Article

Temporal variability of precipitation over Iran: 1966-2005

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Abstract

Precipitation is a principal element of the hydrological cycle and its temporal variability is important from both the scientific and practical point of view. The annual and seasonal precipitation trends of 41 stations in Iran for the period 1966-2005 have been analyzed using the Mann-Kendall test, the Sen's slope estimator and the linear regression. The effective sample size method was applied to eliminate the effect of serial correlation on the Mann-Kendall test. The results indicated a decreasing trend in annual precipitation at about 60% of the stations. The decreasing trends were significant at seven stations at the 95% and 99% confidence levels. The magnitude of the significant negative trends in annual precipitation varied from (-)1.999 mm/year at Zanjan station to (-)4.261 mm/year at Sanandaj station. The spatial distribution of the annual precipitation trends showed that the significant negative trends occurred mostly in the northwest of Iran. On the seasonal scale, the trends in the spring and winter precipitations time series were mostly negative. The highest numbers of stations with significant trends occurred in winter while no significant positive or negative trends were detected by the trend tests in autumn precipitation. The significant negative trends ranged between (-)0.283 mm/year at Zahedan station and (-)0.807 mm/year at Sanandaj station in winter season. In addition, the highest and lowest significant increases of precipitation values were obtained over Semnan and Mashhad in summer at the rates of (+)0.110 mm/year and (+)0.036 mm/year, respectively.

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... These negative trends can affect agriculture and water supply of the regions. On the contrary, no significant trends were detected in the eastern, southern and central parts of the country (Tabari and Talaee, 2011;Raziei, 2018). ...
... In recent decades, some studies has focused on studying precipitation and related parameters in Iran (Domroes, Kaviani and Schaefer, 1998;Dinpashoh et al., 2004;Modarres, 2006;Soltani, Modarres and Eslamian, 2007;Raziei, Bordi and Pereira, 2008;Modarres and Sarhadi, 2009;Tabari and Talaee, 2011). Domroes et al. (Domroes, Kaviani and Schaefer, 1998) applied a network of 71 rain gauges spread disordered across Iran. ...
... A hierarchical cluster analysis was applied at different lags to determine regional climates, and three main climatic sub-regions were determined. Also, trend over different sub-regions of Iran covering the period of 1966-2005 was studied by Tabari and Hosseinzadeh Talaee (Tabari and Talaee, 2011). In these studies, since non-homogeneously distributed rain gauges (in spatial domain) were applied and various methodologies were applied, the determined sub-regions varied from one study to another, especially in mountainous regions of western Iran, that are affected by a complex orography (Raziei, Bordi and Pereira, 2008). ...
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In environmental and hydrological studies, issue of variability of precipitation is of great importance, particularly for the regions located in arid and semi-arid environments such as Iran. Hence, the present study proposed a model using Ensemble Empirical Mode Decomposition (EEMD)-based multiscale entropy (EME) approach to measure and evaluate the monthly precipitation variability and spatially categorize the rain gauges in Iran.
... The Mann-Kendall test is a non-parametric test commonly used to detect monotonic trends in the series of meteorological data, hydrological data, environmental data, etc. [23,[29][30][31]. The main advantages of Mann-Kendall test are the low sensitivity in homogeneous time series [32] and the non-requirement of normal distributed time series [33] since the test is non-parametric (distribution-free test). The null hypothesis (H0) shows no trend in the series and data, which come from an independent population, are identically distributed. ...
... A positive Z value denotes increasing trend, while a negative Z value indicates decreasing trend. At α level of significance, (H0) is rejected if the absolute value of Z is greater than Z 1−α/2 , where Z 1−α/2 is obtained from the standard cumulative distribution tables [31,33]. ...
... The magnitude of a trend was also assessed by using the Theil-Sen estimator. This slope is a robust estimation of the magnitude of a trend [31,33] and it is calculate as following: ...
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Observed rainfall data (1961–2016) were used to analyze variability, trends and changes of extreme precipitation indices over Benin. Nine indices out of the ones developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. The results indicate a mix of downward and upward trends for maximum 1-day precipitation (RX1day) and maximum 5-days precipitation (RX5day). Decrease trends are observed for annual total precipitation of wet days (P), while significant increases are found for the simple daily intensity index (SDII). The number of wet days (RR1) and maximum consecutive dry days (CDD) show a mix of increase/decrease trends. However, the number of heavy (R10) and very heavy (R20) wet days and maximum consecutive wet days (CWD) show decreased trends. All wet indices increased over 1991–2010 in relation to 1971–1990. The increase in all wet indices over Benin could explain the intensification of hydrology, and the increase in the frequency and the intensity of floods. It caused damages such as soil erosion, crop destruction, livestock destruction, displacement of populations, proliferation of waterborne diseases and loss of human life. Some adaptive strategies are suggested to mitigate the impacts of changes in extreme rainfall.
... Lack of attention to water issues and climate change causes severe management problems and a serious threat to human society. Rainfall changes in Iran have been studied by various researchers (Modarres and Silva 2007;Rahimzadeh et al. 2009;Some'e et al. 2012;Tabari and Talaee 2011). The trend of changes in annual rainfall in Iran is decreasing and the most change in this trend has been observed in winter (Alijani 1996). ...
... During this period, in spring, the slope of changes is − 1 mm per year and the maximum and minimum rainfall in this season are 1996 and 2008, respectively, which shows a decreasing trend in spring and winter during the statistical period. The results of Tabari and Talaee (2011), also show a decreasing trend in these seasons (spring and winter). The year 2007 shows the relationship between the temperature of the Indian Ocean water level and the summer rainfall of Iran (Fathnia et al. 2017). ...
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One of the characteristics of arid and semi-arid regions is low rainfall and lack of uniform distribution throughout the year, which has a direct effect on water resources in these regions. In this research, daily precipitation and flow rate data of 39 meteorological stations and 9 hydrometric stations in the period 1994–2015 have been used. To evaluate seasonal and annual changes, the average data was calculated, and also MK and SQMK tests were used to detect the type of trend and mutations of changes. Sen slope, correlation, and Pettitt tests were used to determine the slope of changes, type of relationship, and also to determine the breaking point in the data time series, respectively. The results show that in all seasons, Tashk, Bakhtegan, and Maharloo sub-basins had the highest average rainfall; however, flow rate and precipitation changing curve in this region has decreased. The time-changing curve in precipitation is decreasing in winter and spring and increasing in summer and autumn. Thus, the spatial study of the udic moisture regime shows an increase in systems' activity that affects the region in the hot (summer) and cold (autumn) seasons. The trend of leap changes in winter and summer (autumn) in 7 sub-basins with 95% confidence level has been decreasing (increasing) which has decreased (increased) the river water flow in these areas. The highest percentage of decreasing and increasing changes in precipitation is in region 9 with values of − 6.66 and 2.55. The trend of leap changes in annual precipitation and flow rate in 5 sub-basins with a 95% confidence level has been reduced. The decrease in rainfall in areas 8 and 9 have had a direct effect on flow rate and has caused a significant decrease. The correlation between rainfall and flow is positive in all sub-basins and the highest coefficient of determination is in regions 3 and 9 with 40%.
... They have been found repeatedly to be associated with the risks of floods and droughts and reduced agricultural productivity and plant diversity (Choo et al., 2019;Croke et al., 2017). Hence, it is both scientifically and practically imperative to deepen our understanding of the spatiotemporal variability of precipitation and temperature (Alimoradi et al., 2017;Tabari & Talaee, 2011;Tošić, 2004) and their potential future impacts on vegetation under different scenarios. Although much research has been directed toward the spatiotemporal variability of changing climates, the evidence is not yet clear about their future impacts. ...
... (Sen, 1968). The trend magnitude is also estimated by using the age estimator slope (Tabari & Talaee, 2011). In other words, the time series is considered a linear trend with noise, and the estimator (Theil-Sen ...
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Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.
... Both seasonal precipitation and annual precipitation have multi-time scale characteristics. The trend of temperature warming is basically the same all over the country, and the climate tendency rate is slightly different in different regions [40]. ...
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Based on the observation data of daily temperature and precipitation in summer and autumn of 68 representative meteorological stations in Fujian Province from 1971 to 2018, using the climate Tendency Rate, Mann-Kendall trend test, Morlet wavelet analysis and other methods, this paper analyzes the variation trends of air temperature and annual precipitation and the wavelet periodic variation characteristics of annual precipitation time series in summer and autumn of Fujian Province over a period of approximately 48 years. The results show that over the approximately 48 years, the temperature and precipitation in summer and autumn in Fujian showed an obvious upward trend, which had a mutation around 2000, but the mutation time was different, and the precipitation was slightly earlier. The annual temperature and precipitation in summer and autumn experienced three oscillations on the 28a scale. In the 28a time scale of summer autumn seasonal oscillation, there are three negative centers and two positive centers. According to the characteristics of annual average temperature and annual precipitation in the first major cycle, the annual precipitation in summer and autumn will continue to increase in the future.
... Precipitation and temperature are essential atmospheric parameters that have created wide interest as manifested by a large number of studies over the last decades addressing their direct and noteworthy impact on the environment and society (Zolina et al. 2008;Durao et al. 2010;Caesar et al. 2011;Lukovic et al. 2013). A literature review reveals a number of studies in Iran on the spatial and temporal variations of these elements based on their geographical and topographical setting (Dinpashoh et al. 2004, Modarres and Sarhadi 2009, Tabari and Talaee 2011, Raziei et al. 2012. Soltani et al. 2012, Somee et al. 2012, Dinpashoh et al. 2014, Darand and Daneshvar 2014, Darand et al. 2015, Zarenistanak et al. 2015, Ghalhari et al. 2016, Roushangar et al. 2018. ...
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The main goal of this study was to survey a possible correlation between atmospheric parameters (air temperature, precipitation rate) and subsequent earthquakes in Iran and the surrounding Middle Eastern region. This research was carried out in response to previous work regarding atmospheric anomalies prior to major earthquake events. Area-averaged daily and monthly time-series data were compiled from global reanalyzed datasets for the study area between 1980 and 2018. The time-lagged correlation test through the cross-correlation function was examined to distinguish possible relationships between earthquake events and climatic elements within daily and monthly shifts. The results revealed that the precipitation has a strong ability to predict the earthquake series at least from 3½ months prior to the earthquakes. The estimated lagged correlation confirms a positive relationship between precipitation and subsequent earthquake events within 3 to 103 days lag-time (CCF= 0.036 to 0.046). Contrarily, no precursory relation was found between atmospheric temperature variations and subsequent earthquake events in Iran and the surrounding region.
... where, a is the regression coefficient indicating magnitude of precipitation trend. The rank-based Mann-Kendall was applied to study the statistical significance of the trend, which is generally recommended by the World Meteorological Organization [52]. The rank-based Mann-Kendall is based on the standard normal distribution Z ...
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Precipitation during the main rain season is important for natural ecosystems and human activities. In this study, according to daily precipitation data from 515 weather stations in China, we analyzed the spatiotemporal variation of rain-season (May–September) precipitation in China from 1960 to 2018. The results showed that rain-season precipitation decreased over China from 1960 to 2018. Rain-season heavy (25 ≤ p < 50 mm/day) and very heavy (p ≥ 50 mm/day) precipitation showed increasing trends, while rain-season moderate (10 ≤ p < 25 mm/day) and light (0.1 ≤ p < 10 mm/day) precipitation showed decreasing trends from 1960 to 2018. The temporal changes of precipitation indicated that rain-season light and moderate precipitation displayed downward trends in China from 1980 to 2010 and rain-season heavy and very heavy precipitation showed fluctuant variation from 1960 to 2018. Changes of rain-season precipitation showed clear regional differences. Northwest China and the Tibetan Plateau showed the largest positive trends of precipitation amount and days. In contrast, negative trends were found for almost all precipitation grades in North China Plain, Northeast China, and North Central China. Changes toward drier conditions in these regions probably had a severe impact on agricultural production. In East China, Southeast China and Southwest China, heavy and very heavy precipitation had increased while light and moderate precipitation had decreased. This result implied an increasing risk of flood and mudslides in these regions. The advance in understanding of precipitation change in China will contribute to exactly predict the regional climate change under the background of global climate change.
... To understand the effect of rainfall on discharge, the non-parametric test, i.e. the Mann-Kendall test is applied (Smith 2000; Salmi et al. 2002;Kampata et al. 2008;Zhang et al. 2009;Xu et al. 2010;Tabari and Talaee 2011). To avoid the problem of data skewness, the nonparametric test has been adopted rather than using a parametric test (Smith 2000). ...
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The flow regime of a river is an essential aspect of river hydrology. The changes of flow regime impact on peak flood discharge, sedimentation process, seasonal flow pattern, morphology of the rivers. The Barakar River, the main tributaryriver of the Damodar River in the Chhotanagpur plateau and plateau fringe region of India, has a significant flow character that is altered by human interventions. The discharge data of the Barakar River are available from Maithon and Panchet hydraulic stations. Mann–Kendall test depictsa decreasing trend of discharge. However, rainfall has an increasing trend at Maithon, thereby the relationship between discharge and rainfall is very insignificant. In the seasonal variation, a rising trend of water discharge in the pre-monsoon and the post-monsoon season is significant. Conversely, in the monsoonal season, there is an indication of a decrease in the flow over time. The uneven release of water from the dams may be the probable cause for the reduction in monsoon flow discharge. At the Maithon station, a tendency of late shifting of hydrograph indicates that the peak flow season has shifted towards the right side over time. The late release of water from the dams has caused the late shifting of the hydrograph. The annual maximum discharge for both Tilaiya and Maithon tends to decrease across the period of 1980–2013. Nevertheless, the annual minimum discharge of the Maithon shows a tendency to increase. The increase in water discharge depicts the increase in water availability during dry months of the year. The overall trend of the water flow discharge has decreased from 1980 to 2013 at both the gauging stations. The changes inflow regimes are the results of human interventions through the modification of water discharge from the dams.
... The mean annual precipitation is less than 250 mm and ranges from almost no rain in the desert to more than 1800 mm in the Zagros and the southwestern shore of the Caspian Sea. Only 8% of the country's area receives more than 500 mm/year (Tabari and Talaee, 2011). Different climate regions need to be treated differently in the form of separate clusters for gridded precipitation interpolation (Garcia et al., 2008;Teegavarapu, 2014). ...
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Study region: Iran Study focus: Gridded precipitation products are of great interest for hydrological applications. The inhomogeneous geography and uneven spatial distribution of rain gauges in Iran make it difficult to estimate valuable interpolated precipitation with daily or monthly resolutions. Therefore, we evaluated the performance of two empirical and four geostatistical interpolation methods. New hydrological insights for the region: Atmospheric circulation pattern (CP) classification was used to understand precipitation behavior and to improve interpolation. Based on 500 hPa geopotential fields, six CPs were identified, in order to explain large scale precipitation behavior. Variograms were normed and clustered to reduce the computational effort of the geostatistical methods. Leave-one-out cross-validation shows that the geostatistical methods outperform the empirical ones, and the differences among the geostatistical methods are small. The difference among all the methodologies decreased substantially for spatial aggregation to coarser resolutions. In contrast, temporal aggregation reduced the difference to a much lower extent. A large dataset consisting of 1561 locations with daily observations was used for this study. Comparison with the GPCC daily dataset shows that the data used for interpolation has a larger influence than the choice of the interpolation method.
... Meanwhile, the Mann-Kendall test is the most popular method to study hydrological time series (Longobardi and Villani 2010;Wang et al. 2012;Yang et al. 2012aYang et al. , 2012b. It is recommended by WMO as a method to evaluate the trend of hydrological series, and has been widely used in the statistical test of precipitation, temperature, and runoff worldwide (Tabari and Talaee 2011;Wang et al. 2015). M-K method is applied to test the trend statistical significance of extreme temperature and precipitation indices in this study. ...
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According to the daily maximum and minimum temperature and the precipitation at 40 meteorological stations in the Daqing River Basin of China during 1980–2015, the spatial and temporal trends of extreme temperature and precipitation are analyzed. The trend strengths, stability, and magnitude are calculated for ten indices of temperature and eight indices of precipitation. The results show that trends of extreme temperature indices are significant, but extreme precipitation indices are insignificant. Through the extreme temperature indices, the cold indices of extreme temperature decrease steadily and the warm indices of extreme temperature rise steadily, indicating that the trends of temperature rising in the basin are obvious and stable. In addition, indices of the extreme precipitation indicate that the consecutive dry days (CDD) decrease, the heavy precipitation days (R20) and the consecutive wet days (CWD) increase, and the annual total precipitation (PRCPTOT) increases steadily. The results have certain scientific value for climate change and a series of impacts brought by climate change in the Daqing River Basin.
... This is very crucial in planning adaptation strategies, responding to crises and for policy making and implementation. In this regard, various case studies have been reported in the literature (Yunling and Yiping 2005;Vincent et al. 2008;Einesr et al. 2010;Karaburun et al. 2011;Tabari and Hosseinzadeh Talaee 2011;Ceppi et al. 2012;Gocic and Trajkovic 2013), wherein climate variability data were analysed. Majority of the studies have mainly focused on urban areas and on temperature and rainfall data. ...
Article
Rice is an important crop grown globally under different climatic and soil conditions. However, the effects of the interplay between climate variability (CV) and land use changes on rice production have not been well addressed, especially in developing countries like Nigeria. Thus, a case study was undertaken in Adani, Enugu state, Nigeria. The aim is to provide further insight on CV and land use interactions and influence on the trend of rice productivity in the study area. The study utilised climate data and satellite imageries of the area. Primary data on perception of farmers regarding rice productivity was also obtained through questionnaire. The climate data was analysed using non-parametric time series analysis (Mann-Kendall and Sen’s slope estimator), while the satellite imageries were analysed using GIS and remote sensing. Results demonstrate that CV has occurred in the area, with noticeable inter-annual fluctuations. The trend shows statistical significance for maximum temperature, rainfall, modified Fournier-Maule index, relative humidity and solar irradiance, while the trend for minimum and mean temperatures and wind speed were statistically insignificant. Within the study period, land cover for the various land use patterns; bare land, built up area and water body increased, whereas vegetation cover diminished. Based on farmers’ data, rice productivity has declined, which is associated with the effects of CV that has affected the land use pattern, in addition to the topography of Adani. The primary concerns believed to be responsible for decline in rice productivity are leaching of nutrients and deposition of toxic metals from resultant flooding effect. Adaptation strategies are therefore recommended in form of remediation methods, particularly phyto-remediation and the utilisation of irrigation facilities in Adani to mitigate the adverse effects that hamper rice productivity.
... Different statistical models were applied in several ways (Cannarozzo et al., 2006;. The trend of spatiotemporal rainfall investigation undertaken in various studies (Shahid, 2011;Tabari & Talaee, 2011;Tabari et al., 2012;Teyso & Anjulo, 2016;Ullah & Ali, 2018;Zhang et al., 2014). However, they only emphasised seasonal and annual rainfall with traditional climatic stations, whereas no studies focused on trend studies with climatic zones. ...
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Rainfall trend analysis is common for climate change observation following the flood, drought, and other extreme hydrometeorological possibilities. Therefore, this study aims to evaluate the spatiotemporal rainfall trend for seven climatic zones in Bangladesh during 1979–2019. For the trend exploration Mann-Kendall (MK) trend test, slope estimator (Sens) and IDW techniques were utilised from the dataset of 27 stations. The findings shows descending annual trend of >-2.50, >1.95, >-1.80, >-1.60, >-1.31 and >-0.50 for the zones of (C)western region, (A)northern part of northern region, (B)north-western region, (E)south-central region, (D)south-western region and (G)north-eastern region, respectively, whereas ascending trend found for only (F)south-eastern region >1.83. Except for post-monsoon season zone F > 2.90 trends, all other seasonal trend is in a declining position. An increasing magnitude of rainfall is found >0.0355(F) for annual, >0.136(A), 0.0146(C), 0.0047(F) and 0.0093(G) for pre-monsoon, >0.0046(D), >0.0329(F) for post-monsoon, >0.0039(G) for winter and >0.0273(F) for monsoon seasons while all other zones are in decreased nature. Heterogeneously significant rainfall magnitude for annual, pre-monsoon, post-monsoon and monsoon seasons was also found, which includes >.03(F), >0.01(C), >0.03(F), >1.51(F), respectively. The findings recommend adopting operations and advanced design for water management with consideration of agricultural development and climate change.
... The FAO-56(PM) estimation method uses relative humidity, air temperature, solar radiation, and wind speed. Numerous researchers demonstrated that estimating irrigation water requirements is critical for the proper operation of a sophisticated irrigation process in various places around the world (Allen et al., 1998;Tabari & Talaee, 2011;Thepadia & Martinez, 2012;Tabari et al., 2013;Çakir et al., 2017;Gul et al., 2021). In addition, ET o estimates are frequently used to develop, supervise, plan, and perform water assets in hydrology, agriculture water resources, irrigation, and drainage engineering (Gul et al., 2021;Valipour, 2014Valipour, , 2015. ...
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Reference evapotranspiration (ETo) is critical for irrigation design and water management in rainfed and irrigated agriculture. The Penman-Monteith (FAO-56(PM)) equation was demonstrated to be the most reliable and adaptive to a wide range of humid to semi-arid climates. However, it requires several environmental parameters (e.g., wind speed, solar radiation), rarely available in developing countries. Therefore, numerous temperature-based formulas have been designed to address this issue for various environments. Their calibration and validation against the local climate frequently lead to increases in performance. We revised the Hargreaves exponent (EH) and substituted a value of (0.16) for the original value (0.5). The modified Hargreaves formula enhances the ETo predictions with a mean absolute error ranging from (0.791) mm per day for Balakot to (2.36) mm per day in Risalpur, averaging (3.797) mm per day, as compared to the Hargreaves-Samani (16.827) mm per day. In general, all the selected models showed high accuracy. However, the modified Hargreaves equation appeared to give the most promising results. It ranked first in (50%) of the whole area based on the standard error of estimate for estimating ETo in Khyber Pakhtunkhwa. Additional research must be conducted to determine the study's relevance to other regions. HIGHLIGHTS The main objective of this paper is to investigate the possibility of calibrating the Hargreaves equation and comparison for spatial domain Khyber Pakhtunkhwa, Pakistan.; The performance evaluation of three radiation-based methods (Priestly-Taylor, Makkink and Turc) and two temperature based methods (Hargreaves-Samani and modified Hargreaves) are evaluated in this paper. Bayesian Kriging is used for interpolation.;
... Previous studies showed that the ability of trend identification is disturbed due to the serial structure in a time series (Tabari and Talaee 2011). The MK test is not robust against serial correlation (Ali et al. 2019), sample size, and against the seasonal fluctuation in the climatic time series data (Dinpashoh et al. 2014) Therefore, trends in drought series needed to be evaluated using various trend tests (Sagarika et al. 2014) such as MK, modMK1 and modMK1 lag-1 as shown in Fig. 9, to choose the best suited for the region. ...
Article
Climate change in Pakistan has a great impact on the spatial and temporal variation of precipitation and ultimately alters the frequency and duration of droughts. In this study, spatial and temporal trend analyses of precipitation and droughts were observed at 58 meteorological stations across Pakistan from 1981 to 2018. The existing trend analysis methods were evaluated to address the issue of serial correlation in the climatic data. Results of precipitation analysis showed significant decreasing trends in winter (November, December) and significant increasing trends were observed in summer (June and September) at a confidence level of 95 percent. The magnitude of the precipitation trends showed the highest variation during summer season and the least variation in winter season. Rotated Principal Component (RPC) analysis showed the severe droughts (high positive loading) in southeastern side (Sindh province) of Pakistan due to lack of summer rains. Furthermore, variance correction approaches are identified as the most suitable in coping with the effect of serial correlation. The highest drought frequencies were observed in the southern areas of Pakistan and the drought events are expected to occur more frequently in the late winter, early spring, and early autumn, while droughts were expected to occur least frequently in summer.
... Iran is approximately located between 25°N and 40°N in latitude and between 44°E and 64°E in longitude. Based on the Koppen climate classification, most parts of Iran are categorized as generally arid (BW) and semiarid (BS) climates (Tabari and Talaee 2011). The mean annual precipitation of Iran is about 241 mm. ...
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This paper aims to find the possible relationships between winter precipitation (December, January, February; DJF) in Iran with three oceanic sources through the correlation wavelet analysis by applying the continuous wavelet transform (CWT), the cross–wavelet transform (XWT), and the wavelet transform coherence (WTC). The sources in the North Atlantic Ocean (30°W-70°W, 10°N-30°N), the South Pacific Ocean (80°W-120°W, 20°S-40°S) and the Indian Ocean (50°E-100°E, 10°S-40°S) were selected using Pearson correlation coefficient (PCC > 0.5) that can represent the possible relationships between Iran’s winter precipitations with the oceanic sea surface temperature (SST) anomaly. The monthly gridded precipitation and SST data with a 2.5° × 2.5° resolution were evaluated from 1984 to 2019 to achieve this goal. The XWT results of precipitation and SST anomaly showed that the 8–16 months period is the most effective and predominant period between the South Pacific Ocean and 81% of all the precipitation zones. WTC results for the North Atlantic Ocean and 72% of all the precipitation zones showed periods of 4–8 (36%) and 16–32 (36%) months as the dominant duration. Despite the proximity of the Indian Ocean to the precipitation zones, there is no significant causal relationship between them, based on the XWT results. However, due to Madden–Julian oscillation (MJO), the 4–8 months period (45%) was seen between the Indian Ocean and some precipitation zones, based on WTC results.
... For the 1979-2014 averaged period, Pr has a value of 0.53 ± 0.20 mm day −1 from the MMM ensemble for Iran country; this value is according to the results reported by Ghasemi and Khalili (2008) of 0.68 mm day −1 (~ 25 cm in a year). In general, the MMM ensemble correctly reproduces the typical strong gradient with higher values towards the western parts of the Caspian Sea coast (~ 0.38 mm day −1 ) and lower values toward the southeast of Iran (~ 0.06 mm day −1 ); this pattern is consistent with the mean annual precipitation pattern in Iran (not shown) (Tabari and Talaee 2011;Shifteh Some'e et al. 2012). Furthermore, from validation results (Fig. 3c), there are lower variability in models' performance; additionally best metrics correspond to MPI-ESM1-2-XR (MAE = 0.31, RMSE = 0.35, MAPE = 2.84) and HadGEM3-GC31-MM (MAE = 0.31, RMSE = 0.36, MAPE = 2.38) models; in contrary worst performance is observed for CMCC-CM2-VHR4 and HadGEM3-GC31-HM models (Table 2). ...
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It was evident from observations in the recent past that atmospheric variables are changing at regional scale and may continue to impact the regional weather in the coming future. An 8-member ensemble from the HighResMIP experiment is used to analyze projected changes in temperature, atmospheric pressure, precipitation, and surface wind over Iran during 2015–2050 period. A considerable increase of temperature between 2 and 2.5 °C by 2050 with respect to the baseline period (1979–2014) is expected with a higher rate towards southwestern and southeastern of Iran. From the seasonal analysis, an increase of ~ 4 °C (2 °C) by 2050 would be maintained in summer (winter) season over the country. Furthermore, a reduction in atmospheric pressure between 0.2 and 1 hPa by 2050 with respect to the baseline period towards the northwestern region of the country is foresaw; however, no consistent changes are expected in the remain regions where lack of coherence between models is recognized. Besides, precipitation changes are expected to be significant towards the northwestern Iran region with values between 0.1 and 0.3 mm day−1 by 2050 with respect to the baseline period, contrary to the results obtained in the eastern region with changes between − 0.1 and 0.1 mm day−1 towards the Lut and the Kavir deserts. Additionally, an interesting behavior was noticeable in all the models selected with a reduction in precipitation of 0.3 mm day−1 between June and September which announce temperature increases principally in boreal summer, thus can exacerbate extensive droughts in different regions of Iran. Finally, surface wind speed and direction behavior were assessed, showing an increase of surface wind speed between 0.05 and 0.1 ms−1, but no significant trends were observed in the majority of the country similar to expected changes in wind direction
... Other studies mostly observed negative trend on monthly rainy days in Iran (Soltani et al., 2012;Rahimzadeh et al., 2009). Also, the findings of studies mostly noticed decreasing trends in precipitation over Iran (Some′e et al., 2012;Tabari and Talaee, 2011). A study assessed by Zhai et al. (2005) revealed that the annual precipitation decreased over the southern northeast parts of China, while a significant increase was detected in western region. ...
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The civil war, harsh climate, tough topography, and lack of accurate meteorological stations have limited the number of consecutive synoptic data across Afghanistan. The global data (gridded precipitation datasets) pave the way to assess the precipitation indicators of climate, where stations are sparsely located. This study assessed the mean annual precipitation trend in 33 stations over Afghanistan. Non-parametric linear regression technique was employed to find upward and downward trends and magnitudes. The daily of precipitation was obtained from the database of the CPC-NOAA (Climate Prediction Center - National Oceanic Atmospheric Administration) for the period of 1979–2019. The CPC spatial resolution of daily precipitation is 0.5×0.5 degree. Analysis of mean annual precipitation showed a significant decreasing trend at six provinces in the north, while an increasing trend of 9.2 mm per decade has been observed at three provinces. In the south, a notable reduction of the precipitation trend has been experienced in Helmand, Kandahar, and Nimruz provinces, but Ghazni and Uruzgan show a positive trend. Data revealed that mean annual precipitation has remarkably decreased in the western part of Afghanistan. According to the study period, the mean annual rainfall in the central regions indicates a raise of 37.5 mm per decade in Kabul, while in Vardak, the precipitation increases up to 9.21 mm per year. Eastern regions include 8 provinces, and the eastern highland covers the smallest area that is mainly covered by rangeland and the largest existing forests. These regions are directly influenced by the moist air masses of Indian monsoon getting trapped at the high mountain slopes, and it can lead to an increase of rain. Data reveals an upward trend of precipitation in the eastern part of Afghanistan.
... Other studies mostly observed negative trend on monthly rainy days in Iran (Soltani et al., 2012;Rahimzadeh et al., 2009). Also, the findings of studies mostly noticed decreasing trends in precipitation over Iran (Some′e et al., 2012;Tabari and Talaee, 2011). A study assessed by Zhai et al. (2005) revealed that the annual precipitation decreased over the southern northeast parts of China, while a significant increase was detected in western region. ...
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The civil war, harsh climate, tough topography, and lack of accurate meteorological stations have limited the number of consecutive synoptic data across Afghanistan. The global data (gridded precipitation datasets) pave the way to assess the precipitation indicators of climate, where stations are sparsely located. This study assessed the mean annual precipitation trend in 33 stations over Afghanistan. Non-parametric linear regression technique was employed to find upward and downward trends and magnitudes. The daily of precipitation was obtained from the database of the CPC-NOAA (Climate Prediction Center-National Oceanic Atmospheric Administration) for the period of 1979-2019. The CPC spatial resolution of daily precipitation is 0.5×0.5 degree. Analysis of mean annual precipitation showed a significant decreasing trend at six provinces in the north, while an increasing trend of 9.2 mm per decade has been observed at three provinces. In the south, a notable reduction of the precipitation trend has been experienced in Helmand, Kandahar, and Nimruz provinces, but Ghazni and Uruzgan show a positive trend. Data revealed that mean annual precipitation has remarkably decreased in the western part of Afghanistan. According to the study period, the mean annual rainfall in the central regions indicates a raise of 37.5 mm per decade in Kabul, while in Vardak, the precipitation increases up to 9.21 mm per year. Eastern regions include 8 provinces, and the eastern highland covers the smallest area that is mainly covered by rangeland and the largest existing forests. These regions are directly influenced by the moist air masses of Indian monsoon getting trapped at the high mountain slopes, and it can lead to an increase of rain. Data reveals an upward trend of precipitation in the eastern part of Afghanistan.
... The Mann-Kendall (MK) test has been widely used to assess the significance of monotonic trends in hydrometeorological series [44,55] due to its insensitivity to outliers and normally distributed time-series data [56]. In this study, the MK test was used to detect whether the change trends in graded precipitation were statistically significant. ...
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Under the background of global warming, the trends and variabilities of different grades of precipitation have significant effects on the management of regional ecosystems and water resources. Based on a daily precipitation dataset collected from 148 meteorological stations in the Yangtze River Basin from 1960 to 2017, precipitation events were divided into four grades (small, moderate, large, and heavy precipitation events) according to the precipitation intensity to analyze the temporal and spatial change trends of different grades of precipitation amounts and frequencies, and the influence of different grades of precipitation on total precipitation was also discussed in this study. The results revealed that small precipitation amounts over the Yangtze River Basin decreased significantly, with a rate of −1.22%/10a, while heavy precipitation amounts showed a significant increasing trend (4.27%/10a) during the study period. The precipitation frequency of small and total events decreased significantly, with rates of −3.86%/10a and −2.97%/10a, respectively. Regionally, from the upper reaches to the lower reaches of the Yangtze River Basin, the contribution rate of small precipitation amounts and frequencies to the total precipitation gradually decreased, while heavy precipitation amounts and frequencies increased. The different grades of precipitation in region II showed a decreasing trend due to its unique geographical features. Furthermore, a Pearson correlation analysis was used to analyze the response of precipitation to long-term air temperature, demonstrating that small and moderate precipitation amounts and frequencies were mainly negatively correlated with long-term air temperature and that heavy precipitation amounts showed a stronger positive correlation with long-term air temperature (13.35%/K). Based on this, the rate of change in heavy precipitation in the Yangtze River Basin may be higher under the background of climate warming, which will lead to greater risks of extreme floods in the future. Evaluating and predicting the trends of different grades can provide a theoretical reference for agricultural production, flood control, and drought mitigation.
... Numerous studies have investigated the characteristic elements of extreme precipitation events and their associated physical mechanisms, but most previous analyses focus on the spatio-temporal variability (Zhang et al 2008, Tabari andTalaee 2011) or changes in the frequency (Kunkel 2003, Jung et al 2011, intensity (Pavan et al 2008, Donat et al 2013, Tandon et al 2018, and duration (Liu 2011) of precipitation extremes based on precipitation observations (Alexander et al 2006, Peterson et al 2008 or climate model simulations (Tebaldi et al 2006, Sun et al 2007. Analyses of temporal characteristics of precipitation extremes were generally conducted on observed (Zhang and Zhou 2019) and projected (Asadieh and Krakauer 2015, Kitoh and Endo 2016, Zhan et al 2020 precipitation data for each station or grid individually, without considering the co-occurrence of precipitation extremes between neighbor stations and grids. ...
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Understanding the variability of spatial extents of precipitation extremes favors an accurate assessment of the severity of disasters caused by extreme precipitation events. Using a restricted neighborhood method, we identify the spatial extents of global precipitation extremes over 1983–2018 and examine their spatiotemporal variability and associated changes. Results show that the mid-latitudes shows the largest spatial extent of precipitation extremes, and the spatial extents in non-tropical regions over the Northern Hemisphere show significant seasonal differences. In non-monsoon regions, the spatial extents of precipitation extremes in autumn and winter are larger than those in spring and summer, and the annual average spatial extents of precipitation extremes all exceed 500 km, which are larger than those in monsoon regions. All the five non-monsoon regions over the Northern Hemisphere and three monsoon regions in the western Pacific show statistically significant increases in the spatial extent of precipitation extremes in most seasons.
... Modarres and Sarhadi (2009) found that negative trends of annual rainfall are mostly observed in northern and northwestern regions. Tabari and Talaee (2011) showed that significant negative trends occurred mostly in the northwest of Iran. Abarghouei et al. (2011) indicated a significant negative trend of drought in many parts of Iran, especially the southeast, west, and southwest regions of the country. ...
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The study of the maximum number of consecutive dry days (MCDDs) is one approach to analyze precipitation behavior in arid and semi-arid regions of Iran. This study is a first attempt to investigate the MCDDs and their relationship with the El Niño/Southern Oscillation (ENSO) in winter months over Iran. The study was carried out using Tropical Rainfall Measuring Mission (TRMM) satellite data on a daily basis at 1° latitude × 1° longitude spatial resolution and reanalysis data for the period 1998–2019. Results showed that the highest values of MCDDs are observed in southeastern Iran and the lowest in northwestern Iran. Based on the coefficients of the linear trend of the MCDDs, the significant increasing trends are remarkably more abundant than declining trends, especially in the northern half of the country in December and January. The results regarding the relationship between ENSO and MCDDs indicated a non-stationary behavior, with a significant negative correlation for December (especially in the southwest) and positive correlation for January and February (especially in the southeast). The largest differences in the correlation coefficients were observed between December and January. In general, during El Niño (La Niña) phases, the length of MCDDs decreases (increases) in December and increases (decreases) in January especially in the southern half. By comparing different large-scale climate parameters for the 2 months, we found that during El Niño (La Niña) phases, a negative (positive) anomaly of geopotential height and a positive (negative) anomaly of zonal wind and specific humidity are observed over the region in December, while the opposite situation occurs in January. The innovation of this study is the use of satellite data that provide a continuous spatial coverage of the region and the consideration of the ENSO teleconnection pattern in regards to dry spells. We find that El Niño (La Niña) has contradictory effects on MCDDs in different winter months in the southern half of the country. These findings are of great importance for a country like Iran that lies in arid and semi-arid regions, as they can be useful for water resources management.
... The previous studied by many researchers (Smith, 2004;Joshi and Rajeevan, 2006;Guhathakurta and Rajeevan, 2008;Subash et al., 2011;Tabari et al., 2011;Patra et al., 2012;Singh and Borah, 2013;Taxak et al., 2014;Gajbhiye et al., 2016;Singh, 2018b;Dwivedi et al., 2019;Malik and Kumar, 2020) give insights about the sp atio-temporal distibution of rainfall and variability in hydro-meteorological time series with respect to climate change in Indian context. Several studies show a rise in the frequency of intense rainfall events in many parts of Indian subcontinent while a decrease in number of rainy days and total annual precipitation (Sinha Ray and Srivastava, 2000;Lal, 2003, Goswami et al., 2006andDash et al., 2007, 2009). ...
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Our study has investigated spatio-temporal distribution of rainfall and rain day trends during different seasons for all districts of Haryana, India. Gridded rainfall dataset of 120 years (1901 to 2020) from India Meteorological Department (IMD) was analysed using mean rainfall, rainfall deviation, seasonal rainfall ratio (SRR), coefficient of variation (CV), number of rain days, rainfall intensity, trends of rain days, Empirical Orthogonal Functions (EOF) and Principal Component (PC) analysis. Districts lying in eastern Haryana have experienced more rainfall (less variability) than the ones lying in western Haryana during each season. SRR and CV analysis depicted most consistent rainfall during monsoon and maximum variability during post-monsoon season. Highest number of rain days was observed during monsoon season followed by pre-monsoon, winter and post-monsoon season in Haryana. Innovative trend analysis method (ITAM) shows a declining trend in number of rain days during winter and post-monsoon season while an increasing trend was observed during pre-monsoon season. Overall, monsoon season has shown a falling trend in moderate while rising trend was observed in both light and heavy rainfall intensity categories in most of districts. Dominant EOF explained maximum variability during post-monsoon season followed by winter, pre-monsoon, and monsoon season respectively. PC analysis captured inter-annual variability in rainfall during each season. Our findings highlight qualitative and quantitative aspects of seasonal rainfall dynamics at districts level. This study is beneficial in understanding impact of climate change and climate variability on rainfall dynamics in Haryana which may guide policymakers and beneficiaries in optimizing use of hydrological resources.
... Mann-Kendall trend test (Mann 1945;Kendall 1975) was adopted to analyse rainfall onset dates trends. The Mann-Kendall (MK) test is a non-parametric test commonly used to detect significant trends in hydrological and meteorological time series (Tabari and Talaee 2011). The test is suitable for the data that do not follow a normal distribution (Tabari and Nikbakht 2012) and supports multiple observations per time series (Kampata et al. 2008). ...
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This study characterised the spatio-temporal patterns of effective rainfall onset dates, their variability and their relationship with ENSO/IOD over Savanna zones of Nigeria. Daily rainfall and ENSO/IOD data for the period 1971–2015 were used. The Intra-Seasonal Rainfall Monitoring Index (IRMI) was applied to identify and classify effective rainfall onset dates. The classified effective rainfall onset dates were subjected to the Mann-Kendall trend test. The coefficient of variation (CV) was employed for the variability test, while Pearson’s product-moment correlation was employed to establish an association between variables. The results indicate a variation in the effective start of rainfall of 15 days, and 30–60 days, in the Guinea Savanna and Sudano-Sahelian Savanna zones, respectively, between the western and eastern axes. The onset date trend test revealed that stations in the guinea savanna zone tended to have later effective onset dates while stations in the Sudano-Sahelian savanna zone tended to have earlier onset dates of rainfall. The correlation test showed a significant and insignificant positive relationship between effective rainfall onset dates and the ENSO/IOD phase, particularly in the stations across the guinea savanna zones of the study area. It is expected that this information on the variability of effective rainfall onset dates, when provided in aid of rain-fed agriculture, could support decision-making on crop types to be cultivated and on the planning of sowing dates across the study area. These findings are of high importance to the entire West African sub-region, including other parts of the world that share similar monsoon rainfall and physical characteristics of these savanna zones.
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Accurate estimates of reference evapotranspiration are critical for water-resource management strategies such as irrigation scheduling and operation. Therefore, knowledge of events such as spatial and temporal reference evapotranspiration (ET o ) and their related principle of statistical probability theory plays a vital role in amplifying sustainable irrigation planning. Spatiotemporal statistical probability distribution and its associated trends have not yet has explored in Pakistan. In this study, we have two objectives: (1) to determine the most appropriate statistical probability distribution that better describes ET o on mean monthly and seasons wise estimates for the design of irrigation system in Khyber Pakhtunkhwa, and (2) to check the trends in ET o on a monthly, seasonal, and annual basis. To check the ET o trends, we used the modified version of the Mann-Kendall and Sen Slope. We used Bayesian Kriging for spatial interpolation and propose a practical approach to the design and study of statistical probability distributions for the irrigation system and water supplies management. Also, the scheme preeminent explains ET o , on a monthly and seasonal basis. The statistical distribution that showed the best fit ET o result occupying 58 . 33% and 25% performance for the design of irrigation scheme in the entire study region on the monthly level was Johnson SB and Generalized Pareto, respectively. However, according to the Anderson-Darling (AD) and Kolmogorov–Smirnov (KS) goodness of fit measure, seasonal ET o estimates were preferably suited to the Burr, Johnson SB & Generalized Extreme Value. More research work must be conduct to assess the significance of this study to other fields. In conclusion, these findings might be helpful for water resource management and policymaker in future operations.
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Climate change significantly affects the hydrologic process and consequently the availability of water resources in a region. In certain regions, it may cause large variations in rainfall with occurrence of extreme rainfall events that result in either floods or droughts. In the rapid climate change scenario, it is therefore pertinent to study regional rainfall trends and corresponding trends of other climatic variables for optimal and sustainable utilization of water resources of a region. The present study focuses on climate variability and its impact on seasonal and annual rainfall trends in the regions of Andhra Pradesh and Telangana states, India. Daily rainfall data along with relative humidity, temperature, vapour pressure and wind speed at Anantapur, Arogyavaram and Kurnool located in Rayalaseema region, Kakinada, Machilipatnam and Nellore in Coastal region of Andhra Pradesh state and, Hyderabad, Nizamabad and Ramagundam of Telangana state, collected for the period 1969–2008 from India Meteorological Department (IMD) Pune, were used in the analysis. Trend analysis of seasonal (monsoon and post-monsoon) and annual rainfall and other climatic parameters indicated an increase in rainfall with an increase in relative humidity, vapour pressure and temperature and a decrease in wind speed. An increase in annual rainfall of 7.4 mm/year at Kurnool may be due to increase in relative humidity by 0.093%/year and temperature by 0.016 °C/year . Monsoon and annual rainfall increased by 6.04 mm/year and 4.96 mm/year at Kakinada and Machilipatnam, respectively, due to respective increase in vapour pressure by 0.019 mbar/year and 0.38 mbar/year. Increase in relative humidity by 0.07%/year and vapour pressure by 0.058 mbar/year at Hyderabad of Telangana state showed a significant increase in annual rainfall of 10.92 mm/year. The climate variability at the stations in the regions reported in the present study may be helpful in the assessment of seasonal/annual rainfall in the regions.
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Iran’s groundwater hydrochemistry has not been well understood. In this study, Iran’s groundwater hydrochemistry is evaluated using a rich, ground-trusted data sampled from 9,468 wells distributed across the country in 2011. Twelve groundwater quality parameters were analyzed in each sample, resulting in 113,616 parameters over the study period. Examination of anions-cations shows that concentrations of sodium, calcium, chloride, and sulfate are higher than the acceptable threshold for drinking-use suggested by the World Health Organization in about 40%, 21%, 25% and 20% of the samples, respectively. The results of the water quality index reveal that most of the groundwater resources in the central, southern and eastern regions of Iran, which supply the majority of the domestic water for populated cities, do not meet the requirements for drinking-use. Although the groundwater in northern parts fulfills the requirements for irrigation-use, it is only suitable for irrigation of salinity-friendly crops in central, eastern and southern regions. Ionic types and hydrochemistry facies indicate the dominance of mix water type in 13 out of 30 of Iran’s sub-basins, followed by sodium-chloride water type in nine sub-basins. Local geology and lithology are mainly attributed to the distribution of groundwater facies in Iran. In general, our findings reveal a distinctive relationship between Iran’s geological-geomorphological features and hydrochemical facies/groundwater quality. The findings can be used in the formulation of new strategies and policies for Iran’s groundwater quality management in the future.
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Under the global climate change, research on the response characteristic of precipitation to climate change and its variation trend is of great significance. By employing the empirical orthogonal function (EOF), the TPFW-MK test and the PCD and PCP method, the multiple-time scale variability and spatial distribution of precipitation in different climate zones are studied by the monthly precipitation data from 122 meteorological stations in Northwestern China (NWC) during 1960–2015. The results indicated that the annual precipitation in 68% of the stations exhibited upward trends and the average annual precipitation increased at 2.6 mm per decade from 1960 to 2015. Opposite variation trends of annual precipitation were detected in different climate zones, significant positive trends in arid and semiarid zones, but negative trends in humid and semi-humid zones. Based on the Z-statistics by TPFW-MK test, winter precipitation exhibited a generally increasing trend, but the variation of summer precipitation showed remarkable regional differences. Mutation test indicated that middle 1980s was the major mutation point of precipitation series. According to the CDF plots, the proportion of precipitation between 0 and 300 mm decreased, while the proportion of precipitation more than 700 mm increased. The EOF analyses showed that the spatial distribution of precipitation had three typical modes, whole area consistent type, east–west opposite type and north–south opposite type. The greatest proportion of the whole area pattern revealed that the climate condition was controlled by some common factors despite the different variation trends. Trend analyses of PCD and PCP indicated that the inter-annual precipitation in about 77.3% of the stations had a high concentration degree, the unevenness of inter-annual precipitation distribution increased in humid and semi-humid zones and decreased in arid and semiarid zones, which was opposite to the variation trends of annual precipitation. Besides, the concentrate period of inter-annual precipitation had advanced over the last decades. The results will provide reliable references for addressing climate change, protecting ecological environment and preventing meteorological disasters.
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An attempt has been made to study the intra-monsoonal spatio-temporal variability of rainfall (VoR) in the Pravara-Mula Basin (PMB) of Maharashtra state, India. This paper aims to investigate and analyze the spatio-temporal variation of the intra-monsoonal rainfall for the period of 31 years (1976–2006) considering 11 rain-gauge stations data. The precipitation concentration index (PCI) has been calculated by Oliver’s method and presented by graphic chronological treatment information (MGCTI) of Bertin matrix types which shows current trends of spatio-temporal analysis of intra-monsoonal rainfall variability. The distribution of average intra-monsoonal precipitation and isohyets maps were obtained by inverse distance weighting (IDW) interpolation technique using the GIS software. It was found that the distribution of intra-monsoonal rainfall is uneven and highly influenced by the regional topography of the region. The western part of the study area receives the highest rainfall (> 1500 mm), whereas in the eastern part rainfall is more erratic (< 500 mm). Due to the geographical location of the Mandohol station, a strongly irregularity (PCI > 20) of spatio-temporal precipitation distribution has been observed in the years 1987, 1988, 1990, 1991, and 1996. The strongly irregular variability is temporally associated with the year 1991, irregular variability in the years 1977 and 1994. In the years 1987, 1994, and 2004, the uniform distribution of rainfall is observed in PMB. This type of effort is innovative for bids in PMB and also in the other river basins which has similar geographical conditions for water resource management.
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The present study aims to investigate Iran’s agrometeorological drought history and its properties using Multivariate Standardized Drought Index (MSDI). For this purpose, precipitation and soil moisture recorded at 99 synoptic stations in Iran during 1985 to 2018 were selected. Based on MSDI time series, drought properties including duration and severity were calculated and trend analysis was carried on using Trend Free Prewhitening Mann Kendall test. Also, the standard normal homogeneity test was applied to investigate chronological drought change-point detection. From agrometeorological perspective, results showed that longer and more severe droughts are more dominant in southern, southeastern, northeastern, and some western regions of the country. Trend analysis revealed that most study stations have rising frequency and significant drying trend especially in winter at central plateau and western regions. Also, we recognized two main periods 1991–2000 and 2006–2010 that many stations experienced change-point in their MSDI time series, mainly because of climatic and anthropogenic causes. Drought properties assessment shows 6 stations with serious upward trend in drought duration and severity in northeast and western regions. Sens’s Slope statistics in these stations was calculated around 1.5 degree per event for drought severity and 1 month per event for drought duration. It is also observed that the 75th quantile of drought severity for most parts of the country is between 13 and 18 and the 75th quantile for drought duration varies between 8 and 24 months in different regions. The probability analysis revealed that most stations have a ratio around 2–5 times increase in drought occurrence probability after change point, leading to longer and more severe droughts in these stations. The paper indicates a serious situation related to agrometeorological drought occurrence, persistence, and severity in Iran because of many climatic and anthropogenic factors over the last 30 years.
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The results showed that the rainfall persistence in Iran had four patterns. The first pattern was due to the establishment of Rex blocking and moisture convergence in the southern Mediterranean. The second pattern of persistence of days was due to the establishment of a split blocking pattern and the existence of a semi-deep trough in the eastern Mediterranean, as well as the injection of moisture from the Mediterranean Sea. In this pattern, the role of the Sudan low pressure was less significant. In the third model, the persistence of rainfall was the result of the establishment of the omega blocking within 55° and the strengthening of its humidity was also the result of the cooperation of the Arabian Sea and the Red Sea. In the fourth model, the continuity of days was more influential in further moisture convergence due to the establishment of a trough in the eastern Mediterranean and the strengthening and injection of moisture from the Black, Red, and Mediterranean Seas, as well as the collaboration of Sudan low pressure and Mediterranean low-pressure systems. In the first three models, the increase in the amount and persistence of precipitation was due to the role of blockings in slowing down the movement of systems. In the fourth pattern, the increase in precipitation was more related to the injection of more moisture into the precipitation system. In general, the results showed that the occurrence of blockings plays an important role in both the persistence of rainy days and the amount of rainfall.
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In this research, temporal trends and change points in heating degree-days (HDD), cooling degree-days (CDD), and their simultaneous combination (HDD + CDD) were analysed for a 60-year period (1960–2019) in Iran. The results show that less than 20% of the study stations had significant trends (either upward or downward) in HDD time series, while more than 80% of the stations had significant increasing trends in CDD and HDD + CDD time series. Abrupt changes in HDD time series mostly occurred in the early 1980s, but those in CDD time series were mostly observed in the 1990s. The cooling energy demand in Iran has dramatically increased as CDD values have raised up from 690 ºC-days to 1010 ºC-days in the last 60 years. HDD, however, almost remained constant in the same period. The results suggest that if global warming continues with the current pace, cooling energy demand in the residential sector will considerably increase in the future, calling for a change in residential energy consumption policies. Highlights Monotonic trends in HDD, CDD and HDD + CDD time series were analysed in Iran. The series were also analysed for possible change points using the non-parametric method. Energy demand for cooling houses increased, while that for heating houses remained constant. Up to three upward abrupt change points were observed in the annual CDD series.
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Hydrologic alteration can be attributed to climate and human effects with some confidence. However, when quantifying the hydrologic alteration induced by dams using historical flow records, there is a lack of consideration concerning the impacts of climate variability on hydrologic alteration. Evaluating dam-induced and climate-influence-induced hydrologic alteration has emerged as a key problem , which is the process of quantifying the extent that they have altered the river's hydrologic attributes. Central to this process is restoring the hydrologic attributes without dam influence. This study simulates hydrologic regimes without dam influence and evaluates the dam and climate influences on hydrologic processes in the Lancang-Mekong River. The results showed that the meteorological variables were closely related with runoff. Therefore, a stepwise-regression model was established and validated using meteorological variables with their time lags, and it showed good performance. The simulative evaluation revealed that runoff from the Lancang River was simultaneously and significantly affected by dam construction and climate variability, and the damming effects were mainly concentrated in the primary stage of reservoir operation. Meanwhile, the dam operation increased the minimum and maximum monthly runoff over a year. During the study period, the degree of hydrologic alteration (DHA) indicated that the Manwan Dam compensated for the impacts of climate variability on the Lancang River.
Chapter
The rivers and their floodplains are integrated systems. The biodiversity of the Lower Danube River (LDR), in terms of species and habitats, is strongly linked with its hydro-geomorphic-diversity and the natural regions it passes. Human activities, directly and indirectly, are the primary cause which has induced changes in hydrologic regime, longitudinal and lateral connectivity, floodplain geomorphology and function, biodiversity of the river waters and riparian zone. During the twentieth century, particularly after World War II, the LDR has undergone alteration of physical habitat, significant landscape changes, and ecological loss as a result of hydropower damming works and their associated water reservoirs, floodplain embankment, wetlands drainage, chemical pollution, eutrophication, and invasion of exotic species. The extensive embankments and drainage work along LDR in Romania converted about 80% of the annual flooded zone of the floodplain area primarily into agricultural region, obviating its essential connection with the river. Few areas, including reed marshes, meadows, floodplain forests, large shallow lakes, fluvial islands, and the braided section of the river named “the Small Island of Brăila”, have been preserved in natural regime in order to preserve valuable samples of biodiversity, hydro-morpho dynamic processes, and particular fluvial landforms. Most of them are ecotonal areas that have an increased and extremely dynamic biodiversity. This increased turnover of species is exacerbated by anthropogenic factors, which sometimes they can negatively influence certain species of fauna, such as sturgeons, modifying their habitats for reproduction, feeding and resting. After the 1990s, due to the change of the political system in Romania and following integrated programs of the Danube Riparian States, some areas of the engineered floodplain are subject to ecological restoration and integrated management in order to provide convenient ways of reconciliation between nature and human society for a sustainable development. The currently Ramsar and Natura 2000 sites network designed along the LDR provides the national and international legal framework of protection and conservation of wildlife and its habitats. The objectives of this chapter are to present a review of: (1) human interventions from the last century that lead to alteration, degradation, and irreversible losses of habitats along the LDR valley, (2) restoration projects of former floodplain areas, and (3) biodiversity protection and conservation actions carried out over the area in the last decades.
Chapter
Hydrological extremes, as a manifestation of the natural flow regime, have negative impacts on the environment through the effects they produce. Floods cause significant fatalities and economic losses and leave their long-term psychological imprint on local communities. Hydrological droughts also represent complex hydrological phenomena, that have direct negative effects on agricultural productivity. In this study, analysis of the hydrological extremes’ including anomalies and trends was carried out across 25,000 km2 in the eastern part of Romania, between the last two major tributary of the Danube River, namely Siret and Prut. This study investigates the anomalies and trends associated to extreme hydrological events, for both high and low flow events, using data from hydrometric stations in the Siret-Prut area, by applying quantile perturbation method (QPM) and innovative trend analysis (ITA) method, respectively. Also, a magnitude corresponding to each type of hydrological extremes, associated with ITA, was calculated. Data from 11 hydrometric stations was processed, spanning over 64 years of recordings (between 1955 and 2018). Results reveal more trends than expected, related to random occurrence for most of the measures of extreme flow characteristics. Annual and spring maximum flows show a decreasing trend in flow magnitude (for 90% of the hydrometric stations analyzed) with magnitudes ranging between −0.089 m3/s and −3,070 m3/s on annual level. Low flow magnitudes exhibit both increasing trends (in winter, for 55% of hydrometric stations), and decreasing trends during the spring season (for 64% of hydrometric stations). The results reveal that important investments in the associated infrastructure are required to reduce the impact of hydrological extremes, for both high and low flows.
Technical Report
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Lake Urmia, the twentieth largest lake in the world, is the most valuable aquatic ecosystem in Iran. The lake water level has decreased in recent years due to human activities and climate change. Several studies have highlighted the significant roles of climatic and anthropogenic factors on the shrinkage of the lake. Management policies for water resources harvesting must be adopted to adapt to climate change and avoid the consequent problems stemming from the drought affecting Lake Urmia, and rationing must be applied to the upstream water demands. This study analyzes strategies and evaluates their effectiveness in overcoming the Urmia Lake crisis. Specifically, system dynamics analysis was performed for simulating the water volume of Lake Urmia, and the Hadley Centre coupled model was applied to project surface temperature and precipitation for two future periods: 2021–2050 and 2051–2080. Six management scenarios were considered for decreasing the allocation of agricultural water demand corresponding to two options: (1) one-reservoir option (Bukan reservoir only), and (2) six-reservoir option. The net inflow of Urmia Lake was simulated for the two future periods with the IHACRES model and with artificial neural network models under the six management scenarios. The annual average volumes of Lake Urmia would be 30 × 10 ⁹ and 12 × 10 ⁹ m ³ over the first and second future periods, respectively, without considering the management scenarios. The lake volumes would rise by about 50% and 75% for the first and second periods, respectively under the management scenarios that involve strict protective measures and elimination of the effect of all dams and their reservoirs. Implementing strict measures would increase the annual average lake volume to 21 × 10 ⁹ m ³ in the second period; yet, this volume would be less than the long-term average and strategic volume. The human water use would be completely eliminated under Scenario 6. Nevertheless, Lake Urmia would experience a considerable loss of storage because of drought.
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Climate change has led human beings to take an interest in the study of meteorological and climatic phenomena. In fact, the main impact of climate change on different sectors of society is caused by extreme events since the occurrence of extreme events leads to more impact related to change in mean climate. Unfortunately, the West African region is vulnerable to extreme rainfall impact because its economy is based on rain-fed agriculture. This study examined the seasonal variability of extreme rainfall in West Africa. Eight (8) climate indices were chosen from among the 27 defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The nonpa-rametric Mann-Kendall test was used to assess the seasonal trends. The indices of the same types (frequency or intensity) were compared to assess the intra-seasonal variation of extreme precipitation. The results indicate that, regardless of the season, the Gulf of Guinea receives more rainfall than the Sahel. This phenomenon is due to the fact that the coastal part of West Africa is under the influence of evaporation which is observed at the Atlantic Ocean and during the monsoon, while the other part is dominated by the desert. Mann-Kendall's test revealed upward and downward trends during each season. The increase in extreme rainfall trends in the number of consecutive dry days suggests that droughts, due to global warming, could be observed and could have severe consequences in terms of water availability, energy supply, agricultural yields and ecosystems in West Africa. In addition, it can lead to the loss of biodiversity and health issues. It is therefore essential for policy-How to cite this paper: Tore, 151 Atmospheric and Climate Sciences makers or decisions makers to determine strategies and mitigation measures against climate change and its impacts on populations.
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Reliable information on the frequency and duration of excessive precipitation in floods, droughts, earthquakes, coastal floods, and hill torrents is critical to natural disaster planning and disaster risk reduction strategies. The current study examined precipitation on a monthly, seasonal, and annual scale at varying amplitudes. Moreover, the Mann–Kendall and Sen Innovatiove trend analysis (ITA) approaches are used to examine precipitation variations. This study aims to evaluate the Mann–Kendall and Sen Innovative Trend Analysis techniques to understand better how they apply to the topic under consideration. Overall, 84.16% of testing months showed trendless precipitation based on the MK trend test. Comparatively, the ITA monthly analysis showed statistically significant variation in 80% months and 88% considerable rate in seasonal perspective over the entire study regions. The research recognized that the Sen Innovative trend test outperforms the Mann–Kendall analysis in a range of circumstances. First of all, Sen Approach has simple assumptions, and the study of skewed distributions with fewer data could apply. Another benefit of using the ITA was that all data sets could be viewed on a graph, making it easier to see patterns and interpret the trends. Thus, the research recommends that the Sen Trend Method (ITA) analyze monthly, seasonal, and annual precipitation patterns to facilitate water resource scheduling and establish natural disaster strategies in the future.
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This paper presents an evaluation of the spatio-temporal patterns of hydrologic alteration induced by dam construction and precipitation variability in the Lancang River Basin of southwest China from 1957 to 2000. Analyses were conducted using the linear regression method, the Mann-Kendall test, and the Range of Variability Approach. The results indicate that there was considerable variation in the average monthly precipitation between the pre-and post-dam periods in the Lancang River Basin. Second, the magnitude of monthly runoff was strongly related to precipitation , which showed an up-down annual variation, and was significantly altered by dam construction and precipitation variability. In the modified series (hydrologic series with the precipitation impacts removed), runoff deviations between the pre-and post-dam periods became larger. Third, the extreme runoff cycles were influenced by dam construction and precipitation variability downstream from the dam, and the monthly maximum runoff increased from the pre-dam to post-dam period at all hydrologic stations. Fourth, the degree of hydrologic alteration (DHA) indicates that the precipitation variability not only affected the hydrologic regime of unregulated river reach but also modified the negative impacts of dam construction, which could provide a modest mitigation of the hydrologic alterations induced by dam construction, possibly decreasing the level of DHA. Last, the overall degree of hydrologic alteration in the observed series reached 25.2, 25.3, and 29.1 % for the upstream, midstream, and downstream areas, respectively. These results show that the hydrologic regimes of the Lancang River during the 1957-2000 period were affected by damming and precipitation variability, but the hydrologic alteration was relatively low in the upstream areas of the river without a dam.
Chapter
Lakes only cover 2.8% of the earth’s surface, which is under the risk of shrinkage and extinct in the context of global change and human activities. There are over thousand lakes distributed within the Changjiang River basin and serve significant value for social, economic, and river health, particularly Poyang Lake and Donting Lake, the top two largest freshwater lakes in China that locate in the middle–lower Changjiang River. However, the two lakes both risk the shift from accretion to erosion, early seasonal drying and water resources shortage in the recent decades. In this chapter, water and sediment budget of the two lakes, particularly the exchange process between lake and Changjiang River, are explored in detail. Dongting Lake and Poyang Lake both in the state of erosion and switch from being the sediment sink to depositional source, which have greatly mitigated the sediment hungry along the middle–lower reach and the estuary. However, the significant down cutting of the main stream enlarges the water level gradient between the lake and river, which induce larger outflow velocity from the lake and early appearance of low lake level. It should be the basic reason for the exposure of the Ming Dynasty “thousand-eye bridge”. Furtherly, less sediment from Changjiang River and lake basin to the lake, local sand mining, and sediment trapping behind Three Gorges Dam are dominated factors that induce accretion to erosion shift of the two lakes. Moreover, this chapter also proposes a way how to quantify respective contributions of natural forcings and human activities to impact lake changes. The work has vital research significance for the consequence of global dam construction, water and sediment exchange between lake and river, and lake evolution, which will be conductive to estimate the potential hydro-morphodynamic alteration of other large rivers of the world that are or will be affected by large dams.
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In this study, we assessed the impacts of climate variations on streamflow in 28 near-natural catchments in Iran. To this end, we analyzed the trend of annual streamflow, precipitation, and temperatures using the Mann-Kendall test and Sen’s slope between water years 1982 and 2011. We evaluated the frequency of precipitation in different classes, i.e., below 5, 5-10, 10-15, and above 15 mm/day. Our results indicate a decline in streamflow at 25 catchments with a rate of -5.66 to -0.19 mm/year. The annual precipitation amount had not decreased significantly, while the frequency of light precipitation events (<5 mm/day) increased. About 60% of the upward trend was significant. Mean temperature increased at all studied catchments with an average rate of 0.055 ℃/year. In short, our results indicate that increases in temperature and the frequency of light precipitation events are two leading factors of streamflow reduction across studied catchments.
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The study of teleconnection patterns is important to define and predict the temperature and precipitation anomalies and climate changes on a regional scale. In this study, the precipitation anomalies and intensities are analyzed in different El Niño–Southern Oscillation (ENSO) phases based on statistic-synoptic and dynamic approaches in Iran’s basins. For this purpose, a network of 717 meteorological stations and rain gauges was created during the period 1987–2015 in 6 basins and 30 sub-basins in Iran. The precipitation anomalies and intensities of these basins were statistically analyzed in different ENSO phases and Oceanic Niño Index (ONI), respectively. To analyze the synoptic and dynamic conditions in a medium El Niño, the negative and positive anomalies in the precipitation were examined in winter 2003 and spring 1992 using monthly European Centre for Medium-Range Weather Forecasts (ECMWF) data. Also, moisture flux convergence (MFC) was calculated and plotted for the lower (850–1000), middle (700–750), and upper (500–600) hPa troposphere layers using GrADS. The results of the precipitation anomalies showed positive and negative fluctuations of ± 100 to ± 150 mm in ENSO phases and ± 50 mm in the neutral phase. Consequently, the seasonal and annual precipitation anomalies were escalated in different ENSO intensities and their different phases. Moreover, it was found that the southeastern, eastern, and central plateau basins were slightly affected by the ENSO. Synoptic and dynamic analysis of precipitation anomalies also demonstrated the role of westward displacement (sea to land) and eastward (land to sea) components of Saudi Arabia’s high-pressure system. During the positive precipitation anomalies (with a significant eastward displacement to the east and settled on the Arabian Sea), advection of heat and humidity toward Iran and penetration trough in the Middle East caused the increased intensity and extension of precipitations.
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Evaporation loss is a key component of water resource management in arid and semi-arid regions where they are not uniformly distributed temporally. Also, due to the climate condition and physical characteristics of arid areas, a major part of rainfall will be out of reach in the form of flash floods and a few percent is recharged to groundwater aquifers. Rainwater harvesting system (RWHS) is considered as one of the most instrumental techniques that can save rainwater for domestic or agricultural uses. It is a technology used for collecting and storing rainwater in rooftops, land surfaces, or rock catchments using some simple techniques, such as natural and/or artificial ponds and reservoirs. In recent years, climate change has caused significant changes in the meteorological and hydrological components. Also, since precipitation is the main driver of RWHS, changes in its value and time can significantly change the operation of these systems. Therefore, in order to reach sustainable development, water resource management based on rainwater harvesting systems will be inevitable. These systems are moderately reliable methods to increase available water. The main aim of this study is the reliability assessment of rainwater harvesting systems designed for a future period (2017-2030) in Birjand, the center of Southern Khorasan Province, east of Iran.
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For the trend analysis of the annual, seasonal and monthly precipitation linear regression and Mann-Kendall (MK) tests at the 5% significance level were applied. In this study, precipitation data from two stations in Serbia for the 1949-2019 period were used. Results indicate that increasing trends of precipitation for the selected station can be observed but these trends were not statistically significant according to MK test. Then again, MK test has shown that only on Palić station during autumn precipitations have statistically significant increase during the observed period with a p value of 0.0441 at the significant level p=0.005.
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Mountain snowmelt is a critical water resource for achieving food and water security in drylands. Climate change impacts the snowmelt and consequently water resources reliability in downstream communities in drylands. Data limitation is one of the main challenges for assessing such impacts. This study assessed the trend in snow depth (SD), snowy day to wet day (SDWD), and snow phenology-related metrics in data-scarce snowy areas of Iran over 1987-2017. Furthermore, the contribution of temperature warming, precipitation and Arctic Oscillation (AO) anomalies to the snow metrics trends was investigated. The analyses were performed using the more accurate reanalyses selected between ERA-Interim and ERA5. The trend magnitude and significance were also assessed during the December-January-February (DJF), March-April (MA), and December-January-February-March-April (DJFMA) using the Sen’s estimator and Mann-Kendall (MK) test, respectively. Given the ERA5’s superiority, this product was employed for the trend and contribution analyses. The SD, SDWD and snow cover duration (Sdur) had a decreasing trend at more than 90% of study area. Except for snow cover onset date (Ds), MK detected a significant trend in the snow metrics at 40% or more of the studied regions. The more humid regions experienced a greater SD reduction. The SDWDDJF also decreased by less than 1% for the areas having average winter wintertime temperature below the threshold of -2.80 oC. The downward trend in Sdur was largely due to the earlier snowmelt rather than later Ds. A decline of 5 > day per decade was found for Sdur at the areas with DJFMA temperature below the melting point. The SD, SDWD and phenology metrics changes can be accounted for by temperature warming in most regions. The SDWD-AO relationship was statistically significant for the majority of the cases. The AO anomalies seem to impact SDWD via affecting wintertime temperature. The decrease of snow metrics indicates the occurrence of more severe and frequent dry snow droughts in the studied sub-basins. Thus, drought adaptation strategies need to consider the patterns of snow metrics in addition to total precipitation under global warming. The ERA5 outputs can be applied for evaluating snow drought under data scarcity.
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The slight change of sea surface temperature (SST) may affect the marine climate, the coastal climate, and the distribution of aquatic resources. Therefore, in order to understand marine climate change and aquatic resources, long-term investigation of SST change tendency is particularly important. Satellite remote sensing is one of the effective means to monitor sea surface temperature. In the face of a large number of remote sensing data sources, it is very important to choose an appropriate multi-source remote sensing data fusion method to improve the inversion accuracy and coverage of sea surface temperature. Big data technology is becoming an important force to promote the development of national economy. In the process of accelerating the penetration of big data technology into various fields of economy and society, it promotes the change of production mode and greatly improves productivity. After the accuracy of ensemble Kalman filter in sea surface temperature fusion is verified by sea surface temperature simulation based on big data, the fused SST is processed into abnormal form and decomposed by empirical orthogonal function, and its spatial and temporal distribution characteristics are analyzed. Based on the above big data, big data technology makes the business English translation industry usher in earth-shaking changes. Massive translation information based on big data platform can not only improve the efficiency of business English translation, but also improve its translation accuracy. However, due to the short time of big data technology, cultural and pragmatic differences, and other factors, the personal development of business English translators is limited. Therefore, by combining the basic connotation and existing problems of business English translation, this paper puts forward strategies to improve translation skills from two aspects of the main body of the teacher and the main body of the learner, in order to improve the accuracy of English translation of foreign trade vocabulary.
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Precipitation and temperature data, such as the homogeneity, trend, abrupt change, and periodicity, obtained at 40 meteorological stations in the Daqing River Basin from 1980 to 2015 are analyzed using the Mann–Kendall method, anomaly accumulation, Rescaled range analysis (R/S analysis) and wavelet transform. The regularity of climate change is studied to provide guidelines for the rational utilization of water resources. The results show that the annual precipitation has an insignificant upward trend and suddenly changes in 2007. The precipitation evolution can be divided into three types of periodicity, that is, 22–32, 8–16, and 3–7 year time scales, where the 28 year scale is the first main period of precipitation change. The annual average temperature shows a notable upward trend, with 1992 as the change year. The annual average temperature can be divided into three types of periodicity, that is, the 25–32, 14–20, and 5–10 year time scales, where the 28 year scale is the first main period of temperature change. In conclusion, the climate of the Daqing River Basin gradually turns into humid and hot climate. The results provide valuable reference for the assessment of the effects of climate change, and the management of water resources. HIGHLIGHTS The evolution of precipitation and temperature is analyzed, including the homogeneity, trend, abrupt change, and periodicity, making use of the anomaly accumulation, Rescaled range analysis, Mann–Kendall method and wavelet transform in the Daqing River Basin, North China.; The conclusion is that the climate of the Daqing River Basin gradually turns into humid and hot.;
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An investigation was conducted to detect the change-point years in the Southern Oscillation Index (SOI) and precipitation time series in Iran for the period 1951-1999 (49 years). Due to the unavailability of data, the record length of the precipitation time series was not consistent for all stations, varying from 34 to 49 years. The Pettitt- Mann-Whitney and Mann-Whitney-Wilcoxon tests were applied to determine the significance of the detected changes. The difference in SOI and precipitation amounts for the period before and after the change years was investigated. The coincidence of change-point years in the SOI time series and precipitation data was explored to evaluate the possible forcing effects of the El Niño-Southern Oscillation (ENSO) phenomenon on the suppression or enhancement of Iran's hydrological cycle. The results indicated that the mid 1970s are the most probable change- point years in the time series of Southern Oscillation Index (SOI) data. The frequency and intensity of El Niño events have increased since then. Consistent with this finding, precipitation data from both south-western and northern parts of Iran have also shown significant change years in or around the mid 1970s. Compared to the period before 1975, annual precipitation over most of the studied regions has increased. This increase was found to be more considerable in southern rather than northern districts. Seasonal precipitation amounts in southern regions have generally increased during autumn and winter and decreased in spring. On the other hand, for northern regions, precipitation has increased during summer and autumn and decreased throughout winter and spring. The most enhanced portions of the hydrological cycle in the southern and northern regions were centred on March and May, respectively.
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Attempts were made to study temporal variation in monthly, seasonal and annual rainfall over Kerala, India, during the period from 1871 to 2005. Longterm changes in rainfall determined by Man-Kendall rank statistics and linear trend. The analysis revealed significant decrease in southwest monsoon rainfall while increase in post-monsoon season over the State of Kerala which is popularly known as the “Gateway of summer monsoon”. Rainfall during winter and summer seasons showed insignificant increasing trend. Rainfall during June and July showed significant decreasing trend while increasing trend in January, February and April. Hydel power generation and water availability during summer months are the concern in the State due to rainfall decline in June and July, which are the rainiest months. At the same time, majority of plantation crops are likely to benefit due to increase in rainfall during the post-monsoon season if they are stable and prolonged.
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This paper quantifies the impact of the El Niño Southern Oscillation (ENSO) on the intensity and occurrence probability of dry and wet periods in Iran during boreal autumn and winter. Three phases (warm, cold, and neutral) were defined based on the Southern Oscillation (SO) status, and precipitation composites were constructed for each phase. The 30th and 70th percentiles of neutral phases were used as the thresholds for distinguishing normal conditions from dry and wet anomalies, respectively. The shifts in the amount and occurrence probability of these thresholds associated with warm and cold ENSO phases were then quantified. It has been found that, compared to the neutral period, warm events substantially reduce (increase) the intensity and occurrence probability of autumnal drought (wet) periods, particularly for southern districts. On the other hand, when a vigorous La Niña prevails, the chance of wet (dry) conditions is low (high) and the probability of severe autumnal drought is intensified. During winters of warm ENSO phases, although most of the country receives precipitation above the drought threshold, in the southeastern and northwestern districts of Iran, the risk of winter drought is high. For these phases, there is little chance that precipitation in these areas is above the wet threshold. A mechanism is proposed to justify the seesaw fluctuation of winter precipitation over the southwestern and southeastern Caspian Sea coasts. It is likely that the interaction between the Siberian high and ENSO controls rainfall variability over these coasts. It was found that during cold ENSO phases, winter drought (wet) periods in southern Iran are mostly coincident with wet (dry) conditions over the tropical Bengal Gulf (TBG) region. Such a strong coincidence was not found when rainfall in southern Iran and the Indian Ocean Extension region was compared. For western and northwestern parts of Iran, the probability and intensity of winter drought was found to be low during La Niña events.
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In this study we have examined the spatial and temporal variability of the annual precipitation observations over the Iberian Peninsula (IP) for 47 years and 51 stations. Empirical orthogonal functions (EOFs) were obtained in order to characterise the variability. Four regional precipitation regimes have been identified and the corresponding principal components (PCs) were subjected to spectral analysis in order to obtain the structure of the temporal variations. The relationship between the precipitation and circulation patterns is also investigated. The four leading PCs of annual precipitation are associated with the following patterns: East Atlantic (EA); North Atlantic Oscillation (NAO); Southern Oscillation Index (SOI); Scandinavia (SCAND). The spectra of the precipitation PCs show statistically significant oscillations coherent with those found in the time series of the teleconnection indices. A reconstruction of the time series as a function of the PCs is provided in order to obtain a characterisation of precipitation climatology over the IP.
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SummaryLong-term trends in annual, seasonal, and monthly mean temperature (abbreviated as AMT, SMT, MMT, respectively) in Japan are investigated. The magnitude of a trend is measured by assuming it to be linear. The statistical significance of a site trend is assessed by the Mann-Kendall (MK) with consideration of serial correlation. The statistical field significance of trends in three major climatic regions: Hokkaido (I), areas adjacent to the Japan sea (II), and to the Pacific Ocean (III), is evaluated by the bootstrapping test which preserves cross-correlation among sites.From 1900 to 1996, AMT increased from 0.51 to 2.77 C averaged across all 46 sites. At the regional scale, AMT increased by 1.38, 1.08, and 1.32 C in regions I, II, and III, respectively. The trends at both sites and regions are statistically significant even at the significance level (α) of 0.005. SMT increased from 0.47 to 3.69 C at all the 19 available sites with the highest increases in winter and spring. Except for a few series, the changes in SMT are statistically significant at α &equals; 0.01. The upward trends in SMT are statistically significant even at α &equals; 0.001 in both regions II and III. MMT at 19 sites increased within a wide range from 0.17 to 4.12 C. The increases are largest in the winter and spring months, and most of the site increases are statistically significant at α &equals; 0.05. The trends are statistically significant at α &equals; 0.025 and 0.001 in regions II and III, respectively. The trends in both SMT and MMT in region III are larger than those in region II.
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Two methods of estimation of the trend magnitude are compared: the parametric one (least-squares regression) with the non-parametric one (median of pairwise slopes). The comparison is carried out for seasonal and annual trends of ten climatic variables at a network of stations in the Czech Republic. We show that the difference between the two trend estimates is very small, falling well within the 95% confidence limits of the parametric estimate. The magnitude of the difference does not depend on the degree of normality of the distributions, with the exception of two variables, maximum temperature and precipitation, for which a slight dependence is observed. As a by-product, the normality of seasonal and annual means of the climatic variables is evaluated by the Kolmogorov-Smirnov one-sample test.
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Annual, winter and summer precipitation records for the period 1951–2005 from 160 stations in China were analysed using the rotated empirical orthogonal function (REOF), the Mann–Kendall trend test and the Continuous Wavelet Transform (CTW) method. The REOF method was used to analyse the annual and seasonal variability of precipitation patterns over China, the Mann–Kendall method was used to detect the temporal trend of the rotated principal components time series, and the continuous wavelet method was used to explore the periodicity of precipitation changes. In general, six coherent regions across China are identified using the REOF method: north-east China; the middle and lower Yangtze River basin; the Haihe River and the Liaohe River; north-west China; the middle Yellow River and the South-east Rivers (rivers in south-east China). Continuous wavelet transform results indicate that the significant 2–4 year and 6–9 year bands are the major period components. Precipitation in China is uneven in space and time, and its complex temporal structure and spatial variations are different in each season. The Mann–Kendall test results show that, in general, the middle and the lower sections of the Yangtze River are dominated by increasing annual, summer and winter precipitation. Increasing annual precipitation can be observed in north-west China. Increasing summer precipitation is found in north-east China and the Pearl River basin, and the South-east Rivers are dominated by increasing winter precipitation. The availability of water as a resource is in close association with precipitation changes; therefore, this research will be helpful to watershed-based water resource managers in China.
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The main characteristics of the spatial and temporal variability of summer precipitation observed in 40 rainfall stations of the Emilia-Romagna region in northern Italy, are analysed for the period 1922 to 1995. Non-parametric tests and Empirical Orthogonal Function (EOF) analysis were used as tools in order to achieve the paper’s objective. The Pettitt and Mann-Kendall tests detect shift points and trends in the precipitation time series, respectively, while the EOF analysis reveals the main characteristics of spatial variability. The Standard Normal Homogeneity Test (SNHT) was used to detect the inhomogeneity of the data set. Almost all stations exhibit an increasing trend with a systematic significant upward shift around 1962. The climate signal is more significant in the north-western, central and north-eastern part of the region, and the spatial extension strongly depends on the network density and the time period analysed. The change in summer precipitation is mainly due to a change during August and is confirmed by the SNHT test which does not reveal an inhomogeneity in the series. The first EOF pattern indicates that a common large-scale process could be responsible for summer precipitation variability in the Emilia-Romagna region. The second EOF pattern shows an opposite sign of climate variability between north-western and south-eastern areas. The Apennine mountains show the largest climate variability in the summer precipitation field.
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The influence of the Sea Surface Temperatures (SSTs) on the seasonal precipitation over northern and southwestern parts of Iran was investigated. The warm, cold and base phases of the SSTs were defined and the median of precipitation during each of these phases (Rw, Rc and Rb, respectively) was determined. The magnitude of Rw/Rb, Rc/Rb and Rc/Rw were used as criteria for the assessment of the effects of the alternation of SST phases on seasonal precipitation. The results indicate that in association with cold SST phase, winter rainfall is above median over western and central parts of the coastal region, central and southern parts of Fars Province and all the stations studied in Khozestan Province. On the other hand, the prevalence of warm SST phase has caused about 20% decrease in winter precipitation over the Caspian Sea coastal area and northern parts of both Fars and Khozestan provinces. In association with warm SST phase in winter, precipitation during the following spring was found to be above normal for all the stations studied in the coastal region of the Caspian Sea. The highest sensitivity levels were found in Bandar- Anzali and Astara for which spring precipitation has increased by 80% due to the dominance of warm winter phase. However, the occurrence of boreal cold SST events causes shortage of precipitation in the eastern parts of the coastal areas along the Caspian Sea. A Possible Physical mechanisem justifying the influence of the Caspian Sea SST on the Precipitation variability was introduced. According to this mechanisem, temporal and spatial variability of the Siberian High is forced by the fluctuations in these SSTs.
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Time-series of annual rainfall, number of rainy-days per year and monthly rainfall of 20 stations were analyzed to assess climate variability in and and semi-arid regions of Iran. The results showed mixed trends of increasing and decreasing rainfall, which were statistically significant (p<0.05 and p<0.01) only for Sabzevar and Zahedan stations by the Mann-Kendall test. Also, with the exception of Kashan and Torbat stations there was no statistically significant trend in the mean number of rainy-days per year. Increasing and decreasing monthly rainfall trends were found over large continuous areas in the study region. These trends were statistically significant mostly during the winter and spring seasons, suggesting a seasonal movement of rainfall concentration. Results also showed that there is no significant climate variability in the and and semi-arid environments of Iran.
Article
Annual, winter and summer precipitation records for the period 1951-2005 from 160 stations in China were analysed using the rotated empirical orthogonal function (REOF), the Mann-Kendall trend test and the Continuous Wavelet Transform (CTW) method. The REOF method was used to analyse the annual and seasonal variability of precipitation patterns over China, the Mann-Kendall method was used to detect the temporal trend of the rotated principal components time series, and the continuous wavelet method was used to explore the periodicity of precipitation changes. In general, six coherent regions across China are identified using the REOF method: north-east China; the middle and lower Yangtze River basin; the Haihe River and the Liaohe River; north-west China; the middle Yellow River and the South-east Rivers (rivers in south-east China). Continuous wavelet transform results indicate that the significant 2-4 year and 6-9 year bands are the major period components. Precipitation in China is uneven in space and time, and its complex temporal structure and spatial variations are different in each season. The Mann-Kendall test results show that, in general, the middle and the lower sections of the Yangtze River are dominated by increasing annual, summer and winter precipitation. Increasing annual precipitation can be observed in north-west China. Increasing summer precipitation is found in north-east China and the Pearl River basin, and the South-east Rivers are dominated by increasing winter precipitation. The availability of water as a resource is in close association with precipitation changes; therefore, this research will be helpful to watershed-based water resource managers in China.
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The suspected impact of climate warming on precipitation distribution is examined in the Yangtze River Basin. Daily precipitation data for 147 meteorological stations from 1961–2000 and monthly discharge data for three stations in the basin have been analyzed for temporal and spatial trends. The methods used include the Mann–Kendall test and simple regression analysis. The results show (1) a significant positive trend in summer precipitation at many stations especially for June and July, with the summer precipitation maxima in the middle and lower Yangtze River basin in the 1990s; (2) a positive trend in rainstorm frequency that is the main contributor to increased summer precipitation in the basin; and (3) a significant positive trend in flood discharges in the middle and lower basin related to the spatial patterns and temporal trends of both precipitation and individual rainstorms in the last 40 years. The rainstorms have aggravated floods in the middle and lower Yangtze River Basin in recent decades. The observed trends in precipitation and rainstorms are possibly caused by variations of atmospheric circulation (weakened summer monsoon) under climate warming.
Article
The Shannon Entropy method, Mann–Kendall method (M–K method) and linear fitted model were applied in this study to investigate the spatial and temporal patterns of trends of the precipitation in the Yellow River Basin (YRB) during 1960–2006. Results indicated that the precipitation possessed longitude zonality and had no clearly linear relationship with the latitude, it showed a decreasing trend in most of the precipitation stations, only two meteorological stations displayed upward trend in the YRB. The abrupt changes revealed by the M–K method mainly occurred to the south of 38 °N in the middle-lower reaches of the YRB. Furthermore, the abrupt changes occurred in the period ranged from 1963 to 1998 and the abrupt changes in the lower reaches appeared earlier than those in the middle and upper reaches of the YRB.
Article
The least squares estimator of a regression coefficient β is vulnerable to gross errors and the associated confidence interval is, in addition, sensitive to non-normality of the parent distribution. In this paper, a simple and robust (point as well as interval) estimator of β based on Kendall's [6] rank correlation tau is studied. The point estimator is the median of the set of slopes (Yj - Yi)/(tj-ti) joining pairs of points with ti ≠ ti, and is unbiased. The confidence interval is also determined by two order statistics of this set of slopes. Various properties of these estimators are studied and compared with those of the least squares and some other nonparametric estimators.
Article
An investigation of the relationships between Iranian autumn rainfall and the El Niño–Southern Oscillation (ENSO) phenomenon was explored for the period 1951–1990. A negative correlation between the Troup Southern Oscillation Index (SOI) and rainfall data was found for almost all of Iran. The relationships were found to be stronger and more consistent over some regions comprising the southern foothills of the Alborz Mountains, northwestern districts and central areas. For the other parts of the country, correlations were found to be either less significant or non-stationary. It was determined that the associations between SOI and rainfall over central parts of Iran have persistently improved for the recent period studied. The impacts of ENSO on rainfall amounts during low and high phases of the SO index were also studied. It was found that during El Niño episodes, the amount of rainfall over various parts of the country was several times more than during La Niña periods. The associations between SOI and surface air pressure data were found to be poor and insignificant. The possibility of rainfall forecasting was also explored and the results suggest that autumn rainfall could be predicted a season ahead for some parts of the country. A mechanism for the influence of the ENSO cycle on Iranian rainfall is suggested. Copyright © 2000 Royal Meteorological Society
Article
This study aims to determine trends in the long-term annual mean and monthly total precipitation series using non-parametric methods (i.e. the Mann–Kendall and Sen's T tests). The change per unit time in a time series having a linear trend was estimated by applying a simple non-parametric procedure, namely Sen's estimator of slope. Serial correlation structure in the data was accounted for determining the significance level of the results of the Mann–Kendall test. The data network used in this study, which is assumed to reflect regional hydroclimatic conditions, consists of 96 precipitation stations across Turkey. Monthly totals and annual means of the monthly totals are formed for each individual station, spanning from 1929 to 1993. In this case, a total of 13 precipitation variables at each station are subjected to trend detection analysis. In addition, regional average precipitation series are established for the same analysis purpose. The application of a trend detection framework resulted in the identification of some significant trends, especially in January, February, and September precipitations and in the annual means. A noticeable decrease in the annual mean precipitation was observed mostly in western and southern Turkey, as well as along the coasts of the Black Sea. Regional average series also displayed trends similar to those for individual stations. Copyright © 2005 John Wiley & Sons, Ltd.
Article
The non-parametric Mann-Kendall (MK) statistical test has been popularly used to assess the significance of trend in hydrological time series. The test requires sample data to be serially independent. When sample data are serially correlated, the presence of serial correlation in time series will affect the ability of the test to correctly assess the significance of trend. To eliminate the effect of serial correlation on the MK test, effective sample size (ESS) has been proposed to modify the MK statistic. This study investigates the ability of ESS to eliminate the influence of serial correlation on the MK test by Monte Carlo simulation. Simulation demonstrates that when no trend exists within time series, ESS can effectively limit the effect of serial correlation on the MK test. When trend exists within time series, the existence of trend will contaminate the estimate of the magnitude of sample serial correlation, and ESS computed from the contaminated serial correlation cannot properly eliminate the effect of serial correlation on the MK test. However, if ESS is computed from the sample serial correlation that is estimated from the detrended series, ESS can still effectively reduce the influence of serial correlation on the MK test.
Article
Trends in the time series of air temperature, precipitation, snow cover duration and onset of climatic seasons at ten stations in Estonia during 1951–2000 are analysed. Using the conditional Mann-Kendall test, these trends are compared with trends in the characteristics of large-scale atmospheric circulation: the NAO and AO indices, frequency of circulation forms according to the Vangengeim-Girs’ classification, and the northern hemisphere teleconnection indices. The objective of the study is to estimate the influence of trends in circulation on climate changes in Estonia. Statistically significant increasing trends in air temperature are detected in January, February, March, April and May, in winter (DJF), spring (MAM) and in the cold period (NDJFM). The trends in precipitation, as a rule, differ from station to station. Increasing trends are present during the cold half-year – from October until March – and also in June. Snow cover duration has decreased in Estonia by 17–20 days inland and by 21–36 days on the coast. The onsets of early spring and spring have shifted to an earlier date. Some important changes have occurred in the parameters of atmospheric circulation during 1951–2000. Intensity of zonal circulation, i.e. westerlies, has increased during the cold period, especially in February and March. Results of the conditional Mann-Kendall test indicate that the intensification of westerlies in winter is significantly related to climate changes in winter and also in spring. A negative trend in the East Atlantic Jet (EJ) index, i.e. the weakening of the westerlies in May has caused warming during that month. Decrease in northerly circulation, i.e. in frequency of circulation form C and in East Atlantic/West Russia teleconnection index (EW) is related to an increase in precipitation in October.
Article
Evaporation is an important component of the hydrological cycle and its change would be of great significance for water resources planning, irrigation control and agricultural production. The main purpose of this study was to investigate temporal variations in pan evaporation (Epan) and the associated changes in maximum (Tmax), mean (Tmean) and minimum (Tmin) air temperatures and precipitation (P) for 12 stations in Hamedan province in western Iran for the period 1982–2003. Significant trends were identified using the Mann–Kendall test, the Sen’s slope estimator and the linear regression. Analysis of the Epan data revealed a significant increasing trend in 67% of the stations at the 95% and 99% confidence levels. To put the changes in perspective, the trend in Epan averaged over all 12 stations was (+)160mm per decade. Trend analysis of the meteorological variables for examination of causal mechanisms for Epan changes showed warming trends in Tmax, Tmean and Tmin series in almost all the stations, which were significant over half of the total stations. On the contrary, no significant changes in precipitation were found approximately at all of the stations. Furthermore, a moderate positive correlation was observed between Epan and Tmax, Tmean and Tmin, while a inverse correlation was found between Epan and P data. The results indicated that the study area has become warmer and drier over the last 22years, hence the evaporative demands of the atmosphere and thereby crop water requirements have increased. KeywordsTrend analysis-Temporal variations-Class A pan evaporation-Air temperature-Precipitation
Article
 Series of annual and seasonal precipitation from 32 stations, distributed over all Italian territory and divided in two groups climatically homogeneous, were studied for the period 1833–1996. The series were checked for homogeneity and the time series analysis was performed with the Mann Kendall test and its progressive application according to Sneyers (1990). The results show considerably different trends for different seasons and zones. On a yearly basis a decreasing trend is present over all Italy, but it is statistically significant only in the Central-South. On a seasonal basis a decreasing trend is significant only for spring in Central-South, and for autumn in the North.
Article
The main characteristics of the spatial and temporal variability of winter and summer precipitation observed at 30 stations in Serbia and Montenegro were analysed for the period 1951–2000. The rainfall series were examined spatially by means of Empirical Orthogonal Functions (EOF) and temporally by means of the Mann-Kendall test and spectral analysis. The Alexandersson test was used to detect the inhomogeneity of the data set. The EOF analysis gave three winter and summer dominant modes of variations, which explained 89.7% and 70.4% of the variance, respectively. The time series associated with the first pattern showed a decreasing trend in winter precipitation. The spectral analysis showed a 16-year oscillation for the dominant winter pattern, around a 3-year oscillation for the dominant summer pattern, and a quasi-cycle of 2.5 years for the winter third pattern.
Article
A method is developed for summarizing the power of the parametric t tests and the nonparametric Spearman's rho test and MannWhi THETA against step and linear trends in a dimensionless 'trend number6 which is a functiontrend magnitude, standard deviation of the time series, and sample size. For the case of dependent observations, use of an equivalent independent sample size rather than the actual sample size is shown to enable use of the same trend number developed fore independent case.
Article
One of the commonly used tools for detecting changes in climatic and hydrologic time series is trend analysis. A number of statistical tests exist to assess the significance of trends in time series. One of the commonly used non-parametric trend tests is the Mann-Kendall trend test. The null hypothesis in the Mann-Kendall test is that the data are independent and randomly ordered. However, the existence of positive autocorrelation in the data increases the probability of detecting trends when actually none exist, and vice versa. Although this is a well-known fact, few studies have addressed this issue, and autocorrelation in the data is often ignored. In this study, the effect of autocorrelation on the variance of the Mann-Kendall trend test statistic is discussed. A theoretical relationship is derived to calculate the variance of the Mann-Kendall test statistic for autocorrelated data. The special cases of AR(1) and MA(1) dependence are discussed as examples. An approximation to the theoretical relationship is also presented in order to reduce computation time for long time series. Based on the modified value of the variance of the Mann-Kendall trend test statistic, a modified non-parametric trend test which is suitable for autocorrelated data is proposed. The accuracy of the modified test in terms of its empirical significance level was found to be superior to that of the original Mann-Kendall trend test without any loss of power. The modified test is applied to rainfall as well as streamflow data to demonstrate its performance as compared to the original Mann-Kendall trend test.
Article
Changes in catchment response as a result of climate change and/or variability continue to be of concern to hydrologists and water managers and thus identification and study of changes in rainfall as a major input into the hydrologic system remains pivotal in water resources management and planning for reliable input into modelling catchment response systems. An attempt has been made in this study to analyse long-term rainfall data obtained from five rain gauges (Kabompo, Kasempa, Mwinilunga, Mongu and Kaoma) located in the headstream regions of the Zambezi river basin in Zambia and to determine if these time series belonged to similar regime, have had any significant trends and if there was any homogeneity in trends among stations. To detect change in regime, the data were separately subjected to intervention analysis (using Cumulative Summation or CUSUM technique) and step change analysis (using rank-sum test) and subsequently the trend in each of the time series were determined using Mann–Kendall-statistic. The analyses undertaken to identify possibility of any intervention due to either natural and/or man-made causes, through the CUSUM technique, did not show signs of any major interventions except for Mongu station, where a change in regime was observed around 1980. This was even confirmed through step change analysis using the rank-sum test. Though the five stations showed marginal downward trends, these were not significant. Even, the test of homogeneity in trends observed at different stations showed homogeneity between them. Based on these findings, it was concluded that the rainfall data in the entire sub-basin belonged to a similar climate regime and the rainfall data for the entire period could be used for developing rainfall-response relationship except for Mongu, where the time series from 1981 onwards appear to have been subjected human/instrumental errors and needs to be investigated and updated.
Article
Reference evapotranspiration (ETo) is an important element of the hydrological cycle, and changes in ETo are of great significance for agricultural water use planning, irrigation system design and management. In this study, annual, seasonal and monthly trends in the Penman-Monteith ETo at 20 meteorological stations during 1966-2005 in the western half of Iran were examined using the Mann-Kendall test, the Sen's slope estimator and the linear regression. Annual analysis of the ETo series indicated a positive trend in 70% of the stations according to the Mann-Kendall test and the Sen's slope estimator and in 75% of the stations according to the linear regression. The magnitude of significant positive trends in annual ETo varied from (+)11.28 to (+)2.30 mm/year. On the seasonal scale, stronger increasing trends were identified in ETo data in winter and summer compared with those in autumn and spring. Meanwhile, the highest numbers of stations with significant trends were found in the monthly ETo series in February, while the lowest numbers of stations with significant trends were observed in November. Analysis of the impact of climatic variables on the significant increasing trend in ETo showed that the increasing trend was mainly caused by a significant increase in air temperature during the study period.
Article
The Southern Oscillation Index (SOI) is an acceptable scientific index for determining the strength of El Niño Southern Oscillation (ENSO) phenomenon. Because of the importance of reference evapotranspiration (ET0) in determining crop water demand, this study was conducted to assess the impacts of different ENSO phases on ET0 variability in some warm climates of Iran. For the estimation of ET0, the daily meteorological variables from a set of stations during a period of 50 years (1957–2006) were used in an aerodynamic energy balance approach and the correlation between SOI and the estimated ET0 values for two scenarios (with and without time lag) was constructed. Using Spearman, Pearson and Mann-Whitney approaches, the correlation coefficients (r) and the statistically significant relative differences between the mean ET0 values and their corresponding variations in each phase were verified. The results of seasonal ET0 showed that in 54% of the study sites, significant (P < 0.05) correlations between ENSO events and the ET0 variations exist. In the monthly timescale, 88% of the significant SOI-ET0 correlations experienced positive signs. In most of the cases, the spring and winter ENSO events influenced the ET0 values one or two seasons after the occurrence of the ENSO. On average, the mean monthly ET0 values during El Niño phases were 10.1 and 9.3% lower than the corresponding ET0 values during La Niña and normal phases, respectively. On the contrary, the mean monthly ET0 values during La Niña were 8.4% higher than that in normal phase. It was found that the degree of impact of ENSO on ET0 variability is sensitive to the timescale of analyses. Furthermore, the ET0 variations in warm arid sites were more sensitive to teleconnection impact of ENSO than the humid sites. Copyright
Article
Sixteen water quality parameters have been monitored at four stations located along the Maroon River during 1989-2008. The trend analysis was performed on seasonal and annual time-scales using the Mann-Kendall test, the Sen's slope estimator and the linear regression. The relationships of the water quality parameters to river discharge were also investigated. The statistical methods showed both positive and negative trends in annual water quality data. However, significant trends were detected by the statistical methods only in calcium, magnesium, sodium absorption ratio, pH, and turbidity series. The results indicated that the concentrations of the water quality parameters increased in spring and winter seasons, while the concentrations were diluted in summer and autumn seasons in the last two decades. Moreover, the highest numbers of significant trends were found in the spring and summer series, respectively. According to the regression analysis, most of the water quality parameters were negatively correlated with river discharge.
Article
In an earlier paper (Durbin & Watson, 1950) the authors investigated the problem of testing the error terms of a regression model for serial correlation. Test criteria were put forward, their moments calculated, and bounds to their distribution functions were obtained. In the present paper these bounds are tabulated and their use in practice is described. For cases in which the bounds do not settle the question of significance an approximate method is suggested. Expressions are given for the mean and variance of a test statistic for one- and two-way classifications and polynomial trends, leading to approximate tests for these cases. The procedures described should be capable of application by the practical worker without reference to the earlier paper (hereinafter referred to as Part I).
Article
Accurate estimation of regional evapotranspiration (ET) is essential for many agricultural water related studies. The data from 81 weather stations, with at least 30 years of data during the period of 1956–2000, were used for estimation of reference crop ET (ET0) in Iran. Monthly ET0 values were computed based on corrected mean air temperature for non-ideal conditions. This study focused mainly on the prediction of ET0 of 7 months of active crop growth season (April–October). Two main objectives of this study were: (i) prediction of mean monthly and annually ET0 in Iran using the suitable method from the three selected candidates, which are Hargreaves adjusted in 1985, adjusted Thornthwaite and Linacre methods, and (ii) study of spatial variation of annual ET0. Results showed that long-term mean annual ET0 vary between 830mm to over 3627mm across the country. The lowest monthly and yearly ET0 belonged to the Caspian Sea shoreline but highest ET0 belonged to the central and southeast parts of Iran. The mean annual ET0 in the southeast parts of Iran was about 33 times greater than that of its mean annual precipitation.
Winter rainfall in Iran: ENSO and aloft wind interactions
  • M J Nazemosadat
Nazemosadat, M.J., 2001a. Winter rainfall in Iran: ENSO and aloft wind interactions. Iranian Journal of Science and Technology 25, 611–624.
The impact of the Persian Gulf sea surface temperature on Iranian rainfall
  • M J Nazemosadat
  • I Cordery
  • S Eslamian
Nazemosadat, M.J., Cordery, I., Eslamian, S., 1995. The impact of the Persian Gulf sea surface temperature on Iranian rainfall. In: The Proceedings of the Regional Conference on Water Resources Management, Isfahan, Iran.