Journal of Irrigation and Drainage Engineering

A method for modeling flow regime changes at gate structures in canal reaches is presented. The methodology consists of using an approximate Riemann solver at the internal computational nodes, along with the simultaneous solution of the characteristic equations with a gate structure equation at the upstream and downstream boundaries of each reach. The conservative form of the unsteady shallow-water equations is solved in the one-dimensional form using an explicit second-order weighted-average—flux upwind total variation diminishing (TVD) method and a Preissmann implicit scheme method. Four types of TVD limiters are integrated into the explicit solution of the governing hydraulic equations, and the results of the different schemes were compared. Twelve possible cases of flow regime change in a two-reach canal with a gate downstream of the first reach and a weir downstream of the second reach, were considered. While the implicit method gave smoother results, the high-resolution scheme—characteristic method coupling approach at the gate structure was found to be robust in terms of minimizing oscillations generated during changing flow regimes. The complete method developed in this study was able to successfully resolve numerical instabilities due to intersecting shock waves.

Numerical simulations of free-surface flows are important to provide a prediction tool for the optimal management of irrigation canals. Here, we consider an alternative to solving the shallow-water equations. We propose a free-surface model in which the vertical component of the water current is fully resolved. We believe that such a detailed description can be useful to model the flow around gates or in other situations where the vertical structure of the flow will be important such as in the case of sediment transport and deposition. Our approach is based on a two-fluid lattice Boltzmann model. We compare the predictions obtained from numerical simulation and experiments performed on a laboratory microcanal facility.

Storage and release functions of western U.S. traditional river valley irrigation systems may counteract early and rapid spring river runoff associated with climate variation. Along the Rio Grande in northern New Mexico, we instrumented a 20-km-long irrigated valley to measure water balance components from 2005 to 2007. Hydrologic processes of the system were incorporated into a system dynamics model to test scenarios of changed water use. Of river water diverted into an earthen irrigation canal system, some was consumed by crop evapotranspiration (7.4%), the rest returned to the river as surface return flow (59.3%) and shallow groundwater return flow that originated as seepage from canals (12.1%) and fields (21.2%). The modeled simulations showed that the coupled surface water irrigation system and shallow aquifer act together to store water underground and then release it to the river, effectively retransmitting river flow until later in the year. Water use conversion to nonirrigation purposes and reduced seepage from canals and fields will likely result in higher spring runoff and lower fall and winter river flow.

To sustain productive irrigated agriculture with limited water resources requires a high water use efficiency. This can be achieved by the precise scheduling of deficit irrigation systems taking into account the crops’ response to water stress at different stages of plant growth. Particularly in the light of climate change with rising population numbers and increasing water scarcity, an optimal solution for this task is of paramount importance. We solve the corresponding complex multidimensional and nonlinear optimization problem, i.e., finding the ideal schedule for maximum crop yield with a given water volume by a well tailored approach which offers straightforward application facilities. A global optimization technique allows, together with physically based modeling, for the risk assessment in yield reduction considering different sources of uncertainty (e.g., climate, soil conditions, and management). A new stochastic framework for decision support is developed which aims at optimal climate change adaption strategies in irrigation. It consists of: (1) a weather generator for simulating regional impacts of climate change; (2) a tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (3) mechanistic models for rigorously simulating water transport and crop growth. The result, namely, stochastic crop-water production functions, allows to assess the impact of climate variability on potential yield and thus provides a valuable tool for estimating minimum water demands for irrigation in water resources planning and management, assisting furthermore in generating maps of yield uncertainty for specific crops and specific agricultural areas. The tool is successfully applied at an experimental site in southern France. The impacts of predicted climate variability on maize are discussed.

A vital key to the development of a reservoir eutrophication management strategy is to link the watershed-nutrient model to the model of reservoir water quality. To develop a cost-effective optimization model, a coupled watershed-reservoir model with an optimization model has been developed to design control strategies in the watershed in a planning time horizon. This methodology can help reduce the phosphorus concentration of a reservoir to the standard level. In this study, the weather data for the next 10 years was generated using downscaled GCM data to simulate the watershed phosphorus load using the SWAT model. Then an optimal model for selection and placement of best management practices (BMP) at watershed scale is developed by linking the coupled watershed and reservoir models with a genetic algorithm. This model is able to identify the minimum present cost design (type and location) of BMP structural alternatives. The objective of water quality is obtained using a system dynamic model for reservoir phosphorus concentration to determine a permissible phosphorus load as the main agent of eutrophication in a reservoir. Structural BMPs in this study include, filter strips, parallel terraces, grade stabilization structures, and detention ponds. The optimum solution was obtained through a trade-off curve between cost and exceedance magnitude from the standard of reservoir phosphorus concentration. The case study is the Aharchai River Watershed upstream of the Satarkhan Reservoir in the northwestern part of Iran.

Storm water control measures (SCMs), also known as best management practices (BMPs), such as rain gardens, are designed to infiltrate storm-water runoff and reduce pollutant transport to surface waters. The life span of these SCMs may be limited depending on the composition of sediments in runoff water. Settling of fine sediments may clog soil pore spaces, reducing the infiltration capacity of the soil and reducing the potential benefits of this SCM. A study was conducted on a Villanova campus rain garden that accepts runoff from an adjacent parking lot to determine if there was a relationship between the accumulation of fine sediments over time and the infiltration capacity. The soil textural profile within the rain garden was characterized prior to SCM installation (2001), after installation, after five years, and after seven years of receiving storm-water runoff. Infiltration data were collected by the single-ring infiltrometer method in 2006 and 2009. Differences in soil texture were found between locations within the infiltration basin, and accumulation of fines smaller than 0.1 mm was observed at both locations sampled in 2009. Infiltration rates were significantly different between the two locations measured within the rain garden, but infiltration rates did not change significantly over time within those regions. This SCM was designed at a 10:1 watershed to SCM area ratio, which is twice what is recommended by the PA DEP BMP Manual. The data collected over the seven years since installation indicate that while fines have accumulated in the SCM there has been no significant change in infiltration potential.

Finite aquifer solution exists for the constant head in a fully penetrating well. Their use for well recharge is limited, as they do not permit simultaneous computation of unsteady wellhead pressure and variable recharge rate. In the present paper semianalytical solutions are presented for well recharge under variable head boundary condition. These solutions were developed using the method of separation of variables and Duhamel’s convolution theorem. The solution developed in the paper was verified with the Jacob-Lohman solution and subsequently validated using field data pertinent to constant-head boundary conditions. Subsequently for variable head boundary condition such an appropriate background was found missing in the literature.