Journal of Irrigation and Drainage Engineering

Currently, point measurement and remote sensing technique are two frequently used methods to study the spatial-temporal distribution and pattern of soil moisture. However, point measurement is known as cost-intensive and time-consuming, whereas remote sensing is limited in precision to describe spatial and temporal characteristics of soil moisture especially for deep layer soil. This study introduced a method to map farmland soil moisture using a distributed hydrological model (MODCYCLE) combined with the kriging interpolation method (KIM) at the regional scale. Handan City in the North China Plain was chosen as the study area to verify the method. According to the result, there is a significant consistency relationships between observed soil moisture data collected, respectively, from 12 monitoring stations and simulated results in this paper. The maximum relative error coefficient is as low as 8.8%, and even the minimum correlation coefficient is more than 0.66, which shows a good reliability and feasibility of this method. Moreover, the authors also analyzed the spatial characteristics of the soil moisture and assessed the drought vulnerability in the study area based on the soil moisture distribution map. Meanwhile, this paper also summarized a series of suggestions that could cope with agricultural water scarcity and ensure the sustainable development of grain production in this study area.

Five different sinuosities of trapezoidal meandering channels were tested to investigate the effects of the geometry and flow parameters on the resistance to flow in meandering channels. The Manning’s roughness coefficient is considered to depend on the aspect ratio, Reynolds number, Froude number, bed slope, and sinuosity. An empirical equation to predict the Manning’s roughness coefficient of a meandering channel is obtained by using laboratory experimental data. The empirical equation used takes care of these geometric and hydraulic nondimensional parameters. The equation gives satisfactory stage-discharge results as compared to other approaches for large-scale channels, small-scale channels, and natural river data.

Treated wastewater reuse (TWWR) offers a promising solution for farm crop and turf irrigation while also mitigating the environmental pressures resulting from effluent disposal in the environment. Most attention is devoted to ensuring that treatments are safe for human health. Nevertheless, the treatment may be incomplete or some pathogens resulting from biofilm development may be dispersed through the system. Therefore, end-users must take specific precautions and implement practices to prevent any unintended dispersal of contaminants transported by the water, in particular when using sprinkler irrigation practices. To generate data to evaluate dissemination hazards, and thereby facilitate risk calculation, a sprinkler was operated in (windy) field conditions and the wetted area drift as well as the transport of small particles downwind was measured within a perimeter 4 times the sprinkler range. The volumes collected at such distances on the ground and along the wind axis remained below $0.5\mathrm{mL}{\mathrm{m}}^{-2}{\mathrm{h}}^{-1}$, and below $4\mathrm{mL}{\mathrm{h}}^{-1}\mathrm{per}{\mathrm{m}}^2$ of vertical section, for winds of $5\mathrm{m}{\mathrm{s}}^{-1}$, and below 0.25 and $1.4\mathrm{mL}{\mathrm{h}}^{-1}\mathrm{per}{\mathrm{m}}^2$ of vertical section for winds of $3\mathrm{m}{\mathrm{s}}^{-1}$. The measurement method, based on the use of fluorescent dye, is proposed along with an empirical model that can be used to estimate the volumes of potentially contaminated water that can escape from the wetted zone under wind influence for the specific sprinkler used.

The effective scheduling of irrigation requires knowledge of a crop’s consumptive water use according to its metabolic activities. Conversely, to know a crop’s consumptive water use, one must know its exact evapotranspiration (ET) rate. Although the United Nations’ Food and Agricultural Organization (FAO) has recommended using the standard Penman-Monteith method to determine crop ET (${\mathrm{ET}}_{\mathrm{crop}}$), the method’s intricacies render it impractical to use in the field in predicting agricultural and irrigation requirement-based water needs. The present study investigated the use of a new approach, extreme learning machines (ELMs), for estimating ${\mathrm{ET}}_{\mathrm{crop}}$ using climatic variables such as temperature, relative humidity, rainfall, sunshine hours, and wind speed. ELM is a single, hidden layer, feed-forward network that provides a unified learning platform with widespread types of feature mappings. It can also be applied in regression. This study compares results obtained using the standard Penman-Monteith method, ELM, artificial neural networks (ANNs), genetic programming (GP), and support vector machines (SVMs). Results suggest that ELM can predict ET more quickly and accurately than all other techniques tested. An ELM with sigmoid transfer function predicted ET with greater accuracy than a hard limit transfer function.

Several irrigation water delivery methods are in practice in irrigated agriculture throughout the world, and a variety of classifications have been suggested by different researchers. Demand, arranged-demand, and rotation are the three main types of irrigation schedules/delivery methods. Irrigation systems may also be classified as either sequential or simultaneous. Supplying water sequentially to farmers according to their requested times constitutes an irrigation scheduling problem analogous to the classical earliness/tardiness single machine scheduling problems in Operational Research (OR). In this paper, the authors describe an irrigation scheduling problem analogous to the complex multimachine scheduling problem. The authors develop a genetic algorithm (GA) and test this algorithm against solutions obtained from an integer program to draw conclusions about the solution quality of the GA. The researchers demonstrate the potential of this GA through an engineering application of the Maira Branch Canal. The authors show that if this canal is operated at a constant discharge, the arranged-demand schedule requires the canal to be operated at 75% of the discharge required if this canal were operated on an on-demand schedule.

This study was carried out to determine the effect of regular deficit drip irrigation strategies on growth, yield, and yield components, as well as water use efficiency (WUE) under Mediterranean conditions. Peanut (Arachis hypogaea cv. NC-7) crops were grown in the seasons of 2013 and 2014. Irrigation water applications were 0 ($I_0$), 25% ($I_{25}$), 50% ($I_{50}$), 75% ($I_{75}$), 100% ($I_{100}$), and 125% ($I_{125}$) based on cumulative evaporation (Epan) measured in a Class A pan. Different irrigation levels applied have statistically significant effects on yield components such as plant height, primary branch length and number, dry shoot and root weight, number of pods, and 100-seed weight. In both years, water stress significantly decreased linoleic acid, protein, and oil content, although it increased oleic acid. The $I_{100}$ irrigation treatment produced the highest protein value (32.5% in 2013 and 32.7% in 2014), whereas $I_0$ yielded the lowest values (24.6% in 2013 and 25.9% in 2014). The maximum seed yield was obtained from $I_{100}$ treatment in both years ($5.25\mathrm{t}{\mathrm{ha}}^{-1}$ in 2013 and $5.36\mathrm{t}{\mathrm{ha}}^{-1}$ in 2014). Compared to $I_{100}$, the two-year average seed yield reduction for $I_0$, $I_{25}$, $I_{50}$, $I_{75}$, and $I_{125}$ were 81.0, 68.5, 28.5, 12.0, and 4.5%, respectively. The highest WUE was obtained from $I_{50}$ and from $I_{75}$ treatment in the first and second year, respectively, as much as $7.5\mathrm{kg}{\mathrm{ha}}^{-1}{\mathrm{mm}}^{-1}$. Based on the combined effects of yield reduction, WUE, and seed quality characteristics, peanuts can be irrigated as much as 100% of pan evaporation when water shortage is not a concern, and it can be irrigated as much as 75% of pan evaporation under water shortage conditions.

Dependency of rational formula runoff coefficients on return period for two locations in Texas is evaluated by making use of an uncomplicated procedure for calculating peak discharge from small catchments using standard rainfall-runoff computation methods. Numerical solutions for dimensionless peak discharge are presented in the form of graphical relations, and also as mathematical expressions that approximate the graphs closely. Comparing peak discharge found by this approach to the rational formula provides a means of evaluating the relation between runoff coefficients and rainfall return periods. When compared to runoff coefficient adjustment factors found by others for 36 undeveloped watersheds in Texas, the return period adjustment factors calculated here illustrate the large differences that result because of the wide variability of parameters that influence small catchment runoff (such as precipitation, soils, and land-surface cover) within a region as vast as Texas.