Journal of Irrigation and Drainage Engineering

The management of groundwater resources is a critical issue against the backdrop of the increasing water demand for agricultural, industrial, and domestic uses and dwindling water resources. Various simulation and optimization approaches have been used to solve the groundwater management problems. This paper presents an overview of the simulation and optimization modeling approaches used in groundwater resources conservation and management. The main objective of this review is to analyze simulation and optimization modeling approaches and to provide an assessment of their applications reported in literature. Conclusions are provided based on this evaluation, which could be useful for system managers and planners for selecting the suitable modeling approach for their specific uses.

The adjustment of a nutrient solution using an automated fertigation system for optimal irrigation conditions increases productivity and decreases the environmental impact of horticulture. A new generation of infrastructure for automated solution preparation is becoming more common in high-technological protected horticultural areas; for example, the direct injection of all components into the nutrient solution using a Venturi device on the irrigation headpiece is being widely used. The present study evaluates the utility of a passive mixing device that was incorporated into the circuit of the fertigation headpiece and its impact on parameters such as the electric conductivity (EC) and pH of the nutrient solution. The results suggest two important effects, as follows: (1) the device helps in the adjustment of the EC and pH in the nutrient solution, compared with values set during programming, and (2) there is a lower variation in the dispersion between the maximum and minimum values.

This study evaluated the performance of the simulateur multidisciplinaire pour les cultures standard (STICS) crop model for predicting grain yield and dry biomass of corn under three nitrogen (N) treatments—low, medium, and high N levels—applied on a conventional drainage field in eastern Canada over a 2-year period. The impacts of climate change on simulated grain corn and biomass yield in eastern Canada under tile-drained conditions was also evaluated over a 30-year future period (2040–2069). The 2008 data set was selected for calibration, whereas the 2009 data set was used for validation of the model. Corn grain yield was underestimated by $1.5–2.6\mathrm{Mg}{\mathrm{ha}}^{-1}$ for the 2 years of measurement. Total dry biomass was also underestimated by $0.9–2.6\mathrm{Mg}{\mathrm{ha}}^{-1}$. Tukey’s studentized range (HSD) test of corn grain yield indicated that yields at high and low N and high and medium N were different at the 95% confidence level. Grain and biomass production from 2040–2069 under B1 emission scenarios responded differently ($P<0.05$) for the three N treatments. A Mann–Kendall, nonparametric test performed on simulated corn grain and biomass yields attributable to climate change under B1 emission scenarios showed neither an increasing nor a decreasing trend at a 95% confidence level.

Living walls are becoming popular solutions to alleviate negative effects of urban development. They are vertical greening systems that allow vegetation to spread across a wall surface to cover a building facade or an interior wall. Because of their characteristics, irrigation becomes essential, but the infrastructure and management required differ from a regular irrigation system. This study aims to evaluate the influence of variables such as the type of substrate used, emitter flow rates, and drip line and emitter spacing on the system performance in terms of water losses and irrigation uniformity. The results show that the main differences are marked by the type of substrate used and the emitter flow rate. Higher flows are recommended when using recirculation systems, as more uniformity is achieved in spite of the higher runoff losses. In “run-to-waste” systems, the use of lower flows and short irrigation lengths (increasing the frequency) is advised. Some management recommendations such as irrigation lengths are also provided.

The concept of major direction correction is proposed, which includes complete major direction correction, major direction correction without roughness, and no major direction correction, based on the dimensional splitting expression of a two-dimensional surface water flow model in surface irrigation. The dimensional splitting finite-volume methods for basin irrigation were developed based on the major direction correction and existing dimensional splitting numerical methods, in addition to the scalar dissipation finite-volume method. The simulation performance of two-dimensional surface water flow models of basin irrigation constructed by the dimensional splitting finite-volume methods were comparatively validated and analyzed based on basin irrigation experiments. The results show that the models based on the Strang dimensional splitting methods with complete major direction correction and major direction correction without roughness have similar simulation accuracy and convergence rates with the model based on the dimensional nonsplitting finite-volume method. By comparison, the models based on the Strang dimensional splitting methods with no major direction correction and major direction correction without roughness exhibit better water conservation ability and computational efficiency than the model based on the dimensional nonsplitting finite-volume method. Consequently, the Strang dimensional splitting method with major direction correction without roughness can be used as a numerical method in the development of two-dimensional surface water flow models for basin irrigation.

The world population is increasing continuously and is expected to reach the 9.5 billion mark in 2050 from the current 7.1 billion. The importance of the groundwater resources is also increasing with the increase in population, because the quality and quantity of water resources are continuously declining because of urbanization, contamination, and climate change impact. Thus, under the current environment, the conservation and management of groundwater resources is a critical challenge for fulfilling the rising water demand for agricultural, industrial, and domestic uses. Various simulation and optimization approaches have been used to solve the groundwater management problems. Optimization methods have proved to be of great importance when used with simulation models, and the combined use of these two approaches gives the best results. The main objective of this review is to analyze combined uses of simulation and optimization modeling approaches and to provide an impression of their applications reported in literature. In addition to traditional optimization techniques, this paper highlights the application of computational intelligence techniques, such as artificial neural networks, response matrix approach, and multiobjective approach. Conclusions are drawn based on this review, which could be useful for system managers and planners for selecting the best suitable technique for their specific uses.

As regulators in the United States develop plans to mitigate microbial pollution via the design of total maximum daily load (TMDL) plans, historical data sets are often used to establish existing conditions for watersheds. Due to the revision of guidance recommending Escherichia coli (E. coli) as the preferred target indicator species in surface-water quality-monitoring programs, historical fecal-coliform concentration data are often used to estimate E. coli concentrations and loadings. Data from Raleigh and Durham, North Carolina, suggest the ratio of E. coli to fecal coliform (EC/FC) varies significantly by season throughout the year ($p<0.05$). These seasonal differences are not accounted for in most translator equations, which assume a single linear relationship between E. coli and fecal coliform regardless of season. These observations imply that seasonal translator equations may more accurately reflect the relationship between fecal coliforms and E. coli, and would thus result in the development of more accurate and effective TMDL plans.

The aim of this study was to calibrate the Diviner 2000 capacitance probe in the field and in the laboratory. Field calibration was carried out on an agro-forestry farm with soil of colluvial origin with two textural horizons, clay loam overlying clay. The same soil was used for laboratory calibration at the Universidad de Chile. Prior to calibration, the Diviner 2000 probe was normalized to obtain the scaled, or standardized, frequency (SF). For each method of calibration, three sets of soil moisture conditions were generated: dry, moist and saturated, with two replicates per set. The soil was evaluated with the probe at two depths per horizon, and the volumetric water content ($\theta$) was immediately determined gravimetrically in situ at each depth. To calibrate the probe, the $\theta$ values for the samples were compared with the SF values recorded by the probe and the coefficient of determination was determined through regression analysis. A nonlinear correlation was found between the SF measured by the probe and the $\theta$ values obtained through gravimetry for each horizon and method of calibration, with adjustment to a potential function with a high coefficient of determination (field: $R^2=0.77$; laboratory: $R^2=0.98$). The manufacturer’s calibration equation proved to be quite precise in laboratory conditions, but in field conditions it underestimated the water content of both clay loam and clay soil.

A water quality research facility located at Parking Lot K on the Auraria campus of the University of Colorado, Denver was used to create a calibrated hydraulic model that represents rainfall and runoff from a small, developed urban watershed. The calibrated model was used to test effective impervious values that have been proposed in previous research. Field tests included a hydraulic model that was calibrated with 3 years of recorded rainfall and runoff data and four case studies. Each case study compared the theoretical development of paved area reduction factors with two types of storm water low-impact development practices, a porous pavement section, and water quality pond. These two types of storm water best management practices have been defined as a conveyance-based and storage-based reduction factors in previous studies. This study found a strong correlation with theoretical reduction factors when they are compared to measured rainfall events and also when design storm distributions are applied to the calibrated field model. Four case studies presented in this paper conclude that the reduction factors presented in previous studies are accurate and applicable to for the Denver, Colorado area. The reduction factors were also tested with more widely used unit hydrograph procedures, and it was found that the reduction factors are accurate for other hydrologic modeling procedures and storm distribution types.