Journal of Irrigation and Drainage Engineering

The effects of some common vapor pressure deficit (VPD) and net irradiance $\left(R_n\right)$ calculation methods on the accuracy of ${\mathit{ET}}_o$ values estimated by using the standardized ASCE Penman-Monteith (ASCE-PM) equation for short grass were examined by comparing the estimated ${\mathit{ET}}_o$ values with measured ${\mathit{ET}}_o$ values in a humid climate. Sensitivity analysis showed 17% and 84% change in the estimated daily ${\mathit{ET}}_o$ values per unit change in the calculated VPD and $R_n$ values, respectively. A total of 12 VPD and 27 $R_n$ calculation methods were examined. Analyses of variance indicated lack of equality in the means of estimated ${\mathit{ET}}_o$ values obtained by different VPD and $R_n$ methods. The percent mean error in the estimated ${\mathit{ET}}_o$ values ranged from $-0.9\text{to}-8.4\%$ for VPD methods and from $-0.3\text{to}-19.7\%$ for $R_n$ methods. On the basis of the coefficient of determination $\left(r^2\right)$ and the standard error of the estimated $\left(S_{y∕x}\right)$ values, the VPD calculated from saturation vapor pressure $\left(e_s\right)$ , estimated by averaging the $e_s$ at the maximum and minimum daily air temperatures, and actual vapor pressure $\left(e_a\right)$ , estimated by using either the average of minimum and maximum relative humidity or the dew-point temperature, gave more accurate results. Net irradiance $\left(R_n\right)$ estimated by using a regression of relative short-wave solar irradiance, as well as a linear regression on the square root of $e_a$ , resulted in relatively more accurate estimates of ${\mathit{ET}}_o$ than that obtained by methods based on $e_a$ or clear-sky data alone. These results indicate that in a humid climate, some of the VPD and $R_n$ methods have a significant effect on the accuracy of the ${\mathit{ET}}_o$ estimated by using the standardized ASCE-PM equation.

Reference crop evapotranspiration $\left({\mathit{ET}}_o\right)$ is a key variable in procedures established for estimating evapotranspiration rates of agricultural crops. As per internationally accepted procedures outlined in the United Nations Food and Agriculture Organization's Irrigation and Drainage Paper No. 56 (FAO-56), using the Penman–Monteith (PM) combination equation is the recommended approach to computing ${\mathit{ET}}_o$ from ground-based climatological observations. Applying of the PM equation requires converting input climate and site data into a number of parameters, and FAO-56 recommends exact procedures for estimating these parameters. However, a plethora of alternative procedures for estimating parameters exist in literature. As a consequence, it is likely that ambiguous results may be obtained from the FAO-56 PM equation because of the adoption of such alternative (nonrecommended) supporting equations. The purpose of the present study is to evaluate differences that could arise in FAO-56 ${\mathit{ET}}_o$ estimates if nonrecommended equations are used to compute the parameters. Using historical climate records from 1973 to 1992 of a station located in the humid tropical region of Karnataka State, India, monthly ${\mathit{ET}}_o$ estimates computed by FAO-56 recommended procedures were statistically compared with those obtained by introducing alternative procedures for estimating parameters. In all, 13 alternative algorithms for ${\mathit{ET}}_o$ estimation were formulated, involving modified procedures for parameters associated with weighting factors, net radiation, and vapor-pressure-deficit terms of the PM equation. For the $240\text{-}\text{month}$ period considered, nine of these algorithms yielded ${\mathit{ET}}_o$ estimates that were in close correspondence with FAO-56 estimates as indicated by mean absolute relative difference (AMEAN) values within 1% and maximum absolute relative difference (MAXE) values within 2%. The remaining four algorithms, involving nonrecommended procedures for the vapor-pressure-deficit and net-radiation parameters, yielded considerably different ${\mathit{ET}}_o$ estimates, giving rise to AMEAN values in the range of 2 to 8% and MAXE values ranging between 8 and 28%. The results of this study highlight the need for strict adherence to recommended procedures, especially for estimating of vapor-pressure-deficit and net-radiation parameters if consistent results are to be obtained by the FAO-56 approach.

Evaporation pan $\left(E_p\right)$ data are often used to estimate reference evapotranspiration $\left({\mathrm{ET}}_0\right)$ for use in water resource planning and irrigation scheduling. This paper reviews equations to estimate ${\mathrm{ET}}_0$ from $E_p$ and provides a simpler method to make this conversion for arid climatic conditions like in California. The new method accounts for fetch differences by first adjusting the $E_p$ rates to values expected for $100\mathrm{m}$ of grass fetch. Then it relies on an empirical relationship between ${\mathrm{ET}}_0$ and the adjusted $E_p$ to determine $K_p$ values; thus, eliminating the need for relative humidity and wind speed data that are often unavailable. The method is conceptually simpler, easier to code into computer applications, and within California, it gave better results than methods based on relative humidity and wind speed. However, the method might require calibration in more humid or windier climates.

This paper presents the area and water allocation model (AWAM), which incorporates deficit irrigation for optimizing the use of water for irrigation. This model was developed for surface irrigation schemes in semiarid regions under rotational water supply. It allocates the land area and water optimally to the different crops grown in different types of soils up to the tertiary level or allocation unit. The model has four phases. In the first phase, all the possible irrigation strategies are generated for each crop-soil-region combination. The second phase prepares the irrigation program for each strategy, taking into account the response of the crop to the water deficit. The third phase selects the optimal and efficient irrigation programs. In the fourth phase of the model, irrigation programs are modified by incorporating the conveyance and the distribution efficiencies. These irrigation programs are then used for allocating the land and water resources and preparing the water release schedule for the canal network.

The resource allocation model, area and water allocation model, incorporates the concept of deficit irrigation through a variable depth irrigation approach, VDI. It uses this to allocate land and water resources optimally to different crops in a heterogeneous irrigation scheme with limited water under rotational water supply. This model was applied to a medium irrigation scheme in India as a case study, to obtain the land and water allocation plans. These optimal allocation plans were compared to those obtained by using the model with the existing approach (full irrigation with a fixed irrigation interval of 21 days in Rabi and 14 days in the summer season). The allocation plans were obtained taking into account the different parameters that were included in the model, such as crops and cropping pattern, soils, irrigation interval, initial reservoir storage volumes, efficiencies, and the outlet and canal capacities. The total net benefits were compared for the two cases of fixed cropping distribution and free cropping distribution and a sensitivity analysis was conducted on other parameters. Summaries of the allocation plans with the VDI approach are presented for the two cases. The total net benefits obtained with the VDI approach introduced in the model were found to be 22% higher than those obtained with the existing approach. The results of this study are thus indicative of the benefits of deficit irrigation and its application within irrigation schemes that have limited water supply.

Because of the increasing importance of on-demand irrigation systems, a support system for general use has been developed to aid in selecting and regulating pumping stations. This innovation will improve the balance between total costs (project and energy) and operation quality. The procedure first determines the maximum and minimum system head curves, followed by the evolution of demand curves to obtain the maximum discharge needed. Once this discharge is determined, it is possible to carry out the dimensioning and regulation of the pumping station. An easy tool to select the number of variable and fixed speed pumps has also been developed Excel and Visual Basic can be used. The results demonstrate the importance of selecting pumps that are best adapted to the system head curve. The minimum total cost solution has been obtained by using one variable-speed pump in conjunction with another operating at fixed speed.

The accuracy of runoff curve numbers (CNs) is unknown, and empirical evidence has suggested that with the current CN table, hydrological systems are being over designed—which some believe is due to a variable known as the initial abstraction coefficient $\left(\lambda \right)$ . Therefore, guidelines to produce a new CN table are needed. In order to develop this set of guidelines, the following objectives were met: Determination of CN and $\lambda$ sensitivity, assessment of the accuracy of alternative methods for determining CNs, examination of the effect of the range of data, and evaluation of the potential change in hydrologic design due to a new table. Using measured and simulated data, the methods of estimating the CN were evaluated and assessed for accuracy. A new method using concepts of lognormal frequency was developed and found to be more accurate than the current practices. It was also found that $\lambda$ is an insensitive variable when compared to the CN, and therefore, may complicate the optimal fitting of the CNs. Finally, it was determined that developing a new CN table would affect the estimation of peak discharge rates, and thus hydrologic designs. Therefore, it may be advantageous to develop a new CN table based on peak discharge measurements rather than depths of rainfall and runoff. Guidelines that should lead to a revised CN model with improved accuracy are provided.

A data reconciliation module, based on the measurements from the hydraulic network, has been recently developed and implemented in the supervisory system of the Société du Canal de Provence (SCP). The software has initially been used daily to check the measured flow on the main canal. The data reconciliation occurs just after the measurement process. The measurement network on the hydraulic system includes many sensors subject to failure or deviation and is spread over a huge area. In addition, discharge and volume measurements in open-channel hydraulic networks are characterized by large uncertainties. The objective of the data reconciliation is to take advantage of information redundancy on a system to make a cross-check of real-time measurements. By using this information redundancy, a data reconciliation module allows detection of inconsistent measurements and measurement deviations and provides corrected values whether the initial measurements are valid, biased, or invalid. A derived consequence is better scheduling of the maintenance of sensors. The results are corrected values for measured variables and proposed values for nonmeasured quantities. A statistical analysis of the results is performed. This analysis allows evaluation of the uncertainties attached to the estimated flows and volume values. It allows also detecting invalid measurements and drift of sensors and making decisions about which maintenance operations to perform.