Journal of Irrigation and Drainage Engineering

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Accurate determination of grass-reference evapotranspiration (ETo) is very important for agricultural, hydrological, and environmental studies, especially under increasing water scarcity and climate mitigation conditions. The FAO-56 Penman-Monteith (FAO-PM) model is renowned for being the most accurate model; however, it requires a full climate data set that is not always available at all weather stations, especially in most of the developing countries. Thus, using ETo models that require a reduced set of climate data continues to be an important alternative in such cases. The objectives of this study were to (1) evaluate the FAO-56 Penman-Monteith equation to estimate ETo with limited climate data, and (2) evaluate two of the latest ETo equations developed by Valiantzas. Climatic variables, including maximum and minimum air temperature, maximum and minimum relative humidity, solar radiation, and wind speed were collected from eight weather stations across Burkina Faso. The results showed that when solar radiation data were missing, solar radiation estimation from maximum and minimum daily air temperatures generated accurate estimates of ETo, with regression slope from 0.98 to 1.04, root mean squared error (RMSE) less than $0.60\mathrm{mm}/\mathrm{day}$, and low mean biased error (MBE) within the range of $-0.18–0.02\mathrm{mm}/\mathrm{day}$. In the case of lacking relative humidity data, the RMSE and MBE varied from 0.07 to $0.47\mathrm{mm}/\mathrm{day}$ and from $-0.45$ to $0.22\mathrm{mm}/\mathrm{day}$, respectively, and the regression slope varied from 0.90 to 1.14, and the coefficient of determination (${\mathit{R}}^2$) ranged from 0.77 to 0.92. In the case of missing wind speed, the method that used long-term average wind speed (ETo-um) resulted in the best estimates, especially for lower ETo rates ($\mathrm{ETo}<6\mathrm{mm}/\mathrm{day}$) as compared to the method (ETo-w2) that adopted the default wind speed of $2\mathrm{m}/\mathrm{s}$. Indeed the ETo-w2 method overestimated ETo from 4 to 35%. With the ETo-um method, RMSE varied from 0.43 to $0.57\mathrm{mm}/\mathrm{day}$ and the MBE varied from $-0.05$ to $0.04\mathrm{mm}/\mathrm{day}$ whereas the (ETo-w2) method had the RMSE ranging from 0.59 to $2.11\mathrm{mm}/\mathrm{day}$ and the MBE ranging from 0.26 to $1.90\mathrm{mm}/\mathrm{day}$. The FAO-PM equation had the least accurate performance when only temperature data is available. The Valiantzas 1 equation that uses only air temperature and relative humidity data was not suitable and is not recommended for use in Burkina Faso climatic conditions. The Valiantzas 2 equation with full climatic data resulted in good ETo estimates relative to the FAO-PM ETo with full data under the Burkina Faso climate conditions; however, the FAO-PM equation is recommended because of limitations of the Valiantzas 2 equation under limited data conditions.

A methodology is proposed for estimating furrow infiltration under time-variable ponding depth. The methodology approximates the solution to the two-dimensional Richards equation, and is a modification of a procedure that was originally proposed for computing infiltration under constant ponding depth. Two computational approaches were developed and tested using several combinations of soil hydraulic properties, furrow geometry, and flow depth variations. Both methods yielded solutions of reasonable and similar accuracy relative to numerical solutions of the two-dimensional Richards equation. The analysis also showed that the accuracy of the approximate model varies mostly as a function of soil hydraulic properties. The accuracy of the approximate solution can be improved with calibration. Two calibration methods were examined, one assuming that the calibration parameter varies with depth, and the other assuming a constant value. The analysis showed that latter approach, in combination with one of the proposed computational methods, reproduced the Richards equation solution more accurately. This means that a unique calibration parameter can be developed for the particular soil and geometric configuration conditions, and applied to different patterns of ponding depth variation.

A proposed stochastic dynamic programming (SDP) method with uncertainties in stream flow and water demand is developed to calculate optimal reservoir operation rules. The SDP method extends the classic SDP method that considers only one uncertainty in its operation rules. Time series of reservoir inflow and agricultural water demand for the Aydoghmoush Reservoir in eastern Azarbayejan, Iran, were obtained from meteorological data, available climate parameters, hydrologic data, and crop water demand. The application of the developed SDP with two uncertainties was evaluated with operation rules corresponding to four different scenarios, and optimal reservoir releases were determined for a drought year. Reservoir operation results were evaluated with different performance indices. This study’s results demonstrate the advantage of considering uncertainties in reservoir inflow and water demand with the SDP method. The developed SDP method has general applicability under a range of climatic conditions, and the calculated operation rules cover the expected ranges of streamflow and water demand during the operating years.

The study of generation process of subsurface stormflow, typical of well-drained and high-permeable soils, can be theoretically carried out by applying the continuity and motion equations with the appropriate boundary conditions. However, difficulties and uncertainness on determining soil hydraulic properties and soil physics heterogeneities mean this way is not always feasible. In a different way, process dynamic can be derived by the local scale through a coarse graining procedure, allowing preservation of medium motion character, while hydraulic fluctuation of the motion is lost. Following an approach like this, a simplified model to predict the runoff generation time, the so-called delay time, is developed in this paper. Under the assumption of sloped hillslope and Dunnian mechanism of runoff generation, which implies a time-varying active length of the hillslope where runoff occurs, a relationship of the active length versus time is derived. Finally, the effect induced by the interception process on the delay time is modeled and discussed and an application is carried out. Generally, these simplified solutions could be applied for any condition in which high-permeable soil surface horizons lay on much lower permeable layers, and it could be of some interest for the simplified modeling of the surface–subsurface hillslope hydrologic response and in planning agricultural subsurface drainage systems.

The experimental procedure largely verified the validity of the theory of probability in on-demand irrigation networks. The irrigation water demand, during periods of high requirement, in the region’s network of the irrigation pumping station $\mathrm{\Sigma }9$, in the three years from 1988 to 1990, followed the five distributions: Erlang, gamma, lognormal, normal, and Weibull, in four of the total six data sets. The Erlang, gamma, lognormal, and Weibull distributions fit well to four data sets of the years from 1988 to 1990, whereas the normal distribution fits well also to four data sets but only of the two year period 1988–1989. The new demand formula approximates better the irrigation water demand in the peak consumption period. In a network with conduit of very small slope and use of self-propelled sprinklers with operating characteristics adapted to the hydraulic conditions of the network, the population of outlets may be uniform in the provision without a flow limiter, when there is discipline among the users. The same crop in the same plain area with specific local climate, small general slope, and high territorial homogeneity can significantly alter the demand for irrigation water in time, which favors the randomization of demand over time.

Most of the models developed to simulate the cohesive sediment transport processes refer to estuary or marine environments and are generally not developed for the specific characteristics of irrigation schemes provided with the different types of hydraulic structures. The aim of this study is to simulate the cohesive sediment transport in irrigation canals. The fine sediment transport (FSEDT) model was developed using a software program to estimate the sediment transport and deposition rates of cohesive sediments in irrigation canals. The model has been applied in the Gezira Scheme in Sudan, which is threatened by high sediment supply from the Blue Nile River. The model was calibrated and validated using the field data selected during the flood seasons in 2011 and 2012. The hydrodynamic part of the model was verified by comparing the water surface profile obtained by the developed model and by using a microcomputer program for simulating one-dimensional steady/unsteady flow in open canals. The results of the two models show good agreement. The sensitivity of different parameters to the deposition was tested. The model is a useful tool that can be applied to study the mechanism of sediment transport under different operation and maintenance scenarios not only in the Gezira Scheme but also in similar cases.

Pollution discharge to rivers is the leading cause of freshwater pollution. This paper presents a method for predicting the concentrations of a pollutant that is suddenly released into a river. The prediction method is based on a first-order Gaussian function. The coefficients of the Gaussian function are calculated using three power equations. These equations have six parameters whose values are optimized with the genetic algorithm (GA). The results of this paper’s case study are compared with those obtained with the artificial neural network method (ANN), genetic programming (GP), and from the analytical solution of the differential equation for riverine transport of suddenly released pollutants. The proposed equation is applied in a case study that confirms its suitability for estimating the concentration of pollutants downstream from a sudden release location in a river. The correlation coefficient ($R^2$) and the root mean square error (RMSE) of the training and testing data obtained from the application of the proposed equation increase and decrease approximately 14 and 50%, respectively, in comparison with the values associated with the application of the analytical advection-dispersion to calculate the transport of sudden pollution in rivers.

Net radiation ($R_n$) is one of the effective inputs for controlling soil heat flux, thermal convection, moisture flux exchange, and reference crop evapotranspiration (${\mathrm{ET}}_0$) rate. In this research, the accuracy of some empirical and semiempirical $R_n$ models is examined for different climates of Iran versus the recommended net radiation model as proposed in the Penman–Monteith Food and Agricultural Organization of the United Nations 56 standard (FAO 56) model for the period 1980–2007. For estimating daily net radiation, various net radiation models [Wright, basic regression model (BRM), Linacre, Berliand, Irmak, and Monteith] were examined. Model evaluations were implemented for four climate types. On regional averages, the linear BRM had the superior performance in generating the most accurate daily ${\mathrm{ET}}_0$. Results showed that for 70% of the study sites, the linear $R_n$ models can be reliable candidates instead of sophisticated nonlinear $R_n$ models, which are proposed in the reference FAO 56 model. For some sites, with low altitude and high relative humidity (e.g., coastal humid sites), the Irmak model suggested the minimum deviations from the reference FAO 56 model. Using the best-performing $R_n$ models is recommended for the agricultural sites where comprehensive weather data are not available.

In the present study, the changes in system efficiency were investigated at constant pressure and at different flow rates between 100 and 50% of the nominal flow rate in an irrigation pumping plant. For this purpose, programable logic controller (PLC) and human machine interface (HMI) panel software was developed to automatically control motor speed by means of frequency, and valve opening by means of servomotor in an irrigation pumping system. In this automation system, pump flow rate was measured using an electromagnetic flowmeter and pump discharge pressure was measured using a pressure sensor. According to the results of the study, optimum system efficiency was observed at the point corresponding to 70% of the nominal flow rate. This system efficiency value was found to be 6.9% higher than the nominal system efficiency. However, the system efficiency at points corresponding to 50% or lower ratios of the nominal flow rate was found to be lower than the nominal system efficiency.

DRAINMOD 6.1 was evaluated for hydrological simulation of two drained (1.0 m drain depth, 20 m spacing) peat extraction areas in Northern Finland. Water table depth (WTD) and drainage outflow were recorded continuously during two years, and the data were used for model calibration and validation. Despite some under- and overestimation of certain events, WTD fluctuations simulated quite accurately, whereas the model did not simulate drainage outflow well compared to observed data, especially for daily runoff. Mean absolute error (MAE) was 11.29 and 9.09 cm and Nash–Sutcliffe modeling efficiency (EF) was 0.64 and 0.62 for both study sites during the validation period, indicating good agreement between predicted and observed WTD. These results demonstrate that DRAINMOD 6.1 can satisfactorily simulate the WTD fluctuations in peat extraction areas in the cold climate of northern Finland, but further studies are needed to improve the model to better include frozen condition and peat extraction activities.

Soil water content sensors placement is an important factor affecting the efficiency of drip irrigation scheduling systems. The main goal of this study is to introduce the concept of time stable representative positions (TSRPs) in soil water content–based drip irrigation scheduling systems and to investigate if such positions, which can provide representative water content readings during the whole duration of the irrigation cycle, can be identified for a wide set of conditions. To this end, several numerical experiments were conducted using a custom-made mathematical model, implementing a system-dependent boundary condition in order to be able to simulate the operation of drip irrigation scheduling systems based on soil water content sensors. The results obtained indicated that sensors’ representativeness considerably varies according to the sensor position, the existing conditions (e.g., meteorological conditions or soil hydraulic properties), and the irrigation systems characteristics, however, at least one (or more) TSRP can be identified in all the examined cases. Based on the obtained results, recommendations for the optimum sensor placement are provided. Finally, numerical simulation models proved to be efficient tools for the further investigation of optimum sensors placement under various conditions in order to improve irrigation management.

The management improvement of irrigation networks is inevitable because of limited water resources and competition in various sectors of industry, agriculture, environment, and urban water consumption. Application of appropriate water delivery scheduling is one of the methods to improve irrigation management. Several delivery methods are practiced in irrigation networks according to water availability, type of network control system, and exiting capacities. One promising delivery method is the on-request system, which could be applied manually in irrigation networks. High performance of delivery methods arise from the determination of appropriate operation instructions. In previous studies, the Fuzzy SARSA learning (FSL) method was applied to determine operation instruction for on-request delivery in a canal of the Aghili irrigation network located in southwest Iran (SARSA is the definition of state, action, reward, state, action). In this work, the conventional manual operation on the same canal was evaluated, and the results were compared with FSL. The results for both methods in the normal condition of the network were acceptable because the adequacy and efficiency indicators were more than 90%, and the maximum deviation of water depth was less than 10%. However, in the circumstance of water shortage, the results indicated that applying the FSL method provided good and valid results, so that the index of adequacy was almost 0.7 for all blocks. Therefore, the FSL is able to distribute the water more equitably among the consumers in water shortage conditions.

This study investigated rice irrigation water use in the University of Arkansas Rice Research Verification Program between the years of 2003 and 2012. Annual irrigation water use averaged 763 mm (30.0 in.) over 10 years. A significant (40%) water savings was found for rice grown using a zero-grade irrigation system [486 mm (19.1 in.)] compared to contour-levee or straight-levee systems. No differences in irrigation water use were found between contour-levee systems [814 mm (32.1 in.)] and straight-levee systems [822 mm (32.4 in.)]. Surface water irrigators used significantly less irrigation water [624 mm (24.6 in.)] than groundwater well fields [786 mm (30.7 in.)] and cost US$77.51 less per hectare (US$31.37 less per acre) to operate. Diesel pumps cost significantly more [$\$88.38/\mathrm{acre}$ ($\$218.29/\mathrm{ha}$)] to operate than electric pumps [$\$58.69/\mathrm{acre}$ ($145.96/\mathrm{ha}$)] ($P=0.02$), although fields that used diesel as an energy source averaged 152 mm (6.0 in.) less irrigation water than electric pumps. Arkansas producers implementing the multiple-inlet water delivery practice on contour-levee or straight-levee systems, irrespective of soil type, did not realize a water savings but did realize improved yields. These results are in contrast to those in earlier studies and suggest that an educational effort may be necessary if the field research–proven multiple-inlet water savings are to be realized.

Methods of handling drastic inflow fluctuations without any constructional changes in the canal or the off-take structures are studied. Regarding the operational problem, automation of the regulating structures in the main canal is proposed. To this end, a centralized model predictive controller (MPC) is designed to achieve better operational performance in combination with an in-line water storage strategy. The controller is tested in a wide range of operational conditions, representing conventional operation, operation under predictable and unpredictable inflow fluctuations, and operation with and without water storing capabilities within the canal. The test bench is an accurate mathematical model of a canal consisting of five water regulators and seven off-takes. The results show significant improvement for canal operations employing automation. For the predictablefluctuations scenario, the results show that the stored water within the canal effectively handles the fluctuation. Compared to the conventional canal operation scenario, calculated evaluation performance indicators show an approximately 21% improvement for the maximum absolute error (MAE) and a 12% enhancement for the integral magnitude of absolute error (IAE).

Side weirs are hydraulic control structures widely used in irrigation and drainage systems as well as wastewater treatment plants. These structures also serve as adjusting/diverting flow structures with a minimum head loss. In the present study, by applying experimental data of more than 400 laboratory tests and using the multivariable nonlinear partial least-squares (PLS) method, three nonlinear equations are proposed for discharge coefficient, $C_M$, of triangular and asymmetric labyrinth side weirs. These equations relate the discharge coefficient to the relevant geometrical and hydraulic dimensionless characteristics of flow. Results indicate that the new proposed equations are more accurate compared to those of former studies, being the best tools to estimate the diverted flow discharge over the side weirs.