Journal of Irrigation and Drainage Engineering

This paper addresses the impact of climate change on the volume of inflow to a reservoir and the volume of downstream water demand by considering three climate change scenarios in an East Azerbaijan river basin. The HadCM3 model was used to estimate possible scenarios of temperature and rainfall for the period 2026–2039 under an emission scenario (A2). A hydrological model (IHACRES) was first calibrated for the basin; and then, a monthly time series of future temperatures and rainfall were entered into IHACRES. In addition, a 14-year time series of monthly runoff was simulated for 2026–2039. Modeling results indicated that the average long-term annual runoff volume decreased by 0.7% relative to the base period (1987–2000). However, by assuming a nonchanging cultivation area, the average long-term annual water demand volume for crops increased by 16%. Both simulation and optimization models of reservoir operation were used. The simulation of reservoir performance in the delivery of water demand was implemented according to the standard operating policy (SOP) and by using the water evaluation and planning (WEAP) model. The three aforementioned climate change scenarios were then introduced to the WEAP, and the reservoir performance indexes (reliability, vulnerability, and resiliency) were calculated. Results showed that indexes would change in the future relative to the base. Next, for the optimal operation of the reservoir with a water supply for agricultural and environmental purposes, the minimization of total squared deficiencies in the allocation to these purposes was determined for each month and climate change scenario by the using LINGO Version 11.0 software [nonlinear programming (NLP)] algorithm. Results showed that the indexes would change.

Climate change and its impacts on hydrometeorological variables and surface runoff have been demonstrated in many investigations around the world. General circulation models (GCMs) are widely used in climate change studies; however, their applications are limited because of low resolution for regional investigations. Different downscaling models have been developed to overcome this shortcoming, but most of them cannot preserve the monthly characteristics of rainfall that are mostly important in water resources planning and management. In this study, a self-organizing Gaussian-based downscaling (SOGDS) scheme is proposed to preserve the monthly characteristics of rainfall variations. The Gaussian mixture distribution (GMD) was employed to determine the monthly rainfall class based on observed climatic predictors. The monthly characteristics of rainfall were estimated, including the number of dry days (days without rainfall) and the maximum number of wet and dry spells, by developing an artificial neural network (ANN) model. The output of the ANN model was applied to a probabilistic scheme to develop a daily rainfall time series. Finally, the generated daily rainfall time series was used to evaluate the performance of a drainage system in the northeastern part of the Tehran metropolitan area in Iran, to consider climate change impacts. The results indicated that the proposed model was capable of downscaling rainfall by preserving its statistical characteristics when compared to a statistical downscaling model (SDSM), which was used as an alternative model. The results indicated that climate change will significantly increase the flood volume/risk in the study region, which should be considered in the future planning of drainage systems in the study area.

Increasing competition for water and the desire for high-quality turfgrass require sound irrigation water management. The main objective of this study was to evaluate two types of commercially available irrigation control technologies: one based on evapotranspiration (ET) estimates and the other based on feedback from a soil-moisture sensor (SMS). Irrigation treatments were combinations of controller technology: a timer-based standard controller system (TIM), an add-on (1 set point) SMS system (SMS1), and an evapotranspiration (ET)-based system (ETB), and watering frequency: weekly, twice per week, and daily (1, 2, and 7 days per week, respectively) plus a 10th treatment of an on-demand (2 set point) SMS system (SMS2). Both irrigation efficiency and adequacy were best for the SMS2 treatment when averaged over all three years. The SMS1 treatment provided good irrigation efficiency, but irrigation adequacy suffered, most noticeably with the twice per week treatment. The ET treatment provided good irrigation adequacy, but had the poorest irrigation efficiency. SMS treatments resulted in average water savings of 39% in SMS1 treatments and 24% in the SMS2 treatment compared to the timer-based treatments, whereas the ET treatments applied 11% more water, on average, than the timer-based treatments. The weekly SMS1 treatment applied the least amount of water ($10\mathrm{mm}{\mathrm{week}}^{-1}$), whereas the twice per week ET treatment applied the most water ($26\mathrm{mm}{\mathrm{week}}^{-1}$).

Bioretention cells have been found to improve the hydrologic and water quality performance of urban impervious areas. This study recorded continuous hydrologic data from a bioretention cell in Silver Spring, Maryland, over a period of 2 years. Two evaluation methods were used to assess bioretention performance, curve number (CN) volumetric analysis, and flow-duration flow regime analysis. CN-derived Woods B and C land uses were used to analyze cell volumetric performance, and data from a nearby forested stream were used to evaluate the cell flow regime. A CN of 75 was fit to the cell outflow with relation to rainfall depth. A larger cell, from 4.5 to 8.3% of the drainage area, was required to match the CN of woods land use. Flow duration comparisons between cell outflow and forested streamflow data suggested that bioretention may not match the predevelopment hydrologic regime despite performing similarly volumetrically. The overall natural hydrologic regime, not only peak flows and flow volume, of an area should be used both as a design factor as well as a performance metric for bioretention cells and other low-impact development (LID) facilities.

Rise in groundwater and salinity levels causes water congestion and soil salinization in the root zone of the crop, which adversely affects the growth and development process of plants, leading to reduced production. Thus, water table and salinity should not be allowed to encroach and occupy root zone longer than the crop tolerance period, and a suitable technique should be adopted for its control. Subsurface drainage seems a feasible alternative to overcome such a problem. In the present study, hybrid finite analytic solution of a one-dimensional Boussinesq equation incorporating evapotranspiration has been obtained to describe spatial and temporal variation of water table between two drains in a sloping unconfined aquifer. Assuming the unsteady state drainage criteria of a 30 cm fall of water table within 2 days once it has reached near the land surface, the spacing between two drains has been computed, and the effect of slope of the impermeable barrier, evapotranspiration (ET), depth dependent reduction factor on spacing, and water table fall has been studied and discussed with the help of a numerical example. It was observed that consideration of ET and the slope of the impermeable barrier results in an increase in spacing between two drains and economizes the design. Fall of water table in the midregion computed by hybrid finite analytic solution is faster than the fall computed by existing analytical solution. Similarly, spacing between drains computed by hybrid finite analytic solution is more than the spacing computed by the existing analytical solution.

In this paper, a novel procedure is presented and demonstrated for the optimal design of rural drainage networks, based on the coupling of a genetic algorithm with suitable hydrologic and hydraulic models. The models, which allow the evaluation of water depth and discharge through the network, differ for the levels of simplification introduced into the representation of physical phenomena (rainfall-runoff transformation and flood wave propagation through channels). Their applications are shown and the use of oversimplified approaches is discussed: although very popular in practice, they can adversely affect the characteristics of the optimal network.

Flow diversion head works are constructed across rivers to divert flow into irrigation, navigation, or power generation channels. Hydraulic structures, such as weirs or barrages, are integral parts of these diversion head works. The optimal design of these hydraulic structures is generally obtained by considering the deterministic values of hydrogeological parameters. However, there is a high degree of local soil variability and imprecision in the determination of soil parameters, such as the safe exit gradient. The seepage head also exhibits a high degree of variability, depending on complex hydrological and metrological factors. This work considers the hydrogeological parameters safe exit gradient and seepage head as imprecise or uncertain. An optimization-based methodology is presented to incorporate uncertainty in the safe exit gradient and seepage head in the optimization formulation and obtain the optimum structural dimensions that minimize the total cost. The subsurface flow consideration is embedded in the optimization formulation. The nonlinear optimization formulation (NLOF) solution procedure using a genetic algorithm (GA) is implemented to demonstrate the characterization of uncertainty in design and hence, overall cost from the uncertain safe exit gradient and seepage head. The limited evaluation shows the potential applicability of the proposed methodology.

In Egypt, the government has initiated large-scale projects to reuse drainage water to face the great challenges due to its limited water resources. Taking into consideration the environmental aspects of drainage water reuse, the diffuse pollution of water resources from agricultural sources (fertilizers) is a major environmental issue. A high percentage of applied fertilizers is lost because of poor management, which leads to nutrients leaching through different crop rotations. An integrated precise tool to predict nitrate leaching is needed for the adoption of management policies to address water quality problems and to establish limits for sustainable drainage water reuse. To quantify and analyze subsurface nitrate leaching, a combination model of the system was made in DRAINMOD-N software. The study was applied to the Mashtul Pilot Area, Egypt, as a case study. In addition to analyzing subsurface nitrate leaching, the model calculated nitrate leaching for the year 2020 for the area. The modeling system combination was applied to the study site to model nitrate leaching predictions after ten years. The system combination consisted of DRAINMOD-N and Geostatistical Analyst. The study revealed that the modeling system performed well and was reliable and accurate in predicting nitrate leaching. Therefore, this system can be used to develop guidelines for drainage design and water management to control nitrate pollution. The system can potentially be used by policymakers in the long-term strategic management of large-scale irrigation development projects.

Focusing on triangular gutters with one vertical side, four issues pertaining to the design of street gutters are addressed: (1) the proper coefficient in Manning’s formula for uniform flow and friction loss in gutters; (2) adjustment of frictional resistance for spatial inflow; (3) whether uniform flow occurs in gutters with spatially increasing flow; and (4) interaction with inlets. The first of these issues is addressed by considering historical and modern information to recommend the best of two different equations that have been put forward for determining the uniform flow capacity and friction loss in gutters. The second concern is addressed for subcritical and supercritical gutter flow, for which practical, generalized numerical solutions are derived. The range of parameters for which uniform flow provides an adequate approximation is demonstrated theoretically and by example. Among the important conclusions is that the common practice of using Manning’s equation alone for such problems is not always adequate. Practical recommendations are made to address the third issue. The fourth concern is addressed by building on the material thus presented and literature information. This work has important implications for more generally regarding the characteristics and relationships for subcritical and supercritical flow in open channels.

Best management practices (BMPs) for storm water drainage systems are used to increase storm water quality and reduce the amount of storm water runoff that is generated from a developed watershed. Paved area reduction factors, referred to as PARFs, are developed in this study to determine the reduction of storm water runoff when storm water BMPs are incorporated into storm water designs. PARFs determine the amount of runoff reduction by evaluating the effective impervious values of a watershed compared to the impervious value that is commonly determined by weighting the impervious and pervious areas. This study shows that there is a difference between the effective imperviousness and area-weighted imperviousness of a watershed. It also investigates PARFs that are developed under temporally varied rainfall and infiltration parameters and presents how they can vary from PARFs that are derived using constant rainfall and infiltration rates. This study creates an effective line to relate site-effective imperviousness with the infiltration to rainfall index that was developed in previous studies. The effective line provides an easy application to determine site-effective imperviousness from area-weighted impervious values. This study also quantifies the incentives of storm water BMPs by defining the net present value when imperviousness is a basis for storm water fees. It is found that a cost savings in storm water fees can be used to encourage storm water BMPs, and that applying temporally varied rainfall and infiltration for computing PARFs can show an increase in cost savings over previous methods.