Journal of Irrigation and Drainage Engineering

Circular overflow structures are used in irrigation and drainage networks as water measuring structures. Different approaches can be found in the literature to formulate the stage-discharge relationship of the circular weir. They are mainly categorized in three groups: (1) methods trying to simplify the complex elliptic integrals coming from the theoretical discharge equation; (2) methods that use the orifice formula and a discharge coefficient specific for the circular weir; and (3) approaches using dimensional analysis and Buckingham’s Theorem. In this study, a nondimensional stage-discharge formula was obtained using Buckingham’s Theorem to define the flow over the sharp-crested circular weir. Then the current available methods and experimental data from the literature were employed to calibrate the theoretically deduced stage-discharge relationship. The effect of the approach channel on the stage-discharge formula was also investigated using the experimental data available in the literature. Finally, the performances of different stage-discharge relationships are discussed and practical suggestions are provided.

The transient water-table recession in lands drained by parallel lines of ditches extending down to a horizontal floor was numerically modeled for sand and silty clay when the ditch-water level was dropped from an initial equilibrium level to zero. For initially surface-ponded conditions, numerical results agreed well with analytical recessions that assumed the water table behaved as a succession of momentarily steady states and the specific yield to be that for equilibrium soil-water profiles above the water table. They also agreed for sand, but agreed less for silty clay when the initial water table was at depth. The agreement found between the modeled and analytical results for this simple situation gives confidence in the use of similar analyses in modeling the water-table movement in drained lands subject to more complicated hydrological conditions.

This paper presents a matrix algebraic expression based on the probability of pressure deficit. A set of expressions to calculate the average and the variance of the aggregated head losses in any pathway of the irrigation network is proposed, and the probability law of the aggregated head losses is deduced. A methodology to design and manage on-demand branched irrigation networks based on the probability of pressure deficit is developed. The proposed methodology corrects some weak points detected in previous methods related to the probability of pressure deficit concerning certain sections with large head losses. The methodology is tested in two networks (one simulated and one real network belonging to the Canal de Estremera Irrigation District). The resulting data show the capability of the methodology to model the simulations. The results also show that when designing the network with the proposed methodology, the total cost of the project decreases and management of the network becomes more efficient compared with certain traditional methods for irrigation network design.

A test program consisting of two field-scale compacted clay liners (test pads) is conducted to evaluate field-obtained soil water characteristic curves (SWCCs) and hydraulic conductivity functions (k-functions). The test pads are instrumented with volumetric water content and soil water matric potential sensors. Each test pad is subjected to an infiltration cycle, using either a sealed double-ring infiltrometer or a two-stage borehole infiltrometer, followed by a drying cycle. To compare the results from the field-obtained SWCCs and k-functions, laboratory tests are performed on Shelby tube samples. A comparison of the results obtained from field-scale and laboratory techniques illustrates the evidence of hysteresis between the drying and wetting curves. The shapes of the field-obtained and laboratory-obtained SWCCs are similar, although at different volumetric water contents. There is poor agreement between field-obtained and laboratory-obtained k-functions, as reported in other studies; therefore field k-functions are preferential when available.

The scarcity of water resources throughout the world has caused many complexities in meeting water demands, which in turn has created a tendency toward developing more efficient and effective methods for optimum operation of reservoirs. In this study, the cat swarm optimization (CSO) algorithm is applied to determine optimal operation of reservoir systems (a single-reservoir system and a hypothetical four-reservoir system). Comparison with the commonly used genetic algorithm (GA) demonstrates the superiority of this metaheuristic algorithm. For the single-reservoir system, the global optimum of 1.213 was computed using the nonlinear programming method, whereas the average objective-function values for 10 runs of the CSO algorithm and GA were 1.222 and 1.635, respectively. The CSO algorithm scored a convergence rate of 99.58% compared with 78.76% by GA, and a coefficient of variation that was 1/31 that of the GA in 10 runs. In the four-reservoir system, the convergence rate of the CSO algorithm was 99.97% compared with 98.47% by GA, with average objective-function values of 307.76 and 303.59, respectively. The results for the mathematical test functions and operations of the reservoir systems demonstrated the superior performance and high efficiency of the CSO algorithm in finding the global optimization solutions.

Sprinkler irrigation is widely used in agricultural irrigation as an important component of conserving water. Traditional fixed-sprinkler irrigation systems interfere with farming operations. To address this shortcoming, a novel self-extending sprinkler irrigation device was developed that resides beneath the tillage layer during cultivation and harvesting. When pressurized water flows into the buried sprinkler, the sprinkler begins to rotate and release water at its ejection point. With the increase in moisture content, the soil shear strength is significantly reduced until it is effectively zero, resulting in the sprinkler rising above the ground surface for irrigation. The sprinkler can retract below the tillage layer under atmospheric pressure after irrigation, and no equipment remains exposed. No manual installation or removal of equipment is required during the sprinkler’s operation, which greatly reduces the labor associated with the current fixed-sprinkler irrigation systems. An analysis of the ground-breaking capacity and retraction capability of the novel sprinkler device revealed that it can rise above the ground surface for sprinkling and retract in most cases. The results of this demonstration project showed that the device is convenient to use, durable, and cost-effective for agricultural irrigation.

The present study documents the successful application of a Reynolds-averaged Navier-Stokes model with conventional turbulence closure to calculate discharge coefficients for submerged flow conditions at ogee-type weirs. The flow pattern downstream of submerged weirs is complex. At low submergence, there is a plunging jet and submerged hydraulic jump. At higher levels of submergence, the jet detaches from downstream of the crest and develops toward the free water surface. The results presented are of particular interest to the hydraulic engineer because they demonstrate that reliable results for the complex flow problem are achieved, but only with the use of a fine computational mesh. It is well known that the results of computational fluid dynamics (CFD) models are strongly mesh dependent, but extensive sensitivity analysis is often time-consuming and costly. Therefore, engineering practice relies on cases that have been tested extensively. For the mesh resolution, the present study recommends a nondimensional number that can be used as a reference for modeling flow over weirs. An important result for hydraulic engineering applications is that the minimum mesh resolution for submerged flows is completely different compared to nonsubmerged flows. The simulations are compared to physical experiments from the literature. With sufficient mesh resolution, an average relative error in capacity of 2% across the simulations is achieved for the finest mesh resolution compared to physical experiments.

The HSPF [Hydrologic Simulation Program—FORTRAN (Computer software). EPA National Exposure Research Laboratory, Athens, Georgia] and SWAT [Soil and Water Assessment Tool (Computer software). USDA Agricultural Research Service and Texas A&M AgriLife Research, Temple, Texas] models are often used to assess hydrological processes in a shallow water table setting. In the paper, these two models are evaluated and compared for accuracy in simulating runoff to the Peace River Basin in Central Florida, based on the generalized likelihood uncertainty estimation (GLUE) method. Both models performed reasonably well in predicting daily streamflow in three gauges with acceptable $R^2$ values (0.66–0.85) and Nash-Sutcliffe’s $Ens$ (0.60–0.76) with reasonable $P$ and $R$ factors. The parameter sensitivity was quantified, and the GLUE method involved Monte Carlo sampling over feasible spaces of calibration parameters. The parameter pairwise correlation is investigated, as well as the uncertainties along with equifinality. The results indicate that HSPF and SWAT models performed satisfactorily after the calibration and the parameters of both models are identified with considerable uncertainty.

A new formula is introduced to estimate solar radiation, $R_S$ ($\mathrm{MJ}/{\mathrm{m}}^2/\mathrm{d}$), using maximum and minimum air temperature, $T_{\max }$ (°C) and $T_{\min }$ (°C), respectively, as well as relative humidity, $RH$ (%). This technical note describes a modification to the original equation of the Hargreaves–Samani model. The new formula is obtained by calibration using data obtained from a global database. The new version of the formula is: $R_S\approx 0.338\times R_A\times {(T_{\max }-T_{\min })}^{0.3}\times {(1.001-RH/100)}^{0.2}$ where $R_A$ is the extraterrestrial radiation ($\mathrm{MJ}/{\mathrm{m}}^2/\mathrm{d}$). The proposed modification was tested under various climatic conditions using high-quality daily weather data from 32 stations across California, Florida, Arizona, and Greece, showing improvement of the accuracy of estimates of solar radiation. The proposed modification is not as generalized as the original Hargreaves–Samani equation that allows estimation of $Rs$ using widely available $T_{\max }$ and $T_{\min }$ data because it is restricted to locations where good quality $RH$ data is measured.