Journal of Irrigation and Drainage Engineering

Various approaches based on climatological data (CD) have been used to estimate evapotranspiration (ET). A multiple regression with ordinary least square analysis (OLS) has been commonly used to assess the relatively important CD used as predictors. An optimum ridge regression analysis (OPT) is introduced to overcome the problem caused by the OLS analysis when multicollinearity exists among the CD. An ideal method used for ET estimation should be chosen based as minimally as possible on the input of the CD variables without affecting the accuracy of estimation, so that not only can the multicollinearity problem be eliminated but also the CD availability can be improved considerably. Particularly, a model based on two variables of air temperature and solar radiation can provide a quite satisfactory estimation of the ET in southern Florida for irrigation requirement prediction. The technique developed can be used to improve the assessment of the relative importance of the CD used not only for developing a better ET equation but also for improving future programs of the weather data collection.

A skimming well is a partially penetrating well in a thin unconfined layer of fresh water which overlies saline water in an aquifer. A three‐dimensional, unconfined, transient miscible flow model of skimming well operation, involving both ground‐water flow and the mass transport of salt, is presented here. The Galerkin finite element method is used in spatially discretizing the model; transient aspects are modeled via finite differences. The primary computational features of this model are described that make it feasible to operate the model computer program on a moderate‐size computer. Preliminary results show that the magnitudes of the changes in the salinity of the pumped well water do significantly depend on the local geometry of the well and aquifer.

Based on Jensen‐Haise's formula, an equation is recommended for predicting reference evapotranspiration (ETR) under extremely arid conditions. This equation is reached by comparing and evaluating selected estimation methods with results obtained from measured reference evapotranspiration, ETR. Monthly values of ETR are estimated by each of the selected methods using climatic data collected from four observation stations within the area under study. In spite of the satisfactory correlation obtained between values estimated from different methods at the same station as well as the same method in different stations, considerable differences are found in the numerical ETR values suggested by each of these methods. Such differences are very serious when noting that most of these methods are currently used for estimating irrigation water requirements, in many extremely arid areas where the main source of water could be a limited storage of nonrenewable groundwater. In such circumstances future disappointments are sure to be confronted since all of the selected estimation methods indicate much lower ETR values than those obtained by direct measurements.

Methods from calculus may be used to determine a channel cross section which minimizes hydraulic resistance or alternatively, determines the least cost channel dimensions. In either case, established procedures ignore channel freeboard. The traditional methods of channel geometry optimization are reformulated to include freeboard considerations. The results are shown to revert to traditional solutions when the freeboard parameter is set to zero. A graphical solution is provided to simplify the resulting equations.