Journal of Irrigation and Drainage Engineering

A new unified extreme-value (UEV) distribution is proposed that combines EV-1 (Gumbel), EV-2 (Frechet), and EV-3 (Weibull) distributions to better replace the generalized extreme-value (GEV) distribution in that sense. Two simple methods, one graphical and other objective, are devised for estimating parameters of the new UEV, with the diagnostic property of identifying the concerned extreme-value distribution implicitly from the data series used. Its application on illustrative examples suggests an ease of application, reliable estimates of parameters, full transparency in the estimation process, and outperformance of widely used computationally and mathematically more complex methods, e.g., method of moments, maximum likelihood, and probability weighted moments, on GEV and EV distributions, resulting in savings of time and resources. Parameter determination and application of the UEV distribution can even be worked out on a spreadsheet. A new concept and quantification of a deterministic confidence limit is also proposed for its easy application to avoid and replace the tedious process with statistical hypothesis-testing involved in the currently used probabilistic confidence interval. The new UEV, estimation methods, and deterministic confidence limit will be of help to field engineers and practitioners.

Energy dissipation is one of the main considerations in the design of drop manholes and is closely related to the flow regimes observed. Four flow regimes in a drop manhole are classified according to different flow conditions at the inlet and outlet: free overfall flow, orifice flow, pressurized outflow, and fully submerged manhole condition. Theoretical predictions of energy dissipation in drop manholes under different flow regimes compare well with previous experimental data. The drop height limitation for drop manholes is suggested to be 3 m in this study, as larger drop heights can cause the water flow to disintegrate into drops and result in excessive air entrainment. Designs of drop manholes based on different flow regimes are presented. A single drop manhole is also compared with a prior reported stacked drop manhole in terms of energy dissipation. It is found that a well-designed single drop manhole has a similar performance in energy dissipation compared with a stacked drop manhole.

Water flow through vadose zone is important for soil ecology and for groundwater development. A thorough knowledge of water flow and solute transport through unsaturated zone is also needed for sustainable irrigation management, soil-water conservation measures, pollution risk assessment, groundwater recharge, and for applying remediation techniques. Therefore, in this study, practical and simulation experiments were performed to evaluate the role of drainage flux, recharge influx on moisture flow, and nitrate movement in subsurface. The water flow in unsaturated zone was simulated using the nonlinear Richards’ equation having dependency of its parameters on soil moisture content and pressure head. In this study, the following cases were evaluated for soil moisture and nitrate transport though variably saturated zones: (1) drainage flux to study domains, (2) recharge flux to study domains, (3) transient infiltration in unsaturated soil columns, and (4) nitrate movement in a two-dimensional (2D) sand tank setup. The single porosity model was used for the simulation of soil hydraulic parameters in the study domain. The results showed that the groundwater table position decreased with time quite significantly by applying drainage flux at the bottom boundary. The water table position in the study domain increased slowly under the constant recharge flux. The soil moisture front moved toward the groundwater level, when a constant infiltration flux was applied. Further, the nitrate movement was dominated by advective flux and significantly affected by the recharge flux in the vertical direction.

The hydraulic conductivity of soils varies over several orders of magnitude, and its measurement is affected by experimental and field conditions. This paper applies Monte Carlo simulation (MCS) to ascertain the impact of hydraulic conductivity’s uncertainty on the bioremediation of groundwater contaminated with dissolved petroleum hydrocarbons. The model BIO PLUME II is implemented for simulating the bioremediation treatment. The effect of hydraulic conductivity uncertainty on bioremediation is assessed by means of MCS. This paper’s results indicate that the uncertainty in prediction of the residual contaminant concentration produced by bioremediation is higher at the center of mass of the contaminant plume than at its periphery. The results also show that the effect of hydraulic conductivity uncertainty on residual contaminant concentration is larger at intermediate times since the start of bioremediation than at early or late times of the treatment phase.

The optimal allocation of crop area can improve the management of agricultural water resources for sustaining agricultural productivity and sustainable development. In this study, an approach that integrated the multiobjective optimization model with an orthogonal experimental design was developed for decision makers to choose the optimal crop area under limited water and land resources. The approach was developed in three stages—(1) preparation stage; (2) calculation stage; and (3) decision-making stage—and included five steps: (1) data collection; (2) establishment of an optimal model; (3) orthogonal experimental design; (4) screening; and (5) decision making. The agricultural drought degree, which can reflect the drought conditions of the irrigation district, was introduced to the established model in Step 2 as a social objective. Furthermore, a village called Qu, which is part of the Yellow River water irrigation district and is located in the southwest of Puyang city, Henan province, China, was taken as an example to demonstrate the approach.

A hydraulic jump can be washed out or drowned if the downstream tailwater depth is lower or higher than the downstream sequent depth, respectively. Stilling basins built downstream of water control structures are designed to freeze the jump within the confines of the basin to dissipate energy and keep the jump from washing out. The structure of the flow associated with both washed-out and drowned jumps may result in significant scour downstream of stilling basins, which can in turn pose a threat to the stability of hydraulic structures that the stilling basin is intended to protect. This paper presents novel experimental results of observations of hydraulic jumps at the stilling basin downstream of a low-head spillway model that capture the occurrence of a temporally oscillating hydraulic jump (a jump that alternates between drowned and washed-out types in a quasi-periodic manner). Such a type of jump is found to result in the maximum scour conditions downstream of the stilling basin, which are larger than those induced by well-formed hydraulic jumps. The observations presented herein underscore the point that the conditions that result in temporally oscillating hydraulic jumps should be avoided as part of the design of stilling basins downstream of water control structures to reduce the risk of scour-induced damage.

This paper investigates the accuracy of three different adaptive neuro-fuzzy inference systems (ANFISs), ANFIS with grid partition (ANFIS-GP), ANFIS with substructive clustering (ANFIS-SC), and ANFIS with fuzzy c means (ANFIS-FCM) in estimation of long-term monthly air temperatures. Data of 71 stations in Turkey are used in the applications. The periodicity (month of the year) and geographical variables (latitude, longitude, and altitude) are used as inputs to the models. ANFIS models are also compared with artificial neural networks (ANNs) and multilinear regression (MLR). Three ANFIS methods provide superior accuracy to ANN and MLR methods, and the ability of the ANFIS-GP is observed to be superior to the ANFIS-SC and ANFIS-FCM models. Among the ANFIS methods, the worst estimates are obtained from the ANFIS-FCM method. The maximum determination coefficients ($R^2$) are observed as 0.998, 0.995, and 0.995 for the ANFIS-GP, ANFIS-SC, and ANFIS-FCM at S.Urfa, Tunceli, and Usak stations, individually. The minimum $R^2$ values are individually found as 0.902 and 0.921 for the ANFIS-GP and ANFIS-SC at Sinop station, whereas the ANFIS-FCM model gives a minimum $R^2$ of 0.934 at Yalova and Yozgat stations in the testing stage. The outcomes show that long-term monthly air temperatures can be effectively assessed by the ANFIS-GP method using geographical inputs. The interpolated air temperature maps are likewise produced by using the ideal ANFIS-GP and are assessed in this study. The temperature maps demonstrate that the most noteworthy measures of temperatures happen in the southeastern, northeastern, western, and northwestern parts of Turkey.

The complexity of agricultural water management practices has challenged researchers attempting to determine how hydrological pathways affect water and nitrogen (N) losses. Field experiments in a typical rice agricultural catchment in the Zhanghe Irrigation District in China were conducted in 2014 and 2015 to evaluate and quantify the connections between hydrological pathways and water and N losses. Four water management periods—namely, the irrigation period (IP), the rainfall period (RP), the normal-drainage period (DP), and the nonirrigation-drainage period (NP)—were defined based on climate conditions and artificial irrigation and drainage periods. The experimental results indicated that most water and N losses occurred in DP and RP and that lateral seepage and tailwater were the main sources of the observed drainage. Low average concentrations of ammonia N (${\mathrm{NH}}_4^{+}─\mathrm{N}$, $0.373\mathrm{mg}{\mathrm{L}}^{-1}$) and nitrate N (${\mathrm{NO}}_3^{-}─\mathrm{N}$, $0.285\mathrm{mg}{\mathrm{L}}^{-1}$) and low proportions of dissolved N (42.2–54.0%) were detected in association with green manure application, whereas the average concentration of total N (TN, $1.376\mathrm{mg}{\mathrm{L}}^{-1}$) was relatively high, which resulted in slight N pollution in the studied agricultural area. The concentrations and proportions of dissolved N were greastest in DP and RP. The average daily mass fluxes of ${\mathrm{NH}}_4^{+}─\mathrm{N}$, ${\mathrm{NO}}_3^{-}─\mathrm{N}$, and TN were 0.027, 0.020, and $0.095\mathrm{kg}{\mathrm{ha}}^{-1}{\mathrm{day}}^{-1}$, respectively, and the magnitudes in DP and RP were significantly greater than those in IP and NP. The average concentrations of ${\mathrm{NH}}_4^{+}─\mathrm{N}$, ${\mathrm{NO}}_3^{-}─\mathrm{N}$, and TN were not correlated to drainage discharge according to a Pearson correlation analysis, whereas a power function can quantify the relationship between N mass fluxes and discharge during various water management periods. The average thresholds of drainage discharge, at which N export from paddy fields equalled to zero, were $45.2{\mathrm{m}}^3{\mathrm{day}}^{-1}{\mathrm{ha}}^{-1}$ for ${\mathrm{NH}}_4^{+}─\mathrm{N}$, $51.9{\mathrm{m}}^3{\mathrm{day}}^{-1}{\mathrm{ha}}^{-1}$ for ${\mathrm{NO}}_3^{-}─\mathrm{N}$, and $55.5{\mathrm{m}}^3{\mathrm{day}}^{-1}{\mathrm{ha}}^{-1}$ for TN. These findings indicate that controlling drainage discharge is important for the reduction of water loss and N loss from paddy fields.