Journal of Irrigation and Drainage Engineering

A methodology for determining the length of advancement of wetting front and potential groundwater recharge under variable depth of ponding is presented. The methodology provides no restrictions to infiltration time period, depth, and nature of ponding and soil types. Performance of the proposed methodology has been compared with other models using the published laboratory and field experimental data. The quantitative statistics, namely, coefficient of determination ($R^2$), index of agreement ($d$), and percent bias (PB), are utilized to assess the performance of the proposed methodology. Results show that the proposed methodology worked with the same potential as the numerically rigorous solution of the other models. The quantitative statistics $R^2$ and $d$ between the models’ estimates approached unity. Analyzed results shows that the proposed methodology for estimation of advancement of wetting front, cumulative potential recharge, and 5rate of potential recharge has a maximum PB of $-12.98$, $-14.33$, and 12.62%, respectively, in comparison to the other models, which is within permissible limit of 25%. The derived methodology is also successfully applied with 3 years (2006–2008) of field data from small recharge ponds located over a watershed in the semiarid region of India. The response of the methodology is found most promising for simulating the length of advancement of wetting front and corresponding potential groundwater recharge from small recharge ponds. Results of the comparative and field studies of the proposed methodology under variable depth of ponding over a variety of soils demonstrated the capability of the proposed methodology for their field uses to design artificial groundwater recharging facilities, irrigation systems, and resolving solute transport problems.

The present work describes a procedure for the evaluation of the optimal number, position, configuration, and sizes of detention tanks in urban drainage networks, to decrease the maximum flow depths and velocities for an assigned return period and to comply with the local design requirements. Each candidate solution of the optimization problem is evaluated by means of a semidistributed hydrological model in which the kinematic wave is used as flood routing model, whereas the variational approach is used to evaluate the critical flow characteristics corresponding to a given return period. The procedure, which makes use of a genetic algorithm to search for the optimal solution among the candidates, is applied to a case study drainage network, considering superpipe-based detention tanks as detention systems. The results indicate that these tanks are effective in the rehabilitation of the drainage network and that the cost of this intervention is substantially lower than that corresponding to the upgrading of existing pipes.

Drought quantification is a decision-making approach for water resources planners and managers. There are different statistical methods for regional quantification of droughts, depending on the event being regionally discrete or continuous. Calculating a drought index in the measured grid points of a given region is a prerequisite for the regionalization process of drought by these methods. The aim of this study is the regional analysis of the streamflow drought using the multivariate technique of principal components analysis (PCA). To this end, the streamflow drought index (SDI) was calculated in the seven hydrometric stations of the Sefid-Rud basin in Iran for the period of 1984–2013 in seasonal (winter, spring, summer, and autumn), semiannual (October–March and May–September), and annual (October–September) time scales. Regional monitoring of the SDI was carried out using the PCA technique summarizing the SDI series of all stations into a new series, the so-called the multivariate streamflow drought index (MSDI). The MSDI series at each time scale were analyzed from several statistical aspects. Results showed that there are relatively high correlations between the SDI series of the stations for given time scales. The first principal component (${\mathrm{PC}}_1$) explains 58–85% of the regional variations of the SDI series at the mentioned time scales. The MSDI series at multiple time scales follow all stations’ SDI fluctuations and appropriately monitor droughts that occurred in the region, especially in long dry periods. The dry and wet severity classes derived from the MSDI series greatly corresponded to those of the SDI time series on different stations. The highest percentage of correspondence between MSDI and SDIs was calculated for the semiannual time scale and the lowest for the spring season.

The study and computation of free surface flows is of paramount importance in hydraulic and irrigation engineering. These flows are computed using mass and momentum conservation equations, their solutions exhibiting special features depending on whether the local Froude number ($\mathsf{F}$) is below or above unity, thereby resulting in wave propagation in the upstream and downstream directions or only in the downstream direction, respectively. This dynamic condition is referred to in the literature as critical flow and is fundamental to the study of unsteady flows. Critical flow is also defined as the state at which the specific energy and momentum reach a minimum, based on steady-state computations, and it is further asserted that the backwater equation gives infinite free surface slopes at control sections. So far, these statements were not demonstrated within the context of an unsteady-flow analysis, to be conducted in this paper for the first time. It is demonstrated that the effects of unsteadiness break down critical flow as a generalized open-channel flow concept, and correct interpretations of critical flow, free surface slopes at controls, minimum specific energy, and momentum are given within the context of general unsteady-flow motion in this paper.

The area irrigated by furrow irrigation in the United States has been steadily decreasing but still represents about 20% of the total irrigated area in the United States. Furrow irrigation sediment loss is a major water quality issue, and a method for estimating sediment loss is needed to quantify the environmental effects and estimate effectiveness and economic value of conservation practices. Artificial neural network (NN) modeling was applied to furrow irrigation to predict sediment loss as a function of hydraulic and soil conditions. A data set consisting of 1,926 furrow evaluations, spanning three continents and a wide range of hydraulic and soil conditions, was used to train and test a multilayer perceptron feed forward NN model. The final NN model consisted of 16 inputs, 19 hidden nodes in a single hidden layer, and 1 output node. Model efficiency (ME) of the NN model was $\mathrm{ME}=0.66$ for the training data set and $\mathrm{ME}=0.80$ for the test data set. The prediction performance for the complete data set of 1,926 furrow evaluations was $\mathrm{ME}=0.70$ with an absolute sediment loss prediction error of less than $\pm 5$, $\pm 10$, $\pm 20$, and $\pm 30\mathrm{kg}$ per furrow for 35, 53, 72, and 85% of the data set values, respectively. The NN model is applicable to predicting sediment loss rates between 1 and 300 kg per furrow for furrow lengths between 30 and 400 m, slopes between 0.1 and 4%, flow rates between 5 and $75\mathrm{L}{\min }^{-1}$, and silt or sand particle–sized fractions between 0.1 and 0.75.

Recent California legislation requires irrigation water agencies larger than 25,000 acres to measure volumetric water deliveries within specified levels of relative uncertainty. Although the meter gate is one of the most widely used flow measurement devices in California, little investigation has been conducted into the accuracy, limitations, and uncertainties of the rating tables developed over 60 years ago. A meter gate testing facility was constructed at the Cal Poly Irrigation Training and Research Center’s Water Resources Facility capable of testing gates up to 0.76 m (30 in.). The facility was constructed with gates oriented perpendicular to the supply channel flow to match actual field conditions. Three commonly used gate sizes of 0.30 m (12 in.), 0.46 m (18 in.), and 0.61 m (24 in.) were examined under a variety of upstream head, head loss, and gate opening conditions. Based on the limitations, guidelines are included to assist users and lower the uncertainty of these devices. It was found that meter gates can be an accurate flow measurement device if installed and operated correctly according to guidelines provided. Limitations were found: upstream head above the top of the turnout pipe must be maintained equivalent to at least half the pipe diameter, and gate openings less than 25% open can lead to large uncertainties. Using the new rating tables for the three gates examined, the relative uncertainty is less than $\pm 5$ to $\pm 7\%$ at the 95% confidence level with the new rating tables, as compared with less than $\pm 10\%$ at a 95% confidence level using common published tables. Uncertainties are lower than the required estimated 10.7% instantaneous flow rate uncertainty that will be needed to meet current SB X7-7 requirements.

Traditional meter gates for farm delivery flow measurement from an open channel conveyance have traditionally incorporated round canal gates (Armco type) for control. In recent years, some irrigation water agencies (i.e., irrigation districts) have replaced deteriorating round gates with lower-cost rectangular gates that cover round holes. Similar to the situation described in a companion paper, where round gates were examined, there have been no investigations into flow measurement uncertainty using the existing rating tables for these gates. In this study, two commonly used rectangular gate sizes, 0.46 m (18-in.) and 0.61 m (24-in.), were tested under scenarios of various gate openings, upstream heads, and head differences. Coefficient of discharge ($C_d$) values were computed based on actual gate open areas. These improved $C_d$ values were used to generate new discharge rating tables for 0.46 m (18-in.) and 0.61 m (24-in.) rectangular meter gates. Limitations for these rectangular gates are discussed. If guidelines presented in this paper and in the companion paper are followed, the average instantaneous flow measurement uncertainty that could be expected is better than $\pm 5\%$. However, uncertainty is higher (up to approximately $\pm 9.5\%$) at the lower end of the recommended gate openings [0.10 m (4 in.)] for these rectangular gates.

Irrigation for cold protection in strawberries has been used for many years to protect plants from cold damage; however, large volumes of high-quality water are needed for this purpose. Based on computer modeling for citrus, an application rate (AR) of $6.35\mathrm{mm}{\mathrm{h}}^{-1}$ with impact sprinklers providing full coverage has been recommended and successfully used for this practice in other crops. Nevertheless, lower rates have not been field verified. Thus, the objective for this study was to assess the effect of varying irrigation system pressure and sprinkler spacing on AR and strawberry yield. The treatments evaluated consisted of grower’s practices (GROW), representing grower cold protection practices using 345-kPa irrigation pressure at 14.6-m sprinkler spacing; automated control (AC), with the same setup as GROW but testing an automated control system based on real-time dew point; low-pressure system (LOW), evaluating irrigation at 207 kPa and 14.6-m spacing; shorter spacing (SPC), assessing an irrigation system at 345 kPa and 12.2-m spacing; and nonirrigated (NI) or control. A thermostat and resistive thermodevices (RTDs) controlled irrigation for GROW, LOW, and SPC treatments in 2011–2012 and 2012–2013, respectively, whereas wireless temperature and relative humidity (RH) sensors computed dew point (DP) and activated the AC irrigation on the basis of plant specific thresholds. Significant yield differences between the irrigated treatments and NI were observed in both seasons. After a cold event, only irrigated treatments showed a comparable linear recovery of yield; however, this recovery was not found in the NI treatment. Water savings of 5% and up to 23% were achieved during the 2011–2012 and 2012–2013 seasons, respectively, using an automated irrigation system for cold protection (AC treatment). No yield differences were obtained when the irrigation system pressure was reduced from 345 to 207 kPa, but 22% water savings was achieved. Thus, a lower pressure can reduce irrigation use without affecting yield in years with mild freezes.

This paper evaluates the effect of six water treatment combinations for the treatment of turbid surface water on four types of emitters by looking at clogging potential and distribution uniformity. The pilot plants use different combinations of upflow gravel filtration, disc filters, and slow sand filtration, fed with natural water from the Cauca River (Cali, Colombia). The outflow of these systems was used to feed four different types of emitters. The paper analyzes the removal of physicochemical parameters that affect emitter clogging and the distribution uniformity of the lower quarter (DUlq). All treatment schemes reduced clogging potential, with the best performance being obtained with upflow gravel filtration followed by slow sand filtration and upflow gravel filters in series. The effect on DUlq differed for the four types of emitters. The longest irrigation time was obtained for the pressure compensated emitter and for the Lyn emitter with 600 h of continuous operation until the DUlq was below 80%.

This study presents two gray models with which to forecast groundwater levels at two study sites; one is located on an island area, and one is in an inland area. These models used the moving average of daily infiltration depth, historical groundwater level, and water demand from irrigated paddy-field districts as variables, taking into account the characteristics of the sites. For the site on an island area, the sea water surface level was additionally used as one of the variables. The model parameters were estimated by integrating the models with a global search method, the annealing-simplex method. The comparisons between the observed values and the forecasts in calibration and validation show that the forecasts are in close agreement with the observations. The sensitivity analyses of the models revealed that the variable for water demand affects the groundwater levels, depending on irrigation practices, and that the variable for sea water surface level is one of the factors affecting groundwater discharges. In comparing the predictive capabilities of the models with those of the other gray models, it was proved that the models have appropriate variables for forecasting groundwater levels with 1–10 days of lead time. Moreover, the accuracies of the models are higher than those of the base models. Finally, these results demonstrate that the models are slightly superior to other models and can reasonably forecast groundwater levels and the effects of groundwater pumping on groundwater states in real situations.

The velocity field and surface profile of an open channel flow with a submerged hydraulic jump from a vertical sluice gate are investigated for two different flow cases. The governing equations are numerically solved using a finite-volume method for flows having the same conditions with experiments. The volume of fluid method is used to calculate the free surface. In modeling the turbulence stresses, standard $k\text{-}\epsilon$, renormalization group $k\text{-}\epsilon$, realizable $k\text{-}\epsilon$, shear stress transport $k\text{-}\omega$, and Reynolds stress turbulence closure models are employed. A grid convergence index analysis is carried out to determine the discretization error for the grid-independent solution. Experimental validations of the numerical results show that in predicting the velocity field, the Reynolds stress turbulence model is the most successful among the five. It also estimates the free-surface profile of the flow successfully.

The SRFR program is a modeling system for surface irrigation. It is a central component of WinSRFR, a software package for the hydraulic analysis of surface irrigation systems. SRFR solves simplified versions of the equations of unsteady open channel flow coupled to a user-selected infiltration model. SRFR was reprogrammed using a modern object-oriented architecture with the objective of facilitating its continued development and, thus, the addition of new modeling options and functionalities. The upgraded software is SRFR 5. An important component of the modeling system is the code that manages computational incidents. While the computational methods used by SRFR 5 have been widely tested and are generally robust, calculations are prone to failures due to problems with the solution of the nonlinear finite difference system of equations, discretization problems, and problems with the determination of the appropriate boundary condition at each computational time step. Code that manages computational incidents has been greatly enhanced in SRFR 5. SRFR 5 has undergone systematic testing, partly to fix programming errors, but also to improve computations leading to unacceptable volume balance errors. This article discusses the SRFR 5 modeling system and provides details about its computational methods, architecture, and new features.

Reservoir systems are built to deliver multiple functions, such as water supply, energy production, flood control, recreation, and fisheries protection in a safe, economic, and efficient manner. This paper presents a sample three-reservoir system with comprehensive physical and hydrologic characteristics. The sample reservoir system considers energy production, water supply, and recreational and flood-control objectives. The results from the operation of this paper’s reservoir system under four different scenarios show that this system’s characteristics and structure conform well with actual reservoir operational processes. The reliabilities associated with meeting reservoir-operation objectives were calculated for the sample reservoir system for the four operational scenarios, ranging from independent reservoir operation with single objectives to integrated reservoir operation with multiple objectives. The results show acceptable ranges of reliability for the three objectives considered under each operational scenario. The sample reservoir system can be used to test a wide range of optimization models that are commonly used in reservoir operation.

In Tunisia, the salinization phenomenon in irrigated areas is frequently worsened by poor drainage. In this context, the irrigated area of Cebala Borj-Touil was studied in order to conceive an efficient drainage network. The characterization of the shallow groundwater was based on depth and salinity observations. Three selected piezometers were equipped with sensors (CTD Diver) for automatic measurement of groundwater depth and salinity. A finite difference model was developed to simulate groundwater flow and solute transport in the irrigated area. The model results showed a limited effect of the present design of the drainage network, particularly downstream in the central axis of the drainage system (the CPII canal). Various management alternatives were modeled: (1) a CPII canal performance decrease, (2) a 1 m deepening of the CPII canal level compared with the present level, and (3) a 1.5 m deepening of the CPII canal level compared with the present level. The results of scenarios 1 and 2 showed a piezometric level lowering, a drainage flow rise and a rate evaporation and salt concentration decrease. The improvement of the drainage network efficiency is more significant with an important deepening of the CPII canal level.

Sustainable water management is paramount to effective and efficient irrigation water management. Over decades, excessive irrigation water application has caused erosion, poor crop quality, water logging, salinity, and wastage of scarce water resources. Variable rate irrigation (VRI) is a recent technique that aids the application of irrigation water according to crop needs and soil physical and chemical properties. A challenge in applying VRI is the determination of appropriate water management zones (MZs). Two software and associated clustering techniques stand out as the best in determining the optimal number of MZs: management zone analyst (MZA), based on a fuzzy c-means algorithm, and regionalization with constrained clustering and partitioning (REDCAP), based on combinatorial graph theory. This study assesses the two techniques for VRI application on a 44 ha field in southern Alberta, Canada, using electrical conductivity (EC) and land elevation. Wedges of 8° and 24° generated the same number of optimal MZ classifications, although the heterogeneities in the 8° wedges were greater than those for the 24° wedges, although it seems that using 24° wedges may mask soil properties, such as the apparent soil EC or elevation, that are critical to crop productivity and efficient water application; however, in terms of costs, in this field, 24° wedges with MZA software appear to be the optimal solution. This study highlights the effectiveness of the two techniques and shows how they can be used to create or classify MZs for VRI.

A multiobjective programming model is proposed for optimal allocation of surface and groundwater resources under water deficits in arid and semiarid regions. This paper considers a biobjective problem in water allocation to agricultural areas by using a nondominated sorting genetic algorithm (NSGAII) as a multiobjective optimization method. Accordingly, there are two maximization objectives: (1) net benefit and (2) relative water use efficiency. Moreover, the optimized results of the aforementioned objectives have been determined to verify NSGAII solutions. Groundwater discharge, economic parameters, and evapotranspiration is formulated as three groups of constraints are linked together by the appropriate linear mathematical functions. The applicability of the irrigation scheduling is evaluated in the experimental field located at Baghmalek plain, Khuzestan province, Iran. The values of crop factors for different growth stages were estimated to obtain the production functions of wheat, barley, rice, maize, melon, tomato, onion, vegetable, and bean. The results showed that the model did not suggest deficit irrigation for melon and tomato during the middle stage. Overall, incorporating multiobjective optimization techniques using NSGAII can effectively improve precision in irrigation scheduling.

Channel expansions are common in both natural and artificial open channels. With increasing cross-sectional dimensions in an expansion, flow decelerates. Because of the complexity of flow patterns, physical models alone cannot provide a clear understanding of the physics governing the flow field and it is necessary to study this phenomenon not only in the field and experimentally but also numerically. In this study, the flow pattern in an expansive transition was numerically simulated. For simulating turbulence characteristics, a Reynolds stress model was used in addition to continuity and Navier-Stokes equations. Water surface and velocity profiles at different sections of transition were compared with experimental results and showed good agreement. After calibration, the model was run to consider the effect of inflow Froude numbers on turbulent kinetic energy and bed-shear stress at different cross sections. The results show that increasing the inflow Froude number increases turbulent kinetic energy and bed-shear stress.