Ali Javadi; b m; m sh; m m
Abstract
In order to design or evaluate an irrigation system, the infiltration phenomenon and its variations should be determined accurately. In saline and sodic soil and water conditions, the importance of this issue will become greater. The main objective of this study was to estimate the coefficients of different ...
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In order to design or evaluate an irrigation system, the infiltration phenomenon and its variations should be determined accurately. In saline and sodic soil and water conditions, the importance of this issue will become greater. The main objective of this study was to estimate the coefficients of different infiltration equations (Kostiakov, Kostiakov-Lewis, Horton, Philip, and U. S. Soil Conservation) and to evaluate the performance of these equations under different qualities of irrigation water, initial soil moistures, and constant water head. Using a laboratory method, infiltrations were measured in soil columns for constant water head. Then, by applying the cumulative infiltration and drainage outflow data to HYDRUS-1D model, soil hydraulic parameters were determined by the inverse solution. To determine the coefficients of infiltration equations, the outputs of the HYDRUS-1D model including cumulative infiltration verses time were corrolated. The values of root mean square error (RMSE), standard deviation root mean square error (SDRMSE), normalized root mean square error (NRMSE), percent relative absolute error (AE) and percent relative error (RE), were used to evaluate the performance of each infiltration equation and to rank the equations. The equation that had the highest rank was considered as the best and more stable equation. The Horton equation with RMSE, SDRMSE, NRMSE and AE of 0.043, 0.018, 0.006 and 1 and the Kostiakov equation with the values of 0.234, 0.175, 0.025 and 4, were the most and the least suitable eqations, respectively. The evaluation of the performance of infiltration equations using statistical indicators showed that the Kostiakov-Lewis and the Kostiakov infiltration equations were the best and the worst equations, respectively. Comparison of NRMSE values showed that in most cases, under deficit irrigation, infiltration equations estimate infiltration more accurately. For a given treatment, the errors of Kostiakov-Lewis and Philip infiltration equations increased as the amount of irrigation water increased, and as the end of the season approached. The rest of the equations did not show any especial trends. To measure infiltration, it is necessary to consider the effects of irrigation water quality, initial soil moisture, and water heads, because these parameters influence the coefficients of infiltration equations and, consequently, the irrigation efficiency.
A J; M M; H E
Abstract
In management of surface irrigation, infiltration function is important. Quantitative understanding of this phenomenon is essential in preventing soil erosion and water losses. The main objective of this study was to estimate the coefficients of infiltration equations (Kostiakov-Lewis, Philip, and Horton) ...
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In management of surface irrigation, infiltration function is important. Quantitative understanding of this phenomenon is essential in preventing soil erosion and water losses. The main objective of this study was to estimate the coefficients of infiltration equations (Kostiakov-Lewis, Philip, and Horton) and evaluate the sensitivity and performance of these equations under various initial (initial soil moisture) and boundary conditions (water head on soil surface). Therefore, two-dimensional infiltration for furrow irrigation were simulated by changing the initial soil moisture (before irrigation) and water head on soil surface (during irrigation) using the solution of the Richards’ equation (HYDRUS model). To determine the coefficients of infiltration equations, outputs of the HYDRUS model (cumulative infiltration over time) were fitted. Evaluating the performance of infiltration equations via statistical evaluation indicators showed that infiltration empirical equations (Kostiakov-Lewis and Horton) had better performance than the physical equation (Philip) to estimate the cumulative infiltration under various initial and boundary conditions. Kostiakov-Lewis equation ranked the first in all cases of estimating infiltration by simulations, followed by Horton and Philip equations. Sensitivity assessment of the coefficients of the equations showed the power coefficient (b) of Kostiakov-Lewis equation as the most sensitive coefficient, while the final infiltration rate coefficient ( 15ff"> ) in Horton equation was the least sensitive. The results also showed that Horton equation was the most sensitive equation in evaluation of infiltration equations sensitivity.