Journal of Irrigation and Drainage Engineering

This paper presents furrow and border irrigation design optimization models for corn. The models, which have nonlinear objective functions and constraints, are linearized to take advantage of existing linear programming codes that perform sensitivity analysis and can be run in microcomputers. The models give the optimal values of the design variables (inflow discharge, length of the run, time of irrigation cutoff, and width of border for border irrigation). Field data are used to obtain solutions to the models. Results indicate that time of irrigation cutoff is the most critical design variable. Water supply and time available for irrigation are important factors to be considered in the design process.

For flow through a transverse rectangular slot located in an open channel floor, the slot width and the characteristics of flow in the approach channel are the important parameters that determine the slot discharge. To determine the relationship that governs the slot discharge, an existing model of the lateral efflux from a two‐dimensional channel is used as the basis. Experimental results are presented to validate the proposed relationship.

Capillary pressure‐saturation data were measured on unconsolidated porous media containing 40% montmorillonite, as a function of total electrolyte concentration and sodium adsorption ratio (SAR) of the wetting fluid. Data were also obtained with a nonpolar wetting fluid. The Su‐Brooks retention function was fit to the experimental data; the average $R^2$ for all treatments was 0.9967. The liquid retention curves were scaled to account for differences in properties of the wetting fluids. The change in scaled liquid retention curves due to changes in solution concentration and SAR followed a pattern reported by earlier investigators, except at high solution concentrations. There were significant clay‐solution interactions affecting retention of solution at high electrolyte concentrations. Previous researchers assumed that at high solution concentrations clays did not swell sufficiently to affect hydraulic properties.

Hydraulic roughness coefficients have been derived from runoff plot data originally collected for erosion studies. The data were collected from different agricultural and natural surfaces by applying constant rainfall rates from rainfall simulators. The derived roughness coefficient is actually an “effective” roughness coefficient that includes: the effect of raindrop impact; the effect of channelization of flow; the effects of obstacles such as litter, crop ridges, rocks, and roughness from tillage; the frictional drag over the surface; and the erosion and transport of sediment. A ready reference of friction factors for overland flow is presented in tabular format with a description of the various surfaces and land uses. Surface conditions varied from very smooth asphalt to extremely rough, litter‐strewn agricultural and rangeland areas.

Subsurface drainage systems installed in soil overlying artesian aquifers should be spaced to handle both upward artesian water flow and normal downward seepage flow from irrigation and rainfall. Proper drain spacing depends on several parameters, while a narrower than normal spacing is required for drains subject to artesian conditions. The hydraulic conductivity of the soil above an artesian aquifer determines the ease with which water flows to the drains and the magnitude of the upward artesian water flux for a given piezometric head and soil layer thickness. Since water movement to subsurface drains depends on both the horizontal and vertical components of hydraulic conductivity, anisotropy of the soil affects the drain spacing. For most soil formations, the hydraulic conductivity in the horizontal direction exceeds that in the vertical direction. Neglecting anisotropy may lead to under‐design of the drainage system for a formation above an impermeable layer and can lead to over‐design of a drain system for a formation subject to artesian conditions with no downward flow. For a soil subject to upward flow as well as downward flow, anisotropy effects depend on the magnitude of the different parameters influencing the problem.

The objective of this paper is to study the stochastic structure of weekly irrigation requirement of a crop. The irrigation requirement time series is assumed to be represented by an additive model with trend, periodic and stochastic as its components. Each component is identified and, if found, removed from the original series. The turning point test and Kendall's rank correlation test are applied for detecting the trend. In the analysis of series, the correlogram technique is used to detect the periodicity, which is then analyzed by Fourier series method. Harmonic analysis is done for identifying the number of significant harmonics. The series is then tested for stationarity and the dependent part of the stochastic component is found to be well expressed by the second order autoregressive model. Therefore, as a result, the developed model superposes a periodic‐deterministic process and a stochastic component. The adequacy of fit is judged by the insignificant correlation and normal distribution of the obtained residuals. The developed periodic‐stochastic model may be used for representing the time based structure of the irrigation requirement time series of a paddy crop.