Colorado State University Irrigation and Drainage System (CSUID)

CSUID Model Download Files
 
File Name Version # Date Description
csuid_v1_1_0.zip 1.1.0 8/9/2006 Current version of CSUID
csuid_v2_0_13.zip 2.0.13 11/13/2009 Beta version of new model
csuid_exmpl.zip 1.0 3/24/2004 Sample CSUID dataset with input and output.

The following documents are available:

Introduction

Irrigated agriculture has been essential in this century to provide food and fiber for an expanding population. Production per unit area of irrigated land will become more important in the future if population continues to grow. Some estimates show that world population has doubled in only 32 years and there is no indication population growth will slow down. At the same time, the productivity of many irrigation projects has been declining due to waterlogging, salinity and poor irrigation management practices. The long-term practice of intensive irrigation for cultivated areas has in many cases transformed fertile land with high crop yields to salinized soils with low fertility and reduced crop yields. Examples of the effects of this practice include the Nile Valley in Egypt, the Tigris- Euphrates Valley in Iraq and California's San Joaquin Valley in the United States.

Irrigation alters the natural hydrological cycle in arid and semiarid regions. After irrigation has been introduced the total water added to soils often exceeds evapotranspiration (ET) and this causes increases in the water table within the root zone. When the water evaporates, water will move upward from the water table. At the same time plant roots deplete water from the top soil causing an effect described as a capillary rise of water from shallow groundwater sources. This water can be used to supplement irrigated water. However, unless the land is properly managed, capillary rise from saline groundwater may cause the salinization of the soil. Salinization occurs when water moves upward through the soil and the dissolved salts move with it. Then, when the water evaporates from the soil surface or is taken into the roots of a plant the salts remain behind in the soil. Eventually, the salt build-up will cause decreased crop yields.

To solve the problem of salinization, additional irrigation water needs to be added to leach the excess salts from the root zone and drains must be installed to make a net downward movement of water. Soluble salts increase or decrease in the root zone depending on whether the net downward movements of salt is less or greater than the net salt input from irrigation water and other sources.

Control of waterlogging and salinity in arid and semiarid regions depends on integrated water management which includes irrigation, leaching and drainage. Sustained long-term crop production in areas with saline shallow water tables requires designing and managing irrigation and drainage systems conjunctively. Decisions about irrigation and drainage must take into account the consequent soil salinity and waterlogging which affects crop yields over a season.

The rate of expansion of irrigated land reached a peak of 2.3 percent per year from 1972 to 1975. It has declined since and is now less than 1 percent per year. The decline in rate of expansion is due to higher costs and lowered performance. Since projects that have adequate drainage are much more efficient with higher performance and lower costs, irrigated land can be improved for higher productivity by designing irrigation and drainage systems conjunctively with adequate modeling and considerations of all the parameters.

CSU-ID is a computer-based Decision Support System (DSS) for the design and management of conjunctive irrigation and drainage systems. The DSS can be used to improve the design and management of new irrigation projects and it can be used for the rehabilitation of existing projects. It will provide advanced technology to assist professionals in analyzing field- scale irrigation and drainage systems in semiarid and arid areas.

Software Design

CSUID runs on a PC running Windows. The graphical user interface (GUI) was developed using the "C" programming language and "Motif" and "X Intrinsic Libraries" for graphics. This GUI is based on a mouse driven approach that allows the user to select the options from the program by pressing the different mouse buttons (there are three mouse buttons on a Sun Workstation mouse). With this user friendly interface, users are freed from time-consuming tasks associated with analysis of numerical output in the form of large output files, file input, and computer program execution.

CSU-ID allows users to manipulate large amounts of spatial information required to manage irrigation and drainage systems. The user can study the spatial variability of data and the impacts of design and management decisions on an irrigation and drainage systems. CSU-ID significantly reduces the amount of effort involved in the creation and/or debugging of a input data set, and improves the understanding of the output.

Graphical User Interface

The GUI for CSUID is a combination of window, menu, and icon selections designed to allow movement quickly and easily through the model. CSUID was written to run on a Sun SPARCstation and it has been ported to a Data General UNIX workstation. The graphical user interface (GUI) was developed using the "C" programming language combined with OSF/Motif and Xt Intrinsic Libraries for the graphics. It is based on a mouse driven approach with pull-down menus and pop-up windows. The GUI makes tasks of data entry, editing, or viewing easier and faster with the provision of editing tools that allows the user to graphically specify the data. Different irrigation and drainage scenarios (drain spacing, depth from the ground surface, irrigation rate, irrigation duration, and irrigation frequency) can be easily formulated for sensitivity analysis. Moreover, the modular arrangement of the data allows the user to specify only the part of the data that needs to be edited.

The main window of the interface is shown in Figure 1. There are five pull-down menus in the menu bar along the top of the window. These pull-down menus contain the major functions of CSUID including: 1) file, provides the user the ability to save and retrieve input files in project directories, start new projects, and manage different projects in different directories; 2) edit input, allows the user to view all simulation data related to input for simulation parameters, grid spacing, drain-collector connectivity, irrigation schedule, and print controls; 3) view output, allows the user to view parameters spatially and to select the output day for viewing results; 4) run, allows the user to start the simulation program; and 5) help, a hierarchical help facility describing in detail all the options in the program.

The common options used in both editing input and viewing output are provided along the left-hand side of the main window. These options allow the user the ability to zoom into a particular area on the grid, query a grid cell, view time series data, edit the spatial input parameters, edit the boundaries, select locations where time series data are requested, blink all the cells with the same value, and show or remove grid lines. There are two additional items in the common options for viewing output; they are, selection of viewing axis (x-y, x-z, y-z) and display of all or selected boundaries (natural boundaries, drains, collectors, and basins). A map scale is provided in the main display where the spatial map is shown. A message window near the bottom of the screen displays status information about the program.

Irrigation and Drainage Systems

Historically, most irrigation and drainage systems were designed separately and the responsibility for the management of irrigation and drainage systems has generally been assigned to different agencies. But, the optimal use of irrigated agricultural lands requires irrigation and drainage systems to be designed, constructed and managed as an integrated unit. A combined system can be very complex, requiring modeling to fully understand and predict long-term performance. Irrigation practices have direct effects on the water table, drain spacing is dependent on excess water applied and rainfall, and the costs and benefits of irrigation and drainage need to be mutually considered.

Modeling Irrigation and Drainage Systems

Many of the variables affecting irrigation and drainage systems are stochastic in nature. Irrigation scheduling is based on ET, crop growth stage and available soil water. The stochastic nature of meteorological variables can be simulated using a weather generator. Generated meteorological time series can be used as input into the scheduling model. The resulting stochastic schedules generated creates uncertainty in the system behavior. Similarly, system boundary conditions, soil flow and formation properties (hydraulic conductivity, pressure-saturation characteristics, etc.), irrigation application efficiency and other parameters can be modeled as cross-correlated spatial- temporal random fields.

The Numerical Model

The numerical model is a quasi-three dimension model used as the basis for computing the spatial and temporal distributions of soil water and salinity as affected by irrigation and drainage design and management practices in the presence of a saline shallow water table. The model solves the depth-averaged Boussinesq equation for aerial flow in the saturated zone below the water table and the Richard's equation for one-dimensional vertical flow in the unsaturated zone above the water table. The mixing cell concept is used to predict advection- dominated salinity transport. Solutions are obtained via finite difference approximations of the equations at discrete grid points in the domain. In addition to calculating salinity and water distributions, the model predicts depth to the water table, upward flux from the water table, leaching efficiency, volume and salinity of drainage effluent collected, and relative crop yield. The model explicitly considers variability due to the diverse soil and crop properties and irrigation practices on multiple fields in an area. Future enhancements will allow a fully stochastic option where selected parameters (representing system boundary conditions and properties) may be modeled as cross-correlated spatial-temporal random fields.