Evaluation of the effects of climate change on meteorological and hydrological parameters using climatic models and Mann – Kendall test (case study: Urmia Lake)

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J. Bio. & Env. Sci. 2014 Introduction Increasing greenhouse gases after industrial revolution disturbs <strong>the</strong> earth energy balance and has causes <strong>the</strong> earth to be warm. According to <strong>the</strong> reports <strong>of</strong> Intergovernmental Panel on Climate Change (IPCC), if emission <strong>of</strong> greenhouse gases is not reduced, mean temperature <strong>of</strong> <strong>the</strong> earth increases by 1.1 to 4.4 ⁰C. Global warming phenomenon and its resulted <strong>climate</strong> <strong>change</strong> have significant impacts on water cycle and water resources system. Climate <strong>change</strong> results in <strong>change</strong> in run<strong>of</strong>f volume, duration and time, and consequence <strong>of</strong> this happening will make much <strong>change</strong>s in water resources management (IPCC, 2007). In studies <strong>of</strong> <strong>climate</strong> <strong>change</strong> investigation <strong>of</strong> its impacts on different sections, various uncertainties affect <strong>the</strong> final result. Greenhouse gases emission scenario and Atmosphere Ocean General Circulation Model (AOGCM) are uncertainties in climatic simulations. If <strong>the</strong>se uncertainties are not considered in analysis, validation <strong>of</strong> <strong>the</strong> results will be reduced. Therefore, use <strong>of</strong> only AOGCM model under an emission scenario for <strong>climate</strong> <strong>change</strong> analysis cannot cover whole <strong>the</strong> range <strong>of</strong> related uncertainties and will provide abnormal results. So, <strong>the</strong> researchers have attempted to consider <strong>the</strong>se uncertainty sources by more than one climatic model under emission scenarios in <strong>climate</strong> <strong>change</strong> studies (Massah Bavani, 2006). For example, Kamga (2005) used three climatic models under emission scenarios A2 and B2, Massah Bavani (2006) used seven climatic models under emission scenarios A2 and B2. Maurer et al. (2009) used 16 climatic models under emission scenarios A2 and B2. Khani Tamalieh et al. (2012) used a climatic model under scenario A2 in evaluation <strong>of</strong> <strong>the</strong> <strong>effects</strong> <strong>of</strong> <strong>climate</strong> <strong>change</strong> on drought traits. They found that, in future periods <strong>of</strong> <strong>climate</strong> <strong>change</strong>s <strong>the</strong>re will be more variations for parameters <strong>of</strong> precipitation and temperature in <strong>the</strong> east <strong>of</strong> Urmia Lake than its west. Grieser and Tromel (2002) investigated temperature <strong>of</strong> 100 years in Europe and demonstrated that, annual temperature fluctuations are significantly increased in <strong>the</strong> Eastern Europe and almost has had increasing trend throughout <strong>the</strong> region. In a same research in which Wilby and Dettinger (2006) investigated <strong>the</strong> effect <strong>of</strong> <strong>climate</strong> <strong>change</strong> on <strong>the</strong> amount <strong>of</strong> low flows <strong>of</strong> Teams River in England, uncertainty sources associated with AOGCM Model, downscaling methods, greenhouse gases emission scenario, various models <strong>of</strong> simulating precipitation-run<strong>of</strong>f and uncertainty related to <strong>the</strong>ir parameters considering different weights and Monte Carlo method were simulated. The results showed that, uncertainties associated with AOGCM models have <strong>the</strong> highest proportion and greenhouse gases have <strong>the</strong> minimum proportion in estimating <strong>the</strong> probability function <strong>of</strong> run<strong>of</strong>f. Minville et al. (2008) investigated <strong>the</strong> uncertainty <strong>of</strong> <strong>the</strong> effect <strong>of</strong> <strong>climate</strong> <strong>change</strong> on <strong>the</strong> run<strong>of</strong>f <strong>of</strong> Canada watershed using HSAMI. They used five GCM models and two emission scenarios. Results reveals an increase in temperature by 1 to 14 ⁰C and seasonal precipitation by -9 to 55%. Also, <strong>the</strong> amount <strong>of</strong> run<strong>of</strong>f <strong>of</strong> <strong>the</strong> watershed affected by <strong>climate</strong> <strong>change</strong> will <strong>change</strong>. In a research conducted by Samadi and Massah Bavani (2008), downscaling <strong>of</strong> precipitation and temperature was done by statistical method (SDSM) and Artificial Neural Network (ANN). At <strong>the</strong> end <strong>of</strong> <strong>the</strong> mentioned research it was concluded that, successfulness <strong>of</strong> both methods has been same for temperature downscaling while, ANN was more successful than SDSM for downscaling <strong>of</strong> precipitation (Samadi et al., 2008). In ano<strong>the</strong>r research carried out by Ash<strong>of</strong>teh et al. (2008), <strong>the</strong> effect <strong>of</strong> <strong>climate</strong> <strong>change</strong> on <strong>the</strong> peak discharge <strong>of</strong> Aidoghmoush in period 2040-2069 for scenario A2 was investigated. Seven AOGCM models had been used in this study. The results show that, temperature <strong>of</strong> <strong>the</strong> watershed increases in period 2050 between 1 and 6 ⁰C compared with <strong>the</strong> base period. Also, <strong>the</strong> range <strong>of</strong> precipitation variations will be -80 to 100%. Comparison <strong>of</strong> <strong>the</strong> samples flood intensity in various return periods in two future decades showed that, peak discharge <strong>of</strong> <strong>the</strong> watershed affected by <strong>climate</strong> <strong>change</strong> will <strong>change</strong> (Ash<strong>of</strong>tehsadat et al., 2008). Ghorbani & Soltani (2002) studied <strong>the</strong> <strong>climate</strong> <strong>change</strong> <strong>of</strong> Gorgan meteorology station using 113 | Khaneshan et al
J. Bio. & Env. Sci. 2014 40 years statistics <strong>of</strong> precipitation and temperature. The results <strong>of</strong> this research showed that, <strong>climate</strong> <strong>change</strong> in this region has not had tangible effect on temperature but, it has caused to decrease precipitation. Taghavi (2005) studied <strong>the</strong> trend <strong>of</strong> temperature and precipitation indices in 16 synoptic stations in order to detect <strong>climate</strong> <strong>change</strong> in various regions. Then it was concluded that, most <strong>of</strong> warm indices have increasing trend as well as decreasing trend for cold indices. Azizi et al., (2008) used multivariate statistical analysis and Box-Jenkins model in order to investigate <strong>the</strong> existence <strong>of</strong> significant trend in temperature and humidity variables <strong>of</strong> <strong>the</strong> western half <strong>of</strong> Iran. Seyf et al. (2009) in <strong>the</strong> study <strong>of</strong> <strong>climate</strong> <strong>change</strong> <strong>of</strong> Sabzevar city in a 50 year statistical period concluded that, mean annual precipitation does not show a significant trend but, <strong>the</strong> data <strong>of</strong> mean annual temperature has a rising trend. Khosravi et al. (2010) investigated <strong>the</strong> effect <strong>of</strong> <strong>climate</strong> <strong>change</strong> on water resources <strong>of</strong> <strong>the</strong> Middle East using World Bank and IPCC. The results <strong>of</strong> this research explain that, according to IPCC <strong>climate</strong> <strong>change</strong> scenario, <strong>the</strong>re will increase by 1 to 2 ⁰C and precipitation will decrease by 20%. Change in water level in <strong>the</strong> lakes is mostly due to <strong>change</strong> in river flows and <strong>change</strong> in precipitation on <strong>the</strong> lakes and evaporation from <strong>the</strong>ir surface. Water level <strong>of</strong> a number <strong>of</strong> lakes has been dropped throughout <strong>the</strong> world during <strong>the</strong> past decades because <strong>of</strong> human activities (Khosravi et al., 2010). Atmosphere General Circulation Models are threedimension models which have been developed based on various climatic scenarios in order to simulate <strong>the</strong> effect <strong>of</strong> greenhouse impact on current <strong>climate</strong> <strong>of</strong> <strong>the</strong> earth, those are able to forecast future <strong>climate</strong> <strong>of</strong> <strong>the</strong> earth (IPCC, 2007). One <strong>of</strong> <strong>the</strong> main limitations in <strong>the</strong> use <strong>of</strong> climatic outputs <strong>of</strong> general circulation models is that, <strong>the</strong> accuracy <strong>of</strong> <strong>the</strong>se models is about 200 km which is inappropriate for investigation <strong>of</strong> mountainous regions and climatic parameters such as precipitation and temperature. SDSM is one <strong>of</strong> <strong>the</strong> most famous generating models <strong>of</strong> random data on wea<strong>the</strong>r, and is used to produce daily precipitation, radiation, minimum and maximum daily temperature in a station under current and future climatic conditions (Dehghanipoor et al., 2012). Downscaling algorithm <strong>of</strong> SDSM model has been used with much appropriate results in many meteorological, hydrological and environmental branches in geographical ranges from Europe, Nor<strong>the</strong>rn America and Sou<strong>the</strong>astern <strong>of</strong> Asia (Willy et al., 2002). The purpose <strong>of</strong> this study is to investigate <strong>the</strong> effect <strong>of</strong> <strong>climate</strong> <strong>change</strong> on variation trend <strong>of</strong> meteorological and hydrological parameters <strong>of</strong> some stations located in <strong>the</strong> watershed <strong>of</strong> Urmia Lake using climatic models and Mann Kendall test. Materials and methods Study area Urmia Lake is located in <strong>the</strong> northwest <strong>of</strong> Iran and between Western and Eastern Azerbaijan provinces. This lake is <strong>the</strong> second most saline lake <strong>of</strong> <strong>the</strong> world after Bahrolmeyet in Palestine. Length <strong>of</strong> <strong>the</strong> lake is 13 to 140 km and its width is 15 to 85 km, its mean depth is 6 m and <strong>the</strong> height is 1274 m from sea level. Area <strong>of</strong> Urmia Lake has been reported by 5000 to 5500 km 2 . Urmia Lake watershed has been placed between nor<strong>the</strong>rn latitude 35⁰ 29ʹ to 38⁰ 40ʹ and eastern longitude 44⁰ 13ʹ and 47⁰ 53ʹ. The highest point <strong>of</strong> <strong>the</strong> watershed is close to Sabalan mountaintop by 3850 m. Therefore, existing elevation difference in <strong>the</strong> watershed is estimated by 2576 m. Considering that <strong>the</strong> province has been located on <strong>the</strong> path <strong>of</strong> air masses entrance from <strong>the</strong> west and northwest, and existence <strong>of</strong> Zagros mountains in <strong>the</strong> south and southwest, heights in <strong>the</strong> west and Ararat in <strong>the</strong> north, <strong>the</strong> maximum amount <strong>of</strong> precipitation has been occurred in this region and it has generated high flow rivers. The purpose <strong>of</strong> this research is to investigate <strong>the</strong> effect <strong>of</strong> <strong>climate</strong> <strong>change</strong> on meteorological and hydrological parameters <strong>of</strong> Urmia Lake watershed. With regard to <strong>the</strong> importance <strong>of</strong> temperature, precipitation and evaporation parameters in investigating <strong>the</strong> <strong>effects</strong> <strong>of</strong> <strong>climate</strong> <strong>change</strong>, <strong>the</strong>se meteorological parameters were used in this research. 114 | Khaneshan et al
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Evaluation of the effects of climate change on meteorological and hydrological parameters using climatic models and Mann – Kendall test (case study: Urmia Lake)

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