Journal of Irrigation and Drainage Engineering

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

On a stepped spillway, the staircase invert profile generates some intense turbulent dissipation during the spill, associated with a significant reduction of kinetic energy, as well as strong self-aeration. The present study focused on the effects of inclined downward steps on the air–water flow properties, flow resistance, and head losses because these mostly relate to spillway design. Some physical modeling was conducted in a relatively large facility with a 45° stepped chute ($\mathrm{1}\mathrm{V}\mathrm{:}\mathrm{1}\mathrm{H}$) operating with Reynolds numbers $2.8\times {10}^3<\mathrm{Re}<1\times {10}^6$. The presence of downward steps induced some elongated asymmetrical cavity shapes, creating a less stable cavity recirculation pattern along the entire chute, leading to different interactions with the main stream. In terms of basic air–water flow properties, the distributions of void fraction and bubble count rate presented very close results for all three stepped geometries, both qualitatively and quantitatively. The interfacial velocities did not reach any uniform equilibrium (i.e., normal flow) condition, and the fastest velocities were recorded with the $\mathrm{1}\mathrm{V}\mathrm{:}\mathrm{2.33}\mathrm{H}$ inclined downward stepped chute geometry ($\delta =23.3°$ and $\lambda /k=3$), and the slowest velocities on the horizontal stepped chute ($\delta =0$ and $\lambda /k=2$). The Darcy-Weisbach friction factor $f$ and relative head loss $\mathrm{\Delta }H/H_{\max }$ were estimated in the self-aerated flow. The comparative analyses suggested that the largest total drag and head losses were observed on the stepped chute with flat horizontal steps. An inclined downward stepped design yielded lesser head losses for all investigated flow conditions, providing an important information for practical engineers designing these hydraulic structures.

Abstract

The present paper attempts to study the flood wave propagation at a right-angled combining open channel junction utilizing the three-dimensional (3D) transient Reynolds-averaged Navier-Stokes (RANS) equations. The present study advocates using the 3D model over the depth-averaged two-dimensional (2D) model by comparing simulations obtained from 3D and 2D models for steady flows. The 3D model is validated against the experimental results of the flood routing in a single reach channel, available in the literature. The flood wave at the channel inlet is generated by a half-cycle of the sinusoidal function. Three different cases (Cases 1, 2, and 3) are considered by applying the flood wave at the inlet of the main channel, tributary channel, and both the channels, respectively. The steady-state junction flow with equal discharge in both the upstream channels is considered as the initial condition for the flood wave simulations. The rising flood flow of the main channel offers huge flow blockage to the tributary channel flow in Case 1, while vice versa in Case 2. The blockage causes significant flow accumulation leading to the stage rise. In Case 2, the flow reversal occurs as the flow in the main channel is entirely blocked by the rising flood flow of the tributary channel. The interplay of the flow blockage by the main channel to the tributary channel and vice versa results in water accumulation and release, alternatively. The maximum stage rise occurs in Case 3 due to the combined effects of the rising flood wave and flow blockage, simultaneously.

Practical Applications

The previous flood routing studies at the channel junction have disregarded the momentum equation. This may not be accurate as momentum exchange occurs between the main and tributary channel flow. Considering the dynamic interaction between the approaching flows, the present paper attempts to study the flood wave propagation at a right-angled combining open channel junction utilizing the fully three-dimensional numerical model. Three different simulation cases considered for investigating the flood wave propagation demonstrate the impact of the main channel flood wave on the tributary flow and vice versa. The alternate amplification and attenuation of the flow discharge in both the upstream channels continue to happen due to the interplay of the blockage offered by the main channel to the tributary channel and vice versa before the junction flow attains the base flow condition. The results of the present study improve the understanding of flood wave propagation at the channel junction.

Abstract

Currently, land surface models (LSMs) are limited in representing realistic water and energy fluxes owing to the absence of reliable parameterization of irrigation. In this study, a novel method was employed to incorporate irrigation in the Community Land Model (CLM) Version 4.0. Two CLM experiments were set up, designated CLM-default run and CLM-irrigated run. The SM2RAIN algorithm was employed to reproduce the observed precipitation and irrigation using soil moisture (SM) information measured at the Fluxnet sites. The results showed that SM2RAIN reliably reproduced the observed precipitation on a daily timescale ($R\sim 0.70$ for all three sites) but significantly underestimated high-intensity precipitation (bias $\sim 0.5\mathrm{mm}{\mathrm{day}}^{-1}$ for all sites). The bias-corrected SM2RAIN output showed improved representation of observed daily precipitation ($R=0.89$ and 0.86) and monthly irrigation ($R=0.89$ and 0.96) at US-Ne1 and US-Ne2, respectively. The SM2RAIN estimated irrigation was input to CLM as independent forcing data along with other atmospheric forcings. The simulated surface energy fluxes from CLM were compared with eddy covariance–based flux tower observations. The results showed that CLM simulated energy fluxes from the CLM-irrigated run improved the representation of turbulent heat fluxes (latent and sensible). Overall, mean bias decreased by 32% and 64% for sensible and latent heat fluxes, respectively. This indicates that SM2RAIN-estimated irrigation is reliable input data for LSMs that potentially improved model representations of surface energy fluxes, which are important for comprehending the complex interactions between land surface and atmosphere in irrigated areas.

Practical Applications

A novel method of estimating actual irrigation amount is presented for incorporating into land surface models (LSMs). The primary goal of the study was more accurate simulation of land surface states and fluxes by better representing agricultural land use. Moreover, this technique may allow numerical weather prediction (NWP) models to more precisely represent land–atmosphere feedback in managed areas, hence improving forecast skill. It was demonstrated in this study that using the novel irrigation method in LSMs can reliably represent surface water and energy fluxes. The findings of this study are very relevant to regional-to-global–scale water and energy cycle research, which has struggled to quantify the consequences of agricultural management practices like irrigation in the past. It is anticipated that improved representation of managed lands will make it possible to provide better weather and climate forecasting when the new irrigation plan is incorporated in NWP models.

The emptying process of initially stagnant full-pipe flows in sewer systems and water transmission lines was extensively studied in the literature. The following air intrusion and depressurization wavefronts can cause several issues such as the collapse of pipes, damage to joints, and valves. However, there is a lack of study on the emptying process when the flow has initial velocity. Thus, the present study focuses on the emptying process of a full-pipe flow with an initial flow rate, which decreases during the emptying process. For this purpose, two experiments without and with initial flow rates were performed in a reservoir-circular pipe system. In both experiments, an air cavity intrusion starts downstream of the pipe at the top of the free-surface flow and propagates upstream. It was found that when there is no initial flow rate, the pressure inside the cavity is atmospheric. However, when there is an initial flow rate, at the onset of the air intrusion, a subatmospheric pressure develops inside the air cavity. It was also found that the magnitude of this subatmospheric pressure decreases when the cavity further propagates upstream. In addition, when there is an initial flow rate, the cavity appears at a certain driving pressure.

To reduce flood risk in urban areas, an optimal design of drainage networks for urban areas is essential for flooding control and drainage management of the urban stormwater drainage system (USDS). A conventional design is generally used for drainage networks, resulting in high computational costs and limited flooding reduction effect. In this study, based on an on-line data-driven evolutionary algorithm coupled with the storm water management model (SWMM), a novel approach for USDS drainage network optimization design was developed. A case in Xi’an City, China, was then selected for practical implementation, where the performances of the local planning scheme, the particle swarm optimization algorithm (PSO) and the proposed approach were compared. Results confirmed that our proposed methodological approach is feasibility and highly efficiency, leading to a 32% reduction in total flooding from that resulting from the local planning scheme. In addition, the average computational time was reduced by 57%, while the flooding control effect was better, compared to PSO algorithm optimization. These results suggest that our optimization design approach is reliable and applicable, and can benefit and assist designers in practice.

This paper offers a new model for determining the optimal spacing of mini center pivot system (MCPS) nozzles for high water application uniformity. The strengths of the study included an in-depth analysis of optimum nozzle spacing and the high impact on the efficiency of the MCPS. To achieve this goal, a genetic algorithm was used to maximize the uniformity coefficient under the MCPS when the design parameters were inputted and combined with the formula of Heermann and Hein. The optimization is based on the water distribution modeling, and Heermann and Hein uniformity coefficient (CUH) calculation of three existing MCPS, 60, 50, and 46 m in length. A comparison between the CUH values obtained experimentally and by the proposed model, is used to validate the proposed model. According to the findings of this study, the proposed model can optimize the CUH uniformity coefficient by 23.87%, 29.99%, and 17.96% for the three studied MCPSs 60, 50, and 46 m in length, respectively, while determining optimal nozzle spacing.

Studies of the estimation of reference evapotranspiration (${\mathrm{ET}}_0$) in Iran are mostly related to areas with humid and semiarid climates and less related to arid areas. On the other hand, few studies in arid regions have reported high root-mean square error (RMSE) values. However, these regions make an important contribution to agricultural production, and thus, water management of these regions is crucial. It motivated the implementation of such a study in an arid environment of Karaj, Iran, as a case study, in order to estimate daily ${\mathrm{ET}}_0$ with as much accuracy as possible. To achieve this purpose, the performance of 21 known models estimating ${\mathrm{ET}}_0$, including 9 empirical models and 12 machine learning (ML) models, were evaluated. The method provided by the food and agriculture organization (FAO) known as FAO-56 Penman-Monteith (FPM) was regarded as the main reference method for measuring ${\mathrm{ET}}_0$. A new climate data set related to the period of 2005–2020 (April–September) was used to calibrate and cross-validate models. In fact, this study intended to develop an approach for simulating day-to-day variations in ${\mathrm{ET}}_0$ in arid environments by benefitting minimal weather data (i.e., temperature, humidity, and wind speed) for practical purposes because most regions suffer from a lack of weather data, especially radiation data. Therefore, the performance of the best models calibrated in Karaj station was also validated based on data recorded in a research field with a similar climate during 2020–2021. The cross-validated results showed that the deep-learning (DL) model had the lowest RMSE as well as the highest $R^2$ compared with other models. As averaged over all months in Karaj, the DL model exhibited a RMSE 64% less than the best-calibrated empirical model (i.e., Valiantzas-VTS), which is a solar radiation–based model. Furthermore, the improvements arising from using the DL model were more considerable in the extremes than in the middle values. The findings of the field research also demonstrated that the approach developed in the current study would be beneficial at locations other than the calibration station. This approach requires few inputs, is independent of solar radiation data, and also has the lowest RMSE compared with that of other studies. For future studies, the combination of the daily ${\mathrm{ET}}_0$ estimator developed in this study with a recently developed empirical approach to estimate crop coefficients is suggested to manage irrigation on croplands if arid regions.

A simple explicit formula was derived to determine the maximum irrigation depth ($D_{\max }$) that can be applied per irrigation without any runoff under a center pivot and/or linear move irrigation system. The analysis is built on the assumption that $D_{\max }$ is achieved when the water application rate is tangential to the Green-Ampt infiltration rate function. The surface storage was not considered here but tillage effects can be inherently incorporated if parameters of the Green-Ampt equation are properly measured. A power form formula was proposed to simulate the infiltration rate, while the application rate pattern had a parabolic shape. The proposed equation for $D_{\max }$ is a function of soil saturated hydraulic conductivity, sorptivity, and the peak application rate. Numerical examples covering different combinations of soil properties and peak application rates indicated the high accuracy of the proposed formula with maximum and average absolute errors of 1 and 0.4 mm from the numerical stepwise solution, respectively. The quick calculation of $D_{\max }$ here allows us to easily estimate a minimum lateral speed that will not trigger runoff under center pivots.