zero-inertia model

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.

Surface irrigation methods are the most common methods for irrigation of agricultural land. These methods are superior to sprinkler, drip and underground irrigation, because they have lower costs of funding and implementation, is inexpensive, needed maintenance of equipment is simple and does not require skilled labor. New requirements for the use of municipal water, energy, industrial, and military intends to further improve the performance of surface irrigation systems. In other words, the low efficiency of surface irrigation is not related to the method of it, but the weakness is because of the design, implementation and management. Due to the special place of Khuzestan province in southwest of Iran in agriculture and applied surface irrigation for most of the farms in this province, in the present study was simulated water flow in furrow irrigation by using WinSRFR4.1 and the optimum length of furrow was determined in the experimental farm of the Water Sciences Engineering Shoshtar University. For this purpose, advance and recession of flow were simulated by Zero inertia and Kinematic wave model and result were compared with observed data.
In order to calculate and predicte advance and recession curves field measurement is necessary, but it takes a lot of time and cost. Therefore, the use of mathematical models and software for access information is important. In this research the amount of advance in furrow irrigation was measured and the results were compared with simulation of WinSRFR4.1.Field experiments was conducted in the research field of Water Sciences Engineering Shoshtar University. Data were collected from three furrows. The lengths of them were 60, 80 and 100 meters. Irrigation was performed under three discharges (1, 1.25 and 1.5 L/s), with three iterations. Three experiments furrows were provided which central furrow was for measurement data and side furrows were as buffer furrow. Before experiment in order to determine soil texture undisturbed soil samples were prepared from four depths 25-0, 50-25, 75-50 and 100-75 cm. Soil texture was determined in laboratory using the hydrometer method. The water supply was transported by pumping the water to the farm. This research was conducted in the winter of 2012 and spring of 2013. The end of furrow was opened. Input and output flows were controlled with W.S.C flume. Infiltration data were also measured according to two point method. Model using 27 set of field data was run and the results were compared with WinSRFR4.1 software. For evaluating the results of the model were used Esfandiari and Maheshwari’s statistical method.
For comparison between measurement and simulation data , , and indices were applied. The results of this study indicated that the phase advance of predicted values for all models is greater than the observed values. The average relative error rate of zero inertia models was 9.588 percent which indicated that Zero inertia models is the best model to predict the advance phase. The worst predictions were for Kinematic wave models with an average relative error equal to 33.21%. According to the results, the value of λ and for the Zero inertia model was 1.0912 and 98.76 respectively. The amount of error of field parameters such as; infiltration characteristic and hydraulic resistance are important for selection of model. So, for adjusting the amount of error in all models to predict an acceptable threshold tolerance was defined.
According to the results, Zero inertia and Kinematic wave models estimated advance time more than real condition. The results of the Zero inertia model were closer to measurement data than a Kinematic wave model. The maximum relative error was in discharge equal to 1.25 (l/s) in all models. With increasing the length of the furrow and input discharge the relative error of zero inertia models will be decreased. The results represented that in low discharge the infiltration depth was increased. Finally, it can be concluded thatthe zero inertia models are suitable for the study area and in study area, suitable length of the furrow is 100 (m).