Shahriar Khaledi; Ghasem Keikhosravi; Farzaneh Ahmadibarati
Abstract
Extended AbstractIntroductionAmong the climatic elements, the effect of temperature in an area and its changes is the perception of land reclamation and can be maintained and land use of a place. Mean while, surface temperature is an important factor in global warming studies and as a representative ...
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Extended AbstractIntroductionAmong the climatic elements, the effect of temperature in an area and its changes is the perception of land reclamation and can be maintained and land use of a place. Mean while, surface temperature is an important factor in global warming studies and as a representative for climate change and radiation balance estimation in energy balance studies. Due to the special heat that each cover has on the ground. Vegetation land uses, barren lands, water resources, residential areas, absorb some of the sun's radiant energy and increase the temperature of the earth's surface. Finally, this heat is emitted from the surface of various coatings to the environment in the form of long wavelength radiation. If the surface temperature is calculated in different periods, the process of increasing or decreasing the surface temperature of different types of surface coverings can be modeled. MethodologyIn this study, to study the changes in land cover, MODIS images related to land cover from 2001 to 2019 were received. Surface cover product (MCD12Q1) Surface temperature product (MOD11) was prepared on a daily scale for both Terra and Aqua satellites to provide a variety of surface temperature indicators in the Google Earth engine system. In environmental studies, we often deal with observations that are not independent of each other and their interdependence with each other is due to the location and location of the observations in the study space. For this purpose, to reveal the effect of land cover on surface temperature components, global Moran correlation analysis tool was used and to analyze clusters and non-clusters, local Moran insulin index was used. In the last step, to evaluate the relationship between circadian surface temperature, daily temperature and night temperature After converting NDVI and LST raster maps to vector maps, Pearson correlation coefficient, regression relationship and significant value between variables in R programming environment were calculated.DiscussionBased on the land cover product of Modis 5 sensor, the predominant cover including shrubs, grasslands, agricultural lands, scattered vegetation and residential areas were identified between 2001 and 2019. The largest area of the region is scattered vegetation (50%) and secondarily grasslands (20%). During these 19 years, the cover of shrublands and the cover layer of scattered plants has an increasing trend and the cover of grasslands and arable lands has a decreasing trend. The surface temperature of this region has a spatial structure and is distributed in the form of clusters, so it has a spatial relationship with the natural features of the region. Spatial patterns of spatial data on surface temperature are divided into three categories: hot spots, cold spots, and clusters. Low-lying areas of the south and part of the east and west of the area, hot spots, high-altitude areas that include parts of the central areas in the south and north of the area, cold spots and cold spots margin, clusters (foothills) they give. On the 24-hour surface temperature scale, the land use layer of settlements and agricultural lands shows the most significant relationship between the types of land surface cover. In the daily temperature scale, the land use layers, grasslands and scattered vegetation have a decreasing trend and the use layer of shrubs and settlements has an increasing temperature. At night surface temperature scale, the trend of significant surface coatings in relation to the microclimatic element of surface temperature intensifies so that field cover, scattered vegetation and habitat layer have the highest correlation with increasing night surface temperature Show them selves. Therefore, in the study of spatial pattern of surface temperature, latitude and altitude are the most influential factors and in the study of the effects of land cover, the layer of settlements in three surface temperature parameters (minimum, maximum, average) of the highest temperature increase compared to others. Uses have been enjoyed. ConclusionLand use type and land use changes and vegetation have a significant effect on land surface temperature changes. In the northeastern region of the country, shrub cover, grasslands, arable lands, scattered vegetation cover and residential areas are the dominant cover of the region. During 19 years, the increase in the area of scattered vegetation and barren shrubs indicates negative changes in the ecosystem of the region. In such a way that the area of other classes such as arable lands and grasslands has been reduced and the area of these classes has been increased. The surface temperature of this region has a spatial structure and is distributed in the form of clusters in 3 clusters. Hot clusters, low-lying areas, cold clusters, high-altitude areas and inconveniences covered the foothills. Elevation factor, latitude are influential in the distribution of clusters. In studying the effects of land cover on the surface temperature of the land, during 19 years, the circadian temperature of the settlement layer has increased by about 1.12 degrees and the arable land layer by 0.41 degrees Celsius. On the daily temperature scale, the settlement layer has a temperature increase of about 1 degree. At night surface temperature scale, arable land cover, scattered vegetation cover and habitat layer recorded 6.2, 0.8 and 0.6 ° C temperature increase, respectively.
Mahmood Ahmadi; Hasan Lashkari; Ghasem Keikhosravi; Madjid Azadi
Abstract
Abstract
The present study was conducted to simulate precipitation and temperature with the RegCM4 and LARS dynamic model in two states, with and without using the statistical post-processing technique of direct model output in the north-east of Iran (Great Khorasan) and the statistical period of 1987-2011 ...
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Abstract
The present study was conducted to simulate precipitation and temperature with the RegCM4 and LARS dynamic model in two states, with and without using the statistical post-processing technique of direct model output in the north-east of Iran (Great Khorasan) and the statistical period of 1987-2011 in the annual time period. Based on the results, the annual bias average raw precipitation is equal to 53.63 millimeters and the post-processed is -11.25 in the LARS model in the study area during the 2007-2013 verification period. In summary, performing post-processing technique has been effective at 84% of the study stations in annual time scale and has reduced severely the bias error rate in most stations. Based on the results obtained from the RegCM4 model, the annual bias average raw rainfall of the RegCM4 model is calculated to be 85.3 millimeter and the post-processed to be 61.04 during the 2006-2011 verification period. Therefore, error values in most stations are very high before and after processing and the model results are not acceptable. In summary, performing post-processing technique has been effective at 75% of the research stations in annual time scale. Therefore, the absolute value of the bias error of the average annual rainfall post-processing of the LARS and RegCM4 models are equal to 13.6 and 61 respectively. The annual bias average raw temperature of the LARS model is equal to 0.096 degrees Celsius and the post-processed is -0.432. Practically, this is larger than the bias without post-processing, so post-processing operation is not effective in all stations and is only well defined in 46% of the stations. Simulation of 2 meter temperature data at the meteorological stations using the RegCM4 model as well as MA operations showed high efficiency.The annual bias average raw temperature of the RegCM4 model was -2.78 degrees centigrade which fell to -0.05 after applying post-processing technique. At all stations, the modelled annual temperature is different from observational data less than 0.1 ° C. Therefore, in the simulation of annual rainfall data, the LARS model is even more responsive than the RegCM4 model. And, in simulating the annual temperature data, the RegCM4 dynamic model shows a much better reality than the LARS statistical model.
Ghasem Keykhosravi; Zahra Yarmoradi
Volume 23, SEPEHR , July 2014, , Pages 25-31
Abstract
Supplying crops’ water needs in arid areas is only possible through irrigation, since low precipitation, high evaporation and inappropriate distribution of rainfall makes dry farming economically unjustifiable. Yet, perennial rivers cannot supply water needs of different sectors, and the shortcomings ...
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Supplying crops’ water needs in arid areas is only possible through irrigation, since low precipitation, high evaporation and inappropriate distribution of rainfall makes dry farming economically unjustifiable. Yet, perennial rivers cannot supply water needs of different sectors, and the shortcomings must be compensated from other areas like underground resources. In arid and semi-arid areas, inconstant distribution of precipitation across time and space and lack of appropriate vegetation have changed the life-giving precipitation into a natural disaster which becomes useless in the form of devastating flood. In such areas, artificial feeding of groundwater resources by floodwater is a way of preventing land degradation.
In the present article, we first produced different maps (slope, soil, land usage, Isohyetal) of Sabzevar city. Then adapting information layers using GIS, appropriate places for artificial feeding of groundwater were exploited. Afterwards, distribution map of Quaternary alluviums across the city was exploited in GIS environment to determine appropriate places for distributing floodwater.
Results indicate that 3279.96 km2 (out of 20502 km2, 16%) are appropriate for artificial feeding plans, and around 6017.76 km2, i.e. around 29.4 percent of the city area are appropriate for floodwater distribution plans. Finally integrating these two maps, an area of around 1591.56 km2 (7.76%) is estimated to be appropriate for artificial feeding and distributing floodwater in this city.
Hassan Lashkari; Ghasem Key Khosravi
Volume 19, Issue 75 , November 2010, , Pages 60-66
Abstract
Strong winds have been named storms, which, in various forms and at high speed, blow over for a short time and are usually accompanied by unstable air. If unstable air is humid, a thunderstorm, and if it is dry, a dust storm will form (Alijani, 2000). In all stations of Hamadan province the majority ...
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Strong winds have been named storms, which, in various forms and at high speed, blow over for a short time and are usually accompanied by unstable air. If unstable air is humid, a thunderstorm, and if it is dry, a dust storm will form (Alijani, 2000). In all stations of Hamadan province the majority of thunderstorms occur in the spring. In this season, the greatest number of thunderstorms have occurred due to increased solar radiation energy, which is characterized by significant atmospheric moisture content due to evaporation and vegetation cover, wet lands and transitional thermodynamic systems from the west and southwest of the country. The fall season is second in terms of the number of Thunder storms. In this season, due to the high radiation energy and the arrival of unstable systems with an appropriate moisture source, the number of thunderstorms is significant. The smallest number of thunderstorms belongs to winter. The maximum average of dust storms occurs mainly in dry areas without vegetation, and the number of these storms is less in the mountainous areas of Hamadan. The seasons with most frequent storms in the districts of Ekbatan, Hamadan, Noghe and Malayer are spring and summer, and at Nahavand station the summer season. The study of the trend of hourly changes in storms frequency shows that the maximum occurrence of these storms is from 9 am on, and at 6 p.m. their intensity and frequency decreases, and in all stations the frequency of these storms is higher in days than in nights. According to the conducted surveys, the most activity of dust storms is in the spring and summer. Although during this period of time the ground for local instability is provided due to the high radiation energy and suitable topographic conditions, but the energy of the systems is evacuated as dust storms because of the lack of adequate moisture.
