Physical Geography Research
Year:2015 | Volume:47 | Issue:3 |Papers Count:12

IntroductionHydrograph of springs represents clearly all physical processes that control ground water flows inside aquifer (Kuto et al., 2012: 41). Study of the curve can reveal information about structure and function of aquifer, particularly hydrodynamic parameters including permeability and storage (Troch et al., 1993: 228). Analysis of recession curve has the advantage to calculate parameters of drainage mechanism such as recession coefficients. The volume of the primary discharge is sum of rapid and base flows and the specification of sub-regimes (Malık and Vojtkova, 2012). Identification of base flow properties and its prediction in dry period is necessary to determine the storage and to prevent it from pollution (Dewandel et al., 2003). Karstic aquifers are an enormous reservoir of water in many regions of the world and with decline in quality and the amount of alluvial aquifers they got important more as a strategic hoard of water (Suta, 2008: 856). The karstic aquifers are the main source of water for human society and ecosystem of Alvand Basin. They also provide the base flow of Alvand and are important in initiation and continuation of civilization in this basin. The purpose of the study is to assess the development of karst in the aquifers of Alvand using the analysis of recession curve hydrograph.

IntroductionSelection of the clear and transparent index for the precipitation using long-term homogeneous data is an important point for the researchers. Several investigations have led to different indices for heavy rainfall. In some cases the specific amount of precipitation was used for heavy rainfall (Rahimzadeh, 2005; Masoodian, 2008; Kamiguchi et al., 2006), e.g. Alijani (2002) has suggested the precipitation more than 30 millimeter. Some investigators have used the percentage of daily precipitation as a heavy rainfall index (Mohammadi and Masoodian, 2010), e.g. Easterling et al. (2003) used the greatest annual 5-days total precipitation amount and the percentage of annual precipitation, due to all 24-h rainfall totals exceeding the 95th percentile of daily amounts. A series of international workshops have introduced a set of indicators to show the effect of climate change on extreme events (Folland et al., 1999; Nicholla and Murray, 1999; Manton et al., 2001).

IntroductionThis research addresses the automatic extraction of alluvial fans using four methods of segmentation from satellite data. This segmentation method divides images into partitions. It is typically used to recognize objects or other relevant purposes in digital images (Fu, 2013:3260). Alluvial fans have always been a landform that attracts human because they are suitable areas for living due to freshwater and appropriate soil for drinking, cultivation, making pottery, making mud-brick and other activities (Maghsoudi and Azizi, 2012: 23). Therefore, alluvial fan extraction is significant in the planning of engineering geomorphology and other related disciplines.

IntroductionThe main perspective in seasonal prediction of precipitation is presentation of a qualitative prediction for upcoming seasons. The information gained from such predictions can be used for decision making in various disciplines such as agriculture, water management and hydropower production. Besides, it can help us reduce the adverse effects of climatic changes like drought and flood. But General Ciculation Models (GCMs) outputs have coarse resolution (>100 km). Dynamic downscaling is a method to obtain high-resolution climate data from relatively coarse resolution global climate models which do not capture the effects of local and regional forcing in areas of complex surface physiography. GCMs outputs at spatial resolution of 150-300 km are unable to resolve important sub-grid scale features such as clouds and topography. Many impact models require information at scales of 50 km or less. Several statistical and dynamical methods are developed to estimate the smaller-scale information. Dynamical downscaling uses a limited area, high resolution model (a regional climate model: RCM) driven by boundary conditions from a GCM to derive smaller scale information.

IntroductionThunderstorms pose a significant threat to modern societies and their assets. Despite their local-scale characteristics, severe thunderstorms and associated extreme events like heavy rainfall, hail, gusts, or tornadoes can cause considerable damage to agriculture, buildings, or infrastructure, and facilities. Thunderstorms are highly localized and largely stationary weather systems. They affect a limited area of about 20–50 km2, depending on the size of the cumulus tower. They are associated with shower clouds in which electrical discharges can be seen as lightening and heard as thunder on the ground. They represent an advanced stage in the development of convection in moist air. The importance of the rainfall generated by the thunderstorms lies in the fact that it is largely torrential and of high intensity, and as a result much is lost as runoff which causes flooding. Basically thunderstorms occur more frequently above land areas in the warm season, while they are more frequent in the cold season over oceans. A lot of factors impact their occurrence. Among them the most important are the thermodynamic and kinematic states of the atmosphere, topography, land cover, and its coastal configuration and atmospheric circulation conditions. Ardabil is located in the northwest part of Iran, for this reason it has always been under the influence of the thunderstorms. Due to the geographic location and specific local conditions in this region, every year numerous thunderstorm events happen in this area and cause severe damages to the agriculture, utilities and infrastructure sectors. From this point of view, studying this phenomenon in detail and identifying the synoptic patterns of the ground surface and upper levels in which they are formed in Ardebil are vital and important for the region.

IntroductionPrecipitation plays an important role in the global energy and water cycle. It is important for assessment and management of land use, agriculture and hydrology such as flood and drought risk reduction to know about the amount of precipitation reaching the ground water. Assessment of climate change and its effects require long-term rainfall analysis in all spatial scales. Growing concern in the scientific community (Nicholls and Alexander, 2007) is about whether there is a significant change in the amount of precipitation?. About 29% reduction in the daily maximum water flow caused higher temperatures and increased evaporation with any change in rainfall causing drought in southern Canada during the years 1847 to 1996 (Zhang, Harvey, Hogg and Yuzyk, 2001). Recently summer drought caused by unusually dry heating in the areas related to tropical West Pacific and Indian Ocean (Andreadis, Clark, Wood, Hamletand and Lettenmaier, 2005; Pagano and Garen, 2005) including studies of climate change on global precipitation regimes. Germer (2008) has examined monthly variations in rainfall, floods, droughts and runoff in the Yangtze River Basin in China. In another study, Dao (2004) studied the daily variation of rainfall in semi-arid regions of northern China. Raziyy and Azizi (2008) said that topography and latitude are main factors of controlling the precipitation in the west part of Iran. Also, Asakereh (1386) has investigated spatiotemporal variation in Iran precipitation.

IntroductionLand use change and its effects on soils is one of the important factors that decrease soil quality. Nowadays because of rapid growth of population, vast forest areas are changed into agricultural lands but chemical properties of the soils are commonly affected by changes in land usage. Converting the forest areas into agricultural lands is one of the prevalent issues in Iran, especially in north Iran. Nevertheless, relevant studies about the effects of land use change are very limited and lack of enough and suitable studies due to quantifying of these effects is so significant. Because of that, this study was carried out to investigate the impact of changes in usage of forest lands into the dry farming lands (canola) and paddy lands on some chemical properties of soil such as: pH, organic carbon, total nitrogen, available phosphorous and potassium, electrical conductivity and cation exchanging capacity in Zarin Abad area of Sari, in northern Iran.

IntroductionPrecipitation is a vital component in the hydrological cycle. Its spatio-temporal variations have great environmental and socioeconomic impacts. The spatial variation of rainfall depends upon many factors. Some of these variations are due to synaptic systems and some others formed by local physiographical characteristics of stations such as elevation from sea level, slope, windward and leeward slopes, land cover and land use and etc. If the rainfall is formed by widespread and pervasive synoptic system, it can show a significant spatial similarity and homogeneity in the amount of a given rainfall in all over the region. This is affected by synoptic system. But if the rainfall is dominated by local factors the higher heterogeneity of given amount of the rainfall can be expected.

IntroductionIdentification of active tectonic areas, especially in convergent zone are very important because of their potential risks. Nowadays, there are several algorithms that are used for tectonic analysis; one of them is TecDEM that is used in this research. In this study, using Remote sensing techniques, geomorphometric analysis and fieldwork were conducted to analyze morphometric and geomorphologic characteristics of Roodak basin in northeast region of Tehran in the TecDEM model within Matlab software. This model used new indices such as Skewness and Kurtosis of hypsometry diagram, concavity and steepness indices and finally Isobase Map. The obtained results from this calculation represent morph otectonic changes on the watershed. The results in the TecDEM model in comparison with field studies. The obtained evidence through Garmabdar Geodynamic station data shows accuracy of the model at Description and Analysis neotectonic terms area.

IntroductionWater is the most important parameter in the development of human societies. One of the pillars in the development of water resources is the investigation of environmental conditions and environmental compatibility of the project. Identification of the areas vulnerable to pollution can play a major role in development strategies. In most areas of Iran, located in the arid and semi-arid region, groundwater is the most important water supply for agricultural, domestic and industrial uses. In most areas, the risk of groundwater contamination is considered as a serious restriction for this source. Therefore, it is essential to avoid groundwater contamination in groundwater resources management. One of the methods to identify vulnerable areas is the use of qualitative indicators. Among the qualitative indicators, the DRASTIC index of vulnerability to groundwater pollution has many applications. This index is obtained by combining seven different parameters. Each of the parameters of the model investigates the potential and the possibility of accepting the contamination of the aquifer and each parameter has a unique weight. So far, most studies which have been done with this indicator have led to aquifer vulnerability mapping but model calibration and optimization of input coefficients is less studied. This study was conducted to investigate the vulnerability of Birjand aquifer and increase in the accuracy of the model.