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Showing 2 results for Zero-Inertia

B. Moravejalahkami,
Volume 23, Issue 3 (12-2019)
Abstract

Furrow irrigation is the most common method of surface irrigation. However, the accurate estimation of the soil water infiltration equation is the most important challenge for evaluating this method of irrigation. In this study, a fast and simple method that is named soil intake families and presented by USDA-NRCS (RSIF), evaluated for estimation of the Kostiakove-lewis infiltration equation parameters based on soil information. Also, this method was developed based on irrigation condition and considering soil characteristics (D-RSIF). Two treatments including constant and variable inflow discharge were tested with 4 repetitions and different irrigation phases including advance, storage and recession were simulated by developed Zero-Inertia model using RSIF and D-RSIF methods. The results showed that using the zero- inertial model, the difference between simulated advance times and simulated runoff were significant at 5% level for D-RSIF and RSIF methods. For variable inflow discharge, the error of estimating runoff volume was 10%, 6%, 12% and 41% for RSIF, D-RSIF, multilevel calibration and two-point methods respectively. Also, the irrigation scheduling error, based on soil physics characteristics (RSIF) was 14% that means consuming water more than required.

B. Moravejalahkami, M.h. Rahimian,
Volume 26, Issue 1 (5-2022)
Abstract

The current research was performed to present a quick and proper method for basin irrigation infiltration equation estimation by optimization of the Manning roughness coefficient. A two-level optimization of the Manning roughness coefficient method was presented by developing a zimod simulation model and initial intake families method, USDA-NRCS, (infiltration equation based on soil characteristics), and modified intake families (infiltration equation based on soil characteristics and inflow discharge). The investigation of the results of the model based on observed advance, recession, and surface storage showed the relative error of surface storage volume estimation was decreased by 38 to 50 % by adjusting the initial intake families method. The normalized root mean square error (NRMSE) of the advance estimation was between 0.22 to 0.85 for initial intake families and this parameter was between 0.09 to 0.5 for modified intake families. NRMSE of the recession estimation was between 0.13 to 0.75 for initial intake families and this parameter was between 0.09 to 0.19 for modified intake families. The presented method based on modified intake families increases the accuracy of infiltration estimation as compared to the initial intake families method and can evaluate basin irrigation acceptably. In addition, this method needs less time for basin irrigation evaluation as compared to the complete methods of optimization of infiltration parameters and roughness coefficient. 

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