Journal of Irrigation and Drainage Engineering

A method was developed for the design of microirrigation laterals based on the required average emitter discharge and the required uniformity of water application. The finite-element method was used to analyze the hydraulics of a lateral. The golden section search was employed to find the operating pressure head of the lateral that can produce the required average emitter discharge along the lateral. Analytical results show that the lateral length for the required uniformity of water application may have three solutions and the diameter may have two solutions when laterals are laid on sloped fields. The design procedure was implemented. When the required average emitter discharge, the required uniformity of water application, one parameter—either the lateral length or diameter, and other conditions are given, then the unknown parameter, the best submain position (paired laterals), and the operating pressure head can be accurately obtained using personal computers. A flowchart of the computer program for design of the length of paired laterals is included.

A method was developed for designing microirrigation submain units. The lateral discharge equation was used to express the relationship between the discharge and pressure head at the inlet of a lateral to allow a submain unit to be considered as a lateral and a lateral as an emitter. The finite-element method was employed to analyze the pressure head and discharge distributions along laterals and submain. The golden section search was applied to find the operating pressure heads of the lateral and submain corresponding to the required average emitter discharge. When the required average emitter discharge, the required uniformity of water application, one parameter—either the lateral length or diameter, one parameter—either the submain length or diameter, and the field conditions are given, then the unknown parameters, the best submain position (paired laterals), and the operating pressure head of the submain unit can be accurately designed using a personal computer.

The purpose of this study was to investigate the reliability of combining a surface irrigation model (SRFR) and two functional solute transport models (RAO and TETrans) in predicting the position of bromide (Br ⁻ ) measured in a 0.81-ha field under furrow irrigation. The SRFR model was used to first predict the infiltrated depths and then RAO and TETrans models were used to predict the position of the solute. Solute was transported according to piston flow theory for the first irrigation and both models predicted the position of the solute with good accuracy. The solute was transported slightly faster than estimated by piston flow for the second irrigation, resulting in a reduction of correct predictions by both models. Both models predicted poorly for the third irrigation because deviations from piston flow were large. RAO model was more successful in predicting the peak solute position, while TETrans was more accurate in predicting mean solute depths. The latter was attributed to the differences between the two models and the sensitivity of TETrans to nodal spacing when predicting peak solute position.

Procedures and guidelines are recommended for assessing integrity, quality, and reasonableness of measured weather data and equipment calibration for automated and electronic agricultural weather stations. The procedures include calculation of hourly and 24-h clear sky envelopes for solar radiation, validation of net radiation measurements using calculation equations, and evaluation of expected trends and relationships between air vapor content and air temperature. The procedures for creating clear sky solar radiation envelopes include equations to account for the effects of atmospheric water vapor content and sun angle. Procedures for adjusting air temperature and air vapor content data are introduced to compensate for the aridity of the weather station environment. All of the guidelines are simple and straightforward, and can serve as preliminary “filters” by which to scrutinize weather measurements and as near real-time data flagging procedures for agricultural weather networks.

Simple calendars are described that express best dates of irrigation based on long-term weather data. The calendars are intended to promote easy and ready adaption of improved water management practices by farmers in both developed and developing countries by presenting simplified, nontechnical scheduling guidance. The calendars are developed using a daily soil-water balance-crop yield model. Once developed, the calendars require no updating and no further input by technical personnel. Calendars are developed for several planting dates, soil types and initial water contents. Developed calendars graphically show recommended irrigation occurrences expressed in days or weeks after sowing that correspond with the type of irrigation water delivery schedule utilized. The calendars are generalized as much as possible to promote widespread public usability. The graphical nature of the calendars encourages use by illiterate or semiliterate farmers. The methodology demonstrated is transferable to any site where sufficient weather data are available.

Manually determining drainage patterns from topographical maps for a grid-based model is time consuming and occasionally subjective. Eight methods including neural network are developed in this study to automatically determine the pattern from Digital Elevation Model (DEM) data. These methods are tested for a subwatershed located on Chin-Mei Creek, Taipei County, Taiwan, R.O.C. Results obtained using the neural network method are superior to those obtained using the drainage network method, which has performed the best among the other seven methods excluding the neural network method. The neural network method has a self-learning capability that could likely replace human assessment involved in the conventional approach. The implementation of the drainage network and neural network methods is described. Performances of the two methods are compared on the basis of their differences from the manually determined result.

Rational evaluation of surface irrigation systems should consider the effects of spatial variations in soil intake properties on advance trajectories and on the uniformity of infiltrated depths. The objective was to quantify the effects of spatial variations in infiltration parameters on the variability of advance trajectories and on infiltration depths. The soil properties were expressed as random space functions, and small perturbation analysis was applied to analytical solutions for the advance phase. This resulted in closed-form expressions relating the variability in soil properties to the variability in advance trajectories. The expressions were tested using Monte Carlo (MC) simulations. The results show good agreement between the analytical expressions and the simulated mean and variance of advance trajectories for a wide range of intake variabilities. In all cases, a sharp increase in the variance of advance times was observed toward the end of the field. This resulted in discrepancies between the simulated and the closed-form approximation for infiltration depths at large distances from the field inlet. The study provides a predictive tool for the evaluation of management strategies for surface irrigation in heterogeneous fields once the extent of spatial variability in soil intake properties has been estimated. Some applications for the estimation of uniformity and application efficiency are illustrated.