Journal of Irrigation and Drainage Engineering

Grass establishment on railway embankment steep slopes for erosion control in Central Queensland, Australia, is aided by drip lateral irrigation systems. The effective field values of the lateral parameters may be different from the manufacturer supplied ones due to manufacturing variations of the emitters, environmental factors, and water quality. This paper has provided a methodology for estimating drip lateral effective parameter values under field conditions. The hydraulic model takes into account the velocity head change and a proper selection of the friction coefficient formula based on the Reynolds number. Fittings and emitter insertion head losses were incorporated into the hydraulic model. Pressure measurements at some locations within the irrigation system, and the inlet discharges, were used to calibrate the lateral parameters in a statistical framework that allows estimation of parameter uncertainties using the Metropolis algorithm. It is observed that the manufacturer’s supplied parameters were significantly different from the calibrated ones, underestimating pressures within the irrigation system for a given inlet discharge, stressing the need for field testing. The parameter posterior distributions were found to be unimodal and nearly normally distributed. The emitter head loss coefficient distribution being very significant suggests the need to incorporate it into the hydraulic modeling. Although the example given in this paper relates to steep slopes, the methodologies are general and can be applied to any use of drip laterals.

The design of trickle irrigation systems is crucial to optimize profitability and to warrant high values for the emission uniformity (EU) coefficient. EU depends on variation of the pressure head due to head losses along the lines and elevation changes, as well as the water temperature, and other parameters related to the emitters (manufacturer’s coefficient of variation, number of emitters per plants, emitter spacing). Trickle irrigation plants are usually designed using small diameter plastic pipes (polyethylene or polyvinyl chloride). The design problem, therefore, needs to consider head losses along the lines as well as emitter discharge variations due to the manufacturer’s variability. Variations in the hydraulic head are a consequence of both friction losses along the pipe and local losses due to the emitters’ connections, whose importance has been recently emphasized. Since each local loss depends on the emitter type (in-line or on-line) as well as on its shape and dimensions, the morphological variability of the commercially available emitter requires experimental investigations to determine local losses in drip laterals. On the other hand, local losses can be estimated by the mean of computational fluid dynamics (CFD) models, allowing analysis of velocity profiles and the turbulence caused by the emitters’ connections. FLUENT software can be considered a powerful tool to evaluate friction and local losses in drip irrigation laterals, after the necessary validation has been carried out by means of experimental data. The main objective of this study was to assess a CFD technique to evaluate friction and local losses in laterals with in-line coextruded emitters. The model was initially used to choose the turbulence model allowing the most accurate estimation of friction losses in small diameter polyethylene pipes, characterized by low Reynolds number. Second, the possibility of using CFD to predict local losses in drip irrigation laterals with a commercially available coextruded emitter was investigated. Simulated local losses were obtained as difference of the total and friction losses along a trunk of pipe, where one single emitter was installed, not considering the emitter outflow. The proposed procedure allows to evaluate local losses for other different emitter models, avoiding tedious and time-consuming experiments.

The scarcity of water resources is the driving force behind modernizing irrigation systems in order to guarantee equal rights to all beneficiaries and to save water. Traditional distribution systems have the common shortcoming that water must be distributed through some rotational criteria. This type of distribution is necessary to spread the benefits of scarce resources. Irrigation systems based on on-demand delivery scheduling offer flexibility to farmers and greater potential profit than other types of irrigation schedules. However, in this type of irrigation system, the network design has to be adequate for delivering the demand during the peak period whilst satisfying minimum pressure constraints along with minimum and maximum velocity constraints at the farm delivery points (hydrants) and in the pipes, respectively. In this paper, optimum design and management of pressurized irrigation systems are considered to be based on rotation and on-demand delivery scheduling using a genetic algorithm. Comparison is made between the two scheduling techniques by application to two real irrigation systems. Performance criteria are formulated for the optimum design of a new irrigation system and better management of an existing irrigation system. The design and management problems are highly constrained optimization problems. Special operators are developed for handling the large number of constraints in the representation and fitness evaluation stages of the genetic algorithm. The performance of the developed genetic algorithm is assessed in comparison to traditional optimization techniques. It is shown that the methodology developed performs better than the linear programming method and that solutions generated by the modified genetic algorithm show an improvement in capital cost. The method is also shown to perform better in satisfying the constraints. Comparison between on-demand and rotation delivery scheduling shows that a greater than 50% saving can be achieved in total cost at the cost of reducing flexibility in the irrigation time. Finally, it is shown that minimizing standard deviation of flow in pipes does not result in the best distribution, and therefore minimum cost, neither for systems with uniform flows or those with large variations in discharge at hydrants.

Physically based modeling of the interacting water flow during a furrow irrigation season can contribute to both a sustainable irrigation management and an improvement of the furrow irrigation efficiency. This paper presents a process based seasonal furrow irrigation model which describes the interacting one-dimensional surface–two-dimensional subsurface flow and crop growth during a whole growing period. The irrigation advance model presented in a previous study is extended to all hydraulic phases of an irrigation event. It is based on an analytical solution of the zero-inertia surface flow equations and is iteratively coupled with the two-dimensional subsurface flow model HYDRUS-2. A conceptual crop growth model calculates daily evaporation, transpiration and leaf area index. The crop model and HYDRUS-2 are coupled via its common boundaries, namely (1) by the flux across the soil-atmosphere interface; and (2) by the flux from the root zone, which is associated with the plant water uptake. We assume the water stress is the only environmental factor reducing crop development and hence final crop yield. The model performance is evaluated with field experimental data in the companion paper, Part II: Model Test and Evaluation (Wöhling and Mailhol 2007).

A physically based seasonal Furrow Irrigation Model was developed, which comprises three modules: The one-dimensional surface flow, the two-dimensional subsurface flow, and a crop model. The modeling principles of these modules, their simultaneous coupling, and the solution strategies were described in a companion paper (Wöhling and Schmitz 2007). In the current contribution, we present the model testing with experimental data from five real-scale laboratory experiments [Hubert-Engels Laboratory (HEL)], two field experiments in Kharagpur, Eastern India (KGP), one literature data set [Flowell-wheel (FW)], and data from three irrigations during a corn growing season in Montpellier, Southern France [Lavalette experiments (LAT)]. The simulated irrigation advance times match well with the observations of the HEL, FW, and KGP experiments, which is confirmed by coefficients of determination $R^2⩾0.99$ and coefficients of efficiency $C_e⩾0.7$ . Predicted recession times also match with the observations of the HEL runs, however, the values of $R^2⩾0.9$ and $C_e⩾0.6$ are lower for predicted recession times as compared to predicted advance times. In contrast to the other experiments in the study, advance times are underpredicted for the experiments in France. The established soil hydraulic parameters for this site lead to an underestimation of the actual initial infiltration capability of the soil. In the long-term simulation, however, the overall change in soil moisture storage is correctly predicted by the model and the calculated yield of $12.8\mathrm{t}{\mathrm{ha}}^{-1}$ is in very good agreement with the observations $\left(12.7\mathrm{t}{\mathrm{ha}}^{-1}\right)$ . We evaluated the sensitivity of the input parameters with regards to predicted advance time and runoff in both a $26.4\mathrm{m}$ long furrow and a long $360\mathrm{m}$ long furrow. The analysis revealed that calculated runoff is four to five times more sensitive to the inlet flow rate than to infiltration parameters. Furrow geometry parameters are most sensitive to calculated advance times in the short furrow with low infiltration opportunity time, whereas the inflow rate and infiltration parameters are more sensitive to calculated advance times in the long furrow with larger infiltration opportunity time.

Optimization of water use is a complex problem in a large scale river basin. One of the most important approaches in optimizing water use in a river basin is to find the relationship between water demand and water supply. The parameters that affect demand, supply, and the methods of evaluation of such elements are discussed in this study. Also, a method is presented for providing objective and constraint functions from considering these effects. Fuzzy logic theory is used to modify the stochastic dynamic programming (SDP) method such that an optimization model is developed for allocating water and can be defined as the “stochastic fuzzy dynamic programming (SFDP)” method. This method is applied to optimize water use in the Kor and Seevand river basins, located in the Bakhtegan watershed, Fars, Iran. The primary water resources management consisted of the variability ranges of decision variables such as release from Doroodzan Dam and reservoir storage and was also used for allocating water in these river basins based on the SDP method. Therefore, in the present study, these variability ranges are obtained based on historical data, and divided into several record classes. Optimum class of release, a case of the record classes, was obtained from the optimization model for each month during the past 4 out of 25 years. Although, the SFDP method can be used in optimizing water allocation during each period, the method is structured and discussed only during the drought periods (4 years). Later, a comparison was made between optimum classes and record classes that were operated during the primary water resources management. During this period, the SFDP method reduced the difference between the release from the dam and the total water demand of the river basin. Therefore, approximately a 27% improvement in adaptation between release and demand could be attained. Finally, if the decision maker makes the decision for the release from the dam that is optimal according to our objective function, the reliability of reservoir operating can be increased by 51% during future droughts.

Traditional irrigation zones in the east of Spain have been denoted by the high level of parcellation. The layout of the irrigation network design in highly parcelled territories presents an important degree of difficulty, the previous experience of the designer in this task being crucial in the final result. In this work, a new heuristic algorithm for layout of the irrigation network design is presented. We start from a classical graph theory algorithm (Dijkstra’s algorithm) used for solving the shortest path spanning tree problem. This algorithm is modified to assign weights to the arcs and plot limits are used as if they were the arcs of a graph. The algorithm is implemented on a geographical information system, thus creating an application that automatically generates the layout of the irrigation network design. The only necessary initial data are the origin of the network (supply point) and the hydrants (delivery points). The advantage of this heuristic is that the subjectivity introduced for the designer is removed. Moreover, it allows for solving complex problems, and therefore it is applicable to highly parcelled zones, where the number of vertices and edges is so high that it would inhibit calculating capacity of any optimization process. A practical example is presented, in which the layout design obtained by applying the heuristic is compared with the original existing layout.

Four permeable pavement applications in North Carolina’s Coastal Plain were constructed and monitored to determine their effectiveness of reducing runoff quantity and improving water quality. Sites were either constructed of permeable interlocking concrete pavers (2), porous concrete (1), or concrete grid pavers (1). One site of each pavement type was monitored for runoff reduction for periods ranging from 10 to 26 months. Measured runoff depths from rainfall events over $50\mathrm{mm}$ were used to determine permeable pavement equivalent curve numbers for the sites, which ranged from 45 to 85. Only the two permeable interlocking concrete pavement (PICP) sites were monitored for water quality. Runoff and exfiltrate samples were intended to be collected, in addition to runoff monitoring, from the Swansboro PICP site. However, no runoff was produced during this study from the Swansboro PICP site for rainfall events up to $88\mathrm{mm}$ . From exfiltrate concentrations, nutrient retention was estimated to be 3.4 and $0.4\mathrm{kg}∕\mathrm{ha}∕\mathrm{year}$ for total nitrogen and total phosphorus, respectively. For the Goldsboro PICP site, water quality of asphalt runoff and PICP exfiltrate were compared. Analysis of water quality samples from the second site determined that concentrations of total Kjeldahl nitrogen, ammonia, total phosphorus, and zinc were significantly $(p⩽0.05)$ lower in permeable pavement exfiltrate than asphalt runoff.

Infiltration Best Management Practices (BMPs) are becoming more readily acceptable as a means of reducing postdevelopment runoff volumes and peak flow rates to pre-construction levels, while simultaneously increasing recharge. However, the design, construction, and operation of infiltration basins to this point have not been standardized due to a lack of understanding of the infiltration processes that occur in these structures. Sizing infiltration BMPs to hold and store a predetermined volume of runoff, typically called the Water Quality Volume, has become a widely accepted practice. This method of sizing BMPs does not account for the infiltration that is occurring in the BMP during the storm event; which could result in significantly oversized BMPs. The objective of this study was to develop a methodology to simulate varying infiltration rates observed from a large scale rock infiltration basin BMP. The results should aid in improved design of such structures. This methodology is required to predict the performance of these sites using single event and continuous flow models. The study site is a Pervious Concrete Infiltration Basin BMP built in 2002 in a common area at Villanova University. The system consists of three infiltration beds filled with coarse aggregate, lined with geotextile filter fabric, overlain with pervious concrete and underlain by undisturbed silty sand. The BMP is extensively instrumented to facilitate water quantity and quality research. The infiltration performance of the site is the focus of the study. Recorded data indicates a wide variation of linear infiltration rates for smaller storm events. A model was developed using the Green–Ampt formula to characterize the infiltration occurring in the basin for small storm events characterized by an accumulated depth of water in the infiltration bed of less than $10\mathrm{cm}$ . The effectiveness and accuracy of the model were measured by comparing the model outputs with observed bed water elevation data recorded from instrumentation on site. Results show that for bed depths of $<10\mathrm{cm}$ , hydraulic conductivity is the most sensitive parameter, and that the storm event measured infiltration rate is substantially less then the measured saturated hydraulic conductivity of the soil. The governing factor affecting hydraulic conductivity, and subsequently, infiltration rate is temperature; with higher rates occurring during warmer periods, affecting the infiltration rate by as much as 56%.

A simple procedure is proposed, using a linear transform, for obtaining a single representative effective rainfall hyetograph (ERH) and the corresponding direct runoff hydrograph (DRH) by processing multistorm data. Using these representative ERH and DRH, the representative parameters of the two-parameter gamma distribution instantaneous unit hydrograph (IUH) is determined by either the proposed optimization method or the conventional method of moments. The optimization method is found superior to the method of moments and yields reliable IUH. However, the method of moments is easier to apply and yields acceptable results. A two-parameter gamma distribution is used for the parametric representation of the IUH, which yields a smooth shape of the IUH. A linear programming or a least-squares approach does not yield a IUH and the UH it identifies does not have a smooth shape (oscillations are observed in the tail of the UH). The new method yields a reliable representative IUH. The use of the methods is illustrated using the published data sets.

Two irrigation water assessment methods, the USDA classification scheme and the soil infiltration potential, were applied to water from three different locations (Ankwaso, Dominase, and Prestea) of the Ankobra River basin in Ghana, to evaluate its effectiveness as a sustainable water resource for irrigation. The study classifies water from all three locations into the low salinity, low sodicity zone with Prestea and Ankwaso having waters of the highest sodicity and salinity, respectively. A classification scheme based on effects of the water on the hydraulic properties of soils reveals that water from all locations of the basin has the potential to affect the infiltration properties of soils, especially when applied over a long period of time. Linear regression analysis indicates a strong relationship between electrical conductivity (EC) and sodium adsorption ratio (SAR) at $R^2=0.773$ $(n=30)$ for Prestea. This relationship is probably due to the fact that Na, Mg, and Ca, which are the major determinants of water SAR, are also the major contributors to the water EC at Prestea, and this is probably due to surface mining activities, which encourage the weathering of calcic and albitic feldspars. Time series analysis reveals that EC and SAR for Dominase and Prestea, respectively, have increased from 1989 to 1992. On the other hand, SAR and EC have been decreasing since 1989, for the two locations. Forecast data from the time series analyses agree well with observed data, at 0.01 level of significance. Projections were made at ten time steps ahead of 1992 using time series analysis.