Hajar Malakouti; Alireza Shokoohi; Hasan Zolfagharzadeh
Abstract
This study aims to determine the design strategy of a nuclear power plant near the river by assessing flood risk as a design precondition and the Darkhovin Nuclear Site near the Karoun River in Khuzestan Province was considered as a case study. In this study, by sampling the probabilistic space fitted ...
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This study aims to determine the design strategy of a nuclear power plant near the river by assessing flood risk as a design precondition and the Darkhovin Nuclear Site near the Karoun River in Khuzestan Province was considered as a case study. In this study, by sampling the probabilistic space fitted to the flow rate and by filtering and removing flood flows that does not overflow from the river to the flood plain, the two-dimensional HEC-RAS hydraulic model was used to determine the depth and flow velocity within the power plant site. Frequency analysis of flood depth simulated by the model for different discharges showed that the frequency distribution of flow depth and the generating flood are different from each other. The safe design of a power plant site requires consideration of the many uncertainties that make it difficult to use conventional methods. In this research, for the first time, the Rosenbluet technique was used to evaluate the uncertainty and finally to determine the maximum possible water level for locating the reactor core. The results show that to create the maximum probable depth with a return period of 100 years, there should be a flood with a return period of 10,000 years in Karoun downstream of Ahvaz. The method presented in this research can be the basis of a standard for the safe design of nuclear power plants in the vicinity of rivers considering flood hazards.
Fahimeh Razi
Abstract
Long meteorological drought can lead to the onset of hydrological drought. In this research, the lag time between the two types of drought was investigated for determining the hydrologic drought onset after realizing the climatological drought. This is a matter to provide managers with enough time for ...
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Long meteorological drought can lead to the onset of hydrological drought. In this research, the lag time between the two types of drought was investigated for determining the hydrologic drought onset after realizing the climatological drought. This is a matter to provide managers with enough time for decision making before the occurrence of water shortage in the watershed. The SWAT water balance model was used to determine and predict the lag time between the two types of drought for Foomanat (Anzali wetland) watershed in Gilan province Due to the ability to simulate the long-term flow of representative rivers in the basin. The OAT method was employed for the sensitivity analysis of the water balance model. Among the parameters used in SWAT, three parameters including curve number, available water, and the evaporation compensation factor in the soil were recognized as the most effective parameters for the results of the model. Calibration and validation of SWAT were performed using SCH model. The calculated Nash-Sutcliff and correlation coefficient in estimating runoff as well as determining and predicting the lag time between the two types of drought by SWAT were acceptable. The Nash coefficient was obtained as 0.68 and 0.8 for calibration, and 0.65 and 0.79 for validation periods, respectively. Using the calibrated model, one can predict the water balance situation and the lag time between the onset of meteorological drought and the emerging hydrological drought in the watershed for any interested meteorological drought scenarios. Based on the results, the chance of having a one -month lag time, is more than 70 percent, while the chance of a 2-month lag time in the Foomanat watershed Anzali wetland) is more than 23 percent.
Alireza Shokoohi; Asghar Azizian; Razieh Jemaat; Vijay Singh
Abstract
Flood forecasting in a sound way leading to correct results has been a challenge for all researchers and engineers for many decades, which is the basic reason for developing many different types of mathematical rainfall runoff models. Correct estimation of infiltration during a storm is essential to ...
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Flood forecasting in a sound way leading to correct results has been a challenge for all researchers and engineers for many decades, which is the basic reason for developing many different types of mathematical rainfall runoff models. Correct estimation of infiltration during a storm is essential to a justified and rational modeling of runoff at watershed scale. There are many experimental or mathematical models for simulating infiltration and deriving net rainfall with pros and cons. In the present research, instead of evaluating infiltration simulation methods solely, four more widely used methods; namely, ɸ index, Horton, Green-Ampt and SCS methods were selected to find out their effects on the performance of a kinematic wave based geomorphological model called KW-GIUH. Furthermore, a sensitivity analysis with respect to different infiltration methods and different overland and channel roughness coefficient were performed. Horton and ɸ method led to a better performance of the model in terms of observed and simulated hydrographs in the study watershed. In this regard, Nash-Sutcliffe efficiency indices for Horton and ɸ index methods were obtained as 94.9 and 90.3, respectively, while it was 77.7 for Green–Ampt and 76.3 for SCS infiltration method. According to results of sensitivity analysis, KW-GIUH performance has the most and least sensitivity when using Green–Ampt and ɸ index as the infiltration method, respectively. Although studying in a steep watershed with an overland slope of about 17% and a small area of about 38 km2, changing the overland roughness coefficient has more effect on the model performance comparing with the change of channel roughness coefficient. Simulated flood peaks changed about 64 % due to changing the overland roughness coefficient while this value amounted to 25% for channel one. Shortly, it is concluded that KW-GIUH is highly sensitive to infiltration simulation method and overland roughness coefficient.
