Showing 2 results for A. A. Kamgar Haghighi
N. Pirmoradian, A. A. Kamgar Haghighi, A. R. Sepaskhah,
Volume 6, Issue 3 (fall 2002)
Abstract
This research was conducted in Kooshkak Farm Research Station of Shiraz University in 1997 and 1998 in order to determine crop coefficient and water requirements of rice, using lysimeter. The variety used was Champa-Kamfiroozi which is an early mature variety and is grown by most farmers in the area. Results showed that potential evapotranspiration varied from 3.76 to 9.34 mm/day. Penman FAO method was used in calculating reference evapotranspiration. Crop coefficient was 0.97 in the initial growth stage, 1.25 in the mid-season growth stage, and 1.09 at the time of harvest. Total crop evapotranspiration rates in 1996 and 1997 were 560 and 757 mm, respectively. Average deep percolation rates in the growing season was 3.4 and 3.5 mm/day in 1996 and 1997, respectively. Finally the total water requirements of rice in 1996 and 1997 were 1983 and 2361 mm, respectively.
V. Khaksari, S. A. A. Moosavi, S. A. M. Cheraghi, A. A. Kamgar Haghighi, Sh. Zand Parsa,
Volume 10, Issue 2 (summer 2006)
Abstract
Since performing field experiments for determining the optimum amount of water for soil desalinization is costly and time consuming, use of computer models in leaching studies has received more attention. However, the accuracy of the results of these models should be evaluated by comparison with the results of the field experiments. In this study SWAP and LEACHC models were used for the simulation of soil moisture profile and salinity, and the results were compared with those of a field leaching experiment. The SWAP model gave better results in simulating soil moisture movement and profile, compared to LEACHC model, but statistical indexes showed that both models produced satisfactory results in predicting soil moisture profile. LEACHC model gave better results in comparison to SWAP model for the prediction of soil salinity profile at different time, possibly because it takes into account different solute transport mechanisms such as advection, diffusion, dispersion and also chemical interactions such as adsorption, precipitation and dissolution. In spite of the differences between predicted and measured values of salinity in the initial stages of leaching process, both models were able to predict the trend of leaching process with an acceptable accuracy.
