Showing 4 results for Bahremand
M. R. Bahremand, M. Afyuni, M. A. Hajabbassi, Y. Rezaeinejad,
Volume 6, Issue 4 (winter 2003)
Abstract
A field experiment was conducted to investigate the effects of sewage sludge and of time lapse after sludge application on soil physical properties. Four sewage sludge treatments (0, 25, 50, and 100 ton/ha) in a complete randomized block design with three replications were applied and mixed to a depth of 20 cm. Wheat was planted and soil physical properties were measured 23, 85, 148, and 221 days after sewage sludge application.
Sewage sludge application significantly increased MWD, hydraulic conductivity, final infiltration rate, moisture percentage at 1/3 and 15 bars, and plant available soil moisture, while it significantly decreased soil bulk density. In general, the best results obtained with the 100 ton/ha sewage sludge treatment. Time lapse after sewage sludge application caused soil physical properties to approach the values of the control. However, even 221 days after sludge application, the 50 and 100 ton/ha treatments had significantly different values compared with the control treatment. The results in this research show that sewage sludge can help to improve soil physical conditions and this effect persists over long periods. This effect is specially important with plant available soil moisture and infiltration.
H. Akbari Mejdar, A. Bahremand, A. Najafinejad, V. Sheikh,
Volume 18, Issue 67 (Spring 2014)
Abstract
Over-parameterization is a well-known and often described problem in hydrological models, especially in distributed models. Therefore, using special methods to reduce the number of parameters via sensitivity analysis is important to achieve efficiency. This paper describes a sensitivity analysis strategy that graphically assigns for each parameter a relative sensitivity index and relationship of the parameter and the outputs of the model. The method is illustrated with an application of SWAT model in the Chehelchai catchment, Golestan province. In this study, total water yield, along with four major parts of water budget including surface runoff, lateral flow, groundwater and evapotranspiration was selected as objective function. SWAT is a river basin model that can be used to predict the impact of land management practices on water, sediment and agricultural chemical yield in watersheds. A relative sensitivity index was used for ranking the sensitivity of parameters. The results showed that soil evaporation compensation facto (ESCO), CN, soil available water capacity (SOL-AWC), deep aquifer percolation fraction (RCHRG-DP) and soil bulk density (SOL-BD) have the most influence on river flow. These parameters are generally stated as the most sensitive parameters of SWAT model in most of the same researches worldwide
Sh. Moradipour, H. Zeinivand, A. Bahremand, A. Najafinejad,
Volume 18, Issue 69 (fall 2014)
Abstract
Evaluation of hydrologic behaviour and soil erosion as an environmental crisis is important in order to maintain watershed ecological safety at optimum level. The aim of this study is to evaluate the performance of the distributed hydrological WetSpa model in simulating erosion and sediment transport and also sedigraph in Taleghan watershed, Iran. Base digital maps and daily meteorological time series data for 9 years are the major model inputs. The calibration of global parameters was done for the first 5 years and the model validation was carried out for 4 years considering three month warm-up period at the beginning of both calibration and validation periods. The Nash-Sutcliffe criterion for the calibration and validation periods pointed out the efficiency of model simulation (82.7% and 79%, respectively). The next phase, the erosion module was calibrated for erosion and sediment transport simulation. The results showed the Nash-Sutcliffe efficiency criterion (60% and 64% for suspended sediment concentration and transport, respectively). Overall, the evaluation results reveal the good ability of WetSpa model in simulation of the hydrological processes e.g., runoff, raindrop detachment, runoff detachment, net soil loss, etc., in a given time and space
N. Dehghani , M. Vafakhah, A. R. Bahremand,
Volume 19, Issue 73 (fall 2015)
Abstract
Rainfall-runoff modeling and prediction of river discharge is one important parameter in flood control and management, hydraulic structure design, and drought management. The goal of this study is simulating the daily discharge in Kasilian watershed by using WetSpa model and adaptive neuro-fuzzy inference system (ANFIS). The WetSpa model is a distributed hydrological and physically based model, which is able to predict flood on the watershed scale with various time intervals. The ANFIS is a black box model which has attracted the attention of many researchers. The digital maps of topography, land use, and soil type are 3 base maps used in the model for the prediction of daily discharge while intelligent models use available hydrometric and meteorological stations' data. The results of WetSpa model showed that this model can simulate the river base flow with Nash- Sutcliff criteria of 64 percent in the validation period, but shows less accuracy with flooding discharges. The reason for this result can be the small and short Travel time noted. This model can simulate the water balance in Kasilian watershed as well. The sensitivity analysis showed that groundwater flow recession and rainfall degree-day parameters have the highest and lowest effect on the results, respectively. Also, ANFIS with the inputs of rainfall 1-day lag and evaporation 1-day lag, with Nash-Sutcliff criteria of 80, was superior to WetSpa model with Nash-Sutcliff criteria of 24 percent in the validation period.
