جستجوی مقالات مرتبط با کلیدواژه « آبدهی » در نشریات گروه « آب و خاک »

The excavation of underground structures, especially water conveyance tunnels, disrupts the natural groundwater flow regime in the area around the structure and continuously reduces the hydraulic head of the groundwater; causing problems such as drying up wells, qanats and springs close to the tunnel axis. Therefore, predicting the decline of groundwater level and flow in the water resources around the tunnel axis is one of the monitoring requirements in such projects. The Kerman Water Conveyance Tunnel, with a length of approximately 38 km, is designed to supply drinking water to the city of Kerman. According to the initial field studies in the area, there are about 242 springs along the tunnel route. In this research, the method provided by Demattis was used to investigate the possibility of changing the groundwater discharge of the resources due to the excavation of the Kerman tunnel. For this purpose, factors such as fracture frequency, rock mass permeability, the tunnel overburden, the plastic zone radius around the tunnel, the distance of the springs from the tunnel, the existence of main intersection faults between tunnel and water resources, and the type of groundwater resources were evaluated. Finally, the drawdown hazard index was classified into four categories: 1) minimal drawdown 2) partial drawdown, 3) significant drawdown, and 4) complete drawdown. Based on the obtained results, 52% and 27% of groundwater resources were placed on the partial drawdown and complete drawdown classes, respectively. The rest of the groundwater resources belonged to the other categories.

Unsustainable development without considering regional planning can create adverse environmental effects, especially in karst water resources of a region from a qualitative point of view. Accordingly, in this study, a combination of two methods for determining spring vulnerability and qualitative zoning by MDHT method was used. This study was performed for three springs downstream of Seymareh Dam for a period of 5 years. The results showed that the value of vulnerability index in S1 spring was higher than the other two springs and the value was 150.4. Analysis of the results showed that the degree of vulnerability was an inverse function of spring discharge. By increasing the amount of discharge, the vulnerability index decreases. Considering the choice of MDHT method for qualitative zoning of the spring and the role of flow rate in determining the zoning scenario, the highest flow rate was related to S3 spring. The value of obtained MDHT index was also higher than the other two sources and the value of 417 has been calculated. The lowest flow rate was related to S1 spring and the MDHT index value was 14.75. The highest level is related to spring S1 and the lowest level is related to springs S2 and S3. The results show that the karst network of springs in the region is vulnerable, which affects the quality of these resources and sensitive areas of the region to develop exploitation are strongly associated with the risk of pollution.

Changes in temperature and rainfall have a large impact on the quantity and quality of water resources, In this research, the effects of climate change on the development of special Qanats in Khusf city (Giw, Mazhan and Vahad Abad) were investigated. For this purpose, minimum and maximum temperature and precipitation were firstly estimated in the two near future (2030-2060) and far future (2070-2100) using the CANESM2 large scale model and two emission scenarios of RCP4.5 and RCP8.5. These data were then quantified by two downscaling models of LARS-WG and SDSM. Using rainfall data for the upcoming period, Discharge value for 3 Qanats were estimated for future periods. The results showed that the minimum and maximum temperatures in the RCP8.5 scenario would be higher than RCP4.5 in the results of both downscaling methods and will increase for both future periods. Rainfall also has slight variations for two scenarios of RCP8.5 and 4.5 for the upcoming period and the base period. Also, comparing two methods of downscaling, the LARS-WG model estimates the temperature changes less than the SDSM model and less changes in rainfall. The results of Qanat change in the upcoming period also showed that in all qanats, the discharge average for the coming period is less than the base period. Also, the RCP4.5 scenario compared to RCP8.5 in two methods of LARS-WG and SDSM is estimated to be greater. Given the changes in discharge in the future, management strategy can be adopted to deal with possible droughts.

Grouping of catchments based on their climatic factors and physiographic characteristics is a prerequisite for regional analysis of runoff and its use for estimating discharge of catchments without discharge measurement station. In this study, catchments located in Ardabil province were separated into homogeneous hydrological zones using discharge, mean annual precipitation and physiographic characteristics of catchments and hierarchical clustering method. Due to the large number of parameters, by using principal component analysis, the first four components with 83.6% of total variance were selected as inputs for cluster analysis. Then, the optimal number of clusters was determined by using hierarchical method and drawing the tree diagram, and finally the final clustering was done by K-means method. Subsequently, the sub-catchments that followed a hydrological process were identified using the Dalrymple uniformity test. The results of the uniformity test showed that by excluding stations outside the confidence limits of each cluster, catchments that were similar in terms of annual discharge and other physiographic and meteorological parameters were clustered. Therefore, the number of sub catchments located in clusters 1, 2, 3 and 4 were 8, 4, 9 and 9 catchments, respectively, which can be used in regional analysis to estimate runoff and floods in catchments without discharge measurement data.

To investigate the reason for decreasing Qanat’s discharge and providing technical and agricultural solutions, 15 limes of Qanats were selected in the Khorasan Razavi province. The discharge of Qanats in the years of 1386 and 1396 was measured together with filling of the questionnaires. The results show that the mean discharge of Qanats decreased by 21%. The reasons for this reduction include: technical issues (disregard for the technical nature of the Qanats), and management issues (disregard for proper utilisation of the Qanats and lack of credit). This research recommends some solutions in order to adapt to the decrease in Qanats’ discharge. The most important solutions include: cultivating products with less water requirements and improving drought tolerance, improving farm management by changing the pattern of crops, using modern technology, planning for proper use of Qanat water, and the integrity of the lower land of Qanats.

In the past decade the different methods have been used to analyze and predict the physical variables, one of which is singular spectrum analysis (SSA) statistical methods. SSA is one of the methods, used in modeling various statistical processes and more recently, its use in various engineering disciplines including water resources, in order to eliminate random components in time series has been expanded. The main objective of this study was to forecast streamflow in the Karkheh basin using singular spectrum analysis. The gage stations in the Karkheh basin (five station) were selected for this study. The high flow period for these gage stations were determined. In order to modeling methods, 70% and 30% of data were used for calibration and validation respectively. The singular spectrum analysis method was used for pre-processing of data and elimination of noise in the time series of streamflow. Then, the recursive algorithm of the singular spectrum analysis model was used to develop forecasts models of streamflow in the Karkheh basin gage stations. To evaluate the performance of the model Normalized root mean square error, mean absolute error and correlation coefficient were used. In the validation the highest and lowest value of the NRMSE and MARE statistics were 0.47 and 0.50 for Pol Chehr station. The lowest value of the NRMSE statistic for Pol Dokhtar and Cham Anjir stations was 0.3 and 0.31 respectively and close to each other and the lowest value of the MARE statistic for Cham Anjir and Pol Dokhtar stations was 0.29 and 0.30 respectively and close to each other. Finally, the best and the weakest results in two stages of calibration and validation were for Cham Anjir and Pol Chehr Stations respectively. The results of this research showed that singular spectrum analysis can be used to forecast streamflow with reasonable accuracy

Groundwater resources in Syahtalu- Garmabdsht region are important sources for drinking water supply for Gorgan City. In this region, there are a number of water wells in a small area which indeed forms a well field. Intersection of cone of depressions of these water wells causes the large decline in their water levels. Decline of water level in these water wells results in the considerable decrease of flowrate of water wells and some of them destroyed. Considering to the limited surface water resources to supply new needs of drinking water resources, the main focus is on groundwater resources of Gorgan. Since the groundwater basins that supply drinking water for the region is located in a small area, the quantity of groundwater in this area are affected. So far¡ comprehensive study on the well field on reducing water discharge has not been done. For this purpose, in this study the effects of well field within a small area (Garmabdasht) on the amount of water extracted is investigated.
Uncontrolled exploitation of groundwater can cause a sharp drop in groundwater levels that reduce the discharges of the factors affecting the well field are wells adjacent to each other, This means that the wells are closer to interfere cone drops more. As a result of an increase in decline and reduce discharges and another agent that is effective in reducing the discharge of water from well field. Based on the above factors and impact on reducing discharge wells Syahtalu- Garmabdsht area, a number of statistical indicators used. Distance index and discharge- Distance index are based on the factors affecting the capacity reduction defined. Another factor that played a significant role in reducing the discharge of wells in well field, structure wells. Using the evaluation of statistical indicators presented in this study, a simple and practical method to determine the impact of structure wells to reduce water discharge has been introduced.
After reviewing the discharge rates and reduce water discharge, it was found that the discharge of the index changes, DQI shows the highest correlation. And to determine the distance between the wells can minimize the impact of these factors on capacity reduction. As for the structure of wells, the results of this research indicate that the impact of structure wells to reduce water discharge varied from zero to 75 percent.
Indicators can be defined using a suitable space to create cone drop created around the wells to prevent interference cone drops and changes in the discharges wells in which the harvest is reduced to a minimum. DQI index the best statistical indicators for the lowest rate of decline is known discharges. In order to assess the impact of structure wells to reduce water discharge in this paper is a new way which the discharge index to the distance (DQI), the greater the percentage is even higher water discharge.

Awareness of flow rate data in rivers is essential for management of water resources, flood forecasting, engineering design and environmental management. The presented models for flow rate predicting in rivers, such as rainfall-runoff and time series are not consistent with the observed data in many cases due to the lack of accuracy and complexity of the factors affecting the discharge. Wavelet is one of the methods that has been considered in recent years in the field of hydrology. Wavelet method is also very effective in the field of signals analysis and time series. This paper presents a hybrid intelligent model based on artificial neural network and wavelet transforms is used to simulate monthly average discharge in Kor River and Pol-e-Khan Station. Performance of prediction models were evaluated using the criteria of Root Mean Square Error (RMSE) and determination coefficient. The results showed that the hybrid model of artificial neural network and wavelet transform with 2 degrees of decomposition offers the best results for the most suitable structure. In this structure, the output discharge for flow rate in the following month is calculated based on discharge in 4, 3, 2 and 1 month ago and current month and the values of RMSE and obtained 7.14 and 0.941 respectively.

In this study daily river flow of Barandouz-Chai in the period of 1973 to 2009 has been forecasted using nonlinear time series and Genetic programming models and result have been analyzed with root mean square error and regression coefficient methods. After evaluating model by goodness of fit، nonlinear BL (1،11،1،1) with the minimum AICC selected for modeling daily river flow forecasting. For BL (1،11،1،1) model regression coefficient and RMSE calculated equal to 0. 902 and 3. 52 (m3/s) respectively. Genetic programming has been used for modeling river flow with consideration to memory of one، two، three and four days before. Results showed until three days memory accuracy of model is acceptable but after that accuracy of model decreased. Regression coefficient and RMSE of Genetic programming in the testing phase calculated equal to 0. 928 and 2. 863 (m3/s) respectively. As results showed، Genetic programming with 22. 9 percent less error was better than Bilinear time series model in Barandpuz-chai river flow forecasting

One of the major factors on the amount of water resources is river flow which is so dependent to the hydrologic and meteorologic phenomena. Simulation and forecasting of river flow makes the decision maker capable to effectively manage the water resources projects. So, simulation and forecasting models such as artificial neural networks (ANNs) are commonly used for simulation and predicting the exact value of such factors. In this research, the Dez River basin was selected as the case study. This paper investigates the effectiveness of temperature, precipitation and inflow factors and the lag time of those factors in inflow simulation and forecasting. Genetic algorithm (GA) has been thus used as an optimization tool, determining the optimum composition of the effective variables. Thus, in a flow simulation and forecasting model, the number of hidden layers, effective neurons in each layer, effective meteorologic and hydrologic parameters and also the lag time of each factor of flow simulation and forecasting has been considered as decision variables, and GA has been used to obtain the best combination of those variables. In this study, minimization of the total mean square error (MSE) has been considered as the objective function. Results show GA's effectiveness in flow simulation and forecasting with consistent accuracy. The value of R2 criterion has been obtained 0.86 and 0.79 in the simulation and forecasting models, respectively. The results also showed superiority replies obtained from the simulation model to the prediction model. One of the reasons for this superiority can be considering the meteorological factors in the current month in river flow simulation.