Identification of Trends in Hydrological and Climatic Variables in Urmia Lake Basin, Iran

Theor Appl Climatol (2015) 119:443–464 DOI 10.1007/s00704-014-1120-4 ORIGINAL PAPER

Identification of trends in hydrological and climatic variables in Urmia Lake basin, Iran

Farshad Fathian & Saeed Morid & Ercan Kahya

Received: 2 August 2013 /Accepted: 1 February 2014 /Published online: 4 March 2014 # Springer-Verlag Wien 2014

Abstract The drawdown trend of the water level in Urmia the streamflow in Urmia Lake basin is more sensitive to Lake poses a serious problem for northwestern Iran which has changes in temperature than precipitation. In general, the had negative impacts on agriculture and industry. This re- decline in the lake water level can be related to both the search investigated likely causes of the predicament by esti- increase of temperature in the basin and an improvement in mating trends in the time series of hydroclimatic variables of over-exploitation of the water resources. the basin. Three non-parametric statistical tests, the Mann– Kendall, Spearman rho, and Sen’s T, were applied to estimate the trends in the annual and seasonal time series of tempera- 1 Introduction ture, precipitation, and streamflow at 95 stations throughout the basin. The Theil–Sen method was also used to estimate the Urmia Lake has been shrinking for the last 15 years, and its slopes of trend lines of annual time series. The results showed area has decreased from 6,100 to 4,750 km2 (Jalili 2010) a significant increasing trend of temperature throughout the resulting in about 6 m drawdown in water level. The decline basin and an area-specific precipitation trend. The tests also of the water lake has jeopardized the region’sindustrialand confirmed a general decreasing trend in the basin streamflow agricultural sectors. Furthermore, the decrease in water level that was more pronounced in the downstream stations. The of the once vibrant and vivid lake has led to buried-underwater annual trend line slope was found to be from 0.02 to 0.14 °C/ salt exposure. Persistence of this situation allows the exposed year, −7.5 to 3.8 mm/year, and −0.01 to −0.4 m3/s/year for salt to blow away, causing a serious threat to the health of the temperature, precipitation, and streamflow, respectively. The inhabitants of the region. Various reasons have been stated as homogeneity of the monthly trends was also evaluated using the major causes of this predicament, including changes in the Van Belle and Hughes tests as confirmation. Temporal hydroclimatic variables, human activities (development of analyses of the trends for the temperature and streamflow of agricultural lands due to increasing water diversion for irrigat- the basin detected significant increasing trends beginning in ed agriculture), and mismanagement (Eimanifar and Mohebbi the mid-1980s and 1990s. The correlations between 2007; Golabian 2011; Zarghami 2011; Hassanzadeh et al. streamflow and climate variables (temperature and precipita- 2012). Thus, a trend analysis of rivers’ inflows to the lake is tion) were detected by Pearson’s test. The results showed that a first step to investigate the plausible causes. However, the existence of an increasing or decreasing trend in a hydrologic F. Fathian (*) time series can also be explained by changes in precipitation Department of Water Resources Engineering, Tarbiat Modares and temperature as two of the most effective meteorological University, Box: 14115-139, Tehran, Iran drivers in rainfall–runoff processes. e-mail: [email protected] A number of statistical techniques have been used to iden- S. Morid tify significant trends in climate variables using either para- Department of Water Resources Engineering, Tarbiat Modares metric or non-parametric tests (e.g., Kahya and Kalaycı 2004; University, Box: 14115-139, Tehran, Iran Partal and Kahya 2006; Bandyopadhyay et al. 2009; Pal and Al-Tabbaa 2011; Tabari et al. 2012; Kumar et al. 2009; Zhao E. Kahya Hydraulics Division, Civil Engineering Department, Istanbul et al. 2010;Shahid2011). The former trend tests are more Technical University, Maslak, 34469 Istanbul, Turkey powerful than the latter ones; however, they require data to be

444 F. Fathian et al. independent and normally distributed. In contrast, the non- the temporal trend of annual precipitation trends in ULB. parametric trend tests only require the data to be indepen- Their results showed extreme fluctuations in annual precipi- dent and can tolerate outliers of the data (Huth and Pokorná tation during 39 years so that this trend is decreasing in most 2004; Zhang et al. 2006;Chenetal.2007). The Mann– stations over basin. Katiraei et al. (2006) and Rezaei Kendall (MK), Spearman’s rho (SR), and Sen’s T (ST) tests Banafsheh et al. (2010) focused on daily precipitation. They are typical examples of some non-parametric techniques. applied the MK test for the period 1960 to 2001 and found Moreover, the Van Bell and Hughes (VH) test used to similar results about precipitation trend in the basin. Their detect the homogeneity of seasonal trends has been used results showed that most stations located in the ULB have in few studies (Kahya and Kalaycı 2004; Dinpashoh et al. decreasing precipitation trend. In another study, Jalili (2010) 2011; Jhajharia et al. 2012). also used the MK test and reported no trend in the precipita- In Urmia Lake basin (ULB), previous studies have not tion time series of synoptic stations in the basin for the period much concentrated on climate variables, except those 1990 to 2005 as increasing temperature trends at most with focus on temperature and precipitation. Streamflow, stations. as the most important data are used in planning and The objective of present study is to explore temporal designing water resources projects, has received less monotonic trends in the time series of temperature, precip- attention. Thus, there is an obvious need for more re- itation, and streamflow in the ULB using three non- search in this area to provide an integrated prospective parametric statistical techniques, namely the Mann–Ken- about status of streamflow, and no study has yet been dall, Spearman rho, and Sen’s T tests. Trends in one or both exclusively conducted for streamflow trend in Iran, es- of these variables could be seen as potential evidence of pecially in ULB. climate change and its impact on the hydrologic cycle, Large body of research throughout the world has involved which could eventually lead to shifts in the availability of trend analysis of hydrological and climatic variables with water across the ULB. In order to locate the beginning important indications of climate change. In this context, a year(s) of a trend and estimate the slope of trend, we review of the literature showed that temperature is increasing adopted two respective tests: the sequential Mann–Kendall throughout the world (Stafford et al. 2000; Brunetti et al. (SMK) and Theil–Sen (TS). Moreover, the Van Belle and 2000; Yue and Hashino 2003;Feidasetal.2004;Wuetal. Hughes homogeneity test is used to check the homogeneity 2007;Zhaoetal.2010; Fan and Wang 2011), that is, a fact of trends. emphasized by the Intergovernmental Panel for Climate Change (IPCC 2001). However, it is not the case for precipitation as their results have not appeared to be consistent to 2 Data and methodology those of temperature (Zhang et al. 2000;Staffordetal.2000; Partal and Kahya 2006; Kumar et al. 2009; Pal and Al-Tabbaa 2.1 Study area and data 2011; Fan and Wang 2011). The analysis results showed that there are different results of precipitation trends depending on The ULB is located in northwest Iran and covers an area of the region of the study. For example, decreasing trends of 51,800 km2 (Fig. 1). It is the largest lake in the country and is annual and seasonal rainfall were noted in Italy (Brunetti et al. also one of the world’s saltiest bodies of water. The lake basin 2000), India (Duan et al. 2006;PalandAl-Tabbaa2011), Sir includes 14 main subbasins that surround the lake with the Lanka (Zubair et al. 2008), southeastern Australia (Murphy areas that vary from 431 to 11,759 km2. The most important and Timbal 2008), and Turkey (Partal and Kucuk 2006). On rivers are ZarrinehRoud, SiminehRoud, and Aji Chai. Numer- the other hand, increasing rainfall trends were found in ous hydrometeorological stations exist in the basin; because Spain (Mosmann et al. 2004), the USA (Groisman et al. some had short record lengths, not all were applicable. The 2001), and Canada (Zhang et al. 2000). Trend analysis for selected stations are shown in Fig. 1.Theycomprise35rain streamflow is more complicated, since it is affected by gauge stations, 35 stream gauge stations, and 25 temperature climate variables as well as land processes. Streamflow gauge stations (Table 1). The gauging stations selected for trends have been extensively analyzed in different parts analysis were based on a large record of data (>30 years) for of the world to document long-term hydrologic trends and validity of the time series and trend analysis results and possible effect of climate change on hydrology. Studies continuity of their records as evenly distributed throughout include both analyzing trends at catchment (Zhang et al. the basin as possible (Githui 2009). All records started from 2006; Masih et al. 2010;Zhaoetal.2010) and national 1950s, 1960s, and 1970s and ended on with the year 2007 for scale (Lettenmaier et al. 1994; Kahya and Kalaycı 2004; all analysis. Stations were selected having records with min- Kumar et al. 2009). imum continuous 30 years of observations. In addition, data Specifically, Jahanbakhsh-Asl and Ghavidel Rahimi recorded annually from 1966 to 2008 of the lake level at (2003) used the linear and polynomial regressions to analyze Golmankhaneh station was also prepared and applied for

Identification of trends in hydrological and climatic variables 445

Fig. 1 Map showing the study area

further analysis. We applied three non-parametric tests, name- a linear trend is present in a time series, respectively. ly Spearman, Mann–Whitney, and run test to evaluate the Since the time scale of our analysis is monthly, the Van independence, homogeneity, and randomness status of data, Belle and Hughes homogeneity test is used to check the respectively. The results confirmed the quality of data under homogeneity of the monthly results (Van Belle and consideration. Hughes 1984).

2.2 Methodology MK test This test, commonly known as the Kendall’s τ, has been widely used to test stationary statistics against We selected three non-parametric methods in this study trend statistics in hydrology and climatology (Burn and to detect and confirm an existing trend with more confi- Elnur 2002). It is a rank-based procedure and good for use dence, namely the Mann–Kendall (Mann 1945;Kendall with skewed variables. The MK trend test starts first with 1975), Spearman rho (Sneyers 1991), and Sen’s T (Yue computing the test statistic S as: et al. 1993) test. In addition, we applied the sequential – – Mann Kendall (Sneyers 1991)andTheilSen (Theil Xn −1 Xn ÀÁ 1950;Sen1968) test in order to locate the beginning S ¼ Sgn x j −xk ð1Þ year(s) of a trend and to estimate the slope magnitude if k¼1 j¼kþ1

446 Ta b l e 1 Listing of temperature, precipitation, and hydrogauge stations used in this study

Basin no. Station number Station name Location Height (m) Span of temperature Length (years) Span of precipitation Length (years) Span of streamflow Length (years)

1 1 Sahzab Aghimon Chai River 1,900 ––1972–2007 36 1975–2007 33 2 Saransar Aji Chai River 1,660 ––1972–2007 36 1975–2007 33 3 Vanyar Aji Chai River 1,450 ––1972–2007 36 1950–2007 58 4 Sahlan Sanikh Chai River 1,330 1973–2007 35 –––– 5 Mirkooh Tajyarsarab River 1,400 1973–2007 35 –––– 6 Akholeh Aji Chai River 1,310 ––1972–2007 36 1975–2007 33 7 Sarab Aji Chai River 1,682 1978–2007 30 –––– 8 Tabriz Aji Chai River 1,361 1951–2007 57 –––– 2 9 Yangjeh Ghaleh Chai River 1,650 ––1972–2007 36 1975–2007 33 10 Shishvan Ghaleh Chai River 1,270 ––1972–2007 36 1975–2007 33 3 11 Alavian Sofi Chai River 1,600 ––1972–2007 36 1974–2007 34 12 Chekan Chekan Chai River 1,440 ––1972–2007 36 1975–2007 33 13 Maraghe Sofi Chai River 1,478 1978–2007 30 –––– 4 14 Moghanj Moghanj Chai River 1,500 1978–2007 30 –––– 15 Gheshlagh Amir Mardogh Chai River 1,450 ––1972–2007 36 1975–2007 33 16 Shirinkand Leylan Chai River 1,380 ––1972–2007 36 1974–2007 34 5 17 Ghabghablou Saghez Chai River 1,500 ––1970–2007 38 1975–2007 33 18 Nezam Abad ZarrinehRoud River 1,283 ––1972–2007 36 1975–2007 33 19 Pol Anian Jighato Chai River 1,460 1978–2007 30 1972–2007 36 1975–2007 33 20 Safakhaneh Sarogh Chai River 1,475 ––1972–2007 36 1975–2007 33 21 Senteh Kherkhereh Chai River 1,434 ––1972–2007 36 1975–2007 33 22 Sari Ghamish ZarrinehRoud River 1,380 ––1967–2007 41 1956–2007 52 23 Sad ShahidKazemi ZarrinehRoud River 1,473 1978–2007 30 –––– 24 Saghez ZarrinehRoud River 1,523 1961–2007 47 –––– 25 Takab ZarrinehRoud River 1,682 1978–2007 30 –––– 6 26 Bokan SiminehRoud River 1,350 ––1967–2007 41 1951–2007 57 27 Tazekand SiminehRoud River 1,290 1974–2007 34 1972–2007 36 1975–2007 33 28 Sad Noroozlou SiminehRoud River 1,330 1978–2007 30 –––– 7 29 Kotar Mahabad Chai River 1,380 ––1971–2007 37 1975–2007 33 30 Pol Sorkh Mahabad Chai River 1,350 1975–2007 33 – 31 Pol Bahramlou Gadar Chai River 1,285 ––1967–2007 41 1958–2007 50 32 Mahabad Mahabad Chai River 1,352 1978–2007 30 –––– 8 33 PeyGhaleh Gadar Chai River 1,500 1978–2007 30 1967–2007 41 1966–2007 42 34 Naghadeh Gadar Chai River 1,340 ––1967–2007 41 1966–2007 42 al. et Fathian F. 9 35 Ghasemlou Balanj Chai River 1,380 1978–2007 30 1969–2007 39 1974–2007 34

36 Babaroud Barandoz Chai River 1,285 ––1967–2007 41 1950–2007 58 10 37 Mir Abad Shahr Chai River 1,525 1978–2007 30 1967–2006 40 1974–2007 34 Identification of trends in hydrological and climatic variables 447

where n is the number of observations, xj is the jth observation, and Sgn(.) is the sign function, which can be computed as:

Length (years) 2 ÀÁ ÀÁþ1 if ÀÁx j −xk > 0 4 Sgn x j −xk ¼ 0 if ÀÁx j −xk ¼ 0 ð2Þ −1 if x j −xk < 0 2007 33 20072007 57 43 20072007 58 2007 33 33 200720072007 33 2007 33 38 33 – – – – – – – – – –

The mean of S is zero and its variance can be computed years) Span of streamflow (Kendall 1975)as: Xm nnðÞ−1 ðÞ2n þ 5 − ttðÞ−1 ðÞ2t þ 5 ¼ VarðÞ¼S i 1 ð3Þ 18 2007 36 1975 20072007 41 39 1951 1965 2007200720072007 40 37 37 36 1975 1975 1970 1975 200720072007 41 40 37 1950 1975 1975 – – – – – – – – – – an of precipitation Length ( where m is the number of groups of tied ranks, each with ti tied –––– 1972 –––– –––– 1967 –––– 1968 1977 1971 1971 1967 –––– observations. Mann–Kendall is designated by Z and is com- putedas(Douglasetal.2000): 8 > S −1 > pffiffiffiffiffiffiffiffiffiffiffiffiffiffi < VarðÞS if S > 0 ¼ ¼ ð Þ Z > 0 if S 0 4 > S −1 < :> pffiffiffiffiffiffiffiffiffiffiffiffiffiffi if S 0

perature Length (years) Sp VarðÞS 2007 57 20072007 40 37 20072007 30 37 1969 2007 302007 30 1968 1972 2007 30 – – – – – – – – –– –– –– –– –– –– –– Thus, in a two-sided test for trends, the null hypothesis should be accepted if at the α level of significance. A positive value of Z indicates an upward trend. The critical value at a 0.10 significance level of the trend test is ±1.64.

SR test A quick and simple test to determine whether correlation exists between two classifications of the same series of observations is the Spearman rank correlations test. Given a

sample data set {Xi, i=1,2,…,n}, the null hypothesis H0 of the SR test over the trend tests is that Xi is independent and ocation Height (m) Span of tem identically distributed. The alternative hypothesis is that Xi increases or decreases with i, that is, a trend exists. The test statistic is: .X ÀÁ 2 3 rs ¼ 1− 6 ½RXðÞi −i N −N ð5Þ

sffiffiffiffiffiffiffiffiffiffiffi n−2 Z ¼ r ð6Þ SR S − 2 1 rS 52 Shanjan Shanjan River 1,650 1971 51 Sharafkhaneh Daryan Chai River 1,270 1968 45 Urmia Nazlou Chai River 1,328 1951 44 MarzSarv Bardook River 1,640 1971 43 Abajalousofla Nazlou Chai River 1,290 1978 474849 Nazar Abad Tamr YalghozAghaj Darik Chai River Zola Chai River 1,620 Kherkhereh Chai River 1,410 1,300 1978 41 Kalhor Rozeh Chai River 1,500 3839 Band Urmia Kamp Urmia Shahr Chai River Shahr Chai River 1,390 1,381 1978 (continued) where R(Xi) is the rank of the ith observation Xi in a sample of size n. Positive values of ZSR indicate upward trends, while 13 4614 ChehrighOlia 50 Zola Chai River Daryan 1,600 1978 Daryan Chai River 1,600 12 42 Tapik Nazlou Chai River 1,450 11 40 GoyjaliAslan Nazlou Chai River 1,285 Ta b l e 1 Basin no. Station number Station name L negative ZSR indicate downward trends in the time series. The

448 F. Fathian et al.

ZSR statistic is approximately normally distributed for the SR way of locating the beginning year(s) of a trend (Partal and statistic (Yue et al. 2002). Kahya 2006).

ST test This technique is an aligned rank method having TS method The magnitude of the slope of the trend is estimat- procedures expressed in a matrix such as, where n denotes ed using the approach developed by Theil (1950) and Sen the number of years and m denotes the number of seasons. The (1968). The slope is estimated using Eq. 11 where Xt and Xs test is based on the calculation of the test statistic T, under the are data values at time t and s (t>s), respectively (Kumar et al. null hypothesis of no trend. In the present study, in order to 2009). detect trends for each season, ST test was applied to each − individual season. If |T|>z , a trend exists at that station at the β ¼ X t X s ð Þ a − 11 α level. Mathematical developments of the test are well de- t s scribed by Partal and Kahya (2006).

SMK test This method analyzes the temporal trends of The median of N=n(n−1)/2 for βi is Sen’s estimator of slope hydroclimatic time series (Zhang et al. 2005). The time series where n is the number of time periods. The value of βmedian is −α is assumed for n variables as x1, x2, … xn; pi denotes the tested using a two-sided test at the 100(1 )% confidence cumulative samples where xi>xj (1≤j≤i); dk is calculated as interval, and the true slope is obtained using the non- (Zhao et al. 2010): parametric test.

Xk 2.2.1 Test of homogeneity of trends dk ¼ PiðÞ2 ≤ k ≤ n ð7Þ i ¼ 1 The three non-parametric trend tests used in our study implic- itly assume trend homogeneity between seasons. Using an imaginary data set, Van Belle and Hughes (1984)demonstrat- When the original time series is random and independent, the ed that the overall statistic indicates no trend, although a trend mean and the variance of d are defined as: k is apparent for each season. As a result, an overall trend test at kkðÞ−1 a station leads to an ambiguous conclusion when the trend, in Ed½¼ ð8Þ k 4 fact, is heterogeneous between seasons. They suggested computing the following three chi-square terms with a standard normal deviate (Z) based on the MK statistic for each season (Kahya and Kalaycı 2004). Homogeneity of seasonal trends at a station can be calculated as: kkðÞ−1 ðÞ2k þ 5 ½¼ ðÞ≤ ≤ ðÞ Var dk 2 k n 9 Xm 2 72 χ2 ¼ χ2 −χ2 ¼ 2 − ð Þ homogenous total trend Zi m Z 12 i ¼ 1

Under the above assumption, the statistic index UFk (MK test based on the data) is calculated as: Zi and Z are: d −Ed½ pkffiffiffiffiffiffiffiffiffiffiffiffiffiffiffik Xm UFk ¼ k ¼ 1; 2; 3; …; n ð10Þ S 1 Var½d Z ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffii and Z ¼ Z ðÞm ¼ 12 for monthly data k i ðÞ i Var Si m i ¼ 1 ð13Þ where UFk satisfies the normal distribution and the null hypothesis can be rejected at the significance level of α,if|UF|>

UF1−α/2.Also,UF1−α/2 is the critical value of the standard where Si is the MK statistic for month i.Thisproducestwo 2 normal distribution with a probability exceeding α/2. Com- possible results: (a) If xhomogeneous exceeds the critical value puting UB (MK test based on adverse sequence of the data) is for the chi-square distribution of (m−1) degrees of freedom repeated based on the adverse sequence of the above, meaning (df), the null hypothesis of homogeneous seasonal trends over that the sequence is from xn to x1. When the UF and UB curves time (trends in the same direction) must be rejected; (b) if 2 2 intersect, the intersection point denotes the jumping (or turn- xhomogeneous does not (m−1) df, then the value of the x trend is ing) point (Zhang et al. 2005). In other words, the sequential a chi-square distribution where df=1 to test for a common version of the Mann–Kendall is considered as an effectual trend in all seasons.

Identification of trends in hydrological and climatic variables 449

3 Results and discussion of temperature stations exhibiting upward or downward trends for monthly and annual time scales. The results of trend 3.1 Annual and monthly trend analysis in ULB analysis using the selected methods for hydrologic and climatic variables at 10 % or lower significant level are shown in In this section, we present trend analysis results for each Fig. 2. The number of stations having significant upward variable at the both annual and monthly scales. The three (positive) or downward (negative) trends in temperature is non-parametric methods nearly resulted in the same number shown in Fig. 2a. It has been observed that 20, 21, and 22

Fig. 2 Number of stations a Temperature showing significant upward 25 (positive) and downward MK SR ST t

(negative) trends for time series of n a 20 c i a temperature, b precipitation, f i n

and c streamflow variables, g i obtained through the MK, SR, s 15 g n and ST methods at 10 % or lower i v significant levels in ULB a 10 h n o i t 5 a t s f o

r 0 e b positive and negative trends m u

N -5 Apr Oct Jan Jun Feb Mar July Aug Sep Nov Dec May

Time Annual

b Precipitation 35 MK SR ST

t 30 n a c i

f 25 i n g i

s 20 g n

i 15 v a h 10 n o i t 5 a t s f

o 0 r e b

positive and negative trends -5 m u

N -10 Apr Oct Jun Jan Mar Feb Dec Sep July Nov Aug May

Time Annual

c Streamflow 10 MK SR ST t

n 5 a c i f i 0 n g i s -5 g n i v

a -10 h n o

i -15 t a t s

f -20 o r e

b -25 positive and negative trends m u

N -30 Oct Apr Jan Jun Feb Mar Nov Dec July Aug Sep May

Time Annual

450 F. Fathian et al. out of 25 stations show a significant increasing trend in having significant either positive or negative precipitation temperature on the annual time scale according to the MK, trends are 9 for MK, 10 for SR, and 20 for ST at the annual SR, and ST tests, respectively. time scale. Spatial distribution of annual precipitation trends is Spatial distribution of annual temperature trends depicted depicted in Fig. 3b implying that the entire basin almost in Fig. 3a implies that the entire basin almost demonstrated demonstrated unique no trend behavior (e.g., 25 out of 35 unique upward trend behavior. Temperature data showed a stations). Exceptions are downward trends in four precipita- significant decreasing trend in only two small portion of the tion stations in the upper western and one station in the eastern western (Urmia station) and southern (Saghez station) basin. It basin. is important to note that at least two tests confirmed the On the monthly time scale, a large number of no significant indicated trends in our analysis. trends are almost observed in all months, with more appear- On the monthly time scale, a large number of positive ance in April and October (Fig. 5). This finding is fairly significant trends are observed in June, August, and October consistent with that of annual scale. A number of increasing as a low number of those in January, February, and December (decreasing) trends are mainly detected in the period of July to (Fig. 4). It can be also noticed that most of the stations November (March to June) in the ULB. demonstrated statistically significant increasing trends in the Jalili (2010) also reported that there was no trend in the summer and autumn seasons. Negative significant trends were precipitation time series of synoptic stations in the basin from detected in few stations (that is to say, two to four of 25 1990 to 2005 using the MK test whereas an increasing tem- stations) at both annual and monthly time scale, except for perature trend was observed at most stations. In contrast, February and March months. Considering the extended period Ghahraman and Taghvaeian (2008) as well as Dinpashoh of May to October, it can be said that prevailing trend-type et al. (2013) showed a significant decreasing trend in annual temperature behavior is in upward mode across the ULB. It is precipitation over the northwest Iran (covering ULB) using also evident that there is no prevailing trend-type temperature the linear regression and MK methods, respectively. behavior across the ULB in the period of November to April, In the evaluation of streamflow trend results, Fig. 2c indicating a persistent pattern in relation to climate change. shows the number of streamflow stations having both sig- Consequently, it can be expected that evaporation and evapo- nificant upward and downward trends (in most cases). transpiration trends would be increasing as noted by the Drastic negative significant trends (reduction of inflows) studies of Dinpashoh et al. (2011) and Sabziparvar et al. were detected in a number of stations varying from 20 to (2010) for northwestern Iran. 71 % of 35 stations. The MK, SR, and ST methods came In the evaluation of precipitation trend results, Fig. 2b out to be the same conclusion being quite consistent in shows that the number of precipitation stations having signif- number as the case of temperature. icant upward and downward trends is not only less than those The spatial distribution of streamflow trends can be seen in of temperature and streamflow, but somewhat unparalleled Fig. 3c. Negative trends were located in the northwest, south- indications of the three methods outcomes are also evident. ern, and eastern of ULB. The downstream subbasins show Unlike temperature, 11 to 37 % of all stations revealed signif- more significant non-stationary and negative trends (17 out of icant trends on the annual time scale, depending on testing 35 stations). Most of these areas were agricultural regions, and method. Out of the 35 stations, the total numbers of stations this reflects the effect of human interference and the growing

Fig. 3 Spatial variation of annual trends for a temperature, b precipita- lower significance level in main subbasins of ULB (the numbers near tion, c streamflow with increasing trend (up-pointing triangles), decreas- each station represent the station number according to Table 1) ing trend (down-pointing triangles), and no trend (circles) at the 10 % or

Identification of trends in hydrological and climatic variables 451

Fig. 4 Spatial variation of monthly trends for temperature with increasing trend (up-pointing triangles), decreasing trend (down-pointing triangles), and no trend (circles) at the 10 % or lower significance level in main subbasins of ULB from January to December exploitation of the upper subbasins. According to the study of water level decline in Urmia Lake so that 65 % of the decline Hassanzadeh et al. (2012), various factors have influenced the was from changes in inflow caused by climate change and

452 F. Fathian et al.

Fig. 5 Spatial variation of monthly trends for precipitation with increasing trend (up-pointing triangles), decreasing trend (down-pointing triangles), and no trend (circles) at the 10 % or lower significance level in main subbasins of ULB from January to December diversion of surface water for upstream use. It can be also streamflow and the stations with no trend also have negative noticed that there are no increasing significant trends for trend, but not significantly.

Identification of trends in hydrological and climatic variables 453

Fig. 6 Spatial variation of monthly trends for streamflow with increasing trend (up-pointing triangles), decreasing trend (down-pointing triangles), and no trend (circles) at the 10 % or lower significance level in main subbasins of ULB from January to December

The highest number of negative (positive) monthly trends decreasing trends in annual streamflow in ULB seems to be (Fig. 6) was reported for October (August). A view of combined effects of decreasing trend tendency in all months

454 F. Fathian et al.

Fig. 7 Estimated trend slopes of 0.15 annual mean: a temperature, b 0.13 a Temperature Slope precipitation, and c streamflow

C/year) 0.11 calculated by the Theil–Sen o method in ULB 0.09 0.07 0.05 0.03 0.01 -0.01 Slope of TemperatureSlope of ( -0.03 7 4 5 8 27 33 35 43 44 46 13 14 19 23 24 25 28 30 32 37 39 45 49 51 52 Station Number 4

-2

-4

-6 b Precipitation Slope

Slope of Precipitation (mm/year) -8 3 1 2 6 9 50 42 10 12 16 17 20 21 22 29 35 37 38 46 48 49 11 15 18 19 26 27 31 33 34 36 40 41 43 47

Station Number 0.15

0.05 /s/year) 3 -0.05

-0.15

-0.25

-0.35 c Streamflow Slope

Slope of streamflowSlope of (m -0.45 3 6 9 1 2 37 40 46 47 11 15 17 18 26 27 35 36 38 41 42 43 48 49 50 12 16 19 20 21 22 29 31 33 34 10

Station Number particularly in January, February, September, and October. number of stations having negative significant streamflow Furthermore, comparison of the results shows that the total trends is 17 for MK, 14 for SR, and 25 for ST for the annual

Fig. 8 Averages of normalized 2 time series for annual temperature, precipitation, discharge at selected stations, and 1 lake level in ULB 0

-1

-2 Temperature Streamflow Urmia Lake Level Surrounds Temperature Precipitation

Averages of normalized time series -3 1968 1973 1978 1983 1988 1993 1998 2003 2008 Time

Identification of trends in hydrological and climatic variables 455

70 Fig. 9 Results of Van Belle and Critical value of X2 Hughes homogeneity test of a a temperature, b precipitation, and c 60 streamflow monthly trends in 50 ULB (crossing the critical threshold confirms heterogeneity 40 of monthly trends within a station) 30 20

homogenous temperature 10 2 X 0 4 5 7 8 13 14 19 23 24 25 27 28 30 32 33 35 37 39 43 44 45 46 49 51 52 Station Number 30 b Critical value of X2 25

5 homogenous precipitation 2 X 0 2 3 9 1 6 37 10 11 15 16 17 18 19 20 21 22 26 27 31 35 36 38 40 46 48 49 50 12 29 33 34 41 43 47 42 Station Number

80 c Critical value of X2 70 60 50 40 30 20 10 X2 homogenous streamflow 0 1 6 9 2 3 20 10 15 50 18 19 21 37 11 12 16 27 31 42 46 22 38 49 17 29 33 36 41 43 26 47 48 34 35 40 Station Number time scale. For the monthly time scale, ST test, unlike the this is 20 out of 35 (57 %) and 15 stations are located below other methods, detected more stations with a significant trend. zero line (Fig. 7b); also for streamflow, 33 out of 35 (95 %) It should be noted that the results belonging to the MK and TS stations show negative slope (Fig. 7c). It can be said that the tests for trend detection of monthly and annual temperature, annual mean increase in basin temperatures varies from 0.02 precipitation, and streamflow were similar, and it was ignored to 0.14 °C/year and the average value is about 0.05 °C/year for to show in Fig. 2. the stations under consideration. Similarly, the annual mean values vary from −7.5 to 3.8 (mm/year) for precipitation and 3.2 Trend slope of hydrological and climatic variables from −0.01 to −0.4 (m3/s/year) for discharge. Generally, it can in ULB be concluded that the slope values of the annual mean temperature and streamflow are positive and negative, respective- The respective variations in significant upward and downward ly, as being alternating positive and negative for precipitation. trends of hydrological and climatic variables using slope Moreover, the general behavior of these time series has values calculated by the TS method for each station are shown been evaluated for all selected stations in this study. Figure 8 in Fig. 7. Temperature slopes for 23 out of 25 (92 %) stations shows the averages of normalized time series for the recorded are located above zero line (Fig. 7a). In case of precipitation, annual temperature, precipitation, and discharge at selected

456 F. Fathian et al.

Fig. 10 Results of Van Belle and 160 Critical value of X2 Hughes trend test of a a temperature, b precipitation, and c 140 streamflow monthly trends in 120 ULB (crossing the critical threshold confirms homogeneity 100 and existence of common monthly trends) 80 60 trend temperature

2 40 X 20 0 4 5 7 8 13 14 19 23 24 25 27 28 30 32 33 35 37 39 43 44 45 46 49 51 52 Station Number

16 b Critical value of X2 14 12 10 8 6

trend precipitation 4 2 X 2 0 1 6 2 3 9 21 48 10 12 15 16 17 18 19 20 22 27 29 31 33 34 35 36 37 38 40 41 42 43 46 47 49 50 11 26 Station Number

80 c Critical value of X2 70 60 50 40 30 trend streamflow

2 20 X 10 0 1 2 3 6 9 10 11 17 20 36 37 38 40 50 16 21 26 29 35 12 15 22 27 31 33 34 48 18 19 41 42 43 46 47 49 Station Number

stations and the lake level. The figure shows continuous temperature at the basin stations and the surrounding ones is positive values for temperature and negative values for dis- similar. A general increase in temperature and decrease in charge and lake level. There was a doubt that this positive streamflow and lake level in the basin are observable after trend is a local phenomenon, and it relates to reduction in the the 1990s. size of the lake and increased available energy to heat air instead of evaporating the lake’s water body. To accommodate 3.3 Homogeneity of detected trends this, several stations around the basin were selected, and averages of their standardized values were calculated and Figure 2 showed that the monthly trends do not necessarily added to Fig. 8. As seen in this figure, the general pattern of similar nor do all months have significant trends.

Identification of trends in hydrological and climatic variables 457

Fig. 11 Spatial variation using VH monthly trend test for a temperature, b precipitation, and c streamflow with homogenous monthly trends (up- pointing triangles), heterogeneity monthly trends (down-pointing triangles), and no trend (circles) at the 1 % significance level in main subbasins of ULB

Nevertheless, when analyzing the hydroclimatic monthly time homogeneity in hydroclimatic trends between months im- series at a station, homogeneity of monthly trends can be plies that some months exhibited upward trends, whereas verified (Kahya and Kalaycı 2004). To test the validity of this others show downward trends. The result of estimated assumption, the VH homogeneity test was applied for indi- monthly trends is shown in Fig. 11a, and 19 out of 25 vidual stations within the 14 subbasins. temperature stations are homogenous (only six out of 25 As stated, this was done in two steps. First, the homogene- stations located in the southeastern and western of the basin 2 ity of the results was evaluated (Fig. 9), and xhomogeneous of the are heterogeneous), and their resemblance to Fig. 3a is stations was compared to its critical value at α=0.01 and evident. This evaluation was expected because the results 2 found to be about 24.72 with a df of 11. Since xhomogeneous of three non-parametric tests for monthly temperature were for all stations was less than critical, the monthly trends were similar for all stations. This conclusion was also confirmed homogenous; otherwise, they were heterogeneous. Thus, the in term of precipitation, and there are no heterogeneous null hypothesis of homogeneity of the stations can be accepted monthly trends for all stations (Fig. 11b). In case of (Zhang et al. 2001;BurnandElnur2002). For temperature, streamflow, most of the subbasins showed homogenous the VH homogeneity of trend test showed that six out of 25 trends, and nine out of 35 stations located in northeastern stations result in heterogeneity in monthly trends (Fig. 9a). and southern of basin are heterogeneous (Fig. 11c). Overall, But, in case of precipitation, all station showed homogeneity the homogeneity test in the present study revealed that of monthly trends (Fig. 9b). In addition, nine out of 35 stations trends are homogenous. This means that similar streamflow stations show heterogeneity of monthly trends direction of trends for average value of Z statistics for (Fig. 9c). months is shown almost for all stations. Moreover, homog- Once the homogeneity of the monthly trends in a station enous nature of monthly trends suggests that trends for all has been confirmed, the second step is to compare x2 trend months were in the same direction for average values of with its critical value (6.63 where df=1 at α=0.01), Z’s for the station. confirming that trends for all months have the same direction. Figure 10 summarizes the results of the VH trend test of 3.4 The results of SMK test temperature, precipitation, and streamflow at the stations under consideration. We found that 88, 28, and 74 % of stations The trends of the annual mean values of the hydroclimatic (numerically 22 out of 25, 10 out of 35, and 26 out of 35, stations were analyzed using the SMK test for the stations that 2 2 respectively) have Xtrend larger than Xcritical (equal to 6.68). showed that significant trends based on at least two tests were Monthly trends in temperature, precipitation, and streamflow performed to confirm a significant trend. The time series are thus homogeneous in the study area. In other words, trends showed a downward trend when UF<0 (Eq. 10)andan in all months for each station have the same direction (upward increasing trend if UF>0. Where UF is greater than the critical or downward). Kahya and Kalaycı (2004)alsoshowedthe value in the figure (the two dashed lines above and below homogeneity of streamflow trends in Turkey, based on the VH zero), the upward or downward trend is at 10 % significance basin wide trend test. level (UF and UB=±1.64 lines). Finally, the UF curve shows a The spatial status of the homogeneity of trends in the changing trend for the hydroclimatic variables at specific basin is shown in Fig. 11. The heterogeneity monthly times (Zhang et al. 2005). trends of stations mean that we cannot assume a monotonic Figure 12 shows the results of the turning point of the MK trend between months. In other words, nonexistence of analysis of the annual temperature for stations having

458 F. Fathian et al.

4 4 3 5 UF UF UF UF Mahabad Maragheh Sarab 4 Tabriz 3 3 UB UB UB UB 2 3 2 2

1 2 1 1 1 0 0 0 0

-1 -1 -1 -1

-2 -2 -2 UF & UB Values UF & UB Values UF & UB Values UF & UB Values -2 -3 -3 -3 -4 -3 -4 -4 -5

-5 -5 -4 -6 1977 1982 1987 1992 1997 2002 2007 1977 1982 1987 1992 1997 2002 2007 1977 1982 1987 1992 1997 2002 2007 1951 1958 1965 1972 1979 1986 1993 2000 2007

3 4 4 5 UF UF UF UF Saghez Urmia Takab Sahlan 3 3 4 UB UB UB UB 2 3 2 2

2 1 1 1

1 0 0 0 0 -1 -1 -1

-1 -2 -2 UF & UB ValuesUF UF & UB ValuesUF UF & UB ValuesUF UF & UB ValuesUF -2

-3 -3 -3 -2

-4 -4 -4

-3 -5 -5 -5 1959 1965 1971 1977 1983 1989 1995 2001 2007 1951 1958 1965 1972 1979 1986 1993 2000 2007 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007

5 5 5 3 UF UF UF UF Mirkooh Tazekand 4 Marz Sarv Abajalousofla 4 UB 4 UB UB UB 2

3 3 3

1 2 2 2

1 1 1 0

0 0 0

-1 -1 -1 -1 UF & UB Values UF & UB Values UF & UB Values UF & UB Values -2 -2 -2 -2

-3 -3 -3 -3 -4 -4 -4

-5 -5 -5 -4 1972 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007 1971 1977 1983 1989 1995 2001 2007 1977 1982 1987 1992 1997 2002 2007

3 3 4 3 UF UF UF UF Yalghoz Aghaj Ghasemlou Pol Anian Pey Ghaleh UB UB 3 UB UB 2 2 2 2

1 1 1 1

0 0 0 0 -1 -1

-1 -2 -1 UF & UB ValuesUF UF & UB ValuesUF UF & UB Values UF & UB ValuesUF -2

-3 -2 -2 -3 -4

-3 -4 -5 -3 1977 1982 1987 1992 1997 2002 2007 1977 1982 1987 1992 1997 2002 2007 1977 1982 1987 1992 1997 2002 2007 1977 1982 1987 1992 1997 2002 2007 4 3 3 3 UF UF UF UF Kamp Urmia Polsorkh Chehrigh Olia Mir Abad 3 UB UB UB UB 2 2 2 2

1 1 1 1

0 0 0 0 -1 -1 -1

-2 -1 UF & UB ValuesUF UF & UB ValuesUF UF & UB ValuesUF UF & UB ValuesUF -2 -2

-3 -2 -3 -3 -4

-5 -3 -4 -4 1977 1982 1987 1992 1997 2002 2007 1975 1979 1983 1987 1991 1995 1999 2003 2007 1977 1982 1987 1992 1997 2002 2007 1977 1982 1987 1992 1997 2002 2007 3 3 3 UF UF UF Sharafkhaneh Shanjan Sad Shahid Kazemi UB UB UB 2 2 2

1 1 1

0 0

-1 -1

-1 UF & UB ValuesUF UF & UB ValuesUF UF & UB ValuesUF -2 -2

-2 -3 -3

-4 -4 -3 1967 1971 1975 1979 1983 1987 1991 1995 1999 2003 2007 1971 1977 1983 1989 1995 2001 2007 1977 1983 1989 1995 2001 2007 Fig. 12 Annual temperature trends turning point detected by the SMK method in ULB significant trends (23 out of 25). Two general patterns can be began in the 1980s (at Tabriz, Sahlan, Mir Kooh, Tazekand, recognized for the basin: (i) a continuously increasing trend Takab, Marz Sarv, and Shanjan stations), and (ii) an other

Identification of trends in hydrological and climatic variables 459

3 4 3 UF UF UF Sahzab Saransar Akholeh UB 3 UB UB 2 2 2 1 1 1

0 0 0

-1 -1 -1 UF & UB Values UF & UB Values UF & UB ValuesUF -2 -2 -2 -3

-3 -4 -3 1972 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007

3 3 4 UF UF UF Chekan Ghabghablou Mir Abad UB UB 3 UB 2 2 2 1 1 1 0 0 0 -1 -1 -1 UF & UB Values UF & UB Values -2 UF & UB Values -2 -2 -3 -3

-4 -3 -4 1972 1977 1982 1987 1992 1997 2002 2007 1967 1972 1977 1982 1987 1992 1997 2002 2007 1967 1972 1977 1982 1987 1992 1997 2002 2007 3 3 5 UF UF UF Goyjali Aslan Kalhor 4 Tapik UB UB UB 2 2 3 2 1 1 1 0 0 0 -1 -1 -1 UF & UB Values UF & UB Values UF & UB Values -2 -3 -2 -2 -4 -3 -3 -5 1967 1972 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007 1967 1972 1977 1982 1987 1992 1997 2002 2007 4 UF Nazar Abad 3 UB

UF & UB Values -1

-2

-3 1971 1977 1983 1989 1995 2001 2007 Fig. 13 Annual precipitation trends turning point detected by the SMK method in ULB increasing trend was observable beginning in the 1990s (at be seen. For instance, Akholeh, Ghabghablou, and Kalhor Maragheh, Sarab, Mahabad, Abajalousofla, Chehrigh Olia, stations showed increasing trends starting from 1980s that Pol Anian, and so on stations). As shown in the figure, all crossed the upper bond of the critical value in the middle UF curves intersected the upper critical value lines (dashed 2000s. In contrast, Saransar, Tapik, and Nazar Abad sta- line), confirming the significant trends. In addition, when the tions showed decreases in precipitations in the 1970s that UF and UB curves intersect at a point in time, the were also significant in the 1990s. All of 10 stations show intersection point denotes the jumping time between jumping (or turning) points where the UB and UF curves 1990 and 2000 in the second pattern. For Saghez and cross. At Chekan station, an obvious jumping point also Urmia stations, the figures also show decreasing signifi- occurred at the beginning of the 1980s; the UF curve cant trend beginning in the 1990s and 1970s (where the increased continuously and crossed the upper critical line turning point is present), respectively. in 1992. Similarly, Fig. 13 shows the results of the SMK analysis Figure 14 shows the MK analysis of the streamflow sta- for stations with significant trends for precipitation (10 out tions with significant trends (14 out of 35). The results reveal of 35) in the basin. There is no dominant pattern for that the trends for the majority of stations are negative, but not precipitation as the both positive and negative trends can necessarily significant. The UF curves passed the lower

460 F. Fathian et al.

5 5 4 UF UF UF Vanyar 4 Akholeh Shishvan 4 UB UB 3 UB 3 3 2 2 2 1 1 1 0 0 0 -1 UF & UB Values UF & UB Values UF & UB Values -1 -1 -2 -2 -2 -3

-3 -4 -3 1947 1953 1959 1965 1971 1977 1983 1989 1995 2001 2007 1975 1983 1991 1999 2007 1975 1983 1991 1999 2007 4 4 4 UF UF UF Alavian Gheshlagh Amir Nezam Abad 3 UB 3 UB 3 UB

2 2 2

1 1 1

0 0 0 UF & UB Values UF & UB Values -1 -1 UF & UB Values -1

-2 -2 -2

-3 -3 -3 1972 1979 1986 1993 2000 2007 1975 1983 1991 1999 2007 1975 1983 1991 1999 2007 5 4 4 UF UF UF Tazekand Naghadeh Ghasemlou 4 UB 3 UB 3 UB

3 2 2 2 1 1 1 0 0 0 UF & UB Values UF & UB Values -1 UF & UB Values -1 -1

-2 -2 -2

-3 -3 -3 1975 1983 1991 1999 2007 1965 1972 1979 1986 1993 2000 2007 1972 1979 1986 1993 2000 2007

3 4 5 UF UF UF Chehrigh Olia Nazar Abad Tamr UB UB 4 UB 2 3 3 2 1 2

1 1 0 0 0 -1 -1 UF & UB Values UF & UB Values -1 UF & UB Values -2 -2 -2 -3

-3 -3 -4 1972 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007 1967 1972 1977 1982 1987 1992 1997 2002 2007 5 5 3 UF UF UF Yalghoz Aghaj Safakhaneh Yangjeh 4 UB 4 UB UB 2 3 3

2 2 1

1 1 0 0 0

-1 -1 -1 UF & UB Values UF & UB Values UF & UB Values

-2 -2 -2 -3 -3

-4 -4 -3 1972 1977 1982 1987 1992 1997 2002 2007 1972 1977 1982 1987 1992 1997 2002 2007 1975 1983 1991 1999 2007 3 3 UF UF Shirinkand Abajalousofla UB UB 2 2

1 1

0 0

-1 -1 UF & UB Values UF & UB Values

-2 -2

-3 -3 1972 1979 1986 1993 2000 2007 1972 1979 1986 1993 2000 2007 Fig. 14 Annual streamflow trends turning point detected by the SMK method in ULB

Identification of trends in hydrological and climatic variables 461

4 3 3 UF UF UF Pol Bahramlou Sari Ghamish Band Urmia UB abcUB UB 3 2 2 2 1 1 1 0 0 0 -1 UF & UB Values UF & UB Values -1 UF & UB Values -1 -2 -2

-3 -3 -2 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 1953 1959 1965 1971 1977 1983 1989 1995 2001 2007 1947 1953 1959 1965 1971 1977 1983 1989 1995 2001 2007 Fig. 15 Status of annual streamflow trend turning points and date of ULB dam exploitation for a Mahabad, b ShahidKazemi, and c Shahr Chai dams critical values at all stations, and all of stations except Nezam 3.5 Relationship between Urmia Lake level, streamflow, Abad had more than one intersection of the UF and UB curves and climate variables trends with many of the most recent intersections occurring in 1990s. Two general patterns can be also recognized for temporal Figure 16 shows time series of the level of Lake Urmia from trends of streamflow in the basin: (i) a decreasing trend began 1966 to 2008. A drastic decrease of more than 5 m in the level in the middle 1990s and the UF and UB curves intersect is seen in the last decade. The figure also shows that UF and between 1995 and 2000 (Vanyar, Akholeh, Ghasemlou, and UB values detect approximately the year of the trend change Nazar Abad stations), and (ii) a continuously decreasing sig- in the lake level time series as 1998. Any correlation between nificant trend began in the 1990s (Shishvan, Nezam Abad, the lake levels, the dates of exploitation of the main basin and Tazekand stations). dams, the detected years of trend change in temperature, and The SMK test was also applied in studies of Zhang et al. discharge time series has been added to the figure. As shown, (2005) and Zhao et al. (2010) for hydroclimatic variables in the significant change in the lake level is close to the detected China. The results of their studies confirmed the similar results year of trend changes in temperature and discharge (around of our study for climate variables. Yet in term of streamflow, 1998). the trend has increased after 1980s. Since streamflow is correlated with climate variables, we The trends and changing points of the streamflow were also attempted to investigate the linear relationship between annual compared with the dates of exploitation from the basin dams streamflow at each station and climate variables in the asso- (Fig. 15). According to the ministry of energy reports of Iran ciated climate stations using correlation analysis. In the same (2010), there are six important dams that are exploiting in context, it is expected that the lake levels are correlated with ULB, and three of them have gauging stations in downstream streamflow; thus, we performed correlation analysis between of their rivers. The figure shows the status of the river time the two variables. For this purpose, Pearson coefficient, r,was series for the first gauging stations after the dams (Mahabad, estimated (McCuen 2003). This analysis was performed for ShahidKazemi, and Shahr Chai dams). It is surprising that no 17 out of 35 streamflow stations that showing significant significant changes occurred in streamflow after the exploita- decreasing trends in ULB (Fig. 3c) in order to better explain tion dates. the probable causes of decline in the lake level. The climate

Fig. 16 Time series of the lake 1278 5 Water Lake Level UF level, UF, and UB of ULB from UB Critical value lines 4 1966 to 2008. Also, the dates of 1277 exploitation of the main basin 3 dams and the detected years of trend change in temperature and 1276 2 discharge time series have been 1 shown 1275 0

1274 -1 UF & UB values Water Lake Level (m) -2 1273 -3 Exploitation Mahabad dam Trend changes of discharge Exploitation of Shahr Chai dam Exploitation of Shahid Kazemi dam 1272 Trend changes of temperature -4 1966 1972 1978 1984 1990 1996 2002 2008 Time

462 F. Fathian et al.

Ta b l e 2 Correlation (r) of streamflow with precipitation, temperature, stations, which seem to be concentrated mostly in downstream and lake levels for the selected stations in ULB of subbasins and play a key role as inflow coming into the lake Station number Station name Precipitation Temperature Lake (Fig. 7c). Consequently, as the lake level declines, the exposed of streamflow of streamflow levels lakebed is left with a covering of salts and making a vast salty desert on more than 400 km2 of lost surface area (Golabian 3 Vanyar 0.26 −0.53c 0.40b 2011). 6 Akholeh 0.11 −0.64c 0.49c 9Yangjeh0.60c −0.46c 0.32a − b c 10 Shishvan 0.23 0.37 0.53 4 Conclusions 11 Alavian 0.46c −0.48c 0.37b c − c b 15 Gheshlagh Amir 0.56 0.48 0.43 This study documented monotonic trend behaviors in monthly c − b b 16 Shirinkand 0.53 0.41 0.38 and annual time series of temperature, precipitation, and − a c 18 Nezam Abad 0.13 0.31 0.54 streamflow in ULB using a number of non-parametric statis- b b a 20 Safakhaneh 0.36 −0.36 0.31 tical methods. Our results can be summarized as follows: 27 Tazekand 0.33a −0.49c 0.39b c c b 34 Naghadeh 0.67 −0.60 0.38 (i) Temperature has significantly increased throughout the c c c 35 Ghasemlou 0.51 −0.60 0.59 basin. Unlike temperature, trends in precipitation were b b b 43 Abajalousofla 0.41 −0.38 0.41 not basin-wide. There was no trend for about 75 % of the 46 ChehrighOlia 0.34a −0.58c 0.45b stations. Both decreasing and increasing trends were ob- 47 Nazar Abad 0.13 −0.51c 0.62c served in the remaining stations. The streamflow results 48 Tamr 0.40a −0.58c 0.34a were closer to the temperature trends, and about 80 % of 49 YalghozAghaj 0.68c −0.56c 0.53c them show a decreasing trend. (ii) Spatial distribution of significant trends in streamflow a Significant correlation at 90 % confidence levels indicated by bold numbers revealed that the downstream subbasins face decreasing b Significant correlation at 95 % confidence levels indicated by bold trends (a decrease in water flowing into the system) and numbers consequently have declined water level in Urmia Lake. c Significant correlation at 99 % confidence levels indicated by bold Therefore, it can be primarily attributed to climate change numbers and over-exploitation of the upper catchments. (iii) A comparison of estimated monthly and annual trends by data were also selected in the stations near the streamflow the non-parametric methods showed that they do not station. It can be noticed that defining the significance of r obey the same pattern in a given station. To check the values varies with the number of observations and selecting general homogeneity of trends, the Van Belle and the confidence bound, i.e., in case of 30 observations, the Hughes method was applied. This test confirmed the values outside the range of ±0.361 are defined as significant homogeneity of the trends in 76, 100, and 75 % for at 95 % confidence level. temperature, precipitation, and streamflow gauging Correlation coefficients (CC) between annual streamflow stations, respectively. and precipitation ranged from 0.11 to 0.68 (Table 2), and 12 (iv) Timing of trends in the study variables showed two out of 17 stations showed significant correlation, while all of regional patterns for temperature. One trend increased 17 temperature stations exhibited significant correlation (CC continually beginning in the 1980s and another began in ranged from −0.31 to −0.64), indicating that annual 1995. For streamflow, two general patterns can be also streamflow and temperature are well correlated. Comparably, discerned in the basin. One decreasing trend beginning precipitation is not completely associated with streamflow in the middle 1990s between 1995 and 2000 and the (Table 2), although the CC of most stations shows positive other began in 1990s, but not significant. However, values. Furthermore, according to spatial distribution plot changing points in these time series are mainly observ- (Fig. 3a, b), unlike streamflow decreasing trends, precipitation able in the mid-1990s. trends do not show sensible change over ULB. Furthermore, (v) There are three large dams in the basin. No correlation area showing decreasing trends in streamflow do not exhibit was observed from the SMK analysis between the ex- decreasing trend in precipitation. The presence of high corre- ploitation dates of dams and the detected trends or the lations at annual scale is in agreements with similar studies in changing points of the annual time series of streamflow. different basins (Masih et al. 2010;Zhaoetal.2010). In the (vi) In general, this research showed that there are two main case of lake levels, CC with streamflow showed significant reasons for the decline of the lake water level. One is correlation ranging from 0.32 to 0.62 (Table 2). This may be related to the increase in temperature and the associated concluded from the geographical distribution of streamflow increases in evaporation and evapotranspiration, and the

Identification of trends in hydrological and climatic variables 463

other is caused by over-exploitation in upstream. A Fan X, Wang M (2011) Change trends of air temperature and precipitation – – quantitative analysis of these is under investigation by over Shanxi Province, China. Theor Appl Climatol 103(3 4):519 531. doi:10.1007/s00704-010-0319-2 the authors. Feidas H, Makrogiannis T, Bora-Senta E (2004) Trend analysis of air (vii) A comparison of precipitation trends in ULB with stud- temperature time series in Greece and their relationship with circu- ies in Turkey (Partal and Kahya 2006), which is also lation using surface and satellite data: 1955–2001. Theor Appl – affected by the Mediterranean atmospheric system, re- Climatol 79:185 208. doi:10.1007/s00704-004-0064-5 Ghahraman B, Taghvaeian S (2008) Investigation of annual rainfall vealed similar results with the exception of streamflow. trends in Iran. J Agric Sci Technol 10:93–97 For instance, Kahya and Kalaycı (2004) reported no Githui F. W (2009) Assessing the impacts of environmental change on the trend for the eastern rivers of Turkey, which are adjacent hydrology of the Nzoia catchment, in the Lake Victoria Basin. to the western boundaries of ULB. This fact confirms Dissertation, Vrije University Brussel Golabian H (2011) Urumia Lake: hydro-ecological stabilization and the susceptibility of basin hydrology to significant hu- permanence. In: Macro-engineering seawater in unique environ- man impact. ments. Springer, Berlin, pp 365–397 (viii) Generally, the results of trend analysis show a relation- Groisman PY, Knight RW, Karl TR (2001) Heavy precipitation and high ship between observed streamflow trends and changes in stream flow in the contiguous United States: trends in the twentieth century. Bull Am Meteorol Soc 82(2):219–246 climatic variables (temperature and precipitation). These Hassanzadeh E, Zarghami M, Hassanzadeh Y (2012) Determining the may not completely explain the variability in streamflow main factors in declining the Urmia Lake level by using system caused by the changes in other catchment properties. dynamics modeling. Water Resour Manag 26:129–145. doi:10. More importantly, this study can provide a base for 1007/s11269-011-9909-8 Huth R, Pokorná L (2004) Parametric versus non-parametric estimates of additional research that estimates the effects of human climatic trends. Theor Appl Climatol 77:107–112. doi:10.1007/ activities on the hydrological processes. For instance, s00704-003-0026-3 land use change can also significantly influence the IPCC (2001) The scientific basis of climate change, contribution of annual and seasonal streamflow, although the effect of working I to the third assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge climate is the dominant factor in annual streamflow. Jahanbakhsh-Asl S, Ghavidel Rahimi Y (2003) Modeling of precipitation Overall, it is concluded that this study provides a useful trend and drought prediction in Urmia Lake basin. Journal of Social overview of hydroclimatic time series trends in ULB for and Human Sciences (in Persian) further research. Jalili Sh (2010) Spectral analysis of Lake Urmia level time series and impact of climate and hydrological variables on it. Dissertation, Tarbiat Modares University, Iran Jhajharia D, Dinpashoh Y, Kahya E, Singh VP, Fakheri-Fard A (2012) Trends in reference evapotranspiration in the humid region of north- east India. Hydrol Process 26(3):421–435 References Kahya E, Kalaycı S (2004) Trend analysis of streamflow in Turkey. 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