فصلنامه جغرافیا و پایداری محیط
پیاپی 35 (تابستان 1399)

One of the most important issues related to rainfed wheat cultivation is the date of the First Effective Precipitation (FEP) which can provide soil moisture for cultivation. The current study aims to evaluate the variability and probable trend in the date of the first effective precipitation and the synoptic conditions that lead to its occurrence in northwestern and western Iran. Therefore, precipitation data were extracted from Iran’s Meteorological Organization. First precipitation with a value of at least 5 mm and duration of one to two consecutive days, associated with another precipitation occurring less than 10 days apart, was selected as the first effective precipitation. Then, the trend of first effective precipitation was investigated using Man-Kendall test and linear regression method. Finally, geopotential height, wind speed and humidity data (ERA-Interim) at 850 and 500 hPa levels were obtained from ECMWF website to identify synoptic patterns of the first effective precipitation by cluster analysis method. The findings reveal that more than 90% of the first effective precipitation has occurred during October. Accordingly, Ardebil, Sanandaj, Khorramabad, Kermanshah, Zanjan, Orumieh, Tabriz and Hamadan stations had earliest climatic average of the first effective precipitation date during the period of 1987 to 2016, respectively. Despite the high annual variations regarding the occurrence date of first effective precipitation, evaluating the trend of the first effective precipitation by Mann-Kendall test at the significant level of 5% show that there is no significant trend in all studied stations. Furthermore, synoptic patterns including the short trough, omega block, cutoff low and the Mediterranean long trough are identified as responsible patterns on the occurrence date of the first effective precipitation. Among the patterns, omega block has been associated with widespread rainfall at the studied stations due to greater access to moisture and unstable conditions caused by the cold weather.

Land suitability evaluation plays an important role in environmental sustainable management. Besides, it is a prerequisite for land planning which affects sustainability of the activities and sustainable development. The current study aims to evaluate and model the agricultural, urban and industrial development in Great Isfahan (as the most crowded center of Isfahan province and the most important agricultural and industrial hub of the country) using the data in 2018. Land-use planning is increasingly focusing on the aspects of environmental conservational and sustainable development. Choosing the appropriate areas for this purpose is a complex process which requires lots of effective factors. We use multi-criteria evaluation of the land-use allocation models applying geographic information system. First, the required data (including topographic variables, water resources, geology, land-use, accesses, infrastructure factors, biological resources, soil and climatic parameters) were identified, suitability maps were prepared using fuzzy method, and the weight of the factors was determined employing the analytic hierarchy process. Then, the prepared maps were combined using the weighted linear combination method. Finally, the final maps of land-uses suitability were prepared and classified according to the expert opinions. The findings show that approximately 586.9, 197.2 and 24 km2 (20.3%, 6.9% and 0.08%) of the total area of the region is suitable for agricultural, urban and industrial development, respectively. Besides, the northwest and southeast of the region are in an appropriate area. We conclude that MCE and GIS techniques are effective tools for land evaluation and planning. The results of the present research can be used as a multi-criteria decision analysis to obtain a deep insight into the sustainable use of natural resources. Moreover, three possible scenarios (current ecological and socio-economic trend, conservation of agricultural lands and urban-industrial development) can be designed and modeled based on.

Climate variables and their fluctuations dramatically affect terrestrial ecosystems and their variations. Vegetation indices have been used in numerous studies to investigate the relationship between ecosystem changes and climate parameters. In this study, GIS based spatiotemporal analyses were applied to model the relationship between vegetation variations based on the EVI-MODIS and its response to land surface temperature (LST) and rainfall in Mazandaran province during the period of 2000-2016. The LST parameter was derived from the MODIS data and rainfall parameter was achieved via meteorological station data in the region. Correlation and linear regression analyses were used to study the relationship between spatiotemporal enhanced vegetation index (EVI) and two climatic parameters. The findings indicated that the EVI had a rising trend over the study period which was mostly due to the increase in paddy fields. There was also a significant spatial correlation between EVI and LST which was significant and direct in the winter months and reversed during summer. The tabulate area analysis showed that throughout the winter months the spatial distribution of the highest EVI pixels matched to the maximum temperature pixels (20 to 27 ° C), while during June to September, the maximum EVI values were related to the areas in which the LST was less than 25 °C. Although there was no significant relationship between EVI/MODIS and rainfall in studied area, they reached a peak with a lag time of 1/5 to 2/5 months in the spring. The final results showed that the temperature is the main EVI climate factor in region and MODIS products have high potential to reveal the spatiotemporal dynamics of vegetation, the impact of human factors and its relation with the climatic factors of temperature and rainfall in the region.

Land use and land cover change are critical motivations for environmental changes. It mainly arises from human activities, e.g., the expansion of urban areas, the changes in agricultural land areas, and the destruction of water area which rooted in population growth. The present research used a combination of cellular automata (CA) and the Markov chain to simulate the present land-uses in the Lake Urmia Basin using remote sensing data. First, the land-use map was produced by the maximum likelihood classification method using the Landsat satellite imagery for the years 1998, 2008, and 2018. After the integrated CA-Markov approach assessed the model, the land-use maps were predicted for the years 2028 and 2038. The trend of land-use change between 1998 and 2018 revealed that agricultural areas and urban/human-made areas have increased by 3.31 and 2.74 percent, respectively, but water areas and other uses have decreased by 6.87 and 0.71 percent, respectively. The kappa coefficient was estimated at 80% for the model, implying its high accuracy in predicting land-uses. Based on the simulation results for 2028 and 2038, agricultural land area and urban/man-made areas will expand by 40.12 and 476.36% versus those in 1998 whereas water areas and other uses will shrink by 26.67 and 5.80%, respectively. The results can greatly help policymakers and managers of natural resources to make management decisions on land uses in different regions.

Population growth, development of residential areas, as well as man-made land use, are causing landcover change. Shorelines are more sensitive to landcover change. Therefore, the current study aims to evaluate the trend of landcover changes in the southeast of Bushehr province from Asaloyeh city to Shirino village. The study used Landsat satellite images from the 1990, 2000, 2010 and 2019 and the LCM model to assess the trend of landcover change. The procedure is that first the landcover maps are prepared and then the process of land use change changes, changes in other landcovers to man-made areas and also the coastline change process is evaluated. The assessment of the change indicates that the use of man-made areas has had significant changes in a period from 1990 to 2019 under the influence of the development of economic activities and in parallel with the development of residential areas, refineries, as well as other facilities related to the Gas Company. Depending on the location of the study area and the type of anthropogenic, man-made use (refineries and other facilities and infrastructure related to the gas company), land-use changes mostly direct to coastline. Therefore, 11.2 km2 of the sea has been changed to an arid area during a 29-year period. Besides, the development of economic activities and job creation, residential areas in Assaluyeh and Nakhl have experienced significant growth, and this development has further changed the use of sandy lands to the construction of man-made areas.

Earthquakes are one of the most important environmental hazards that always lead to a lot of damage. In addition to the effects that earthquakes on residential areas, they also have many tangible and intangible effects on landforms that can cause hazards. Due to the importance of the issue, the current study investigates the tangible and intangible effects of herd earthquakes on landforms in the Ezgeleh region. The research data includes the 30-meter SRTM digital elevation model, digital data layers, Sentinel 1 images, and information obtained through field visits. The most important research tools include ARCGIS software (for mapping and final output) and GMT (for radar interference). This research has been done in 3 stages. In the first stage, using the radar interferometry method, the amount of vertical displacement of the area is calculated. In the second stage, the vertical displacement of the landforms of the region has been evaluated and in the third stage, the tangible effects of the earthquake on the landforms of the region have been investigated. The results of the research indicate that under the influence of earthquakes, the area had a displacement of between -613 and +917 mm. Due to the vertical displacement that has occurred in the region, the landforms of the region have also faced a lot of displacement so that the plains in the region have been affected by this displacement in which the highest displacement with 382 to 917 mm elevation is related to Zahab plain. Unlike the plains of the region in which the movement and changes have been mostly imperceptible, the slopes located in the region, in addition to the imperceptible effects, have also encountered many tangible effects. Therefore, many slopes of the region, including the slopes located near the villages of Ramaki Ramazan, Meleh Kaboud and Ghouchbashi have lnadslice, as well as the slopes near Piran waterfall and Baba Yadegar valley have Debriz.

Destruction and habitat fragmentation are considered as the most challenging issues of biodiversity and establishment of protected areas is one of preventive methods to reduce biodiversity. Therefore, there are different criteria to choose it. Kermanshah province has covered different habitats due to its diverse ecologic condition. The current study aims to evaluate and compare the distribution of effective indices on habitat diversity in protected areas of Kermanshah province. In this regard, Surrogates such as altitude, slope, aspect, roughness  of altitude, Shortwave Infrared Water Stress Index (SIWSI), Compound Topographic Index (CTI), normalized different vegetation index (NDVI), vegetation type and Roughness of NDVI have been used as Biodiversity surrogates. Since the protected areas should be indicative samples of their surroundings, all the mentioned variables were prepared for Kermanshah province area and then all maps for slope and cover type were divided into 10 classes based on Jenks method. Shannon-Wiener (H), Simpson (D) and Macintosh (D) indices were used for diversity analysis, and Pielou (J') and Macintosh (E) indices were used for richness analysis. The results show that in terms of diversity indices for slope, CTI, altitude, NDVI, roughness  of altitude, Roughness of NDVI, SIWSI and slope ,Hashilan no hunting area, Ghalajeh protected area, Nava Koh no hunting area, Dalakhani and Amroleh no hunting area, Bistoon protected area and Bistoon Wildlife Refuge have the highest diversity indices, respectively. The slope and CTI variables share most similarity in terms of distribution of classes among the protected areas, and the vegetation type variable has had the least similarity among the protected areas. Among the hunting-banned and protected areas, the highest diversity exists in the Amroleh and Dalakhani and Bistoon protected area, respectively.The results of this study can be useful in choosing the correct complementary protected logic.