Irrigation and Drainage最新文献

Groundwater is an essential nonrenewable resource for agricultural activities. In this study, groundwater samples were collected from the Shouguang area, and the level of groundwater contamination was investigated by measuring the NO₃⁻, SO₄²⁻, F⁻, Cl⁻, Ca²⁺, Mg²⁺, total dissolved solids (TDS) and chemical oxygen demand (COD). Exploratory data analysis was employed initially to study the hydrochemical characteristics and the sources of pollutants. Finally, the groundwater quality was measured using principal component analysis, entropy weight and complex correlation coefficient methods. As a common observation, the groundwater in the Shouguang area is slightly alkaline, so Ca²⁺, Mg²⁺ and NO₃⁻ acted as predominant pollutants. These contaminants originated from the excessive use of chemical fertilizers and large-scale sewage irrigation. Second, perennial overexploitation of groundwater in Shouguang led to the generation of funnels and led to seawater intrusion. As a result, Cl⁻ and TDS in the water samples collected from the north Shouguang area exceeded the regulatory guideline value, which indicates the risk of land salinization. However, the measured concentrations of SO₄²⁻, F⁻ and COD were within the normal range. This confirms the minimal contribution of industries to groundwater pollution. East of the Ni River the groundwater is severely polluted, and the detected concentrations of pollutants are far beyond the standard limit and pose a potential risk to human health. Therefore, protection and treatment are urgently needed.

The primary source of water for irrigation and other agricultural activities is rainfall. It has an immediate effect on crop growth and productivity. Forecasting this rainfall in advance allows farmers to effectively plan their cropping pattern. In recent years, forecasting rainfall has become very popular due to the availability of the latest computation techniques. Artificial neural networks (ANNs) are one such technique widely used for rainfall prediction by a number of researchers. These models are more reliable as they make better predictions because of their nonlinear data learning method. In the present study, an ANN model was developed to predict the annual, monsoon and postmonsoon season rainfall. The model was developed using 34 years of data from 1985 to 2018 in the command area of the Loktak Lift Irrigation Project in Manipur, India. The ANN model was trained using the rectified linear unit (ReLU) activation function. The 3-year input model excelled in all seasons, with the best model achieving a 0.36 coefficient of determination (R²), 75.7 root mean square error, 0.60 correlation coefficient and 62.5 mean absolute error. These performance indicators were comparable with studies performed by other researchers. Thus, the model can be adopted for the study area.

High evapotranspiration and low precipitation are known as the main challenging factors for pistachio (Pistacia vera L.) orchards situated in arid and semi-arid regions. Therefore, it is necessary to take some measures to mitigate surface evaporation. This study was carried out to assess water productivity (WP) as well as yield and annual shoot growth of pistachios using a new method of irrigation known as the stratified vertical gravel tube subsurface drip irrigation (SVGTSD) system in a 15-year-old pistachio orchard in an arid region in Iran. In this system, each tree contained four vertical gravel columns with different lengths. A randomized complete block design with a split-plot arrangement with three replicates (five trees in each plot) for 3 years was used. Three irrigation regimes included 100% crop evapotranspiration (100% ET_c), 85% ET_c and 70% ET_c (as the main plots), and seven vertical gravel column with a depth arrangement of 40–40–40–40 cm (using a gravel column from the lateral pipe level and without a gravel tube as the control) and gravel-filled tubes with depths of 10–10–10–10 cm, 10–10–20–20 cm, 10–10–30–30 cm, 10–10–20–30 cm, 10–10–20–40 cm and 10–10–20–50 cm (all 30 cm below ground level) (as subplots) were used. The results showed that the different depths of gravel tube placement significantly affected the annual shoot growth and yield. The deeper the tube was placed, the greater the yield and annual shoot growth, resulting in 10–10–20–50 cm being the most productive. Regarding tree growth, yield and WP, the best performance was observed at full irrigation (100% ET_c) with a 10–10–20–50-cm vertical gravel tube arrangement. Furthermore, in this subsurface irrigation method, there was no concern regarding emitter clogging by roots, root accumulation around the emitters or root intrusion into the emitters. In addition, having a low additional cost (only 13.9%) in comparison with conventional subsurface drip irrigation together with a higher yield (3475 kg ha⁻¹), WP (0.9 kg m⁻³) and shoot growth (35 cm), SVGTSD is more economical and feasible compared to other irrigation methods and can be extensively applied in pistachio orchards.

The engagement of farmers in the governance of farm irrigation systems is crucial for meeting irrigation demands and enhancing farm productivity. Theoretically, grassroots organizations' concerns and support for farmers will encourage them to participate in the activities of the organization, thus improving the management performance of the irrigation system. This paper examines the influence of organizational aid on the governance of agricultural irrigation systems using field survey data in the Yellow River basin, China. The seemingly unrelated regression model is used to explore the group disparities under distinct organizational circumstances and farm household characteristics. The study demonstrates that the software and hardware support provided by organizations can promote improved management performance of irrigation systems. In addition, considering the heterogeneity of organizational environments, such support is more conducive to enhancing the governance of systems in organizations with more cooperative atmospheres and higher degrees of fairness. From the perspective of the heterogeneity of system users, providing organizational support to growers with a low degree of nonagricultural transformation and labour shortage is more conducive to improving governance performance. Consequently, establishing an excellent organizational atmosphere and targeting organizational support to farmers is a viable means to optimize the governance of irrigation systems.

Growing water imbalance requires a systematic development process to enable the agriculture sector to address what it faces as challenges. However, the overall longevity and efficiency of developed infrastructure become doubtful if water users are not involved in the development process. Thus, the assessment of the impact of irrigation improvement on all sides of the management, including smallholders, is fundamental. The paper investigates the impact of irrigation improvement on farmers' satisfaction with transferred water services in the Old Lands in Egypt. A counterfactual analysis, relying on four alternative estimation methods, is introduced to measure the average treatment effect of irrigation improvement on farmers' perceptions of reliability, flexibility and equity of the water service. Such indicators' selection was planned under the assumption that combined social and engineering-based approaches to impact assessments are more suitable to represent the perspectives of all stakeholders. The results of the analysis are consistent and show that increases in perceptions are positive and significant in each case, as the result of the improvement. The paper argues that modern infrastructure framed in successful co-management can work towards a mutual interest.

This study was conducted to identify the determining factors of participation in irrigated farming and to estimate its impact on households' farm income and food security using cross-sectional data collected from Gimbo District, south-west Ethiopia. Primary data for this study were collected from 200 irrigator and 219 non-irrigator households using a structured questionnaire. Both descriptive and econometric analyses were employed to analyse the data using farm income, calorie intake, binary food security and dietary diversity as the outcome variables. As the propensity score matching result revealed, small-scale irrigation significantly and positively increases calorie intake, annual farm income and diet group by 320 kcal, 7653 Ethiopian birr (ETB) and 0.65 points, respectively. The results obtained from the logit model further revealed that the age of the household head, education level of the household head, distance of land from the irrigation source, land size, off-/nonfarm income, distance from the nearest market, slope of the land and access to irrigation services are the variables that were found to significantly affect participation in irrigation. Given the significant contributions of small-scale irrigation to rural households' annual farm income and food security, policy priorities should be placed on awareness creation about the relevance of irrigation technology by informing households of how much irrigator households differ from non-irrigators in terms of their annual farm income and food security. The study further recommends that the government and any other concerned bodies ought to toil in the expansion of irrigated farming and technological development of small-scale irrigation schemes.

The aim of this study was to determine the health risk associated with vegetable irrigation using lowland water in the town of Mbouda. Watered vegetables and water from five yards and three wells used by market gardeners were analysed in the dry season using standardized methods. Bacterial levels ranging from 6.37 ± 0.71 to 9.03 ± 0.43 Log CFU/100 g/DM (dry matter) were detected in the various vegetables produced in the lowlands of Mbouda: Escherichia coli (4.10–5.03 Log CFU/100 mL), faecal coliforms (5.28–5.99 Log CFU/100 mL), Shigella spp. (4.86–6.25 Log CFU/100 mL) and Salmonella spp. (3.85–5.21 Log CFU/100 mL) in irrigation water; Ascaris spp. eggs, Entamoeba spp. cysts, Ancylostoma spp. eggs and nematode larvae were detected at levels above the standard recommended by the World Health Organization. This sets 3 Log CFU/100 mL of these bacteria in water, 1–2 Log CFU/25 g/DM on vegetables, but 3 Log CFU/25 g/DM for faecal coliforms as acceptable limits and zero for any parasitic stage (eggs, cysts, and larvae). This constitutes a real health risk for consumers. The town's virtually nonexistent sewage system could be at the root of this water pollution.