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1.
An accurate estimate of the groundwater inflow to a tunnel is one of the most challenging but essential tasks in tunnel design and construction. Most of the numerical or analytical solutions that have been developed ignore tunnel seepage conditions, material properties and hydraulic-head changes along the tunnel route during the excavation process, leading to inaccurate prediction of inflow rates. A method is introduced that uses MODFLOW code of GMS software to predict inflow rate as the tunnel boring machine (TBM) gradually advances. In this method, the tunnel boundary condition is conceptualized and defined using Drain package, which is simulated by dividing the drilling process into a series of successive intervals based on the tunnel excavation rates. In addition, the drain elevations are specified as the respective tunnel elevations, and the conductance parameters are assigned to intervals, depending on the TBM type and the tunnel seepage condition. The Qomroud water conveyance tunnel, located in Lorestan province of Iran, is 36 km in length. Since the Qomroud tunnel involved groundwater inrush during excavating, it is considered as a good case study to evaluate the presented method. The groundwater inflow to this tunnel during the TBM advance is simulated using the proposed method and the predicted rates are compared with observed rates. The results show that the presented method can satisfactorily predict the inflow rates as the TBM advances.  相似文献   
2.
Flood frequency analysis based on simulated peak discharges   总被引:2,自引:0,他引:2  
Flood frequency approaches vary from statistical methods, directly applied on the observed annual maximum flood series, to adopting rainfall–runoff simulation models that transform design rainfalls to flood discharges. Reliance on statistical flood frequency analysis depends on several factors such as the selected probability distribution function, estimation of the function parameters, possible outliers, and length of the observed flood series. Through adopting the simulation approach in this paper, watershed-average rainfalls of various occurrence probabilities were transformed into the corresponding peak discharges using a calibrated hydrological model. A Monte Carlo scheme was employed to consider the uncertainties involved in rainfall spatial patterns and antecedent soil moisture condition (AMC). For any given rainfall depth, realizations of rainfall spatial distribution and AMC conditions were entered as inputs to the model. Then, floods of different return periods were simulated by transforming rainfall to runoff. The approach was applied to Tangrah watershed in northeastern Iran. It was deduced that the spatial rainfall distribution and the AMCs exerted a varying influence on the peak discharge of different return periods. Comparing the results of the simulation approach with those of the statistical frequency analysis revealed that, for a given return period, flood quantiles based on the observed series were greater than the corresponding simulated discharges. It is also worthy to note that existence of outliers and the selection of the statistical distribution function has a major effect in increasing the differences between the results of the two approaches.  相似文献   
3.
Rainfall threshold (RT) method is one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the threshold rainfall curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall impacts the flood peak discharge and the time to peak. To revisit a previous study conducted by the authors, in which spatially independent rainfall pattern was assumed, the spatial distribution of rainfall was simulated following a Monte Carlo approach. The structure of the spatial dependence among sub‐watersheds' rainfalls was taken into account under three different scenarios, namely independent, bivariate copula (2copula) and multivariate Gaussian copula (MGC). For each set of generated random dimensionless rainfalls, the probabilistic RT curves were derived for dry moisture condition. Results were evaluated with both historical and simulated events. For the simulated events, threshold curves were assessed by means of categorical statistics, such as hit rate, false rate and critical success index (CSI). Results revealed that the best performance based on the CSI criterion corresponded to 50% curve in 2copula and MGC scenarios as well as 90% curve in the independent scenario. The recognition of 50% curve in 2copula and MGC scenarios is in agreement with our expectations that the mean probable curve should have the best performance. Moreover, the proposed inclusion of spatially dependent rainfall scenario improved the performance of RT curves by about 25% in comparison with the presumed spatially uniform rainfall scenario. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
4.
Pattern recognition is the science of data structure and its classification. There are many classification and clustering methods prevalent in pattern recognition area. In this research, rainfall data in a region in Northern Iran are classified with natural breaks classification method and with a revised fuzzy c-means (FCM) algorithm as a clustering approach. To compare these two methods, the results of the FCM method are hardened. Comparison proved overall coincidence of natural breaks classification and FCM clustering methods. The differences arise from nature of these two methods. In the FCM, the boundaries between adjacent clusters are not sharp while they are abrupt in natural breaks method. The sensitivity of both methods with respect to rain gauge density was also analyzed. For each rain gauge density, percentage of boundary region and hardening error are at a minimum in the first cluster while the second cluster has the maximum error. Moreover, the number of clusters was sensitive to the number of stations. Since the optimum number of classes is not apparent in the classification methods and the boundary between adjacent classes is abrupt, use of clustering methods such as the FCM method, overcome such deficiencies. The methods were also applied for mapping an aridity index in the study region where the results revealed good coincidence between the FCM clustering and natural breaks classification methods.  相似文献   
5.
Nowadays, Flood Forecasting and Warning Systems (FFWSs) are known as the most inexpensive and efficient non‐structural measures for flood damage mitigation in the world. Benefit to cost of the FFWSs has been reported to be several times of other flood mitigation measures. Beside these advantages, uncertainty in flood predictions is a subject that may affect FFWS's reliability and the benefits of these systems. Determining the reliability of advanced flood warning systems based on the rainfall–runoff models is a challenge in assessment of the FFWS performance which is the subject of this study. In this paper, a stochastic methodology is proposed to provide the uncertainty band of the rainfall–runoff model and to calculate the probability of acceptable forecasts. The proposed method is based on Monte Carlo simulation and multivariate analysis of the predicted time and discharge error data sets. For this purpose, after the calibration of the rainfall–runoff model, the probability distributions of input calibration parameters and uncertainty band of the model are estimated through the Bayesian inference. Then, data sets of the time and discharge errors are calculated using the Monte Carlo simulation, and the probability of acceptable model forecasts is calculated by multivariate analysis of data using copula functions. The proposed approach was applied for a small watershed in Iran as a case study. The results showed using rainfall–runoff modeling based on real‐time precipitation is not enough to attain high performance for FFWSs in small watersheds, and it seems using weather forecasts as the inputs of rainfall–runoff models is essential to increase lead times and the reliability of FFWSs in small watersheds. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
6.

Tunneling is often unpopular with local residents and environmentalists, and can cause aquifer damage. Tunnel sealing is sometimes used to avoid groundwater leakage into the tunnel, thereby mitigating the damage. Due to the high cost of sealing operations, a detailed hydrogeological investigation should be conducted as part of the tunneling project to determine the impact of sealing, and groundwater modeling is an accurate method that can aid decision-making. Groundwater-level drawdown induced by the construction of the Headrace water-conveyance tunnel in Sri Lanka dried up 456 wells. Due to resulting socio-environmental problems, tunnel sealing was decided as a remedy solution. However, due to the expectation of significant delays and high costs of sealing, and because the water pressure in the tunnel may prevent groundwater seepage into the tunnel during operation, there was another (counter) decision that the tunnel could remain unsealed. This paper describes groundwater modeling carried out using MODFLOW to determine which option—sealed or unsealed tunnel—is more effective in groundwater level recovery. The Horizontal Flow Barrier and River packages of MODFLOW were used to simulate sealed and unsealed tunnels, respectively. The simulation results showed that only through tunnel sealing can the groundwater level be raised to preexisting levels after 18 years throughout the study area. If the tunnel remains unsealed, about 1 million m3/year of water conveyed by the tunnel will seep into the aquifer, reducing the operational capacity of the tunnel as a transport scheme. In conclusion, partial tunnel sealing in high-impact sections is recommended.

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7.
Water resources management is an important driver in social and economic development. Water shortage is one of the most critical issues threatening human welfare, public health, and ecosystems. This issue has turned into a major challenge in many river basins all around the world due to the imbalance in water supply and demand. Use of simulation models can be effective tools in providing water managers with scientifically supported decisions in dealing with complex and uncertain water resource systems. System dynamics approach serves as a management tool and may play an important role in understanding the cause–effect in water resources systems. In the present study, system dynamics approach was applied to simulate management strategies dealing with Tehran metropolitan water resources systems. In the developed model, the trend of water storage in the next 30-year period and the effectiveness of water supply strategies were simulated. The results showed that, despite the growing shortage of the water resources, optimal use of existing resources under appropriate strategies could reduce water deficit within the next 30 years.  相似文献   
8.
Implementation of structural and non-structural flood control measures in flood-prone watersheds is on increasing demand. Different watershed areas are not necessarily hydrologically similar and impose variable effects on the outlet flow hydrograph. Meanwhile, prioritization of watershed areas in terms of flood generation is essential for economic flood control planning. Previous works have focused on the definition of a flood index that quantifies the contribution of each subwatershed unit or grid cell to the outlet flood hydrograph through the application of unit flood response (UFR) approach. In the present research, for the first time, the effect of spatial pattern of storm events on the flood index variation was assessed via a Monte Carlo uncertainty analysis. To do so, the UFR approach was carried out for a large number of randomly generated rainfall spatial pattern. The proposed methodology was adopted to the Tangrah watershed in northern Iran. The watershed is frequently hit by floods that have historically caused loss of life and properties. The results indicated that for the more frequent flood events, the flood index is quite sensitive to the spatial distribution of rainfall such that for the highest ranked subwatershed (SW6), the standardized variation of the flood index values (i.e., the uncertainty range) decreases from 1.0 to 0.5 when the rainfall depth increases from 20 to 150 mm, respectively. The results further revealed that increasing the rainfall depth from 20 to 150 mm would cause the effect of rainfall spatial distribution on subwatersheds’ flood indices to diminish. The implications are that if flood control measures are designed for more frequent floods with lower return periods, an uncertainty analysis is required to identify the range of flood index variations.  相似文献   
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