Eduardo Bautista

Understanding the spatial and temporal variations of infiltration in furrows is essential for the design and management of furrow irrigation systems. A key difficulty in quantifying the process is that infiltration depends on the depth of flow, which varies along a furrow and with time. An additional difficulty is that under many field conditions, a large fraction of the infiltrated water flows through cracks and/or macropores. This study examines the spatial and temporal variability of a furrow-irrigated field and evaluates a proposed semiphysical furrow infiltration model that accounts for flow-depth and macroporosity effects. Parameter estimation techniques were used to determine two parameters of the infiltration model, the hydraulic conductivity and the macroporosity term, in addition to the Manning roughness coefficient. The methodology was tested using published data from 30 furrow irrigation data sets collected in six furrows over five irrigation events. The evaluation revealed substantial variations in the final infiltrated volume among furrows and from one irrigation event to the next. Variability patterns differed markedly for infiltration measured during the advance phase in comparison with infiltration measured during the storage phase of the irrigations. Advance-phase infiltration varied systematically between irrigations for all furrows. Interfurrow inflow rate variability contributed to the variability of the infiltration during the postadvance phase, but not during the advance phase. Thus, cracks and/or macropores were an important contributor to the variability of infiltration during the advance phase. The analysis produced reasonable estimates of hydraulic conductivity relative to values reported in the literature. Hydraulic conductivity and post-advance infiltration volumes exhibited similar patterns of temporal variability. Hydraulic conductivity estimates were statistically correlated to the applied inflow rate. Although the reasons for this correlation are not clear, a possible explanation is that they are the result of systematic differences in the applied inflow rate among furrows. As with the advance-phase infiltration volumes, the estimated macroporosity term exhibited greater variation among irrigation events than among furrows during an event. The estimation procedure produced smaller differences between volume balance computed infiltration volumes and predicted values when using the semiphysical infiltration model than when using an empirical infiltration equation. Overall, the results show that the proposed furrow infiltration model represents the infiltration process adequately and that, at least for the studied data sets, the proposed estimation procedure yields a coherent set of infiltration and hydraulic resistance parameter values.

The study of spatial and temporal variations of infiltration in furrows is essential for the design and management of surface irrigation. A key difficulty in quantifying the process is that infiltration is dependent on the depth of flow, which varies along a furrow and with time. An additional difficulty is that under many field conditions, a large fraction of the infiltrated water flows through macropores. This study evaluates a proposed furrow infiltration model that accounts for both effects. Flow depth dependent infiltration is computed based on porous media flow theory. The macropore contribution is modeled as water that infiltrates instantaneously. Parameter estimation techniques were used to determine two of the model parameters, the hydraulic conductivity and the macroporosity term, and the Manning roughness coefficient. The methodology was tested using 30 furrow irrigation data sets collected in 6 furrows over 5 irrigation events. The analysis produced reasonable estimates for hydraulic conductivity relative to values reported in the literature. The estimated macroporosity term exhibited greater variation between irrigation events than between furrows during an event. Irrigation simulations were conducted with the estimated infiltration and roughness parameters. The observed irrigation measurements (advance, recession times, outflow rates, and flow depths) were simulated with reasonable accuracy for all events. Results show that the proposed furrow infiltration model can represent the infiltration process reasonably and that the proposed estimation procedure can yield consistent infiltration and hydraulic resistance parameters. Results also illustrate the large infiltration variability that can be encountered in furrow irrigated fields.

Infiltration in irrigated furrows depends on the variation of depth of flow and, thus, wetted perimeter along the field and in time. However, the magnitude of the wetted perimeter effect has not been clearly established due to soil variability, erosion and deposition, macropore flow, and other processes that affect the infiltration process. Hence, furrow irrigation models currently offer various alternatives, mostly empirical but some physical, for modeling the infiltration process as a function of wetted perimeter. In principle, the selected modeling approach can have a significant impact on the predicted performance. This is of particular importance for operation and design analyses cases in which performance is examined, respectively, over a wide range of inflow rates and physical configurations. A simulation study was conducted to examine the operational solutions that can be developed with different furrow infiltration models. The analysis was based on the modeling options offered by a softwa...

A methodology is proposed for estimating furrow infiltration under time-variable ponding depth. The methodology approximates the solution to the two-dimensional Richards equation, and is a modification of a procedure that was originally proposed for computing infiltration under constant ponding depth. Two computational approaches were developed and tested using several combinations of soil hydraulic properties, furrow geometry, and flow depth variations. Both methods yielded solutions of reasonable and similar accuracy relative to numerical solutions of the two-dimensional Richards equation. The analysis also showed that the accuracy of the approximate model varies mostly as a function of soil hydraulic properties. The accuracy of the approximate solution can be improved with calibration. Two calibration methods were examined, one assuming that the calibration parameter varies with depth, and the other assuming a constant value. The analysis showed that latter approach, in combination with one of ...

The SRFR program is a modeling system for surface irrigation. It is a central component of WinSRFR, a software package for the hydraulic analysis of surface irrigation systems. SRFR solves simplified versions of the equations of unsteady open channel flow coupled to a user-selected infiltration model. SRFR was reprogrammed using a modern object-oriented architecture with the objective of facilitating its continued development and, thus, the addition of new modeling options and functionalities. The upgraded software is SRFR 5. An important component of the modeling system is the code that manages computational incidents. While the computational methods used by SRFR 5 have been widely tested and are generally robust, calculations are prone to failures due to problems with the solution of the nonlinear finite difference system of equations, discretization problems, and problems with the determination of the appropriate boundary condition at each computational time step. Code that manages computationa...

This article discusses a methodology for estimating furrow infiltration derived from the two-dimensional Richards equation. The method was originally derived assuming a constant pressure head at the infiltrating surface. Application of the methodology to cases where the pressure head is variable with time is examined. The procedure was programmed into the WinSRFR surface irrigation software. Initial results show that the method provides a reasonably accurate reproduction of infiltration predicted with the two-dimensional Richards equation.

Volume-balance models of surface irrigation calculate the infiltrated volume at a given time as a product of the stream length, upstream infiltration, and shape factors. The best-known expression of this type was derived by combining the Lewis-Milne equation with empirical power-law expressions for infiltration and advance as functions of time. This expression results in systematic errors that are not well understood by users of volume-balance methods. This article examines those errors in furrow irrigation by comparison with infiltrated volumes computed with zero-inertia simulation. The potential for errors is greatest with light soils and where the bottom slope is large enough to produce kinematic flow conditions. An example is presented to show how these errors in a parameter-estimation problem based on a volume balance can be corrected iteratively with the help of zero-inertia simulation.

This article reviews procedures for estimating surface storage in surface irrigation volume balance calculations. Those procedures are based on the assumption of a power law relationship for flow depth as a function of distance along the stream. The analysis uses zero-inertia simulation and a system of dimensionless variables to examine how the depth profile varies as a function of hydraulic conditions when infiltration is given by the empirical extended Kostiakov equation. Alternatives for approximating the exponent of the depth profile power law (β ) are suggested. The magnitude of the resulting errors relative to zero-inertia model predictions is quantified. Results show that the range of variation for the parameter β increases with field slope, with increasing advance length relative to the maximum advance distance, and when infiltration rates are relatively constant with time during the irrigation event. Estimating β as a function of advance distance is most challenging under these condition...

WinSRFR is a software package for the hydraulic analysis of surface irrigation systems. The software can be used to conduct simulations, carry out design and operational analyses, and evaluate performance from field-measured data. Version 3.1 was released in 2009 and a new version, V. 4.1 is scheduled for 2012. This release provides a limited number of analytical enhancements for the end user, but it represents a major software upgrade. The simulation engine, known as SRFR, has been entirely rewritten using modern object-oriented programming concepts. This recoding effort was undertaken to facilitate the continued development of the SRFR code and to provide the application with a well-defined application programming interface. The paper discusses the architecture of the new SRFR engine and the resulting enhancements to the WinSRFR program.