Journal of Irrigation and Drainage Engineering

This paper describes the application of artificial neural networks (ANNs) for estimating reference evapotranspiration $\left({\text{ET}}_{\mathrm{o}}\right)$ as a function of local maximum and minimum air temperatures as well as exogenous relative humidity and reference evapotranspiration in different continental contexts of the autonomous Valencia region, on the Spanish Mediterranean coast. The development of new and more precise models for ${\text{ET}}_{\mathrm{o}}$ prediction from minimum climatic data is required, since the application of existing methods that provide acceptable results is limited to those places where large amounts of reliable climatic data are available. The Penman-Monteith model for ${\text{ET}}_{\mathrm{o}}$ prediction, proposed by the FAO as the sole standard method for ${\text{ET}}_{\mathrm{o}}$ estimation, was used to provide the ANN targets for the training and testing processes. Concerning models which demand scant climatic inputs, the proposed model provides performances with lower associated errors than the currently existing temperature-based models, which only consider local data.

This study investigates the ability of fuzzy genetic (FG) approach in modeling of reference evapotranspiration $\left({\text{ET}}_0\right)$ . The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed from three stations, Windsor, Oakville and Santa Rosa, in central California, are used as inputs to the FG models to estimate ${\text{ET}}_0$ obtained using the FAO-56 Penman-Monteith equation. A comparison is made between the estimates provided by the FG and those of the following empirical models: the California Irrigation Management System Penman, Hargreaves, Ritchie, and Turc methods. The FG results are also compared with the artificial neural networks. Root-mean-square errors (RMSE), mean-absolute errors (MAE), and correlation coefficient statistics are used as comparing criteria for the evaluation of the models’ performances. The comparison results reveal that the FG models are superior to the ANN and empirical models in modeling ${\text{ET}}_0$ process. For the Windsor, Oakville, and Santa Rosa stations, it was found that the FG models with ${\text{RMSE}}_W=0.138$ , ${\text{MAE}}_W=0.098$ , and $R_W=0.999$ ; ${\text{RMSE}}_O=0.144$ , ${\text{MAE}}_O=0.102$ , and $R_O=0.999$ ; and ${\text{RMSE}}_S=0.167$ , ${\text{MAE}}_S=0.115$ , and $R_S=0.998$ in test period is superior in modeling daily ${\text{ET}}_0$ than the other models, respectively.

Overirrigation of lawns with limited resources of potable water has increasingly become an issue for the state of Florida. A previous study showed that soil moisture sensors systems (SMSs) could lead to irrigation water savings during relatively wet/normal weather conditions. This research, as a follow-up comparison, was conducted under dry weather conditions. The first objective was to statistically evaluate the water savings potential of different commercially available SMSs during the first half of 2006. In the second half, the objectives were to quantify irrigation water use and to evaluate turfgrass quality differences among: (1) a time-based irrigation schedule system with and without a rain sensor; (2) time-based schedules compared to SMS-based systems; and (3) SMS-based systems under different irrigation frequencies. The experimental area was located in Gainesville, Fla. and consisted of common bermudagrass [Cynodon dactylon (L.) Pers.] plots. Four commercially available SMSs (brands Acclima, Rain Bird, Irrometer, and Water Watcher) were used to bypass scheduled irrigation cycles when the soil water content at the 7- to 10-cm depth was above field capacity. Time-based treatments with and without rain sensor feedback were set up as comparisons for irrigation depth applied, and a nonirrigated treatment for turf quality comparison purposes was implemented. Due to the dry weather conditions and/or infrequent rain events during the experiment, the nonirrigated plots (as well as a broken SMS treatment) resulted in turfgrass quality below the minimum acceptable level. The rest of the treatments had at least minimum acceptable turf quality. The treatment with rain sensor resulted in 13 to 24% less water applied than without the rain sensor treatment. Most SMS-based treatments resulted in significant irrigation water savings compared to the treatment without rain sensor, which ranged from 16 to 54% in the first half, and from 28 to 83% in the second half of 2006, for three of four SMS brands tested.

Analytical solutions for groundwater head in the presence of subsurface drains are important in assessing the effectiveness of an existing drainage system under a probable extreme variation in the rate of recharge and designing a new drainage system. Generalized analytical solutions for groundwater head in inclined aquifers in the presence of parallel subsurface drains are obtained considering the transient rate of recharge as a power series (polynomial) function and depth-dependent rate of evapotranspiration. An appropriate function, new to analytical drainage studies, is used for correctly representing the depth-dependent rate of evapotranspiration. The solutions are obtained considering the practical situation of drains placed at shallow depth in a considerable depth of aquifer. Two conditions of large and small saturated thicknesses in comparison to the increase in groundwater head are considered. A mathematical criterion is proposed to distinguish between large and small saturated thicknesses. The analytical equations for discharge to drains for different cases considered are also obtained. The discharge equations used by prior investigators are found inappropriate.

A study of performance of a combined natural wastewater treatment system was conducted in an arid and semiarid area of West Texas from October 2005 to September 2007. This study investigated the organic matter and nitrogen removal capability in a municipal wastewater land application system following a pond system. Municipal wastewater from the city of Littlefield, Tex. was pretreated by a pond system, and the secondary wastewater effluent from the pond system was surface applied to sprayfield at the wastewater treatment plant and the city farm. The 16 lysimeters were installed in situ to collect the leached water passing the grass root zone. The water samples were taken from the storage pond and the lysimeters for analysis of chemical oxygen demand (COD), total nitrogen, nitrate nitrogen, and ammonia nitrogen. The data show that the pond system played an important role in the treatment. The pond system pretreated COD in the municipal wastewater to the range of 10 to 127 mg/L, total nitrogen to the range of 5 to 19 mg/L, nitrate nitrogen to the range of 2.4 to 8.2 mg/L, and ammonia nitrogen to the range of 0.01 to 6.4 mg/L. The average mass removals and cumulative mass removals were 94 and 96% for total nitrogen, 92 and 93% for nitrate nitrogen, and 96 and 100% for ammonia nitrogen, respectively. There was no potential nitrogen contamination to groundwater found during the research period. The study illustrated that this type of combined natural wastewater treatment system can be used to effectively treat and safely dispose municipal wastewater, and save freshwater used for agricultural irrigation in arid and semiarid area.

Excessive runoff and its undesirable effects (erosion, siltation, and suspended load), as well as water quality degradation in agricultural landscapes, are recurrent concerns in France. Special sediment control or pollution mitigation basins can consist of agricultural fields simultaneously ponded and subsurface drained. After having identified convenient nondimensional parameters for system description, two hydraulic methods for flow modeling and empiric design formulas are presented in this technical note for the evaluation of adequate water filtration flow rates through such remediation devices, under given hydraulic head conditions. The first method is an analytical one with an infinite soil domain and the second is a numerical one limited to the vicinity of the ponded zone. For engineering purposes, discharge capacity is given as a function of the number of drains as well as drain spacing, radius, and depth.