fatemeh bayati; rasoul mirabbasi; Roohollah Fatahi Nafchi; mahdi radfar
Abstract
One of the most important challenges of researchers in rainfall-runoff modelling is the estimation losses and extracting excess rainfall, which can affect on accuracy of the model and hydrograph characteristics. In the present study, at first the infiltration index of was estimated based on the depth ...
Read More
One of the most important challenges of researchers in rainfall-runoff modelling is the estimation losses and extracting excess rainfall, which can affect on accuracy of the model and hydrograph characteristics. In the present study, at first the infiltration index of was estimated based on the depth of runoff and rainfall and also effective rainfall time. Then, instantaneous unit hydrograph was computed through Russo Method and the dimensions of direct runoff hydrograph were determined for 20 rainfall- runoff events. Then in order to increase the precision in estimating the dimensions of obtained hydrograph, the value of penetration index was estimated based on bivariate distribution resulted from infiltration index and one of rainfall characteristics which obtained from Copula function. For this purpose, at first the correlation between infiltration index of , characteristics of rainfall hyetograph and runoff hydrograph was calculated, then the best- fitted marginal distribution on each variable was specified. Finally, Galambos function was chosen as the best copula function for creating bivariate distribution for pairs of infiltration index of and rainfall height, infiltration index of and maximum velocity, infiltration index of and average flow and also infiltration index of and velocity. Therefore, the hydrograph dimensions were obtained for each event. Comparing the various dimensions of computed and observed hydrograph by copula function in Russo method showed that the infiltration index of can be estimated more accurately by using the copula function.
Zeynab Hosseinpour; Mahdi Radfar; Rasoul Mirabbasi
Abstract
One of the resources that have been severely affected by drought is groundwater, however it has been considered less than other water resources. Due to the recent droughts especially in the central regions of Iran, investigating the impact of droughts on water resources is very important. The main aims ...
Read More
One of the resources that have been severely affected by drought is groundwater, however it has been considered less than other water resources. Due to the recent droughts especially in the central regions of Iran, investigating the impact of droughts on water resources is very important. The main aims of this study are characterization of meteorological and hydrogeological droughts, assessment the effects of drought on groundwater level fluctuations and determining the critical regions of Shahrekord Plain Aquifer. For this purpose, modified Standardized Precipitation Index (SPImod) and Groundwater Resource Index (GRI) were used to assess meteorological and groundwater droughts, respectively. Also, the cross-correlation test was used to investigate the relationship between the meteorological drought and the groundwater drought. In this research, the monthly precipitation data of Shahrekord synoptic station and monthly groundwater level data of 35 piezometers in this plain in the period of 1984-2015 were used. Based on the result of GRI index, Shahrekord Aquifer was divided into three regions which cover the north and northwest, central and south-east and southwest. The results of correlation between modified SPI in various time scales of 1, 3, 6, 9, 12, 18, 24 and 48 months and GRI index indicates the highest correlation between 18-month modified SPI and GRI. The results also showed that the effect of meteorological drought on GRI index appears with 6 and 18-month delay on northern and central areas, respectively, and without delay on the South West of the Shahrekord Aquifer.
Mohammadtaghi Sattari; Mohammadreza Abdollah Pourazad; Rasoul Mirabbasi Najafabadi
Abstract
Floods are the main natural disasters that produce serious agricultural, environmental, and socioeconomical damages in many parts of the world. Accurate estimation of river flow in streams can have a significant role in water resources management and in protection from possible damages. This study aims ...
Read More
Floods are the main natural disasters that produce serious agricultural, environmental, and socioeconomical damages in many parts of the world. Accurate estimation of river flow in streams can have a significant role in water resources management and in protection from possible damages. This study aims to compare the abilities of Support Vector Machine (SVM), M5 model trees and Linear Regression (LR) methods in forecasting hourly discharge flow of Aharchay River. The hourly water level-discharge and 14 flood events data of Aharchay River measured at the Tazekand hydrometric station was used for modeling. The results showed that the SVM method gives more accurate results than the M5 model and LR method in forecasting river flow for next one and two hours with the R2=0.96 and RMSE=0.0472 (m3s-1) and the R2=0.90 and RMSE=0.1596 (m3s-1), respectively. Comparing the performance of SVR and M5 models indicated that, however the SVR approach may present more accurate results than the M5 model tree, but the M5 model provides more understandable, applicable and simple linear relation in forecasting hourly discharge. Thus, the M5 model tree can be used as an alternative method in forecasting hourly discharge.
