Irrigation and Drainage最新文献

Precision irrigation and fertigation using IoT-based decision-making tools have proven effective in optimizing real-time nutrient solutions for agricultural production. IoT is essential for real-time sensor monitoring and for wirelessly activating fertigation and irrigation systems. Soilless or hydroponic culture presents a viable alternative to traditional soil-based cultivation. This study evaluated an IoT-based fertigation system for soilless Dutch bucket hydroponic cucumber production in field experiments conducted from August to October 2023 and 2024. Two treatments were compared: conventional soil-based cultivation (Drip irrigation at 100% ETc) and IoT-enabled Dutch bucket hydroponics. The system monitored crop microclimate and automated fertigation, applying nutrients when EC was ≤ 2.5 dS/m and turning off at ≥ 4 dS/m. Crop performance parameters were assessed, including plant height, leaf area, root volume, yield and water productivity. Results showed that the IoT-enabled hydroponic system produced significantly higher yields than traditional soil-based cultivation. Yield and water productivity increased by 7% and 53%, respectively, with 12% less irrigation water. While testing under protected cultivation, the system's waterproof design indicates its suitability for outdoor conditions. The IoT system effectively records and displays environmental and fertigation data via the cloud, enabling fully automated fertigation and minimizing human intervention.

Biochar application and alternate wetting and drying (AWD) irrigation are promising practices for achieving cleaner rice production. This study evaluated the combined effects of biochar and AWD irrigation on the grain yield and water productivity (WP) of wet direct-seeded rice (WDSR). A pot experiment combining five biochar doses (0, 5, 10, 15 and 20 t ha⁻¹) with three soil water potential levels (0, −15 and −30 kPa) via AWD irrigation was conducted. Biochar at 20 t ha⁻¹ significantly increased panicle number plant⁻¹ (18%) and SPAD value (5%) compared with 0 t ha⁻¹ biochar. The performance of the plants was similar between 0 and −15 kPa, whereas −30 kPa was stressful. Despite the reduced water input, −30 kPa resulted in 27% lower grain yield compared with 0 kPa at 0 t ha⁻¹. In contrast, −15 kPa did not cause notable growth or yield abnormalities. Moreover, 20 t ha⁻¹ in combination with −15 kPa resulted in better crop performance, resulting in 86% greater root dry matter, 24% greater grain yield and 85% greater WP than those of the control. The results highlight the potential of the integrated application of biochar and AWD irrigation for enhancing the grain yield and WP of WDSR.

This study models the combined effects of irrigation water, nitrogen fertilizer and water salinity on maize growth and yield via the AquaCrop model, as experimental methods can be costly. Data were obtained from experiments in southwestern Iran (2009–2010), with three irrigation levels (I1: 1.25 ETc, 0.75 I1 and 0.5 I1), three nitrogen levels (0, 150 and 300 kg N ha⁻¹) and three salinity levels (0.6, 2 and 4 dS m⁻¹). The model performed acceptably in simulating grain yield, dry matter, canopy cover and soil water content but poorly in simulating soil salinity. The average normalized root mean square error (NRMSE) values for grain yield, dry matter, canopy cover and soil water content, on the basis of calibration and validation, were 0.18, 0.15, 0.13 and 0.18, respectively, with d index values of 0.89, 0.98, 0.80 and 0.64, respectively. The soil salinity simulation was more accurate early in the growing season and in the surface layers than in the later stages and deeper layers. The accuracy of the AquaCrop model in estimating these parameters decreased with increasing stress intensity. While the model showed acceptable performance, its limitations under severe stress conditions highlight the need for further refinement.

Climate change and population growth have led to a decline in water resources, necessitating more efficient water use. This study aims to analyse water use efficiency in the Eskişehir Water User Association by evaluating irrigation performance. Based on irrigation data from 2016 to 2022, the research examines water management efficiency and economic indicators. The findings indicate that the total volume of distributed irrigation water varied between 103 × 10⁶ m³ and 28 × 10⁶ m³ over the years. The amount of irrigation water per unit area ranged from 6207 to 1670 m³ ha⁻¹, whereas the annual water supply ratio fluctuated between 1.13 and 0.24. In terms of economic assessments, the return on investment ranged from 146% to 39%, the ratio of maintenance costs to revenue varied between 54% and 21%, and the water fee collection performance was recorded between 96% and 46%. The annual total agricultural production value was calculated to be between 86,188 × 10³ US$ and 46,187 × 10³ US$. The results revealed that the Eskişehir Water User Association has improved water use efficiency, achieved significant progress in optimizing water utilization and enhanced agricultural productivity. These findings can contribute to the development of critical strategies for regional irrigation management and the sustainable use of water resources.

This study examined how organic mulching and deficit irrigation affect soil moisture and salinity in sandy soils, comparing field data with the SALTMED model outputs. The field experiment featured four irrigation treatments—100% IRg, 75% IRg, 50% IRg and 50% IRg with partial root drying (PRD)—and four mulching treatments: uncovered soil (UC), plastic mulch (PM), rice straw mulch (RSM) and compacted rice straw mulch (CRSM) over the 2022 and 2023 seasons. In 2022, the 50% IRg–PRD with CRSM yielded the highest at 8611 kg ha⁻¹, while the 50% IRg with UC had the lowest at 6009 kg ha⁻¹. The highest irrigation water productivity (IWP) was 5.56 kg m⁻³ under the 50% IRg–PRD and CRSM treatment, and the lowest was 2.45 kg m⁻³ with 100% IRg and UC. The SALTMED model accurately simulated crop yields with R² values of 0.982 and 0.949 across all treatments and high R² values of 0.996 and 0.992 for observed versus simulated IWPs. The model showed significant sensitivity in simulating soil moisture and salinity changes across treatments.

The aim of this study was to determine the potential of biochar to alleviate salt stress in beans, as well as how salinity stress affects the growth and physiological characteristics of bean plants during development. Three distinct irrigation water salinity doses (control, 2.3 dS·m⁻¹ and 4.6 dS·m⁻¹ NaCl concentrations) and three different doses of biochar (0%, 5% and 10% by weight of soil) were used to assess the effects. Salinity stress and the use of biochar significantly affect many attributes of bean development. Compared with the untreated control, the application of biochar increased the plant height by up to 133%, increased the stem diameter by up to 44% and increased the vegetative biomass by as much as 93%. The number of pods produced by every plant increased by 43%, the pod length increased by 32%, the pod width increased by 39%, the number of seeds per pod increased by 46% and the pod yield per plant increased by 64% when the concentration of biochar was 10%. The application of biochar under salt stress increased the chlorophyll content and relative water content, decreased electrolyte leakage and proline accumulation and decreased the total soluble sugar concentration. The present study elucidates the potential use of biochar for phytoremediation in hypersaline soil through the modification of physiological responses and pigment contents in addition to mitigating the adverse effects of salt stress on bean growth and productivity.

This study examines the social and moral impacts of irrigation water distribution on farmer satisfaction in Khyber Pakhtunkhwa, Pakistan. For this purpose, 466 farmers were selected through a multistage stratified random sampling method, as the sample size and interview schedule were used for data collection. The study utilized chi-square and Kendall's T^c tests to analyse data on farmers' satisfaction with irrigation water distribution, examining social and moral influences. The findings of the study revealed a highly significant and positive association of no significant difference between poor and rich farmers prevailing in irrigation systems (p = 0.000; T^c = 0.443); wealthy farmers not receiving a better water supply (p = 0.000; T^c = 0.345); not paying bribes to authorities to obtain a better share of irrigation water (p = 0.000; T^c = 0.325); not practising irrigation water stealing (p = 0.000; T^c = 0.451); encroaching on watercourses is socially proscribed (p = 0.000; T^c = 0.245); social rejection of polluting water (p = 0.000; T^c = 0.238); and flowing irrigation water management roles and principles such as moral and social responsibility (p = 0.000; T^c = 0.252), with farmer satisfaction with irrigation water distribution.

This study presents a multi-objective optimization method for the design of irrigation pipe networks based on a hybrid harmony search algorithm (HEV-HS). The primary motivations for this study are the challenges of uneven flow, water pressure distribution and frequent pipe failures commonly encountered in large-scale irrigation pipe network systems. The proposed method minimizes the investment cost of the pipe network and the variance of the surplus head at nodes. A generalized multi-objective optimization model was formulated to enhance the economic efficiency and operational reliability of irrigation networks. The proposed HEV-HS algorithm combines harmony search with energy valley optimization and incorporates dynamic adaptive step-size adjustment alongside an iterative control factor mechanism to increase the ability of the algorithm to escape local optima and improve the quality of the solution set. Simulation tests demonstrated the effectiveness of the proposed method in solving high-dimensional, complex optimization problems, achieving superior convergence speed and solution quality. An application involving a drip irrigation project in Xinjiang, China shows that the optimized scheme reduces investment costs by 5.1% and decreases the variance of the node surplus hydraulic head by 7.5%. These results confirm the validity and practicality of the method and its potential to improve pressure uniformity and cost efficiency in irrigation pipe network design.

Excessive irrigation significantly reduces rice (Oryza sativa L.) water productivity in Pakistan. This study evaluated crop water requirements, irrigation trends and water productivity across Pakistan's rice-growing regions. Field data on crop yield, soil characteristics, irrigation practices and 10 years of weather data were collected from 11 districts across four provinces. The FAO AquaCrop model was used to assess crop water requirements (evapotranspiration, ET), the root zone water balance and water productivity. The crop water requirements ranged from 787 to 1151 mm, while irrigation consistently exceeded these needs by 95% to 123%. The irrigation water productivity (WPi) ranged from 0.09 to 0.19 kg/m³, and the evapotranspiration (ET) water productivity (WPet) ranged from 0.20 to 0.41 kg/m³. Excessive irrigation, 2 to 3 times the actual crop water needs, is attributed to traditional practices, a lack of knowledge and suboptimal irrigation schedules. Optimizing irrigation scheduling, adopting advanced technologies, and using high-yielding, drought-tolerant rice varieties could reduce water losses and improve crop yields. These findings offer actionable strategies to increase water productivity and ensure food security in Pakistan's rice-growing regions, with potential applications in other water-scarce, rice-producing countries facing similar challenges.