---

Commonly almost in many research cases in which meteorological data is required the interpolation reconstruction have been used, because of lack or limitation of meteorological stations in the whole study area. The main object of present research is evaluation of different interpolation methods to prepare rainfall map of Esfahan province. We used normal rainfall data of province and regression, IDW, Spiline, Kriging methods. We used RMSE for determination of the best method rainfall Interpolation with comparing real and estimated data. The results show that the elevation has the lowest and the Kriging has the highest error in rainfall maps.

---

Frequency of cloudiness effects on the climate in the southern coasts of Caspian Sea are through increasing humidity, precipitation and cooling. The clouds format in different synoptic patterns and special thermodynamic and dynamic conditions. In this research, sea level pressure levels patterns were studied and compared in convective, nonconvective and heavier precipitation events in the Southern coasts of Caspian Sea. For this aim, on the basis of daily precipitation and with regard to 25 and 50 percent probability, precipitation events were divided into 2 groups of heavy and super heavy precipitations as well. Clouds synoptic indexes were grouped into two classes of convective and nonconvective clouds. The results show that there are 16 slp patterns in heavier precipitation groups. In general, Black Sea high pressure and Siberian high pressure generated heaviest and the most cover in convective and nonconvective precipitation events respectively.

---

Abstract In this study, the relationship between annual sunspot number (ASN) and annual precipitation totals (APT) has been investigated over the northern coasts of the Persian Gulf and Oman Sea using two statistical methods: cross-correlation function and contingency tables. Bushehr, Jask and Shiraz stations are alone stations in which long term annual precipitation records more than 100 years exist have in the south half of Iran. Precipitation records of these three stations were collected from three resources of Iran Meteorological Organization, Regional Water Organization of Fars Province and Smithsonian Miscellaneous Collections, respectively. The statistical gaps were filled with suitable regression models. Daily international sunspot numbers in 1871-2005 periods were prepared from the National Geophysical Data Center. Results indicate negative significant cross-correlation coefficients between 3-year lagged ASN and APT over two stations of Bushehr and Jask but nothing is found Whatsoever significant relationship for Shiraz station in none of lags. On the basis of this 3 year lags, for two stations of Jask and Bushehr have been constructed several contingency tables. The chi-square test was used to determine whether there was a dependency between observations. Also Kendal Tau-b coefficient can show the intensity of association between observations. Almost in all cases for Jask (Tau-b=-0.2 averagely), the Chi-square tests Were significant at the 5% level while there Were not a significant relationship for Shiraz and Bushehr but there Were minor cases in Bushehr (tau-b=-0.03 averagely).Inasmuch as a sunspot minimum has occurred in 2007 and 2008, therefore we Would expect that Oman Sea coasts precipitation during 2009-2011 Was higher than normal.

---

In the 6 to 8 June 2007 occurrence of the Gonu tropical storm caused heavy rainfall in the South East region was Iran and after heavy rainfall the severe floods occurred in South East Iran. In effects of Gonu super Cyclone in the 3-day period from 6 to 8 June 2007 of the South East region saw rain was showery precipitation. The total rainfalls in the study area to the number 503.5 mm were mature. Using various data related to atmospheric moisture in different levels, and low moisture supply source and quality and qualities in the event of rain caused by Gonu storm in 2007 was studied. studding of the atmospheric Moisture Flux Convergence (MFC) during Gonu storm in 6 to 8 June 2007, using the physical equations of related to the MFC in the atmosphere, map atmospheric MFC map's at levels 1000, 850, 700 and 500 hpa for 00z, 06z, 12z and 18z times have been illustrated and analyzed. The achieved results showed that the maximum convergence has taken place in 1000 and 850 hpa levels, and the other atmospheric levels had Lesser role in a rain storm days occurred in June 2007 Gonu. Also the results showed that moisture origin of precipitation in 6 June at 1000 and 850 hpa levels are the Indian Ocean, Gulf of Aden, and Arabian Sea and at other levels, are the Arabian Sea and Gulf of Oman. in June 8th the most effective moisture are related to the Gulf of Oman and Arabian Sea. Attention to the time of year and considering the moisture transfer path of from the warm seas, the South East meteorological stations of Iran, and with attention to convectional rainfall maps we can be note to this important point that and flooding rainfall caused by Gonu storm have occurred due to pass and dominance of a warm and humid air mass by the convection and convergence mechanism.

---

To doing this study, daily precipitation, minimum and maximum daily data from synoptic Kermanshah station during 1/1/1961 to 31/12/2011 have been used. In order to detection extreme temperature and precipitation, 27 indices recommended by Expert Team Climate Change and Indices (ETCCDI) and 6 other extreme indices have been used. Before any analysis, data have been quality controlled and pert values eliminated from data time series. To investigation climate change occurrence, recommended statistics tests by World Meteorology Organization (WMO) have been used. Two test Cumulative Density Test(CDT) and Worseley Likelihood Ratio Test (WLRT) applied in order to clarify the homogeneity and non homogeneity and jump in the indices time series. The significant of the jump in time series examined by Mann Whitney test and significant trend tested by Mann Kendal. So changing rate of trend for each 33 indices estimated by Sen Estimator. The results showed that cold extreme indices including FD0, TNx, TN10P, TX10P in Kermanshah are decreasing while extreme warm indices SU25, TR20, TX90P, TN90P, WSDI, TMIN Mean and TMAX Mean are increasing. The indices of R5, R10, CWD and PRCPTOTO are decreasing. In 1976 displacement of Kermanshah station occurred that result in jumping of DTR, TN10P and TMIN Mean indices. The behavior of these indices after jumping year is significant.

---

Precipitation acts as one of the most important elements of the climate. There has been much discussion and research in this regard. Spatial and temporal distribution of precipitation is very important in a place. This study aims at the understanding of the distribution of precipitation in specified time period for optimization of its use in agriculture, industry and human consumption. Estimation of flood and determination of the potential flooding and drainage system design, including the use of spatial and temporal distribution of precipitation is considered in the current research. To study the spatial and temporal distribution of precipitation in the city of Tabriz daily data from 11 stations were used for the period 1378 to 1388. To achieve the above objectives and zoning of the area in terms of precipitation, the first step was to prepare maps which were then converted to the data. Data were also used to remove cells outside the borders of original matrix that contained daily precipitation. The results showed that Tabriz county precipitation is separable into three distinct groups of with average precipitation, low precipitation and few others had some of the highest precipitation amounts.

---

Two deterministic methods [Radial Basis Functions (RBF) and Inverse Distance Weighting (IDW)], and two stochastic interpolation methods [Kriging and Co-Kriging] have been evaluated to estimate the annual precipitation in Ardebil Province. For this purpose, we used data taken from various stations across the province [4 synoptic stations, 1 climatological station and 24 rain gauges], over a decade (2005-1995). The performance of the above model was examined using cross validation and the indices of Mean Bias Error (MBE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE).Finally, to identify under-estimated and over-estimated areas of each method at elevations above the spatial distribution of stations, the output of each model was examined. The results suggested that Kriging model had lower errors than other methods and was more compatible with the elevation surfaces. Therefore, this method was identified as the best option for estimating f precipitation in areas without adequate data and intense topographic gradients in Ardebil Province.

---

Precipitation variability and drought - wet forecasting are related to changes in signals of atmospheric - oceanic.Considering this, the most important goal this study is to investigate the relationship of stations rainfall in the West of Country and the Eastern Mediterranean Oscillation. Hatzaky and Flokas identified two cores using methods of correlation analysis and principal component analysis (PCA) on a monthly and seasonal time series which were situated between the East Mediterranean and Northeastern Atlantic and at 300 and 500 hPa levels that named as the eastern Mediterranean pattern (EMP).To identify the relationship between rainful in west of Iran and eastern meditrranean oscillation,the values of this index which are standardized have been studied and compared with normalized data of country,s west stations rainful,using pearson correlation analysis,linear and polynomial process. The study results show that ther is a negative correlation between the stations precipitation of the north of the under study region and the above mentioned oscillation,and ther is a strong positive correlation in southern stations,that most of them are meaningful at 0.05 level. Also, this study proves that stations precipitation in southern half of the under study region in positive phases increases from 5 to 41 mms and in negative phases decreases from 4 to 20 mms.But, contrary to southern half, in the northern half the rainful increases up to 8 mms in negative phases and precipitation decreases in posetive phases.

---

To doing this research, daily precipitation data from 188 synoptic, climatology and rain gauges stations in and out of Kurdistan province during 21/3/1961 to 19/1/2011 have been used. Daily precipitation interpolated on 6*6 km pixels by Kriging spatial statistic over Kurdistan province. One matrix with dimension 18203*811 has been created that located time (days) on the rows and column were pixels. For each pixels total monthly precipitation has been calculated. Data of ten teleconnection patterns extracted from NCEP/NCAR.  Linear regression has been used to detection correlation between precipitation and teleconnection patterns. The correlation tested in 95% confidence level. The results showed that correlation between precipitation and teleconnection patterns is significant in 95% confidence level. The extent and intensity of significant correlation go to head in autumn season. The impact of South Oscillation Index (SOI), North Sea Caspian Pattern (NCP) and East Atlantic and West Russia (EAWR) is high in autumn. In cold seasons, SOI has negative correlation while NCP and EAWR have positive correlation with precipitation. In warm seasons two recent indices have negative correlation with precipitation. In total, increase sea level pressure and geopotential height in 500 hPa over Western European parts and decrease over eastern Mediterranean, Caspian Sea and north Caspian result in increase precipitation in Kurdistan province during cold seasons. In contrast, increase sea level pressure and geopotential height in 500 hPa over northern part of Caspian Sea result in increase precipitation during warm seasons. 

---

Temperature and precipitation are among the most important elements playing major roles in the study of climate change. These parameters have particular importance on water resources and natural ecosystems and also environmental, economic and social impacts. So in this research, we are about to simulate changes of temperature and precipitation in the Urmia Lake Basin where is facing environmental crisis and risk of drying is discussed for 2011- 2030 period. It was done by SDSM downscaling model. Meteorological stations evaluated are including four stations Saghez, Tabriz, Khoy and Urmia where have had full datum in the base period (1990 -1961). In the study, first of all, the efficiency of SDSM model was evaluated using observed data and station renovated data of National Center for Environmental Prediction (NCEP). Indices such as MSE, RMSE, MAE and the coefficient of determination and correlation were used. After ensuring the accuracy of the simulation model, climate parameters (rainfall, minimum and maximum temperature) was simulated using general circulation HadCM3 model under two scenarios A2 and B2 within 2030 for the study area. The results showed that the model has relevant ability to simulate temperature and rainfall. Based on the results of HadCM3 temperature and precipitation would be increased during 2020s (2011 -2030), comparing to the base period. In fact, minimum and maximum temperatures would be increased 29.7 mm, 0.3 and 1.4 degrees respectively.

---

Heavy precipitations and severe floods are one of the most important hazards affecting many parts of the country, including the northwest of the country, and it causes extensive damage to farms, gardens, houses, urban facilities, etc. In this research, the atmospheric conditions accompanying the occurrence of flood events in the northwest of the country on April 14, 2017 are studied. For this purpose, the data of sea level pressure, geopotential height, vertical velocity, zonal and meridional components at pressure levels of 850, 700, 500 and 300 hpa, as well as specific humidity in pressure levels of 1000 and 850 hpa(12 hours before the flood event) were obtained from European Centre for Medium-Range Weather Forecasts with a .075 -degree spatial resolution and the desired maps were drawn and the following results were obtained. The presence of severe gradient of pressure in the sea level in the northwestern region of the country and the high humidity in the lower atmosphere as well as the presence of western troughs at all levels of the troposphere exacerbate the meridian flows, and cause the subsequent formation of jets at a pressure of 700 to 300 hpa on the northwest region of Iran. On the other hand, extreme ascent, due to the severe vertical shear of the horizontal wind and the presence of a great deal of moisture, especially in the lower layers of the atmosphere, have created cumulonimbus clouds from a pressure level of 850 to 370 hpa, with lightning strikes at a pressure of 850 to 600 hpa. All of the above conditions have caused the instability and flooding and extreme precipitations in this region of the country.

---

Drought is a random characteristic of natural phenomena, drought about by the irregular deficit or shortage of available water, affects injuriously the plant growth and reduces their yield. Drought is not a physical but a biological phenomenon and should, be defined separately for each plant species and environment .To estimate the intensity and frequency of drought will help to reduce the injurious effect of drought.
In this study we used the water-budget methods and Thornthwaite’s aridity index and its standard deviation for Tehran city of Iran during 1951-2013 to show the frequency and intensity of drought effects in this place.
 The precipitation water evaporates as fast as it comes with the result that there is no accumulation of any moisture in the soil at any time of the year. The capital city of Iran, i.e., Tehran during its study period (1951-2013) experienced a total of 32 different types of droughts.
The result shows during this period this place is faced 32 times different type of drought on the five time disastrous and from the years of 2000 its severity and intensity is increased so far 2011 and 2012 the station is affected disastrous drought.
 

---

Introduction: The climate of the earth has begun to warming since 1980’s which has created very serious problems for the human living and natural environment. As a result the study of the global warming and its solutions has become the focal point of the climate change research all over the world. The climatologists are trying to understand, predict and finally give solutions to it. Many different models have been developed to predict and project the future climate conditions among which the Regional Climate Model is to some degree has lower values of uncertainty. The impacts of climate change is relatively higher in the
naturally dry climate of the Middle East including Iran. Here the main parameters of the climate that is temperature is increasing and precipitation decreasing. As a result the projection and understanding of these two elements are very important for the region and Iran. For this reason this studyhas focused on the efficiency of the Regional Climate Model in projecting the future climate of the region and Iran.
 
Data and Methods: In order to test the efficiency of RegCM 4.3the monthly temperature and precipitation
Data were extracted for the window 24N-40N and 43E-64E from the ECMWF database with spatial resolution of 2.5 degrees. These data were compared and corrected with the station data of Bandar Anzali, Bandar Boushehr, Mashad, Tehran, Yazd, Zahedan, Khorramabad and Zanjan . The simulated model data for RegCM 4.3were extracted for the same period and area with the same spatial resolution. Both data were transported into the Matlab environment and compared.
Results and Discussion: Results of simulated RegCM 4.3data were compared withobserved data of eight stations. The temperature data were slightly (about 2 degrees C) more than observed data. But the precipitation projections were somewhat complicated. The values of rainy stations such as Anzali were overestimated ( about 257 mm) while  that of most dry stations such as Zahedan were underestimated (about 58 mm).  But the RegCM 4.3 simulations were the same as the observed data inthe normal stations such as Zanjan. The results showed that the RegCM 4.3is suitable for projecting temperature data more than the precipitation. This is in agreement with the findings of many other studies. 
 

---

Introduction
Annual precipitation forecasting usually guarantees success in sustainable management of water resources and watersheds in cases like determination of rain-fed and water cultivation area and water resources consumption planning. Although precipitation does not follow a specified pattern; however, it has a correlation with some climatic parameters. If these parameters were easy to find, simple applicable models could be developed to predict annual precipitation. One of the simplest methods for predicting annual precipitation is regression models. The block box models such as Artificial Neural Network (ANN) has also been used for precipitation forecasting.  This study was an attempt to predict annual precipitation using some climatic parameters by multiple linear regression and ANN models.  
Materials and Methods
Chaharmahal-Bakhtiari and Yazd provinces are located in the southwestern and central part of Iran with semi-arid and arid climate, respectively. Mean annual precipitation of these two provinces are 560 and 110 mm, respectively. Meteorological data of the weather stations belong to 2001-2011 in Chaharmahal-Bakhtiari and 2003-2013 in Yazd province; respectively, were analyzed. Various parameters were calculated for predicting annual precipitation using long-term daily precipitation and temperature data of the meteorological stations. Among the parameters, total precipitation in the first half of the water year (R_6m, mm), time to 47.5 mm cumulative precipitation since the beginning of autumn (t_47.5, day), long-term mean annual precipitation (R_m, mm), average summer temperature of the preceding water year (T_su, °C) and average temperature of preceding summer and current autumn of water year (T_su.au, °C) that had a high correlation with annual precipitation, were used in multiple linear regression (MLR) models and artificial neural network (ANN) techniques. normalize mean square error (NRMSE) and degree of agreement (d) were used to evaluate accuracy of the models for predicting annual precipitation.
Results and Discussion
Results showed that the obtained MLR models were significant at a probability level of less than 0.01. Results also showed that both methods (MLR and ANNN) could accurately estimate the annual precipitation. Evaluation and verification of the models with NRMSE values less than 0.3 and d values greater than 0.8 confirmed the performance of the models. The best topology of the ANN network in the study was a multiple layer perceptron network with one hidden layer and two neurons and sigmoidal activation function. The findings of the study support the fact that higher temperature in summer and autumn was a sign of higher and lower annual precipitation in Chaharmahal-Bakhtiari and Yazd Provinces, respectively. Besides, higher time period to 47.5 mm cumulative precipitation from the beginning of autumn implies fewer amount of annual precipitation.  
Conclusion
This study showed that annual precipitation could be predicted by MLR and ANN methods in both arid and semi-arid regions with acceptable accuracy. According to the results, a rainy water year will be expected continuing a warmer summer and autumn in Chaharmahal-Bakhtiari Province; however, there will be a dry water year in Yazd Province followed by these conditions. Furthermore, if 47.5 mm cumulative precipitation takes a longer time since the beginning of autumn annual precipitation will decrease.
 

---

One of the important issues in recent years is the drying up of Zagros oak forests and since Zagros oak forest is one of the natural resources of Ilam province, this issue needs to be evaluated. The main purpose of this study is to analyze the spatial relationship between drought in Zagros forests and droughts in the area. For the spatial and temporal analysis of drought in Ilam province, Standard Precipitation Index (SPI) for the period 2000 to 2016 was used from the rainfall data of the province and for spatial analysis of oak forest drying relationship using spatial pattern distribution models, Moranchr('39')s spatial autocorrelation model. A systematic random sampling of 15 m² of dried oak trees at the surface of the area was performed using GPS and simulated using Landsat satellite images with 15 m² resolution. The results of Moran model showed that oak drought has a cluster pattern and the Moran index with SPI coefficient was 0.914532 in positive drought zone and 0.938461 in severe drought zone and 0.985233 in relatively dry zone and 996512 in near-normal drought zone. The mean Moran index was 0.956758 with a significant level of 0.00001 indicating the effect of drought on oak dryness.

---

  Extreme precipitation is one of the climatic risky behaviors that are associated with abnormalities and environmental-human consequences. This study has investigated daily rainfall  of 20 rain gauge and synoptic stations over 30 years (1987-2016) in the West of Gilan province, to determine the trend of extreme precipitation changes. In this regard, non-parametric Mann-Kendall test, Sen's Estimator slope, Poisson distribution, and IDW interpolation have been applied, respectively, to determine the existence of trend, significance, to determine the probability of rainfall occurrence   and to identify spatial patterns of precipitation occurrence with different probabilities. The results suggested an increasing trend in Astaneh-ye Ashrafiyeh, Bandar-e Anzali, Masuleh, and Astara and an extreme decreasing trend in Bash Mahalleh due to the Mann-Kendall test. Studying the significance or insignificance of changes trend by Sen indicated that this trend has been significant in Mashin khaneh, Bash Mahalleh, and Punel Stations; and the null hypothesis, that is, the insignificance of change, was rejected. Sen's Method revealed that there were no significant changes in other stations, and their randomization will be confirmed. To this end, the spatial probability distribution of  to  indicate kernel probability displacement for different x.  The maximum probability to various occurrences has been at Masuleh station and Poisson distribution is a proper assessment of precipitation in this region.
 

---

The aim of the study was to investigate the conditions of atmospheric circulation patterns in the very wet months of Syria. By calculating the standard precipitation index (SPI) and using the precipitation data of 16 Syrian synoptic stations in the statistical period of 2016-2017, very wet months were identified. Then, combined maps of sea level pressure parameters, geopotential height and wind components at 850, 700, 500 and 250 hpa levels, as well as specific humidity at 850 level and 700 hpa level omega from NCEP-NCAR gridded reanalysis data were produced and were used to study the synoptic atmospheric patterns of very wet months. The findings show that formation of a deep trough is the most important model for creating very humid Syrian months, which is centred almost between eastern Turkey and western Egypt, and Syria is located in front of this trough. This trough, especially in the middle and upper atmospheric levels, causes to falling cold air on the eastern Mediterranean. The moving polar trough pattern at 700 and 500 hpa levels towards lower latitudes had caused the aforementioned advections. Formation of negative values of omega and rising air currents, along with southwest winds at sea level and other levels over Syria, have caused above-average rainfalls.

---

Introduction: The climatology of Thunderstorms is an important component in research for severe weather. Thunderstorms are among the first meteorological phenomena, which have attracted human attention (Khorshiddoust et al, 2017). Thunderstorms are dangerous and one of the most important, abundant and severe atmospheric hazards. Thunderstorms can be associated with a number of hazards. This phenomenon is associated with severe storms, showery precipitation, hail, and thunder and lightning. Heavy rains can lead to flash flooding events. High winds generated by thunderstorm can cause damage to homes, overturn vehicles, uproot or damage trees, causing wide spread power outages. Generally, researchers consider the intense weather instability as a result of convection in lower levels of the atmosphere with high levels enough of humidity. Usually statistic instability, the humidity of lower levels of the atmosphere and lifting mechanisms near the ground are the main factors leading to convection. Moreover, the combination of three factors, instability, humidity and convergence in lower levels of the atmosphere plays an important role in increasing the possibility of thunderstorms (Masoompour Samakosh et al, 2016). In connection with thunderstorms extensive research work has been carried out in Iran and the world in including: Chignon et al. (2001), Manzato, (2003), Doswell et al. (2005), Henderson (2006), Sadeghi et al. (2006), Romero et al. (2007), Schmeits et al. (2008), Siedlecki (2009), Sanaeinejad et al. (2010), Tajbakhsh et al. (2010), Ghavidel Rahimi (2011), Masoompour Samakosh et al. (2014)  Masoompour Samakosh et al. (2016), Tavousi (2016), Dehani (2017), Khorshiddoust et al. (2017), Tavousi  et al. (2016).The city of Kermanshah is the capital of the Kermanshah province and is located in the west of Iran. The latitude of the Kermanshah meteorological station is 34: 21 N and the longitude is 47: 9 E and altitude 1318.6 meters. Kermanshahchr('39')s climate is classified as warm and temperate. The winters are rainier than the summers in Kermanshah. The climate here is classified as Csa by the Köppen-Geiger system. The average annual temperature is 13.3 °C in Kermanshah. The average annual rainfall is 437 mm (Climate data for cities worldwide, 1982-2012). Kermanshah has annually been witnessing a variety of thunderstorms systems and associated precipitation. This city has suffered lots of damage resulted from the phenomena caused by thunderstorms.
Matherials & Methods: In this research, instability conditions of heavy precipitation in Kermanshah are investigated. For this purpose, high atmospheric instability indices such as lifted index, showalter index, K index, convective available potential energy (CAPE) index, precipitable water capacity (PWC) and thermodynamic diagram Skew-T Atmospheric is studied using the radiosound data. The data of upper atmosphere (radio-sound data), available in the website of Wayoming University, were applied to investigate the thermodynamic features of the occurred thunderstorms. The thermodynamic features include KI, SI, TT, LI, CAPE indices and skew- T chart in RAOB software.
Discussion of Results & Conclusions: The results showed that the valuses of K index in days with heavy precipitation were 20.7-34.8 and in a day before 20.9 - 37.7. The lowest values recorded in January, February and March, and the peaked were in November, April and May. This suggests heavy precipitation in winter with less instability and is accompanied by more instability in the fall and spring. The lifted index in 1997 and 2002 in days has heavy precipitation were 0 to -2.2, which represents the probability of storms with rain and snow showers. The value of the lifted index in a day before precipitation on November 1, 1993 was zero to -2 and on May 12, 1993, November 21, 1994, and April 18, 2002 from -2 to - 5, which represents the probability of thunderstorm occurring. Study of precipitable water capacity (PWC) in the peak days of precipitation and one day before is showed that is most matches with the days that air convection has been intense. On peak precipitation days, the PWC was between a minimum of 35/7 on16 January 1997 and a maximum of 19.92 on 2 November 1993. The wind speed has been between 40-50 knots in all days, except on March 11, 2005, the wind had a speed of about 80 knot. The Prevailing winds are southwest which shows the direction of the Westerly winds system to this area. Investigation of thermodynamic charts showed that rapid convective ascent of available potential energy depending on the weather in the region has been so high and caused the weather to approach three days in advance to the upper layers of the atmosphere and atmospheric turbulence was created for the region.

---

Modeling of water flowing into dam reservoir is one of the most important steps in watershed management, exploitation of dams, flood warning systems, and priority areas for erosion and sedimentation. In fact, optimal management of water resource systems, such as dams requires the accurate prediction of inflow into the dam reservoir. Therefore, it is essential to estimate this parameter more accurately. Several methods have been developed to predict the dam reservoir inflow. In the current study, the intelligent Support Vector Machine (SVM) and Nero-Fuzzy Adaptive Inference System (ANFIS) methods are used to estimate the inflow rate of the Sattarkhan dam and the effect of different input parameters such as monthly precipitation, discharge and temperature on improving the models accuracy is investigated. The results showed the desired efficiency of the Meta model approaches in estimating the monthly inflow into the Sattarkhan dam reservoir. The best results for the test data, in the state of modeling based on monthly discharge and precipitation was obtained the values of R= 0.878 DC= 0.782, RMSE= 0.063 and in the state of modeling based on monthly temperature, precipitation and discharge was obtained the values of R= 0.805, DC= 0.708 and RMSE= 0.108 were obtained. According to the results, the model with the parameters of the monthly discharge and precipitation leads to more accurate results.

---

The complex process of rainfall-runoff relationship in each catchment area is controlled by numerous known and often unknown factors in the time and place dimension. One of these factors is precipitation. Precipitation is the most important atmospheric phenomenon that is directly affect the hydrological cycle, especially in discharge changes. In this study, in order to investigate the relation between rainfall and runoff and investigating their temporal and spatial variation, the daily precipitation data of 160 synoptic and rain gage stations and 12 hydrometric stations with different statistical period were used for 12 sub basins in Karun. Linear and nonlinear correlation equations between the two elements were calculated. In the final stage, cumulative coefficients of precipitation and runoff and its temporal-spatial­ correlation were calculated. The results showed that nonlinear transformations did not affect the relation between precipitation and runoff and the relation between the two elements is linear. The height, type of precipitation and temperature affected different influences on the correlation between rainfall and runoff. Also it has been shown that the physical properties of the basin, especially tectonic plates, and the impact of human factors, especially dam construction and water transport, have a great impact on the relationship between them.