Journal of Irrigation and Drainage Engineering

In this study, a hydrodynamic model is presented for simulating basin irrigation. An explicit, second-order-accurate finite-volume technique is used for solving the two-dimensional governing equations of basin irrigation. The empirical Kostiakov-Lewis infiltration equation is used for the calculation of infiltration. The model is validated using field data and numerical results available in the literature. The proposed model was used for simulating a basin irrigation event in an irregular field with a high spot inside the computational domain. The resulting numerical error was smaller than that produced by previous models applied to the solution of this problem. The proposed model was also used for studying the effect of basin shape on the time of advance and to check the validity of one-dimensional flow assumption when the inflow to the field is provided only through a part of the edge. In the case of a rectangular field with a partial line inflow, the two-dimensionality effects become significant when the ratio of inflow width to the field width is less than a particular value. A simple subgrid technique was introduced to obtain a high grid resolution near the advancing front and maintain a low computational cost.

Assessment of the surface storage is of great importance in hydrological surface irrigation. For the Horton infiltration law used in the ALIVE model (Advanced LInear VElocity), an accurate measurement of surface storage is the key to successfully predicting infiltration. For the Kostiakov function, the conclusion is paradoxical due to the fact that this law systematically underpredicts infiltration for times greater than the time used for fitting. Measuring surface storage accurately is cumbersome, and, consequently, most of the models use empirical formulas, which are reasonable, if not always precise. The constant mean cross-section assumption that is implied in hydrological models is discussed from a practical point of view. A representation of nonuniform storage distribution is presented through the ALIVE approach, and the feasibility of an inverse solution is discussed. Finally, field records and numerical tests indicate that if the variation of the cross-section remains low (less than half or double the mean) and is randomly distributed the constant mean cross-section assumption is acceptable. With large variations in the flow cross section, the error is lumped with variation in infiltration characteristics. Low variations that are not randomly distributed can affect the infiltration evaluation process. Models using the Kostiakov function are much more sensitive to this phenomenon than the ALIVE model, which uses the Horton law. The reason is likely that the ALIVE model is based on the analysis of the advance rate as a function of distance x′(x) rather than advance time at given location t_a(x).

It is essential to standardize the definitions and approaches to quantifying various irrigation performance measures. The ASCE Task Committee on Defining Irrigation Efficiency and Uniformity provides a comprehensive examination of various performance indices such as irrigation efficiency, application efficiency, irrigation sagacity, distribution uniformity, and others. Consistency is provided among different irrigation methods and different scales. Clarification of common points of confusion is provided, and methods are proposed whereby the accuracy of numerical values of the performance indicators can be assessed. This issue has two companion papers that provide more detailed information on statistical distribution uniformity and the accuracy of irrigation efficiency estimates.

Evaluation of actual irrigation system performance should rely on an accurate hydrologic water balance over the area considered. In a companion paper, water uses are categorized as consumptive or nonconsumptive, and beneficial or nonbeneficial. Real performance is based on water uses over a specified period of time, rather than observation of a single irrigation event (with associate potential, but not yet actual, consumptive and/or beneficial uses). Once the components in the water balance have been determined, it is shown that the accuracy of irrigation performance parameters can be determined from the accuracy of the components in the water balance, using standard statistical procedures. Accuracy is expressed in terms of confidence intervals. Equations, procedures, and examples are provided for making these calculations. It is recommended that confidence intervals be included in all reporting of irrigation system performance parameters.

For most irrigation systems, the most practical method for determining the global distribution uniformity (i.e., that experienced by the entire crop) is to measure the uniformity resulting from several components and combine them statistically. In this paper, procedures and equations are presented for determining global distribution uniformity from several components. Distribution uniformity is defined in terms of extreme values in the distribution, representing some fraction of the field area (e.g., low quarter). The equations and procedures provided herein apply regardless of the size of the area under consideration (e.g., low quarter, low half, etc.), and whether the low or high values are of concern. Procedures and equations for estimating the accuracy of these estimates are also provided.