Regionalization of the East part of Lake Urmia Basin based on impact of seasonal precipitation on rainfed yield using the ward and K-means methods

Document Type : Research Article

Authors

1 MSc. in Water Resources Engineering, Department of Water Engineering, Agriculture Faculty, Tabriz University, Tabriz, Iran

2 Professor, Department of Water Engineering, Agriculture Faculty, Tabriz University, Tabriz, Iran

3 Associate Professor, Department of Water Engineering, Agriculture Faculty, Tabriz University, Tabriz, Iran

4 Assistant Professor, Department of Water Engineering, Agriculture Faculty, Tabriz University, Tabriz, Iran

Abstract

Management and optimal use of water in agriculture is essential for management and conservation of water resources. This study aimed to evaluate the effect of seasonal precipitation fluctuations on annual rainfed yield. Monthly precipitation data for 26 rainfall stations with Statistical period of 1992 to 2014 of the east part of Lake Urmia basin were used. Clustering was done with Ward and K-means methods. The homogeneity of cluster was checked through H-Statistics method and homogeneous clusters were shown in GIS environment. The effect of seasonal precipitation was compared with annual rainfed yield. Results showed that the effect of precipitation in the spring, autumn and winter on the amount of rainfed yield is positive and precipitation in these seasons has a remarkable effect on increasing yield. In the three seasons, precipitation caused an increase of soil moisture storage which is used in summer. But, there is an inverse relationship between precipitation and annual rainfed yield in the summer. In order to identify areas combined with increased precipitation and rainfed yield, iso-line of precipitation seasons with the rainfed yield of the study area was drawn. The results of this line showed that in the spring, autumn and winter at the Daryan, Lighvan, Khormazard, Sahlan, Harvy, Saidabad, ShirinKandy, Ghorigol, Tabriz and Moghanjigh, the increased amount of pricipitation is directly related to the amount of yield. These areas can introduce more eligible rainfed cultivation in East of Lake Urmia and recognition of the effects of precipitation on yield rainfed areas can be more practical and reliable.

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منابع
[1]. Dinar A, editor. Measuring the impact of climate change on Indian agriculture. World Bank Publications; 1998; 402 p.
[2]. Oche CY. Agroclimatic zonation for wheat production in the savanna region of Nigeria. Singapore Journal of Tropical Geography. 1998; 19(1): 39-50.
[3]. Munoz-Diaz D, Rodrigo FS. Spatio-temporal patterns of seasonal rainfall in Spain (1912-2000) using cluster and principal component analysis: comparison. InAnnales Geophysicae. 2004; 22 (5): 1435-1448.
[4]. Nassiri M, Koocheki A, Kamali GA, Shahandeh H. Potential impact of climate change on rainfed wheat production in Iran: (Potentieller Einfluss des Klimawandels auf die Weizenproduktion unter Rainfed-Bedingungen im Iran). Archives of agronomy and soil science. 2006; 52(1): 113-124.
[5]. Liu S, Mo X, Lin Z, Xu Y, Ji J, Wen G, Richey J. Crop yield responses to climate change in the Huang-Huai-Hai Plain of China. Agricultural water management. 2010; 97(8):1195-209.
[6]. Parracho AC, Melo-Gonçalves P, Rocha A. Regionalisation of precipitation for the Iberian Peninsula and climate change. Physics and Chemistry of the Earth, Parts A/B/C. 2016; 94:146-154.
[7]. Azizi GH, Yarahmadi D. The relationship between climatic parameters and wheat yield using regression model case study of sliding Sylankhor. Journal of Geographical Research. 2003; 44:23-29. (Persian)
[8]. Rasouli AA, Ghasemi GHolazani K, Sobhani B.The Role of precipitation and height in determining for cultivation of rainfed wheat using GIS (Case study: Ardebil), Journal of Geography and Development. 2005; 3:183-200. (Persian)
[9]. Feizizadeh B, Blaschke T. Land suitability analysis for Tabriz County, Iran: a multi-criteria evaluation approach using GIS. Journal of Environmental Planning and Management. 2013; 56(1):1-23. (Persian)
[10]. Balyani y, Hajarizadeh Z, Farjai A, Biat A. Agricultural climatic zoning of wheat cultivation using Geographic Information System Case Study: Fars province. Journal of Physical Geography. 2012; 5 (15): 33-50. (Persian)
[11]. Hasheminasb FS, Mousavi BM, Balhtiari B, Bannayan M. The Effects of Rainfall on Dryland Wheat Yield and Water Requirement Satisfaction Index at Different Time Scales. Iranian of Irrigation and Water Engineering. 2014; 5 (17): 1-13. (Persian)
[12]. MacQueen J. Some methods for classification and analysis of multivariate observations. InProceedings of the fifth Berkeley symposium on mathematical statistics and probability 1967; 1 (14): 281-297.
[13]. Moemeni M. Data clustering 2nd Tehran. Mansour Momeni. 2014. (Persian)
[14]. Ward Jr JH. Hierarchical grouping to optimize an objective function. Journal of the American statistical association. 1963; 58(301): 236-244.
[15]. Hosking JR, Wallis JR. Some statistics useful in regional frequency analysis. Water resources research. 1993; 29(2):271-281.