All other Geographic fields of studies , Interdisciplinary
Sajjad Bagheri Seyed Shakeri; Abbas Alipour; saman maroofpour; Seyed Moustafa Hashemi
Abstract
Introduction The exploitation of natural water resources requires recognition of the quantity and, in particular, its quality. It is important to study the quality and quantity of flow in the river in order to evaluate its locative changes for its various uses. Usually the flow crossing the river is ...
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Introduction The exploitation of natural water resources requires recognition of the quantity and, in particular, its quality. It is important to study the quality and quantity of flow in the river in order to evaluate its locative changes for its various uses. Usually the flow crossing the river is a source of water supply in various sectors of consumption, including drinking, agriculture and industry. Therefore, knowing the changes in the quality of river flow can have a significant impact on management and planning at harvest time and water consumption, especially drinking. Various studies have been done to predict and study water quality, but in terms of the quality of surface water, less attention has been paid to smart modeling. The superiority of smart models is determined in solving nonlinear and bulky problems that cannot be solved with high precision. Najah et.al (422: 2009) also emphasized the ability of neural networks to predict Malaysian ink's river water quality indices and the ability to estimate electrical conductivity (EC) and total dissolved solids (TDS) values and opacity in this basin. Kunwar et.al (95: 2009) has also used perceptron neural networks to model the quality parameters of the biological oxygen demand (BOD) and dissolved oxygen (DO) of Gottmy river in India and has emphasized its proper efficiency.The main objective of the present research is to construct a soft calculation model for estimating the salinity of the Nisa river flow at the site of the Yalkhary hydrometric station using various input scenarios which in areas such as the present study, there is the problem of data deficits, information, as well as lack of facilities and enough cost, can be done by using an estimation model with acceptable water quality accuracy.
Climatology
Yousef Ghavidel Rahimi; Mohammad Rezaei
Volume 19, Issue 54 , February 2016, , Pages 253-277
Abstract
Heat waves are considered as one of the important climatic hazards in the world and especially in Iran and it seems that, due to intensification of global warming, their occurrence has increased in recent years than in the past. This study has paid attention to quality and quantity evaluation and synoptic ...
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Heat waves are considered as one of the important climatic hazards in the world and especially in Iran and it seems that, due to intensification of global warming, their occurrence has increased in recent years than in the past. This study has paid attention to quality and quantity evaluation and synoptic analysis of heat waves in the KermanProvince. For this purpose, At first, the daily maximum temperature data, in month of July (as the warmest month in the year) was put in a statistical period of 24-years (1986-2009) from meteorological organization, for 4 synoptic stations of Kerman, Bam, Anar and Sirjan. In order to classify heat waves, standardized temperature data and on its basis, anomalies of 0 to 0.75 as a heat wave, 0.75 to 1.5 as severe heat waves, and greater than 1.5 were determined as super heat wave. The threshold values of 43.1, 42.1 and 41.2° C were calculated for all stations, respectively as threshold of heat wave, severe heat wave, and super heat wave and its continuity were considered at least for two days. Accordingly, During Statistical period of study, it was found 7 heat waves, which were, identified within 3 severe heat waves, and 1 super heat wave. Super heat wave in July 1998, was selected For the Synoptic analysis. This three-day wave, with an average temperature of 43/11° C, has been the most severe heat wave in KermanProvince. Results of synoptic analysis of super heat wave indicated that the establishment of Ganges low pressure on the ground and the domination of subtropical high-pressure of azores in high levels and also, high thickness atmosphere on the study area caused the subsidence of warm air and excessive heating of earth's surface, and created them mentioned super heat wave.
Kamal Omidvar; Mehdi Mahmodabadi; Farshad Safarpour
Volume 19, Issue 51 , April 2015, , Pages 21-39
Abstract
Abstract In this research we investigated synoptic pattern of heavy rain 1 and 2 February 2011 in southern and central regions of Iran specially Kerman province. At the first we calculated heavy rain for all of synoptic stations with use Extreme value type1 then thermodynamic characteristics of heavy ...
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Abstract In this research we investigated synoptic pattern of heavy rain 1 and 2 February 2011 in southern and central regions of Iran specially Kerman province. At the first we calculated heavy rain for all of synoptic stations with use Extreme value type1 then thermodynamic characteristics of heavy rain analyzed with use radio sounding and Skew-t data. For analyzing of this phenomenon we used daily rainfall data 32 synoptic stations of southern and central regions and SLP and 850, 500 and 300 hgt maps. In the 5 day periods, we investigated synoptic pattern formation and its trend in weather maps. The results show that main factor of precipitation in region is formation of cut off low on Mediterranean sea. This system act so blocking and with move onto east, it causes that trough of east Mediterranean reinforcement thus west systems penetrate to lower latitude and they get high level of humidity from south seas and they makes sever precipitations in the study area.
Swywd Hossein Mirmousavi; Mina Mirain
Volume 16, Issue 38 , February 2012, , Pages 153-178
Abstract
Ggiven that assessment data often point to be made, are necessary to generalize to the entire region, Interpolation operation have been done on areas of precipitation. In this study using Kriging and inverse weight method, interpolation of rainfall in KermanProvince has been attempted. For this purpose, ...
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Ggiven that assessment data often point to be made, are necessary to generalize to the entire region, Interpolation operation have been done on areas of precipitation. In this study using Kriging and inverse weight method, interpolation of rainfall in KermanProvince has been attempted. For this purpose, the monthly rainfall statistics for 9 synoptic stations in Kerman province and 11 synoptic stations neighboring provinces have been used.
The results of this study indicate that Kriging method with lower error levels is more appropriate for the interpolation of rainfall in this region. Models based on fitted Semivariogram models, Spherical, linear and exponential models provide better facilities for the preparation of a precipitation isomap. Between models in the spherical model for the months January to June and also in December, the exponential model for the month of July and the exponential model for the months August to November show the most appropriate change model views that are detected. Based on maps prepared for different months, while the highest rainfall occurred in winter time change the amount of the highest range 42-13 mm in the season. Spatial gradients of changes in precipitation decrease trend are from south to north. Other seasons in the low average range of precipitation changes also showed no significant fluctuations.
