جستجوی مقالات مرتبط با کلیدواژه "دشت قزوین" در نشریات گروه "جغرافیا"

Desertification is one of the factors that seriously threatens semi-arid areas. Climate changes and human activities in recent years have intensified this phenomenon. In this research, Sentinel 2 images in 2023 have been used to evaluate desertification in Qazvin Plain. At first, TGSI, albedo, NDVI and MSAVI indices were extracted. Then, for linear regression analysis, different combinations of indices were considered and Pearson correlation relationship was established between NDVI and albedo, MSAVI and albedo, TGSI and albedo, TGSI and MSAVI indices. Then, by using the regression relationships between NDVI-albedo and MSAVI-albedo, DDI desertification degree index was estimated. Finally, the map of desertification was drawn for the entire studied area in five classes: very severe, severe, moderate, low and very low. The obtained results showed that there is a negative correlation between albedo and MSAVI and NDVI indices, and a positive correlation between this index and TGSI. MSAVI-albedo combination has the best correlation coefficients with a value of -0.417 and the lowest correlation is estimated at 0.33 between albedo and TGSI. According to the DDI index, the desertification situation in the region has been in the alarming range. In fact, based on the albedo ratio with the MSAVI index, 55.6% of the region is classified as very severe desertification. While only 1.9% was very low in the area of desertification. According to albedoNDVI ratio, 68% of the region is in a very severe desertification state. The values obtained for the two models are very close to each other and similar estimates have been obtained in the estimation of extreme and very low values. Investigations showed that the studied area has been severely affected by desertification.

In addition to yield, drought also affects water quality. Therefore, for long-term agricultural planning, the climatic situation of the regions must be determined. Therefore, in the present study, while evaluating the effects of drought on the quality of surface water salinity, the effects of drought and water salinity on the rent of agricultural lands were examined. For this purpose, by using SPI index, drought classes in the region were determined and by using QUAL2K model, water salinity was simulated in Taleghan river. Then, using Ricardian's approach, the effect of climatic, salinity and economic variables and their interactions on agricultural land rent were evaluated. The results of the QUAL2K model show that the drought has a direct and non-linear relationship with surface water quality, so that with decreasing river flow during moderate, severe and very severe drought classes, salinity decreases by 20.5, 41.3 and 57.8%, respectively. Based on the results of the Ricardin model, agricultural land rent is inversely related to water salinity and temperature, and is directly related to rainfall. The results of changes in the rent of agricultural land also showed that during the middle, severe and very severe drought classes, land rent decreased by 17.7, 32 and 42.4 percent, respectively. Therefore, it is suggested that farmers' compensation be determined on the basis of the amount of "lost rent", as it provides an accurate estimate of the actual amount of drought damage.

In recent years, with droughts and declining irrigation water, efficient use of water and water management has become inevitable. For this purpose, in this study, the risk effects of irrigation strategy in Qazvin plain in the 2015-2016 were analyzed. Initially, the percentage change in water quantity was calculated during the drought period. Then, using water-yield functions, deficit irrigation was applied to plants in four scenarios of 19, 32, 44 and 51% corresponding to the periods of weak, medium, severe and very severe droughts. Then, using the TM-PMP model, the risk effects of drought were investigated on the cropping pattern and water consumption productivity. The results showed that deficit irrigation increased the area under crops of wheat, barley and beans. This management strategy drastically reduces gross income by 24 percent in very severe drought conditions. Income risk is reduced by applying a deficit irrigation scenario during drought periods. Gross margin also decreases non-linearly as income risk. Water use efficiency decreased for wheat, barley, corn, tomato, maize and bean crops, and increased for beet and alfalfa crops. Therefore, if the irrigation strategy is implemented, the rate of income reduction in drought conditions will be 24%, but otherwise the income reduction will reach 58 percentages.

Soil salinity and soil salinization as one of the problems facing agriculture and natural resources are of great importance which needs to be prevented with proper knowledge. In this regard, it is important to obtain information about soil salinity and vegetation, such as their amount and distribution. The use of satellite data enables extensive study of soil salinity and vegetation. Since vegetation in most arid and semi-arid regions is strongly influenced by soil properties such as salinity, therefore, this study investigated the effects of Interceptor Drain on soil salinity and vegetation changes using remote sensing capabilities in a 15-year interval. Results showed that construction Interceptor Drain in Salt Marsh Qazvin plain had no effect on soil salinity changes and vegetation cover. According to the results of correlation test between measured soil elements and satellite image bands, bands 5 and 7 were highly correlated with soil SAR (Sodium Adsorption Ratio) index prior to drainage construction and thus, the two bands after drainage construction had a significant correlation with soil EC (Electrical Conductivity) index. In fact, indices including red and infrared bands showed a significant relationship with soil salinity parameters. Also the results of correlation test of remote sensing indices and ground data in the salinity area showed that SI (Salinity Index) index had a highly significant correlation with soil salinity data.

One of the methods of salinity monitoring is ground-based data, which can be time-consuming and costly, especially if large-scale monitoring is performed over multiple time periods. Using Remote Sensing method and georeferenced and laboratory data, soil salinity changes over time can be monitored. The spectral reflectance of a variety of salts at the soil surface has been studied in several studies which has been used as a direct indicator in remote sensing. However, when the soil moisture is high or the salt layer is not visible at the soil surface or the salt is mixed with other soil components, the direct salinity detection approach will become more complex. However, vegetation and saline-friendly plants can be used as a sign of soil salinity for indirect detection and identification of saline areas based on spectral reflectance of plants. The purpose of the present study was to investigate the trend of soil salinity and vegetation changes using remote sensing capabilities in two intervals before and after construction of Interceptor Drain in Salt Marsh Qazvin plain. Therefore, the trends of soil salinity and vegetation changes over a 15-year period have been studied.

The study area is located in a part of Qazvin province, 150 km northwest of Tehran and the major cities adjacent to the area in Qazvin are Takestan  in the west, Abike in the north and Dansfahan in the southwest. Due to the geological conditions of the bedrock and deposition of sediments and groundwater discharge from Qazvin and Hashtgerd Plains, the marsh has been formed which has become saline due to years of severe evaporation. Most saline species have little growth in the salinity range and only in the months when rainfall increases and it is moderately saline, the plants with moderate to low salinity resistance and with a low vegetative period have a short time. Then, with increasing salinity, the soil is seated and dried; only saline-resistant plants in this area survive for the remainder of the year.In this study, spatial and temporal variations of vegetation and soil salinity were investigated using Landsat 7 satellite images. After calculating salinity and vegetation indices, the spatial variability map of soil salinity and vegetation index was prepared. In this study, Landsat satellite images during years 2004 to 2018 were used to study the trends of soil salinity and vegetation changes in Salt Marsh Qazvin plain. After analyzing the remote sensing indices in the study area, the data from satellite images and georeferenced data were compared. The soil salinity and vegetation indices used in the study included 6 soil salinity indices and 5 vegetation indices. The soil samples used in this study were related to 99 observation wells dug in the Proximity of Interceptor Drain of Salt Marsh Qazvin plain during 2010 and 2012.

According to the results of correlation test between measured elements in soil and satellite image bands, bands 5 and 7 were highly correlated with soil SAR index before drainage construction, and thus two bands after drainage construction, with soil EC index. The use of different soil salinity and vegetation index equations gives the results the differential preferences to achieve adequate soil salinity and vegetation index estimation on a large scale using remote sensing data. The evaluation of different soil salinity indices was based on the Statistical test. Statistical test results comparing mean at seasonal variations scale showed that remotely sensed indices related to soil salinity monitoring including BI, SI, SI1, SI2 and SI3 indices showed significant response to seasonal changes in surface soil condition. On the other hand, indices related to monitoring of vegetation status showed a significant difference in vegetation status from spring to summer. The results of correlation test of remote sensing indices and ground data expressed that in the salinity range of SI index there was a significant correlation with soil salinity data. Mean correlation results demonstrated that GVI had a high negative correlation with all salinity indices, but there was less correlation between salinity and other vegetation indices. The satellite images used in this study indicated the highest correlation with soil salinity in the dry months of the year and the correlation between the two factors was reduced in the months with precipitation. Soil salinity estimation based on SI index has been investigated in several cases which revealed that this index is accurate in estimating surface soil salinity in arid and semi-arid regions.

The present study showed that Interceptor Drain of Salt Marsh Qazvin plain had no effect on soil salinity and vegetation changes in the region, so none of the 11 indices derived from satellite images had significant changes in the period before and after drainage. In other words, soil salinity and percentage of vegetation in the Salt Marsh Qazvin plain have not changed significantly over a period of 15 years. However, due to the dryness of the area and the lack of rainfall as well as the incidence of drought, the fresh water content for natural leaching of adjacent drainage lands is limited and the drainage increases the intensity of groundwater flow and reduces soil salinity by creating a hydraulic gradient. Strengthening of vegetation in the area is affected by drainage. As the Qazvin Plain is one of the agricultural hubs of the country, hence the expansion of saline lands is one of the biggest threats to agriculture in the region. Since deep soil salinity status is one of the important factors in the establishment of vegetation in the region, studies combining remote sensing method, geophysical data and simulation models can lead to a better understanding of the status of the area.

The knowledge of spatial and temporal distribution of water requirement provides a relationship between land use, water allocation and consumption that can lead to an appropriate management of water resources. In the present study, based on mapping of spatial and temporal water requirement distribution and applicability of METRIC Algorithm was assessed for estimating daily evapotranspiration and seasonal water requirement, as well as crop coefficient in Qazvin highland desert. For this purpose, five high resolution (30m×30m) Landsat 7 ETM images were used during April to November 2000, as the agricultural activity period. The latent heat flux of evapotranspiration and instantaneous evapotranspiration were obtained based on the algorithm. The instantaneous evapotranspiration was extended to a daily scale and to the whole growing season through two extrapolation procedures. The accuracy of the maps was analyzed using lysimetric of alfalfa and maps of the produced crop coefficient were evaluated by using lysimetric of alfalfa and grass. Results indicated that relative error in crop coefficient estimation was between 0.053 and 0.138. Comparison of estimated and measured evapotranspiration demonstrated an appropriate consistency between results (r=0.92 and RMSE=0.60 mm/day). The amount of evapotranspiration at the pixel of the lysimeter location was estimated 1232 mm during the studied period. The findings revealed that METRIC algorithm can be applied as an effective, practical and affordable approach in accurate estimation of actual evapotranspiration at semi-arid and arid highlands area.

The Approach of being compatible with nature is very important so that complying withenvironmental housing will be a valuable step in modulating the energy challenges. Thevillages and the rural - urban located suburban have considerable importance .In this study,firstly, population-based study has been done to determine the need for housing in ruralnorthern plains of Qazvin using Statistics, Population and Housing in the years, 1996, 2006and 2011 .Then according to the data from meteorology stations within and adjacent areas,climatic zoning in Arc GIS was performed. Finally, climate comfort zone with experimentaleffective temperature (ET) and the application of physiologically equivalent temperature(PET) was calculated. The results showed, In terms of population, study rural housing is thejustified. Map and typing climate became semi-arid to arid climate along the northwest to thesoutheast of the region. As a result of the differences in climate, the climate comfort in thesoutheast direction, shows a significant decrease. The results of this study is to recommendpractical cases such as run compact architecture with heavy roof and wall, locating veranda inthe North East of houses, roof openings and brick facade of the application .