A study was conducted to test the validity of four different mathematical models imbedded in CropWat software, which is widely used to estimate effective rainfall. The model values were statistically compared with the actual effective rainfall values measured by a field infiltrometer experiment. The study was conducted in a sugarcane land–use system under the tropical climate of Sevanagala, Sri Lanka, during the 2018 to 2019 growing season. The measured effective rainfall in the Sevanagala sugarcane growing area during the 12-month period was 1,068 mm, around 70% of the total rainfall of 1,517 mm. It was also found that 9% of the rainfall received at the top of the canopy was lost due to canopy interception. The results demonstrated the applicability of the mathematical models embedded in CropWat software to estimate the effective rainfall for sugarcane land–use systems in Sevanagala. Furthermore, the empirical regression formula embedded in CropWat software appeared to be the best-fit model for the estimation of effective rainfall because it had the highest index of agreement value, with an accuracy greater than 96%.

The main producers of agricultural drainage water in Khuzestan province in Iran are the sugarcane agro-industries. As a result of the accumulation of drainage water in the region, environmental and social problems have arisen. In general, the salinity of this drainage water averages 6.3 dS/m throughout the year. The cultivation of salinity-resistant varieties of paddy rice can be considered as a suitable substrate for the optimal use of drainage water. In this regard, a study was conducted in one of the sugarcane fields in southern Khuzestan based on randomized complete block design with three replications. The main factor was three intermittent irrigation regimes using drainage water of sugarcane fields, which included daily irrigation (I0), one-day irrigation interval (I1) and two-day irrigation interval (I2). In addition, the subplots included three salinity-resistant rice lines (S1, S2, and S5), four drought-resistant rice lines (M2, M5, M7, and M12), a control cultivar “Hashemi” and a local cultivar “Hoveyzeh.” The results showed that with a significant reduction in applied water from the I0 to I1 and I2, the yield in I1 increased by 6% over I0, but the yield in I2 decreased by 30%. The highest and lowest water productivity were related to I2 and I0 at the rates of 0.13 and 0.06 kg/m3, respectively. In I1 irrigation regime, the local cultivar Hoveyzeh produced a yield of 2,444 kg/ha, while the salinity-resistant lines S1 and S5 produced acceptable yields of 2,385 and 2,263 kg/ha, respectively. According to the findings from monitoring the soil exchangeable sodium percentage (ESP), farm soils in both irrigation regimes I0 and I1 were nonsodic and saline. In I2, however, the soil profile status approached the sodic state as a result of the drying of the topsoil and the influx of salinity into the surface layer, resulting in a 17% increase in ESP. Consequently, when using agricultural drainage water for irrigation, leaching at the end of the growing season and drainage are necessary to remove salts. Based on the findings of this article, it is possible to maintain stability in rice production for a wide range of regions around the world with warm climates by reusing agricultural drainage water.

This study aimed to clarify the effect of irrigation water amount and planting pattern on water use and yield of cotton in Northern Xinjiang. A field experiment was conducted during 2020–2021 comprising four irrigation water amounts (360, 450, 540, and 630 mm) and two planting patterns (same row spacing, R1; and wide-narrow row planting, R2). The results showed that the evapotranspiration (ET), soil evaporation (Es), and plant transpiration (T) of cotton under both planting patterns increased with the increasing irrigation amount. During the entire growth period, the annual average daily ET and T under R2 were higher than those under R1, but the annual average daily Es under R2 were lower than those under R1. The daily Es was highest between one and four days after irrigation. The Es/ET under R1 was approximately 27.45%–31.82%, and that under R2 was approximately 24.52%–28.56% under the four irrigation treatments. The relationship between the Es/ET and leaf area index was fitted based on an exponential equation (R2>0.85). The yield increased with an increase in the irrigation amount, although there was no significant difference between the yields obtained with 540 mm and 630 mm irrigation amounts. The water use efficiency (WUE) increased first and then decreased with an increase in irrigation water amount, with the highest WUE observed under the 540 mm condition and the lowest under the 630 mm condition.

Entrapped air pockets reduce flood conveying capacity of a surcharged drainage tunnel, and could be released explosively as geysers from vertical dropshafts. Nevertheless, the impact of dropshaft inflow on air pocket expulsion has hitherto not been fully understood. In this work, experiments was performed on a simplified drainage system consisting of a dropshaft with inflow. An air pocket was introduced into the tunnel; its dynamics in the dropshaft was measured with a high speed camera and pressure transducers. A heuristic analysis on the kinematics of the air pocket showed that when the dropshaft inflow is greater than a critical flow dependent on the dropshaft diameter, the increased compression leads to stronger air pocket expulsion, as spewing and/or ejection of air-water mixture. Observed occurrence of the phenomena generally agrees with the prediction. © 2022 American Society of Civil Engineers.

This study measured the cost efficiency and estimated the optimal cost structure in operating and maintaining the irrigation systems of eight provinces in the Red River Delta (RRD), Vietnam, from 2014 to 2016 using the input-oriented model of data envelopment analysis. The inputs included in the model were the costs of labor, materials, electric energy for irrigation, irrigation structure safety, maintenance, depreciation, administrative expenses, and overhead cost. The output was the irrigation area, which was converted to paddy areas. The findings of this study showed a large inefficiency in using the total input financial cost subsidized. The optimal technical efficiency scores under constant returns to scale (CRS) and variable returns to scale (VRS) were 0.86 and 0.98, respectively. The results implied that total input costs should be reduced by 14% under CRS and 2% under VRS to avoid cost inefficiency. The results also showed that scale efficiency occurred in the operation and maintenance (O&M) management of the irrigation systems. The O&M management in the irrigation systems in the RRD should allocate the major proportion of the costs to labor to be efficient. Application of the optimal input cost structure would improve irrigation management performance for the RRD region by 48.7% for the efficient input target (EIT) under CRS and by 5.03% for the EIT under VRS. These were the significant bases for recommending policy options for reviewing the irrigation tariff subsidy according to each input factor. And then it could create the incentives for private participation partnership in the irrigation sector.

Automatic canal control is essential to improve water utilization efficiency in irrigation districts. Water level error in the model used by the control algorithm significantly impacts performance. The integrator delay model, which has a linear structure, is widely used in multi-input/multioutput control algorithms, including linear-quadratic control and model predictive control. However, the integrator delay model is suboptimal for large irrigation districts; the canals are long, the flows are large, there are many scattered offtakes, and the operating conditions vary. We developed an adaptive predictive control mode for the Qinhan Canal in Ningxia Province, China. We used a segment integrator delay model for this large irrigation district and employed a differential evolution algorithm for online system identification; this minimizes error. We analyzed and controlled for various uncertainties (i.e., flow observation noise, geometric and hydraulic parameter errors, and accidental interference with the automatic control system). Simulations indicated that the water level fitting errors were significantly reduced compared with the original model, and water level regulation was significantly improved, especially in terms of the maximum absolute error. Adaptive predictive control was better than linear-quadratic control and model predictive control approach for water level. Adaptive predictive control coped well with several uncertainties. The main factors affecting water level control were the flow observation and gate opening control accuracy, and the extent of real-time data coverage. These features require careful attention when automating and modernizing irrigation districts.