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Journal of Arid Land  2020, Vol. 12 Issue (6): 964-983    DOI: 10.1007/s40333-020-0100-z     CSTR: 32276.14.s40333-020-0100-z
Research article     
Influence of non-stationarity and auto-correlation of climatic records on spatio-temporal trend and seasonality analysis in a region with prevailing arid and semi-arid climate, Iran
Mahsa MIRDASHTVAN*(), Mohsen MOHSENI SARAVI
Department of Range and Watershed Management, Faculty of Natural Resources, College of Agriculture and Natural Resources, University of Tehran, Karaj 3158777871, Iran
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Abstract  

Trend and stationarity analysis of climatic variables are essential for understanding climate variability and provide useful information about the vulnerability and future changes, especially in arid and semi-arid regions. In this study, various climatic zones of Iran were investigated to assess the relationship between the trend and the stationarity of the climatic variables. The Mann-Kendall test was considered to identify the trend, while the trend free pre-whitening approach was applied for eliminating serial correlation from the time-series. Meanwhile, time series stationarity was tested by Dickey-Fuller and Kwiatkowski-Phillips-Schmidt-Shin tests. The results indicated an increasing trend for mean air temperature series at most of the stations over various climatic zones, however, after eliminating the serial correlation factor, this increasing trend changes to an insignificant decreasing trend at a 95% confidence level. The seasonal mean air temperature trend suggested a significant increase in the majority of the stations. The mean air temperature increased more in northwest towards central parts of Iran that mostly located in arid and semi-arid climatic zones. Precipitation trend reveals an insignificant downward trend in most of the series over various climatic zones; furthermore, most of the stations follow a decreasing trend for seasonal precipitation. Furthermore, spatial patterns of trend and seasonality of precipitation and mean air temperature showed that the northwest parts of Iran and margin areas of the Caspian Sea are more vulnerable to the changing climate with respect to the precipitation shortfalls and warming. Stationarity analysis indicated that the stationarity of climatic series influences on their trend; so that, the series which have significant trends are not static. The findings of this investigation can help planners and policy-makers in various fields related to climatic issues, implementing better management and planning strategies to adapt to climate change and variability over Iran.



Key wordsclimate change      trend analysis      stationarity tests      serial correlation      seasonality      arid and semi-arid regions     
Received: 23 August 2019      Published: 10 November 2020
Corresponding Authors:
About author: *Mahsa MIRDASHTVAN (E-mail: mirdashtevan@ut.ac.ir)
Cite this article:

Mahsa MIRDASHTVAN, Mohsen MOHSENI SARAVI. Influence of non-stationarity and auto-correlation of climatic records on spatio-temporal trend and seasonality analysis in a region with prevailing arid and semi-arid climate, Iran. Journal of Arid Land, 2020, 12(6): 964-983.

URL:

http://jal.xjegi.com/10.1007/s40333-020-0100-z     OR     http://jal.xjegi.com/Y2020/V12/I6/964

Fig. 1 Location of the synoptic stations in different climatic zones of Iran
Climatic zone Drought coefficient Number of stations selected
Very humid type 1 >55.0 4
Very humid type 2 35.0-54.9 1
Humid 28.0-34.9 1
Semi-humid 24.0-27.9 0
Mediterranean 20.0-23.9 6
Semi-arid 10.0-19.9 27
Arid 5.0-9.9 16
Extremely arid <4.9 18
Table 1 De-Marton drought coefficient range
Fig. 2 Procedures and steps of the study
Station Longitude Latitude Altitude (m) Climatic class
Arak 49°46′E 34°06′N 1708.0 Semi-arid
Ardebil 48°17′E 38°15′N 1332.0 Mediterranean
Oroomiyyeh 45°03′E 37°40′N 1328.0 Semi-arid
Esfahan 51°40′E 32°37′N 1550.4 Extremely arid
Aqajari 49°40′E 30°46′E 27.0 Arid
Omidiyyeh 49°39′E 30°46′N 34.9 Arid
Ahwaz 48°40′E 31°20′N 22.5 Arid
Iranshahr 60°42′E 27°12′N 591.1 Extremely arid
Ilam 46°26′E 33°38′N 1337.0 Mediterranean
Abadan 48°15′E 30°22′N 6.6 Semi-arid
Abadeh 52°40′E 31°11′N 2030.0 Arid
Abali 51°53′E 35°45′N 2465.2 Semi-arid
Babolsar 52°39′E 36°43′N -21.0 Humid
Bojnourd 57°16′E 37°28′N 1112.0 Semi-arid
Bam 58°21′E 29°06′N 1066.9 Extremely arid
Bandar Anzali 49°27′E 37°29′N -23.6 Very humid
Bandar Abbas 56°22′E 27°13′N 9.8 Extremely arid
Bandar Lengeh 54°50′E 26°32′N 22.7 Extremely arid
Boushehr (Coastal) 50°49′E 28°54′N 8.4 Arid
Birjand 59°12′E 32°52′N 1491.0 Arid
Moqan 47°55′E 39°39′N 31.9 Semi-arid
Tabriz 46°17′E 38°05′N 1361.0 Semi-arid
Torbat Heidariyyeh 59°13′E 35°16′N 1450.8 Semi-arid
Tehran 51°19′E 35°41′N 1190.8 Arid
Jask 57°46′E 25°38′N 5.2 Extremely arid
Boumousa Island 54°50′E 25°50′N 6.6 Extremely arid
siri Island 54°29′E 25°53′N 4.4 Extremely arid
kish Island 53°59′E 26°30′N 30.0 Extremely arid
Jolfa 45°40′E 38°45′N 736.2 Mediterranean
Chabahar 60°37′E 25°17′N 8.0 Extremely arid
Khorramabad 48°17′E 33°26′N 1147.8 Semi-arid
Khoy 44°58′E 38°33′N 1103.0 Semi-arid
Dezfoul 48°23′E 32°24′N 143.0 Arid
Doushan Tappeh 51°20′E 33°42′N 1209.2 Semi-arid
Dogonbadan 50°49′E 30°20′N 726.0 Semi-arid
Ramsar 50°40′E 36°54′N -20.0 Very humid
Rasht 49-37′E 37-19′N -8.6 Very humid
Zabol 61°29′E 31°02′N 489.2 Extremely arid
Zahedan 60°53′E 29°28′N 1370.0 Extremely arid
Zanjan 48°29′E 36°41′N 1663.0 Semi-arid
Sabzevar 57°39′E 36°12′N 972.0 Arid
Sarakhs 61°10′E 36°32′N 235.0 Arid
Saqqez 46°16′E 36°15′N 1522.8 Mediterranean
Semnan 53°25′E 35°35′N 1127.0 Arid
Sanandaj 47°00′E 35°20′N 1373.4 Mediterranean
To be continued
Continued
Station Longitude Latitude Altitude (m) Climatic class
Sahand 46°07′E 37°56′N 1641.0 Semi-arid
Sirjan 55°41′E 29°28′N 1739.4 Extremely arid
Shahroud 54°57′E 36°25′N 1349.1 Arid
Esfahan (East) 51°52′E 32°40′N 1543.0 Extremely arid
Shahrekord 50°21′E 32°17′N 2048.9 Very humid
shiraz 52°36′E 29°32′N 1484.0 Semi-arid
Tabas 56°55′E 33°36′N 711.0 Extremely arid
Ferdows 58°10′E 34°01′N 1293.0 Arid
Fasa 53°41′E 28°58′N 1288.3 Semi-arid
Qazvin 50°03′E 36°15′N 1279.2 Semi-arid
Qom 50°51′E 34°42′N 877.4 Arid
Qouchan 58°30′E 37°04′N 1287.0 Semi-arid
Kashan 51°27′E 33°59′N 982.3 Extremely arid
Kerman 56°58′E 30°15′N 1753.8 Arid
Karaj 50°54′E 35°55′N 1312.5 Semi-arid
Kermanshah 47°09′E 34°21′N 1318.6 Semi-arid
Konarak 60°22′E 25°26′N 12.0 Extremely arid
Gorgan 54°24′E 36°54′N 0.0 Mediterranean
Maku 44°26′E 39°20′N 1411.3 Semi-arid
Maraqeh 46°16′E 37°24′N 1477.7 Semi-arid
Masjed Soleiman 49°17′E 31°56′N 320.5 Semi-arid
Mashhad 59°38′E 36°16′N 999.2 Semi-arid
Mahabad 45°43′E 36°45′N 1351.8 Semi-arid
Minab 57°05′E 27°06′N 29.6 Arid
Nowshahr 51°30′E 36°39′N -20.9 Very humid
Hamedan 48°32′E 34°52′N 1741.5 Semi-arid
Hamedan (Nowjeh) 48°43′E 35°12′N 1679.7 Semi-arid
Yazd 54°17′E 31°54′N 1237.2 Extremely arid
Table S1 Characteristics of the selected synoptic stations over Iran
Station Mean air temperature Precipitation Station Mean air temperature Precipitation
Arak 0.835 0.394 Zabol 0.845 0.281
Ardebil 0.812 0.149 Zahedan 0.840 0.216
Oroomiyyeh 0.843 0.283 Zanjan 0.840 0.282
Esfahan 0.846 0.307 Sabzevar 0.842 0.337
Aqajari 0.852 0.335 Sarakhs 0.831 0.380
Omidiyyeh 0.844 0.332 Saqqez 0.838 0.333
Ahwaz 0.853 0.295 Semnan 0.845 0.222
Iranshahr 0.846 0.117 Sanandaj 0.847 0.388
Ilam 0.852 0.427 Sahand 0.832 0.231
Abadan 0.851 0.288 Sirjan 0.850 0.220
Abadeh 0.847 0.280 Shahroud 0.840 0.312
Abali 0.844 0.389 Esfahan (East) 0.850 0.280
Babolsar 0.844 0.359 Shahrekord 0.843 0.398
Bojnourd 0.837 0.304 Shiraz 0.852 0.337
Bam 0.838 0.189 Tabas 0.847 0.297
Bandar Anzali 0.841 0.353 Ferdows 0.842 0.380
Bandar Abbas 0.845 0.150 Fasa 0.854 0.283
Bandar Lengeh 0.846 0.177 Qazvin 0.841 0.357
Boushehr (Coastal) 0.847 0.395 Qom 0.847 0.346
Birjand 0.841 0.444 Qouchan 0.834 0.422
Moqan 0.843 0.047 Kashan 0.845 0.228
Tabriz 0.842 0.284 Kerman 0.846 0.238
Torbat Heidariyyeh 0.842 0.383 Karaj 0.839 0.330
Tehran 0.842 0.362 Kermanshah 0.848 0.415
Jask 0.832 0.123 Konarak 0.824 0.129
Boumousa Island 0.852 0.164 Gorgan 0.842 0.149
Siri Island 0.842 0.195 Maku 0.833 0.290
kish Island 0.849 0.228 Maraqeh 0.843 0.323
Jolfa 0.836 0.275 Masjed Soleiman 0.851 0.294
Chabahar 0.817 0.085 Mashhad 0.836 0.378
Khorramabad 0.849 0.423 Mahabad 0.840 0.366
Khoy 0.832 0.279 Minab 0.843 0.194
Dezfoul 0.849 0.281 Nowshahr 0.844 0.324
Doushan Tappeh 0.840 0.378 Hamedan 0.838 0.383
Dogonbadan 0.854 0.348 Hamedan (Nowjeh) 0.837 0.357
Ramsar 0.844 0.296 Yazd 0.845 0.241
Rasht 0.834 0.316
Table 2 Serial correlation coefficient of mean air temperature and precipitation time series
Fig. 3 Slopes of annual mean air temperature trend over Iran from 1985 to 2014
Fig. 4 Slopes of seasonal mean air temperature °C trend over Iran from 1985 to 2014
Fig. 5 Slopes of annual precipitation trend over Iran from 1985 to 2014
Fig. 6 Slopes of seasonal precipitation trend (mm) over Iran from 1985 to 2014
Station DF KPSS
Tau P-value Hypothesis Eta P-value Hypothesis
Abadan -19.022 0.0001> Ha 0.037 0.776 H0
Abadeh -18.483 0.0001> Ha 0.022 0.970 H0
Abali -18.835 0.0001> Ha 0.018 0.991 H0
Boumousa Island -19.379 0.0001> Ha 0.069 0.358 H0
Ahwaz -19.404 0.0001> Ha 0.022 0.969 H0
Arak -18.579 0.0001> Ha 0.022 0.969 H0
Ardebil -18.735 0.0001> Ha 0.069 0.355 H0
Babolsar -19.427 0.0001> Ha 0.013 0.999 H0
Bam -19.064 0.0001> Ha 0.066 0.384 H0
Bandar Abbas -19.451 0.0001> Ha 0.073 0.325 H0
Bandar Lengeh -19.388 0.0001> Ha 0.098 0.172 H0
Bandar Anzali -19.069 0.0001> Ha 0.012 1.000 H0
Birjand -19.094 0.0001> Ha 0.014 0.998 H0
Bojnourd -18.978 0.0001> Ha 0.044 0.657 H0
Boushehr (Coastal) -18.789 0.0001> Ha 0.073 0.325 H0
Chabahar -17.327 0.0001> Ha 0.058 0.476 H0
Dezfoul -19.041 0.0001> Ha 0.081 0.264 H0
Doushan Tappeh -18.705 0.0001> Ha 0.036 0.791 H0
Dogonbadan -18.544 0.0001> Ha 0.026 0.935 H0
Esfahan (East) -18.715 0.0001> Ha 0.020 0.979 H0
Esfahan -18.764 0.0001> Ha 0.013 0.999 H0
Fasa -18.661 0.0001> Ha 0.028 0.900 H0
Ferdows -19.457 0.0001> Ha 0.010 1.000 H0
Qouchan -18.911 0.0001> Ha 0.016 0.995 H0
Gorgan -18.954 0.0001> Ha 0.04 0.731 H0
Hamedan -18.628 0.0001> Ha 0.015 0.997 H0
Hamedan (Nowjeh) -18.768 0.0001> Ha 0.030 0.878 H0
Ilam -18.881 0.0001> Ha 0.047 0.620 H0
Iranshahr -18.985 0.0001> Ha 0.082 0.254 H0
Jask -19.070 0.0001> Ha 0.050 0.567 H0
Jolfa -18.651 0.0001> Ha 0.063 0.410 H0
Karaj -18.889 0.0001> Ha 0.021 0.973 H0
Kashan -19.426 0.0001> Ha 0.018 0.990 H0
Kerman -19.157 0.0001> Ha 0.039 0.745 H0
Kermanshah -18.574 0.0001> Ha 0.013 0.999 H0
Khorramabad -19.341 0.0001> Ha 0.021 0.974 H0
Khoy -18.412 0.0001> Ha 0.043 0.686 H0
Station DF KPSS
Tau P-value Hypothesis Eta P-value Hypothesis
Kish Island -19.298 0.0001> Ha 0.080 0.270 H0
Konarak -18.964 0.0001> Ha 0.047 0.611 H0
Mahabad -19.249 0.0001> Ha 0.027 0.914 H0
Maku -18.985 0.0001> Ha 0.073 0.326 H0
Maraqeh -19.104 0.0001> Ha 0.031 0.860 H0
Mashhad -19.948 0.0001> Ha 0.013 0.999 H0
Masjed Soleiman -19.406 0.0001> Ha 0.019 0.987 H0
Minab -19.460 0.0001> Ha 0.050 0.575 H0
Nowshahr -19.122 0.0001> Ha 0.010 1.000 H0
Aqajari -18.919 0.0001> Ha 0.041 0.706 H0
Omidiyyeh -18.648 0.0001> Ha 0.042 0.700 H0
Oroomiyyeh -18.620 0.0001> Ha 0.058 0.470 H0
Moqan -18.018 0.0001> Ha 0.040 0.729 H0
Qazvin -18.018 0.0001> Ha 0.015 0.997 H0
Qom -18.838 0.0001> Ha 0.060 0.448 H0
Ramsar -18.329 0.0001> Ha 0.018 0.991 H0
Rasht -18.842 0.0001> Ha 0.016 0.996 H0
Sabzevar -19.386 0.0001> Ha 0.012 1.000 H0
Sahand -17.720 0.0001> Ha 0.136 0.069 H0
Sanandaj -18.914 0.0001> Ha 0.018 0.991 H0
Saqqez -19.602 0.0001> Ha 0.029 0.894 H0
Sarakhs -19.714 0.0001> Ha 0.023 0.957 H0
Semnan -19.254 0.0001> Ha 0.028 0.906 H0
Shahrekord -18.823 0.0001> Ha 0.013 0.999 H0
Shahroud -19.415 0.0001> Ha 0.030 0.879 H0
Shiraz -18.677 0.0001> Ha 0.029 0.898 H0
Siri Island -19.515 0.0001> Ha 0.093 0.190 H0
Sirjan -19.157 0.0001> Ha 0.067 0.373 H0
Tabas -19.332 0.0001> Ha 0.014 0.998 H0
Tabriz -18.502 0.0001> Ha 0.019 0.984 H0
Tehran -18.997 0.0001> Ha 0.026 0.929 H0
Torbat Heidariyyeh -19.854 0.0001> Ha 0.042 0.699 H0
Yazd -18.902 0.0001> Ha 0.011 1.000 H0
Zabol -19.591 0.0001> Ha 0.063 0.418 H0
Zahedan -19.251 0.0001> Ha 0.057 0.486 H0
Zanjan -18.679 0.0001> Ha 0.027 0.920 H0
Table 2 Stationarity results of precipitation series at 95% confidence level
Station DF KPSS
Tau P-value Hypothesis Eta P-value Hypothesis
Abadan -6.728 0.0001> Ha 0.013 0.999 H0
Abadeh -5.697 0.0001> Ha 0.022 0.968 H0
Abali -8.147 0.0001> Ha 0.016 0.995 H0
Boumousa Island -6.882 0.0001> Ha 0.013 0.999 H0
Ahwaz -6.487 0.0001> Ha 0.013 0.999 H0
Arak -10.190 0.0001> Ha 0.011 1.000 H0
Ardebil -10.704 0.0001> Ha 0.013 0.999 H0
Babolsar -7.903 0.0001> Ha 0.012 1.000 H0
Bam -8.180 0.0001> Ha 0.014 0.999 H0
Bandar Abbas -7.134 0.0001> Ha 0.013 0.999 H0
Bandar Lengeh -7.256 0.0001> Ha 0.017 0.992 H0
Bandar Anzali -8.273 0.0001> Ha 0.012 1.000 H0
Birjand -8.070 0.0001> Ha 0.013 0.999 H0
Bojnourd -8.572 0.0001> Ha 0.013 0.999 H0
Boushehr (Coastal) -7.164 0.0001> Ha 0.012 1.000 H0
Chabahar -8.708 0.0001> Ha 0.012 1.000 H0
Dezfoul -6.949 0.0001> Ha 0.119 0.101 H0
Doushan Tappeh -7.880 0.0001> Ha 0.041 0.714 H0
Dogonbadan -8.050 0.0001> Ha 0.017 0.993 H0
Esfahan (East) -6.944 0.0001> Ha 0.013 0.999 H0
Esfahan -7.621 0.0001> Ha 0.013 0.999 H0
Fasa -9.051 0.0001> Ha 0.011 1.000 H0
Ferdows -8.107 0.0001> Ha 0.014 0.998 H0
Qouchan -8.804 0.0001> Ha 0.012 1.000 H0
Gorgan -8.063 0.0001> Ha 0.013 0.999 H0
Hamedan -8.232 0.0001> Ha 0.011 1.000 H0
Station DF KPSS
Tau P-value Tau P-value Tau P-value
Hamedan (Nowjeh) -8.160 0.0001> Ha 0.020 0.979 H0
Ilam -7.377 0.0001> Ha 0.016 0.995 H0
Iranshahr -7.172 0.0001> Ha 0.015 0.997 H0
Jask -8.120 0.0001> Ha 0.013 0.999 H0
Jolfa -8.371 0.0001> Ha 0.012 1.000 H0
Karaj -8.333 0.0001> Ha 0.015 0.998 H0
Kashan -7.470 0.0001> Ha 0.013 0.999 H0
Kerman -7.510 0.0001> Ha 0.013 0.999 H0
Kermanshah -7.201 0.0001> Ha 0.012 1.000 H0
Khorramabad -6.840 0.0001> Ha 0.013 0.999 H0
Khoy -8.877 0.0001> Ha 0.012 1.000 H0
Kish Island -7.112 0.0001> Ha 0.013 0.999 Ha
Konarak -8.865 0.0001> Ha 0.266 0.003 H0
Mahabad -8.185 0.0001> Ha 0.013 0.999 H0
Maku -8.773 0.0001> Ha 0.012 1.000 H0
Maraqeh -7.876 0.0001> Ha 0.012 0.999 H0
Mashhad -8.785 0.0001> Ha 0.012 1.000 H0
Masjed Soleiman -7.454 0.0001> Ha 0.013 0.999 H0
Minab -7.545 0.0001> Ha 0.014 0.998 H0
Nowshahr -7.948 0.0001> Ha 0.014 0.999 H0
Aqajari -6.793 0.0001> Ha 0.014 0.999 H0
Omidiyyeh -6.810 0.0001> Ha 0.099 0.166 H0
Oroomiyyeh -7.718 0.0001> Ha 0.013 0.999 H0
Moqan -7.923 0.0001> Ha 0.013 0.999 H0
Qazvin -7.992 0.0001> Ha 0.012 0.999 H0
Qom -7.28 0.0001> Ha 0.016 0.995 H0
Ramsar -7.945 0.0001> Ha 0.012 1.000 H0
Rasht -9.003 0.0001> Ha 0.012 1.000 H0
Sabzevar -7.932 0.0001> Ha 0.012 1.000 H0
Sahand -8.888 0.0001> Ha 0.044 0.660 H0
Sanandaj -7.320 0.0001> Ha 0.012 1.000 H0
Saqqez -8.494 0.0001> Ha 0.017 0.992 H0
Sarakhs -9.222 0.0001> Ha 0.011 1.000 H0
Semnan -7.537 0.0001> Ha 0.012 0.999 H0
Shahrekord -7.714 0.0001> Ha 0.011 1.000 H0
Shahroud -8.102 0.0001> Ha 0.013 0.999 H0
Shiraz -8.998 0.0001> Ha 0.011 1.000 H0
Siri Island -12.748 0.0001> Ha 0.039 0.735 H0
Sirjan -7.032 0.0001> Ha 0.014 0.998 H0
Tabas -7.302 0.0001> Ha 0.013 0.999 H0
Tabriz -7.897 0.0001> Ha 0.012 0.999 H0
Tehran -7.929 0.0001> Ha 0.013 0.999 H0
Torbat Heidariyyeh -8.057 0.0001> Ha 0.013 0.999 H0
Yazd -7.599 0.0001> Ha 0.012 1.000 H0
Zabol -7.558 0.0001> Ha 0.016 0.995 H0
Zahedan -8.005 0.0001> Ha 0.015 0.997 H0
Zanjan -8.153 0.0001> Ha 0.012 0.999 H0
Table 4 Stationarity results of mean air temperature series at 95% confidence level
[1]   Abbaspour M, Sabetraftar A . 2005. Review of cycles and indices of drought and their effect on water resources, ecological, biological, agricultural, social and economical issues in Iran. International Journal of Environmental Studies, 62(6):709-724.
[2]   Ahmad I, Tang D, Wang T, et al. 2015. Precipitation trends over time using Mann-Kendall and Spearman’s rho tests in Swat River Basin, Pakistan. Advances in Meteorology, 2015(2):1-15.
[3]   Alijani B. 1995. Climate of Iran. Tehran: Piame Noor University, 21-35.
[4]   Amiri M, Eslamian S. 2010. Investigation of climate change in Iran. Journal of Environmental Sciences and Technology, 3:208-216.
[5]   Aziz O I A, Burn D H. 2006. Trends and variability in the hydrological regime of the Mackenzie River Basin. Journal of Hydrology, 319(1-4):282-294.
[6]   Blain G C. 2015. The influence of nonlinear trends on the power of the trend-free pre-whitening approach. Acta Scientiarum Agronomy, 37(1):21-28.
[7]   Brockwell P J, Davis R A. 1991. Time Series: Theory and Methods. New York: Springer Science and Business Media.
[8]   Burn D H, Elnur M A H. 2002. Detection of hydrologic trends and variability. Journal of Hydrology, 255(1-4):107-122.
doi: 10.1016/S0022-1694(01)00514-5
[9]   Burn D H, Cunderlik J M, Pietroniro A. 2004. Hydrological trends and variability in the Liard River basin. Hydrological Sciences Journal, 49(1):53-67.
doi: 10.1623/hysj.49.1.53.53994
[10]   Delju A, Ceylan A, Piguet E, et al. 2013. Observed climate variability and change in Urmia Lake Basin, Iran. Theoretical and Applied Climatology, 111:285-296.
[11]   Duan W, He B, Sahu N, et al. 2017. Spatiotemporal variability of Hokkaido's seasonal precipitation in recent decades and connection to water vapour flux. International Journal of Climatology, 37(9):3660-3673.
[12]   Duan W, Hanasaki N, Shiogama H, et al. 2019. Evaluation and future projection of Chinese precipitation extremes using large ensemble high-resolution climate simulations. Journal of Climate, 32(8):2169-2183.
[13]   El-Nesr M N, Abu-Zreig M M, Alazba A A. 2010. Temperature trends and distribution in the Arabian Peninsula. American Journal of Environmental Sciences, 6(2):191-203.
doi: 10.3844/ajessp.2010.191.203
[14]   Fathian F, Morid S, Kahya E. 2015. Identification of trends in hydrological and climatic variables in Urmia Lake basin, Iran. Theoretical and Applied Climatology, 119:443-464.
doi: 10.1007/s00704-014-1120-4
[15]   Feizi V, Mollashahi M, Farajzadeh M, et al. 2014. Spatial and temporal trend analysis of temperature and precipitation in Iran. Ecopersia, 2:727-742.
[16]   Field C B, Barros V R. 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Working Group II Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.
[17]   Gocic M, Trajkovic S. 2013. Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia. Global and Planetary Change, 100:172-182.
doi: 10.1016/j.gloplacha.2012.10.014
[18]   Golian S, Mazdiyasni O, AghaKouchak A. 2015. Trends in meteorological and agricultural droughts in Iran. Theoretical and Applied Climatology, 119:679-688.
doi: 10.1007/s00704-014-1139-6
[19]   Hamed K. 2009. Enhancing the effectiveness of prewhitening in trend analysis of hydrologic data. Journal of Hydrology, 368(1-4):143-155.
doi: 10.1016/j.jhydrol.2009.01.040
[20]   Hirsch R M, Alexander R B, Smith R A. 1991. Selection of methods for the detection and estimation of trends in water quality. Water Resources Research, 27(5):803-813.
doi: 10.1029/91WR00259
[21]   Hirsch R M, Slack J R, Smith R A. 1982. Techniques of trend analysis for monthly water quality data. Water Resources Research, 18(1):107-121.
doi: 10.1029/WR018i001p00107
[22]   Hosseinzadeh T P. 2014. Iranian rainfall series analysis by means of nonparametric tests. Theoretical and applied climatology, 116:597-607.
doi: 10.1007/s00704-013-0981-2
[23]   Houghton J T, Albritton D L, Meira F, et al. 2001. Technical summary of working group 1. Cambridge: Cambridge University Press.
[24]   Kahya E, Kalaycı S. 2004. Trend analysis of streamflow in Turkey. Journal of Hydrology, 289(1-4):128-144.
doi: 10.1016/j.jhydrol.2003.11.006
[25]   Kendall M. 1975. Multivariate analysis. Charles Griffin.
[26]   Kumar S, Merwade V, Kam J, et al. 2009. Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology, 374(1-2):171-183.
doi: 10.1016/j.jhydrol.2009.06.012
[27]   Kwiatkowski D, Phillips P C, Schmidt P, et al. 1992. Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1-3):159-178.
doi: 10.1016/0304-4076(92)90104-Y
[28]   Libanda B, Zheng M, Ngonga C. 2019. Spatial and temporal patterns of drought in Zambia. Journal of Arid Land, 11(2):180-191.
doi: 10.1007/s40333-019-0053-2
[29]   Mann H B. 1945. Nonparametric tests against trend. Econometrica: Journal of the Econometric Society, 13:245-259.
doi: 10.2307/1907187
[30]   Masih I, Uhlenbrook S, Maskey S, et al. 2011. Streamflow trends and climate linkages in the Zagros Mountains, Iran. Climatic Change, 104:317-338.
doi: 10.1007/s10584-009-9793-x
[31]   Modarres R, da Silva V. 2007. Rainfall trends in arid and semi-arid regions of Iran. Journal of Arid Environments, 70(2):344-355.
doi: 10.1016/j.jaridenv.2006.12.024
[32]   Parey S, Hoang T, Dacunha-Castelle D. 2019. Future high-temperature extremes and stationarity. Natural Hazards, 98:1115-1134.
[33]   Peel M C, Finlayson B L, McMahon T A. 2007. Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences Discussions, 4:439-473.
doi: 10.5194/hessd-4-439-2007
[34]   Raziei T, Arasteh P D, Saghafian B. 2005a. Annual rainfall trend in arid and semi-arid regions of central and eastern Iran. Water and Wastewater, 54:73-81.
[35]   Raziei T, Arasteh P D, Saghafian B. 2005b. Annual rainfall trend in arid and semi-arid regions of Iran. In: ICID 21st European regional conference, 15-19.
[36]   Sahoo D, Smith P. 2009. Hydroclimatic trend detection in a rapidly urbanizing semi-arid and coastal river basin. Journal of Hydrology, 367(3-4):217-227.
doi: 10.1016/j.jhydrol.2009.01.014
[37]   Samadi S, Carbone G J, Mahdavi M, et al. 2013. Statistical downscaling of river runoff in a semi-arid catchment. Water Resources Management, 27:117-136.
doi: 10.1007/s11269-012-0170-6
[38]   Shadmani M, Marofi S, Roknian M. 2012. Trend analysis in reference evapotranspiration using Mann-Kendall and Spearman's Rho tests in arid regions of Iran. Water Resources Management, 26:211-224.
doi: 10.1007/s11269-011-9913-z
[39]   Shao Q, Li M. 2011. A new trend analysis for seasonal time series with consideration of data dependence. Journal of Hydrology, 396(1-2):104-112.
doi: 10.1016/j.jhydrol.2010.10.040
[40]   Solomon S, Qing D, Manning M, et al. 2007. Climate change 2007: The Physical Science Basis. Working group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.
[41]   Some'e B S, Ezani A, Tabari H. 2012. Spatiotemporal trends and change point of precipitation in Iran. Atmospheric Research, 113:1-12.
doi: 10.1016/j.atmosres.2012.04.016
[42]   Stocker T F, Qin D, Plattner G-K, et al. 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 1535.
[43]   Sun F, Roderick M L, Farquhar G D. 2018. Rainfall statistics, stationarity, and climate change. Proceedings of the National Academy of Sciences, 115(10):2305-2310.
[44]   Tabari H, Marofi S. 2011. Changes of pan evaporation in the west of Iran. Water Resources Management, 25:97-111.
doi: 10.1007/s11269-010-9689-6
[45]   Tabari H, Marofi S, Aeini A, et al. 2011. Trend analysis of reference evapotranspiration in the western half of Iran. Agricultural and Forest Meteorology, 151(2):128-136.
doi: 10.1016/j.agrformet.2010.09.009
[46]   Toller M, Santos T, Kern R. 2019. SAZED: parameter-free domain-agnostic season length estimation in time series data. Data Mining and Knowledge Discovery, 33:1775-1798.
doi: 10.1007/s10618-019-00645-z
[47]   Um M-J, Heo J-H, Markus M, et al. 2018. Performance evaluation of four statistical tests for trend and non-stationarity and assessment of observed and projected annual maximum precipitation series in Major United States cities. Water Resources Management, 32:913-933.
doi: 10.1007/s11269-017-1846-8
[48]   Unal Y S, Deniz A, Toros H, et al. 2012. Temporal and spatial patterns of precipitation variability for annual, wet, and dry seasons in Turkey. International Journal of Climatology, 32(3):392-405.
doi: 10.1002/joc.2274
[49]   Wang W, van Gelder P, Vrijling J. 2005. Trend and stationarity analysis for streamflow processes of rivers in Western Europe in the 20th century. In: Proceedings: IWA International Conference on Water Economics, Statistics, and Finance Rethymno, Greece, 8-10.
[50]   Webb B W, Nobilis F. 2007. Long-term changes in river temperature and the influence of climatic and hydrological factors. Hydrological Sciences Journal, 52(1):74-85.
[51]   Wu Z, Huang N E, Long S R, et al. 2007. On the trend, detrending, and variability of nonlinear and nonstationary time series. Proceedings of the National Academy of Sciences, 104(38):14889-14894.
[52]   Xu Z, Takeuchi K, Ishidaira H. 2003. Monotonic trend and step changes in Japanese precipitation. Journal of Hydrology, 279(1-4):144-150.
doi: 10.1016/S0022-1694(03)00178-1
[53]   Yue S, Pilon P, Phinney B, et al. 2002. The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological Processes, 16(9):1807-1829.
[54]   Yue S, Wang C Y. 2002. Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test. Water Resources Research, 38(6): 4-1-4-7, doi: 10.1029/2001WR000861.
[55]   Zhang Q, Liu C, Xu C Y, et al. 2006. Observed trends of annual maximum water level and streamflow during past 130 years in the Yangtze River basin, China. Journal of Hydrology, 324(1-4):255-265.
[56]   Zhao J, Huang Q, Chang J, et al. 2015. Analysis of temporal and spatial trends of hydro-climatic variables in the Wei River Basin. Environmental Research, 139:55-64.
doi: 10.1016/j.envres.2014.12.028 pmid: 25619963
[57]   Zhou J, Liang Z, Liu Y, et al. 2015. Six-decade temporal change and seasonal decomposition of climate variables in Lake Dianchi watershed (China): stable trend or abrupt shift? Theoretical and Applied Climatology, 119:181-191.
[58]   Zohrabi N, Bavani A M, Goodarzi E, et al. 2014. Attribution of temperature and precipitation changes to greenhouse gases in northwest Iran. Quaternary International, 345:130-137.
doi: 10.1016/j.quaint.2014.01.026
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