Journal of Irrigation and Drainage Engineering

The prognostic capabilities of a lumped hydrologic modeling approach may be complicated by routing and connectivity among infiltrative and impervious surfaces. We used artificial rainfall to generate runoff from impervious and bare soil boxes arranged in series to simulate different extents and connectivity of impervious surfaces under different moisture conditions for pervious areas. Curve numbers were calculated from observed rainfall and runoff data, compared with published values, and used in the curve number infiltration algorithm in the U.S. EPA Storm Water Management Model 5 (USEPA SWMM5) to generate runoff hydrographs. Experimental curve numbers were higher than tabular USDA values, ranging from 91 to 96. Simulations of infiltration and runoff response with experimental curve numbers showed overall good agreement with observed data, although SWMM5 was unable to re-create early term infiltration patterns, and simulated runoff lagged observed, which is attributed to implicit accounting for soil moisture and other assumptions of the SWMM5 curve number application. Our results highlight some prospects for the use of curve numbers in modeling infiltration and runoff.

The use of infiltration storm-water best management practices (BMPs) has become a more commonly used approach as a means of reducing postdevelopment runoff volumes in many areas throughout the United States. Although studies regarding the performance of infiltration BMPs are emerging, much remains to be learned about their design, construction, and operation. The increase in knowledge will improve the performance and longevity of these BMPs. The performance of one such infiltration basin over a 2-year cycle is presented in this paper. The study site is a pervious concrete infiltration basin BMP built in 2002 in a courtyard common area at Villanova University. The system consists of three linked infiltration beds lined with geotextile filter fabric, filled with coarse aggregate, and overlaid with pervious concrete. The natural soil beneath the infiltration BMP is a silty sand. The BMP is extensively instrumented to facilitate water quantity and quality research. Both water-quantity and -quality results are presented. The water-quantity analysis showed that the performance of the basin was directly related to its infiltration characteristics. The infiltration rate of the silty sand is cyclic, with higher rates during warmer periods and lower rates during colder periods. The water quality analysis investigated the pollutant reduction for chloride, copper, nitrogen, and phosphorus from the inlet to the surface-water outlet of the structure, as well as differences in pollutant concentration levels between the basin, surrounding ground, and varying soil layer elevations beneath the basin. In general, the pollutant reduction to the surface waters was greater than 90% from inlet to outlet, primarily influenced by the infiltration of the storm water into the natural soils below the BMP. The pollutant concentration of the infiltrating runoff was found to be higher than expected in the area adjacent to the bed when compared to concentration levels found at a similar depth beneath the infiltration bed. Comparison of pollutant concentration levels, as the water moved from within the storage bed to the soil beneath the bed, were shown to vary, with statistical differences found for mean concentration levels of both pH and copper levels; and no statistical differences were found for conductivity, total phosphorous, and chloride at each elevation.

An important issue that integrated hydrologic models (IHMs) for river basins can address is the management of water resources in heavily inhabited and cultivated basins. To address this issue, these models need to simulate water demands and root zone flows in a basin. Irrigation scheduling models (ISMs) have been widely used by professionals to compute farm level water demands and root zone flows. Available ISMs are neither suitable for use at basin scale nor can they be easily linked to IHMs. This paper describes a new model that utilizes methods used by ISMs to compute root zone flows and water demands in river basins and can be linked to IHMs. The model was applied to a basin in California, and the simulated water demands were compared with data compiled for the basin. The differences in the results were attributed to differences in input potential evapotranspiration rates. The paper demonstrates that simulated water demands for rice are very sensitive to saturated soil hydraulic conductivity, whereas demands for other crops are sensitive to the pore size distribution index.

A study conducted by the Utah Water Research Laboratory assessed the accuracies of a wide variety of flow measurement devices currently in service. During the study, a wide variety of flow measurement devices, including flumes, weirs, and rated sections in open channel systems, were evaluated; magnetic and ultrasonic meters in closed-conduit systems were also tested. The specified design accuracies for each device are presented. Actual flow measurements were determined at 70 sites and were compared with the theoretical discharges of each device. Comparison of actual and theoretical flow indicates that only 33% of the measurement devices tested currently measure flow within manufacturer-designed specifications. Field data is presented, and possible reasons for the flow measurement errors and their corrections are discussed.

This paper presents a new method to design pressurized branched irrigation networks. This method is called recursive design and is based on application of the problem-solving technique known as backtracking to the problem of the optimum design of pressurized branched irrigation networks with a known delivery piezometric head (pipe-sizing). Recursive design is a heuristic optimizer, like genetic algorithms, and has been implemented in a fast, versatile computer application. After presenting and precisely defining the design problem, the writers review the theoretical foundations of some of the main existing design methods: maximum velocity, recommended velocity, Mougnie velocity, constant hydraulic slope, Lagrange multipliers, linear programming, Labye’s method, and genetic algorithms. Next, the writers explain what recursive design consists of and apply its methodology in detail to a simple network. In the results section, the solutions obtained by recursive design are compared with those obtained by the other design methods, giving satisfactory results. For example, in an analyzed standard network, genetic algorithms take more than 20 minutes to offer a solution, whereas recursive design offers a cheaper solution with less than 3 seconds of computation time.

Optimal crop planning and the conjunctive use of surface water and groundwater resources are imperative for the sustainable management of water resources, especially in semiarid regions. In recent years, considerable attention has been given to crop planning and water resources management under uncertainties caused by climate changes that affect irrigation planning in terms of decisions to determine the amounts of water that can/must be allocated. In this paper, optimal crop planning and conjunctive use of surface water and groundwater are developed for the Najafabad Plain, a part of the Zayandehrood River basin in west-central Iran. The fuzzy inference system (FIS) is used to account for the experience and expert judgments of decision makers and farmers to obtain optimal crop planning and cultivation with a reliable water demand based on climate conditions. In the present work, fuzzy regression is used for considering uncertainty and ambiguity in the data used in the simulation model as well as the uncertainties in interactions between surface water and groundwater. The objective function of the optimization model is to minimize shortages in supplying irrigation demands. The results are applicable to a wide range of climate conditions.

Magnetized water is obtained by passing water through a strong permanent magnet installed in or on a feed pipeline. This study was performed at Gorgan Agricultural and Natural Resources Research Center, Gorgan province, Iran, to investigate soil moisture distribution under trickle irrigation. Two main treatments of magnetic and nonmagnetic water and three subtreatments of irrigation water salts, including well water as a control, 200-ppm calcium carbonate, and 400-ppm calcium carbonate were used. The experiment was laid out with a complete randomized block design with three replications. Soil moisture distribution around the emitters were measured 24 h after irrigation during the 3-month irrigation period. The results showed that the mean soil moisture contents at depths of 0–20, 20–40, and 40–60 cm below the emitter for the magnetized irrigation water treatment were more than the nonmagnetized irrigation water treatment, and the differences were significant at the 5% level. The irrigation with magnetic water as compared with the nonmagnetic water increased soil moisture up to 7.5%, and this increase was significant at the 1% level. The effect of irrigation water salinity on soil moisture was significant. The highest soil moisture content was from the 400-ppm calcium carbonate subtreatment. The use of magnetized water for irrigation is recommended to save irrigation water.