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This paper presents a simple and quick method for estimating furrow infiltration using a single advance point based on the volume balance equation. The furrow infiltration and water front advance along the furrow are assumed to follow the modified Kostiakov infiltration and power advance equations, respectively. The volume balance equation, including these equations, is simplified to a function containing two parameters, i.e., the exponents of power advance and Kostiakov infiltration equation (with a prior-known basic infiltration rate). These parameters are estimated by minimizing the function to zero using a quasi-Newton search algorithm, provided with Excel Solver. The estimated exponents are used to determine the Kostiakov infiltration parameters. The proposed one-point method is tested with seven independent furrow irrigation evaluation data sets and the estimated cumulative infiltration is compared with the observed counterparts. Performance of the proposed method was evaluated using the root-mean-square error and index of agreement ([I.sub.a]). The results show that the proposed one-point method estimated cumulative infiltration is closer to the observed; the method performed as good as Valiantzas' method. Shepard's method did not perform well for the tested data sets. The algorithm and the results of the proposed method reveal that the proposed method can be used as a tool for quick estimation of furrow infiltration using a single advance point. DOI: 10.1061/(ASCE)0733-9437(2008)134:6(788) CE Database subject headings: Furrow irrigation; Infiltration; Simulation models.

Manning's roughness coefficient is one of the input parameters in many surface irrigation simulation models. It affects the velocity of flow and thereby its variation with time and distance along the field length influence water application. In this study, variation of Manning's roughness coefficient was studied for a furrow plot consisting of three 40 m long free drained furrows of parabolic shape and having a top width of 0.30 m, a depth of 0.15 m and a slope of 0.5%. The irrigation experiments were carried out with the inflow rates of 0.2, 0.3, 0.4, and 0.5 L [s.sup.1]; and 0.3, 0.4, 0.5, 0.6, and 0.7 L [s.sup.-1] under bare; and cropped field conditions, respectively. Furrow cross-section data were collected before each irrigation event at 0.5, 13, 26 and 39.5 m from the head end along the center furrow using a profilometer. During the irrigation event, water depth and velocity of flow were measured at these locations at an interval of 15 min using point gauge and color dye, respectively. The furrow cross-section data were fitted into a second-degree polynomial equation to determine the furrow shape parameters that were used along with the flow depth data for determining the wetted area and wetted perimeter. The wetted area, wetted perimeter, and the velocity data were used to estimate Manning's roughness coefficient spatially and temporally. It is found that for both bare and cropped field conditions, Manning's roughness coefficient was more at second and last quarter of the furrow due to soil erosion at these locations. Manning's roughness coefficient at these locations varied from 0.019 to 0.022 and 0.015 to 0.018 for bare field whereas from 0.02 to 0.024, and 0.019 to 0.022 for cropped field, respectively. The temporal variation of Manning's roughness coefficient for both bare and cropped furrow conditions decreased with the elapsed time. However, these decreasing trends were observed more for lower inflow rates. Further, the average Manning's roughness coefficient for the subsequent irrigations was varied from 0.018 to 0.02 and from 0.019 to 0.0245 for bare and cropped conditions, respectively. Thus, the values of Manning's roughness coefficients were more for cropped furrow conditions than for bare furrow. DOI: 10.1061/(ASCE)0733-9437(2008)134:2(185) CE Database subject headings: Furrow irrigation; Hydraulic roughness; Coefficient; Velocity; Simulation models; Parameters.

The article presents a discussion on a report that described an algorithm for estimating furrow infiltration. The authors proposed a global optimization technique to search for an optimal combination for which the solution is unique. The issues addressed by the discussers were the selection of power coefficients of infiltration and waterfront advance equations for obtaining a unique solution for infiltration estimation.