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Efficient management of irrigation/drainage systems relies to a large extent on the ability to predict a priori the response of the system to a proposed management plan. However, such numerical prediction of system response (e.g., root-zone hydrosalinity conditions and crop yield) are dependent on several parameters that are spatially and/or temporally variable and are related to soil properties, atmospheric conditions, crop type, and the amount and salinity of water application. This paper presents enhancements to the Colorado State University Irrigation And Drainage (CSUID) model that expand its capacity to fully simulate the dynamics of variably saturated flow and transport in a three-dimensional (3D) variably saturated porous media and to account for spatial and temporal heterogeneity in input parameters. The CSUID model has the ability to simulate irrigation/drainage activities and their impact on the soil and underlying groundwater, as well as on crop yield, taking into account the spatial and temporal variability in available soil moisture, including matric stress, waterlogging, and osmotic stress due to salinity. Having a model with these capabilities is an important step towards understanding the influence of heterogeneous inputs and parameter uncertainty on the design and management of field-scale irrigation/drainage systems. Four benchmark problems are used in this paper to test the CSUID model and the model performs well. In addition, an example is presented to demonstrate model capabilities in representing a 3D time-varying irrigated field with and without subsurface drainage. [ABSTRACT FROM AUTHOR]

Landscapes continuously irrigated without proper drainage for a long period of time frequently experience a rise in water-table levels. Waterlogging and salinization of irrigated areas are immediate impacts of this situation in arid areas, especially when groundwater salinity is high. Flooding and heavy rainfall further recharge groundwater and accelerate these impacts. An understanding of regional groundwater dynamics is required to implement land and water management strategies. The purpose of this study is to quantify the impact of flood and rain events on spatial scales using a geographic information system (GIS). This paper presents a case study of shallow water-table levels and salinity problems in the Wakool irrigation district located in the Murray irrigation area with groundwater average electrical conductivity greater than 25,000 μS/cm. This area has experienced several large flood events during the past several decades. Piezometric data are interpolated to generate a water-table surface for each event by applying the Kriging method of spatial interpolation using the linear variogram model. Spatial and temporal analysis of major flood events over the last four decades is conducted using calculated water-table surfaces to quantify the change in groundwater storage and shallow water-table levels. The drainage impact of a subsurface drainage scheme partially covering the area has also been quantified in this paper. The results show that flooding and local rainfall have a significant impact on shallow groundwater. The study also found that postflood climatic conditions (evaporation and rainfall) play a significant role in the groundwater dynamics of the area. The spatial net average groundwater recharge during the flooding events ranges from 0.19 to 0.52 ML/ha. The GIS-based techniques described in this paper can be used for net recharge estimation in semiarid regions where it is important to quantify net recharge impacts of regional flooding and local rainfall. The spatial visualization of the net recharge in a GIS environment can help prioritize management actions by local communities. [ABSTRACT FROM AUTHOR]

Surface fertigation is widely practiced in irrigated crop production systems. Lack of design and management tools limits the effectiveness of surface fertigation practices. The availability of a process-based coupled surface–subsurface hydraulic and solute transport model can lead to improved surface fertigation management. This paper presents the development of a coupled surface–subsurface solute transport model. A hydraulic model described in a previous paper by the writers provided the hydrodynamic basis for the solute transport model presented here. A numerical solution of the area averaged advection–dispersion equation, based on the split-operator approach, forms the surface solute transport component of the coupled model. The subsurface transport process is simulated using HYDRUS-1D, which also solves the one-dimensional advection–dispersion equation. A driver program is used for the internal coupling of the surface and subsurface transport models. Solute fluxes calculated using the surface transport model are used as upper boundary conditions for the subsurface model. Evaluation of the model is presented in a companion paper. [ABSTRACT FROM AUTHOR]

The development of a coupled surface–subsurface solute transport model for surface fertigation management is presented in a companion paper (Part I). This paper discusses an evaluation of the coupled model. The numerical solution for pure advection of solute in the surface stream was evaluated using test problems with steep concentration gradients. The result shows that the model can simulate advection without numerical diffusion and oscillations, an important problem in the solution of the advection–dispersion equation in advection dominated solute transport. In addition, a close match was obtained between the numerical solution of the one-dimensional advection–dispersion equation and a simplified analytical solution. A comparison of field data and model output show that the overall mean relative residual between field observed and model predicted solute breakthrough curves in the surface stream is 16.0%. Excluding only two outlier (in the graded basin data) reduces the over all mean relative residual between field observed and model predicted breakthrough curves to 5.2%. Finally, potential applications of the model in surface fertigation and salinity management are highlighted. [ABSTRACT FROM AUTHOR]

The prediction of stream water quality (WQ) is essential to understand and quantitatively describe water quality parameters (which include physical characteristics, inorganic metallic, and nonmetallic concentrations) and their structure, watershed health, biodiversity, and ecology of a basin. The spatial variability and temporal randomness of stream water quality parameters makes the problem a complex modeling task by ordinary statistical regression methods. The determination of water quality parameters and their spatial and temporal description in stream networks is even more complex due to the stochastic nature of water flow, atmospheric conditions, meteorological patterns, and nonlocal effects of precipitation and temperature. In this paper, a statistical, geographic information system (GIS) and a neural network based water quality model is developed to study stream water quality parameter structure in a geographic framework in the United States of America (USA) consisting of stream network, watershed, and a variety of different land-use practices. Also, a novel way of representing land use in the form of land-use factor (LUF) is formulated for modeling purposes. [ABSTRACT FROM AUTHOR]

Spatial heterogeneity and measurement error in parameters representing flow and salt transport properties in irrigated and drained fields make numerical prediction of soil hydrosalinity conditions, crop yield response, and other variables prone to uncertainty. This paper presents a method to account for uncertainty of correlated regionalized parameters in simulating key performance variables using a three-dimensional (3D) flow and transport model, the Colorado State University Irrigation and Drainage (CSUID) model, coupled with multivariate Monte Carlo simulation. Sequential indicator simulation is used to generate 3D correlated realizations for hydraulic conductivity, porosity, residual water content, van Genuchten parameters, and dispersivity. Other semiempirical parameters that control crop water uptake, irrigation efficiency, and subsurface drainage conductance also are randomized. The generated ensembles for each of the considered parameters are processed with the CSUID model to obtain the spatial statistical moments of root-zone hydrosalinity conditions and relative crop yield for an irrigated and drained alfalfa field. In addition, the statistical properties of hydrographs of drainage effluent and salt concentration are explored. Results show that parameter uncertainty significantly affects the predicted hydrosalinity responses, consequently affecting uncertainty in the estimate of relative crop yield throughout the field. Spatial distributions of the coefficient of variation of the ensemble of predicted values of water table depth and soil salinity ranged from 1-21% and 12-31%, respectively, across the field at the end of the 60-day simulated period. Corresponding spatial distributions of the coefficient of variation of the predicted relative yield of alfalfa values ranged from 16-36%. With respect to the simulated period, the temporal distribution of the coefficient of variation of the drainage effluent rate and salt concentration ranged from 23-42% and 1.5-0.8%, respectively. [ABSTRACT FROM AUTHOR]

Overwetting and soil salinization processes are common in irrigated date palm orchards in Israel. Subsurface drainage systems are generally used to overcome soil salinity. Subsurface drainage models can contribute to the selection of a proper drainage system and its proper placement in the field. In this paper, the groundwater flow modeling program MODFLOW was used to simulate groundwater levels in a date palm orchard in Argaman, in the Jordan Valley, Israel. Using a three-layer groundwater flow model, the most efficient drainage system was a combination of 4.5-m depth primary drains and 3-m depth drains of different lengths installed at a different spacing between drains. Installation of this drainage system would cost approximately NIS$2.6 million, i.e., 30% less than the initially proposed project. Given certain input, a spatially distributed groundwater flow model such as MODFLOW can provide more reliable information than different analytical solutions for planning an effective subsurface drainage system. [ABSTRACT FROM AUTHOR]

A novel method for irrigation with saline water uses a polymer membrane, formed into a tube, to treat and distribute the water simultaneously. The flux of water across the membrane occurs by the process of pervaporation, during which a phase change from liquid to vapor occurs. Thus, water arrives in the soil in the vapor phase. The experimental results presented in this paper demonstrate that, contrary to previous assumptions, soil vapor flows are a significant transport mechanism during pervaporative irrigation in dry soils. The soil water sorption properties affect the rate of condensation in the soil, which in turn affects both the water distribution in the soil and the loss of water vapor to the atmosphere. The flux from the tube becomes limited by high humidities adjacent to the external surface of the membrane. Thus, enhancing condensation in the soil or increasing diffusion through the soil increases flux from the system. These findings highlight the need to consider how plants might interact with water supplied in the vapor phase. [ABSTRACT FROM AUTHOR]

Irrigated agriculture faces serious threats of waterlogging and soil salinization in the arid and semiarid regions of the world. In this paper, an integrated spatial-agro-hydro-salinity model (SAHYSMOD) was used to analyze water and salt balances of an irrigated semiarid area located in the Haryana State of India where the groundwater level is rising continuously. The calibration, validation, error analysis, and sensitivity analysis of the model parameters were performed. The sensitivity analysis revealed that hydraulic conductivity is the most sensitive model parameter for both groundwater levels and salinities, followed by effective porosity of the aquifer. The leaching efficiency of the soil is sensitive only to the groundwater salinities. The results show a good agreement between the simulated and observed groundwater levels and salinities for almost all the nodes during the calibration and validation periods. The results are also substantiated by the high R-squared values and low mean error (ME) and root mean square error (RMSE) values. On the basis of the results, it could be concluded that the SAHYSMOD performed very well in predicting groundwater levels and salinities during the calibration and validation periods. [ABSTRACT FROM AUTHOR]

Waterlogging and soil salinisation is widespread in the semiarid, irrigated areas of the world. Subsurface drainage is a useful tool in reducing these effects on crops; however, there has been negative downstream effects of drainage in the salt loads discharged to rivers, lakes, and wetlands. Thus, subsurface drainage in semiarid, irrigated areas needs to balance the demands of providing adequate waterlogging and salinity control while minimizing salt loads. Bilevel drainage, in which shallow drains are placed between deeper drains, is a potential method to meet this required balance. This paper describes the development of an analytical solution to this design approach. A previous potential theory was extended to incorporate multiple series of shallow drains placed between two deep drains. The analytical solution was then applied using the Mathematica software to provide useful information on flow rates and flow lines with varying configurations of deep and shallow drains. The theory was then used to compare spacing and drain flow characteristics between a drainage system with only deep drains and multilevel systems that combine shallow drains with deep drains. A large number of possible configurations of shallow drains between deeper drains exist. For ease of comparison, the concept of “drainage equivalence” was developed, representing the drainage discharge per unit spacing between drains. The analytical solution for bilevel drainage situations with single and multiple shallow drains between deeper drains showed that for equivalent rates of total drainage, spacing between deep drains could be increased significantly by the use of shallow drains. It also demonstrated that flow paths and drainage rates from shallow and deep drains and the total system drainage could be altered significantly by altering the number of shallow drains. This information should be useful when considering various drainage configurations to meet the dual objectives of root zone salinity control and minimization of drainage salt loads. [ABSTRACT FROM AUTHOR]

This paper presents a practical method to manage soil salinity and yield in order to obtain maximum economic benefits. The method was applied to a study area located in the southeastern part of the Arkansas River Basin in Colorado where soil salinity is a problem in some areas. The following were the objectives of this study: (1) generate classified maps and the corresponding zones of uncertainty of expected yield potential for the main crops grown in the study area; (2) compare the expected potential productivity of different crops based on the soil salinity conditions; and (3) assess the expected net revenue of multiple crops under different soil salinity conditions. Four crops were selected to represent the dominant crops grown in the study area: alfalfa, corn, sorghum, and wheat. Six fields were selected to represent the range of soil salinity levels in the area. Soil salinity data were collected in the fields using an EM-38 and the location of each soil salinity sample point was determined using a global position system unit. Different scenarios of crops and salinity levels were evaluated. Indicator variograms were constructed for each scenario to represent the different classes of percent yield potential based on soil salinity thresholds of each crop. Indicator kriging (IK) was applied to each scenario to generate maps that show the expected percent yield potential areas and the corresponding zones of uncertainty for each of the different classes. Expected crop net revenue for each scenario was calculated and all the results were compared to determine the best scenarios. The results of this study show that IK can be used to generate guidance maps that divide each field into areas of expected percent yield potential based on soil salinity thresholds for different crops. Zones of uncertainty can be quantified by IK and used for risk assessment of the percent yield potential. Wheat and sorghum show the highest expected yield potential based on the different soil salinity conditions that were evaluated. Expected net revenue for alfalfa and corn are the highest under the different soil salinity conditions that were evaluated. [ABSTRACT FROM AUTHOR]

The Lower Arkansas River (LAR) Basin in Colorado, like many intensively irrigated river basins in the Western United States, faces a variety of problems associated with inefficient irrigation, seepage from earthen canals, and inadequate drainage facilities. Upward flows from high water tables have salinized and waterlogged agricultural soils of the Valley, contributing to reduced crop yields and nonbeneficial water consumption on adjacent uncultivated lands. River water quality has also suffered since intensive irrigation of alluvial soils results in evaporative concentration and the accelerated dissolution of inherent salts and other mineral pollutants into the underlying aquifer, appearing as return flows that threaten the ecological health of the river. A geographic information system-based river basin decision-support system (River GeoDSS) has been developed and applied to the LAR Basin for assessing basinwide strategies for improving agricultural productivity, salvaging water from nonbeneficial consumptive use, and reducing solute concentrations while maintaining compliance with decreed water rights and the Arkansas River Compact between Colorado and Kansas. Development and calibration of River GeoDSS, based on extensive field data collection programs in the LAR Basin, is described herein, with a companion paper detailing its application to evaluation of a wide range of agroenvironmentally focused water management strategies. [ABSTRACT FROM AUTHOR]

Research conducted at the field and regional scales in the Lower Arkansas River (LAR) Valley of Colorado has identified water management alternatives with potential for enhancing agroenvironmental conditions in the basin by reducing waterlogging and soil salinity, salt loadings to the river, and nonbeneficial evapotranspiration in the irrigated stream-aquifer system. The LAR geospatial decision support system (GeoDSS), presented in a companion paper as a customized version of the generalized River GeoDSS, is applied to the evaluation of the feasibility and performance of water management strategies at the basin scale. The LAR GeoDSS allows comparative evaluation of management options for improving irrigation efficiency, minimizing water shortages, and improving water quality at selected control points by augmenting groundwater return flows through dynamic regulation of reservoir releases to abide by legal and administrative constraints on river operations. Results show that conditions favorable to increased agricultural productivity and water conservation can be accommodated, along with the benefits of improved river water quality through reduction of excess irrigation recharge and canal seepage and augmented subsurface drainage, without violating existing water rights and the Colorado-Kansas Interstate Compact Agreement. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop a methodology for collecting soil salinity samples. The objectives of this paper are to: (1) estimate the number of soil salinity samples needed to capture the variability in the soil salinity data with high accuracy; and (2) compare two types of satellite images with different resolutions: Ikonos with 4 m resolution and Landsat 5 with 30 m resolution. To achieve these objectives, two satellite images were acquired (one for Ikonos and one for Landsat 5) to evaluate the correlation between the measured soil salinity and remote sensing data. From the observed data, three subsets were randomly extracted with each subset containing: 75, 50, and 25% of the data for each field. These three subsets were then used in the modeling process. Ordinary least squares (OLS) (i.e., multiple regression) was used to explore the coarse-scale variability in soil salinity as a function of the Ikonos and Landsat 5 bands. A stepwise procedure was used to identify the best subset of satellite bands to include in the regression models that minimized the Akakie information criteria (AIC). Then, the spatial structure of the residuals from the OLS models were described using sample variogram models. The variogram model with the smallest AIC was selected to describe the spatial dependencies in the soil salinity data. If the residuals were spatially correlated, ordinary kriging was used to model the spatial distribution of soil salinity in the fields. A tenfold cross validation was used to estimate the prediction error for soil salinity. To evaluate the effectiveness of the models, various measures of the prediction error were computed. This study provides an accurate methodology that can be used by researchers in reducing the number of soil samples that need to be collected. This is especially valuable in projects that last several years. The results of this study suggest that the number of soil samples that need to be collected and therefore their cost can be significantly reduced and soil salinity estimation can be significantly improved by using kriging. The results also show that the Ikonos image performed better than the Landsat 5 image. [ABSTRACT FROM AUTHOR]

This paper presents a model to estimate the soil salinity for different on-farm management strategies under irrigated conditions. It is based on research in the Maniçoba irrigation scheme in northeast Brazil, where upward flow from the shallow water table is the main cause of soil salinization. The model calculates soil water and salt balances for the topsoil. It is calibrated for the topsoil of abandoned plots and for the root zone (0.9 m) of mango trees. Simulating the effect of different management scenarios on soil salinity may help to organize the switch from intensive surface irrigation to more efficient irrigation practices. [ABSTRACT FROM AUTHOR]

The interdisciplinary nature of water resources problems requires the integration of technical, economic, environmental, social, and legal aspects into a coherent analytical framework. This paper presents the development of a new integrated hydrologic-agronomic-economic model in the context of a river basin in which irrigation is the dominant water use and irrigation-induced salinity presents a major environmental problem. The model’s main advantage is its ability to reflect the interrelationships between essential hydrologic, agronomic, and economic components and to explore both economic and environmental consequences of various policy choices. All model components are incorporated into a single consistent model, which is solved in its entirety by a simple but effective decomposition approach. The model is applied to a case study of water management in the Syr Darya River basin in Central Asia. [ABSTRACT FROM AUTHOR]

Accurate calculation of horizontal diffusive transport is important in modeling temperature, salinity, sediment, and pollutant transport in estuaries and the coastal ocean. Many three-dimensional estuarine and coastal ocean models employ a so-called sigma coordinate transformation because of its useful applications with irregular bathymetry. However, for steep bottom slopes, the conventional definition of horizontal diffusion causes spurious diffusive transport. In this paper, a new formula is presented and tested for salinity diffusion in a quiescent-sloping basin under no external forces. Results indicate that this formula produces almost no spurious diffusion, so that the initial salinity field remains unchanged after a 30-d simulation. [ABSTRACT FROM AUTHOR]

Shallow bays along the fringe of an estuarine channel impact salinity distribution. The primary mechanism of impact has been termed "tidal trapping," and is a result of the phase difference between the filling and emptying of the bay and the flow in the channel. This mechanism has been proposed as a major contributor to salinity intrusion in some locations. This paper creates a conceptual model to explain the increase or decrease in salinity intrusion based upon the channel tidal waveform and the character of the adjacent bay. Two idealized scenarios are used for this explanation: (1) Standing wave in the channel with a small phase lag in the bay tide; and (2) Progressive wave in the channel again with a small phase lag between the channel tide and the bay. This conceptual approach is useful for inspecting and understanding salinity intrusion processes in a complex estuary bay setting since the form of the wave can often be determined by generally available water surface gages along the estuary. A constructed numerical model of an estuary supports the conceptual model. [ABSTRACT FROM AUTHOR]

The main focus of this study is on the near-field flow and mixing characteristics of the thermal and saline wall jets. A numerical study of the buoyant wall jets discharged from submerged outfalls (e.g., from desalination plants) has been conducted. The performance of different Reynolds-averaged Navier-Stokes (RANS) turbulence models has been investigated and various , , and other turbulence models have been studied. The results of cling length, plume trajectory, temperature dilutions, and temperature and velocity profiles are compared to both available experimental and numerical data. It was found that two models perform best among the seven models chosen in this paper. According to the results from different simulations, the paper proposes corresponding relationships and comparative graphs that are helpful for a better understanding of buoyant wall jets. [ABSTRACT FROM AUTHOR]

The quantity and quality of drainage water in areas with shallow and saline groundwater changes over time until it reaches a balance. The balance time is fairly long and depends on the characteristics of the shallow aquifer. Therefore, it is very important to simulate such phenomena in order to manage drain effluent, especially when it is supposed to discharge into the environment. In this paper, the system dynamics technique was used to simulate the performance of a drainage system in the unsteady state condition. The study used the system dynamic programming tool Vensim. The model developed in this study is capable of predicting many hydrological variables such as water table fluctuation, drainage discharge, and the salinity of drain water and ground water. The model was validated using data collected at a tile-drained experimental site irrigated with shallow ground water located in the Khuzestan province of Iran. The results show that the standard error values in determining accuracy of simulated water table level, drainage discharge, and salinity of drain water are 14.4 cm, , and , respectively. A sensitivity analysis was done to determine the response of simulated results to changes in model parameters. The results indicated a good agreement between the observed and simulated variables, and the model can be used to manage and control saline drainage water and also to prevent environmental damage. [ABSTRACT FROM AUTHOR]