Streamflow trend analysis by considering autocorrelation structure,long-term persistence,and Hurst coefficient in a semi-arid region of Iran

Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.     

Iranian rainfall series analysis by means of nonparametric tests

The study of the trends and fluctuations in rainfall has received a great deal of attention, since changes in rainfall patterns may lead to floods or droughts. The objective of this study was to analyze the annual, seasonal, and monthly rainfall time series at seven rain gauge stations in the west of Iran for a 40-year period (from October 1969 to September 2009). The homogeneity of the rainfall data sets at the rain gauge stations was checked by using the cumulative deviations test. Three nonparametric tests, namely Kendall, Spearman, and Mann–Kendall, at the 95 % confidence level were used for the trend analysis and the Theil–Sen estimator was applied for determining the magnitudes of the trends. According to the homogeneity analysis, all of the rainfall series except the September series at Vasaj station were found to be homogeneous. The obtained results showed an insignificant trend in the annual and seasonal rainfall series at the majority of the considered stations. Moreover, only three significant trends were observed at the February rainfall of Aghajanbolaghi station, the November series of Vasaj station, and the March rainfall series of Khomigan station. The findings of this study on the temporal trends of rainfall can be implemented to improve the water resources strategies in the study region.     

Shift changes and monotonic trends in autocorrelated temperature series over Iran

Temperature data from 29 synoptic stations in Iran for a period of 40?years (1966–2005) were analyzed to test for the existence of monotonic trends and shift changes in the annual, seasonal, and monthly mean air temperature series using the Mann–Kendall and Mann–Whitney tests. The influences of significant lag-1 serial correlation were eliminated from data by the trend-free pre-whitening method prior to the trend analysis. The magnitude of the temperature trends was derived from the Theil–Sen’s slope estimator. It was found that annual mean air temperature increased at 25 out of the 29 stations, of which 17 stations showed significant monotonic trends. The magnitude of the annual mean air temperature trends averagely was (+)0.224°C per decade. Most of the stations with the significant positive monotonic trends had a significant upward shift change. The analysis indicated that the change point year of the significant upward shift changes was 1972 for the whole stations except the coastal ones. Moreover, the strongest monotonic increasing trends and upward shift changes were observed in summer especially in August and September. The spatial analysis of the mean air temperature trends revealed the highest numbers of significant monotonic trends in the big cities of Iran. These findings provide more insights for better understanding of regional temperature behavior in the study area.     

Spatiotemporal trends of aridity index in arid and semi-arid regions of Iran

The spatiotemporal trends of aridity index in the arid and semi-arid regions of Iran in 1966–2005 were investigated using the Mann–Kendall test and Theil–Sen’s slope estimator. The results of the analysis showed negative trends in annual aridity index at 55 % of the stations, while just one site had a statistically significant (α?=?0.1) negative trend. Furthermore, the positive trends in the annual aridity index series were significant at the 95 % confidence level at Bushehr and Isfahan stations. The significant negative trend in the annual aridity index was obtained over Mashhad at the rate of ?0.004. In the seasonal series, the negative trends in the spring and winter aridity index were larger compared with those in the other seasonal series. A noticeable decrease in the winter aridity index series was observed mostly in the southeast of the study area. In the summer and autumn aridity index, two significant positive trends were found.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

Recent trends in regional air temperature and precipitation and links to global climate change in the Maharlo watershed,Southwestern Iran

Trends in air temperature and precipitation data are investigated for linkages to global warming and climate change. After checking for serial correlation with trend-free pre-whitening procedure, the Mann–Kendall test is used to detect monotonic trends and the Mann–Whitney test is used for trend step change. The case study is Maharlo watershed, Southwestern Iran, representing a semi-arid environment. Data are for the 1951–2011 period, from four temperature sites and seven precipitation sites. A homogeneity test investigates regional similarity of the time series data. The results include mean annual, mean annual maximum and minimum and seasonal analysis of air temperature and precipitation data. Mean annual temperature results indicate an increasing trend, while a non-significant trend in precipitation is observed in all the stations. Furthermore, significant phase change was detected in mean annual air temperature trend of Shiraz station in 1977, indicating decreasing trend during 1951–1976 and increasing trend during 1977–2011. The annual precipitation analysis for Shiraz shows a non-significant decrease during 1951–1976 and 1977–2011. The result of homogeneity test reveals that the studied stations form one homogeneous region. While air temperature trends appear as regional linkage to global warming/global climate change, more definite outcome requires analysis of longer time series data on precipitation and air temperature.     

Long-term trend analysis for temperature in the Jinsha River Basin in China

On the basis of the mean annual and seasonal temperatures from 30 meteorological stations in the Jinsha River Basin (JRB) from 1961 to 2008, the temperature trends are analyzed by using Mann–Kendall test and linear trend analysis. There is an increasing trend in mean annual and seasonal temperatures during this period, and the increasing trends in winter seem more significant than those in the other three seasons. The mean annual temperature has increased by 0.0158°C/year during the last 48 years. There are more than 70% of stations exhibiting increasing trends for annual and seasonal temperatures. The increasing trends in the headwater and upper reaches are more dominant than those in the middle and lower reaches. The largest increase magnitude occurred in the low temperature area, while the largest decrease magnitude occurred in the high temperature area. The decreasing trends are mainly characterized for the maximum temperature time series, and summer is the only season showing a slight and insignificant increasing trend. All the time series showed a statistically significant increasing trend at the level of α?=?0.05 for the minimum temperature time series. As a whole, the increasing magnitude of the minimum temperature is significantly greater than the decreasing magnitude of the maximum temperature.     

Geographic Variation in Growing Season Rainfall during three Decades in Nigeria Using Principal Component and Cluster Analyses

Summary  Reports of changes in the seasonal and annual rainfall in Nigeria suggests that a more detailed analyses of the geographic extent of these changes and of their impact on agriculture could be of value. Variation in the growing season (April to September) rainfall from stations across Nigeria was analysed over the 30-yr period, 1960–90. Regression analyses were used to examine long-term trends. Principal component and cluster analyses were used to group stations with similar trends in standardised seasonal rainfall. Mean accumulated standardised seasonal rainfall were used to examine short- and medium-term trends for each of the groups identified. Significant (P ≤ 0.05) decreases in rainy season rainfall were found at 8 stations mostly in the Guinea and arid/semi-arid savannas of northern Nigeria, whereas no station showed significant increases. Examination of the monthly (April through September) rainfall showed that only three – Kano, Sokoto and Potiskum in the arid/semi-arid savanna – of the twenty-three stations used in the analysis had declining rainfall trends for each of the months April to September and subsequently declining seasonal rainfall trends. However, 12 to 15 stations had consistently declining rainfall trends in atleast some but not all the growing season months. However, a similar pattern was not the case in terms of increasing rainfall trends, where only one to three stations had consistently increasing rainfall trends in some but not all of the months from April to September. Stations that showed increasing rainfall trends were in the southern parts of Nigeria. Six groups with similar patterns in standardised seasonal rainfall were identified by Principal Component and Cluster analyses. For most of the groups, the period from 1967 to 1973 was that of consistently below average seasonal rainfall. However, the timing and extent of the decline varied with location. Common to stations in four of the six groups was a negative trend in seasonal rainfall for the period considered. The geographic variation in seasonal rainfall trends has tremendous agricultural significance since there are indications that the reliability of the season is decreasing from the humid forest zone with positive seasonal trends to the arid/semi-arid savanna with significant negative seasonal trends. Received June 24, 1998 Revised December 18, 1998     

Regional precipitation trend analysis at the Langat River Basin,Selangor, Malaysia

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982–2011 were examined at the 95 % level of significance using the regional average Mann–Kendall (RAMK) test and the regional average Mann–Kendall coupled with bootstrap (RAMK–bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km?×?5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.     

Time trend and change point of reference evapotranspiration over Iran

Identifying changes in reference evapotranspiration (ET_o) can help in future planning of crop water requirements and water resources for high water-use efficiency. This study analyzes the ET_o trends on a seasonal and annual timescale by applying various statistical tools to data from 41 Iranian weather stations during the period between 1966 and 2005. The Mann–Kendall test after removal of significant serial correlation was used to determine the statistical significance of the trends, and the change point in the ET_o time series was determined using the cumulative sum technique. The results showed that (1) the significant increasing trends of annual ET_o were observed at seven stations which are located in different parts of Iran, (2) the stations located at the southeast, northeast, and northwest corners of Iran experienced the highest positive change of annual ET_o, and (3) the changes in seasonal ET_o were most pronounced in the winter season, both in terms of trend magnitude and the number of stations with significant trends.     

Precipitation in Italy from 1833 to 1996

Summary  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. Received June 29, 1998 Revised October 16, 1998     

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955–2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann–Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.     

Trend analysis of precipitation in Jharkhand State,India

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901–2011) from 18 meteorological stations. Autocorrelation and Mann–Kendall/modified Mann–Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt–Mann–Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901–2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901–1949, which was reversed during the subsequent period (1950–2011).     

Detection of trends in precipitation during 1960–2008 in Jiangxi province, southeast China

Changes in precipitation exert an enormous impact on human life, and it is of vital importance to study regular patterns of meteorological and hydrological events. In order to explore the changing spatial and temporal patterns of precipitation amounts, precipitation extremes and precipitation concentration in Jiangxi province in southeast China between 1960 and 2008, several precipitation indices series were analysed using the Mann–Kendall test in this study. Our results indicate remarkable differences among the stations with negative and positive precipitation trends at the annual, seasonal and monthly scales, significant increasing trends are mainly found during January, August, winter and summer, while significant decreasing trends mostly are observed during October and autumn. For precipitation extremes, most precipitation indices suggest that both the intensity and the days of extreme precipitation are increasing; the mean precipitation amount, especially, on a wet day shows a significant positive trend. When it comes to precipitation concentration, the monthly rainfall heterogeneity shows an insignificant downward trend, while the contribution of the days with greatest rainfall displays an insignificant upward trend. Furthermore, the long-range persistence is detected for changing process of precipitation amount, extreme precipitation and precipitation concentration using the Rescaled Range Analysis.     

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31–162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann–Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878–1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970–2000 and 1989–2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.     

Trend analysis of maximum,minimum, and average temperatures in Bangladesh: 1961–2008

The present study is about the analysis of mean maximum and mean minimum temperatures carried out on annual, seasonal, and monthly timescales examining the data from 15 meteorological stations in Bangladesh for the period 1961–2008. Various spatial and statistical tools were used to display and analyze trends in temperature data. ArcGIS was used to produce the spatially distributed temperature data by using Thiessen polygon method. The nonparametric Mann–Kendall test was used to determine whether there is a positive or negative trend in data with their statistical significance. Sen’s method was also used to determine the magnitude of the trends. The results reveal positive trends in annual mean and mean maximum temperatures with 95 % significance. Trend test reveals that the significant positive trend is found in June to November in case of mean maximum temperature, but according to the mean minimum temperature, the situation is different and a significant positive trend was found from November to February. The analysis of the whole record reveals a tendency toward warmer years, with significantly warmer summer periods and slightly colder winters. These warming patterns may have important impacts on energy consumption, water supply, human health, and natural environment in Bangladesh.     

Long-term historic changes in climatic variables of Betwa Basin,India

In this study, trend analyses of historic past climatic variables were investigated for the Betwa basin located in Central India. In the serially independent climatic variables, Mann–Kendall test (MK test) was applied to the original sample data. However, in the serially correlated series, pre-whitening is used before employing the MK test. The long-term trend analysis showed several of the meteorological stations to exhibit a decreasing trend in annual and seasonal precipitation in the study area. Seasonal and yearly numbers of rainy days are decreased. However, onset of effective monsoon (except for Shivpuri and Tikamgarh stations) did not show any trend during the study period. For maximum temperature, five out of 12 stations showed a decreasing trend in monsoon season whereas almost all other stations showed an increasing trend in winter and no trend in summer season. For minimum temperature, only two stations of the basin showed a decreasing trend in monsoon and all other stations exhibited a significant increase in winter and summer season. The increase of winter temperature may adversely affect the growth of Rabi crop (wheat and mustard) in the study area. Potential evopotranspiration (PET) did not show any trend in monsoon, except for Jalaun and Jhansi stations, showing decreasing trends. Raisen and Vidisha stations showed an increasing trend in winter only, and the trend for other stations were random in nature. In summer, five out of 12 stations showed an increasing trend in PET. Results of this study can be employed in preparation of water resources development and management plan in the Betwa Basin.     

An investigation of near surface wind speed trends in arid and semiarid regions of Iran

Wind plays an important role on the ecosystems and hydrological cycles besides other meteorological parameters such as temperature, precipitation, sunshine, and relative humidity. It strongly affects evapotranspiration, especially in arid and semiarid regions where there are serious problems in regard to water resource management. Evaluating the wind speed trend can provide good information for future agricultural planning. This study was conducted in order to investigate the wind speed trends over 24 synoptic meteorological stations located in arid and semiarid regions of Iran from 1975 to 2005. Near-surface wind speed was trended by nonparametric Mann–Kendall test spatially and temporally in three time scales (annual, seasonal, and monthly). Then, Sen’s slope estimator was used to determine the amount of the changes; furthermore, 10-year moving average low-pass filter was applied to show general trends. Finally, the smoothed time series derived from the mentioned filter were classified in three clusters for each time series and then mapped to show their spatial distribution pattern. Results showed insignificant and significant, increasing and decreasing trends during the surveyed time. Wind speeds in less than 50 % of stations changed statistically in all time scales, and in most cases, the frequency of the upward trends was more than that of downward ones. The spatial distribution of significant wind speed showed that the increase mostly occurred in eastern part. Clustering gave us the turning point around 1990. Clearly, when clusters were mapped, they indicated the same pattern as the Z value maps derived from Mann–Kendall test which meant that the outputs of the mentioned method confirmed the other one. As the wind speed trends in different stations likely to follow the previous evapotranspiration (ET₀) trend results in Iran, it confirms that wind speed was an effective parameter on ET₀, even though other parameters should be considered too.     

Precipitation analysis over southwest Iran: trends and projections

Analysis of trends and projection of precipitation are of significance for the future development and management of water resource in southwest Iran. This research has been divided into two parts. The first part consists of an analysis of the precipitation over 50 stations in the study region for the period 1950–2007. The trends in this parameter were detected by linear regression and significance was tested by t test. Mann–Kendall rank test was also employed to confirm the results. The second part of the research involved future projection of precipitation based on four models. The models used were Centre National de Recherches Meteorologiques (CNRM), European Center Hamburg Model (ECHAM), Model for Interdisciplinary Research on Climate (MIROCH) and United Kingdom Meteorological Office (UKMOC). Precipitation projections were done under B1 and A1B emissions scenarios. The results of precipitation series indicated that most stations showed insignificant trend in annual and seasonal series. The highest numbers of stations with significant trends occurred in winter while no significant trends were detected by statistical tests in summer precipitation. No decreasing significant trends were detected by statistical tests in annual and seasonal precipitation series. The result of projections showed that precipitation may decrease according to majority of the models under both scenarios but the decrease may not be large, except according to MIROCH model. Autumn precipitation may increase with higher rates than other seasons at the end of this century.