NIVAR
Year:2021 | Volume: | Issue: |Papers Count:12

the European Mid-Term Prediction Analysis version (ERA5) data with horizontal spatial resolution of 0. 25 * 0. 25 degrees and using From air temperature maps, wind vector orbital component, zero level wind vector orbital component at 1000 hPa, wind vector meridian component, wind speed component, meridional performance current function, long wave output of ground output wave for 40 years (1979-1979) and was done using Gardes and MATLAB software. The results showed that the Hadley cell is confined to the lower margin of the subtropics and is due to the density difference resulting from the thermal gradient between the equator and the pole. Due to the rotation of the earth and the Coriolis deviation, heat transfer Low geography is observed in the tropics and its descent is about 30 degrees north and 35 degrees south, and the wind component orbital component winds rise from the west to the east near the earth's surface and from the east to the west at the high level. The meridional wind, the air that ascends, moves in a meridional direction towards the poles, then subsides and reverses in its direction and moves towards the equator, causing the formation of a Hadley rotation. To be. In the Northern Hemisphere, the desert regions of North Africa, the Middle East, Iran, and the southwestern United States are mostly in the Hadley cell dynamic branch, with a relative humidity of 22% Also in the southern hemisphere, the regions of Australia and South Africa with 32% relative humidity.

Importance of climate change and global warming and effect of soil temperature on issues such as changing the hydrological behavior of the system shows that it is essential to have a clear understanding of the temperature trend especially in arid region. Therefore, in this study, the trend of air temperature and various depths of soil temperature at three central synoptic stations in southeast of Iran including Kerman, Zahedan and Bandar Abbas during the years (1957-2018) was investigated using nonparametric Mann-Kendall test, Spearman test and Pearson's correlation coefficient. For this purpose, monthly and annual air and soil temperatures data in various depths of 5, 20, 50 cm were used. Also the power test percentage method was used to evaluate the accuracy of the methods used. The results demonstrated that the trend of mean air temperature in Kerman and Zahedan station showed a significant increasing trend in annual scale. But, the air temperature at Bandar abbas station did not follow a specific trend. Also, soil surface temperature was increased from surface to depth 20 cm in annual scale at 3 stations. In the monthly scale, , the trend of soil temperature changes was incremental in depth 50 cm from august to December at 3 stations. Based on the test power percentage results, The nonparametric Mann-Kendall test was determined as the most accurate test for estimating air and soil temperature trends.

In recent years, due to the occurrence of frequent floods in Iran, finding a significant relationship between climatic signals and precipitation has become an important issue. In this context, many studies have been conducted which shows a strong relationship between these signals and climatic parameters, especially precipitation. In this research an attempt has been made to depict the general view of the available studies which are published in International and national journals during 2004 to 2018 and to make the results more applicable for those interested in further research in this field. For this purpose, 50 articles have been collected in the field of studying “ the relationship between climatic signals and Iran rainfall” and their results have been summarized in the form of tables, graphs and maps to provide a general understanding of the process and results of the studies. The common point of the results explained that the impact of SOI, NAO and NINO group indices are more than other indices. Also, the SOI index is more effective than the NAO and NINO group indices. However, climatic indices have the most effects on precipitations in winter and autumn. In addition, the greater impacts of indices can be seen in the western regions of the country and also impacts of the most indices are associated with lag, which has been another common result of various studies.

The purpose of this study was to simulate surface runoff of the Ghareh-Chay River that was modeled using SWAT hydrological model. In this regard, GIS software version 10. 4, DEM and waterways and river network characteristics were first extracted. The statistics used for the 2003-2016 Ghareh-Chay Basin Pole Doab Khondab, Joshiravan, and Sarouq stations were considered. Soil curve number (CN) method was used to calculate basin mortality. Model calibration and validation were performed by SWAT-CUP software with SUFI-2 algorithm. To evaluate the model's ability to simulate runoff discharge, Nash-Sutcliffe, R2, p-factor and r-factor indices were used. Eight years of measured data (2004-2011), precipitation, temperature and daily discharge were used to calibrate the model. And model validation with residual data (2012– 2016). The model validation results with Nash-Sutcliffe, R2, p-factor and r-factor indices for the Khondab station were 0. 65, 0. 66, 0. 35, 0. 07%, and for the Pole Doab station, respectively, the results were 0. 57, 0. 72, 0. 07, 0. 05. The model evaluation confirms the SWAT model's ability to simulate surface runoff of the Ghareh-Chay River. Finally, the comparison of simulated hydrographs and monthly observations showed that the model modeled well the peak discharge and base discharge times but estimated the peak discharge values more than the actual values.

The shortage of usable water and the rising water consumption due to the increasing population, the increasing standard of living, and the growth of technology are a concern worldwide that raise water need and scarcity. Therefore, in this study, the effect of atmospheric parameters on Koohrang's snow cover from 2010 to 2018 years was investigated. Snow has an essential role in the hydrological cycle due to water resources' supply in low water seasons and energy production. For this purpose, the role of the atmospheric parameters on snow cover was determined using statistical methods. In this study, by examining linear and non-linear regression relationships between atmospheric parameters (maximum, minimum and average temperature and precipitation) and snow cover, it was found that the highest correlation coefficient is related to the maximum temperature parameter (0. 87) and the lowest correlation coefficient is related to precipitation (0. 26). Among the used regressions, nonlinear regression recorded a higher correlation coefficient in the parameters of total annual precipitation (0. 34), minimum and maximum temperatures (0. 74 and 0. 87, respectively). At the same time, there was no change in the correlation coefficient calculated for the mean temperature parameter. The results of researech also show a decreasing trend in snow cover of the watershed during this period. There is also a significant relationship between temperature and snow cover parameters that can be used to diagnose snow cover in the region.

Increasing greenhouse gas concentrations can lead to global warming and climate change. In this study, the trend of changes in precipitation and temperature of Varamin synoptic station during the period from 2021 to 2050 AD was investigated using the CMIP5 data of the Fifth IPCC Assessment (AR5). One of the major limitations of using these models is their low spatial resolution, which does not match the accuracy required by hydrological models in terms of space and time. Therefore, downscaling method by LARS-WG model was used to overcome this limitation. Finally, temperature and precipitation data were simulated under two scenarios of RCP2. 6 and RCP8. 5 for the Future period and compared with the base period. Due to the effect of temperature and precipitation on the future drought status of the plain, De-Martonne drought index was determined under two scenarios of climate change and compared with the base period. The results of the study showed the significant effects of climate change on the aggravation of conditions in the region and consequently a-1/3 degree of centigrade increase in temperature and change in precipitation pattern and changes in drought index. According to the obtained results, it can be stated that although the drought trend is affected by several factors, but in the shadow of possible climate change in the future there is a possibility of increasing the drought trend in Varamin plain, due to changes in rainfall and rising temperatures, so that both climate scenarios also predicted a drought condition for the study area.

In this study, the relationship between mean zonal and meridional variations of westerlies with wet and dry periods in the western Iran was investigated. Therefore, the data cumulative precipitation values of the study area from Eropean Center for Medium-Range Weather Forecasts (ECMWF) version (ERA-Interim) with spatial resolution of 0. 125*0. 125 and also the geopotential height data of the version ERA5 with a spatial resolution of 0. 25*0. 25 degrees was received from the same center for the years 1979 to 2019. The Standard Precipitation Index (SPI) was used to determine the monthly wet and dry periods. So, to investigate the relationship between mean zonal and meridional variations of the westerlies with wet and dry periods in western Iran, the Middle East Synoptic Index (MESI) was defined based on variations of the westerlies from 25 to 45 degrees north latitude at atmospheric levels of 500, 600 and 700 hPa. The results indicated, that when wet periods occur in western Iran, MESI upper than the threshold and westerlies on the Middle East (Mediterranean and Red Seas) have a meridional flow. Whereas in dry periods, MESI is lower than the threshold and westerlies have a zonal flow. According to the results, no wet and dry periods was found, the value of which MESI was lower and upper than the threshold. Therefore, it seems that variations of the westerlies flow can be effective as one of the factors in formation wet and dry periods in the western Iran.

Particular matters are one of the important air pollutants that have direct effects on human health. In this research, by comparing, feed forward ANN and NARX has been estimated particular matter of Tabriz city. metrology data and air quality data from 2013 to 2017 has been used. Particulate matter estimated by considering temperature, wind speed and rain precipitation in each model and the results compared. Also PM2. 5 data form BaghShomal air quality station in Tabriz has been used. 50 present of data used for testing and validation and the rest of data used for training network The results showed that best state estimating with seasonal effect belong to feed forward ANN train with amounts of R=0. 85, MSE=0. 057and without seasonal effect belong to NARX with amounts of R=0. 999, MSE=0. 005. Modeling results with real data showed that best results belongs to feed forward ANN with 0. 0007 error.

In this study, salinity prediction of Karkheh River after exploitation of irrigation and drainage projects of Jahad Nasr Institute was investigated using SALTMED salinity simulator model. Due to climatic conditions, cultivation pattern, irrigation schedule, soil and water characteristics and drainage of the Evan, Dowsalagh, Arayez and Bagheh plains that are excluding the Upper Plains, the volume of drainage output and the amount of salt produced from each plain with a total area of 55, 000 hectares were simulated. Also from the data, the years (2013-2017) were used due to completeness of the information. The results showed that based on the prediction of the SALTMED model in the statistical year 2013; the amount of 150, 87, 140 and 197 thousand tons of salts enter the Karkheh River annually from the Evan Plain, Dowsalagh, Arayez and Bagheh, respectively. If the same trend continues for 10 years, an amount of 5. 74 million tons of salt will enter Karkheh and then eventually discharge into the Hawizeh Marshes, which will have many environmental impacts. The overall result showed that by exploiting 37, 000 hectares of 55, 000 hectares in the four plains, the Karkheh water salinity index (EC) increased significantly and on average, it will reach from 1. 15 dS/m to more than 2 dS/m. Now, if all 55, 000 hectares or more of the 550, 000 hectares of land were exploited, how much salt and drainage water would flow into the rivers?

Isfahan district has been faced with limited water resources in recent years because of its special geographical location and highly dependent on the Zayandeh-rood River and groundwater for various uses, including agriculture. Meanwhile, according to available statistics, more than 90% of the country's water consumptions are allocated to the agricultural sector. Calculating effective rainfall, especially in arid and semi-arid regions that face with limited water resources is very important. In this study, effective rainfall in wheat cultivation in the 2015-2016 crop year was estimated by direct (field) method of Ramdas and obtained results from six empirical methods of Renfro, US Bureau of Reclamation (USBR), Evapotranspiration to precipitation ratio, US Soil Conservation Organization (SCS) method, FAO "(FAO/AGLW)", and percentage were compared with Ramdas technique by root-mean-square error (RMSE) tests, normalized root-mean-square error (NRMSE) and the mean absolute error (MAE). The results indicated that the ratio of evapotranspiration to precipitation and the method of the US Soil Conservation Organization (SCS) with RMSE and NRMSE 0. 31 and 0. 7, MAE 0. 11 and 0. 45 respectively could be recommended as empirical approaches in Kabootarabad region (Isfahan district).

Dew point temperature estimation with proper method is useful in many fields such as agricultural planning including crop protection to the damages, meteorological, hydrological and ecological studies. In this study, the forecast combination approach of regression tree, Group Method of Data Handling(GMDH) and experimental method were applied to forecast dew point temperature in Rasht, Yazd and Urmia stations. The input variables of individual models were the maximum wind speed, mean wind speed, maximum, minimum and mean temperature, mean relative humidity, maximum and minimum relative humidity and saturation vapor pressure. The used methods of weight combination approach were inverse variance and least square regression. In the individual models, GMDH is more efficient than other models, so that the RMSE decreasing from empirical and regression tree to GMDH model in Rasht station is 66. 66% and 59. 45%, respectively. The combination approach is more accurate rather than the individual models and least square regression method has less error than the inverse variance with different error criteria, so that Nash-Sutcliff coefficient in Rash, Urmia and Yazd stations is 0. 97, 0. 96 and 0. 87, respectively. Also, the kind of error criteria and defined power in the inverse variance method is effective on forecasting values and the proper power basis on available data was proposed. In order to investigate the impact of climate diversity, Rasht station has the least error. The use of robust individual models will also increase the ability of forecast combination approach.

In this study, the results of 24 and 48 hour rainfall forecasts in the mid-scale WRF model with nested slopes with 18 and 6 km (performed in Lorestan meteorology) and with 27 and 9 km (performed) In the Institute of Meteorology and Atmospheric Sciences), without schematic, for a period of 2 months from March 1, 2019 to the end of April 2019 and compared with precipitation observation data for 10 synoptic meteorological stations in Lorestan. Output post-slip results showed that the 27, 9 and 18 km outputs with values of 7. 3, 4. 8 and 1%, respectively, had the highest increase in the accuracy of 24-hour forecasts after post-processing. And only 6 km output has decreased performance by 7. 7% after post-processing. Also, the output of 27, 18 and 9 km ranges with values of 9. 4, 7. 8 and 4. 8%, respectively, had the highest increase in the accuracy of 48-hour forecasts after post-processing, and only the output of 6 km with-0. 9% has decreased performance after post-processing. Post-processing zoning for the province showed that post-processing by weighted average slider method for both 24 and 48-hour intervals in correcting the model outputs, the altitude factor reduced the accuracy of predictions so that in areas with altitude The less they have been, the more effective they have been.