Journal of Irrigation and Drainage Engineering

Irrigated agriculture faces serious threats of waterlogging and soil salinization in the arid and semiarid regions of the world. In this paper, an integrated spatial-agro-hydro-salinity model (SAHYSMOD) was used to analyze water and salt balances of an irrigated semiarid area located in the Haryana State of India where the groundwater level is rising continuously. The calibration, validation, error analysis, and sensitivity analysis of the model parameters were performed. The sensitivity analysis revealed that hydraulic conductivity is the most sensitive model parameter for both groundwater levels and salinities, followed by effective porosity of the aquifer. The leaching efficiency of the soil is sensitive only to the groundwater salinities. The results show a good agreement between the simulated and observed groundwater levels and salinities for almost all the nodes during the calibration and validation periods. The results are also substantiated by the high R-squared values and low mean error (ME) and root mean square error (RMSE) values. On the basis of the results, it could be concluded that the SAHYSMOD performed very well in predicting groundwater levels and salinities during the calibration and validation periods.

Waterlogging and soil salinization are the twin menaces of canal-irrigated areas located in arid and semi-arid regions of the world. An integrated spatial agro-hydro-salinity model, SAHYSMOD, was applied to analyze water and salt balances of an irrigated semi-arid area located in Haryana, India, where the groundwater level is rising continuously. The model was validated with the observed groundwater level and salinity data. The impact of various water management scenarios on the groundwater levels has been analyzed through the model. The study revealed that, on average, the water table is rising under the existing conditions, although at a slow rate. To prevent the area from further salinization, some recommendations have been made: change the cropping pattern with reduced rice area; increase the groundwater abstraction, and line the surface irrigation systems. It was concluded from the analysis of various scenarios that simultaneously implementing multiple approaches is more effective in controlling waterlogging problems than individual interventions.

Rain sensors are devices that connect to automatic irrigation systems to interrupt scheduled irrigation events as a result of rainfall. The objectives of this study were to evaluate the dry-out time of expanding-disk rain sensors and determine potential irrigation savings under several virtual irrigation schedules. Five rain sensor model/rainfall set point combinations were evaluated at a research site in north central Florida. The five configurations that were compared were Mini-Clik rain sensors with set points of 3, 6, and 13 mm (3MC, 6MC, and 13MC), the Wireless Rain-Clik (WL) rain sensor, and Toro rain sensor at 6 mm setting (6T). The evaluation period ranged from 1,150 days to 1,182 days across the various devices. For each configuration, data for each time a rain sensor switched between allow irrigation to interrupt irrigation modes were collected and compared with how long each stayed in interrupt mode and how much irrigation water a rain sensor could save. Changing the dry-out vents from fully open to fully closed increased the dry-out time by 14% (3 h) but had no influence on irrigation savings. The hygroscopic disks significantly dry out 2 or 3 h after decreasing relative humidity and increasing temperature and solar radiation. Frequent irrigations such as 3 days/week or higher schedules had more potential savings than less frequent schedules. Savings for the WL, 3MC, 6MC, 13MC, and 6T treatments were 9, 11, 5, 8, and 5%, respectively, compared with a schedule without a rain sensor. Lower set points trended toward higher percent irrigation reduction. Six irrigation schedules were included in the analysis with irrigation depth following University of Florida Institute of Agricultural and Food Sciences net irrigation requirement recommendations: 1, 2, 3, and 7 days/week with changing irrigation depth based on recommendations, homeowner (HO, 2 days/week irrigation year round at annual peak ET), and without rain sensor (WORS, 2 days/week). Comparing schedules with WORS, the average percent water savings for 1, 2, 3, 7 days/week, and HO were 6, 8, 10, 28, and $-28\%$, respectively.

Evapotranspiration-based irrigation controllers, also known as weather-based irrigation controllers, are a new water-saving technology that use evapotranspiration (ET) estimates to schedule irrigation. Many ET controllers have the ability to incorporate rainfall events into irrigation scheduling using onsite sensors attached to the controller or weather updates through weather-monitoring services. The Toro Intelli-Sense controller can use an onsite rain sensor (rain switch) that immediately interrupts irrigation or a weather service that causes the controller to enter a rain pause mode to incorporate rainfall into irrigation scheduling. Four treatments were created using the combination of rain delay features: no rain delay features (TN), rain pause (TRP), rain switch (TRS), and both rain delay features (TRP-RS). A fixed-time irrigation schedule with a rain switch and a fixed-time irrigation schedule without a rain switch were created for comparison: T, timer with a rain switch; and TWORS, timer without a rain switch. During relatively dry periods (72% below historical seasonal rainfall) neither rain pause nor the rain switch resulted in irrigation reduction. However, during periods of rainfall (84% of historically rainy days), both features resulted in significant irrigation savings. The combination of rain switch and rain pause reduced irrigation 41% compared with the use of no rain features, whereas the rain pause feature alone saved 25%. Because of the variability of rainfall in humid climates, using both a rain switch and the rain pause feature is recommended to delay irrigation on the Toro Intelli-Sense controller.

Estimation of spatially distributed evapotranspiration (ET) with remote sensing could be especially valuable for developing water management tools in arid lands. For decision support over irrigated crops, these spatial ET estimates also depend on good spatial resolution ($<30\mathrm{m}$) at timely intervals, which for practical operations means no less frequent than approximately 5 days. For a variety of reasons, current remote sensing platforms usually cannot meet these needs. Commonly, overpass frequencies are no better than 16 days and sometimes are much worse considering cloudy skies. One way to reduce this problem is to develop an ET estimation approach that utilizes both remotely sensed data and ground-based observations. By combining episodic spatially distributed data with temporally continuous point observations, it could be feasible to provide continuous ET estimates that are better than can be achieved with either technique alone. Using data from a remote sensing irrigation scheduling experiment over cotton, conducted in 2003 at Maricopa, Arizona, an ET modeling approach was developed that used airborne images of vegetation indices (NDVI) and land surface temperatures (LST) along with ground-based thermal infrared radiometry and meteorology. Fractional vegetative cover were forecast from NDVI at daily time steps using a linear Kalman filter consisting of prior data, cumulative heat units, and spatially oriented beta distribution functions. LST were forecast hourly using a diurnal temperature model and a linear cover/LST estimator. ET accuracies derived from using these data as inputs to a surface energy balance model showed good agreement with independent ET estimates determined from 5-day soil depletion observations. Increased ET attributable to increased crop water use and irrigation applications were reflected in model outputs, and sometimes agreement was within 10% of independently observed soil moisture depletion data sets. These results indicated that combining remote sensing and ground-based data sets could be a feasible way to estimate ET at field-scales at daily time steps.

In the arid Western United States, water is among the most valuable resources. Typically, to successfully and accurately measure a flow rate using most types of flow meters, it is recommended that a straight section of pipe be installed immediately upstream from the flow meter to avoid distorted flow patterns and extreme turbulence at the metering location. In many field piping situations, however, such flow conditions are impossible to achieve. The portable ultrasonic flow meter (USFM) is a commonly used flow meter for field flow measurements in closed conduits and emits two ultrasonic signals across the cross section of pipe. One signal travels with the direction of the flow, and the other travels against the flow. The difference in signal travel time is then used along with the known geometry of the pipe to calculate the average flow velocity of the fluid. The performance of an USFM in nonideal piping scenarios was studied using laboratory experiments and numerical computational fluid dynamics (CFD) models. A transit-time USFM was used downstream of a single 12-in.-long radius elbow, and the error in flow measurement resulting from the flow disturbance was measured. Physical model tests were performed at four locations downstream of the elbow, at three orientations on the circumference of the pipe, and for three flow rates with Reynolds numbers ranging from 250,000 to 750,000. Numerical models were also utilized and the resulting velocity profiles were used to integrate the velocity of the flow across the ultrasonic signal path. The velocity profiles were compared to similar profiles for fully developed flow to determine the error in flow measurement. The USFM measurement errors downstream of the elbow were always negative and were found to be as great as $-16\%$. A correction curve was applied to the results, which provided a method to correct the ultrasonic flow measurement. By applying the correction equation to the USFM measurements downstream of the elbow, the measurement error was reduced by nearly 90%. It appears that CFD is a viable tool for making appropriate corrections to ultrasonic flow measurements in pipes with upstream flow disturbances.

Modernization of today’s irrigation systems attempts to improve system efficiency and management effectiveness of every component of the system (reservoirs, canals, and gates) using automation technologies, along with hydraulic simulation models. The canal flow control scheme resulting from the coupling of the system automation and the simulation models has proven to be an excellent irrigation water management instrument around the world. Nevertheless, the harsh environment of irrigation systems can induce uncertainties or errors in the components of canal flow control that can worsen over time, misleading or confusing both human and computer controllers. These errors can be attributed to parameter measurement and conceptual sources, with the complexity of locating their individual origin. In this paper, a framework is presented to minimize the collective or aggregate error within an irrigation canal flow control scheme that uses a learning machine algorithm (multilayer perceptron and relevance vector machine) embedded in a hydraulic simulation model fed by a canal automation system. This framework is evaluated using actual data from an irrigation conveyance canal located at the Lower Sevier River Basin in Utah. The results obtained prove the adequacy of the proposed framework in minimizing the aggregate error, which affects the simulation results of the automation system (up to 91% in bias and 83% in maximum absolute error) when compared with the original values obtained in the verification period. The temporal correlation of the aggregate error was also significantly reduced, thus resulting in reduced local biases and structures in the model prediction error.

This research presents a new weir section with $n$-segment linear sides and a horizontal bottom. For large $n$, the section sides of the weir become smooth curves. However, piecewise-linear sides provide a weir shape simple enough for ease of construction. General head-discharge equations are analytically derived for the flow discharge. The proposed weir with $n$-segment linear sides can be applied in an optimization procedure to produce a wide range of head-discharge behaviors. An elegant optimization model that implements the general equations is presented and applied in the design of linear and quadratic weirs. This simple model is solved using the Solver toolbox of Microsoft Excel. The versatility of the proposed weir is demonstrated by optimizing the weir parameters to obtain the maximum ranges of measurement under linear and quadratic characteristics. These weirs have least relative errors because of their linear and quadratic head-discharge relationships and are very useful as a flow recorder in irrigation canals. Optimum design parameters for these weirs are presented in a simple dimensionless form suitable for water structure designers to adjust the weir dimensions to suit field conditions. Application of the proposed weir section is not limited to these two weirs; it can also be used to design other specific weirs.

A new prototype of fluidic sprinkler is proposed in this paper. To determine the discharge coefficient (A), pattern radius (B), sprinkler rotation speed (C), droplet diameter distribution (D), and the radial application pattern (E), several sprinkler heads were specially fabricated to carry out the experiments. After systematic experiments were conducted with the 10PXH fluidic sprinkler, the results showed that the inner contraction angle influenced A, B, C, and E, and the geometrical parameters of offset length and working area length influenced E. The operating pressure influenced B, C, D, and E. The reductions in the radius exactly corresponded to the reduction of the discharge coefficient. As the inner contraction angle increased from 10° to 70°, the pattern radius at 250 kPa decreased from 10.7 to 8.4 m and the discharge coefficient decreased from 0.9 to 0.67. The time per rotation and the droplet diameter distribution were analyzed, respectively. The radial application pattern at 250 kPa for all nozzles was established. For the square configurations, the smaller the lateral spacing, the higher the uniformity.

The dissipative process that occurs in the presence of a hydraulic structure is a major topic in river engineering. The energy dissipation has to be correctly evaluated to prevent structural stability risks and to optimize the hydraulic performance of the structure itself. Moreover, the analysis of the dissipative process cannot be limited only to the dissipation that occurs with the structure, but it must also take into account the amount of energy dissipated in the stilling basin. The analysis was conducted considering a block ramp, which is a peculiar stream restoration structure. Experiments were performed in clear water conditions for a fixed ramp slope and different stilling basin geometries. The basin geometry was both symmetrically and asymmetrically enlarged, and mobile bed conditions were also tested. The global energy dissipation was shown to increase for enlarged stilling basins. A simple empirical relationship was derived to evaluate the energy dissipation for both prismatic and enlarged configurations. For asymmetrically enlarged configurations, the flow pattern was analyzed and two hydraulic jump typologies (the repelled asymmetric and the repelled asymmetric oscillating) were distinguished and classified.