The Impact of Climate Variability on Water Footprint Components of Rainfed Wheat and Barley in Qazvin Province of Iran†

THE IMPACT OF CLIMATE VARIABILITY ON WATER FOOTPRINT COMPONENTS OF RAINFED WHEAT AND BARLEY IN QAZVIN PROVINCE OF IRAN† RASTA NAZARI1, HADI RAMEZANI ETEDALI1, BIJAN NAZARI1 AND BRIAN COLLINS2 1Department of Water Sciences and Engineering, Imam Khomeini International University, Qazvin, Iran 2The Centre for Crop Science, The University of Queensland, Toowoomba, Australia ABSTRACT Due to the shortage of precipitation, rainfed farming is facing numerous challenges in Iran. Understanding the impact of climate variables on the production of rainfed crops in each region is of utmost importance for dry farming. Based on the 11-year (2004-2015) data from synoptic stations in Qazvin province of Iran, a comprehensive simulation analysis was conducted with AquaCrop-GIS to study the yield and the green and gray water footprint (WF) of the main rainfed crops (wheat and barley) along with the correlation of the target variables (yield and WF components) with the selected climate variables. Based on the estimated values of green and gray WFs, planting of rainfed wheat and barley in Qazvin and Moalem Kalayeh stations with lower total WF will be more beneficial than in other stations. Regression analysis showed that in most stations, reference evapotranspiration had a direct effect on wheat total WF (TWF) while precipitation has a positive effect on barley TWF in Qazvin and Moalem Kalayeh. The regression equation of barley green WF in the Qazvin station showed the highest correlation with climate variables (R2 = 0.98). TWF of wheat and barley in Buin Zahra had the highest correlation with climate variables (R2 = 0.73 and 0.85, respectively). Finally, it was concluded that in arid regions, the variability in TWF of rainfed products was heavily influenced by spatiotemporal variations of climate variables. † L’impact de la variabilité climatique sur les composantes de l’empreinte hydrique du blé et de l’orge pluviaux dans la province de Qazvin en Iran This is the author manuscript accepted for publication and has undergone full peer review but Dr. Hadi Ramezani Etedali. Imam Khomeini International University, Department of Water Sciences has not been through the copyediting, typesetting, pagination and proofreading process, which and Engineering, Qazvin 34149-16818, Islamic Republic of Iran, T: +982818371279. E-mail: may lead to differences between this version and the Version of Record. Please cite this article [email protected]. as doi: 10.1002/ird.2487 1 This article is protected by copyright. All rights reserved. KEY WORDS: AquaCrop-GIS, climate variability, crop modelling, water footprint, regression analysis. RĖSUMĖ En raison du manque de précipitations, l’agriculture pluviale est confrontée à de nombreux défis en Iran. Comprendre l’impact des variables climatiques sur la production de cultures pluviales dans chaque région est de la plus haute importance pour l’agriculture sèche. Sur la base des données sur 11 ans (2004-2015) des stations synoptiques de la province de Qazvin en Iran, une analyse de simulation complète a été réalisée avec AquaCrop-GIS pour étudier le rendement et l’empreinte en eau verte et grise (WF) des principales cultures pluviales. (blé et orge) ainsi que la corrélation des variables cibles (composantes rendement et WF) avec les variables climatiques sélectionnées. Sur la base des valeurs estimées des WF vertes et grises, la plantation de blé et d’orge pluviaux dans les stations Qazvin et Moalem Kalayeh avec une WF totale plus faible sera plus bénéfique que dans d’autres stations. L’analyse de la régression a montré que dans la plupart des stations, l’évapotranspiration de référence avait un effet direct sur la WF total du blé (TWF) tandis que les précipitations avaient un effet positif sur le TWF de l’orge à Qazvin et Moalem Kalayeh. L’équation de régression de la WF verte de l’orge dans la station Qazvin a montré la corrélation la plus élevée avec les variables climatiques (R² = 0,98). La TWF de blé et d’orge de Buin Zahra présentait la corrélation la plus élevée avec les variables climatiques (R² = 0,73 et 0,85, respectivement). Enfin, il a été conclu que dans les régions arides, la variabilité de la TWF des produits pluviaux était fortement influencée par les variations spatio-temporelles des variables climatiques. MOTS CLÉS: AquaCrop-GIS; variabilité climatique; modélisation des cultures; empreinte hydrique; analyse de régression. INTRODUCTION Wheat is the most important cultivated crop in Iran. Wheat, barley, lentil and chickpea account for about 99% of land area and 92% of the rainfed agricultural production in Qazvin province in central Iran. Iran is in the list of countries with water scarcity. The country’s renewable water resources are expected to drop to less than 1,500 m3 per capita by 2030 (Yang et al., 2006). 2 This article is protected by copyright. All rights reserved. Therefore, management of agricultural water consumption, the largest consumer of water in the country, is of utmost importance. The concept of ‘water footprint’ (WF) was introduced by Hoekstra (Hoekstra, 2003) and is an efficient tool for managing water resources in water scarce areas. This term is an indicator of the allocation of freshwater resources to various sections of the production process (Ababaei and Ramezani Etedali, 2014, 2017). This concept has been adopted in numerous studies on WF (e.g. Hoekstra and Hung, 2002; Hoekstra and Chapagain, 2007, 2008; Liu et al., 2007; Hoekstra and Mekonnen, 2012; Chenoweth et al., 2013; Hoekstra, 2017; Ababaei and Ramezani Etedali, 2014, 2017). Crop models are one useful tool to predict crop growth and development under various management and climate scenarios and to understand the way water is uptaken and appropriated during the production process. AquaCrop, introduced by Food and Agriculture Organization of the United Nations (FAO), is widely used as it requires less input data compared with most other well-known crop models (Raes et al., 2009). The benefits of adopting AquaCop include the flexibility of the model in implementing various management solutions, irrigation method, and the ability to simulate the effects of environmental stresses such as water stress, logging, salinity, fertility and heat. AquaCop has been used in different regions and for various purposes and crops (Farahani et al., 2009; Garcia-Vila et al., 2009; Geerts et al., 2009; Heng et al., 2009; Hsiao et al., 2009; Tavakoli et al., 2010; Andarzian et al., 2011; Salemi et al., 2011; Alizadeh et al., 2010; Babazade and Saraee Tabrizi, 2012; Ramezani Etedali et al., 2016). Knowledge of the causes of variability in WF is important to obtain information on water requirements corresponding to crop production and helps understand the impact of climate variables on WF components, which is especially important in rainfed cropping. Precipitation and temperature, as the most important climate variables, have significant effects on agricultural production. Precipitation plays an important role in the cultivation of rainfed products and is especially important to determine the appropriate time and place for cultivation of a specific crop in order to receive maximum precipitation and obtain highest yields. Therefore, the objectives of this study were: i) to quantify the variability of the yield of rainfed wheat and barley in the Qazvin province of Iran; ii) to estimate the variability in the WF of the studied crops; iii) to analyse the correlation between yield and climate variables. MATERIALS AND METHODS Study area 3 This article is protected by copyright. All rights reserved. The Qazvin province is located in the northwest of Iran. With an area of ~15,820 km2, Qazvin is located between N 36° 15΄and E 50° 00΄. The counties of the Qazvin province are Qazvin, Takestan, Buin Zahra, Abyek, Alborz and Avaj County (Figure 1). The province consists of two main basins of Shur-Rud and Sefid Rud. The Shur-Rud basin is the largest water catchment area in the province and includes 72.4% of the area of the Qazvin plain. Given its history, agricultural products and animal species and with an area of ~65,000 ha, the Qazvin plain is of an economic and historical significance in central Iran. The plain has an advanced irrigation network that, with an age of over 35 years, includes 1,122 ka of concrete canal. The irrigation and drainage network of Qazvin plain covers an area of 17,000 km2. Based on De Martonne aridity index, this region’s climate is semi-arid. The overall pattern of cultivation in the study area is 50% autumn crops, which are mostly wheat and barley. In addition, fruit gardens, forage and corn maize, forage crops and oilseeds are among the dominant cultures of the study area. [Figure 1 is here] According to the De Martonne climagram, the semi-arid cold climate is the largest climatic zone in Qazvin, Abyek and Takestan. In the highlands and in the north parts of these counties, with a decrease in average temperature, the semi-arid ultra-cold climate is observed. The driest region in the province is Buin Zahra and its surrounding areas in the east and south have an arid cold climate. Meanwhile, in the highlands of Avaj, ultra-cold wet and ultra-cold semi-humid climates are dominant. The annual precipitation of the province varies between 210 mm in the east and more than 550 mm on northeast mountains. The meteorological stations are presented in Table I. [Table I is here] AquaCrop-GIS To investigate the spatial variations of the target variables, AquaCrop-GIS (Lorite et al., 2013) was adopted. AquaCrop-GIS and AquaCrop-Data connect the AquaCrop model with ArcGIS enabling the simulation of numerous spatial units under various scenarios. A study was conducted to simulate the impacts of climate change on wheat yield in southern Spain by AquaCrop-GIS and AquaCrop-Data (Lorite et al., 2013).

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