Journal of Irrigation and Drainage Engineering

The proper irrigation of container plants is critical due to the limited substrate volume. This work investigated a zero-energy and self-operating drip irrigation instrument suitable for daily watering of container plants. The instrument consists of a partially filled, inverted solid container exposed to sunshine, and a large insulated one as the reservoir, which were connected hydraulically. This solar-thermophysical irrigation (STI) instrument operates through isobaric thermal expansion and contraction processes during both day and nighttime. The daily water discharge of the STI instrument was investigated experimentally and theoretically for different thermal conditions, pump sizes, and operating days. Field test results showed that the average discharge of this drip micro-irrigation device was ${12\mathrm{cm}}^3/\mathrm{h}$ in sunny climate. In a growth experiment, Solenostemon potted plants were irrigated via the STI instrument and 4-, 7-, and 10-day surface irrigation frequencies with identical water quantity. The results indicated that the STI system enhanced the growth traits of the plants compared with plants that underwent periodic irrigation. The novel STI drip irrigation system was appropriate for potted plants’ water demand, and was characterized by simplicity, passive operation, zero-energy, and microrate flow operation. The system can be used for individual plants and residential and small-scale applications.

Although various optimization algorithms have been developed for operational purposes, the development of new optimization algorithms is still an open problem due to the complex system of irrigation canals that must be addressed. Recently, a new algorithm named gray wolf optimization (GWO) has been introduced and applied in different contexts. It mimics the social hierarchy and hunting behavior of gray wolves in nature. In this research, GWO was formulated, developed, and linked to irrigation canal system simulation (ICSS) to schedule water delivery. A fitness (optimization) function was defined according to the standard water delivery performance indicators. Normal and water shortage operational scenarios in the E1R1 Dez canal in Iran were tested and evaluated. The results revealed that GWO is a powerful optimization method and avoids local optimal points when normal conditions exist. However, it has relatively poor performance in water shortage conditions in which there is not enough water. Water depth variations remain inside acceptable margins. Its results were comparable to fuzzy state, action, reward, state, action (SARSA) learning (FSL) in the same canal, showing a value of maximum absolute error (MAE) and integral absolute error (IAE) of 10.7% and 9.2%, respectively, and it can distribute water between turnouts adequately, efficiently, equitably, and dependably in normal conditions.

This study clarified the migration and accumulation patterns of irrigation water and associated salt in a cropland irrigation and drainage unit and evaluated the water-use rationality of the irrigation and drainage unit in the Hetao Irrigation District. A typical lateral canal-scale irrigation and drainage system was selected, the planting pattern of which was complex and included interplanted crops and interlaced cultivated land and wasteland. The overall regional water balance model for the study area was established based on the monitoring data from a two-year field experiment from 2018 to 2019, and the dissipation of irrigation water and the redistribution of soil water and salt were investigated. The obtained specific water yield of the study area was 0.0443. In 2019, water conveyance losses from canals accounted for approximately 18% of the total water diversion, the irrigation water entering cropland through field canals (i.e., field irrigation) accounted for 77.2%, and surface drainage accounted for 4.8%. There is a lateral exchange of groundwater between different land types. After crops use irrigation water in the field, groundwater replenishes approximately 7% of the total water diversion to the field, wasteland consumes 6% of the total water diversion, and the utilization mode also is groundwater replenishment. In the cropland, evapotranspiration (ET) consumption accounted for 84.2% of the total water diversion, and salt accumulation accounted for 14.2% of the total salt introduced, whereas in the wasteland, ET consumption accounted for 6% of the total water diversion, and salt accumulation accounted for 44.2% of the total salt introduced. Although the wasteland area constituted only 5.43% of the total study area, it functioned as a salt storage area and played a vital role in dry drainage desalting. Maintaining an appropriate wasteland area and improving the drainage system could facilitate desalination and sustainable ecological development in the study area. The results provide a reference for water and salt regulation and modern ecological irrigation district management in similar irrigation districts.

Parameter estimation is a significant aspect of modeling flow through porous media. To avoid any nonuniqueness issues in parameters estimation, it is important to have a deep understanding of the information content and reliability of the available data. In this study, sensitivity and estimability analyses were conducted to compare the outcomes of two successive irrigation events. Water flow through soil was simulated using HYDRUS-2D for two successive irrigation periods. Sensitivity coefficients were evaluated to quantify the sensitivity of pressure head, water content, and cumulative fluxes to five crucial soil hydraulic parameters (namely, ${\theta }_s$, ${\theta }_r$, $n$, $K_s$, and $\alpha$). The estimability analysis is further extended to determine the correlation among these parameters. Results show that sensitivity of pressure head, water content, and cumulative fluxes to the parameters is higher after the first irrigation event in comparison to the second one. The parameters were also found to be more estimable during the first irrigation event. The pressure head was proved to contain the best information content, followed by water content data. It was also inferred that cumulative fluxes data are not suitable to estimate parameters individually. Out of the five parameters, ${\theta }_s$ was found to be the most sensitive and estimable parameter, while ${\theta }_r$ comes out to be the least sensitive and estimable parameter. This study helps in estimating the information content of the available data and identifying the most estimable parameters with the least correlation.

A multilevel drip irrigation system generally uses a first-level pivot as the water source. The water is delivered to each head pivot in the field drip irrigation subsystems through the main water distribution pipe network system (MWDPNS). Subsequently, it is irrigated to farmland through field drip irrigation pipe network subsystems (FDIPNS). This paper focused on the lowest total investment of the pipe network to establish a model for simultaneous optimization of the pipe network layout and pipe diameter selection in a multilevel gravity drip irrigation system, and the method and steps based on atom search optimization are proposed. First, all the FDIPNS are optimized; then, the MWDPNS is optimized with the optimization results of each subsystem as the basic design parameters. For the MWDPNS, the available water diversion nodes other than the water demand nodes can be added and selected. By comprehensively considering the topological and hydraulic constraints, the topology design and pipe diameter selection are optimized simultaneously when the selection of the water distribution nodes is uncertain. For the FDIPNS, the field width is regarded as a linear piecewise function of the field length, and the constraints such as the pipeline layout, flow velocity, discharge, pressure, and rotational irrigation scheme are considered. This model can be applied to most irregular fields. Taking a two-level gravity drip irrigation project in Xinjiang, China as an example, the effectiveness of the proposed model and algorithm was assessed. The results demonstrate that the proposed optimization method has a good application value for the pipe network design of multilevel gravity drip irrigation systems.

To determine the kinetic energy consumption of various spray-sprinkler structural parameters, the hydraulic performance, including the discharge and initial trajectory velocity, was investigated using computational fluid dynamics (CFD) analyses and the particle image velocimetry (PIV) technique. A comparison of the experimental and simulation results showed that a high accuracy was obtained using CFD technology. On this basis, a series of simulations was performed to evaluate the effects of groove length, groove number, and cone angle on jet velocities, and the kinetic energy dissipation was calculated. The results showed that the spray-plate structure had a significant influence on the water fraction patterns, leading to relatively large differences in the initial velocity; the average velocity decreased as the cone angle, groove number, or groove length of the spray plate increased. The wall shear stress results showed that a large amount of kinetic energy was dissipated in the groove, indicating that decreasing the groove number or groove length reduced energy dissipation. In addition, the wall shear stress in the cone area increased as the cone angle increased, resulting in an increase in energy dissipation. The sensitivity analysis indicated that the groove length is the most significant parameter influencing energy consumption.

The application of numerical models for fishway flow enables an improved comprehension of the turbulent flow structure, which is an important covariate used to explain fish passage. Reynolds-averaged Navier–Stokes (RANS) with $\mathrm{K}\text{-}\epsilon$ closure is the main numerical model to characterize the flow in fishways, but recently, large eddy simulation (LES) has been reported to be better at capturing turbulence in incompressible flows. Comparison between RANS and LES in analyses of fishways flows indicate limitations in both approaches to capture the turbulence parameters or sightly performance of LES for detailed scale studies. Vertical slot fishways are one of the most studied fish ladders, but few studies address the effect of different slot displacements on hydraulic parameters. Thus, the flow of the central vertical slot fishway was simulated in the open-source software OpenFOAM, and two models were applied: (1) RANS with $\mathrm{K}\text{-}\epsilon$ closure; and (2) LES with the one-equation eddy viscosity (kEqn) scheme. The numerical results were compared to ADV data sampled in a physical model. The flow in a pool of central vertical slots creates two lateral flow recirculation areas and a central straight flux at different discharges and water levels. The RANS $\mathrm{K}\text{-}\epsilon$ and LES kEqn models provide with the ADV data for all velocity ranges and for the smallest turbulent kinetic energy (TKE ${<0.03\mathrm{m}}^2/{\mathrm{s}}^2$). The LES kEqn model is slightly better in turbulence representation but the RANS $\mathrm{K}\text{-}\epsilon$ reproduces velocity field more accurately. The RANS and LES model application in fish ladders will be useful for improving the comprehension of fish passage performance and practical aspects of fishways.

Traditional land development stormwater management replaces natural pervious surfaces with impervious surfaces such as pavements and buildings. This increases the rate of runoff that is typically then managed through drainage systems and controlled at or near the site discharge location. This approach often leads to increases in total runoff volume, which can lead to higher peak flows in downstream stormwater systems. Low impact development (LID) technologies, such as porous pavements and green roof systems, provide an alternate approach to managing site runoff by mimicking the pervious surfaces they replace. However, these technologies are often used alongside traditional stormwater infrastructure because their entire hydrologic benefit has not been fully explored. Herein we examine the reduction in peak discharge and total runoff volume achieved through the use of porous pavements and green–blue roof systems (a green roof with an underlying storage volume) on three land developments located on the coastal plain of South Carolina. Model results show that the inclusion of green–blue roof systems can significantly reduce peak discharge compared to traditional roof systems and common modular green roof systems, although they have negligible impact on the total volume discharged. Porous pavements significantly reduce total volume discharged, even when placed over low infiltration soils, but have less impact on peak flow depending on their design. The implementation of LID technologies has the potential to improve site performance beyond standard design rainfall depths, indicating that the use of LID may offset the impact of climate change–induced increases in extreme rainfall event depth and intensity.