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Huge floods carrying enormous amounts of transported silt occur annually in the Talar River's catchment area in the province of Mazandaran. In order to investigate the sediment transport from the specified watershed, samples were collected at five different time intervals, specifically on May 22nd, 2018; May 20th, 2018; May 17th, 2018; and May 16th, 2018. The study focused on two dates, 17.11 and 5.11, and a specific stretch of land measuring 16.75 km between Darya Malakala-Najjarkala and Arab Roshan, located outside the urban area. The purpose was to analyse the patterns of sedimentation and erosion throughout a five-year period (2016-2021) using the HEC-RAS model. Inspected. The sediment transport and volume of sediment were analysed and studied based on the long-term statistics of the Kiakla hydrometric station. This analysis focused on flood conditions with return periods of 2, 10, 25, 50, and 100 years for the watershed of the station. The findings indicate that the cumulative sediment input at the start of the simulation period is 0.9 million tonnes lower than the total sediment at the end of the period. Additionally, the river is susceptible to erosion in the majority of situations. Furthermore, during the initial period (22.4-24.7), the sediment's mean height measures 11 cm, with a substantial sedimentation of 6 million tonnes. The deposition during the second period (2018-05-20) amounts to roughly 1 million tonnes. In the third quarter, there is a relatively consistent pattern. During the fourth phase, the erosion conditions, in terms of both depth and volume, are unsuitable for harvesting. During the fifth phase, which lasted from 11.5 to 16.75, the erosion amounted to approximately 8.3 million tonnes. The erosion height change in the fifth interval ranges from 10 to 20 cm. All distances are measured in km from the sea. Under such circumstances, sediment removal is unfeasible, but it is advisable to consider flood management and river engineering measures.

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The term urban heat island (UHI), described the phenomenon of climate change in urban areas compared with surrounding rural areas. UHI effects include: increasing in energy and water consumption, air pollution expansion and interfering in thermal comfort. Surface urban heat island (SUHI) contains patterns of land surface temperature (LST) in urban areas that has interaction with UHI in urban canopy layer and urban boundary layer and investigate with thermal remote sensing. SUHI has diurnal and seasonal variations so requires multi-temporal data to analysis SUHI. In this study, the multi-temporal MODIS (Aqua and Terra) data product were used to analyze the SUHI in day and night in Tehran metropolitan. Physical and biophysical surface properties such as: land cover/land use (LULC), elevation, albedo, vegetation index (NDVI) and impervious surfaces index (NDBI) were used to interpretation of the LST and SUHI changes. The results showed that SUHI in Tehran, has spatial-temporal diurnal and seasonal variation. So that during warm days the surface urban cool island (SUCL) is formed in Tehran. At night times, SUHI index values was different between 2 and 5 ° C (maximum in the spring). The results also showed that different of land cover thermal properties, albedo and elevation was the most important factors is the diurnal changes of SUHI while phonological changes of vegetation and albedo, was the most important factors in seasonal changes of SUHI.

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According to the sensitivity analysis of SIMETAW model, the input parameters of the model are respectively their effect on potential evapotranspiration from maximum temperature, precipitation, dew point temperature and minimum temperature, solar radiation and wind speed.

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Abstract
With the rapid growth of population and urbanization since the last century, the complexity and understanding of the spatial organization of the city, as well as the ability to predict urban events in its spaces, have become difficult and in some cases impossible. Karaj metropolis is one of the major metropolitan areas of Iran that has been experiencing rapid population growth and this has led to complexity of space and consequently to complexity of organization recognition and analysis and its spatial structure and impact of livelihood components. It has become a spatial system. The main purpose of the present study is to identify the role and impact of Karaj's spatial organization on its nuclear viability. The research method is quantitative and descriptive-exploratory. The study area was Karaj metropolis and its main nuclei. The statistical population of this study is citizens living in the sub-nucleus of Karaj. The sample size was 378persons. The data used in this study were collected through library and field research. Data were analyzed using spatial statistics, spatial arrangement, and T-test and Friedman test. The results show that the Karaj metropolitan organization and spatial structure are interconnected and connected to some of the major routes, forming sub-nuclei away from the core and thus transferring the functional and service applications from the center to be the peripheral nucleus. This has affected the viability of the core. Decrease in biodiversity has occurred in different physical, social, economic and environmental dimensions that have affected the environmental and economic aspects less than the other two dimensions, so it can be concluded that the Karaj Spatial Organization has an impact on its viability.
 

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This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error.

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Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.