Yıl: 2021 Cilt: 9 Sayı: 4 Sayfa Aralığı: 769 - 774 Metin Dili: İngilizce DOI: 10.24925/turjaf.v9i4.769-774.4184 İndeks Tarihi: 26-11-2021

Forecasting future performance of irrigation schemes: The case of Bergama

Öz:
Potential outputs of irrigation should be put forth to improve the yields in agricultural practices. Available water resources should efficiently be used to improve yields and inputs should be minimized. Performance assessment of irrigation schemes is an importance issue for improved yields and to take relevant measured. Statistical methods are used for performance assessment of irrigation schemes with the use of various indicators. Forecasts for future performance of irrigation shames will facilitate the steps to be taken by decision-makers to improve performance. In this study, time series – ARIMA method was used to forecast future performance of Bergama irrigation scheme for 2017-2021 period. The indicator values of annual irrigation water supply per unit command area, output per unit command area and total expenditure per unit command area for 2006-2017 period were used to estimate performance indicators for 2017-2021 period. In 2021, at 95% probability, the lowest annual irrigation water supply per unit-command area was calculated as 4365.10 m3 ha-1 and the highest as 16835.69 m3 ha-1 ; the lowest output per unit command area was calculated as -5076.10 € ha-1 and the highest as 10401.2 € ha-1 ; the lowest total expenditure per unit command area was calculated as -2200.41 € ha-1 and the highest as 1866.31 € ha-1 . Present forecasts of time series -ARIMA method with the use of data of 2006-2016 period revealed that annual irrigation water supply per unit-command area and output per unit command area will increase and total expenditure per unit command area will decrease in years.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • Alcamo J, Döll P, Kaspar F, Siebert S. 1997. Global change and global scenarios of water use and availability: an application of WaterGAP 1.0. Center for Environmental Systems Research, University of Kassel, Kassel, Germany.
  • Alcon F, García-Bastida PA, Soto-García M, Martínez-Alvarez V. 2017. Explaining the performance of irrigation communities in a water-scarce region. Irrigation Science, doi: 10.1007/s00271-016-0531-7
  • Aljoumani B, Sànchez-Espigares JA, Canameras N, Josa R, Monserrat J. 2012. Time series outlier and intervention analysis: Irrigation management influences on soil water content in silty loam soil. Agricultural Water Management, 111: 105-114.
  • Anonymous 2020. Republic of Turkey Ministry of Agriculture and Forestry. Annual Report of 2019. Available from: https://cdniys.tarimorman.gov.tr/api/File/GetFile/425/KonuI cerik/759/1107/DosyaGaleri/dsi-2019-faaliyet-raporu.pdf [Accesed 16 February 2021]
  • Arslan F, Değirmenci H. 2018. RAP-MASSCOTE Aproach of modernizing operatıon-maintanence and management of irrigation schemes: A case study of Kahramanmaraş left bank irrigation scheme. Atatürk University Journal of Agricultural Faculty, doi: 10.15832/ankutbd.512677.
  • Boss MG, Murrray-Rust DH, Merrey DJ, Johnson HG, Snellen WS. 1994. Methodologies for assessing performance of irrigation and drainage management. Irrigation and Drainage Systems, doi:10.1007/BF00881553
  • Box GEP, Jenkins GM, Reinsel GC. 1994. Time series analysis; Forecasting and control, Prentice Hall, Englewood Cliff, New Jersey.
  • Burt C. 2001. Rapid appraisal process (RAP) and benchmarking explanation and tools. Retrieved in June, 10, 2020 from http://www.fao.org/3/a-aq443e.pdf
  • Campbell S, Diebold F. 2005. Weather forecasting for weather derivatives. Journal of the American Statistical Association, 100, 6-16.
  • Corcoles JI, Tarjuelo JM, Moreno MA, Ortega JF, De Juan JA. 2010. Evaluation of Irrigation Systems by Using Benchmarking Techniques. In: Proceedings of XVII. World Congress of the International Commission of Agricultural and Biosystems Engineering, 13-17 June, Québec City, Canada, pp: 225-234.
  • Çakmak B. 2001. Evalution of irrigation system performance in irrigation associations Konya. Tarım Bilimleri Dergisi 7: 111- 117.
  • Değirmenci H. 2004. Assessment of irrigation schemes with comparative indicators in Kahramanmaraş region. KSU Journal of Science and Engineering 7(1): 104-110.
  • DSI, 2019. Assessment report of irrigation facilities operated and transferred by DSI. General Directorate of State Hydraulic Works. Ankara, Turkey.
  • Engle R. 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom ináation. Econometrica, 50: 987-1008.
  • Falkenmark M, Rockstrom J, Rockström J. 2004. Balancing water for humans and nature: The new approach in ecohydrology. Earthscan.
  • Kartal S, Değirmenci H, Arslan F. 2019. The effect of irrigation channel type and length on irrigation performance indicators. KSU J. Agric Nat., doi:10.18016/ksutarimdoga.vi.502821.
  • Kartal S, Değirmenci H, Arslan F. 2020. Assessment of irrigation schemes with performance indicators in southeastern irrigation district of Turkey. Journal of Agricultural Sciences. doi:10.15832/ankutbd.543990.
  • Malano H, Burton M. 2001. Guidelines for Benchmarking Performance in the Irrigation and Drainage Sector. IPTRID and FAO, Rome, Italy.
  • Mandal BN. 2005. Forecasting sugarcane productions in India with ARIMA model. New Delhi: IASRI
  • MCGLADE, 2012. Jacqueline et al. Measuring water use in a green economy, a report of the working group on water efficiency to the International Resource Panel. United Nations Environment Programme.
  • Millennium Ecosystem Assessment 2005. A Report of the Millennium Ecosystem Assessment. Ecosystems and Human Well-Being. Island Press, Washington DC.
  • Molden DJ, Sakthivadivel R, Perry CJ, Fraiture CD, Kloezen WH. 1998. Indicators for Comparing the Performance of Irrigated Farming Systems. IWMI, Colombo, Research Report 20: 26.
  • Narayanamoorthy A. 2007. Tank irrigation in India: a time series analysis. Water policy, 9(2): 193-216.
  • Neath A, Cavanaugh J. 2012. The Bayesian information criterion: Background, derivation, and applications. Wiley Interdisciplinary Reviews: Computational Statistics, doi:10.1002/wics.199.
  • Nelson D. 1991. Conditional heteroskedasticity in asset returns: a new approach. Econometrica, 59: 347-370.
  • Pamuk G, Özgürel M, Topçuoğlu K. 2004. Standart yağış indisi (SPI) ile Ege Bölgesinde kuraklık analizi. Ege Üniversitesi Ziraat Fakültesi Dergisi, 41(1).
  • Renault D, Facon T, Wahaj R. 2007. Modernization of Irrigation Management: MASSCOTE Approach Mapping System and Services for Canal Operation Techniques. Food and Agriculture Org., 63: 13.
  • Rodríguez-Díaz JA, Camacho-Poyato E, Lopez-Luque R, PérezUrrestarazu L. 2008. Benchmarking and multivariate data analysis techniques for improving the efficiency of irrigation districts: An application in Spain. Agricultural Systems 96(1- 3): 250-259.
  • Seckler D, Amarasinghe U, Molden D, de Silva R, Barker R. 1998. World water demand and supply, 1990 to 2025: scenarios and issues. Colombo, Sri Lanka: International Irrigation Management Institute (IIMI). vi, 40p. (IWMI Research Report 019 / IIMI Research Report 019) doi: http://dx.doi.org/10.3910/2009.019.
  • Shiklomanov IA, Rodda JC. 2003. World water resources at the beginning of the 21st century. International hydrology series.
  • State Hydraulic Works 2017. 2. Ormancılık ve Su Şurası- DSİ Barajlar ve HES Dairesi Raporu. Afyonkarahisar: OSİB State Hydraulic Works 2018. DSİ Genel Müdürlüğü Resmi Görüşü. Ankara: DSİ.
  • Watershed Management Plans. 2019. Watershed Management Plans. Available from: https://www.tarimorman.gov.tr/SYGM/ Belgeler/NHYP%20DEN%C4%B0Z/ULUSAL%20SU%20P LANI.pdf 2019 [Accesed 16 February 2021]
  • Zema DA, Nicotraa A, Mateosb L, Zimbonea SM. 2018. Improvement of the irrigation performance in water users associations integrating data envelopment analysis and multiregression models. Agricultural Water Management, doi:10.1016/j.agwat.2018.04.032
APA Kartal S (2021). Forecasting future performance of irrigation schemes: The case of Bergama. , 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
Chicago Kartal Sinan Forecasting future performance of irrigation schemes: The case of Bergama. (2021): 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
MLA Kartal Sinan Forecasting future performance of irrigation schemes: The case of Bergama. , 2021, ss.769 - 774. 10.24925/turjaf.v9i4.769-774.4184
AMA Kartal S Forecasting future performance of irrigation schemes: The case of Bergama. . 2021; 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
Vancouver Kartal S Forecasting future performance of irrigation schemes: The case of Bergama. . 2021; 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
IEEE Kartal S "Forecasting future performance of irrigation schemes: The case of Bergama." , ss.769 - 774, 2021. 10.24925/turjaf.v9i4.769-774.4184
ISNAD Kartal, Sinan. "Forecasting future performance of irrigation schemes: The case of Bergama". (2021), 769-774. https://doi.org/10.24925/turjaf.v9i4.769-774.4184
APA Kartal S (2021). Forecasting future performance of irrigation schemes: The case of Bergama. Türk Tarım - Gıda Bilim ve Teknoloji dergisi, 9(4), 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
Chicago Kartal Sinan Forecasting future performance of irrigation schemes: The case of Bergama. Türk Tarım - Gıda Bilim ve Teknoloji dergisi 9, no.4 (2021): 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
MLA Kartal Sinan Forecasting future performance of irrigation schemes: The case of Bergama. Türk Tarım - Gıda Bilim ve Teknoloji dergisi, vol.9, no.4, 2021, ss.769 - 774. 10.24925/turjaf.v9i4.769-774.4184
AMA Kartal S Forecasting future performance of irrigation schemes: The case of Bergama. Türk Tarım - Gıda Bilim ve Teknoloji dergisi. 2021; 9(4): 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
Vancouver Kartal S Forecasting future performance of irrigation schemes: The case of Bergama. Türk Tarım - Gıda Bilim ve Teknoloji dergisi. 2021; 9(4): 769 - 774. 10.24925/turjaf.v9i4.769-774.4184
IEEE Kartal S "Forecasting future performance of irrigation schemes: The case of Bergama." Türk Tarım - Gıda Bilim ve Teknoloji dergisi, 9, ss.769 - 774, 2021. 10.24925/turjaf.v9i4.769-774.4184
ISNAD Kartal, Sinan. "Forecasting future performance of irrigation schemes: The case of Bergama". Türk Tarım - Gıda Bilim ve Teknoloji dergisi 9/4 (2021), 769-774. https://doi.org/10.24925/turjaf.v9i4.769-774.4184