Future Study of Wheat Water Requirement with Time Series Models in East of Urmia Lake

Document Type : Original Article

Author

AREEO

Abstract

Considering the current and prospect situation of Urmia Lake, the future study of variables of irrigation scheduling and management is one of the priorities of agricultural research to improve the cropping pattern in the east of lake. In this study, the time series of wheat evapotranspiration in sixteen regions of East Azarbaijan located at the east of Urmia Lake was determined using the Penman-Monteith FAO method with the regional crop coefficient. The analysis period was 80 years from 1330-31 to 1396-97, which 50 years (from1330-31 to 1379-80) was applied for the time series modeling, 17 years ( from 1380-81 to 1396-97) for testing and 13 years (from 1397-98 to 1409-1410) for future studying up to 1410. Among the eighteen possible models, the appropriate time series model for wheat evapotranspiration in cold climate regions such as Azarshahr, Osko, Bonab, Tabriz, Jolfa, Maragheh, Malekan, Marand and Miyaneh was acquired as ARIMA (0, 1, 1) and for very cold climates such as Ahar, Bostanabad, Sarab, Shabestar, Kaleibar, Harris and Hashtrood was obtained as an exponential trend model. The wheat evapotranspiration in East Azerbaijan in the past 67 years averaged 478 mm and for the next 13 years averaged 500 mm. The findings of this study are valuable and practical for irrigation scheduling in full and deficit irrigated conditions and reduction of drought damage in east Urmia Lake.

Keywords


خلیلی، ع. 1383، تدوین یک سامانه جدید پهنه­بندی اقلیمی از دیدگاه نیازهای گرمایش و سرمایش محیط و اعمال آن بر گستره ایران، فصلنامه تحقیقات جغرافیایی، 75 صفحه­های 14-5.
عنابی میلانی، ا. 1388. تعیین و ارزیابی تبخیر-تعرق، نیاز آبی و ضریب گیاهی گندم در دشت تبریز. کنگره علوم خاک ایران. دانشگاه علوم کشاورزی و منابع طبیعی گرگان.
فرشی، ع.، شریعتی، م.ر.، جاراللهی، م،. قائمی، م.، شهابی‏فر، م.، و تولائی .1376 .برآورد آب مورد نیاز گیاهان عمده زراعی و باغی کشور. نشر آموزش کشاورزی. 900 صفحه.
ناصری، ا.، عباسی، ف.، سهراب، ف.، عباسی، ن. و اکبری، م. 1396. برآورد مقدار آب مصرفی در بخش کشاورزی. گزارش نهایی پروژه تحقیقاتی. موسسه تحقیقات فنی و مهندسی کشاورزی. 199 صفحه.
Adhikary, S.K., Rahman, M., and Gupta, A.D. 2012. A stochastic modelling technique for predicting groundwater table fluctuations with time series analysis. International Journal of Applied Science and Engineering Research. 1(2): 238-249.
Alizadeh, A., and Kamali, G.H. 2007. Crops water requirements in IRAN. Emam Reza University, Mashad. 227p.
Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. 1998. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9), D05109.
Brockwell, P.J., and Davis, R.A. 1996. Introduction to time series and forecasting. Springer-Verlag, New York, Inc. pp.449
Burlando, P., Montana, A., and Raze, R. 1996. Forecasting of storm rainfall by combined use of radar, rain gages and liner models. Atmospheric Research. 42: 199-216.
Castellano-Mendez, M., Gonzalez-Manteiga, W., Febrcro- Bende, M., Prada-Sanchez, J.M., and Lozano-Calderon, R. 2004. Modeling of monthly and daily behavior of the run off the Xallas river using Box-Jenkins and Neural networks methods. Journal of Hydrology. 296: 38-58.
Chatfield, C. 2016. The analysis of time series: an introduction. CRC press; p.205.
Choubin, B., Malekian, A. 2017. Combined gamma and M-test-based ANN and ARIMA models for groundwater fluctuation forecasting in semiarid regions. Environmental Earth Sciences. 76(15): p.538.
Cirkel, D.G., Witte, J.P.M., and van der Zee, S.E. 2010. Estimating seepage intensities from groundwater level time series by inverse modeling: A sensitivity analysis on wet meadow scenarios. Journal of hydrology. 385(1-4):132-142.
Cuthbert, M.O. 2010. An improved time series approach for estimating groundwater recharge from groundwater level fluctuations. Water Resources Research. 46(9):201-212.
Fathabadi, A., Salajegheh, A., and Mahdavi, M. 2008. Forecasting River discharges by Neuro-Fuzzy and time series models. Iran-Watershed Management Science & Engineering. 2(5): 21-30.
Fooladmand, H.R. 2010. Monthly prediction of reference crop evapotranspiration in Fars Province. Water and Soil Science, 1(20):157-169. (In Persian with English abstract).
Ghahraman, N., and Gharekhani, A. 2011. Evaluation of Stochastic time series models in estimation of pan evaporation: case study in Shiraz station. Research Journal of Water in Agriculture. (1):75-81.
Gibrilla, A., Anornu, G., and Adomako, D. 2018. Trend analysis and ARIMA modeling of recent groundwater levels in the White Volta River basin of Ghana. Groundwater for Sustainable Development. 6:150-163.
Hatch, C.E., Fisher, A.T., Ruehl, C.R., and Stemler, G. 2010. Spatial and temporal variations in streambed hydraulic conductivity quantified with time-series thermal methods. Journal of Hydrology. 389(3-4):276-288.
Irvine DJ, Cranswick RH, Simmons CT, Shanafield MA, Lautz LK. 2015. The effect of streambed heterogeneity on groundwater‐surface water exchange fluxes inferred from temperature time series. Water Resources Research 51(1): 198-212.
Johnson, T.C., Slater, L.D., Ntarlagiannis, D., Day‐Lewis, F.D., and Elwaseif, M. 2012. Monitoring groundwater‐surface water interaction using time‐series and time‐frequency analysis of transient three‐dimensional electrical resistivity changes. Water Resources Research. 48(7).
Karimzadeh Moghaddam, M. and Ghahraman, B. 2001. Statistical view of reference evapotranspiration increase in Masshad and its results. The first national conference on procedures of mitigation with water crisis. Pp. 95-108.
Nakhaei, M., and Mirarabi, A. 2010. Flood forecasting by time series of discharge of Sumbar River with Box-Jenkins model. Journal of Engineering Geology. 1(4): 901-910.
Nasseri, A. 2004. Time series analysis of infiltration and spatio-temporal distribution of surface flow along furrows. PhD Thesis. Tabriz University. Iran. p.129.
Niroomand, H.A. 1997. Time series analysis. Ferdowsi University of Mashhad. Iran. pp112.
Peterson, R.N., Santos, I.R., and Burnett, W.C. 2010. Evaluating groundwater discharge to tidal rivers based on an Rn-222 time-series approach. Estuarine, Coastal and Shelf Science. 86(2):165-178.
Rahimi, D., and Gayoor, H. 2010. Analysis of Karoon discharge with Box-Cox transformation and time series. Geographical Research. 25(4):135-151.
Rakhshandehroo, G.R., Amiri, S.M. 2012. Evaluating fractal behavior in groundwater level fluctuations time series. Journal of hydrology. 464:550-556.
Rau, G.C., Andersen, M.S., and Acworth, R.I. 2012. Experimental investigation of the thermal time‐series method for surface water‐groundwater interactions. Water Resources Research. 48(3).
Salas, J.D., Delleur, J.W., Yevjevich, V.M., Lane, W.L. 1980. Applied modeling of hydrologic time series. Water Resources publications. Littleton. Colorado, pp.484.
Sen, Z. 1998. Small sample estimation of the time average in climate time series. International Journal of Climatology. 18; 1725-1732.
Shirvani, A., and Honar, T. 2011. Application of time series models for evapotranspiration forecasting in Bajgah station. Iranian Water Research Journal. (8):135-142. (In Persian with English abstract.
Tarazkar, M.H., Sedghamiz, A. 2008. Comparing monthly discharge forecasting for Karkheh River by using time series and artificial intelligence traits. Pazhohesh and Sazandeghi 21(3):51-58.
Taweesin, K., Seeboonruang, U., Saraphirom, P. 2018. The Influence of Climate Variability Effects on Groundwater Time Series in the Lower Central Plains of Thailand. Water. 10(3), pp.290.
Vandersteen, G., Schneidewind, U., Anibas, C., Schmidt, C., Seuntjens, P., and Batelaan, O. 2015. Determining groundwater‐surface water exchange from temperature‐time series: Combining a local polynomial method with a maximum likelihood estimator. Water Resources Research. 51(2): 922-939.
Yang, Q., Wang, Y., Zhang, J., and Delgado, J. 2017. A comparative study of shallow groundwater level simulation with three time series models in a coastal aquifer of South China. Applied Water Science. 7(2): 689-698.
Zahedi, M., and Ghavidel Rahimi, Y. 2002. Recognition, classification and forecasting drought in Urmia watershed by time series model of Holt-Winters. Geographical Space. 6:19-48.
Zare Abyaneh, H., Saghaei, S., Ershad-Fath, F. and Nozari, H. 2014. Modeling and forecasting of reference crop evapotranspiration Using time series, case study: Kermanshah province. Journal of Agricultural Meteorology. 2(1): 45-56.