جستجوی مقالات مرتبط با کلیدواژه « عدم قطعیت پارامترها » در نشریات گروه « مهندسی آب »

Parameters uncertainty of rainfall-runoff models are the main sources of uncertainty in real time flood forecasting. In this paper, the Monte Carlo method is used to estimate the uncertainty of the forecasted flood hydrograph due to uncertainty in the calibration parameters of the rainfall-runoff model in Dez Basin in southwestern Iran. Precipitation and air temperature were predicted using Weather Research and Forecasting (WRF) model. The HEC-HMS hydrological model was used to forecast the flood hydrograph corresponding to the predicted precipitation and air temperature. The SCS-CN, Clark Unit Hydrograph, and Muskingum-Cung methods were used to model losses, transform and flood routing, respectively. The results show that the best scheme in WRF model is MYJLG to predict hourly precipitation and air temperature in Dez Basin. Therefore, the MYJ boundary layer scheme, Lin cloud microphysics scheme and GODDARD radiant scheme have the best performance in flood forecasting in Dez basin. In addition, the results of this study show that considering the simultaneous uncertainty in all parameters, the uncertainty in peak discharge of the forecasted flood hydrograph is higher than the uncertainty in the volume of the hydrograph. So that the uncertainty in peak discharge and the volume of forecasted flood hydrograph due to the uncertainty of all parameters are equal to 32.5 and 21.2%, respectively. Thus, with the lack of flood forecasting and warning based on risk, quantifying uncertainty has provided additional information about forecasts that will help decision makers make better decisions.

In this study, the different methods for groundwater vulnerability assessment to pesticides contamination and their uncertainties were introduced. Then, the groundwater vulnerability of agricultural regions of Pasha-Kolaa dam (Mazandaran province) to 7 pesticides has been assessed by the mobility potential indices in the typical conditions of pesticide properties (t1/2 and KOC) and the zonation maps of groundwater vulnerability in this region have been generated in the GIS environment. According to the uncertainty of the pesticide properties and the lack of necessary data for uncertainty analysis in the region of study, the mobility potential indices in different scenarios of pesticide properties (worst and best conditions of pesticide properties) (t1/2 and KOC) have been calculated, mapped and zoned. The zonation maps in three scenarios (best, typical and worst conditions of pesticide properties) were compared. Next, according to the regional values of mobility potential indices, generated for different scenarios, the pesticides are ranked using the composite programming method. Finally, the pesticides are clustered to three groups (suitable, transitional and unsuitable) by the combination of the results of previous sections. The clustering results showed that among of studied pesticides, 2,4 D Acid, Dimethoate and Fenvalerate are suitable, and Metsulfuron and Triclopyr are unsuitable pesticides for region of study. The other pesticides showed transitional condition.