Journal of Irrigation and Drainage Engineering

This paper develops a nonlinear optimization model for the determination of optimal cropping patterns in irrigated agriculture. Decision variables are the cultivated area in each soil type at the farm. The objective function of the model is based on crop-water production functions, irrigation technology used, and costs and prices of the products. The model is solved using the GAMS-MINOS package for conditions existing in Chile. The model gives the optimal distribution of areas and crops, irrigation water needs, labor requirements, and total profit. Sensitivity of the optimal solution to land, labor, and water resources is examined. Results of the model show that changes in the prices of exportable products and water cost have a large impact on the cropping patterns and profit. Water availability affects the distribution and area of crops, whereas labor availability is more important for the agricultural enterprise than its wages.

Infiltration rates of soils are spatially and temporally variable, which complicates surface irrigation management. The variability is magnified when water supplies are limited because crops in some portions of the field are intentionally stressed. Soil water content and soil cracking effects need to be considered to better model deficit irrigation with surface systems. A two-dimensional (2D) infiltration model that incorporates the effects of surface sealing, soil cracking, and initial soil water content was developed. The model was compared with a finite difference solution of the Richards equation for vertical infiltration for two surface seal conditions. To further test the model, simulated data were compared with field experiments. Including infiltration through cracks provided a better agreement between observed and simulated data than when cracks were ignored. Simulations showed that the majority of the infiltration through cracks took place during the first few minutes of infiltration. In the future the infiltration model will be combined with other models to simulate deficit irrigation management for surface irrigation systems.

Overland flow erosion has a significant role in determining the drainage properties of a land surface. Most physically based models of soil erosion over hillslopes use a constant value of critical shear stress τ_cr and soil erodibility C_t. The amount of soil loss predicted from hillslopes is very sensitive to these parameters. However, point-scale (or local-scale) measurements of these quantities exhibit variability over hillslopes. This paper presents a method for upscaling these values based on the distributions of τ_cr and C_t. Examples are considered for transient, one-dimensional flow under single storm events to demonstrate the spatiotemporal variation of the field-scale values of τ_cr and C_t for some realistic cases. These examples reinforced the need to account for spatial variability of parameters to make realistic predictions of soil loss through erosion by overland flow. The influence of spatial trend in the mean behavior of the critical shear stresses and soil erodibilities also is shown to have a significant impact on soil erosion from a hillslope.

Simulation models are becoming valuable tools for design and management of furrow irrigation systems. The Manning equation is used often for describing overland flow in these models. The past studies suggest that the Manning equation is not suitable for describing the flow in border irrigation because the value of Manning's n varies with the depth of flow. In this study we examine the suitability of the Manning and other four similar flow equations for flow in furrow irrigation and evaluate how Manning's n varies spatially, temporally, and with flow rate in the furrow. Field tests were monitored for a range of flow rates and two furrow slopes. The Manning and the other equations fitted data satisfactorily. The value of the Manning's n varied slightly with the variation in flow rate at low flow range, but it became fairly constant with changes in flow rate at high flow range. The Manning equation is considered the best for modeling the overland flow in furrow irrigation among the equations examined in the study because the Manning equation requires only one parameter to be estimated, whereas in the other equations up to four parameters should be estimated.

A theoretical submerged flow equation for chimney weir is developed. Based on experiments conducted with five different chimney weirs, it is found that the theoretical submerged flow equation, along with a parabolic equation relating the coefficient of discharge and the ratio of upstream head to crest height, predicts the discharge accurately. The performance of the developed equation is compared with the previously developed submergence formulas for sharp-crested weirs, and it is seen that the developed equation performs better within the experimental range. Further, for simplicity, an empirical equation is also proposed, which is found to give reasonable prediction of submerged discharge.

This paper addresses the problem of draining a heavy soil of low hydraulic conductivity overlying an impermeable layer by means of a combined system of pipe and mole drains. The analysis uses the complex functions and the theory of images to develop formulas for pipe and mole drain discharges and for pipe drain spacing design. A flow pattern predicted on the basis of these formulas shows that boundary conditions are satisfied and the stream line distribution is logical. An equation for the unsteady vertical movement of the water table is presented, from which an approximate but satisfactory spacing equation is established. A numerical example is provided and it is shown that although the spacing formula is implicit, only a small number of trials are needed. It is also shown that introducing mole drains may allow the spacing of pipe drains to be increased several times. A technique is proposed for choosing the number of mole drains between two pipe drains such that the optimal spacing design is achieved.

Current methods of computing regional crop evapotranspiration (ET), the prime variable in estimating irrigation demand, largely ignore the spatial and temporal variability of ET parameters, thus introducing errors. In this research, a methodology was developed to estimate regional ET while considering the spatial and temporal variability of parameters. To consider this variability, spatial databases were developed for agricultural land-use, relevant climatic parameters, and topographic data using geographic information systems (GIS). The Cache la Poudre Basin was selected as the study area due to the availability of field verified land-use survey data. A spatial simulation ET model (GISETMA) was used to develop a baseline estimation of regional ET, incorporating analytical GIS functions of map algebra and map overlay to calculate ET for each field in the system and for each day of the growing season. Various scenarios were developed and compared to the baseline scenario to explore spatial and temporal errors from point estimate of climate data and weather station use, daily versus monthly time-steps, and land-use classification.

A two-year field study was conducted in eastern Ontario to evaluate the effects of water table management on the quality of subsurface drain flows. Drainage discharge volumes and ${\mathrm{NO}}_3^{-}-N$ concentrations in drainage effluent were monitored during the growing seasons. The 3.5 ha experimental field was strip-cropped with corn (Zea mays L.) and soybean (Glycine max Merr.). Controlled-drainage subirrigation was used to manage water from precipitation and subirrigation. The two controlled water table treatments were 50 cm and 75 cm from the surface. There was also a conventional free-drainage treatment (FD). In 1995, mean ${\mathrm{NO}}_3^{-}-N$ concentrations in drainage water were reduced by 84% and 75% by the 50 and 75 cm controlled water table depths, respectively. In 1996, drain flow volumes and ${\mathrm{NO}}_3^{-}-N$ concentrations were significantly reduced relative to free drainage. Total drain flow was reduced by 42% by the 50 cm controlled water table, while ${\mathrm{NO}}_3^{-}-N$ concentrations were reduced by 61% and 52% by the 50 cm and 75 cm controlled water tables, respectively. Consequently, ${\mathrm{NO}}_3^{-}-N$ loadings were also reduced by 94% and 30% by the 50 cm and 75 cm controlled water tables, respectively. Improvements in drainage water quality were attributed to both reduced drainage outflow and enhanced denitrification in the controlled water table plots. In addition to significantly reducing ${\mathrm{NO}}_3^{-}-N$ pollution, economic benefits were achieved through fertilizer equivalent savings, and enhanced crop yields were achieved through subirrigation. Therefore, the practice of water table management in the region was demonstrated to be both environmentally and economically sustainable.

In regions where irrigation water supply is less than the required amount, extensive but deficit irrigation becomes unavoidable, unless the irrigated area can be limited to ensure full supply. When reliable dated crop-water response (DCWR) functions are available, a scientific planning of deficit irrigation schedules can be undertaken. This paper presents the formulation of a nonlinear programming (NLP) problem for identifying optimal cropping pattern as well as optimal deficit irrigation schedule along with its application to a minor irrigation system. The model indicates, for the case studied, that an increase in the cropped area by approximately 50 is possible over that underintensive irrigation approach. In terms of the net monetary return from the system, it means an increase of approximately 20. The adoption of extensive irrigation policy in such a setting is seen to be desirable.

The Kostiakov infiltration equation relates cumulative water infiltrated to the infiltration opportunity time. The kinematic wave model can be used to simulate surface irrigation system performance. Input to the kinematic wave model includes a description of infiltration with respect to time. If all the inputs to the kinematic wave model other than the infiltration characteristics are observed, the model may be used iteratively to estimate the infiltration characteristics based on coincidence between observed and predicted advance and runoff data. An example of this procedure using field data is shown. The results for this single example demonstrate that a wide range of infiltration parameters can lead to acceptable coincidence between the observed and predicted advance trajectory and outflow hydrograph. Fitting the advance trajectory and the outflow hydrograph simultaneously can result in a smaller solution space than fitting either singularly. For the example data set, small errors in inflow rate, surface roughness, or field slope had substantial effects on the infiltration parameters.