبت خاک، تبخیر وتعرق و پوشش کانوپی

آب و خاک

مقاله 1، دوره 35، شماره 3 - شماره پیاپی 77، مرداد و شهریور 1400، صفحه 299-318   

نوع مقاله: مقالات پژوهشی

شناسه دیجیتال (DOI): 10.22067/jsw.2021.15011.0

نویسندگان

اسماعیل فرخی¹؛ مهدی نصیری محلاتی^{* 2}؛ علیرضا کوچکی²؛ علیرضا بهشتی³

¹دانشجوی دکتری گروه اگروتکنولوژی، دانشکده کشاورزی، دانشگاه فرودسی مشهد

²استاد گروه اگروتکنولوژی، دانشکده کشاورزی، دانشگاه فرودسی مشهد

³مرکز تحقیقات کشاورزی و منابع طبیعی خراسان رضوی

چکیده

مطالعه حاضر با هدف شبیه­سازی محتوای رطوبت خاک، تبخیر و تعرق و پوشش کانوپی گوجه­فرنگی تحت رژیم­های مختلف آبیاری در مراحل مختلف رشد با استفاده از مدل آکوواکراپ در شرایط آب و هوایی مشهد به اجرا درآمد. آزمایش به صورت کرت‌های خرد‌شده در مزرعه تحقیقاتی دانشکده کشاورزی دانشگاه فردوسی مشهد در دو سال زراعی 1396-1395 اجرا شد. عامل کرت اصلی شامل کم‌آبیاری به میزان 100، 75 و 50 درصد نیاز آبی گیاه در مرحله رویشی و عامل کرت فرعی شامل کم‌آبیاری به میزان 100، 75 و 50 درصد نیاز آبی گیاه در مرحله زایشی بود. مدل آکوواکراپ با استفاده از داده­های اندازه­گیری شده واسنجی و صحت­سنجی گردید.  به طور کلی، محتوای رطوبت خاک، تبخیر و تعرق و پوشش کانوپی گوجه­فرنگی با دقت قابل قبولی توسط مدل آکوواکراپ صحت سنجی شد، با این وجود کارایی مدل با افزایش تنش آب کاهش پیدا کرد. میانگین مربعات خطای نرمال‌شده بدست آمده برای محتوای آب خاک و پوشش کانوپی گوجه­فرنگی در همه تیمارهای آبیاری 36/13 و 87/13، 25/16 و 87/12 درصد به ترتیب برای مرحله واسنجی و صحت­سنجی بود، که این نتایج نشان­دهنده توانایی بالای مدل آکوواکراپ در شبیه­سازی تغییرات رطوبت خاک و پوشش کانوپی در طول دوره رشد گوجه­فرنگی می­باشد. نتایج این پژوهش نشان داد که مدل آکوواکراپ می­تواند در شرایط تنش آبی در سطح قابل قبولی واسنجی شود و به عنوان ابزاری سودمند برای تصمیمات حمایتی در زمان و میزان آبیاری گوجه­فرنگی تبدیل شود.

کلیدواژه‌ها

آکوواکراپ؛ کراپ وات؛ کم آبیاری؛ مدل‌سازی؛ موازنه آب خاک

مراجع

1- Abrha B., Delbecque N., Raes D., Tsegay A., Todorovic M., Heng L.E.E., Vanutrecht E., Geerts S.A.M., Garcia-Vila M., and Deckers S. 2012. Sowing strategies for barley (Hordeum vulgare L.) Based on modelled yield response to water with aquacrop. Experimental Agriculture 48: 252-271.

2- Agricultural Statistics of Iran. 2018. The yearbook of agriculture statistics of Iran. Bureau of statistics and information technology, The ministry of Agriculture, Tehran, Iran. 232 pages. (In persian)

3- Ahmadi S.H., Mosallaeepour E., Kamgar-Haghighi A.A., and Sepaskhah A.R. 2015. Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements. Water Resources Management 29: 2837-2853.

4- 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. Agricultural Water Management 100: 1-8.

5- Araya A., Habtu S., Hadgu K.M., Kebede A., and Dejene T. 2010a. Test of AquaCrop model in simulating biomass and yield of water deficient and irrigated barley (Hordeum vulgare). Agricultural Water Management 97: 1838-1846.

6- Araya A., Keesstra S.D., and Stroosnijder L. 2010b. Simulating yield response to water of Teff (Eragrostis tef) with FAO's AquaCrop model. Field Crops Research 116: 196-204.

7- Bahmani O., and Eghbalian S. 2018. Simulating the Response of Sugarcane Production to Water Deficit Irrigation Using the AquaCrop Model. Agricultural Research 7: 158-166.

8- Carlson T.N., and Ripley D.A. 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment 62: 241-252.

9- Cusicanqui J., Dillen K., Garcia M., Geerts S., Raes D., and Mathijs E. 2013. Economic assessment at farm level of the implementation of deficit irrigation for quinoa production in the Southern Bolivian Altiplano. Spanish Journal of Agricultural Research11(4): DO - 10.5424/sjar/2013114-4097.

10- Doorenbos J., and Kassam A. 1979. Yield response to water. FAO Irrigation and Drainage, Paper No. 33: 257.

11- FAO STAT. 2018. The State of the World’s Land and Water Resources for Food and Agriculture (SOLAW)-Managing Systems at Risk. Food and Agriculture Organization of the United Nations, Rome and Earth scan, London.

12- FAO. 2019. Downloads for AquaCrop (Version 6.1) Standard Window Program and Plug-in Program. http://www.fao.org/nr/water/aquacrop.html.

13- Farahani H.J., Izzi G., and Oweis T.Y. 2009. Parameterization and Evaluation of the AquaCrop Model for Full and Deficit Irrigated Cotton. Agronomy Journal 101: 469-476.

14- Farrokhi E., Nassiri Mahalati M., Koocheki A., Beheshti S.A. 2022. Simulation of growth and development of tomato (Lycopersicon esculentum Mill.) under drought stress: 2- simulation of water productivity, above ground biomass and yield. Water and Soil. (Accepted). (In Persian with English abstract)

15- Farrokhi E., Nassiri Mahalati M., Koocheki A., Beheshti S.A. 2021. Light extinction coefficient and radiation use efficiency in different growth stages of tomato exposed to different irrigation regimes. Environmental Stresses in Crop Sciences. (Accepted). (In Persian with English abstract)

16- Foster T., Brozović N., and Butler A.P. 2014. Modeling irrigation behavior in groundwater systems. Water Resources Research 50: 6370-6389.

17- Foster T., Brozović N., Butler A.P., Neale C.M.U., Raes D., Steduto P., Fereres E., and Hsiao T.C. 2017. AquaCrop-OS: An open source version of FAO's crop water productivity model. Agricultural Water Management 181: 18-22.

18- García-Vila M., and Fereres E. 2012. Combining the simulation crop model AquaCrop with an economic model for the optimization of irrigation management at farm level. European Journal of Agronomy 36: 21-31.

19- Geerts S., Raes D., and Garcia M. 2010. Using AquaCrop to derive deficit irrigation schedules. Agricultural Water Management 98: 213-216.

20- 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. Agronomy Journal 101: 499-508.

21- Grassini P., Yang H., Irmak S., Thorburn J., Burr C., and Cassman K.G. 2011. High-yield irrigated maize in the Western U.S. Corn Belt: II. Irrigation management and crop water productivity. Field Crops Research 120: 133-141.

22- Greaves E.G., 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.

23- 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: 488-498.

24- 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: 448-459.

25- Jiang Z., Huete A.R., Chen J., Chen Y., Li J., Yan G., and Zhang X. 2006. Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction. Remote Sensing of Environment 101: 366-378.

26- Johnson L.F., and Trout T.J. 2012. Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California’s San Joaquin Valley. Remote Sensing 4.

27- Katerji N., Campi P., and Mastrorilli M. 2013. Productivity, evapotranspiration, and water use efficiency of corn and tomato crops simulated by AquaCrop under contrasting water stress conditions in the Mediterranean region. Agricultural Water Management 130: 14-26.

28- Kim D., and Kaluarachchi J. 2015. Validating FAO AquaCrop using Landsat images and regional crop information. Agricultural Water Management 149: 143-155.

29- 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: 419-427.

30- Mhizha T. 2010. Increase of yield stability by staggering the sowing dates of different varieties of rainfed maize in Zimbabwe.

31- Mhizha T., Geerts S., Vanuytrecht E., Makarau A., and Raes D. 2014. Use of the FAO AquaCrop model in developing sowing guidelines for rainfed maize in Zimbabwe. Water SA 40: 233-244.

32- Nyakudya I.W., and Stroosnijder L. 2014. Effect of rooting depth, plant density and planting date on maize (Zea mays L.) yield and water use efficiency in semi-arid Zimbabwe: Modelling with AquaCrop. Agricultural Water Management 146: 280-296.

33- Paredes P., de Melo-Abreu J.P., Alves I., and Pereira L.S. 2014. Assessing the performance of the FAO AquaCrop model to estimate maize yields and water use under full and deficit irrigation with focus on model parameterization. Agricultural Water Management 144: 81-97.

34- Pirmoradian N., and Davatgar N. 2019. Simulating the effects of climatic fluctuations on rice irrigation water requirement using AquaCrop. Agricultural Water Management 213: 97-106.

35- Raes D., Steduto P., Hsiao T.C., and 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.

36- Richey A.S., Thomas B.F., Lo M.H., Reager J.T., Famiglietti J.S., Voss K., Swenson S., and Rodell M. 2015. Quantifying renewable groundwater stress with GRACE. Water Resources Research 51: 5217-5238.

37- Sandhu R., and Irmak S. 2019. Performance of AquaCrop model in simulating maize growth, yield, and evapotranspiration under rainfed, limited and full irrigation. Agricultural Water Management 223: 105687.

38- Schewe J., Heinke J., Gerten D., Haddeland I., Arnell N.W., Clark D.B., Dankers R., Eisner S., Fekete B.M., Colón-González F.J., Gosling S.N., Kim H., Liu X., Masaki Y., Portmann F.T., Satoh Y., Stacke T., Tang Q., Wada Y., Wisser D., Albrecht T., Frieler K., Piontek F., Warszawski L., and Kabat P. 2014. Multimodel assessment of water scarcity under climate change. Proceedings of the National Academy of Sciences 111: 3245-3250.

39- Shrestha N., Raes D., Vanuytrecht E., and Sah S.K. 2013. Cereal yield stabilization in Terai (Nepal) by water and soil fertility management modeling. Agricultural Water Management 122: 53-62.

40- Steduto P., Hsiao T.C., Fereres E., and Raes D. 2012. "Crop yield response to water," fao Rome.

41- 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: 426-437.

42- Tavakoli A.R., Mahdavi Moghadam M., and Sepaskhah A.R. 2015. Evaluation of the AquaCrop model for barley production under deficit irrigation and rainfed condition in Iran. Agricultural Water Management 161: 136-146.

43- Taylor R. 2014. When wells run dry. Nature 516: 179-180.

44- Todorovic, M., Albrizio, R., Zivotic, L., Saab, M.-T. A., Stöckle, C., and Steduto, P. 2009. Assessment of AquaCrop, CropSyst, and WOFOST Models in the Simulation of Sunflower Growth under Different Water Regimes. Agronomy Journal 101: 509-521.

45- Tsakmakis I.D., Kokkos N.P., Gikas G.D., Pisinaras V., Hatzigiannakis E., Arampatzis G., and Sylaios G.K. 2019. Evaluation of AquaCrop model simulations of cotton growth under deficit irrigation with an emphasis on root growth and water extraction patterns. Agricultural Water Management 213: 419-432.

46- Tsegay, A. 2012. Improving Crop Production by Field Management Strategies Using Crop Water Productivity Modeling: Case Study of Tef (Eragrostistef (Zucc.) Trotter) Production in Tigray, Ethiopia. PhD Manuscript.

47- Tsegay A., Raes D., Geerts S., Vanuytrecht E., Abraha B., Deckers J., Bauer H., and Gebrehiwot K. 2012. Unravelling crop water productivity of tef (Eragrostis Tef (Zucc.) Trotter) through AquaCrop in northern Ethiopia. Experimental Agriculture 48: 222-237.

48- Van Ittersum M.K., Cassman K.G., Grassini P., Wolf J., Tittonell P., and Hochman Z. 2013. Yield gap analysis with local to global relevance—A review. Field Crops Research 143: 4-17.

49- Vanuytrecht E., Raes D., Steduto P., Hsiao T.C., Fereres E., Heng L.K., Garcia Vila M., and Mejias Moreno P. 2014. AquaCrop: FAO's crop water productivity and yield response model. Environmental Modelling & Software 62: 351-360.

50- Zeleke K.T., Luckett D., and Cowley R. 2011. Calibration and Testing of the FAO AquaCrop Model for Canola. Agronomy Journal 103: 1610-1618.

51- 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. Agricultural and Forest Meteorology 151: 1792-1799.