R. Rostamian, J. Abedi Koupai,
Volume 15, Issue 58 (3-2012)
Abstract
To optimize the use of water for agriculture, knowledge of the seepage of the channel is required. Although there are many empirical equations for estimating canal seepage, the coefficients of these equations are different from Iranian conditions and these equations vary in different areas. In this research, the ability of the SEEP model was studied to estimate the seepage from earth canals in downstream of Zayandehrud dam. Seepage from seven different earth canals (degrees of 3 and 4) was simulated with the model of SEEP and the results were compared to the water balance studies. Also, four empirical equations, Davis-Wilson, Moles worth and Yenni dumia, Moritz and Ingham were used to estimate seepage from these canals. The determination coefficients for these methods and SEEP model were obtained 9.3%, 6.7%, 37.3%, 18.3% and 87.9%, respectively. In contrast with empirical models, SEEP model has a proper ability to simulate seepage from degree 3 canals. The empirical models must be calibrated for local conditions.
A. Nasseri,
Volume 27, Issue 2 (9-2023)
Abstract
The selection of precision value for Roughness coefficient (RC) is necessary to design and utilize earth canals due to the vast distribution of Echinocola crus-galli in earth canals. Therefore, the current study was conducted to evaluate roughness coefficients in earth canals with Echinocola crus-galli at the Moghan plain (in the North-west of Iran). In the network of Moghan, 42 canal sections were selected to measure vegetation density and wet weight, water flow velocity (with a flow meter), and canal cross sections (with profilimetery devices). The hydraulic characteristics were estimated after water depth measurements. The Manning roughness coefficient (n) was applied to estimate the roughness coefficient. Path analysis was applied to identify the factors affecting the roughness coefficient. Multivariate cluster analysis using Ward's method and squared Euclidean distance was applied to cluster factors affecting the roughness coefficient in canals. The results revealed that RC averaged 0.015. The path analysis showed that the wetted perimeter, crop biomass, flow cross-sectional area, flow velocity, and hydraulic radius had the highest total effect on the roughness coefficient, respectively. The factors clustering showed that two clusters were obtained in the Euclidean distance of 11. The first cluster included flow velocity, crop biomass, flow rate, and bed slope; and the second cluster included flow cross-sectional area, wetted perimeter, and hydraulic radius. The findings could be helpful for designing and operating canals in the studied or similar regions.
