Abdolkarim Veysi; ebrahim moghimi; Mehran Maghsoudi; Mojtaba Yamani; Sayed Musa Hosseini
Volume 6, Issue 19 , September 2019, , Pages 101-123
Abstract
Yamani[1], Sayed Musa Hosseini[2] Introduction Shahu karstic aquifers are the main sources of drinking and agricultural water in Paveh, Javanrood and Ravansar cities. Therefore, according to the important role of karst aquifers in supplying water to local communities in Kermanshah Province, recognizing ...
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Yamani[1], Sayed Musa Hosseini[2] Introduction Shahu karstic aquifers are the main sources of drinking and agricultural water in Paveh, Javanrood and Ravansar cities. Therefore, according to the important role of karst aquifers in supplying water to local communities in Kermanshah Province, recognizing their hydrodynamic characteristics for qualitative and quantitative management plays an important role in water policy planning in the province. The aim of this study was to identify and analyze the characteristics of karstic Dolines in the Shahu area and its relationship to the hydrodynamic characteristics of the water resources of the region. The identification of the sinkholes and their dispersion along with the morphometric analysis of these forms in the study area can be used in discussions on morphological characteristics and environmental hazards assessment and provide usable data for environmental planning. Methodology The purpose of this study was to evaluate the hydrogeological characteristics of Kavat and Holi springs in connection with the development of Karst geomorphology, which is based on library, field, and applied research. To this end, CCL, elongation index, sinusoidal index, D/H ratio, the analysis of the nearest neighbor in order to analyze the Dolin characteristics of the region and time series analysis methods were used. In addition, automatic correlation and spectral density were used in order to study the hydrodynamic characteristics of aquifers in the study area. The data on discharge and precipitation of hydrometric stations and rain stations of the Ministry of Energy were also used during the period of 2003-2014. The sinkholes identified in the Karst Shahu area were derived from 10-meter digital elevation model. Extensive field activities were carried out to check identified forms. A descriptive table including location, geology and morphometric characteristics for each doline were calculated. The doline morphometric characteristics were recorded. Then the data were analyzed by statistical methods in SPSS software. In this study, parameters including density, area, diameter, depth, slope and distance from faults were analyzed. The analysis of the hydrograph subsidence curve was used to evaluate the type of flow system in the karstic aquifers of the study. Finally, to evaluate the results obtained from the time series analysis, the results of the hydrograph curve analysis and karst geomorphological features in Shahu area were considered and the hydrodynamic features in the study aquifer was determined. Result According to CCL method, 104 dolins were identified in the shahu area. These dolines covered 11km2. The majority of the dolines were located in the central and northwestern parts of the study area. The mean depth of dolines in Shahu was 15m. The morphometry of the hollows generally tended to be elliptical or stretched. In the Shahu area, elliptical dolines were predominant forms. This indicated the significant role of rock mass in the evolution of the dolines. Semi-circular hollows were the lowest type of hollows in the study area. These types of dolines represented the initial forms of the dolines and were in a young stage. The number of dolines associated with distance from fault showed that the farthest doline was located in 3400 km, while more than 60 percent of Dolines were located within 0 to 500 m of faults in the region. Dolin density was related to the area of Karsts and the number of dolin in the study area. Dolin density in the study area reached over 1.5 per km2. The results of the analysis of the nearest neighbor showed that the mean of the nearest neighbor for Dolines in the study area was 0.86, which indicated the cluster distribution of Dolin. The cluster distribution of the Dolines indicated the evolution of the karstic system of the Shahu area. Correlogram of Kavat Spring had three distinct sections. In the first section, there was a quick drop in flow and within 10 days. This represented a quick flow in the karstic conduit. In the second part, the fluctuation was in the upper range of 2%. It is indicative of a semi-fast current in large fractures. In the third section, the fluctuation was mainly in the range between -2 and 2 and had a roughly uniform shape indicating a basic flow and a low inertia and low dynamic reserve in the aquifer. The Holy Spring Correlogram also showed almost the same situation and consisted of three distinct sections. Consequently, the aquifers showed the behavior of a developed karst. The spectral density function of both studied fountains provided a broad spectral band at frequencies below 17% and less than 15%. Ravansar spring at frequencies above 17% had a good filtering effect. And this value for a holly spring was higher than 15%. Indeed, distinct peaks at different frequencies over a period of time led to the identification of periodic events and, thus, to the recognition of the characteristics of the karstic system. The spectral density function indicated low inertia of studied aquifers, poor filtering, rapid flow and expansion of karstic channel networks in this aquifer. Discussion and conclusion The comparative evaluation of the karst geomorphology in relation to the hydrodynamic properties of aquifers in the study area suggested the development of the karst system in Shahu area. The results showed that relatively large parts of the shahu karst area were covered with dolines. The Dolin morphmetery features helped to recognize Dolines origin. More than 90 % of the Dolin area was elliptical doline which had a dissolution origin. The high dolin density in this region indicated the development of karst system. Differences in the Dolin morphometric characteristics indicated that the Dolin type was different from the origin of formation, the conditions and the time of formation. The analysis of the hydrodynamic characteristics of the Kavat and Holi springs also indicated the development of Shah's karstic system. The analysis of the hydrograph of the studied springs suggested a high degree of karstfication and the presence of a quick flow and the presence of karst coundit in Shahu area. The automatic correlation function of the springs confirmed the multiplicity of the behavior of the karstic system, the rapid response to precipitation, and the small volume of dynamic reservoir of aquifers. Accordingly, the existence of the developed karst forms, the multiplicity of elliptical dolin, their high density, the presence of joints, the abundant fracture in karstic masses, the presence of large karst conduit in the Shahu area indicated the development of the karst system and was confirmed by hydrodynamic surveys. [1]- Professor, Factualy of Geography, University of Tehran, Tehran, Iran. [2]- Associate Professor, Factualy of Geography, University of Tehran, Tehran, Iran.
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.
AtaAllah Nadiri; Esfandiar Abbas Novinpour; Rana Faalaghdam; Zahra Sedghi
Volume 5, Issue 17 , March 2019, , Pages 103-123
Abstract
Introduction
Population growth and the development of the agriculture and industry and the excessive use of groundwater resources have caused a drop in the water level. In arid and semi-arid areas, aquifer water management plays an appropriate role within human health of river basins and, therefore, ...
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Introduction
Population growth and the development of the agriculture and industry and the excessive use of groundwater resources have caused a drop in the water level. In arid and semi-arid areas, aquifer water management plays an appropriate role within human health of river basins and, therefore, their protection from anthropogenic contamination sources can be managed by proactive tools based on the aquifer vulnerability indices. The groundwater system does not respond quickly to contaminants. The arrival and diffusion of pollutants to groundwater occurs over time. Groundwater contamination is identified using the aquifer to provide water. Consequently, complete elimination of pollution is a long and often impossible process.The concept of vulnerability was first introduced in the late 1960s in France to provide information on groundwater contamination. The SINTACS framework is a suitable prescriptive approach but despite its popularity, it is susceptible to the need for expert judgment on assigning weights and rates for each parameter, which expose the output vulnerability maps to uncertainties in the same study area. Among different AI techniques, the current study was based on Mamdani Fuzzy Logic (MFL) to remove the expert opinion applied to SINTACS indices.
Materials and Methods
The Bilverdi sub-basin, with an area of 289 km2, is located approximately in 65 km of Tabriz city, East Azerbaijan, Iran. There is a vallilu arsenic mine to the north of Bilverdi plain. There are 208 wells, 7 springs, and 17 qanats in the study area.There is a possibility that the mine drainage leaks into the water resources and also extensive agricultural activities in the region increase the need to evaluate the vulnerability of the Bilverdi plain. In this study, SINTACS methods were used for the assessment of the inherent vulnerability of the Bilverdi plain aquifer. The SINTACS method is a PCMS which was developed by Civita and De Maio(2004) in order to assess the intrinsic vulnerability of groundwater with an increasing weight parameters and the wider range of ratings than the DRASTIC method. The acronym SINTACS originates from Italian words. The SINTACS method uses seven effective environmental parameters including Soggiacenza (depth of water), Infiltrazione efficace (effective infiltration), Non saturo (vadose zone), Tipologia della copertura (soil cover), Acquifero (aquifer), Conducibilità idraulica (hydraulic conductivity), and Superficie topografica (slope of topographic surface) to assess the vulnerability of the aquifer. After assigning weight and rate in the ArcGIS software, it was prepared as raster layers. Then SINTACS optimization was performed using Mamdani Fuzzy Logic (MFL). In this research, for the first time, the SINTACS method was optimized with artificial intelligence methods. Seven layers of the SINTACS method as an input and the SINTACS index corrected with nitrate were selected as the output model.
Results and Discussion
The SINTACS vulnerability Index Obtain by overlaying these seven layers and the Mamdani Fuzzy Logic (MFL) were used to optimize the SINTACS method and the data was divided into two categories of train and test. After model training, the model results were evaluated by the nitrate concentration through coefficient of determination (R2) and correlation index (CI) criteria. The results are as follows: The SINTACS Vulnerability Index was estimated to be between 70 and 169, of which 30, 67 and 3% of the study area were respectively located in low, medium, and high vulnerability zones.The results of the validation of the vulnerability maps with measured nitrate concentrations showed a correlation index (CI = 29). The results of the Mamdani Fuzzy Logic (MFL) were respectively R2 = 0.9, RMSE = 5.1 and R2 = 0.85, RMSE = 7.79 in the training and testing stages. The Vulnerability map of the numerical index is between 167.23 and 88.94 and the correlation index was (CI = 31).
Conclusion
This study used the SINTACS framework to assess groundwater vulnerability for Bilverdi basin, East Azerbaijan, Iran. The combined use of the SINTACS method and the geographical information system (GIS) produced a useful groundwater vulnerability map. The SINTACS index was calculated from 70 to 169. The poor determination coefficient calculated by the basic SINTACS framework made a research case for the application of Mamdani Fuzzy Logic. The results showed that Mamdani Fuzzy Logic (MFL) model showed high capability to improve the results of the general SINTACS and reduced the subjectivity of the model. The most vulnerable areas were in the northeast and southwest plain. The high vulnerability area needed to adopt strategic plans and policies to prevent the pollution of aquifers.
Abolghasem Amir Ahmadi; Mahnaz Naemi Tabar; Bahar Gholkar ostadi
Volume 4, Issue 11 , September 2017, , Pages 105-125
Abstract
Absract:
Introduction
Landslide is one of the natural phenomena causing many financial losses and casualties in Iran every year (Kamranzadeh, 2014: 101). This phenomenon occurs when the force of materials’ weight is higher than the shear strength of the soil shear force (Memarian et al. 2006: ...
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Absract:
Introduction
Landslide is one of the natural phenomena causing many financial losses and casualties in Iran every year (Kamranzadeh, 2014: 101). This phenomenon occurs when the force of materials’ weight is higher than the shear strength of the soil shear force (Memarian et al. 2006: 105). The Shannon entropy is a function of probability distribution and standard for measuring uncertainty in the information content of a parameter, and by considering occurrence frequency of subgroups of that parameter, it shows heterogeneity level. As a result, it calculates the effect of each parameter on the results of the system (Hosseinpour Mil Arghadan et al. 2014). Objectives of the present study are the selection of criteria and standards, preparation of digital factors layers, preparation of the landslide hazard zonation map, diagnosis of high risk points via the Shannon entropy, presentation of strategies appropriate for preventing possible risks and solutions to reduce damages in the study area. Bajgiran is the central district of Bajgiran County and a part Doulatkhaneh Rural District of Ghouchan Township. According to climate divisions, Bajgiran has a moderate mountainous climate. Geologically and structurally, it is a part of Kopeh Dagh Sedimentary Basin. In terms of stratigraphy, outcrops from the Jurassic rock units to the present era can be observed in the study area.
Materials and methods
In the present study, first of all factors affecting the occurrence of landslide including height, precipitation, slope, slope direction, slope shape, distance from the waterway, distance from the road, distance from the fault, land cover and lithology were identified as factors affecting the occurrence of landslides, and the mentioned maps were digitized in GIS. to this end, using the topographic map on a scale of 1:50000, the Digital Elevation Model Map (DEM), factors of slope degree, slope direction, slope shape, height level, distance from the waterway, and distance from the road were prepared. Using the land-use map on a scale of 1:25000, information layers of land use were extracted. To draw the lithological map, the distance from the fault of the geological map on a scale of 1:50000 was used. To draw the precipitation map, statistics of the rain gauge stations of five Daroungar, Mohammad Taghi Beig, Aman Gholi, Kikan, Hey Hey Ghouchan, and Bahman Jan Stations were used. The information content available in the decision matrix in entropy process is calculated via equation 1:
Equation 1: Ej = -K
Where Ej is the entropy value and Pi,j is the decision matrix.
Equation 2: Pij =
Where rij is the value or the special score assigned to each layer.
Equation 3: K= (lnm)-1
Where k is the fixed coefficient and m is the number of landslides.
After the formation of the decision matrix and extraction of the value of Ej, the value of Vj can be calculated via equation 4:
Equation 4: Vj = 1- Ej
Where Vj is the deviation degree of uncertainty.
And finally, to calculate the final weight of all factors (Wj), equation 5 is employed.
Equation 5: Wj =
To prepare the final map, equation 6 is used:
Equation 6:
Where Hi is the landslide hazard occurrence coefficient, Wj is the final weight of all factors, rij is the weight of each factors (Moghimi et al. 2012: 82).
Results and discussion
After converting criteria into integers and the formation of the initial matrix, the value of Pij was calculated via equation 1 and the value of K was calculated via equation 2. To calculate Ej for each criterion, equation 2 was used. The results are indicated table 2. In this equation, the value of E which is a function of n, for each n where Pi is equal, the value of E becomes maximum which is statistically calculated via probability distribution of Pi. Then, uncertainty or degree of deviation of each criterion (dj) obtained from the fraction of the value of Ej from 1 were calculated per each indices effective on landslides of the study area (table 2). After that, using equation 5, the weight of each parameters used in the entropy matrix of landslides (Wj) including height (0.02113), precipitation (0.031142), shape of slope (0.0116110), slope (0.011342), distance from the waterway (0.045161), distance from the road (0.113401), distance from the fault (0.099871), land use (0.997110), and lithology (0.095148) were obtained. Therefore, the regional model of the landslide hazard degree in the area was obtained via equation 6. Hi is the landslide hazard degree in the area (equation 7).
Conclusion
The aim of the present study was to prioritize factors affecting the occurrence landslides and zone their sensitivity in Bajgiran Region via the Shannon entropy. The results of the study shows that the most important factors affecting landslides in the study area are slope layers, slope direction, lithology, distance from the fault, and height. After weighting parameters and formatting the entropy matrix, the zonation mapping were conducted. To this end, information layers were prepared in Arc GIS and converted into Raster formats. With regard to zoning maps obtained from the entropy model, 15 landslides have occurred in the area among which 9 landslides have occurred in a high risk zone (42%), 4 landslides in a moderate risk zone (31%), and 2 landslides in a low risk zone (27%). Regarding the factor of slope, it can be said that the most landslides have occurred in slopes with 60%. It may because the lack of the soil-formation process prone to slippery movements. In case of the factor of slope direction, the most landslides have occurred in northern domains and in heights with 1600 m high. This results is compatible with the faults and calcareous, marl, and Pyura Chilensis organizations of the area. The results of the present study also show that the entropy model has appropriate performance in identifying risk areas and their zonation. In addition, the results can be used in decision making and management of land use and urban planning.
Saeed Jahanbakhsh Asl; Alimohammad Khorshiddoust; Mohammad Hossein Alinejad; Farnaz Pourasghr
Volume 3, Issue 7 , October 2016, , Pages 107-122
Abstract
Saeed Jahanbakhsh Asl[1]* Alimohammad Khorshidoust [2] Mohammad Hossein Aalinejad[3] Farnaz Pourasghar[4] Abstract Temperature and precipitation are two important parameters in hydrology and water resources. The impact of climate change on these two parameters has been the subject of many studies and ...
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Saeed Jahanbakhsh Asl[1]* Alimohammad Khorshidoust [2] Mohammad Hossein Aalinejad[3] Farnaz Pourasghar[4] Abstract Temperature and precipitation are two important parameters in hydrology and water resources. The impact of climate change on these two parameters has been the subject of many studies and studying atmospheric general circulation models is one of the best methods to estimate its effects. In the studies of climate change, lack of uncertainty in various stages of evaluation for the effect of climate change reduce certainty and confidence of the final outputs. In this study for analyzing the effects of climate change on precipitation and temperature in Shahrchay basin and the effects of the uncertainty related to general circulation models, six atmospheric general circulation model and 3 scenarios, A1B, A2 and B1 were downscaled by using LARS-WG. For evaluating the uncertainty of the models and scenarios, the output of models in the future and based period were compared by monthly statistical indices, coefficient of determination (R2) and Root Mean Square Error (RMSE) and the best models and scenarios for producing temperature and precipitation data were selected for the period 2011-2030. As the results, the HADCM3 model under scenarios A1B was used for precipitation and the MPEH5 under scenarios A2 for temperature production. The results of this research showed that in the future period rainfall will be reduced about 9 millimeter, while the minimum and maximum temperature will increase 1.05 and 0.87 °C respectively. Disruptions of rainfall distribution and high temperature have significantly negative consequences than rainfall reduction. [1]- Professor in Department of Meteorological, University of Tabriz, (Corresponding Autor), Email:s_jahan@tabrizu.ac.ir. [2]- Professor in Department of Meteorological, University of Tabriz. [3]- Meteorological Graduate Student of Tabriz Universit, Email:aalineghad63@yahoo.com. [4]- Climatology Ph.D., Meteorology Directorate General of East Azerbaijan Province.
Saeed Jahanbakhsk Asl; Hossein Asakereh Asakereh; Saeideh Ashrafi
Volume 6, Issue 21 , March 2020, , Pages 109-132
Abstract
1-IntroductionStudying and identifying the climate variabilities occurring in different regions, may give insight toward possible future climate variabilities. Using available climate models as well as downscaling, is a way to recognize the possible variabilities of climate components of future. ...
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1-IntroductionStudying and identifying the climate variabilities occurring in different regions, may give insight toward possible future climate variabilities. Using available climate models as well as downscaling, is a way to recognize the possible variabilities of climate components of future. In the present study, the precipitation and runoff of Rood Zard Basin were downscaled and simulated for the time period of 2006-2100. For this purpose, the RCP output scenarios of the CanESM2 model were utilized for 1975-2005. For downscaling the precipitation and runoff of Rood Zard Basin, the daily precipitation data of Baghmalek and the runoff data of the Mashin station and artificial neural network method were used. The mean sea-level pressure, the geopotential height at 500 hPa, and the mean temperature at ground level were all selected as the predictive variables, using correlation and partial correlation calculations, as well as the backward variable elimination method. The verification of the design was carried out by the RMSE and R2 indexes. Finally, the network architecture was selected through the Bayesian Regularization algorithm along with three hidden layers as the optimal network. The results show that annual precipitation have decrease trends in future 95 years. revealed that the precipitation increased in the hot months of the year and decreased in the cold months. In other words, the increase of local rainfalls due to the temperature rise is most probable in future periods. The runoff would decrease in the cold months and increase in the warm months regardless of the temperature and vegetation impact.Climate change is the main phenomenon affecting the climate and the human environment as well as environmental phenomena (such as droughts and wetness years, water resources, sea level changes, temperature alterations, changes in the behavior of climate elements, and many other phenomena). Investigating many phenomena of the past decades revealed that the planet earth's climate is changing. Compared to the previous time periods, the results of the previous studies indicated that the climate variablity trend has become faster in the past 150 years. To fully understand the climate, all the units involved in its formation should be evaluated simultaneously. For this purpose, models may be helpful to some extent. Modeling is the process of creating a model that can provide the structure and function of systems. One of these methods is GCM in which the climate is simulated. These models are developed based on different climate scenarios aiming to simulate the impact of greenhouse gases on the earth's climate. Moreover, they are able to simulate and predict the future climate of the earth.These models create various time series of climate variables with relatively large networking. However, they are not suitable for direct use in the studies relating to the local climate variability. Thus, researchers have designed suitable downscaling methods to gain the climate data on a local scale. One of these methods is the statistical downscaling. 2-Methodology and methodsIn the present study, the precipitation and runoff of the Rood Zard Basin are downscaled based on the RCP climate scenarios. RCPs are new emission stimulant scenarios which are used as the input of CMIP5 climate models and are based on the fifth report of IPCC. Scenarios are important parts of climate simulations that allow the researchers to study the long-term outcomes of the current decisions. In the RCP scenarios, 26 atmospheric parameters were considered for future simulations. Each of these has a relatively high connection to environmental elements. The selection of the most optimal parameter for expressing the relationship between weather conditions and the environmental characteristics depends on the type of environmental parameters. To select the appropriate parameters, the correlation and partial correlation calculations and the Backward Variable Elimination methods were applied.For downscaling, the BOX_019X_44Y data were acquired from the Environment website of Canada. The data were analyzed through calculating the correlation coefficients, partial correlation and also the Backward Variable Elimination method. The results revealed that 3 variables including the Mean Sea Level Pressure, the geopotential height at 500 hPa, and the mean temperature at ground level had an acceptable correlation with the precipitation at the Baghmalek station and omitting other variables created a lower missing variance.Downscaling was carried out based on the artificial neural network model with the Bayesian Regularization algorithm. Artificial neural networks are the patterns for processing data which are produced by imitating the neural network of the human brain. In recent decades, this method has been recognized as a useful and reliable tool for modeling complex maps existing between different variables. Artificial neural networks are able to pick up a system’s hidden behavior through available data. Each network has three layers: the input layer, the hidden layer, and the output layer. The input layer is, in fact, a layer used for producing the data given to the network as an input. The output layer includes values that are simulated by the network. The hidden layer is the place of analyzing the data. Unusually, the number of chosen neurons in this layer is obtained through trial and error.3-Results and discussionIn order to downscale neural network using the output RCP scenarios of the CanESM2 model, the daily precipitation data in the Baghmalek station during a time period of 30 years (1975-2005) were chosen as the base statistical period. After the selection of atmospheric high-scale variables, these variables were introduced into the neural network as input. The precipitation was considered as the target and the network was designed using algorithms and numerous hidden layers. Finally, the network designed with the Bayesian regularization and 3 hidden layers were chosen as the optimal network.As mentioned earlier, the artificial neural network was used for downscaling. Moreover, the daily precipitation data were simulated for the statistical period of 2006-2100. Linear regression was applied for simulating the runoff for the aforementioned period. The daily runoff, as well, was estimated for this period. The results demonstrated that the estimated monthly precipitation rate from November to December in the future 95-year period has decreased. Likewise, the simulated precipitation rates from January to November were higher than the monthly precipitation rates in the base period. Therefore, it can be concluded that the precipitation decreased in the cold months and increased in the hot months. Additionally, the runoff in the base period from January to May was less than the observed runoff and it was more than the observed runoff from June to December. This was due to the fact that only precipitation was used as an independent variable for modeling; whilst, the runoff was affected by other factors such as springs water in addition to the rainfall. From November to May, the estimated monthly rates of runoff for the next 95 years were reduced.Moreover, from November to October, the simulated runoff rates were more than the monthly runoff rates in the base period. Accordingly, it can be concluded that the runoff decreased in the cold season and increased in the hot season, as well. The increase in the precipitation and runoff rates in the hot season could be due to the rise in the local rainfalls. In other words, an increase in the local rainfalls due to global warming was probable in future periods.
Gholam hassan jafari; Zinab Barati
Abstract
1- Introduction The public opinion is that in the landform-topographic study, the drainage system, and the drainage pattern, by using geomorphic indicators one could assess the performance of active tectonics (Maghsoudi et al., 2011). This is true if we do not consider the primary structure of the earth, ...
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1- Introduction The public opinion is that in the landform-topographic study, the drainage system, and the drainage pattern, by using geomorphic indicators one could assess the performance of active tectonics (Maghsoudi et al., 2011). This is true if we do not consider the primary structure of the earth, rock type, and local factors determining the microclimate (Abedini et al., 2015; Jafari and Barati, 2018). Considering these factors, the results question the geomorphic indicators. In this paper, the researchers study the role of various factors in the drainage asymmetric index of 117 sub-basins in the Alvand mountainous of Hamadan. A subject not considered in the drainage asymmetry index of areas such as the Alvand mass of Hamadan is the shape of the magma lies between the sedimentary layers at the time of cooling. In relation to the drainage symmetry index, this paper tries to study the physical properties and the effect of local factors in the watersheds of the Alvand Hamedan Batholith. Although the drainage networks asymmetry of is analyzed with morpho-tectonic indices, the basic land structure, lithological and erosion properties can also affect the asymmetry of the basin. 2- Methodology For this purpose, parameters of the dominant slope, average slope, average height, the area of the right and left of the river, main river length, river airy length total length of the rivers, distance of the source of the dividing line, and rock types in different parts of sub-basins were determined. These parameters were used in calculation and analyses of Gravelius coefficients (compactness coefficient), elongation ratio, drainage density and asymmetry index. For the phenomenological investigation of the drainage network index status, with the help of topographical maps 1: 50000, the outlet point of the Alvand Batholith sub-basin was identified in the mountainous area. Accordingly, 13 sub-basins were classified in the Alvand Batholith. Class B subclasses are located inside the subclasses of class A and subclasses of class C are located inside class B subclasses. To separate sub-basins in each of the 13 sub-basins, the longest river was considered as the main river. All the streams connected to it are separated as subclasses of Class B. In the next step, the main river basin in the sub-basins of class B was also determined and the rivers entering it were designated as the sub-class C. Accordingly, a total of 117 sub-basins was identified. 3-Result and discussion In order to investigate the factors affecting the asymmetry index (tectonics, lithology, microclimate and physiography's characteristics of sub-basins); at first the status of sub-basin rock was studied. The largest area lies in the cordierite-Gabbro Stone (15.4%), and the smallest area lies in the Granite- Schist- Gabbro and cordierite-Gabbro (0.69%) groups. Investigating the elongation coefficient the sub-basins in which the dominant stone is granite shows a very low elongation ratio of these sub-basins. They lie in a group that is less elongated than the rest of the sub-basins in other rocks. In terms of the Gravelius coefficient, it can be said that the more symmetrical the basins tend to be circular in shape, as the mean Gravelius coefficient of the stable sub-basins for the asymmetric index is 3.35 vs. 2.64 in the relatively stable sub-basins, which fully confirms this point. The ratio of bifurcation of unstable sub-basins is very high, and according to the rocky area, the drainage density in the unstable sub-basins is inversely related to the slope of the basin. 4-Conclusion In general, sub-basins of the northeast slopes are more asymmetrical than sub-basins in the southwest slopes, which it can be due to the zhizman form of the Alvand Batholith, the differences in the physiographic properties, and finally the dominant sub-basin rocks. In the wider sub-basins of the slope and the varying direction of slope, are vectors that can have a significant effect on the drainage network asymmetry. The further elongation ratio of drainage of the basin with low drainage density, in granite rock, affects the drainage network asymmetry of the basin. Investigating the conditions of slope values in different classes of the asymmetric index in sub-basins other than granite rocks indicates that the difference between the value of the left and right slopes of rivers is not a significant effect in the basin asymmetry. By decreasing the sub-basins area, the effect of direction and slope value, elongation ratio and bifurcation coefficient on asymmetric basins decreases. The study of the Gravelius coefficient indicates that the shape of the more stable sub-basins is closer to the circular shape. The bifurcation ratio of most unstable sub-basins is very high. The drainage densities of unstable sub-basins have an inverse relationship to the basin slope. The difference between the rock types on the left and right and the river's position on the boundary between the two rocks have an important role in the basins asymmetry.
Reza Ghazavi; Majid Ramezani
Volume 4, Issue 12 , December 2017, , Pages 111-129
Abstract
Extend Abstract Introduction Groundwater is one of the most important resources of fresh water in the world, especially in arid and semi-arid areas. In these areas, the demand for groundwater has increased due to the decline of rainfall, population growth, and industrialization, while its quality has ...
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Extend Abstract Introduction Groundwater is one of the most important resources of fresh water in the world, especially in arid and semi-arid areas. In these areas, the demand for groundwater has increased due to the decline of rainfall, population growth, and industrialization, while its quality has declined via industrial and urban contamination. The removal of the groundwater pollution is very costly and time-consuming. Consequently, the prevention of the groundwater contamination is the best way for groundwater protection. The main aim of this study was to investigate the trend of groundwater quality and quantity changes in the Rafsanjan plain in relation to the groundwater discharge and rainfall change. Methodology The study area is the Rafsanjan plain with an area of 5459.36 km2 (with an altitude of 45°, 30¢ to 56°, 30¢ and latitude of 29°, 59¢ to 29°, 15¢). In this study, the essential maps including topography, drainage, piezometric wells location, and groundwater quality and quantity maps were created using GIS10.1. The groundwater level in 80 pizometric wells and the groundwater quality in 50 wells were investigated and analyzed for a period of 10 years (2002-2012). The groundwater unit hydrograph and rainfall pattern were compared to indicate the impacts of rainfall variability and the groundwater over-extraction on the groundwater level variation. Water quality maps were created using Vilcox method. Based on kriging interpolation method, the quantitative and qualitative maps of the study area were prepared using geographic information system (GIS). Results The groundwater hydrograph of the study plain indicated that the groundwater level declined continuously. As during the past 10 years, the groundwater decline was 8 m, so the annual groundwater decline in the study plain was 0.8 m. comparing the groundwater level of 2002 and 2012 via piezometric wells indicated a significant decline of the groundwater level. In 2002, for 81% of the study plain, the groundwater level was between 30-90 m, while it declined to 68% in 2012. The maximum groundwater decline was related to the area where groundwater level in 2002 was between 30 and 60 m. The area where the groundwater level was between 90 to 120 m, it increased from 683.8 km2 in 2002 to 999.7 km2 in 2012. Also the area where groundwater level was more than 120 m, it increased by 5.3%. A significant relationship was observed between the groundwater level and the volume of the groundwater extraction in 10 years of the study (R2 = 0.6). However, no significant relationship was observed between the groundwater level and the average rainfall between 2002 and 2012 (R2 = 0.04). These results indicated that the impact of the groundwater extraction on the groundwater level decline was more important than the rainfall change. In this study, Wilcox method was used for the investigation of the variability of the groundwater quality. Based on Electric conductivity (EC) and Sodium absorption rate (SAR) in Wilcox method, 16 classes of groundwater quality should be investigated. According to these results, in 10 years of the study period, the number of wells located in C3S2 and C4S2 classes of groundwater quality declined by 2 and 4% respectively. The number of wells located in C4S4 increased from 33% in 2002 to 38% in 2012. Cumulative discharge of all study wells decreased from 610 liter per second to 469 liter per second. The maximum decline was related to C4S3 and C4S2 groups. Discussion The results of this study indicated that the groundwater quality and level declined in the study area. According to the results of the water quality maps, the area of the aquifer with groundwater quality located in C3S2 and C4S2 respectively decreased by 6 and 1.4 %, while the area of the aquifer with groundwater quality located in C4S4 increased by 4.5 percent. The study of the piezometric wells with a depth of 30 m and less indicated that 15% of these wells dried between 2002 and 2012 due to groundwater level declination. The water quality of the profound wells (with a depth of 31 to 200m) decreased by 8.5%. These results indicate that the groundwater quality decreases with increasing of the groundwater level. Conclusion According to these results, the groundwater decline due to the rainfall decline, and the role of the groundwater abstraction in the agricultural area were more important than the rainfall deficits. The qualitative and quantitative maps of groundwater were also prepared via kriging interpolation method and GIS. Based on these results, it can be suggested that rainfall decline leads to the decline of groundwater, but excessive removal of groundwater resources in agricultural lands is a major factor that should reduce the quality of the groundwater in the study area.
Alireza Entezari; Abolghasem Amir Ahmadi; Kazem Aliabadi; Maryem Khosravian; Majid Ebrahimi
Volume 3, Issue 8 , December 2016, , Pages 113-139
Abstract
Received: 2015.01.26 Accepted: 2016.11.02 Alireza Entezari[1]* Abolghasem Amir-Ahmadi[2] Kazem Aliabadi[3] Maryam Khosravian[4] Majid Ebrahimi[5] Abstract Land surface temperature estimated to cater to the wide range of remote sensing, lack of monitoring and limited meteorological stations. With regard ...
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Received: 2015.01.26 Accepted: 2016.11.02 Alireza Entezari[1]* Abolghasem Amir-Ahmadi[2] Kazem Aliabadi[3] Maryam Khosravian[4] Majid Ebrahimi[5] Abstract Land surface temperature estimated to cater to the wide range of remote sensing, lack of monitoring and limited meteorological stations. With regard to the monitoring of land surface temperature in a limited number of weather stations as part of the need for broad distribution across the surface temperature at the same time, land surface temperature was calculated. Parishan lake because of the proximity to the metropolis of Shiraz shows the temperature and humidity play an important moderating role in this city. Drought in recent decades and the subsequent reduction in the water level of the lake has had adverse effects on the surrounding areas, especially in Shiraz temperature and humidity. The purpose of this research is to estimate land surface temperature using SEBAL (SEBAL) (modified surface energy algorithm for land) in Parishan Basin and relationship with land use / cover (LULC). For this purpose, use ETM+ images from 2000 and 2013 and after the various stages processing of image to extract the land use plans based on support vector machine (SVM) was developed during a period of 13 years. By applying SEBAL algorithm on satellite images was prepared heat map. For this purpose implement this method, was calculated the thermal radiance corrected (Rc), the emissivity of the surface of the thermal band (ε), spectral radiance (Lλ), the reflectance of each band (ρλ) and surface albedo (α). The results of this study showed the most of that land use changes in the use of the lake there is about was destroyed 35/97% of the lakes in the course of 13 years and much of it have land use changes uncultivated land and agricultural. In addition, increased desertification and loss of vegetation, it affects increasing land surface temperature (LST). The highest temperature (LST) is evident in the salt marsh and bare rock outcrops are considerable with the passing years and the increasing temperature. The results have been applied in the study of natural resources protection and can be helpful natural resource conservation programs. [1]- Department of Geomorphology and Climatology, Hakim Sabzevari University, Sabzevar (Corresponding Autor),Email:entezari@hsu.ac.ir. [2]- MS.c of Remote Sensing and GIS, Coach of Hakim Sabzevari University, Sabzevar. [3]- MSc Student of Applied Climatology, Hakim Sabzevari University, Sabzevar. [4]- MSc Student of Applied Climatology, Hakim Sabzevari University, Sabzevar. [5]- Ph.D Student of Geomorphology, Hakim Sabzevari University, Sabzevar.
Hossein Asakereh; Faramarz Khoshakhlag; zeanab shamohamadi
Volume 3, Issue 9 , March 2017, , Pages 113-137
Abstract
North Atlantic oscillation effective pattern of variability of atmospheric general circulation in the extra-tropical Northern Hemisphere are the main climatic factors that control precipitation and temperature. They have huge economic and social impacts and also on the energy section, agriculture, ...
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North Atlantic oscillation effective pattern of variability of atmospheric general circulation in the extra-tropical Northern Hemisphere are the main climatic factors that control precipitation and temperature. They have huge economic and social impacts and also on the energy section, agriculture, industry and so son. Considering the importance of the oscillation on human activities and its relationship with climatic elements including precipitation, we identified and analyzed the positive phase of the oscillation and its subsequent relationship with winter rainfall in Iran. Data needed for this study included measurements of the amount of rainfall on a daily basis in synoptic stations, Climate and rain gauge data for the entire country in the years 1340-1388 were used, the sources of which are Meteorological Organization and the Ministry of Energy. By the use of multivariate statistical methods and Matlab, Surfer and Grads software the extraction of synoptic patterns. The results indicated five patterns extractions despite the stable condition in five patterns of the earth's surface in this phase, and the measurement of atmospheric precipitation that justifies this subject, was done by using patterns in 500 hpa level. Iran is located in the axis of cyclone related to the Mediterranean basin. Therefore, atmospheric precipitation in the whole country was dominated by the low pressure occurrence in winter.
Mohammad Javanbakht; Naser Khaiate Kholghi; Mohsen Rezaei Arefi
Volume 5, Issue 14 , June 2018, , Pages 113-134
Abstract
Introduction
Tabarakabad catchment is a sub-catchment of the Gharaghom in the northeastern the Quchan city and in the Razavi Khorasan Province between the 37 º 02´41" until 37 º21´ 8" latitudes and 58 º 24´ 05" until 59 º 03´ 55" longitudes, 145 km away from ...
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Introduction
Tabarakabad catchment is a sub-catchment of the Gharaghom in the northeastern the Quchan city and in the Razavi Khorasan Province between the 37 º 02´41" until 37 º21´ 8" latitudes and 58 º 24´ 05" until 59 º 03´ 55" longitudes, 145 km away from west of Mashhad, which is located in Kopet Dagh geological zone. The formations have forms in the Tabarak Abad sub-catchment from late Jurassic period up to early Cretaceous period. Further, young sediment deposits in this basin are associated with Quaternary period. The purpose of this study was to evaluate the effects of morphometric indexes on textural parameters related to the size of the sediments in the catchment.
Methodology
Two sub-basin catchment the Yadak and Zirabe the Tabarakabad catchment create a choice and some morphometric quantitative indexes like hypsometric integral (H), ratio of valley floor width to valley height (VF), drainage basin asymmetry (AF), index Gradient along the river (SL), transverse topographic symmetry index (T) and the index of mountain front sinuosity (Smf), the shape of the basin (BS) calculated using topographic maps and digital elevation model (DEM) and business information in the field study with the help of ArcGIS and the index (Iat) was classified.
In order to study textural parameters related to the size of the main channel sediments 12 sediment samples (6 samples from the main channel the Yadak basin and of the main channel the Zirabe 6 samples) were taken. The sampling anywhere to help Hoes geological volume of a cylinder with a diameter of 20 and a depth of 25 cm deep were taken in this connection to the example of the local texture deposition was intact removal, as well as in The exact location of the samples were recorded by GPS. Dried samples were then transferred to the laboratory and seed dry sieve methods were classified.
Discussion
According to this Based on the study, the morphotectonic indexes include curves and hypsometry integral (H) of the Yadak 0.39 and class 1 in the Zirabe 0.7 class 3. The index Gradient along the river (SL) is an average value of 305.99 gradient meter in the Yadak and class 1 and 283.35 gradient meter in the Zirabe and class 1, the index of mountain front sinuosity (Smf) has been calculated as the Yadak 0.59 and class 1, and 0.86 in the Zirabe and class 2, the ratio of valley floor width to valley height (VF) index is the Yadak 0.23 and class 1 and the Zirabe 0.47 and class2, the drainage basin asymmetry (AF) is the Yadak 0.54 and class 2 and The Zirabe 0.59 and class 2, the shape of the basin (Bs) is in the Yadak 9.2 and class 1 and the Zirabe 0.47 and class 2, classification of the indexes based on Iat index suggested Class I for the Yadak and class 3 for the Zirabe sub-catchment, which represents the active sub-catchment Yadak of tectonic.
The sediments size it shows that in the Yadak sub-catchment sediment median size is -3.3, mean -2.5, sorting 2.5, skewed -0.05 and kurtosis 1.1. The Zirabe sub-catchment has sediment median size is -1.6, mean -1.2, sorting 2.1, skewed 0.47 and kurtosis 0.87. According to the obtained values for each sub-catchment can be stated that average size of sediments in the Yadak sub-catchment is coarser of the Zirabe sub catchment. Which reflects the high energy sub-catchment of the Yadak relative to the sub-catchment is Zirabe. The skewed shows according to of gravelly the average size of deposits in the sub-catchment Yadak of asymmetric curves have been fine gravel. While in the sub-catchment Zirabe sand deposits have created asymmetry, which reflects the average size of sediment in the subcatchment Yadak is coarser of the sub-catchment sub-catchment in times of low energy flow. The kourtosis sediments in the Yadak sub- catchment far more than the Zirabeh sub-catchment that represents Zirabe Changes less to flow is in the Yadak sub-catchment.
Conclusion
The results show that the Yadak sub-Catchment that was more active in class based on the morphometric indexes related to textural parameters is much higher. Finally it can be concluded in the catchment that have same effective elements in sediment texture, textured sedimentary catchment that are more active morphometry create their coarser.
Volume 1, Issue 1 , January 2015, , Pages 111-130
Abstract
Abstract
Neor is a very beautiful sweet water lake with an area of 240 ha located in the attractive Bagrrodag Mountains at 2700 m above the sea level on tectonic depression. As one of Iran’s unique lakes, Neor is 42 km from Ardabil with total basin area of 5300 ha. The aim of this research ...
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Abstract
Neor is a very beautiful sweet water lake with an area of 240 ha located in the attractive Bagrrodag Mountains at 2700 m above the sea level on tectonic depression. As one of Iran’s unique lakes, Neor is 42 km from Ardabil with total basin area of 5300 ha. The aim of this research was to study the hydrogeomorphology, climatology, tectonic, topography conditions and some properties of surfcal soil formation with quantity models and indexes (according to the fundamental sustainable development) to evaluate the possibilities of establishing tourist resorts in the area. According to the laboratory result the ratio of soil PH of the area under study was optimum. Therefore, the ratio of PH, EC and results of climatic indices indicated that the basin was potentially prone to soil erosion by runoffs. The average sediment yield of 338.65 ton/ha/year and total annually sediment yield 1794845 ton/ha/year in the small watershed indicated the high ratio of soil erosion. After systematic analysis and evaluation of environment potentials, the whole study area was divided into the stable, unstable, and semi stable areas for efficient land using. Ultimately, the study made suggestions on construction of suitable establishments in the Neor lake (water space and their banks and margins ) considering the future environmental potentials, land use map and further implications.
Ata Allah Nadiri; Fatemeh Vahedi; Asghr Asghari Moghaddam
Volume 3, Issue 6 , January 2017, , Pages 115-134
Abstract
Ata Allah Nadiri[1]* Fatemeh Vahedi[2] Asghar Asghari Moghaddam[3] Abstract Groundwater is the main supply of drinking and agriculture demands in Meshginshahr plain located on Northwest of Iran in the Province of Ardebil. The investigation of groundwater level fluctuations is necessary for effective ...
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Ata Allah Nadiri[1]* Fatemeh Vahedi[2] Asghar Asghari Moghaddam[3] Abstract Groundwater is the main supply of drinking and agriculture demands in Meshginshahr plain located on Northwest of Iran in the Province of Ardebil. The investigation of groundwater level fluctuations is necessary for effective groundwater management in this plain. For this purpose, artificial intelligence methods are interested due to high ability, cost effectiveness, needing less data, and fast running. This study presents a supervised committee fuzzy logic (SCFL) model to predict groundwater level at three piezometers in the study area. For implementing SCFL model, first fuzzy logic models such as Mamdani fuzzy logic (MFL), Larsen fuzzy logic (LSL) and Sugeno fuzzy logic (SFL) were applied to predict groundwater level using precipitation, temperature, discharge of abstraction wells and groundwater level with one month lag data. Then a supervised committee fuzzy logic as a non-linear model was used to combine the outputs of individual fuzzy models to reap the advantages of all three models simultaneously. Three different criteria RMSE, MAE and R2 were used to assess the prediction efficiency and accuracy of models. Based on results, MAE values of SCFL model are 0.12, 0.04 and 0.03 for piezometer 1, 2, and 3 respectively for training step. It presents the superiority of SCFL model over the individual fuzzy models. Also SCFL model could reduce prediction RMSE to 6% for piezometer 1 and 8%, 14% for piezometers number 2 and 3 respectively. [1]- Assistant Professor of Hydrogeology, University of Tabriz, Tabriz, Iran (corresponding author), Email:nadiri@tabrizu.ac.ir [2]- Master student of Hydrogeology, University of Tabriz, Tabriz, Iran. [3]- Professor of Hydrogeology, University of Tabriz, Tabriz, Iran.
Zeynab Alimirzaei; Rafat Zare Bidaki; Rasool Zamani-Ahmadmahmoodi
Volume 5, Issue 15 , October 2018, , Pages 115-133
Abstract
Abstract
Introduction
Drought is a natural phenomenon that may occur in all areas of land under any climate conditions. Scientific study of drought is essential for water resource planning and management and for mitigating water shortages. Low rainfall is the main cause of the occurrence of drought. ...
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Abstract
Introduction
Drought is a natural phenomenon that may occur in all areas of land under any climate conditions. Scientific study of drought is essential for water resource planning and management and for mitigating water shortages. Low rainfall is the main cause of the occurrence of drought. Precipitation reduction in a period of time than long term average of an area is defined as meteorological drought. Hydrological drought is defined as a significant reduction in available water of all forms in a landscape. Meteorological droughts lead to hydrological droughts with decreasing flow rates and aquifer discharge.
Methodology
In order to quantify drought phenomenon, some indicators on the basis of drought definitions or computational methods were provided. These indicators are calculated for a single point, but the extent of the drought and its severity vary in different parts of the basin and it is the key point of water resource management and planning for mitigation of drought crisis. The purpose of this study was to investigate the spatial and temporal variations of climatic and hydrologic drought in the North Karun Basin. In this study, some of the meteorological and hydrological indicators such as Deciles (DI), Z score, Standardized Runoff Index(SRI), Stream flow Drought (SDI), Standardized Water Index (SWI) and Groundwater Resource Index (GRI) were calculated to assess the status of the study area. In order to expand point information and convert it to spatial information, after calculating different indices, the meteorological and hydrological drought severity mapping was done using Kriging and IDW(with power 1, 2, 3 and 4) methods.
Result and Discussion
The results of the meteorological drought indices showed that during the 30-year period (1974-2014), the studied area had experienced a severe drought only once between the years 2007 and 2008. The SDI index showed that the river flows had declined at the same time as the meteorological drought between the years 2007 and 2008. In addition, the river flow drought (2007-2008) is clearly obvious in the next water year. In recent years, the SDI has fluctuated from moderate to severe drought, and in general, all stations experienced a moderate drought. SWI indicator analysis showed that groundwater level drop in the North Karun Basin occurred in 2007 and 2008, that has been delayed by one year to the meteorological drought. The results of the GRI in the North Karun Basin showed that the hydrological drought began between 2007 and 2008. Due to the sharp drop in groundwater level, the severity of the groundwater drought in recent years has been dramatically increased in the plains of the study area. The analysis of the Z index map indicated that while the drought is more intense in the eastern parts of the basin, it is less severe and intense in its northern and southern parts. Groundwater drought zoning showed that the severity of groundwater drought in the northeast and southeast of the plains is high. The Shahrekord plain is one of the most important plains in the North Karun Basin, because it has the main concentration of agricultural and animal husbandry activities and has undergone a sharp decline in groundwater over recent years. The groundwater level of this plain reached its lowest level between the years 2013 and 2014.
Conclusion
In general, the findings indicated that sever meteorological droughts in the time period of thirty years (1986-2015) occurred in two years (2000-2001 and 2007-2008). But its impact on surface flow and groundwater recharge is significant due to anomalies in the rainfall – runoff process and excessive withdrawals from the groundwater resources. The meteorological and surface water droughts periods in this basin often take one to two years. The duration and severity of droughts, especially in groundwater resources, have been significant in recent years. The results also showed that geostatistical method of kriging with exponential and gaussian model has a high ability for drought zoning. Also, it can be understood that the eastern part of the area has received fewer precipitation than the other parts. This result is also derived from the zoning of groundwater droughts that the eastern parts of the plains are more severely affected by drought. In general, hydrological droughts in the north Karun Basin are more intensive in the southern and southeastern regions. Simultaneous use of the meteorological and hydrological indicators can be a useful tool for the separation of the meteorological and hydrological droughts as well as the assessment of drought in the region.
Fariba Karami; Maryam Bayati Khatibi
Volume 6, Issue 18 , June 2019, , Pages 115-137
Abstract
IntroductionSoil erosion is one of the most serious environmental degradation problems that adversely affects many natural and human-managed ecosystems. In agricultural watersheds, soil erosion not only removes nutrient-rich top soil on site, but also degrades water quality as a result of transported ...
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IntroductionSoil erosion is one of the most serious environmental degradation problems that adversely affects many natural and human-managed ecosystems. In agricultural watersheds, soil erosion not only removes nutrient-rich top soil on site, but also degrades water quality as a result of transported sediments off site. The estimation of soil erosion is often complicated due to the complex interplay of many factors such as climate, land cover, soil, topography, lithology, and human activities. Erosion models can be used as predictive tools for soil loss assessment, conservation planning, soil erosion inventories, and project planning. Moreover, models can be used as tools for understanding erosion processes and their impact. They are basically categorized into three types of empirical, conceptual, and physical based models. Empirical models are usually statistical in nature and generally applicable only to conditions for which the parameters have been calibrated. The commonly used empirical soil erosion models are USLE, RUSLE, and MUSLE. Soil erosion based- physical models include AGNPS, WEPP, SWAT, and the like. One of the most widely applied watershed models is SWAT which has been extensively used for simulating hydrologic and water quality processes in watersheds with a wide range of scales and environmental conditions. Iran is among the most affected countries in the world in terms of the extent and intensity of soil erosion. Current estimates suggest that soil erosion in Iran is around 25 tons per hectare annually which is four times greater than the world average. In the Northwest of the country, the Sattarkhan Dam has been constructed on the Aharchay River, which is the source of drinking water, agriculture, and industry in the region. In the catchment area of the Sattarkhan Dam, which includes the Aharchay upstream, physical conditions such as being mountainous and the unstability of land management such as the spread of rainforests with plowing in the direction of gradient and developmental activities cause soil erosion, sediment production, damping reservoir capacity reduction and increasing reservoir sedimentation costs. The goal of this study was to model and evaluate the spatial distribution of soil erosion in the Sattarkhan Dam basin. In this study, Soil and Water Assessment Tool (SWAT) and MUSLE models were served for simulating sediment yield and identifying critical areas of soil erosion in the Sattarkhan Dam basin, located in the North West of Iran.MethodologyThe SWAT model is a continuous-time, semi-distributed, process-based river basin or watershed scale model. It was developed to predict the impact of land management practices on water, sediment and chemical yields in agricultural watersheds with varying soils, land use, and management conditions over a long period of time. It divides a watershed into sub watersheds. Each sub watershed is connected through a stream channel. In addition, each sub watershed is divided into Hydrologic Response Unit (HRU). HRU is a unique combination of soil, land use, and slope type in a sub watershed. SWAT predicts the sediment yield within each HRU using Modified Universal Soil Loss Equation (MUSEL). Sequential Uncertainty Fitting-2 (SUFI-2), a SWAT-CUP2012 sub-module computer program, was applied to optimize the parameters of the SWAT using monthly observed sediment yield data at a monitoring site in the Sattarkhan Dam basin. In this study, sediment discharges data series during 2004-2009 and 2010-2013 were respectively used for model calibration and validation. To evaluate model performance, the statistical methods consisted of the determination coefficient (R2), Nash-Sutcliffe coefficient (NS), and root mean square error observations standard deviation ratio (RSR).Results and DiscussionSeven highly sensitive parameters were recognized for sediment yield simulation including CN2, ESCO, CH_K2, SMFMN, CH_N2, PRF, and USLE_K. The calibration outputs for simulation showed a very good model performance for sediment yield where the values of R2, NS and RSR were respectively 0.76, 0.95, and 0.06. During the validation period, the annual sediment yield simulation of R2, NS, and RSR values were respectively 0.96, 0.93, and 0.1. Also, the results showed that the spatial pattern of the regions differed in terms of the erosion and sediment production. The critical areas were located in the upper part of the basin and sediment production was very high and high, which included about 34.15% of the area of the Sattarkhan Dam basin.Conclution This study showed that the SWAT model is competent of predicting sediment yields and, hence, can be used as a tool for water resource planning and management in the study watershed. The prediction of sediment yield at ungauged watershed with SWAT could be possible under comparable topography, land use, soil management, climate condition for the purpose of soil erosion assessment, scenario analysis, and recommendation of best management practices to support watershed management initiatives in the semi-dry mountainous regions of Iran.
Volume 2, Issue 2 , January 2015, , Pages 117-135
Abstract
The aim of this research is to investigate the correlation of greenhouse gases-carbon dioxide and methane - as elements of global warming on the Kashkan River’s discharge values. The data used in this study consist of seasonal and annual data of greenhouse gases and Kashkan River’s debby ...
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The aim of this research is to investigate the correlation of greenhouse gases-carbon dioxide and methane - as elements of global warming on the Kashkan River’s discharge values. The data used in this study consist of seasonal and annual data of greenhouse gases and Kashkan River’s debby between 1984 to 2010, using Pearson correlation coefficient, linear regression and Man-Kendal graphic method. The results show a strong negative correlation between the rate of global warming and the Kashkan River. This process has been intensified over the last 15 years, and from 1995 onwards the Kashkan River’s discharge has faced a sharp decline. Study of the changes in the annual runoff discharge strongly indicates an inverse relationship between global warming and Kashkan River flow; so that 2/55 of the annual discharge decrease in Kashkan River’s basin is the result of the global warming. Global warming has also affected the seasonal scale of Kashkan River’s discharge. The results show a reduction of discharge by 7/47 in summer, 6/45 in autumn, 38 percent in spring and 1/33 percent in winter. Finally, the use of exponential regression model predicted that if the global warming continues with the same scale, the average annual flow of the river will be below 10 cubic meters per second in the next 30 years, i.e. is till 2040.
Mohamad Khanehbad; Niloufar Hajian; Reza Moussavi Harami; Asadullah Mahboubi
Volume 2, Issue 5 , January 2017, , Pages 119-140
Abstract
Mohamad Khanehbad[1]* Niloufar Hajian[2] Reza Moussavi Harami[3] Asadullah Mahboubi[4] Abstract Farub Roman River with a length of about 19 km in the Northeast Neyshabur is a perennial river. To determine the sedimentary parameters in this river, 55 samples were taken from the main channel of this river ...
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Mohamad Khanehbad[1]* Niloufar Hajian[2] Reza Moussavi Harami[3] Asadullah Mahboubi[4] Abstract Farub Roman River with a length of about 19 km in the Northeast Neyshabur is a perennial river. To determine the sedimentary parameters in this river, 55 samples were taken from the main channel of this river and then granulumetry analysis and statistical parameters were calculated. The mean sorting of sediments is1.609phi (Poorly sorted) and skewness is 0.393 (Strongly fine skewed) and Kurtosis is 0.965 (Mesokurtic). This river is of braided type with load gravel bed. In this river, four sedimentary discontinuities and five sedimentary links are detected. Grain form of the river is in the range of very bladed, and major of deposits are in gravel range. Facies that could be identified in this river are: Gci (grain supported gravel), Gmm (matrix supported Gravel), Gmg (graded and matrix supported Gravel), Gh (grain supported gravel with horizontal bedding)) for gravelly facies, sand with horizontal bedding (Sh) for sandy facies and massive mud (Fm) for muddy facies. The facies formed in these structural elements are such as Channel (CH), Gravity flow deposits (SG), Gravel bars and Bed forms (GB) and Fine grain clastic deposits (FF). Based on the results, sedimentary model for Farub Ruman River is of braded type with loaded gravel bed. [1]- Assistant Professor, Faculty Geology, the University of Ferdowsi Mashhad, Mashhad (Corresponding author). Email:mkhanehbad@ferdoswsi.um.ac.ir. [2]- M.A.Student in Sedimentology, the University of Ferdowsi Mashhad, Mashhad. [3]- Assistant Professor, Faculty Geology, the University of Ferdowsi Mashhad, Mashhad. [4]- Assistant Professor, Faculty Geology, the Ferdowsi University of Mashhad, Mashhad.
Shahram Roostaei; Samad Azimirad; Davood Mokhtari; Seyed Asadollah Hejazi; Mojtaba Yamani
Volume 5, Issue 16 , December 2018, , Pages 119-138
Abstract
Abstract
Introduction
Saymarreh landslide is one of the known largest landslides in the world that is located in the southwest of Iran. The purpose of this study was to compare the characteristics and geomorphological influences of this landslide with the largest landslides of the world. Saymarreh ...
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Abstract
Introduction
Saymarreh landslide is one of the known largest landslides in the world that is located in the southwest of Iran. The purpose of this study was to compare the characteristics and geomorphological influences of this landslide with the largest landslides of the world. Saymarreh landslide is one of those large landslides that have undergone significant geomorphological, historical, and cultural changes during the Holocene era. The evolutionary trend of this landslide is highly complicated; in fact, it is one of the most important characteristics of large landslides. This landslide formed several dam lakes, and their formation were frequently repeated. However, it is not clear that whether the formation and evolution of the lakes were due to the river erosion sequences or the repetition of Saymarreh landslide.
Methodology
A large number of researchers believe that Saymarreh landslide is the largest landslide in the world, but some researchers do not believe so and introduce other landslides as the largest ones. Thus, by performing detailed investigations into the region, the geomorphic features of this landslide and its evolution was probed. To achieve this goal, ETM2002 satellite images, IRS of PAN and LISS III satellite images of 2004 and 2006, topographic maps, geological maps of SRTM DEM, and ArcGIS software were employed. The research method was empirical and it was based on the analysis of the field data. In this regard, the process of the landslide formation, its causes and morphometric characteristics in three classes of slide area, mass movement and displacement parameters along with deposited materials in Saymarreh Dam lakes were studied.
Result
The results relevant to the morphometry of the landslide indicated that various factors were involved in the occurrence of Saymarreh landslide. Among these factors, undercutting of the Asmari limestone layers made by Saymarreh and Kashkan Rivers, particularly in front of the landslide, was the most important cause of the landslide occurrence. The landslide had formed a large lake behind the slide mass and had formed sequential terraces due to repeated slides. The results of the morphometry of the lake, particularly through the estimation of its water (45.642 Gm3) and sediment volume (23.422 Gm3), and comparison of the time taken for filling of the water volume (19.8 years) with the time required for deposition of the whole sediment volume (1888 years) showed that the sediments have not been deposited only during one stabile period of the lake and the lake has been renewed at least at several stages. As a result, the reoccurrence of Saymarreh landslide at several times led to the obstruction of the Saymarreh River. Stratigraphy studies on the lake sediments and the age of its terraces clearly implied the renewal of the lake at least at 4 stages. The sequences of the lake terraces and other evidences confirmed the different scales of the reoccurrence of the large Saymarreh landslide.
Discussion and conclusion
This landslide obstructed the Saymarreh and Kashkan rivers and led to the formation a large lake in that region. The lake depleted after destructing the landslide mass, and there was a change in the direction of the Kashkan River.
The main triggering factor for this landslide was undercutting of Saymarreh and Kashkan rivers. Other factors included the direction and the angle of the slope, steep structural slopes, and gravity. The results obtained from the morphometry of Saymarreh Lake and stratigraphy of the lake sediments demonstrateed that Saymarreh landslide had been reactive several times and led to formation of the lake at several stages.
Ezzatollah Ghanavati; Feridoun Babaee Agdam; Taher Hemmati; Masoud Rahimi
Volume 2, Issue 3 , January 2017, , Pages 121-135
Abstract
Khiav Chai basin is located in Ardabil province as the sub basin of Gharasou basin. The
main river of this basin is Khiav Chai basin originating from the Sabalan Mountain,
which after passing through the Moeil valley flows into Gharasou River. Since the
Meshkin Shahr city is located downstream of ...
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Khiav Chai basin is located in Ardabil province as the sub basin of Gharasou basin. The
main river of this basin is Khiav Chai basin originating from the Sabalan Mountain,
which after passing through the Moeil valley flows into Gharasou River. Since the
Meshkin Shahr city is located downstream of this basin and is facing the frequent
danger of flooding, there should be special attention to prevent the flooding risk in this
area. This study focuses on the zoning potential floods in Khiav Chai basin using the
Fuzzy logic. To achieve this end, 8 parameters are used in this study including
vegetation density, drainage density, distance from drainage, lithology, land use,
rainfall, altitude and slope. In this model, all the layers with raster format were uploaded
into the Arc GIS software. Then the layers were fuzzified according to their functions.
In the next step, using different Fuzzy model functions, the zoning of the flooding of the
basin was completed. The results showed that the valleys, thalwegs with concave
slopes, and downstream areas were the most effective watershed areas in preventing
flood hazards. The results of this research can help reduce the loss of life and property
in downstream residential parts in the area, and can also be used as a basis for further
studies in relation to natural hazards.
Maryam Asadi; Ali Fathzadeh; Roohollah Taghizadeh Mehrjerdi
Volume 4, Issue 10 , June 2017, , Pages 121-143
Abstract
The main purpose of this study is an inquiry into the functions of daily, monthly, and annual scales of sediment data in their estimations using machine learning models. For this purpose, suspended sediment load data for three temporal, daily, monthly, and annual, scales at Ohio station, located in the ...
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The main purpose of this study is an inquiry into the functions of daily, monthly, and annual scales of sediment data in their estimations using machine learning models. For this purpose, suspended sediment load data for three temporal, daily, monthly, and annual, scales at Ohio station, located in the USA, between the years of 1992 and 2014 were selected. In order to choose the best model, some machine learning base models such as artificial neural networks, error back propagation as well as radial basis function, k-nearest neighbor, M5 decision tree, Gaussian process, support vector machine (SVR), evolutionary support vector machine (ESVM), and linear regression (LR) models were run and evaluated. The results of this study showed that the k-nearest neighbor with RMSE=5.28, the data Gaussian process model with RMSE=8.7, and the Gaussian process model with a RMSE=7.2 were respectively the best models for the daily, monthly, and annual data. The comparison of the models' assessment also suggested that the predicted annual data were more accurate than the monthly and daily data.
Khadijeh Haji; Shahnaz Mirzaei; Raoof Mostafazadeh; Habib Nazarnejad
Volume 4, Issue 13 , March 2018, , Pages 121-146
Abstract
Extended Abstract
Considering the relative stability of the physical characteristics of a watershed, the variability of the precipitation over space and time, and the direct relationship between rainfall and runoff, the variations of runoff can be expected and analyzed to understand the nature of variability. ...
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Extended Abstract
Considering the relative stability of the physical characteristics of a watershed, the variability of the precipitation over space and time, and the direct relationship between rainfall and runoff, the variations of runoff can be expected and analyzed to understand the nature of variability. Determining changes in the amount of runoff caused by rainfall and detecting the time of rivers' floods can provide a prediction of floods' occurrence and, consequently, reduce their damages. The increasing importance of water resources management in recent years, erosion, and sediment highlights the need for understanding the rivers' behavior and regimes. Regarding the changes in the river flow rate, estimating temporal and spatial variations of runoff changes can be effective in determining and controlling the dependent processes of soil erosion in a watershed and river bank, droughts, floods, and water quality and utilization. The analysis of the river flow variability, its duration and influencing factors, is necessary for an optimal river management/operation as the main sources of water uses.
Methodology
The monthly and annual runoff volumes of different stations were calculated based on the monthly discharge data in different years during the study period. Then, the variability indices were used to study the seasonal variations in the runoff volume at each hydrometric station. Next, using Annual Distribution of Regulating Coefficient and Concentration Rate indices, the seasonal variation in runoff volume of twenty river gauge stations located in Golestan Province were evaluated in 38 years. The values of Annual Distribution of Regulating Coefficient indicated the uniformity/ non-uniformity of changes in runoff volume at the studied river gauge stations. In addition, the annual variation of runoff volume was plotted in triple diagram models based on average runoff volume and time variables. The Kriging method was also used to draw the triple diagram models using two independent variables in a surfer environment. The Annual Distribution of Regulating Coefficient and Concentration Rate indices were considered as dependent variables. The variability of the implemented indices were analyzed over a time period of 38 years.
Results and Discussion
According to discharge data in different years, the monthly and annual runoff volumes of the stations were calculated during the study period. Based on the monthly spatial distribution, the results showed that the maximum amount of runoff volume of the stations were observed in March. The highest amount of surface runoff amounts occurred in Aghghala, Ghazagli, and Basirabad which respectively had an average annual runoff of 33.9, 33.5, and 32.6 million cubic meters. The highest uniformity in runoff occurrence was related to Nodehkhandoz, Tamar, Galikesh, and Gholitappeh stations, respectively with an annual Distribution of Regulating Coefficient of 0.19, 0.21, 0.23, and 0.24. The lowest Rate of runoff concentration was at Nodehkhandoz and Tamar stations respectively with 0.26% and 0.25%. The results also indicated a direct and significant relationship (R2 = 0.60) between Annual Distribution of Regulating Coefficient and Concentration Rate (p < .05). Ramian station had the highest Concentration Rate with a value of 0.62%. The highest significant decreasing and increasing trends, in Mann-Kendall test, were observed at Shirabad and Nodehkhandoz stations
Conclusions
According to the findings, there was a correlation between the annual distribution of regulating coefficient and the concentration rate. The higher values of the Annual Distribution of Regulating Coefficient and the Concentration Rate of runoff volume can be attributed to physiographic properties of watershed such as its slope, vegetation, and soil permeability. In other words, the process of changes in the runoff volume at these stations can indicate the temporal and spatial variations of precipitation, human protection measures such as dam construction in the basin, or the amount of permeability during the statistical period. In conclusion, with the non-uniform distribution of runoff volume in different months of the year, it can be expected that variations between the minimum and maximum values of runoff volume will also be high. Indeed, the higher the uniformity of the monthly distribution of runoff volume, the lower the variations between the minimum and maximum changes in the runoff volume. Variations in the amount of monthly runoff in the studied area can be related to the characteristics of the area, the hydrological response, and land use (agricultural land plowing season), as one of the main factors controlling runoff.
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.
Kaka Shahedi; Haiyeh Asadi; Mohammad Golshan
Volume 3, Issue 7 , October 2016, , Pages 123-139
Abstract
Kaka Shahedi[1]* Haniyeh Asadi[2] Mohammad Gholshan[3] Abstract Estimation of runoff in ungauged catchments has been an important subject for experts in planning of various projects. Focus of this study was on comparison and evaluation of Clark’s model and time- area method in predicting output ...
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Kaka Shahedi[1]* Haniyeh Asadi[2] Mohammad Gholshan[3] Abstract Estimation of runoff in ungauged catchments has been an important subject for experts in planning of various projects. Focus of this study was on comparison and evaluation of Clark’s model and time- area method in predicting output hydrograph in watersheds with lack of basic data. To this end, the time-area histogram was drawn by ArcGIS and the topographic map. Then, using rain gauge data and time-area method, the output hydrograph was estimated. In the next step, the obtained results were compared with the observed output hydrograph. Afterwards the Clark instantaneous unit hydrograph was also estimated using storage coefficient in order to simulate the unit hydrograph in Kasilian watershed. The storage coefficient was estimated using graphical, Clark, Linsley, Mitchell, Johnstone-Cross, Eaton, Hoyt-Langbein, Nash, Carter, Morgan-Johnson and Bell methods. Results were compared using quantitative statistics of root mean square of error, bias in peak discharge, coefficient of efficiency, and relative errors in peak discharge, time to peak and base time. The comparison of results showed that graphical method has had the highest accuracy in estimation of storage coefficient. Also The comparison of results showed that the Clark’s model had a good efficiency rather than time-area method and this showed effect of storage coefficient in flood routing in Kasilian watershed. So this method can be used with more accuracy to estimate output hydrograph in watershed with lack of basic data. [1]- Associate Prof., Sari Agricultural Sciences and Natural Resources University, Sari, Iran, (Corresponding author), E-mail: kaka.shahedi@gmail.com. [2]- Ph.D Student, Sari Agricultural Sciences and Natural Resources University, Sari, Iran. [3]- Ph.D Student, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
Fariba Esfandyari; Morteza Garachorlou
Volume 2, Issue 4 , January 2017, , Pages 125-142
Abstract
Fariba Esfandyari[1]* Morteza Garachorlou[2] Abstract This study seeks to identify and determine the spatial-temporal variations of sediment yield in Qarahsu watershed situated in Ardabil province. To do so, the relations between sediment yield and precipitation were examined in term of temporal-spatial ...
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Fariba Esfandyari[1]* Morteza Garachorlou[2] Abstract This study seeks to identify and determine the spatial-temporal variations of sediment yield in Qarahsu watershed situated in Ardabil province. To do so, the relations between sediment yield and precipitation were examined in term of temporal-spatial variations in order to provide the estimate model of sediment load in the subwatersheds. Data gathered from six water and rain gauges of the same name over a 22-years period was used. The method followed regression analysis between precipitation and sediment yield by SPSS software and analysis of temporal variations of precipitation and sediment yield by Excel software. Analysis of temporal relations between sediment load and precipitation indicated a higher correlation in intra-annual than in inter-annual scale. In terms of intra-annual variations, except for Hir water gauge, that underwent an increasing trend, other stations had decreasing trends in sediment load. Nonetheless, the increasing trend in annual precipitation of 4 rain gauges was considerable. Results of regression analysis, on one hand, indicated weak correlation between precipitation and sediment load in intra-annual scale, but on the other hand, indicated high correlation in inter-annual scale. Meanwhile, the Fournier index, as seasonal precipitation index, can explain 65% variance of specific sediment yield in the studied watershed. Hence, the index, as indicator of precipitation erosive power, can be effectively used to estimate specific sediment yield in the watershed. [1]- Associate Professor; Department of Physical Geography; University of Mohaghegh Ardebili, Iran (Corrosponding author), Email:Esfandyari@uma.ac.ir. [2]- Ph.D Student in Feomorphology; at University of Mohaghegh Ardebili; Iran.
Maryam Azarakhshi; Majid Aboutalebi; Ali Akbar Nazari Samani; Bahram Mohhamadi Golrang
Volume 5, Issue 17 , March 2019, , Pages 125-144
Abstract
Introduction
In arid and semi-arid areas, due to the lack of proper management of renewable natural resources, not only the proper utilization of water and soil resources is not done, but also water becomes a natural disaster, and every year, floods cause many human and financial losses. One ...
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Introduction
In arid and semi-arid areas, due to the lack of proper management of renewable natural resources, not only the proper utilization of water and soil resources is not done, but also water becomes a natural disaster, and every year, floods cause many human and financial losses. One of the integrated methods of flood control operations is flood spreading. This method improves the status of utilization of water and soil resources, plant cover, and artificial recharge of groundwater. Sediments that are carried with the flood, deposit in flood spreading region and may change the physical and chemical properties of soil over time. The most serious danger which threatens the flood spreading networks and artificial recharge schemes is the reduction of the infiltration of soil due to sedimentation. The most important factor affecting the performance of flood spreading systems is the amount of input sediment into the spreading canals, its depositing on the surface and accumulation in the depth of soil, which can change the physical and chemical properties of the soil. In this regard, current research was conducted to investigate the role of input sediments into flood spreading field, determine the penetration depth of sediments and the spatial pattern of physical and chemical changes in soil.
Materials and Methods
Kashmar flood spreading station is located in 17 km east of Kashmar, in the longitude of 58° 38' to 58° 40' of the east and latitude of 35° 15' to 35° 39' of the north. This research was conducted in the first Phase of Kashmar flood spreading. In this research, the first five channels of dewatering were divided into three study networks (outset, middle, and end), and the upstream of the spreading flood arena was considered as the control sample. In each grid, three points were selected as repeat tests and soil profiles were drilled with a depth of 1 m. In each soil profile, the soil samples from 0-50 and 50-100 cm depths were provided. At the test site, soil infiltration was determined using double rings. After transferring soil samples to the lab, the soil texture (clay, silt and sand percentages) was determined by the hydrometer method. In the laboratory, the value of the chemical parameters of the soil, including soil acidity (PH), electrical conductivity (EC), bicarbonate (HCO3ˉ), sulfate (SO4-2), chlorine (Cl), potassium (K+), and sodium (Na+) were measured. The effects of flood spreading on the physical and chemical properties of soil in spreading filed were investigated with the factorial experiment in a completely randomized block design.
Results
The results of the analysis of variance showed that there was a significant difference between the soil infiltration in channels 1 to 5 and the control arena at the probability level of 1%. However, there was no significant difference (p=%5) in soil infiltration in the start, middle, and end sections of the channels. In channels 1 to 5 and in the control arena, there was no significant difference (p=%5) in the amount of sand, silt, and clay. Flood spreading increased the amount of the clay in the depths of the channels compared to the control area. The Analysis of the variance showed all chemical properties of the soil. Except potassium, there was a significant difference (p=%1) between the dewatering channel and the control field. The amount of the variables did not change in the second depth compared to the control arena. The interaction effect between the depth and channel was not significant at 5% probability level. Thus, flood spreading did not change the chemical characteristics of soil in depth.
Discussion and Conclusion
The rate of the soil infiltration in spreading channel reduced 4.3 times of soil infiltration in the control arena. The least infiltration was observed in channels 1 and 2 due to the proximity of these channels to the source of flood and deposition of more suspended load on the surface of the soil. Because the suspended load of floods increased the clay particles and reduced the macro porosity, it decreased the soil infiltration. Flood spreading caused an increase of 1.5% in the soil acidity of the channels compared to the control arena. A 30% reduction in electrical conductivity was observed in the first two and third channels, compared to the control arena. The amount of HCO3-, Cl-, SO4-2, and Na+ reduced in the first, second, and third channels but increased in the fourth and fifth channels. The amount of potassium in all channels decreased compared to the control samples but this decrease was not significant. In general, flood spreading in Kashmar site caused the diminution of soil infiltration, which had a negative effect on flood spreading system. Therefore, it is recommended that water spreading channels are plowed every year to increase soil permeability.
