پژوهشی
Sahar Forotan; Alireza ILdoromi; Hamid Nouri; Matab Safari Shad
Volume 6, Issue 20 , December 2019, Pages 1-20
Abstract
1- Introduction Land use change is a hydrological challenge for urban watershed management that effects on the management methods through surface runoff changes. Remote sensing, GIS techniques and satellite imagery can be used to improve and accelerate the management of natural resources and urban areas. ...
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1- Introduction Land use change is a hydrological challenge for urban watershed management that effects on the management methods through surface runoff changes. Remote sensing, GIS techniques and satellite imagery can be used to improve and accelerate the management of natural resources and urban areas. This study investigates on the relationship between urban development and runoff values using hydrological modeling, GIS and remote sensing. First, the land use maps of the city of Asad abad were prepared using TM and ETM + sensors of Landsat 5 and 7 in May, 1992, 2002 and 2014. For supervised classification and estimate of surface runoff were used maximum likelihood method and Resources Conservation Service National (NRCS-CN) respectively. The maps of land use, curves number and runoff amount were calculated and plotted. The results showed that surface runoff has been increased about 15.8 % due to increase of 4/59 % of urban land use. Management of atmospheric precipitation and surface runoff from watersheds that are a factor in collecting and transporting hazardous pollutants while passing through streets, streets and other urban areas. Risk management is inevitable in relation to public health and urban environmental resources. Increasing the impenetrable levels caused by urbanization and construction of the building on permeable soils, naturally, has decreased the permeable levels of the basin, which is capable of absorbing part of the rainfall, and thus has increased the total amount of runoff in the city. One of the important issues of urban development is the change in surface runoff. So that the delay time of the hydrograph and the base time of the flood is reduced and, consequently, with an equal volume of flood, the peak flood discharge with urban development will be more than the pre-development, in addition, the runoff coefficient also increases (Amir Ahmadi, 2011:92). Regarding the management and optimization of watersheds, accurate prediction of outflow runoff can be very effective in optimizing watershed management to prevent regional flood rebound. Despite the nonlinear relations, the uncertainty and the lack of clarity and the characteristics of time and place variables in the flow systems, none of the proposed statistical and conceptual models have been able to be considered as a superior and capable model in order to accurately model rainfall and runoff. To be known. Remote sensing and GIS technology is one of the most effective and efficient technologies for environmental change and resource management that provides updated information for management purposes (Janson, 2012: 86). Therefore, this tool can be used to study urban development. Considering the previous studies and the importance of the phenomenon of physical development of the city and increasing the impenetrable levels on the relations of rainfall, urban runoff is very important with regard to the urban development process using an efficient tool such as remote sensing along with hydrological models (GIS Special Website, 2014: 1) The city of Asadabad is also no exception because of the increase in inertia levels following the expansion of the city. The location of the city is such that it has spread in three watersheds, and this form of expansion, as well as the lack of such a study, requires the study of urban runoff and The impact of urban development on production runoff in the area is doubled. The present study attempts to investigate the physical development of Asadabad in 1992, 2002, 2014 and its effect on runoff rainfall relations. 2- Methodology The city of Asad Abad, in the area of 1195 km2, forms 6.1% of the area of Hamedan province. The average elevation is 1607 meters.The Annual rainfall is between 350 and 500 mm (Aka Iran,2014:1). In this study, the relationship between urban development with distributed hydrological modeling of the integrated approach of remote sensing and geographic information system was used. Landsat satellite data was used to detect land cover changes (Kavosi and Vatan khah, 2013:4). The SCS method estimates runoff in unobstructed watersheds according to rainfall and the characteristics of the watersheds. Basically, this method will be valid when runoff is due to rainfall, and it is not effective at a time when snowfall. The American Conservation Survey (CNS) Curve Number (CN) method is one of the most common methods for estimating and forecasting flood volume and runoff and flood altitude (Mahdavi, 2009: 86). In this research, the average monthly long-term average was calculated in inches. Then, layer the point rainfall in Arc GIS, and digital calls and using IDW interpolation was to be the second (Javadi, 2011: 59). To estimate the runoff of the study area, we calculated the weighted mean of runoff. For this purpose, the data was transmitted from the descriptive table in the Arc GIS software to the Excel environment (Zhang, 2014: 956). After calculating the total runoff heights, the values obtained were retrieved in millimeters in the tables and graphs. In this research, all of the above was done in three periods of time, 1992, 2002, and 2014, we tried to use the results of 1992 and 2014 to review the changes and to use the 2002 changes to verify. So the results are presented every three times. 3- Results Land use classification maps in Arc GIS software procurement and since the purpose of assessing changes in three different periods, a guide map has been changed for better. After the land use was extracted in the time periods studied, the area of each user and the percentage of the area of each user were calculated. Generally between the years 1992 and 2014 in the area of other Land use 5.45% (equivalent to 63.9 square kilometers) declined. The urban and non-urban usage map was extracted from the land use classification map for three periods of the study, in three periods of 1992, 2002, and 2014, which were obtained in the Arc GIS environment. After extraction of urban and non-urban when the study area and the percentage of urban and non-urban area was calculated in Excel. In order to better understand the relations between runoff rainfall in the study area, rainfall, runoff height was calculated and presented according to the curve number. The results of the study of the impact of urban development on runoff variations are presented at the time of study. By changing the type of use, including the change in area in each polyglone, the calculated CN values will vary in the polyhedron, which results in changes in the runoff height in each polyhedron. By changing the type of use, including the change in area in each polyglone, the calculated CN values will vary in the polyhedron, which results in changes in the runoff height in each polyhedron. According to the results, between 1995 and 2014, urban land increased by 4.95% (equivalent to 57.7 km2), and in the period from 2002 to 2014, urban land increased by 42.3% (equivalent to 127 / 40 sq. Km), and in this period the construction rate has been higher than the previous period. However, urban runoff runoff from 2002 to 2014 increased by 11.29% over the period from 1992 to 2002. Urban development is not the only one in metropolises. It is also important in a small city such as Assadabad. Because it will affect the relations of runoff precipitation. If the runoff height, which is a small number in the city, would be 350 m 3, this volume of runoff in a small town is significant and sometimes dangerous. 4- Discussion and conclusion In the present study, we tried to investigate the impact of urban development on runoff using remote sensing and its integration with GIS. Finally, it was found that using remote sensing; we can consider the variation of runoff from urban development with an accurate precision. It was also determined that urban development in addition to rainfall has been effective on runoff due to the increasing urban use that is related to construction development, industrial development and road construction development. In general, the use of remote sensing because of the cost reduction of field operations, and especially because of the reduction in the time needed to analyze the issues, can be considered as possible solutions to improve the level of water resources management. In addition, using this tool, this opportunity is created for researchers and executives to evaluate different management scenarios (which cannot be executed in a short time without heavy cost), and by analyzing the results, the best Made a decision. It is suggested to use different methods of runoff estimation and compare their results with the results obtained in this study as well as a hydrological model to study the runoff rainfall relationships and compare its results with the results of this study.In order to better study land use changes (especially urban development studies), in different years, it is necessary to use a satellite data format that is also available on a given date. To study more precisely, the relationships between rainfall runoff and time intervals increase. And the last suggestion is to use long-term returns to better predict and understand the impact of urban development on runoff variations.
پژوهشی
Masoumeh Rajabi; Shahram Roostaei; Bahareh Akbari
Volume 6, Issue 20 , December 2019, Pages 21-40
Abstract
1- IntroductionRiver morphology is the science of knowing the river system regarding general shape and form, dimensions and hydraulic geometry, direction and longitudinal profile of the bed, and the process and quality of its changes. The river plan is divided into three classes of direct, braided (multi-branch) ...
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1- IntroductionRiver morphology is the science of knowing the river system regarding general shape and form, dimensions and hydraulic geometry, direction and longitudinal profile of the bed, and the process and quality of its changes. The river plan is divided into three classes of direct, braided (multi-branch) and meandering river in terms of the morphological structure of the river, among which the meandering pattern has attracted the most attention due to its abundance in nature. In order to describe the pattern of the meandering streams, a number of geometric parameters related to the river plan have been defined. By analyzing the frequency and magnitude of these characteristics along the river and at different times, the river changes in the temporal and spatial dimension can be examined. These parameters Such as the length of the pontoon, the width of the pontoon, the width of the river and the length of the river. The purpose of this study is to examine the characteristics and patterns of the Aji Chai River. These parameters are such as the length of meander, the width of meander, river width, and the length of the river. The purpose of this study is to examine the characteristics and pattern of the Aji Chai Rivers’ meanders. 2- MethodologyThe study area was part of Aji-Chay River (Bakhshayesh to Khajeh) with an approximate length of 50 km, located in the northeast of Tabriz. The following materials are used in this study:1) Topographic map of 1:50000 and 1:250000 scales were used to examine the morphology of the study area,2)Geological maps of 1:250000 and 1:100000 scales for the analysis of geological and tectonic characteristics of the study area and 3)Using Landsat-8 and Google Earth satellite images and the ArcGIS, Excel, Autocad softwares.The study area was divided into three reaches. Some circles fitted to the meanders in the AutoCAD environment and the geometric characteristics such as wavelength, arc length, and radius of curvature of the circle, which is tangent to the river path, were measured to calculate the curvature coefficient (S = c / v) and the central angle (c/Rπ = ϴ 180). Then specification of each of the circles of the same samples was obtained and then in the EXCEL software, a plot of the samples was drawn. 3- ResultsDue to the long-range of the study area, the intended path was divided into three reaches. In terms of the central angle index in the first reach, the most frequent central angle was 62.5%, which is related to developed meander pattern. In the second reach, the highest frequency of central angle with 56% was related to the developed meandered pattern. In the third reach also the most frequent central angle was related to the developed meander pattern with a frequency of 57.5%. By comparing the three studied reaches in terms of the central angle index in general, it is concluded that all three reaches have a meandering pattern, in particular, a developed one, so that the average of all three reaches (the first reach 110.2, the second 118.2, and the third 123.1, respectively) are in the developed meandering pattern category (85-158). In each of three reaches, the most frequent central angle belongs to the developed meandering pattern.The average curvature coefficient of the reaches, calculated by dividing the sum of frequencies in each reach by the total number of samples of each reach, is as follows: in the first reach, the average curvature coefficient was 1.18 which is in the range of 1-06 – 1.25 showing a sinusoidal pattern. In the second reach, the average curvature coefficient is 1.30, which is in 1.25-2 range, also has a meandering pattern. In the third reach, the average is 1.26, which is the same as the second average in the range 1.25-2 and the pattern is meandering. In general, the pattern of flow in the first reach was sinusoidal and with the increase of arches in the second reach, it changed to the meandering pattern. In the third reach, although, there was a minor reduction trend was, it retained the meandering pattern. 4- Discussion and conclusionBased on the results from the morphometric indices, including the central angle and curvature coefficient in the studied area, the total mean of the central angle in the three reaches is 126.1 degrees, which is in the range of 85-158, showing the developed meandering pattern in the river morphology.The mean curvature coefficient in the three studied reaches is 1.25, which is in range 1.25-2, takes the meandering pattern in terms of curvature coefficient, so the studied river has a meandering to developed meandering patterns.The findings of the study indicate that the study area has a nearly uniform and smooth slope, and considering the fact that the existence of a gradient is a significant factor affecting the development of the developed arcs and meander formation, as a result, in determining the river pattern and morphology of the study area, the topography factor had the first priority.Due to the fact that erodible formations cover most of the area, the factor of lateral erosion in low-slope areas has been effective in the warping of the river path due to the presence of loose and erodible sediments.
پژوهشی
Abdorreza Vaezihir; Nasser Jabraili andaryan; Shoaib Bakhtiyari
Volume 6, Issue 20 , December 2019, Pages 41-56
Abstract
1- IntroductionThe rocks that can be karstified are divided into two categories of carbonate rocks (limestone and dolomite) and evaporates (salt and gypsum). One of the karstic landforms are caves. Hydrogeologically, caves are dissolved cavities with diameter larger than 5 to 15 mm. This is the threshold ...
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1- IntroductionThe rocks that can be karstified are divided into two categories of carbonate rocks (limestone and dolomite) and evaporates (salt and gypsum). One of the karstic landforms are caves. Hydrogeologically, caves are dissolved cavities with diameter larger than 5 to 15 mm. This is the threshold of turbulent flow. One of the important characteristics of the caves is the cross-sectional pattern and this parameter is a controlling factor of the cave development mechanism. Caves are developed in general due to tectonic factors are structure control with irregular cross section. These types of caves are developed along faults, joints and bedding. On the other hand, caves which are caused by hydraulic phenomena (hydraulic control), have a circular or ellipsoidal cross-section. However, the first factor in the creation of such caves may also be tectonic structures, but the most important factor for their development was the flow of water (Karimi, 2010).The karstic flow model was divided into two types of diffuse and conduit types according to velocity and governor flow equations. In diffuse flow systems, the water moves linearly through the connected fractures less than a centimeter. In this type of flow, the output of the springs is numerous and with low discharge. While in conduit system, water moves through the joints and channels larger than one centimeter and is usually exposed as a large discharge spring. Due to the high distribution of carbonate rocks in Kurdistan province and extensive exploitation of karst springs, recognizing these resources and identification of the role of karstification in supplying the water resources of the province is a necessity. Karstic water sources are strategic water supply sources specially in crisis of drought period. In this research, after determining the karst areas of the province, caves and karstic springs as two important indicators of karst development were studied to evaluate the characteristics of caves and springs of the province in terms of development model and flow system. 2- MethodologyIn order to investigate the development of karst and formation of caves and karstic springs, at the first, comprehensive knowledge of the region's petrology is necessary. The formation and structural conditions of the region should also be identified in order to recognize areas with high potential of karstification. Understanding the types of karstic units also helps to identify the level of karstification in different parts of the areas. Using plan of the caves, it is possible to compare the passage strike of the caves with fault's rose diagram. Study of spring density and the discharge rate of karstic springs in different parts of the area can be done to find out whether the karst development system is conduit or diffuse type. Also, to study the relation between the water quality of the springs with the geological formations, hydraulic conductivity (EC) was focused on. The lower electrical conductivity (EC) values are belonged to springs originated from hard rock and karstic units of the area. One of the ways that can be used to evaluate the permeability of hard and carbonate formations is Special Discharge assessment for each formation.4-Discussion and conclusionAbout 29% of the province area is formed of karstic units including impure and pure lime, lime with volcanic layers, and dolomite with the most coverage percent. The results of this study showed that all caves of the area are located on the karstic units of the province and their dominant strikes are concordant with dominant strike of the faults. By comparing Rose diagrams of fault lines around several caves with that’s of cave passage the effect of water or structure on controlling the development pattern of these caves was determined. The total discharge of the springs is 13.7 m3/s which 9.5 m3/s (about 70%) of that belongs karstic springs. Most springs with discharge above 5 L/S originated from karstic formations are located especially in limestone, impure limestone and limestone with volcanic layers. Average discharge of total karstic springs are 0.4 liters per second, showing poor development of karst or development of diffuse model of flow system. However, karst development system seems to be conduit dominated in the southern parts of the province and diffuse dominated at the other areas. The minimum electrical conductivity (EC) of the study area belongs to springs that discharge fractured and karstic units.The results of this study showed that all caves of the area are located on the karstic units and their dominant length is consistent with the dominant length of the faults. By comparing the Rose diagrams of fault lines around several caves with the cave passage strike revealed that structure and tectonics have the main control on development, pattern and profile of the caves. About 69.5 % of the total discharge of the springs of study area are originated from the karstic units. Karstic springs provide 79.32% of the water use in agriculture and 4% of urban and rural drinking water in Kurdistan province. The karst development system seems to be conduit dominated in the southern parts of the province and diffuse dominated at the other parts. The minimum electrical conductivity (EC) is belongs to springs which discharge fractured rock and karstic units. The most specific discharge rates are related to carbonate rocks and lowest discharge rates are related to crystalline rocks of the province.
پژوهشی
Mohammadreza Goodarzi; Atiyeh Fatehifar
Volume 6, Issue 20 , December 2019, Pages 57-78
Abstract
1-Introduction The assessment report fifth of the Intergovernmental Panel on Climate Change shows that global warming has led to a change in the water cycle due to increased greenhouse gas emissions. In the present time, with the increase of industrial activities and the neglected environmental issues, ...
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1-Introduction The assessment report fifth of the Intergovernmental Panel on Climate Change shows that global warming has led to a change in the water cycle due to increased greenhouse gas emissions. In the present time, with the increase of industrial activities and the neglected environmental issues, the effects of climate change have become more evident and poses this phenomenon as a global difficult. Increasing the probability of occurrence of extreme climatic events such as flood and increasing the frequency and intensity of the effects of climate change. Due to changes in climate and global warming, the probability of heavy rainfall and consequently the risk of flood due to incorrect drainage system and physical and environmental factors have increased. Therefore, the study of the region's climate is important given the new scenarios and flood frequency analysis with suitable statistical distributions for future planning. 2- Methodology In the present study, the effects of climate changes on the runoff of Azarshahrchay Basin with CanESM2 model under RCP2.6, RCP4.5 and RCP8.5 release scenarios assessment report fifth (AR5) of the Intergovernmental Panel on Climate Change (IPCC), with Statistical down scaling model (SDSM), for the period 1976-2005 and 2059-2030 by the hydrologic model SWAT have been investigated. The accuracy of the simulation was evaluated with three indicators: Root Mean Square Error (RMSE), Coefficient of Determination (R2) and Nash–Sutcliffe Efficiency (NSE). An analysis of the frequency of maximum annual flood for both base and future periods using their probability distribution function (PDF) and the Easyfit model. In this model, 5 types of probability distribution including Normal, Normal Log, Pearson, Log Pearson Type 3 and Weibull were used. The best distribution for each basic and future time series were ranked and selected by using three Chi-square, Kolmogorov–Smirnov, Anderson–Darling tests. In order to study how the maximum flood discharge regime changes in the base and future periods were used two indices: 1) The probability and the return period in the equal flows 2) Intensity of flow in the equal return periods 3- Results The obtained factors of the three RMSE, R2, and NSE indicators showed the good performance of the SDSM model in the down scaling the large-scale data. Investigating the performance of the SDSM model in the downscale of the Azarshahr station's climate data with a Coefficient of Determination and Nash–Sutcliffe of 0.99 and 0.98 for temperature for the period 1990-2001 and 0.86 and 0.83 for precipitation in the period 1976-2005. The simulation results showed a rise in temperature during the period 2030-2059 under scenarios and the highest increase was related to RCP8.5 (0.23°c). Also, rainfall at a station increased by 7.44 percent to RCP2.6 and at another station decrease by 7.57 percent to RCP8.5. The performance analysis of the SWAT model indicates a good accuracy of the model in runoff simulation with R2 and Nash 0.6 on average. The results of the 2.1% increase in runoff and the maximum flood peak and the probability of flood events in March and April (late winter and early spring) have been shown by the SWAT model. Results of the study of the regime of maximum annual flows (frequency and intensity) by fitting probabilistic distributions with the lowest error rate for the base distribution period of the Weibull, future period RCP2.6 distribution Log Pearson Type 3, RCP4.5 Log Normal and RCP8.5 Log Normal as best distribution are selected. Also, the frequency and intensity of flood have increased. In the return periods of constant, the maximum discharge increased, and in maximum discharge constant, with increasing return period (1000 years), the discharge rate significantly increased. So, in the 500-year return period is expected a 98% increase in maximum discharge RCP8.5 future period than base period. The most critical scenario is RCP8.5 scenario. 4- Discussion and conclusion The results indicate the impact of climate change on the basin in the future period. Therefore, knowing the increase in precipitation intensity, the flood risk increases. The occurrence of terrible floods due to climate change have caused many damages in different parts of the world in recent decades. The results of this study, like other previous studies, confirm that climate change is significant, especially with the increasing frequency of floods, governments, organizations, and educational centers need to take appropriate measures to eliminate or reduce the effects of climate change and adaptation to extreme events such as floods.
پژوهشی
Hafez Mirzapour; Ali Haghizadeh; Naser Tahmasebipour; Hossein Zeinivand
Volume 6, Issue 20 , December 2019, Pages 79-99
Abstract
1- IntroductionAccurate detection of changes land use in Accurate and timely, Basis for a better understanding of the relationships and interactions of human and natural phenomena to manage and provides better use of resources. Principal land use management requires accurate and timely information in ...
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1- IntroductionAccurate detection of changes land use in Accurate and timely, Basis for a better understanding of the relationships and interactions of human and natural phenomena to manage and provides better use of resources. Principal land use management requires accurate and timely information in the form of a map. Regarding the widespread and unsustainable changes in land use, including the destruction of natural resources in recent years, Investigating how landslide changes during time periods are essential for satellite imagery. Since conservation of natural resources requires monitoring and continuous monitoring of an area, Land-use change models are now used to identify and predict land-change trends and land degradation one of the most widely used models in predicting land use change is the Auto-Markov cell model. the aim of present study is to monitor land use changes in the past years and predict changes in the coming years in Badavar-Nurabad watershed in the Lorestan province with an area of 71600 hectares. 2- MethodologyThe Markov chain method analyzes a pair of land cover images and outputs a transition probability matrix, a transition area matrix, and a set of conditional probability images. The transition probability matrix shows the probability that one land-use class will change to the others . The transition area matrix tells the number of pixels that are expected to change from one class to the others over the specified period (Ahadnejad 2010). Automatic cells are models in which adjacent and continuous cells, such as cells that may include a quadrilateral network, change their state or attributes through simple application of simple rules. CA models can be based on cells that are defined in several dimensions. The rules for changing the state of a cell from one mode to another can be either a combination of growth or decrease, such as a change to a developed cell or without development. This change is the source of the change that occurs in the adjacent cell. Neighborhood usually occurs in adjacent cells or in cells that are close together(Ghorbani et al, 2013). In order to detect land use changes in the studied area, TM , ETM+ and OLI satellite images of Landsat were used during three time periods of 1991, 2004 and 2016. After applying geometric and atmospheric corrections to images, the land use map for each year was prepared using the maximum probability method. The Kappa coefficient for the classified images of 1991, 2004 and 2016was 0.81, 0.85 And 0.90 obtained. Then, to model land use changes using the Auto-Markov cell model for 2028 horizons, First, in the Idrisi Selva software using Markov chain, the map was selected as input from the years 1991 and 2004, the 12-year prediction of the changes was considered by 2016 to determine the likelihood of a change in application. Then, using the CA-Markov method, the data from the Markov chain and the map of 2016 were used as input data for the automated-Markov cell method. 3- ResultsAssessment of the match between simulated and actual map of 2016 with 0.97 kappa index showed that this model is an appropriate model for simulating of land use change. The results from monitoring satellite imagery that in 1991 to 2016, the extent of residential areas, land is Dry farming, garden and irrigated farming land added in front of vast pastures, shrubbery and other is reduced. After verifying the model's accuracy, a 2028 map was prepared to predict the changes over the coming years. Well as the results show that the vast pastures of the forecast is reduced in the amount of 659.89hectares and 395.47 hectares will be added to the extent of irrigated farming. 4- Discussion and conclusionThe results of the Auto-Markov cell model showed that if the current trend continues, the size of the ranges will decrease sharply. Comparison of simulated map of 2016 by model and actual map with Kappa index showed that Auto-Markov cell model is a suitable model for predicting land use change and can accurately assess the future status of land use and vegetation to predict. Therefore, it is suggested protective measures and make appropriate management decisions to control non-normative changes continue to apply more than ever.
پژوهشی
masoud jalali; Mohamad Kamangar; Robab Razmi
Volume 6, Issue 20 , December 2019, Pages 101-119
Abstract
1- IntroductionIn recent years, groundwater level has been descending due to climate change as well as method and use of them, especially in arid and semi - arid regions. According to the United Nations studies, Iran is considered one of the countries facing a shortage of water. In terms of climatic ...
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1- IntroductionIn recent years, groundwater level has been descending due to climate change as well as method and use of them, especially in arid and semi - arid regions. According to the United Nations studies, Iran is considered one of the countries facing a shortage of water. In terms of climatic conditions, much of the country is but arid and semiarid regions. Water Table level control using observation wells are the main source of information to investigate the hydrological changes in these areas. Due to the recent drought and water shortages on a wide area of the country, the importance and sensitivity of groundwater management is increasing. Predicting the Water Table level using mathematical and statistical models can contribute significantly to proper planning and decisions to provide long - term water supply. In this study, the level of underground water using the gradient network and the transfer function of Tangent has been tried. Because of recent decades, neural network model studies show the high capability of this model in exploring the relationship between data and the recognition of patterns. Coppola and al (2003) investigated the possibility of predicting the level of 12 observation wells in different climatic situations, using artificial neural networks, in an area near the Temba Bay of Florida. Their results showed that, in modeling of the waters of the limestone and karstic areas, neural networks performed appropriate performance. diacplous et al. (2005)conducted an investigation to predict 18 months of groundwater level to predict an underground water level in the Mesrar Valley in Crete, Greece. The results indicate that the lonenberg algorithm is the most appropriate model.2- MethodologyThe recent multi - year drought in the province of hormozgan has resulted in the aggravation of drought conditions and the imposition of many problems on water resources in particular in the underground reservoirs in particular. Sarkhoon Plain plain is one of the areas close to the provincial capital of hormozgan. In this paper, prediction of the spatial model of the Water Table plain of Sarkhoon Plain plain using artificial neural network method and Hyperbolic rule is used to investigate the fault level of this model. in this study, the data of ten observation wells during the 25 - year period of 1990 - 1387 to 1392 - 1392 of the regional water organization of hormozgan province have been used. Artificial neural networks are one of the computational methods that utilize the learning process using called Nero, by adjusting the weights, using the input - output samples that are available. This model is subsequently used to estimate the output value for the new data. The weight of the hidden layer and the output layer are changed so that the error rate is min. This error is represented as follows.(1) E = 1 / 2 [(y - O) ^ 2]The following algorithm is illustrated in order to train the neural network.η > 0 and E > 0After implementation of neural network algorithms with different neurons in matlab software, the results of predicting the water height of Sarkhoon Plain with Hyperbolic transformation functions were obtained. to determine the best spatial model of different levels of groundwater depth, the soil water models were used. in order to choose the best extrapolation method in this study, eight methods were used and finally the model that had the lowest fault was considered as optimal model.3- ResultsIn this study, neural network model was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network model was selected as the top model with 40 neurons in the latent layer and with its extension to observation wells a spatial prediction model was obtained from groundwater level. The very low error and the high correlation of this model, from the results of the test data, shows its efficiency in predicting the level of groundwater level. Using this algorithm for data of ten wells, water height was predicted for twelve months of 1400 year. The results of this research have proved the superiority of neural networks to numerical models, This spatial model can be used to control the rate of water harvesting in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evapotranspiration in predicting groundwater levels.4- Discussion and conclusionIn this study, neural network model was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network model was selected as the top model with 40 neurons in the latent layer and with its extension to observation wells, a spatial prediction model was obtained from groundwater level. The results of diacplous et al. (2005) showed the superiority of lonenberg neural network over other models that have sufficient layers of latent layers, while it seems that the use of multiple latent layers with multiple neurons in different models leads to error reduction and the choice of superior model selection. Toarimino, Chua and Sethi (2012) emphasize the short - term forecasts of groundwater fluctuations. They have used the parameters of precipitation, evaporation - evapotranspiration and water level in the neural network model. Despite the higher parameters, the absolute mean of their superior model error has been higher than the average model error of the present research. It is probably due to the low intensity of the hidden layer neurons as well as their short time ranges. The results of the study indicate that the use of a neural network algorithm with the number of static neurons cannot be a measure of the performance evaluation of a model. This spatial model can be used to control the rate of water Picked up in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evatranspiration in predicting groundwater levels.
پژوهشی
Asad'ollah Hejazi Hejazi; Zahra Zanganeh Tabar; Zahra Zamani
Volume 6, Issue 20 , December 2019, Pages 121-140
Abstract
1-IntroductionMaterials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around ...
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1-IntroductionMaterials movement on slope and especially landslides are among the most damaging threats that have been accelerating with human manipulation in natural systems in recent decades (Imami and Ghayumian, 2003). These movements annually cause a lot of financial and psychological damage around the world in different parts of the country. The rapid population growth, the expansion of cities in mountainous areas, the difficulty of predicting the occurrence of landslide events and the multiple factors affecting this phenomenon reveal the necessity of zoning the risk of landslide. Since prediction of the precise time of mass movements is very difficult, identification of these areas is very important (Mosafaei et al., 2009). Using the zoning of the risk of a landslide event, it is possible to identify vulnerable areas with potential risk, and by providing appropriate management approaches and techniques, to some extent prevent the occurrence of landslides or damage caused by them reduced. Accordingly, the purpose of this study is to identify areas susceptible to landslide in the Sarpolzahab Basin. The Sarpolzahab Basin is one of the mountainous regions of the western part of the country which is prone to various types of slopes due to special geomorphological conditions. In this research, for the potential estimation of areas susceptible to landslide, two models of WLC and OWA for zoning and an analysis of the network (AHP) model for weighting into layers have been used.2-MethodologyThe research methodology is based on software, library and analytical methods. In this research, eight layers of information were used to identify landslide susceptibility. Information layers include: 1 elevation, 2 slopes, 3 slopes, 4 rivers, 5 faults, 6 lithology, 7 communication paths and 8 land use areas. The general trend of the present research is that in order to identify the susceptible landslides, information layers were first provided (the choice of information layers was based on the purpose of the research and according to the experts' opinion), and then these layers were based on the opinion of the experts (5 geomorphologist) and using the network analysis model (AHP). After weighing the information layers, the weight is applied to each of the layers, and then, in order to combine and combine the information layers, three methods of fuzzy logic, WLC and OWA have been used.3- ResultsIn this research, in order to achieve the desired goals, information layers are first provided. After providing information layers to combine information layers, layers are standardized using fuzzy area. Layer standardization is based on expert opinion and research objectives. For layers of elevation and gradient, gradient and high-lying areas of value near 1 and low-gradient and low-lying areas are considered to be close to zero. For layers of slope directions, the northern directions are worth close to 1 and the southern directions are close to zero. Also, areas near the lines of the fault, the river and the communication path are worth close to 1 and the distant areas are close to zero. For the land use, the uncovered areas are close to 1, and areas with dense vegetation are close to zero. For the lithology layer, areas with low resistance to lithology such as marl, lime and alluvium have a value of close to 1, and areas with more resilient lithology (basalt areas) are close to zero. 4- Discussion and conclusionThe results of this study indicate that the studied basin has high potential for slippery slopes movement. In fact, the existence of hurdles and the availability of other parameters have led to a relatively large and large part of the eastern basin. Comparison of potentiometric methods suggests that in all three methods, the eastern regions have the highest and western regions with the least potential for landslide occurrence. In the fuzzy logic method, the potential class has the highest potential of 195 km2, and the average potential class with the 121 km2 has the smallest extent, which mainly includes the western regions and the outlet of the basin. In the OWA method, the relatively large potential floor area has a maximum area of 210 square kilometers, which mainly includes the central and eastern heights of the basin. In this method, the high potentiality class with the area of 116 km has the lowest status, and mostly you are the northern and central areas of the basin. In the WLC method, the relatively high potential class with 180 and a high potential floor area of 120 km2 has the highest and the smallest extent.
پژوهشی
Foruzan Ahmadi; Kazem Nosrati; Mohamad Mehdi Hoseinzadeh
Volume 6, Issue 20 , December 2019, Pages 141-164
Abstract
1-IntroductionAccelerated soil erosion is a serious problem in Iran, leading to degradation of soil and water resources, reduction of soil fertility, destruction of range and agricultural lands, desertification, recurring floods, sedimentation of reservoirs, and pollution of fishery habitats. Hence, ...
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1-IntroductionAccelerated soil erosion is a serious problem in Iran, leading to degradation of soil and water resources, reduction of soil fertility, destruction of range and agricultural lands, desertification, recurring floods, sedimentation of reservoirs, and pollution of fishery habitats. Hence, understanding of the potential soil erosion process and opposition to this erosion are necessary environmental. To this end, uptake and refinement of sediment source tracing or fingerprinting techniques has expanded dramatically as an alternative approach to traditional methods of identifying key sediment sources. Sediment source fingerprinting involves discriminating potential sediment sources on the basis of differences in source material properties or tracers and determining the relative contributions of these sources to sampled target sediment. different kinds of sediment sources have been used so far in sediment fingerprinting techniques (e. g., land use, geology, sub-basins, surface and subsurface erosion) but, there is a little attention paid to the selecting the soil erodibility groups as sediment sources. Therefore, the main objective of this study are the Kouhdasht watershed dividing into different erodible units based on soil erodibility index and determination of the contribution of each unit in sediment yield using an un-mixing Bayesian uncertainty model and to find its relationship with soil organic carbon stock. 2- MethodologyKouhdasht basin with 1138 km2 area located in 33° 17´ to 33° 41´ north latitude and 47° 20´ to 47° 50´ eastern longitude in western of Lorestan province. samples were collected in two stages; first, 81 samples in order to estimate erodibility, second, in order to determine the contribution of each source to sediment yield, 70 soil samples were collected form sources and 12 sediment samples collected at the basin outlet. The soil erodibility was calculated based on the soil texture and based on the geometric mean of the soil particle diameter. Based on the amount of soil erodibility, the area was divided into three different erosion units as sediment sources. To determine the contribution of sediment sources to sediment yield used fingerprinting technique is based on estimation of uncertainty.3- ResultsThe erodibility of the study area varied from 0.0386 to 0.0663. Erodible units were identified as sediment sources based on the values obtained from the erosion parameter and according to the results of selecting the optimal combination of tracers. The results showed that the first erosion unit 2%, the second erodible unit 5%, and the third erosion unit 93% contributed in the region's sediment yield. The relative importance of erodible units in sediment yield was obtained by dividing the share of each resource in the production of sediment into the percentage covered by each source. The relative importance of the first, second and third erosion units is 0.08, 0.28, and 1.57, respectively. Regarding the role of organic carbon in erosion, the amount of organic carbon storage in different erosion units of the area was also measured. The amount of organic carbon storage in each erosion unit is first, second and third ones were 70.5, 64.3 and 54.6 mg / ha respectively. 4- Discussion and conclusionThe third unit with 93% has the largest contribution in sediment yield and with 54.6 mg / ha, it has the lowest amount of organic carbon storage in the area. Considering that this unit is most used in agriculture and geologically under quaternary sediments, showed that the parts that are under cultivation and quaternary sediments have both high erodibility and the highest contribution to sediment yield. Measurements of organic carbon storage also showed, there is the least amount of organic carbon storage in this unit and this suggests that in the third unit, the damage caused by the loss of fine sediments such as clay is higher. Given that the third unit is under agricultural use this can be attributed to the type of land use and exploitation. Therefore recommended more attention to the type of use of land and soil management and conservation programs implemented in the region.
پژوهشی
Robabeh Farzinkia; Mohmmadali Zanganehasadi; Abolghasem Amirahmadi; Rahman Zandi
Volume 6, Issue 20 , December 2019, Pages 165-185
Abstract
1- IntroductionToday, the phenomenon of land subsidence is one of the most important geomorphologic hazards on a global scale, causing a great deal of damage to urban and rural construction. According to the UNESCO definition, "subsidence is the collapse or land leveling that occurs due to different ...
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1- IntroductionToday, the phenomenon of land subsidence is one of the most important geomorphologic hazards on a global scale, causing a great deal of damage to urban and rural construction. According to the UNESCO definition, "subsidence is the collapse or land leveling that occurs due to different large and small scale causes" (Amir Ahmadi et al., 2013: 2). Pourkhosravani et al, (2012) Only with radar interferometer technique studied the geometry of duality, The results of this study showed that, firstly, citing excessive productivity of underground waters is not the main reason for the subsidence phenomenon; secondly, the phenomenon of subsidence in Iran's plains is the result of a duality in the crustal motions between the plains and adjacent mountains. In this research, the tectonic indexes and radar interferometry technique have been used with regard to the data and information available to detect the tectonic activity of the area.2-MethodologyIn order to investigate the state of activity of the newly tectonic area, topographic maps of 1: 50000 and 1: 10000 map of geology and radar images are used in the earthquake discussion from USGS US from 1923 to 2018. Also, to study the subsidence of the Joveyn area, the satellite Sentinel-1A satellite radar data for 2017 and 2018 was used in Canada and processed by SNAP software. The resources used in this research were based on library studies and surveys, topographic maps and radar images and field surveys.3-Discussion and results and findingsThe results of the used Indicators, earthquake zoning and radar interference are defined in the research as follows:River Gradient Index) SL): This index was first presented by Hack (1973), in the study of the role of rock resistance on water flow in the Appalachian Mountains in the southeast of America as numerical values of the river gradient index Table1).Table(1): River Gradient Index)SL)HighΔH(m)ΔL(m)Lsc(m)SlCondition1200-13001001476932050217low1100-12001001581467170424medium1000-110010029798122931412medium-Asymmetric index(AF):In this calculation, the obtained numbers (33.7) of the basin showed that the value of the index is less than 50. Therefore, we have the tectonic activity on the left side of the main stream and we face the subsidence phenomenon on the right.-Reverse topographic symmetry index: (T)to calculate this index in the Joveyn basin, a section has been created in each sub-area and its value has been calculated. According to (table 2), the index value in all three sub-basins is less than 1, indicating the asymmetry and active tectonics in the whole basin. Table (2): Reverse topographic symmetry indexRouteDa(km)Dd(km)TCondition118/4321/330/86active215/3816/910/9active314/5316/780/86active-Hypsometric and Hypsometric Integral CurvesIn the hypsometry integral, the numerical value has a value of 0.5 in the range of young to adult topography.Mountain Sinocity Index: (Smf)Table (3): Mountain Sinocity Index shapeLMFLSSCondition126/9412/342/18Semi active241/8611/853/5Semi active333/0518/721/76active446/0223/041/99active-Sinocity index of the river: (S)According to the calculations, the index of the main bend and bend of the main river is less than 1. Which represents the new activities in the region.-Valley Depth Wide Index (VF):In passive regions, the average value of this indicator is usually higher than 7 in terms of over-rupture (Ranjbar Manesh, 2013).Table(4): Valley Depth Wide IndexConditionVfVfwEldErdEscnumberactive1.3629205721101604Figure 1active0.8127140814981307Figure 2active0.873135414241301Figure 3active1.6220153416841475Figure 4active2148150514811421Figure 5active1.2127154515271437Figure 6active0/287232421151877Figure 7-Radar interferometric resultsAccording to this map, the maximum subsidence rate in the study area in 2017 and 2018 will be 6.4 and 5.6 respectively. Regarding the maps drawn on this plain with radar interferometry, both indicate the subsidence of the plain. The analysis of plain radar data shows that the highest elevation in the joghatay heights, and the highest subsidence level, occurred on the joveyn Plain floor.4-ConclusionAlthough most scholars consider untreated groundwater to be an important factor in groundwater depletion and the plains of Iran, the role of tectonic factors in exacerbating this phenomenon should not be overlooked. In a study conducted by Purkhosrovani et al. On the causes of the subsidence, only Duval's discussion of radar interferometry was discussed without examining tectonic indices. In this study, in addition to radar interferometry, the tectonic status of the basin was also investigated. For this purpose, geomorphic indices such as watershed shape, drainage basin asymmetry index, inverse topographic symmetry index, mountain front sinusoidal index, hipsometry integral, valley floor height to its height, river sine index, river gradient index, gradient index They offer some of the activities of the area's baby boomers. Among the morphotectonic indices that all indicate tectonic activity in the region, the VF index in the region was less than 2, which by standards is below 6 in this index indicating rising areas. Subsidence caused by tectonic movements occurs when there are two faults, graben and upwelling, and relative movement of parts causes subsidence. The fault status of the area in the southern and northern parts of the region has placed the plain in the graben position. Statistical analysis also showed that the earthquake of 1923 occurred with a magnitude of 6.4 MS. The future activity of these faults may affect the area. The active morphotectonic conditions of the basin, also showed the results of radar interferometry, in the southern part with higher elevation, parallel to subsidence in the plain. The existence of this scouring and its appearance on the radar interferometer map indicates the tectonic activity in the southern rangesof the study area. These results indicate a significant relationship between the subsidence and its lateral elevations, suggesting that these two movements are dual. Based on the above arguments, it can be concluded that one of the factors affecting the subsidence of the Earth in the juvenile plain is due to its soft crustal motions even in equilibrium. Due to the geomorphic hazards of the basin, it is necessary to prepare a zoning map of the area for development activities and land preparation based on which control, protection, prevention or warning measures will be taken.
پژوهشی
Mohammad Hossein Rezaei Moghaddam; Mir Asadolah Hejazi; Abdollah Behbuodi
Volume 6, Issue 20 , December 2019, Pages 187-204
Abstract
1- IntrodutionWatersheds are open systems which, due to its complexity and in order to achieve the desired goals, are modeled. Through modeling, the cost of study for complex systems is reduced because large-scale field trials are very costly or impossible. Also, by analyzing the results of the model, ...
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1- IntrodutionWatersheds are open systems which, due to its complexity and in order to achieve the desired goals, are modeled. Through modeling, the cost of study for complex systems is reduced because large-scale field trials are very costly or impossible. Also, by analyzing the results of the model, we can manage the watersheds well. In this research, the performance of the IHACRES rainfall-runoff model was evaluated in the simulation of runoff in the Lanbarn basin. The monthly data on rainfall and temperature of Varzaghan station as input variables for flow simulation and observation data of runoff at Cassin hydrometric station were used to measure the accuracy of the IHACRES model. Based on available years, data from 2002-2000 were used for warming up the model and data from 2012- 2012 were used for calibration and data from 2016-2013 were used for validation purposes. To evaluate the ability of the IHACRES model in runoff simulation, the Nash-Sutcliff coefficient was used. The results showed that the coefficient was 0.71 and 0.74 for calibration and verification, respectively. Therefore, according to the results of the evaluation of the IHACRES model using different performance criteria and because of easy access, less inputs and a reduction in the time spent, it can be advised to use the model to simulate and predict runoff in a monthly scale in the Lanbarn watershed and to use it in order to study surface runoff and river flow in future periods.1- IntroductionIn order to manage watersheds and prevent inconsistencies in measures taken at the catchment area, a model is needed which, according to the existing information and conditions, has the efficiency of simulating the outflow of the region (Yong et al., 2014:47). Integrated models require less information than distributed and semi-distributed models, and, on the other hand, they run faster than other models (Golshan et al., 2017:966). The IHACRES model is an integrated concept model that includes a nonlinear reduction model and a linear lattice model. Despite the relatively recent development of IHACRES, this model has been widely accepted among hydrological models (Sriwongsitanon & Taesombat, 2011). The number of parameters in this model is low, while simultaneously compared with distributed models, we have tried to provide more details of the internal processes (Croke & Jakeman, 2008, Golshan, et al., 2017:966).2- MethodologyTo do this research, the monthly data on rainfall and temperature of Varzaghan station as input variables for flow simulation and observation data of runoff at Cassin hydrometric station were used to measure the accuracy of the IHACRES model. Based on available years, data from 2002-2000 were used for warming up the model and data from 2012- 2012 were used for calibration and data from 2016-2013 were used for validation purposes. The IHACRES model is an integrated metric conceptual model for rainfall-run simulation. This model was developed by Jackman in 1990. The model needs 5 to 7 variables for calibration and is suitable for implementation in large scale basins. In this study, version 2 of this software has been used, which is applicable for basins with continuous data of rainfall, temperature and runoff. This model consists of two nonlinear and linear interconnected segments that are respectively defined for calculation of losses and effective rainfall conversion to runoff.3- Results Based on the results, Nash-Sutcliff coefficient was 0.71 and 0.74 for calibration and verification, respectively. Therefore, it can be stated that the model of low discharge simulates well, but in simulating the maximum discharge, it has little ability and simulates lesser amounts of observational flow. In general, due to low model deviations and good simulation of minimum discharge values, it can be argued that the performance of the IHACRES model in the Lanbaran catchment area is satisfactory.4- Discussion and ConclusionGiven the diversity of rainfall-runoff models, selecting an appropriate model for watersheds is important for increasing the efficiency of planning and managing water resources. Hence, in this study, IHACRES model performance was evaluated in runoff simulation in the Lanbaran watershed. According to the results of the calibration and verification of the model in runoff simulation based on different performance criteria, the model was found to have a high accuracy in simulating runoff at the station under study. It also simulates the amount of monthly flow, which is consistent with the results of studies of Zarei et al. in the basin of Kasaliyan, Lotfirad et al. in the Nawarud basin and the studies of Croke and Jakkman. Therefore, according to the results of the evaluation of the IHACRES model using different performance criteria and because of easy access, less inputs and a reduction in the time spent, it can be advised to use the model to simulate and predict runoff in a monthly scale in the Lanbarn watershed and to use it in order to study surface runoff and river flow in future periods.
