Journal of Irrigation and Drainage Engineering

The controllability of an irrigation canal depends on its physical characteristics, on the control algorithm used, and on the actual condition of the canal in relation to the algorithm tuning conditions. The flow conditions and controllability in an irrigation canal may change if the hydraulic friction changes. Great variations in friction were observed in an irrigation canal in Spain owing to the presence of Rhizoclonium hieroglyphicum, a type of algae that grows in clear water. Such large variations in friction may have a significant effect on the stability and performance of automatic canal controllers. Using the unsteady-state model Simulation of Irrigation Canal (SIC), the influence of roughness on the performance of the study canal under distant downstream control of its four coupled pools was investigated. A set of proportional-integral (PI) controllers was tuned for different values of Manning's $n$. The controller’s performance under real conditions is sensitive to the roughness conditions under which the control gains were tuned, and a method to robustly tune the gains of the PI controllers is proposed.

This study developed a one-dimensional numerical model for the simulation of unsteady flow and the resultant soil erosion in irrigation furrows. The model solves a modified version of the Saint-Venant equations that consider the loss of mass and momentum attributable to infiltration and sediment transport. The transport rate of fine sediment was predicted with a modified Laursen formula that treats the tractive shear stress as a function of both Reynolds number and the particle size. The modified Laursen formula was verified by using the erosion data measured in the field and in a laboratory flume. The model accurately predicted flow advance times and outflow hydrographs in comparison with data measured in irrigation furrows at Kimberly, Idaho. Sediment discharge predictions were less accurate.

Location-allocation algorithms allow for situating services in an efficient way in zones where the demand is dispersed across the area. In the present work, the minisum location-allocation algorithm is used to optimize the placement multioutlet hydrants, which are needed to supply irrigation to the region. The objective function aims to minimize the total access costs of the service. Because the total number of hydrants is the same as what currently exists the results can be compared with the presented solution. The proposed model reduces the total distance run to access the service, from 16,177 m to 13,560 m (16.17%), and the objective function (proportional to the cost) by 28.95%.

Throughout the American west, irrigated agriculture has been targeted to increase water-use efficiency because of increased urban demands. Soil-moisture sensors offer a method to achieve efficiency improvements, but have found limited use primarily because of high cost and lack of soil-specific calibration equations. In this paper, the Decagon EC-20 soil-moisture sensor (a low-cost capacitance sensor) has been examined and a unique laboratory-calibration method has been developed. Field-and laboratory-calibration equations were developed for six soil types (sand, sandy loam, silt loam, loam, clay loam, and clay) in the Middle Rio Grande Valley for alfalfa and grass hay fields. The average absolute error in volumetric water content for field calibration was $0.430{\mathrm{m}}^3/{\mathrm{m}}^3$, and $0.012{\mathrm{m}}^3/{\mathrm{m}}^3$ for the laboratory calibration. The factory-calibration equation for the EC-20 was also evaluated and found to yield an average absolute error of $0.049{\mathrm{m}}^3/{\mathrm{m}}^3$. In this study, it was found that the EC-20 is a reliable, cost-effective, and accurate sensor, and it is recommended that the laboratory-calibration method presented in this paper be used to obtain maximum accuracy. It is also recommended that the field calibration of the EC-20 soil-moisture sensor be foregone, as this type of calibration exhibits large error rates that are associated with colocation of samples, voids, organic residues, and root densities. Additionally, it was found that the field-calibration method was time-consuming, covered a small range of moisture content values, and was destructive to the area around installed sensors, which could lead to additional measurement errors.

One of the primary objectives for irrigation and drainage engineers, soil physicists, and hydrologists is to develop effective methods to estimate soil saturated hydraulic conductivity on the basis of readily available soil survey data. Although a few models have been derived from large ranges of soil texture data and successfully applied to many kinds of hydrologic analysis of agricultural lands and watershed for many years, there are few efforts to specifically investigate these models in soils with healthy grass growing. A field study was conducted to investigate and compare the performance of three readily applied models, including the Campbell model, Smettem and Bristow model, and Saxton et al. model, in Texas soils with established grass from September 2009 to May 2010. The results showed that two-parameter models, Campbell and Saxton et al. models, had better performance than the one-parameter model, Smettem and Bristow model. All three models need to be calibrated with local knowledge and data for improved accuracy if they are applied in Texas grassed soils, or even some new methods or models need to be developed with acceptable accuracy and the same simplicity level as these investigated models.

The nonlinear advection-diffusion equation, also known as Richard’s equation, is one of the most famous equations expressing water content in unsaturated porous media with broad applications in hydrology, engineering, and soil sciences. Because of the inherent nonlinearity in the equation, its closed-form analytical solution is rare. The traveling wave solution (TWS) is one of the recent exact approaches used in solving nonlinear partial differential equations (PDEs) and seems to be a suitable and efficient approach to obtain analytical solutions for Richard's equation. This paper presents three major cases of Richard’s equation that are tackled with the TWS method using general and modified forms of $\tanh$ function scheme to obtain the exact solution for each equation. The typical forms of diffusivity and conductivity functions proposed by Brooks and Corey are considered, and the exact solution for Richard’s equation is presented. Solutions have a broad applicability in pertinent engineering and soil science problems. As with any other analytical solution, few unknown parameters are included in the solutions that must be determined according to boundary and initial conditions.

The current engineering design of the highway drainage layer is typically based on the groundwater table elevation predicted by saturated flow models. Capillary effects may become significant, with unsaturated flow playing an important role in conducting water out of the drainage layer. With the capillarity neglected, saturated flow models such as the Boussinesq equation-based model (BM) and the Laplace equation-based model (LM) over predict the groundwater table elevation. This paper aims to modify the traditional BM to account for the capillary effects on the drainage. A correction term was added to the BM to incorporate predominantly horizontal flow in the unsaturated zone above the water-table, with vertical flow neglected. Analytical solutions to the governing equation were developed for both flat and sloping drainage layers. The modified model and analytical solutions were validated against predictions of a Richards equation-based model (RM) that simulated the variably saturated flow directly. The results showed that the assumption of negligible vertical flow made in the modified Boussinesq equation model (MBM) was sound. With capillary effects incorporated, this model predicted well the behavior of the water-table as simulated by the RM with relative errors typically less than 2% for the base case considered. The improvement made through the capillarity correction will enable the MBM to be used for analyzing and predicting the groundwater table in the design of the highway drainage layer.

Estimation of daily pan evaporation values is of most importance in water resource system management and planning. This paper presents a study aimed at developing generalized neurofuzzy (GNF)–based evaporation models corresponding to Penman, Stephens-Stewart (SS), and Griffiths methods. A GNF model was also made by using temperature as the sole input parameter to evaluate the application of single-input temperature-based models for estimating the evaporation values. In the first part of the study, neurofuzzy (NF) evaporation models were developed and compared with Penman, SS, and Griffiths models for three weather stations located in Arizona, USA. Five-parameter NF models were generally found to be better than the Penman, SS, and Griffiths models. The NF models were used for estimating evaporations at the Tucson station by using the data from the Phoenix and Flagstaff stations in the second part of the study. It was found that NF models can be successfully used in cross-station applications. In the third part of the study, the GNF models were obtained by calibrating and using the pooled data from the Phoenix, Flagstaff, and Tucson stations located in Arizona and were tested using the data from weather stations in Albuquerque, NM; Tucumcari, NM; Cedar City, UT; and Ahwaz, Iran). Generalized SS and Griffiths models were also obtained and compared with GNF models. The comparison of the results revealed that the GNF models performed better than the Penman generalized SS, and Griffiths models. However, the generalized SS and Penman models were found to be better than the GNF model for the Ahwaz station.

Salinity ranks high among the list of parameters which demand attention during the planning and management of water quality, particularly for drinking and irrigation. If water quality is adequately predicted, then the proper management is possible within the time. Looking into this importance, in the present study, an artificial neural network (ANN) model was developed to predict the total dissolved solids (TDS) as water quality indicator for the water quality management. Two ANN networks viz, multilayer perceptron (MLP) and recurrent neural network (RNN), which are further referred as the Elman network were developed and applied to the Talkheh Rud River. Comparing the results of the TDS at two monitoring stations, it was observed that the Elman network predicts the TDS very close to the observed values (R = 0.9639). Possession of 1 month’s worth of TDS data beforehand may be helpful for the water quality management decision-making process.

A detention basin is designed for storm-water quantity and quality controls. An in-stream basin is often located on a widened floodplain, whereas an off-stream basin can be part of open space in a parking lot, park, or sport field. The inflow channel associated with an off-stream basin is allowed to carry its base flow not to exceed the downstream capacity. When the inflow channel is full, the excess flood water is diverted into the off-stream basin through the side weir. During the flood recession, the equalizer conduit drains the basin flow back to the channel. In this study, the rational volumetric method was expanded from in-stream to off-stream detention design. The required off-stream detention volume is maximized by the rainfall event longer than the time of concentration of the tributary area. In comparison, the off-stream detention volume can be significantly less than an in-stream, depending on the flow-through capacity in the downstream channel. This paper presents a design procedure to maximize the off-stream detention volume, to size the flow-diversion weir, and to set the floodgate operation on the equalizer conduit. The simplified derivation on the turning moment indicates that the operation of a floodgate is dictated by the water depth differential and the weight of the gate.

Fully saturated, 2-D steady seepage in a homogeneous, isotropic, parallelogrammic ramp is studied using the methods of complex analysis (a conformal mapping and integral representation of mixed boundary-value problem). A porous medium flow is induced by an overland free-surface flow with the latter determining the “shearing” pressure (hydraulic head) of the former through a boundary condition along one side of the polygon serving as a conjugation line. For a uniform overland flow, the stream function along the conjugation line has a single maximum corresponding to the Toth hinge line. The inflow rate into the ramp is divided into a part exfiltrating through the toe and through a toe-adjacent segment of the conjugation boundary. A wavy free surface is shown to generate a more complex seepage topology.

A hydraulic jump is the turbulent transition from a high velocity into a slower flow. A related process is the hydraulic jump in translation. The application of the equations of conservation of mass and momentum in their integral form yields a series of relationships between the flow properties in front of and behind the jump. The effects of the cross-sectional shape and bed friction are investigated. The effect of the flow resistance yields a smaller ratio of conjugate cross-section areas for a given Froude number. The solutions are tested with some field measurements of tidal bores in natural channels, illustrating the range of cross-sectional properties in natural systems and irregular channels.