M. Nazeri Tahroudi; Y. Ramezani; C. De Michele; R. Mirabbasi Najafabadi
Abstract
Introduction: The erosion, sediment transport, and estimation problems in the streamflow are the most complicated and essential subjects in the river engineering studies. It is important to model and predict these parameters correctly to determine the effective life of the hydraulic structures ...
Read More
Introduction: The erosion, sediment transport, and estimation problems in the streamflow are the most complicated and essential subjects in the river engineering studies. It is important to model and predict these parameters correctly to determine the effective life of the hydraulic structures and drainage networks. On the other hand, river flow discharge is considered as one of the main components of water resources, which affects sediments. The increasing need of urban and rural communities for limited resources on the one hand, and issues related to climate change and atmospheric precipitation over the past few years, more and more attention is paid to the attitude of surface flows. The phenomena of erosion, sediment transport, and estimation of sediment load in the rivers due to its damages are one of the most critical and complex issues of river engineering. The primary goal of the frequency analysis is to relate extreme events to their frequency using probability distributions. In the frequency analysis of meteorological and hydrological events, the observed data would be analyzed for a long time at a basin. In these analysis, the assumption of independence and stationarity is considered. In fact, the basic assumption is that the studied data are spatially and temporally independent. The main issue is identifying actual distribution across different exiting distributions when using the frequency distribution to estimate the magnitude of the event. There is no appropriate general distribution for all types of rainfall regimes, river flows, etc. On the other hand, in order to analyze the frequency of a similar case, there is no agreement on the use of a particular distribution function. The experience gained so far in the field of statistical analysis of hydrological data shows that some data are more consistent with some specific statistical distributions.
Materials and Methods: In this study, the frequency analysis of total sediment load of the Zarinehrood basin was investigated in the south-east of Lake Urmia with consideration of the peak flow discharge at the Chalekhmaz hydrometric station during the statistical period of 1992-2016 using copula functions. At first, the correlation of these data was investigated using Kendall Tau correlation statistics, and the correlation coefficient was calculated as 0.75. In this study, Ali-Mikhail-Haq, Clayton, Frank, Galambos, Gumbel-Hougaard, Plackett, and Farlie-Gumbel-Morgenstern copula functions were used. In the conventional method of estimating the return period of extreme values, different statistical distributions are fitted on the studied data. After fitting the statistical distributions on the data series, the accuracy of each distribution is evaluated by one of the goodness of fit tests, such as the Kolmogorov-Smirnov test. After statistically controlling the goodness of fit test and determining the acceptable distributions, the root means square error (RMSE) and the Nash-Sutcliffe criterion are calculated to select the best fit model. Each of the fitting distributions that have the highest Nash-Sutcliffe (NS) criteria, and the lowest RMSE is chosen as an appropriate distribution.
Results and Discussion: With the fitting of 65 different distribution functions into the series, the Weibull distribution for total sediment load values and generalized Pareto distribution for peak flow discharge values were selected based on the evaluation criteria as appropriate marginal distributions. The results of the evaluation of the accuracy and efficiency of copula functions were studied by using root mean square error, Nash-Sutcliffe, BIAS, and AIC statistics. In this regard, the results were compared with the experimental copula functions. Finally, the Galambos copula was selected from the candidate copulas as superior copula function. The conditional and joint return period of the total sediment load based copula was proposed with a probability of 10 to 90 percent.
In univariate mode, the lowest probability of exceedance is 50%. In a bivariate mode, this possibility is presented more accurately. With a possibility of exceedance of 50%, it can be observed that the total sediment load at Chalekhmaz station during the studied period is about 400 tons per day. This is about 56% higher than its univariate mode, which is the average long-term of the total sediment load is closer to the Chalekhmaz station.
Conclusion: By comparing the bivariate analysis and its return period with univariate mode, the results indicated that more accurate calculation. Also the results showed the estimation of total sediment load is closer to the total sediment load of the Chalekhmaz station in bivariate analysis mode. Also, the results showed that in univariate mode, estimation of total sediment load at Chalekhmaz station was less than its actual value during the two-year return period. Regarding the results, the generated return curves can be used as the type curves for the management of water resources in the basin.
Mohammad Nazeri Tahroudi; Hossein Khozeymeh Nejad
Abstract
Introduction: Despite our scientific development and awareness of the consequences of regional and global climate change little attention has been paid to the effects of the changes in the Middle East and Central Asia yet. In the Middle East, climate change is a big challenge, especially if successive ...
Read More
Introduction: Despite our scientific development and awareness of the consequences of regional and global climate change little attention has been paid to the effects of the changes in the Middle East and Central Asia yet. In the Middle East, climate change is a big challenge, especially if successive droughts and persistent increase as well as growing demand for water and water shortages attention, the challenge take on a large scale. Iran is a vast country with a different climate Rainfall distribution. Also precipitation is influenced by air mass entering the country from the neighboring countries, so rainfall in different regions of Iran is heavily influenced by the situation in neighboring countries. The aim of this study is evaluation of the trend of annual and monthly precipitations of the South-West of Asia with modified Mann-Kendall test by considering the effect of autocorrelation.
Materials and Methods: In this study monthly and annual precipitation data of 4152 rain gauge stations in Iran and its 15 neighboring in a period of 1970-2014 was used and been downscaled to evaluate the trend of monthly and annual precipitations. In this study the monthly and annual precipitations time series of Afghanistan, Azerbaijan, India, Iraq, Kuwait, Oman, Pakistan, Saudi Arabia, Syria, Tajikistan, Turkey, Turkmenistan, Qatar, Yemen and Iran were used. The purpose of the trend test is to specify the presence or absence of ascending or descending order in the data series. Since there are assumptions in the parametric methods such as the normality, stationary and independent variables and this assumption is often not valid for hydrological variables, the nonparametric Mann-Kendall method that is applicable to the hydrological and meteorological studies can be used.
Results and Discussion: The results of evaluating the trend of annual precipitation of study stations in the period of 1971-2014 using the Mann-Kendall modified by omitting the effect of autocorrelation indicated that all of the regions of Iran has decreasing trend in annual precipitations and there are significant decreasing trend in the western regions of Iran and western areas of Caspian sea, some central and eastern regions of Iran in five percentage significantly. The rest of the decreasing trend in annual rainfall amounts included in the country has experienced. In annual terms in countries, that border the study area is faced with an increasing trend in annual rainfall amounts so that the country at the center of the crisis (lack of rain) is located. The southern part of India, southwestern Saudi Arabia, the northern region of Turkmenistan and the eastern regions of Afghanistan and Pakistan with the increasing trend in annual rainfall amounts over the 1970-2014 statistical has faced. The trend of monthly rainfall amounts for the month of January (second month) showed that the amount of rainfall during the month trend of central and eastern regions of the study area is decreasing. In February (second month of the year) rainfall conditions in the study area as well as in the country in terms of changes time has improved and areas of Iran is faced with increasing precipitation. Changes decreasing the amount of monthly precipitation in March moved to the West study area and focus a significant decline in rainfall in the western regions of Iraq and Syria and Iran. However, in May (fifth month) most regions of Iran, Turkmenistan, northwestern Turkey and the West areas of India has been facing a decreasing trend in rainfall amounts. Other areas showed an increase in precipitation. In July (the seventh month), India (regions Northeast and East), Pakistan, Qatar, Saudi Arabia, the South East of United Arab Emirates has significant decreasing trend in rainfall amounts. Focus of decreasing monthly precipitation for the August moved to India and much of the country is included. Unlike other months of the study, in the eighth month (September) process to reduce the amount of monthly precipitation moved to south western parts of the study area (South West Asian countries) and Saudi Arabia in this month is central of decreasing.
Conclusion: The results of the annual trend of precipitation in Iran indicated that in an annual scale the North West of Iran is faced with the significant decrease trend in rainfall. The annual rainfall across eastern and northern part Iran also has significant decreasing trend and Central regions had a decreasing trend of precipitation in the period of studied. Iranian medium-scale review of the annual and monthly precipitation showed that the annual precipitation is reduced about 1.06 mm per year that the average amount of it’s in the study area (South-West of Asia) equal to the reduction of 0.33 mm per year which represents more than three times decreasing precipitation of Iran's regional in a year as South West Asia. Also the results of evaluating the slope of trend line in different months indicated that in December, March, January, the Iran’s precipitations is most decreasing as average of annual precipitation in studiing regions about 5, 3 and 5 times respectively
Farshad Ahmadi; Mohammad Nazeri Tahroudi; Rasoul Mirabbasi Najaf Abadi
Abstract
Introduction: Climate change in the current century is an important environmental challenge facing the world. Increase in atmospheric concentration of greenhouse gases such as CO2 as a result of human activities has caused a change in a number of hydroclimatic parameters. Climate change and global warming ...
Read More
Introduction: Climate change in the current century is an important environmental challenge facing the world. Increase in atmospheric concentration of greenhouse gases such as CO2 as a result of human activities has caused a change in a number of hydroclimatic parameters. Climate change and global warming are the most important issues that have attracted many attentions in recent years. Climatic changes have interpreted as significant changes in average weather over a long period (Salari and ghandomkar, 2012). Global warming may cause drastic fluctuations in various processes and also it can significantly affect mean and variance of relative humidity, precipitation, solar radiation and etc. Global warming phenomena can change the components of the hydrological cycle and re-distribute the world's water resources in time and space. This may exacerbate desertification in arid and semi-arid countries such as Iran (Ahmadi and Radmanesh, 2014). Therefore, a large part of hydroclimatic researches has focused on temperature trend analysis at different spatial and temporal scales,
Materials and Methods: In the present study, the long-term temperature data from 24 climatological stations uniformly distributed over the West Azarbayjan province during 1981-2013 were used for investigating the temperature trends. The aim of trend test is to specify whether an increasing or decreasing trend exists in time series. Since parametric tests have some assumptions such as normality, stability, and independence of variables which may not be valid for most hydrologic series, the nonparametric methods are more preferred in meteorological and hydrological studies. In addition, the nonparametric trend analysis methods are less sensitive to extreme values compared to parametric trend tests. Nonparametric tests can also be applied regardless of linearity or nonlinearity of time series trend (Khalili et al. 2015). One of the most well-known nonparametric tests is the Mann–Kendall test (Mann 1945; Kendall 1975). Existence of more than one significant autocorrelation among data is long-term persistence (LTP). The presence of LTP in time series results in the underestimation of serial correlation and overestimation of the significance of the Mann-Kendall test (Koutsoyiannis 2003). In addition, Koutsoyiannis and Montanari (2007) pointed out that the Hurst phenomenon (Hurst 1951) is one of the most major sources of uncertainty in hydrometeorological trend analysis. Hamed (2008) studied the impact of LTP and Hurst phenomenon on the Mann–Kendall test, and Kumar et al. (2009) named it as the MK4. Since the MK3 test (Mann-Kendall method after the removal of the effect of all significant auto-correlation coefficients) is a generalized version of the MK2 (Mann-Kendall method after removing the effect of significant lag-1 auto-correlation), the MK3 and MK4 tests were used in this study and explained briefly in the following sections according to Kumar et al. (2009) and Dinpashoh et al. (2014). In the current study, the MK4 test was employed.
Results and Discussion: In this study, the mean monthly and annual air temperature trends were investigated using non-parametric Mann-Kendall test by considering the Hurst coefficient (MK4) for West Azarbayjan province. The Sen's slope estimator was also used for estimation of the slope of the trend line. Results indicate that 71% of selected stations (17 stations out of 24 considered stations) experienced a significant positive trend and only 7 stations (%29 of studied stations) did not show a significant upward trend in annual temperature time series. The highest increasing temperature rate (0.12 °C/Year) in annual timescale was found in Chehriq station. On monthly time scale, the numbers of months with increasing trends were 6 times greater than those with negative trends. Most of the stations had significant positive trends in mean temperature in February and March, Moreover, according to calculated Sen's slope, the mean air temperature of West Azarbayjan province increased by 0.05 °C/Year (1.65 °C during the study period).
Conclusion: The results show that the temperature of West Azarbayjan province substantially increased. The temperature increment can cause more drought occurrence and crop yield loss. As most of people’s income in this province depends on agricultural activates, temperature rise seems to have led to many social and economic problems in our studied area. Further, drying up of Urmia Lake and decreasing water input to the Urmia Lake basin can intensify the environmental problems.
Mohammad Nazeri Tahrudi; Farshad Ahmadi; Keivan Khalili
Abstract
Introduction: Given the fact that Iran is located in the center of the dryland of earth and is significantly influenced by the deserts of Central Asia and hot dry deserts of Arabia and Africa, is one of the most arid and low rainfall land areas.So is the proper management of water resources is of critical ...
Read More
Introduction: Given the fact that Iran is located in the center of the dryland of earth and is significantly influenced by the deserts of Central Asia and hot dry deserts of Arabia and Africa, is one of the most arid and low rainfall land areas.So is the proper management of water resources is of critical importance. The first step in the proper management of water resources is studying the factors that affected these resources including climate change. In fact climate change is a dynamic process in terms of time and place. Large parts of the Earth's climate as part of their normal variability in short-term and long-term experience. Short-term climate changes due to the difference in terms of average annual values of specific climate variables in average periods such as 30 years. Causes and effects of regional climate change in several parts of the world have been widely studied from various aspects. Among hydrological parameters, precipitation is the most important parameter in the complex hydrologic cycle. Follow the phenomenon of global warming on the Earth's surface, the rainfall pattern has changed.Trends of rainfall in different parts of the world have been studied by many researchers. Due to climate change in Iran and climate change in the Basin of Urmia Lake it seems that evaluation the trend of monthly and annual precipitation and its time of change point in the basin of Urmia Lake changes is important. The goal of this study is evaluatingthe trend and time of the change point trend of monthly and annual precipitation of rain gage stations in Urmia Lake basin.
Material and methods: Lake Urmia is the focus of surplus accumulation of surface currents all the rivers of the basin, with an area of approximately 5750 square kilometers and the average elevation of 1276 m above sea level and is located in the middle of the northern basin. Around of Lake Urmia there are 16 wetlands with an area of 5 to 120 hectares (some have dried up) that mostly have sweet or salty and fresh water and a high value of ecosystems.Urmia Lake Basin is situated in eastern of 44-14 to 47-53 and north of 40-35 to 30-38 coordinates. Urmia Lake Basin rainfall changes is 220 to 900 mm and have mean precipitation about 263 mm that added in central parts of the basin to the highlands.
Trend analysis: The aim of process test is to specify whether an ascending or a descending trend exists in data series. Since parametric tests have some assumptions including normality, stability, and independence of variables, where most of these assumptions do not apply to hydrologic variables, the nonparametric methods are more preferred in meteorological and hydrological studies. The nonparametric methods are less sensitive to extreme values compared to parametric tests in the examination of trends. Nonparametric tests can also be utilized for data time series regardless of linearity or nonlinearity of the trend (Khalili et al. 2014). One of the most well-known nonparametric tests is Mann-Kendall test (Mann 1945; Kendall 1975).
The modified Mann-Kendall test (MMK): The main assumption of Mann-Kendall test is that the sample data has no significant autocorrelation. However, some hydrological series might have a significant autocorrelation coefficient. When a series has a positive autocorrelation coefficient, there is an increased chance for Mann-Kendall test to reveal the existence of a trend in this series. In this case, the null hypothesis i.e. lack of trend is rejected, yet this hypothesis should not actually be. The modified Mann-Kendall test was presented by Hamed and Rao (1998) and has been used by Kumar et al (2009) for the analysis of the trend of Indian rivers. In this method, the effect of all significant autocorrelation coefficients is removed from the time series and is appliesto a series whose autocorrelation coefficients are significant in one or more cases.
Change point test: Pettittest is a non-parametrictest that was developedin 1979byPettit. Themethod is used in order tofind change points ina time series(Salarijazi et al 2012).In this study,thestatisticwas usedtofind asudden change intemperaturedata.Thisstatistic isatest with rank basis and without a distributionin orderto detectsignificantchangesin the mean of the time seriesanditis importantwhenthereis noassumptionabout the change time.
Results and discussion: In this study the trend of monthly and annual precipitation of rain gage stations that located in Urmia Lake basin were investigated using modified Mann-Kendall test. Z values of case study were calculated in two monthly and annual scales. The results of evaluation the trend of precipitation of rain gage stations of Urmia Lake basin showed that in October, December, January, February and March (five months of the year) the trend of precipitation is decreasing and the mean of Z values showed the less than zero values. In April and May there is no sensible changing in precipitation trend. Also the results showed that the March, April and May have a low failure rate and February, December and July have a most of change point of monthly precipitation data. About 60 percentages of the time of change point in precipitation trend are between 1992 and 1998. Also the results showed that two months of May and November there is no changing point in west Urmia Lake rain gage stations. In annual scale the time of changing trend is between 1992 and 1998.
Conclusion: The results of evaluation the trend of Lake Urmia precipitations showed that the Urmia Lake basin has a combination of decreasing and increasing trend in studied time period. The decreasing trend in precipitation often seen in west stations of the basin and west and south-west of Urmia Lake. The increasing trend also seen in south and north-east of Urmia Lake basin. Also the results of zoning the Z values of Mann-Kendall test showed that in annual scale the regions that influenced by polar-continental air mass that they entered Iran have a decreasing trend.
Keyvan Khalili; Mohammad Nazeri Tahrudi; Rasoul Mirabbasi Najaf Abadi; Farshad Ahmadi
Abstract
Introduction: Climate change in the current era is a very important environmental challenge. Our understanding of the impacts of human activities on the environment, especially those related to global warming caused by increased greenhouse gases indicates that, most probably, a number of hydro-climatic ...
Read More
Introduction: Climate change in the current era is a very important environmental challenge. Our understanding of the impacts of human activities on the environment, especially those related to global warming caused by increased greenhouse gases indicates that, most probably, a number of hydro-climatic parameters are changing. Based on the scientific reports, the average temperature of the earth has increased about 0.6 degrees centigrade over the 20th century and it is expected that the amount of evaporation continues to rise. In this case, the atmosphere would be able to transport larger amounts of water vapor, influencing the amount of atmospheric precipitations (21). Low precipitation and its severe fluctuations in the daily, seasonal and annual time scales are the intrinsic characteristics of Iran’s climates. Based on the research background, it seems that no comprehensive study has been conducted on concentration of winter precipitation in Iran. The aim of this study is to calculate the concentration and Trend of precipitation of Iranian border stations over the last half-century.
Materials and Methods: Iran with an area of over16480000 square kilometers is situated in the northern hemisphere and southwest of Asia. Almost all parts of Iran have four seasons. In general, a year can be divided into two warm and cold seasons. In this study, 18 stations were selected among more than 200 synoptic stations existing in the country, for investigating the concentration and precipitation trend.
PCI Index The PCI index has been proposed as an index of precipitation concentration. The seasonal scales of this index are calculated as equation 1(18):
(1)
Where Pi is the amount of monthly precipitation in the ith month. Based on the proposed formula, the minimum value of theoretical PCI is 8.3, indicating absolute uniformity in the precipitation concentration (i.e. the same amount of precipitation occurs every month).
Trend analysis The aim of process test is to specify whether an ascending or a descending trend exists in data series. Since parametric tests have some assumptions including normality, stability, and independence of variables, where most of these assumptions do not apply to hydrologic variables, the nonparametric methods are more preferred in meteorological and hydrological studies.
Results and Discussion: The PCI index was calculated using the monthly precipitation of the selected stations at seasonal and winter time scales over a 50-year period. This period was then divided into two 25-year sub-periods for the investigation of changes in average values of PCI (7). In the first 25-year span, the irregular precipitation distribution has been observed in the Bandarabbas station and its surroundings in winter season. In none of the studied stations, highly irregular precipitation occurred. The highest share of PCI was relatedto the precipitation average distribution class, and the northern, northwestern, and northeastern parts of the country have a uniform precipitation distribution. In winter, within the first 25-year period, the country had ideal conditions in terms of precipitation and its concentration in the mentioned regions. Within the second 25-year period, the intensity of irregular precipitation concentration decreased, as the regions that had confronted strong precipitation irregularities wereadded to regions with uniform concentration. At the seasonal scale and in winter, the country’s share of uniform distribution diminished in the second 25 years, and overall most parts of Iran have been covered by average precipitation distribution. The uniform precipitation distribution in recent years (second 25 years) has decreased in winter in such a way that no uniform distribution has been observed in the northeast of the country and uniform distribution belongedto the Caspian sea border strip, southern regions of west and east Azerbaijan stations (Urmia, Khoy and Tabriz stations) along with Kermanshah, Sanandaj, and Zanjan stations.
Trend analysis of the PCI In winter the Abadan, Ahwaz, Bandarabbas, Birjand, Kermanshah, Sanandaj, Urmia and Zahedan stations experienced an insignificant decreasing trend in PCI. At other stations, an insignificant increasing trend was observed in the PCI series. Overall, 9 out of 18 considered stations, witnessed increasing PCI trend implying increased irregularities in winter precipitation.
The results of Mann-Kendall trend test for precipitation Based on the results it can be observed that in winter Ahwaz, Gorgan, Khoramabad, Kermanshah, Ramsar, Rasht and Sanandaj experienced an insignificant decreasing trend in precipitation. In Khoy, Sanandaj, Tabriz, Urmia, Zahedan, and Zanjan stations, the decreasing precipitation trend in winter was significant. Overall, 12 out of 18 studied stations have been afflicted with a decreasing precipitation trend in winter.
Conclusion: Precipitation Concentration Index (PCI) is an index for determining the precipitation variations in a certain region and PCI analysis can reveal the accessibility to water in an environment. In this study, the PCI was used to analyze the precipitation concentration at two annual and seasonal time scales throughout the Iran (from 1961 to 2010). The PCI zoning results at the seasonal scale demonstrated that precipitation concentration had the same trend within the two 25-year sub-periods. These results also revealed a high PCI in provinces with low precipitation such as Zahedan. These stations, according to Oliver (18) classification, have irregular and sporadic precipitation duringwinter. Overall, the PCI analysis at the seasonal scale indicated that the regions covered by polar-continental, Europe-originated polar-continental and North Atlantic ocean-originated polar-continental have the best precipitation concentration throughout the country. The results of this index provided valuable information for water resources managers in regions with low-precipitation, consistent with research by Gozzini et al (7). The results of modified Mann-Kendall (MMK) test for PCI in Iran revealed a decreasing trend over the last 50 years. Based on the obtained results in winter, the Khoy, Sanandaj, Tabriz, Urmia, Zahedan, and Zanjan stations experienced a significant decreasing trend. The existence of an increasing trend in PCI albeit insignificant reveals changes in Iran's winter precipitations confirmed by Mann-Kendall test for precipitations in 18 studied stations. Overall, it can be concluded that the decreasing trend in Iran's winter precipitation has resulted in increasing PCI and thereby increased irregularities in winter precipitations, especially in winter season.
Mohammad Nazeri Tahrudi; Keivan Khalili; Javad Behmanesh; Kamran Zeinalzadeh
Abstract
Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes ...
Read More
Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes place as hydrological drought considered and studied. So the data on the quantity of flow of the rivers in this study is of fundamental importance. This data are included, level, flow, river flow is no term (5). Overall the hydrological drought studies are focused on annual discharges, maximum annual discharge or minimum discharge period. The most importance of this analysis is periodically during the course of the analysis remains a certain threshold and subthresholdrunoff volume fraction has created. In situations where water for irrigation or water of a river without any reservoir, is not adequate, the minimum flow analysis, the most important factor to be considered (4). The aim of this study is evaluatingthe statistical distributions of drought volume rivers data from the Urmia Lake’s rivers and its return period.
Materials and Methods: Urmia Lake is a biggest and saltiest continued lake in Iran. The Lake Urmia basin is one of the most important basins in Iran region which is located in the North West of Iran. With an extent of 52700 square kilometers and an area equivalent to 3.21% of the total area of the country, This basin is located between the circuit of 35 degrees 40 minutes to 38 degrees 29 minutes north latitude and the meridian of 44 degrees 13 minutes to 47 degrees 53 minutes east longitude. In this study used the daily discharge data (m3s-1) of Urmia Lake Rivers.
Extraction of river drought volume The drought durations were extracted from the daily discharge of 13 studied stations. The first mean year was calculated for each 365 days using the Eq 1 (14).
(1) (For i=1,2,3,…,365)
That Ki is aith mean year, Yijis ith day discharge in jth year and n is number of period years. After the extraction the 1 to ndays drought duration, the years with no data were complete with Regression or interpolation methods. After the extraction, data initial evaluation (Trend, Independence and Stationarity) and completed the drought volume data, these data were fitted by the common distribution functions and select the best function based on Kolmogorov-Sminnov test. To read more information about the data initial evaluations see the NazeriTahroudi et al (15).
Log Pearson type 3 distribution Log Pearson type 3 distribution and its parameters is (7 & 12):
(2)
After selectingthe best distribution function based on Kolmogorov - Smirnov test, estimated the selected function parameter to evaluate the return period. For this purpose, there are many methods such as moments, Sundry Average method (SAM), Logarithm of applied moments observations and maximum likelihood that in this study were compared.
Results and Discussion: In this study, using daily flow data fromstations studied; the drought volume of days 1 to 60 was extracted, corrected, and completed. Before fitting the extraction drought volume river data with distribution function, the mentioned data were investigated with Wald-Wolfowitz (Independence and Stationary), Kendall (Trend) and Wilcoxon (Homogeneity) tests and the results of these tests were accepted in two significant levels of 1 and 5 percentages. Before estimatingthe Log Pearson type III parameters, first the drought volume river data were modeled by the Easy Fit software and common distribution functions and Log Pearson type III was selected by the Kolmogorov – Smirnov test as the best function. Results of two Anderson Darling and Chi Squared tests foraccurate evaluation were added. After initial evaluation of data and statistic tests, the time series of drought Volume River data of the studyarea were fitted by log Pearson type III. To estimatethe Log Pearson type III parameters used the sundry average method and to investigatethe accuracy of this method, 3 methods (moment, maximum likelihood and Logarithm of applied moment observations) were used and 4 mentioned methods for all of rivers were calculated. The most river drought relating to Gadar-Chai river with 1742 million cubic meters low volume and the lowest of it relating to Mardoq-Chai river with 68 million cubic meters low volume in 10000 year return period. After Gadar-Chai river the most low volume of discharge relating the Zarineh-rood river. Two Zarineh-rood and Gadar-Chai rivers among other rivers have a higher average discharge. Log Normal III, Gamma, Wikeby and GEV distributions have a good fitting on river flows data and no difference in investigation models that corresponded with Mosaedi et al (13) and NazeriTahroudi et al (15). The results of Grifits (7) also introduced the Wikeby distribution has a better than Beta distribution. Lee (12) also with evaluation the rainfall frequency in the study the rainfall concentration properties in Chia-Nan (Taiwan) introduced the Log Pearson type III as the best distribution function between the common distribution function. Results of Chi-Squared test in methods of parameter estimation showed that all methods are acceptable.
Conclusion: Drought occurrence can be estimated bythe analysis of historical data for different regions and using the results of predicting problems can be reduced. In this research daily river flow of Lake Urmia basin applied to calculate drought volume of rivers. Log Pearson III distribution selected among current hydrological distribution functions for fitting drought volume of rivers. Using selected distribution function and Sundry Average Moment method for estimating parameters return period of drought from 2 to 10000 years extracted. Results showed that volume of drought for Shahar-chai , Barandoz-chai, Nazlu-Chai, Mahabad-Chai, Rozeh-Chai, Gadar-chai, Simineh-rood, Zola-chai, Aji-chai, Sofi-chai, Leilan-chai and Mardoq-chay rivers in the return period of 10000 years will be 92, 125, 228, 150, 110, 1742, 90, 77, 690, 280, 65, 68 Mm3 respectively.
Mohammad Nazeri Tahrudi; Keivan Khalili; Farshad Ahmadi
Abstract
Introduction: Climate change has been one the most important subject in studies in the recent decades. Precipitation is an effective climatic parameter in the municipal and rural studies and in the industry, architecture, agriculture, climate and other fields. Trend analysis of average monthly and yearly ...
Read More
Introduction: Climate change has been one the most important subject in studies in the recent decades. Precipitation is an effective climatic parameter in the municipal and rural studies and in the industry, architecture, agriculture, climate and other fields. Trend analysis of average monthly and yearly rainfall investigated in many studies, but less researches probe regional rainfall analysis. In this study average yearly precipitation data measured at 31 synoptic stations of Iran in the period of 1961 to 2010 used to study regional variations of precipitation. In this order station divided to five regions by fuzzy clustering. Then, using the regional Kendall method, trend of precipitation investigated at five regions and all of Iran.
Materials and Methods: Iran with an area of over 16480000 square kilometers is situated in the northern hemisphere and southwest of Asia. Almost all parts of Iran have four seasons. In general, a year can be divided into two warm and cold seasons. Iran with range annual precipitation of 62.1-344.8 mm is located between two meridians of eastern 44° and 64° and two orbits of northern 40° and 25°. In order to investigate trend of precipitation two Mann-Kendall and Regional Kendall tests used. Also to evaluate the regional trends the Fuzzy method applied to clustering the studied region. The classic form of Mann-Kendall test has been used in many studies. The null hypothesis (no trends) is accepted when , otherwise H0 is rejected and its opposite hypothesis, i.e. the existence of a trend is accepted (5, 13). To estimate regional trend, the mean S statistic of Regional Mann-Kendall introduced that was presented by Douglas et al (7). Fuzzy Clustering: Clustering the studied area was done using the Fuzzy clustering method. One of the first clustering methods that were based on the objective function and Euclidean distance was presented by Dunn in 1974 and then was generalized by Bezdak in 1981.The FCM clustering algorithm is modified type of K-Means clustering algorithm. This algorithm minimizes the variance of clusters (1). The assumption of this algorithm is that data are in a vector space and the objective of this algorithm is to minimize the sum of variance in the D v cluster.
Results and Discussion: In this section the results of decreasing and increasing trend of annual precipitation of Iran can be observed in order to the data that recorded at provinces synoptic stations in the 1 and 5 percentage significance levels. Isfahan Synoptic station detected an increasing trend insignificant level of 5 percentages and the East Azerbaijan synoptic station followed a significant and severe decreasing trends. In order to investigate regional trend it is needed to use the clustering methods. After investigation the trend of mean annual precipitation at each station, the studied area was clustered using the Fuzzy clustering method and then the regional trend of Iran’s precipitation was evaluated. At first the number of different clusters investigated using the geographic properties and mean annual precipitation of the studied area and then with attention to the correlation of precipitation series in each cluster, five clusters selected to investigate the regional trend of precipitation. Overall the results showed that about 67 percentages of synoptic stations in center of provinces detected decreasing trend in the recent half century. Increasing the precipitation almost accrued in the center and northern part of Iran and other areas detected a decreasing precipitation trend in the studied data period that this subject is corresponded with Azerakhshi and et al (2). The observed trends over Iran and almost all stations and provinces were downward trend. This decreasing trend of precipitation also observed in Iran in the two past decades by Khalili et al (13).
Conclusion: Result showed decreasing trend in the west, north of Iran at each station and regional scale. Results indicated also a significant downward trend at northwest, central and south-west of the country, non-significant downward trend in western of Iran and non-significant upward trends in northern regions and Caspian Sea margins in the regional analysis. The most decreasing trend of precipitation observed at the north west of Iran because of increasing temperature and climate changes in the recent years.
Mohammad Nazeri Tahrudi
Abstract
The application of statistical theory and probability analysis of hydrologic time series is assumed that the variables are normally distributed. Since many time series are not normal, it is required prior to any analysis and modeling, they looked normal. This conversion is done by Const. In this study, ...
Read More
The application of statistical theory and probability analysis of hydrologic time series is assumed that the variables are normally distributed. Since many time series are not normal, it is required prior to any analysis and modeling, they looked normal. This conversion is done by Const. In this study, using 12 common function to convert the normalized data, the average monthly rainfall in different regions of Iran into the data were normally distributed and the skewness coefficient, superior functions in each climate zone was Iran. The results showed that the data used in hot and dry regions with a square, as well as normal and the rest of the climate zones are likely to become a tropical area, Johnson and temperate regions selected for the inverse transform
