Journal of Irrigation and Drainage Engineering

The operation of main irrigation canals is complicated in situations in which the operator does not have full control over the canal inflow, or in which there are very long transmission distances from the point of supply, or both. Experienced operators are able to control the canal, but often supply errors are simply passed downstream, thus creating problems further down the system. In previous work, the writer showed that it is important to contain such errors and not let them pass downstream. With automatic upstream-level control, all flow errors are passed to the downstream end of the canal. Distant downstream water-level control requires full control of canal inflow. Without this, errors will occur at the upstream-most canal pool. An alternative scheme is offered here in which the canal check gates are controlled on the basis of the relative water-level error between adjacent pools. The scheme uses a simple linear model for canal pool response. The scheme is implemented as a multiple-input, multiple-output scheme and is solved as a linear quadratic regulator (LQR). Thus, all gates respond to relative deviations from water-level set point. The scheme works to keep the relative deviations in all pools the same. If inflow and outflow do not match, it effectively treats the canal as a storage reservoir. When in equilibrium, operators will be able to judge the actual flow rate mismatch by the rate of change of water levels. The scheme acts like a combination of upstream-level and distant downstream-level control. It was tested on a simulation model of the Central Main Canal at the Central Arizona Irrigation and Drainage District (CAIDD), Eloy, AZ.

The integrator-delay (ID) model is commonly used to model canal pools that do not exhibit resonance behavior. Simple step tests are often used to estimate ID model parameters; namely, delay time and backwater surface area. These step tests change the canal inflow at the upstream end of the pool and observe water depth variations at the downstream end. Some knowledge of the canal pool characteristics are needed to determine the amount of flow change and its duration. Auto tune variation (ATV) is one method for determining the duration of these step tests. Pools that are under backwater over their entire length tend to exhibit oscillations attributable to resonance waves. Random Binary Sequence (RBS) tests have been used to determine the resonance frequency of such pools, for which step tests with different durations are used. RBS tests are difficult to implement in practice and may not provide the resonance frequency. The intent of this paper is to demonstrate on a real canal that the ATV method can determine both the resonance frequency and the resonance-peak height for canal pools whose water levels oscillate.

Rain sensors are devices that connect to automatic irrigation systems to interrupt scheduled irrigation events as a result of rainfall. The accuracy of expanding-disk rain sensors over nearly five years was evaluated at a research site in north central Florida. Seven rain sensor model/rainfall set point combinations were evaluated. The seven configurations are as follows: Wireless Rain-Clik (WL) rain sensor, Mini-Clik rain sensors with rainfall set point of, 3, 6, 6, and 13 mm (3MC, 6MC, Hunter, and 13MC), Irritrol RFS 1000 at a 6-mm set point (Irritrol), and Toro TWRS at a 6-mm set point (Toro). The MC and WL configurations were evaluated for 1,182 days with four replicates. The Hunter, Irritrol, and Toro configurations were monitored 1,150 days with eight replicates. Data were collected for each configuration to determine the total time in interrupt mode. This information was compared with measured rainfall data on site. On average, the WL, 3MC, 6MC, 13MC, Hunter, Irritrol, and Toro required 3.2, 1.9, 1.6, 6.6, 3.8, 4.3, and 5.8 mm of rainfall for interrupt mode, respectively. Accuracy ranged from 27 to 97%. Rain sensor accuracy had percentile point changes from $-23$ to 25 over the study period, where a negative value indicated a decrease in accuracy. In general, rain sensors at 6-mm thresholds or less become more accurate after 560 days of installation, because they became less sensitive over time. However, rain sensors with newer expanding-disk hygroscopic material seemed to result in more accurate response and were less erratic than sensors in the field in most cases for over a year. Hygroscopic material that had been installed longer had more erratic behaviors such as going into interrupt mode with little or no rainfall. For the best accuracy and most consistent behavior, Hunter Mini-Clik and Hunter Wireless Rain-Clik rain sensors should be replaced after 1 year while Irritrol RSF 1000 and Toro TWRS rain sensors do not need to be replaced for at least three years. Rain sensors could increase water savings to homeowners and have environmental benefits but should not be used in applications requiring consistent accuracy greater than 70%.

Evapotranspiration is an integral part of the hydrologic cycle and an important component in water resource development and management, especially in the arid and semiarid conditions such as those found in Iran in which water resources are limited. The standard Food and Agricultural Organization of the United Nations (FAO)-56 Penman-Monteith (PM) equation requires several meteorological inputs for estimating reference evapotranspiration ( $E{T}_o$ ) that are not usually available in most of the stations. This paper investigates the potential of the adaptive neuro-fuzzy computing technique (ANFIS) for daily reference evapotranspiration modeling under arid conditions from limited weather data. The gamma test technique is applied to find the best input combination and number of sufficient data points for the model calibration. The training and testing data sets are chosen on the basis of the $K$ -fold method of cross-validation to obtain the optimal classifier. The estimates of ANFIS models are compared with calibrated FAO-56 reduced-set PM $E{T}_o$ approaches and some calibrated empirical $E{T}_o$ equations such as Hargreaves, Priestley-Tailor, Makkink, and Blaney-Criddle equations. The FAO-56 full-set PM is adopted as the reference $E{T}_o$ equation, and it is applied to calibrate other $E{T}_o$ equations and ANFIS models. The comparison results indicate that when similar meteorological inputs are used, the ANFIS models performed better than all the methods pursued. This fact strongly suggests using ANFIS technique as an accurate $E{T}_o$ estimator method even in the absence of complete weather data. The minimum required data to construct a good ANFIS model under arid conditions are the minimum and maximum air temperatures and wind speed data.

Development of best management practices (BMPs) such as conservation tillage and winter cover crop to mitigate runoff and reduce dissolved chemicals in irrigation runoff is an important objective for controlling surface water pollution attributable to agricultural activities. In this study, the effect of standard tillage (ST), ST with winter cover cropping (STCC), and no-till (NT) management practices on infiltration, runoff, and dissolved organic carbon (DOC) export from furrow-irrigated fields of 244-m length was investigated for summer 2007 and 2008 irrigations. The practices were implemented for 2 years. The average surface residue cover was 11, 44, and 32% for ST, STCC, and NT, respectively, for 2007 and 11, 59, and 61%, respectively, in the following year of the study. Two irrigations in each year were considered for the analysis. The runoff samples were collected from each tillage treatment using ISCO autosamplers at regular time intervals. The infiltration and runoff were estimated using a volume balance model (VBM) by considering a 0.2-m irrigation requirement. Converting from ST to STCC increased the infiltration by 14 and 43% and reduced the runoff by 48 and 43% in 2007 and 2008 irrigations, respectively; whereas, converting ST to NT enhanced the infiltration by 4% in both years and decreased the runoff by 19 and 23% in 2007 and 2008 irrigations, respectively. The authors observed only slightly higher DOC concentrations in STCC, but there was a 24% increase for NT in 2007 irrigations, and both compared to with ST ranged from 3.98 to $5.46\mathrm{mg}/\mathrm{L}$ . The DOC concentration was not significantly different among the treatments in 2008 irrigations (3.48 to $4.6\mathrm{mg}/\mathrm{L}$ ). Combining the runoff and DOC concentration effects, the DOC export for STCC was decreased by 55% in both years; whereas, it was decreased by 4 and 27% for NT in 2007 and 2008 irrigations, respectively, compared with ST. Although STCC and NT have higher concentrations, the reduction in export in these treatments is attributable to lower runoff. These results suggest that DOC export can be controlled with STCC practice. No-till showed the same trend, although these results must be confirmed after extended implementation of this practice.

The rational method for peak discharge ( $Q_p$ ) estimation was introduced in the 1880s. Although the rational method is considered simplistic, it remains an effective method for estimating peak discharge for small watersheds. The runoff coefficient ( $C$ ) is a key parameter for the rational method and can be estimated in various ways. Literature-based $C$ values ( $C_{\mathrm{lit}}$ ) are listed for different land-use/land cover (two words, no hyphen) (LULC) conditions in various design manuals and textbooks; however, these $C_{\mathrm{lit}}$ values were developed with little basis on observed rainfall and runoff data. In this paper, $C_{\mathrm{lit}}$ values were derived for 90 watersheds in Texas by using LULC data for 1992 and 2001; the $C_{\mathrm{lit}}$ values derived from the two data sets were essentially the same. Also for this study, volumetric runoff coefficients ( $C_v$ ) were estimated by using observed rainfall and runoff depths from more than 1,600 events observed in the watersheds. Watershed-median and watershed-average $C_v$ values were computed, and both are consistent with data from the National Urban Runoff Program. In addition, $C_v$ values were estimated by using rank-ordered pairs of rainfall and runoff depths (i.e., frequency matching). As anticipated, $C$ values derived by all three methods (literature based, event totals, and frequency matching) consistently had larger values for developed watersheds than for undeveloped watersheds. Two regression equations of $C_v$ versus percent impervious area were developed and combined into a single equation that can be used to rapidly estimate $C_v$ values for similar Texas watersheds.

The knowledge of unsaturated soil is indispensable for several hydrological and geoenvironmental problems such as permeation of water through vadoze zone, ground water recharge, and deciding irrigation requirements for crops. The accuracy of these studies depends on the precise characterization of unsaturated soil, which includes the development of the soil suction–water content relationship (SWR) or soil–water characteristic curve (SWCC). It is believed that each soil has a unique SWCC. However, past studies clearly indicate that there are different parameters that would influence the uniqueness of the SWCC. Therefore, the present study purports to critically review the findings reported in the literature to reveal the influence of different parameters on the SWCC. The review is divided into two sections. The first section deals with those parameters that need a critical assessment, and the second section deals with apparent factors that influence the SWCC. The critical evaluation brings out the anomalies associated with the influence of some of the parameters, such as compaction state, measurement procedures, stress history, and range of suction measurement on the SWCC. Compaction water content has a more significant influence on the SWCC than density. The SWCC is found to be unique at a high range of soil suction for which adsorptive forces are predominant. It was found that the extent of influence of parameters on the SWCC is soil specific. However, further experimental investigations are required to quantify soil-specific parametric influence on the SWCC.

Prediction of water infiltration into the soil, fluid movement in the unsaturated soils, and groundwater recharge are important problems in different fields of science and engineering. Moreover, the transfer of the different pollutants (e.g., pesticides) from ground surface to groundwater occurs through the unsaturated zone. In this paper, a comprehensive evaluation of different finite difference schemes (e.g., fully implicit, Crank-Nicolson, and Runge-Kutta) is presented for the solution of head-based and mixed forms of the Richard’s equation. Two examples of water infiltration in very dry and relatively wet unsaturated soils are used for the evaluation of schemes. In addition, the effects of various approximations of moisture capacity function, convergence criteria, and time stepping methods on the performance of the schemes are investigated, and the results showed their significant influences on mass balance, number of iterations, and convergence condition of the numerical schemes. The results of numerical simulations showed that the generally mixed form has better performance than the head-based form. In addition, the Crank-Nicolson scheme showed better results than the Runge-Kutta scheme, but both have convergence problems. In general, the comparison of numerical methods showed that the fully implicit scheme has the best performance among various finite difference schemes and can be selected as a reliable scheme with acceptable solutions for different infiltration problems in unsaturated soils.

In this paper, the outflow process from a sharp-crested triangular labyrinth weir is studied. Applying dimensional analysis and the $\Pi$ theorem, five dimensionless groups, describing the outflow process, are deduced. The measurements, carried out by using sharp-crested weirs placed in a flume, allowed to establish a dimensionless stage-discharge relation. According to this equation, the flow magnification is affected by either the length magnification ratio or head to one cycle width ratio. The proposed equation, which also satisfies two theoretical boundary conditions, was finally tested by using experimental measurements of different reservoir hydraulic models.

The occurrence of hydrological and agricultural droughts in a river-based irrigation scheme in New Zealand was investigated in this study. Hydrological drought occurred when irrigation supplies fell short of demands. Agricultural drought was defined by a soil moisture deficit arising from imbalances in rainfall and evapotranspiration during the irrigation season (September–April). Hydrological drought was further characterized by the number of days supplies fully or partially fell short of demands (duration) and the percentage of irrigation abstractions available when demands were partially met (severity). Based on 37 years (1972–2008) of observed river flow data (supply), it was found that one-fourth of hydrological droughts occurred early (September–December) during irrigation season. Hydrological drought started to intensify, both in duration and severity, from January and peaked in March. On the basis of climate data from 1972 to 2008, the monthly soil moisture deficit (difference between rainfall and evapotranspiration), indicators of agricultural droughts, of various return periods were analyzed. The 5- and 10-year return period agricultural droughts always exceeded the profile total available water (PAW) (estimated as a difference between wilting point and field capacity over a root zone depth of 900 mm) in the two-thirds of the irrigation scheme. Agricultural droughts peaked in January. Spatial variability in agricultural drought across the scheme, when combined with PAW, highlighted the inequity of having a single-design irrigation application rate for the entire scheme, in which large, parallel rainfall and evapotranspiration gradients exist. These gradients indicate that irrigation reliability varies spatially and temporally within the scheme.

A field study was conducted on sugar beet during a two-year period to investigate the effects and comparison of different irrigation methods and treatments on crop yield, irrigation water use efficiency (IWUE), and pan coefficient determination in a semiarid region with limited water resources. The experiments were in complete randomized blocks design. Three replications were used with different levels of irrigation water amounts (25, 50, 75, and 100%), evapotranspiration (ET) of sugar beet seasonal water requirement with surface drip tape (SDT), and conventional furrow irrigation method (CFI), with and without soil and water monitoring, and comparison with CROPWAT modeling. The variety of sugar beet was Rasool. The highest and lowest average irrigation water use efficiencies on the basis of root yield with 16.16 and $9\mathrm{kg}/{\mathrm{m}}^3$ , and sugar yield with 3.82 and $1.33\mathrm{kg}/{\mathrm{m}}^3$ , for both experimental years was achieved under different irrigation treatments of T4 (25% ET) SDT and CFI, respectively. The results of this study showed that by using drip tape irrigation method with different treatments (100% ET), (75% ET), (50% ET), (25% ET), instead of conventional furrow irrigation method with and without soil, water, and root monitoring, (28.8, 46.6, 64.5, and 82.2%) and (38.4, 53.8, 69.2, and 84.6%) of sugar beet seasonal irrigation water requirement can be saved, respectively. The results also showed that sugar beet average annual water, requirement under conventional furrow irrigation method with soil, water, and root monitoring was almost 8.4% and 28.70% lower compared to CROPWAT modeling and conventional furrow irrigation without monitoring. Additionally, this study showed a pan coefficient ( $K_p$ ) equal to 0.80 for the investigated semiarid region.

Reference evapotranspiration rates are often estimated by using pan evaporation data because pan data are widely available. Conversion of pan evaporation estimates to reference evapotranspiration relies on the determination of the pan coefficient ( $K_p$ ). A simple linear equation has been suggested for estimating $K_p$ on the basis of the energy balance, and it is expressed as a linear combination of wind speed and surface temperature at the reference height. In this study, the new equation for estimating $K_p$ was calibrated by using a single-criteria multiple-parameter optimization technique, and cross-validation was performed to test the equation by using data from 10 meteorological stations in Korea. Because lysimeter data were not available, the Penman-Monteith equation was used as a reference in this study to calibrate and validate the suggested equation. The results showed that the averaged coefficient of determination ( $r^2$ ) was 0.92, the NSC was 0.93, and the RMSE was 8.99 mm. In general, the suggested equation provided reasonably accurate estimates of the reference evapotranspiration in the Korean Peninsula. The suggested equation presented here is advantageous because only two readily available pieces of climate data are required to estimate $K_p$ .

A basis of contrast for advanced basin fertigation method can be provided by simulating the one-dimensional surface flow and solute transport process of basin irrigation in traditional surface application of fertilizer. A nonuniform distribution field of water flow velocity and solute concentration along the basin and its arbitrary cross section were constructed on the basis of vertical linear and logarithmic law in turbulence theory and continuous equation of incompressible hydrodynamics. A one-dimensional surface flow and solute transport model for basin irrigation in traditional surface application of fertilizer was proposed. At the same time, validation of the proposed model was carried out by using the results of typical basin irrigation tests. Results show that the proposed model can efficiently simulate the water flow and solute transport processes of basin irrigation, and exhibits good potential in conservation of water and solute quantity. Thus, the proposed model provides a research numerical tool for evaluating the performance of basin irrigation in traditional surface application of fertilizer, and serves as a basis for comparison of basin irrigation systems under different modes of fertilizer application.