نشریه نیوار
پیاپی 122-123 (پاییز و زمستان 1402)

The main goal of this research is to investigate the amount of net irrigation requirement of major cultivated crops in Jiroft plain, including potato, onion, wheat, barley, tomatoes and seed corn in the future period (2031-2050) based on different RCP scenarios using LARS-WG6 model is used. The data required in this research include daily precipitation, minimum and maximum temperature and sunshine hours of Jiroft synoptic station (during 1989-2017), which were obtained from Iran Meteorological Organization. First, the ability of LARSWG 6. model to simulate the climatic variables of Jiroft synoptic station in the base period (1989-2017) was investigated. Then, using HadGEM2 model, these variables were simulated during 2050-2031 based on RCP2.6, RCP4.5 and RCP8.5 scenarios. Finally, by calculating the amount of effective precipitation and potential evapotranspiration, the amount of net irrigation requirement of the studied crops was estimated on a monthly scale in the base and the future period, and their changes were evaluated in comparison with each other. Based on the downscaling results of LARSWG 6. Model, and according to RCP2.6, RCP4.5 and RCP8.5 scenarios, the minimum temperature will be increased by 1.3, 2.3 and 2.753 ºC, respectively, the maximum temperature by 0.6, 1.14 and 1.44 ºC, respectively and the average annual precipitation will be decreased by 10, 20 and 27%, respectively. Also, the total amount of net irrigation needs of all crops will increase under all scenarios in the future period, so that the greatest increase will occur under the RCP8.5 scenario.

Dust is one of the major environmental problems that make health and financial losses in arid and semi-arid regions. As a country located in the Middle East, Iran has been affected by these natural hazards and every year dust storms occur in different parts of Iran causing huge amounts of damage. Dust storms have increased due to recent droughts and internal Sand and Dust Storm (SDS) hotspots in the Middle East. Interactions between the atmosphere and the earth's surface, such as the effect of vegetation or soil moisture and rainfall intensity in an area, can be important in determining the convective activity of the atmosphere (Lee et al., 2016). Since dust emission and wind speed depend on factors such as soil type, soil moisture, and vegetation (Prospero et al., 2002), it is important to study the relationship between the amount and type of vegetation and drought with dust events. Gradually, as the warm season approaches, the pattern of dust formation is intensified by north, and northwest winds and the wind field channeling due to convergent topography, especially over Mesopotamia. . The lowest values of the VCI in the studied region are observed in the countries of Iraq, Syria, and Saudi Arabia; while the seasonal changes of VCI over Iran are not significant. Nevertheless, in the southeast of Iran, the highest values are related to the summer season, which can be due to the rainfall caused by the activity of the Indian monsoon in this region.

More than 70% of the earth's surface is covered by water. Sea transportation is the main means of moving goods and raw materials needed by the economy of maritime countries. Currently, more than 85% of the commercial exchange of our country is carried out by sea. Hydrography is considered as the key to infrastructure development of coastal countries. Lack of resources to provide accurate, reliable, publicly available, networked and up-to-date marine location information has caused many problems for the country's maritime users, which, in addition to the dangers of navigation, the use of foreign mobile software or applications such as Primar, Navionics, Cmap, etc.,Which have sometimes been sanctioned for Iran, by Iranian sailors will bring special security-technical problems. The production and publication of nautical charts is the most important infrastructure of hydrographic knowledge.none of which have achieved the desired result, and at best, they were satisfied with the ability to load grid layers in one system. But surly no institution in the country has provided services based on vector layers and with OGC standards. At the global level, there are various systems for providing nautical chart services, these systems have the ability to provide various types of nautical charts with different features.The launch of this system is vital because by providing an accurate, up-to-date and practical service, all navigational information, including sea charts with appropriate scale, weather information, marine remote sensing identifiers, marine traffic, etc., can be recorded and monitored, and this It shows that it is possible to act more precisely in order to create the aristocracy of spatial information in the maritime domain and to reduce as much as possible the access of other countries to the maritime information of the blue borders and prevent its various consequences.

Nowadays, due to the increase in population and the ever-increasing need for food, providing food security is considered one of the essential requirements in every region. On the other hand, the recent droughts are one of the main reasons for the instability in food security and food production in different regions of the world. The purpose of this research is to select a superior model in order to measure the relationship between drought parameters and food security in Alborz province. Therefore, from the data related to precipitation and temperature in order to calculate SPEI meteorological drought index, as well as the data related to the cultivated area and tonnage (tons per hectare) of the two strategic products of wheat and barley, which provide more than 43% of the province's food. It was used in a period of 21 years (1380-1400). Four methods of Spearman, ANN, ANFIS and M5 were used to investigate the relationship between drought and food security parameters in Alborz province. The results showed that in Taleghan and Karaj, the goodness of fit criteria of R2, RMSE and MAE of Spearman, ANN, ANFIS and M5 methods were from 0.752 to 0.736, 0.242 to 0.217, 0.107 to 114 respectively. 0.847 to 0.837, 0.209 to 0.253, and 0.107 to 0.111 are variable. Also, among the algorithms used, the M5 decision tree method was the best model for measuring the correlation between drought variables and food security...

Extracting water from air humidity as one of the new and sustainable methods for providing water resources in areas with a lack of natural water resources and also in the conditions of drought is of great importance. Considering the influence of the amount of water that can be extracted from air humidity on changes in meteorological variables such as air temperature, wind speed and air humidity, therefore the potential of water extraction from air humidity can be strongly affected by climate changes. Therefore, the current research has been carried out with the aim of investigating the potential changes of water extraction from air humidity under RCP4.5 and RCP8.5 scenarios from the fifth climate change report. The results in the base period showed that the climate models have a suitable efficiency for investigating the potential of water extraction from air humidity, so that the average correlation index at the level of study stations is more than 0.67 and the value of the RMSE error index is 1.83 liters per square meter in The day is limited to In addition, the monitoring of water extraction conditions from air humidity under climate scenarios in the coming periods indicates the existence of an increasing trend at the 95% confidence level in the amount of water that can be extracted from air humidity, such as the value of Menkendall's non-parametric test under RCP4.5 and RCP8.5 scenarios. In the periods of 2026-2050 and 2076- 2100, it is estimated to be more than 1.64. In general, based on the results, it was found that the northwest region of the study area has the greatest potential for the implementation of water extraction projects from air humidity. Therefore, due to the occurrence of global warming in recent years, the increase in water needs in different sectors and the consequent increase in pressure on the available water resources, the need to pay attention to this water source, planning and taking serious action for its use is felt more than ever. The results of the present research can be useful in planning for the sustainable management of water resources under the influence of global warming.

Flood is known as one of the natural disasters that cause financial and human losses not only in developing countries but also in the developed countries. Synthetic Aperture Radar (SAR) sensors are an essential data source for flood crisis planners and experts, because they have the ability to image the earth's surface independently of weather conditions and time of the day. This advantage coupled with cloud computing platforms such as Google Earth Engine (GEE) provide a tremendous opportunity for the crisis response community for effective management plans. It allows them to quickly access ready data for analysis which is of great importance in case of flooding. The purpose of this research is to quickly monitor the flood of Kashkan river. The algorithm presented in this study uses time series images of Sentinel-1 and Landsat 8 along with other auxiliary data for flood monitoring in the GEE system. This algorithm relies on multi-temporal SAR statistics to identify unexpected floods in near real-time. Additionally, historical Landsat-based surface water class probabilities are used to distinguish unexpected floods from permanent or seasonal surface water. Based on the results of this research, Sentinel-1 images have an acceptable performance for flooded areas detection in Sentinel-1 images. Therefore, managers can use this method to obtain flood information and locations in order to reduce flood damages.

In the present research, using the daily precipitation data of 479 meteorological and rain gauge stations in the north west of Iran, the relationship between the changes in the dew point temperature and the precipitation in this region was investigated. For this purpose, the Classification and Regression Trees method was used to determine the effective temperature class in the extreme precipitations and the geographical weighted regression was used to identify the significant areas. The results of this research showed that there is a direct and significant relationship between these two variables and with the increase in the dew point temperature, the intensity of the extreme precipitation also increases in the 90th, 95th and 99th percentiles. The results of the Classification and Regression Trees showed that different dew temperatures (low and high values) both play a role in the occurrence of extreme precipitation in the North West of Iran, but in very intense extreme precipitation (precipitation above the 99th percentile), the role of high dew temperatures is greater than low values. Also, the southwestern part of the studied area has the highest degree of correlation compared to other parts. This section corresponds to the areas that have the most precipitation. This shows that extreme precipitation affected by the dew point temperature occur in areas where the frequency of rain is high and the probability of flooding caused by this type of precipitation is also higher in this section than in other sections.

Accurate prediction of wave parameters is of great significance for marine and coastal operations. The very aim of the present research was to predict the wave characteristics for the northern coastal areas of the Sea of Oman using the MIKE 21 SW model. In this study, firstly, the generation of waves by wind with a spatial resolution of 0.1 degrees, a temporal resolution of 1 hr, and a suitable boundary condition was presented from the study data of the coasts of Iran (phase six - Makran beaches) with a temporal resolution of 1 hr. The results were validated with measurement data obtained from certain stations in 2016. Simulated wave parameters after calibration and adjustment of white capping coefficients as a wave loss parameter corresponded with the results of the measurement data at three stations with a strong correlation of 90%, 86% and 80% and an improvement value of 7.6%, 4 6.6%, and 27.18%, respectively. Moreover, the correlation coefficient of Tp and MWD in the Pasabandar station was 0.33 and 0.58, respectively. The results of this study also revealed that the dispersion index for three stations after calibration was 0.232, 0.363, and 0.684 for Hs, 0.338, 0.337, and 0.393 for Tp, and 0.149, 0.182, and 0.300 for MWD. By inferring from the simulation results and non-dimensional parameters of wave age and steepness, it can be concluded that the sea state and the wave climate are influenced by the waves caused by the northwest wind, monsoon, and the waves of the Indian Ocean. Wave steepness varied from 0.005 to 0.055 in different seasons such that discontinuity could be seen in the combined distribution of inverse wave age-wave steepness data in steepness of less than 0.01.

Drought is one of the main hazards related to weather that can affect all aspects of life. In order to monitor and manage droughts using relevant indicators, six synoptic stations were selected in South Khorasan province, corresponding to the cities of Birjand, Qain, Nehbandan, Ferdous, Tabas and Beshravieh. Then the required data was collected and analyzed. According to the review of the available data, the statistical period of 31 years (1990-2020 AD) was chosen as the statistical period of the research. R software is one of the software that is very useful for statistical analysis and has libraries for calculations in different basins. In this research, SDI and RunDS drought indices were calculated using the Drought library for each of the stations. Also, in order to calculate RAI and PNPI drought indices for each station, coding was done. The results showed that according to the SDI index, the driest month and year during the statistical period are October and 2008, respectively. Also, according to the SPI index, Tabas city is in the extreme drought category and has experienced the most drought compared to other cities. In the case of RunDS, Ferdous city had the longest duration of drought and Tabas had the highest intensity of drought. Based on all indicators, Tabas city was recognized as the driest city due to 53 months of drought. Also, based on the results obtained from the R software, the SDI index estimates results closer to reality than other indices in long-term time scales.

Based on theory, this research investigated the relationship between the penetration depth of electromagnetic waves and the conductivity of sea water based on daily parameters of temperature and salinity in Caspian Sea with low salinity and Oman Sea with high salinity. The data was received from the oceanographic center over a period of one year and the values are calculated daily and the results show that the wave range is more sensitive to salinity. The range decreases with the increase of the frequency, so that at the frequency of 1000 khz, the range for the Caspian Sea and Oman reached about 2 and 5 cm, respectively. The range in the low frequency of 100 Hz has increased significantly and its value for the Caspian Sea is 1.51 m in March (T=11.76 C0, P=7.59psu) and for the Oman Sea it is 16.22 m in January (T=22 C0 , P=36.5 psu) was obtained. Also, the sensitivity of wave range with temperature in the Caspian Sea is more than that of the Oman Sea. This amount of range was seen at minimum and maximum temperatures of 9.74 and 24.30 degrees Celsius for the Caspian Sea, respectively 34 and 45.2 meters, and for the Oman Sea at temperatures of 22 and 32.2 degrees Celsius equal to 19.57 and 22 meters. The penetration depth of radar waves in the Caspian Sea can be three times higher than in the Oman Sea due to its low salinity. Since the range decreases with the increase in salinity, therefore, taking into account the salinity of the effluent of desalination facilities in the range of 74.8psu, the range of waves with a frequency of 100Hz has decreased sharply from 19.7m to 4m, which can be the cause of its tracking in the sea.

Production and use of complete and reliable data is the first step in providing optimal services and reliable weather and climatology studies. Incomplete data makes meteorological services and researches face a challenge. There are many ways to improve and restore data that one of the most important of which is the correct process management of collecting, transferring, storing and using data. The most important field that deals with this issue is the management information systems and information technology. The way of managing this area and coordinating it with the main strategies and other sectors plays a significant role in reducing the data gaps and insufficient data and also improving the quality and quantity of meteorological and climatological data and information, and improving the services of the organization. In this regard, it is considered to identify the strategies of information systems and information technology and its main subsystems to create more coordination between the various components of the organization and finally to produce and use valid and sufficient data. In this article, in order to optimally manage the production and analysis of meteorological data, the design and exploration of the model was discussed with the in-depth and semi-structured interview method. This process was carried out with the participation of 20 data and information experts of the country's meteorological organization, who were selected purposefully and with the help of the content analysis method, with the aim of achieving various aspects of information systems and information technology function. Then the basic concepts and also the reliability of this method were studied. The method of data analysis (Manual and software with MAXQDA10) is a combined content analysis with an inductive and deductive approach, and the acceptability and objectivity of the data is done by combining data collection, multi-dimensional, diversity of research participants, frequent review and revision of data. The final findings of the research with 61indicators, 20categories and 5 themes include "information systems & information technology", "meteorological information infrastructure and technology", "meteorological data and information management", "meteorological service management" and "meteorological information and communication security" and in each of them four subclasses with the help of strategic reference points method was determined. In the end, with the re-review and opinion of respected professors of the university, the relationships of the main themes in the form of information systems and meteorological information technology with the four subsystems and the strategies of each one were drawn in order to create more coordination in decision-making to improve data management and meteorological services

In recent years, the need for energy in the world has increased. Due to climate change and its problems and the increasing global need for energy, the desire to use fossil energy has decreased and the development of new energy has become one of the most important issues of the day. In this research, one of the new types of energy, called wind wave energy, has been investigated. In this research, the Swan model (SWAN: Simulating Waves Nearshore) was used to simulate the characteristics of the waves (Significant wave height, wave direction and wave period) were predicted in a period of 6 years. The output of the WRF model was used to generate the wind field of the SWAN model input. After simulating the waves, the Chabahar buoy and Era5 data were used to verify the wave characteristics, including the height of the wave index (Hs) and the period of wave repetition (Ts). Then, the amount of energy that can be extracted in Makran beaches was calculated. The results of the six-year averaging showed that the highest wave power can be obtained in the summer season in the areas near the Indian Ocean, which was estimated about 7.84 W/m.