Journal of Irrigation and Drainage Engineering

High water table and soil salinization processes are common in irrigated fields in Israel. Subsurface drainage systems are a common technique to solve soil salinity problems. Subsurface drainage models can contribute to the efficiency of the drainage system as it can assist in the selection of the proper drainage system and its proper placement in the field. In this study we used the MODFLOW groundwater flow model to simulate groundwater levels in Jahir irrigated fields, the Jordan Valley, Israel. Using a three-layer groundwater flow model, the most efficient drainage system was found to be a combination of deep drains with relief wells and a pump placed in the area with soil salinity problem and upward hydraulic pressure. It was found that simulated drainage system can yield nearly $\mathrm{200,000}{\mathrm{m}}^3$ of water per year. Given certain information, a spatially distributed groundwater flow model such as MODFLOW can provide more reliable information than different analytical solutions for planning of an effective subsurface drainage system.

Water dynamics in subsurface agricultural drainage systems are described by the Boussinesq equation for an unconfined aquifer that results from the continuity equation, the Darcy law, as well as from a hydrostatic pressure distribution hypothesis. The storage coefficient that appears in the equation is conceptualized according to the unsaturated zone that results from water table drawdown during the drainage process. The difference between drained depth and drainable depth, as well as the hydrostatic pressure distribution hypothesis, allows us to infer a relationship between storage coefficient, drainable porosity, and the soil-water retention curve. This relationship is illustrated by using the van Genuchten and Fujita–Parlange soil-water retention curves. Both resulting storage coefficient expressions are validated in an experiment reported in the literature using a numeric solution of the one-dimensional Boussinesq equation. A good description of the experimental results leads to a conclusion in which the proposed relationship between storage coefficient and the soil-water retention curve can be used in the context of studies in water dynamics in subsurface agricultural drainage systems.

Soil water retention is a critical factor influencing irrigation decisions and hence agricultural crop yields. However, information on soil water retention characteristics (SWRC) is seldom available for irrigation planning, crop yield modeling, or hydrological simulations, especially for problematic soils, such as seasonally impounded shrink-swell soils. As large scale direct measurement of SWRC is not viable due to a number of reasons, researchers have developed pedotransfer functions (PTFs) to estimate SWRC from easily measured soil properties, such as texture, organic matter content, bulk density, etc. However, PTF applicability in locations other than those of data collection has been rarely reported. One of the most recent PTFs that has shown overall reasonable predictions in evaluation studies is Rosetta, a numerical code for estimating soil hydraulic parameters with hierarchical pedotransfer functions. Relatively, the development of large databases makes it one of the widely used PTFs. If validated for spatial application, it has immense use potential in countries like India, where data on soil hydraulic properties are seldom available, a deficiency that hampers better simulations in processes, like partitioning runoff and infiltration, assessing evapotranspiration, irrigation scheduling, etc. Rosetta is also relatively flexible allowing estimation of hydraulic properties from easily available minimum input of textural fractions. This study was conducted to evaluate (1) an applicability of four widely used soil water retention functions to describe SWRC; and (2) the computer program Rosetta for its validity. Statistical indices, i.e., root mean square error (RMSE), mean absolute error, maximum absolute error, and degree of agreement $\left(d\right)$ were computed to evaluate “goodness-of-fit” of the four functions to the measured SWRC data. These indices were also used to compare measured SWRC with estimates of SWRC by Rosetta. For soil samples collected from 41 profiles, 175 SWRC were measured in the laboratory. The van Genuchten function fitted relatively better $(\mathrm{RMSE}=0.052{\mathrm{m}}^3{\mathrm{m}}^{-3})$ to SWRC of clay soils, whereas the Brooks–Corey (BC) function was better in expressing SWRC of clay loam and sandy clay loam soils with $\mathrm{RMSE}=0.06$ and $0.07{\mathrm{m}}^3{\mathrm{m}}^{-3}$ , respectively. Campbell and Cass–Hutson (CH) functions were of intermediate value. Worst performing functions were BC (clay soils), Campbell (clay loam), and CH (sandy clay loam) with corresponding $\mathrm{RMSE}=0.059$ , 0.065, and $0.077{\mathrm{m}}^3{\mathrm{m}}^{-3}$ . Estimates of two important points on the SWRC curve, i.e., field capacity and permanent wilting point were predicted with relatively better accuracy for clay and sandy clay loam soils by all the four functions. RMSE and $d$ ranged from $0.027\text{to}0.043{\mathrm{m}}^3{\mathrm{m}}^{-3}$ and from 0.73 to 0.88 for clay soils. Corresponding values for sandy clay loam soils were $0.008–0.019{\mathrm{m}}^3{\mathrm{m}}^{-3}$ , and 0.92–0.98. However, in clay loam soils, only two functions were found suitable. Estimates of SWRC obtained by applying hierarchical rules in Rosetta were reliable $(\mathrm{RMSE}<0.05{\mathrm{m}}^3{\mathrm{m}}^{-3}$ ). Magnitude of average RMSE increased progressively in clay loam, clay and sandy clay loam soils $(0.028<0.035<0.042{\mathrm{m}}^3{\mathrm{m}}^{-3})$ . The study established that SWRC of the “Haveli” soils could be estimated using generic PTF and thus information that is prerequisite in simulating hydrological processes occurring in seasonally impounded soils could be acquired.

Generalized analytical solutions for groundwater head in horizontal aquifers in the presence of parallel subsurface drains are obtained considering a transient rate of recharge as a power series (polynomial) function and depth-dependent rate of evapotranspiration. A function, new to analytical drainage studies, is proposed for correctly representing the depth-dependent rate of evapotranspiration. The solutions are obtained considering the practical situation of drains placed at a shallow depth in a considerable depth of aquifer. Two conditions of large and small saturated thicknesses in comparison to the changes in groundwater head are considered. A mathematical criterion is proposed to distinguish between large and small saturated thicknesses.

Soil-water movement due to root-water uptake, is a key process for plant growth and transport of water in the soil plant system. There are different root-water uptake models to determine the extraction rate of soil moisture by roots. The present study examines the performance of different root-water extraction models using available data as well as data generated under controlled conditions. Data pertaining to moisture uptake in respect to two crops: wheat (Triticum aestivum L.) and maize (Zea mays L.) along with soil-water characteristics have been monitored at the Indian Institute of Technology Roorkee, agricultural farm. For this purpose, a numerical model is also formulated by incorporating different moisture extraction terms as sink terms in the Richards equation. A nonlinear root-water uptake model selected as the base model was evaluated for its moisture uptake efficiency. The work establishes the merits of the base model over other extraction terms considered, particularly constant and linear extraction terms in predicting the soil moisture depletion in the root zone. The work stresses the nonlinearity parameter of the base model, which is capable of defining crop specific nonlinearity in the plant moisture uptake.

Effective water resources planning, allocation, management, and use in agroecosystems require accurate quantification of actual evapotranspiration $\left({\mathrm{ET}}_c\right)$ during growing and nongrowing (dormant) periods. Prediction of ${\mathrm{ET}}_c$ for a variety of vegetation surfaces during the growing season has been researched extensively, but relatively little information exists on evaporative losses during nongrowing periods for different surfaces. The objectives of this research were to evaluate ${\mathrm{ET}}_c$ in relation to available energy, precipitation, and grass and alfalfa-reference ET ( ${\mathrm{ET}}_o$ and ${\mathrm{ET}}_r$ ) for a maize (Zea mays. L) field and to analyze the dynamics of surface coefficients $\left(K_c\right)$ during the nongrowing period (October 15–April 30). The evaporative losses were measured using a Bowen ratio energy balance system (BREBS) on an hourly basis and averaged over $24\mathrm{h}$ for three consecutive nongrowing periods: 2004–2005 (Season I), 2005–2006 (Season II), and 2006–2007 (Season III). BREBS-measured ${\mathrm{ET}}_c$ was approximately 50% of available energy ( $R_n-G$ ; $R_n$ is net radiation and $G$ is soil heat flux density) during normal and wet seasons (Seasons I and III) and 41% of available energy during a dry season (Season II). Cumulative ${\mathrm{ET}}_c$ ranged from $133\mathrm{mm}$ in Season II to $167\mathrm{mm}$ in Season III and exceeded precipitation by 21% during the dry season. The ratio of ${\mathrm{ET}}_c$ to precipitation was 0.85 in Season I, 1.21 in Season II, and 0.41 in Season III. ${\mathrm{ET}}_c$ was approximately 50% of ${\mathrm{ET}}_o$ and 36% of ${\mathrm{ET}}_r$ in both Seasons I and III, whereas in Season II, ${\mathrm{ET}}_c$ was 32% of ${\mathrm{ET}}_o$ and 23% of ${\mathrm{ET}}_r$ . Overall, measured ${\mathrm{ET}}_c$ during the dormant season was generally most strongly correlated with radiation terms, particularly $R_n$ , albedo, incoming shortwave radiation, and outgoing longwave radiation. Average surface coefficients over the three seasons were 0.44 and 0.33 for grass and alfalfa-reference surfaces, respectively. Using geometric mean $K_c$ values to calculate ${\mathrm{ET}}_c$ using a $K_c{\mathrm{ET}}_{\mathrm{ref}}$ approach over the entire nongrowing season yielded adequate predictions with overall root mean square deviations of 0.64 and $0.67\mathrm{mm}{\text{day}}^{-1}$ for ${\mathrm{ET}}_o$ and ${\mathrm{ET}}_r$ , respectively. Estimates of ${\mathrm{ET}}_c$ using a dual crop coefficient approach were good on a seasonal basis, but performed less well on a daily basis. Regression equations that were developed (accounting for serial autocorrelation in the ${\mathrm{ET}}_c$ and ${\mathrm{ET}}_{\mathrm{ref}}$ time series) yielded good estimates of ${\mathrm{ET}}_c$ . Considering nongrowing period evaporative losses in water budget calculations would enable water regulatory agencies to better account for water use in hydrologic balance calculations over the entire year rather than only for the growing season and to better assess the progression and availability of water resources for the next growing season.

Information about the parameters defining water resources availability is a key factor in their management. Reference evapotranspiration $\left({\mathrm{ET}}_0\right)$ prediction is fundamental in planning, design, and management of water resource systems for irrigation. The application of time series analysis methodologies, which allow evapotranspiration prediction, is of great use for the latter. The objective of the present study was the comparison of weekly evapotranspiration ARIMA and artificial neural network (ANN)-based forecasts with regard to a model based on weekly averages, in the region of Álava situated in the Basque Country (northern Spain). The application of both ARIMA and ANN models improved the performance of $1\text{week}$ in advance weekly evapotranspiration predictions compared to the model based on means (mean year model). The ARIMA and ANN models reduced the prediction root mean square differences with respect to the mean year model (based on historical averages) by 6–8%, and reduced the standard deviation differences by 9–16%. The variations in the performances of the prediction models evaluated depended on the weekly evapotranspiration patterns of the different months.

Three years of daily reference evapotranspiration measured by atmometers $\left({\mathrm{ET}}_g\right)$ were compared to the values computed from the ASCE standardized Penman–Monteith equation $\left({\mathrm{ET}}_r\right)$ using co-located meteorological measurements at 19 locations across North Carolina. The atmometers underestimated daily ${\mathrm{ET}}_r$ by an average of 21% across the study area. Linear regression models between ${\mathrm{ET}}_g$ and ${\mathrm{ET}}_r$ had intercepts significantly different from zero and slopes different from one, but would generally yield a gauge error within $1\mathrm{mm}{\text{day}}^{-1}$ . The ${\mathrm{ET}}_g\text{-}{\mathrm{ET}}_r$ relationship was found to be highly sensitive to precipitation and wind speed, but rather insensitive to humidity, radiation, and temperature. Although wind speed is generally low in the study area, the insensitivity of ETgages to wind caused severe underestimation in those periods when wind speed was high. Mean absolute error increased from 17% when wind speed was below $1\mathrm{m}{\mathrm{s}}^{-1}$ to 64% when wind speed was greater than $5\mathrm{m}{\mathrm{s}}^{-1}$ . Precipitation can temporarily disrupt ETgage evaporation and cause underestimation of ${\mathrm{ET}}_r$ . The linear relationship between ${\mathrm{ET}}_g$ and ${\mathrm{ET}}_r$ in rainy days was significantly different than that of the clear days. Analysis of the local relationships suggested that they are sensitive to their major surrounding physiographic environment and to the strictly local surface conditions, but not to the intermediate mesoscale surface environment. As a result, different linear regression equations were developed to adjust ${\mathrm{ET}}_g$ to ${\mathrm{ET}}_r$ in three land regions and in dry or wet conditions.

The SADREG decision support system was developed to help decision makers in the process of design and selection of farm surface irrigation systems to respond to requirements of modernization of surface irrigation—furrow, basin, and border irrigation. It includes a database, simulation models, user-friendly interfaces, and multicriteria analysis models. SADREG is comprised of two components: design and selection. The first component applies database information, and through several simulation and computational tools, produces a set of design alternatives in agreement with the user options. These alternatives are characterized by several hydraulic, economic, and environmental indicators that allow appropriate selection and ranking. The selection component bases upon multicriteria analysis using composite programming and ELECTRE II ranking models, which support the decision maker to select the best alternative. The decision maker participates in all decision processes through a user-friendly interface that allows expressing design options and priorities. SADREG was tested with data collected from field experiments. In addition to describing the modeling approach, an application to a sector of the Lower Mondego Irrigation Project, Portugal, is presented.

A channel cross section with parabolic sides and horizontal bottom has been recently published and proved to be more economical (provide lesser construction cost per unit length) than the trapezoidal cross section. This paper presents a new and improved cross section with two-segment parabolic sides and horizontal bottom. Each side of the cross section consists of two parabolic segments smoothly connected. Closed-form relationships for the cross-sectional area and perimeter are developed. For specific parameter conditions, the new cross section produces most of the common cross sections, including the parabolic sides—horizontal bottom and trapezoidal cross sections, as well as new cross-sectional shapes. It provides an additional degree of freedom in determining the optimal cross-sectional design. A spreadsheet-based optimization model for the new cross section that minimizes the total construction cost (excavation and composite linings) is developed. The constraints of the model include channel discharge and physical requirements, such as flow depth, top width, and side slope with fixed or depth-dependent freeboard. The model was validated and the cross-sectional performance was evaluated using different design scenarios. The optimization results show that the new cross section is more economical and more flexible than a cross section with (one-segment) parabolic sides. As such, it should be of interest to the irrigation and drainage engineers.

Block ramps are permeable hydraulic structures. Flow that enters the block ramp infiltrates between the blocks and eventually on the porous base material on which the ramp is posed. The percentage rate of subsurface flow with respect to the total flow at the entrance of a block ramp or a rock chute is studied experimentally and analyzed by means of dimensional analysis. This quantity is described as a function of related parameters, such as the total inflow discharge, the particles’ characteristics, the thickness of the base material bed, the geometric characteristics of the block ramp, and the boundary conditions at the toe of the ramp itself. The experimental data were elaborated in order to supply new formulations of the flow discharge through the base ramp material and the block ramp energy dissipation. The amount of energy losses of such structures is essentially a function of the geometry and the bed surface characteristics of the ramp, the hydraulic conditions, and the percentage rate of the subsurface flow.

A variably saturated soil moisture flow model is developed for planted soils with depth varying properties by incorporating a nonuniform macroscopic root water uptake function. The model includes spatial and temporal variation of the root density with dynamic root growth for simulating water uptake by plants along with the impact of soil moisture availability. The governing partial differential moisture flow equation integrated over the depth with a plant water uptake term is solved numerically by the implicit finite difference method using an iterative scheme. The model is first tested for barren soils for two profiles considering constant and depth varying soil characteristics under constant inflow condition. The results obtained are later tested with experimental data available in the literature. A nonuniform plant water uptake term is subsequently incorporated in the model and water uptake by wheat plants under different soil moisture availability conditions is studied. Finally, the moisture flow model is validated with field data of rain fed wheat (Triticum aestivum) using a dynamic root growth model for a layered root zone soil profile. The simulated soil moisture regime of the layered root zone shows a reasonably good agreement with the observed data.

The hydraulic transition between nonorifice and orifice flow regimes at a rectangular sluice gate was analyzed to determine the value of a coefficient $\left(C_o\right)$ used to define the threshold between the two regimes. The transition coefficient was defined as the ratio of vertical gate opening to upstream water depth. Several dozen data sets were collected in a hydraulic laboratory, each including the measurement of upstream and downstream water depth for five different vertical gate openings, and 17 different steady-state discharges from $0.02\text{to}0.166{\mathrm{m}}^3∕\mathrm{s}$ . Various approaches were tested to define the limits of the nonorifice-to-orifice regime transition, but the one presented herein uses the specific-energy equation for open-channel flow. After the transition limits were defined, an estimation of the nonorifice-to-orifice transition coefficient, $C_o$ , was made. The experimental results indicate that orifice flow always exists when $C_o$ is less than 0.83, and nonorifice flow always exists when $C_o$ is greater than 1.00. A procedure was developed to determine the flow regime and the discharge at a rectangular gate in the range $0.83<C_o<1.00$ .

The approach by the author for modeling the large-diameter wells using MODFLOW is extended to the partially penetrating large-diameter wells. The temporal variation of drawdown due to a steady pumping is presented in the form of diagnostic curves for different penetration. These diagnostic curves can also be used to estimate the aquifer parameters from the observed drawdowns in a partially penetrating large-diameter well.