Journal of Irrigation and Drainage Engineering

Contour basin irrigation layouts are used to irrigate rice and other cereal crops on heavy cracking soils in Southeast Australia. In this study, a physically based two-dimensional simulation model that incorporates all the features of contour basin irrigation systems is developed. The model’s governing equations are based on a zero-inertia approximation to the two-dimensional shallow water equations of motion. The equations of motion are transformed into a single nonlinear advection–diffusion equation in which the friction force is described by Manning’s formula. The empirical Kostiakov equation and the quasi-analytical Parlange equation are used to model the infiltration process. The governing equations are solved by using a split-operator approach. The numerical procedure described here is capable of modeling rectangular basins; a procedure for irregular shaped basins is presented in Paper II. The model was validated against field data collected on commercial lasered contour layouts.

The development of a two-dimensional simulation model for single regular shape (rectangular) contour basin irrigation layout in southeast Australia is reported in a companion paper. Contour basin layouts as used in Southeast Australia are often irregular in shape and laid out as multiple basin systems. Irrigation of these basins is carried out sequentially involving back flow to the supply channel and inter-basin flow. This paper presents the extension of the earlier model to incorporate irregular shape basins and multiple basin operation. The governing equation is solved by adopting a “split-operator approach” using the method of characteristics coupled with two-dimensional Taylor series expansion for interpolation and calculation of diffusion terms. The numerical solution scheme is based on a grid of quadrilaterals for spatial discretization, to provide geometric flexibility. Infiltration is computed using either the empirical Kostiakov–Lewis equation or the quasianalytical Parlange equation. The model was validated against field data collected from irrigation events monitored on a commercial laser leveled contour layout consisting of five basins.

Field-based soil moisture measurements are cumbersome. Remote sensing techniques based on active or passive microwave data have limitations. This paper presents and validates a new method based on land surface energy balances using remotely sensed optical data (including thermal infrared), which allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. Root zone depth can be variable when crops are emerging. The pixel-wise “evaporative fraction” (ratio of latent heat flux to net available energy) is related to volumetric soil moisture through a standard regression curve that is independent of soil and vegetation type. Validation with measured root zone soil moisture in cropped soils in Mexico and Pakistan has a root mean square error of $0.05{\mathrm{cm}}^3 {\mathrm{cm}}^{-3};$ the error is less than $0.07{\mathrm{cm}}^3 {\mathrm{cm}}^{-3}$ in 90% of cases. Consequently, soil moisture data should be presented in class intervals of $0.05{\mathrm{cm}}^3 {\mathrm{cm}}^{-3}\text{.}$ The utility of this method is demonstrated at the field scale using multitemporal thematic mapper imagery for irrigated areas near Cortazar in Mexico, and for river basin-scale water resources distribution in Pakistan. The potential limitation is the presence of clouds and the time lag between consecutive images with field-scale resolution. With the falling price of optical satellite imagery, this technique should gain wider acceptance with river basin planners, watershed managers, and irrigation and drainage engineers.

Two equations for estimating grass reference evapotranspiration $\left({\mathrm{ET}}_0\right)$ were derived using the Food and Agriculture Organization Penman–Monteith (FAO56-PM) method as an index. The first equation, solar radiation $\left(R_s\right)$ based, estimates ${\mathrm{ET}}_0$ from incoming $R_s$ and maximum and minimum air temperature, and the second equation, net radiation $\left(R_n\right)$ based, uses $R_n$ and maximum and minimum air temperature. The equations were derived using 15 years (1980–1994) of daily ${\mathrm{ET}}_0$ values estimated from the FAO56-PM method using the measured and carefully screened weather data from near Gainesville, Florida. The performance of the derived equations was evaluated for 6 validation years (1995–2000), including dry and wet years, for the same site and for other humid locations in the Southeast United States. Comparisons of the performance of the derived equations with the other commonly used methods indicated that they estimate ${\mathrm{ET}}_0$ as good or better than those other ${\mathrm{ET}}_0$ methods. The $R_s$- and $R_n$-based equations resulted in the lowest 6 year average standard error of estimate (SEE) of daily ${\mathrm{ET}}_0$ (0.44 and 0.41 mm day⁻¹, respectively). Both equations performed quite well for estimating peak month ${\mathrm{ET}}_0$ and had the lowest 6 year average daily SEE for the peak month ${\mathrm{ET}}_0$ (0.24 mm day⁻¹ for both equations). Estimates for annual total ${\mathrm{ET}}_0$ were very close to those obtained from the FAO56-PM method. The 6 year average ratio of ${\mathrm{ET}}_{0 \mathrm{method}}$ to ${\mathrm{ET}}_{0 \mathrm{FAO}56-\mathrm{PM}}$ were 1.05 and 1.03 for the $R_s$- and $R_n$-based equations, respectively. The derived equations were further evaluated in other humid locations in the Southeast United States, including two locations in coastal regions in Florida, one location in Georgia, and another location in Alabama. The comparisons showed that both equations are likely to provide good estimates of ${\mathrm{ET}}_0$ in humid locations of the Southeast United States. When the required input variables are considered, the Priestley–Taylor (PT) method was the closest method to the second derived equation $(R_n$ based). Therefore, it was necessary to evaluate how the PT method would perform compared to the $R_n$-based equation relative to the FAO56-PM method after it is calibrated locally. Although the performance of the PT method improved slightly after the calibration, its performances for estimating daily and peak month ${\mathrm{ET}}_0$ remained poorer than the $R_n$-based equation in all cases. Considering the limitations associated with the availability and reliability of the climatological data, especially in developing countries, the derived equations presented in this study are suggested as practical methods for estimating ${\mathrm{ET}}_0$ if the standard FAO56-PM equation cannot be used because of the above-mentioned limitations. These equations are recommended over the other commonly used simplified temperature and radiation-based methods evaluated in this study for humid climates in the Southeast United States.

Adequate and reliable estimates of aquifer parameters are of utmost importance for proper management of vital groundwater resources. The pumping (aquifer) test is the standard technique for estimating various hydraulic properties of aquifer systems, viz., transmissivity (T), hydraulic conductivity (K), storage coefficient (S), and leakance (L), for which the graphical method is widely used. In the present study, the efficacy of the genetic algorithm (GA) optimization technique is assessed in estimating aquifer parameters from the time-drawdown pumping test data. Computer codes were developed to optimize various aquifer parameters under different hydrogeologic conditions by using the GA technique. Applicability, adequacy, and robustness of the developed codes were tested using 12 sets of the published and unpublished aquifer test data. The aquifer parameters were also estimated by the graphical method using AquiferTest software, and were compared with those obtained by the GA technique. The GA technique yielded significantly low values of the sum of square errors (SSE) for almost all the datasets under study. The results revealed that the GA technique is an efficient and reliable method for estimating various aquifer parameters, especially in the situation when the graphical matching is poor. Also, it was found that because of its inherent characteristics, GA avoids the subjectivity, long computation time and ill-posedness often associated with conventional optimization techniques. Furthermore, the performance evaluation of the developed GA-based computer codes showed that the fitness value (SSE) of the best point in a population reduces with increasing generation number and population size. The analysis of the sensitivity of the parameters during the performance of GA indicated that a unique set of aquifer parameters was obtained for all three aquifer systems. The GA-based computer programs with interactive windows developed in this study are user-friendly and can serve as a teaching and research tool, which could also be useful for practicing hydrologists and hydrogeologists.

Efficient use of natural water resources in agriculture is becoming an important issue in Florida because of the rapid depletion of freshwater resources due to the increasing trend of industrial development and population. Reliable and consistent estimates of evapotranspiration (ET) are a key element of managing water resources efficiently. Since the 1940s numerous grass- and alfalfa-reference evapotranspiration $({\mathrm{ET}}_o$ and ${\mathrm{ET}}_r\text{,}$ respectively) equations have been developed and used by researchers and decision makers, resulting in confusion as to which equation to select as the most accurate reference ET estimates. Twenty-one ${\mathrm{ET}}_o$ and ${\mathrm{ET}}_r$ methods were evaluated based on their daily performance in a humid climate. The Food and Agriculture Organization Penman-Monteith (FAO56-PM) equation was used as the basis for comparison for the other methods. Measured and carefully screened daily climate data during a 23-year period (1978–2000) were used for method performance analyses, in which the methods were ranked based on the standard error of estimate (SEE) on a daily basis. In addition, the performance of the four alfalfa-based ET $\left({\mathrm{ET}}_r\right)$ equations and the ratio of alfalfa ET to grass ET $(K_r$ values) were evaluated, which have not been studied before in Florida’s humid climatic conditions. The peak month ${\mathrm{ET}}_o$ estimates by each method were also evaluated. All methods produced significantly different ${\mathrm{ET}}_o$ estimates than the FAO56-PM method. The 1948 Penman method estimates were closest to the FAO56-PM method on a daily basis throughout the year, with the daily SEE averaging 0.11 mm⋅d⁻¹; thus this method was ranked the second best overall. Although 1963 Penman (with the original wind function) slightly overestimated ET, especially at high ${\mathrm{ET}}_o$ rates, it provided remarkably good estimates as well and ranked as the third best method, with a daily average SEE value of 0.14 mm⋅d⁻¹. Both methods produced peak month ${\mathrm{ET}}_o$ estimates closest to the FAO56-PM method among all methods evaluated, with daily peak month SEEs averaging 0.07 and 0.09 mm⋅d⁻¹, respectively. Significant variations were observed in terms of the performance of the various forms of Penman’s equations. For example, the original Penman-Monteith method produced the poorest ${\mathrm{ET}}_o$ estimates among the combination equations, with a daily SEE for all months and peak month averaging 0.50 and 0.35 mm⋅d⁻¹, respectively and ranked 11th. An average value of 1.18 was used to convert ${\mathrm{ET}}_r$ estimates to ${\mathrm{ET}}_o$ values for alfalfa-reference methods. The $K_r$ value of 1.18 resulted in reasonable estimates of ${\mathrm{ET}}_o$ throughout the year by the Kimberley forms of the Penman equations. Another ${\mathrm{ET}}_r$-based equation, Jensen-Haise, gave consistently poor estimates. The Stephens-Stewart radiation method was the highest-ranked (10th) noncombination method overall. The temperature-based McCloud method (ranked 19th) produced the poorest ${\mathrm{ET}}_o$ estimates among all methods with a daily SEE for all months and for the peak month averaging 1.93 and 1.22 mm⋅d⁻¹, respectively. In general, the results obtained from the temperature methods suggest that all of the temperature methods, with the possible exception of the Turc method, can only be applicable for these climatic conditions after they are calibrated or modified locally or regionally. The FAO and Christiansen pan evaporation methods (ranked 17th and 18th, respectively) produced poor ${\mathrm{ET}}_o$ estimates and had the largest amount of point scatter in daily ${\mathrm{ET}}_o$ estimates relative to the FAO56-PM ${\mathrm{ET}}_o\text{.}$ Both methods resulted in the highest daily SEE of 1.18 and 1.19 mm⋅d⁻¹ for all months, after the McCloud method (1.93 mm⋅d⁻¹), and with the highest SEE of 1.30 and 1.24 mm⋅d⁻¹ for the peak month of all methods evaluated. The FAO56-PM method uses solar radiation, wind speed, relative humidity, and minimum and maximum air temperature to estimate ${\mathrm{ET}}_o\text{.}$ It has been recommended that the FAO56-PM be used for estimating ${\mathrm{ET}}_o$ when all the necessary input parameters are available. However, all these input variables may not be available, or some of them may not be reliable for a given location if the FAO56-PM equation is used, and one may need to choose other temperature, radiation, or pan evaporation methods based on the availability of data for estimating ${\mathrm{ET}}_o\text{.}$ The results of this study can be used as a reference tool to provide practical information on which method to select based on the availability of data for reliable and consistent estimates of daily ${\mathrm{ET}}_o$ relative to the FAO56-PM method in a humid climate.

The average water surface slope in the lateral direction is taken into account as a local parameter ψ to study flow over a side weir. It was later shown that for smaller side weir lengths and side weir portions with no entrance and exit transition effects, ψ can be obtained from a numerical integral and also from the measurements of water surface elevations in the lateral direction. The effect of elemental weir length was further determined. Dividing the weir length into smaller computational segments has the effect of lowering the water surface to approach the measured profile, the downstream ends being coincident. The model was verified using experimental data.

The use of rotating spray plate sprinklers (RSPS) can reduce the water and energy requirements in pressurized irrigation systems. Installation of RSPS in continuous move irrigation machines, such as traveling trailers (nozzle booms), presents relevant advantages compared to sprinkler-gun machines. The aim of this study is to develop design criteria for continuous-move irrigation machines using the RSPS Nelson Rotator R 3000 D-4. Water distribution by this RSPS was evaluated in an indoor facility under the following experimental conditions: 6.1, 7.0, and 7.8 mm nozzle diameters; 1.0 and 1.5 m nozzle height above the ground; and working pressures of 100, 150, and 200 kPa. The water distribution patterns were overlapped at 3 and 4 m distances, the simulated Christiansen uniformity coefficient averaged 91.8%, and the simulated average precipitation rate under the different experimental conditions ranged between 23 and $57\mathrm{mm}\cdot h^{-1}\text{.}$ These values are acceptable for a wide range of irrigation-machine applications.