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1 Reynolds, C.; Yitayew, M.; Petersen, M. 1995. Low-head bubbler irrigation systems. Part I: Design. Agricultural Water Management, 29(1):1-24.

Irrigation design ; Gravity flow ; Irrigation systems ; Small scale systems ; Hydraulics ; Mathematical models

(Location: IWMI-HQ Call no: PER Record No: H017779)

Low-head bubbler systems differ from other micro-irrigation systems because they are based on gravity-flow, can operate at pressure as low as 1 m (3.3 ft) and do not require elaborate filtration systems. Despite their simplicity and advantages, low-head bubbler systems lack a well-defined design procedure to facilitate design and installation. A comprehensive design procedure for flow-head bubbler systems is presented and an example gradual slope design is given in detail. The design procedure utilizes head loss gradient charts based on the Darcy-Weisbach equation and the delivery hose elevations are calculated from the energy equation.

2 Reynolds, C.; Yitayew, M. 1995. Low-head bubbler irrigation systems. Part II: Air lock problems. Agricultural Water Management, 29(1):25-35.

Irrigation design ; Gravity flow ; Irrigation systems ; Small scale systems ; Water distribution ; Hydraulics ; Velocity

(Location: IWMI-HQ Call no: PER Record No: H017780)

Air locks may occur in pipelines of low-pressure, gravity-flow bubbler irrigation systems located on level fields and with design heads as low as one meter (3.3 ft). Air locks in bubbler systems can partially or entirely block the flow of water, and thereby significantly decrease the uniformity of water application. To develop design criteria to prevent air locks from occurring in the delivery hoses, hydraulic laboratory experiments were conducted in the laboratory for smooth plastic hoses with internal diameters of 6, 8, 10, and 13 mm (1/4, 5/16, 3/8, and 1/2 in). Hose diameters less than 6 mm (1/4 in) and greater than 10 mm (3/8 in) are recommended for low- head bubbler systems due to excessive friction losses and poor water distribution uniformity, respectively. For bubbler systems with design heads less than 2 meters (6.6 ft), the 10 mm (3/8 in) diameter hose is recommended with design flows and velocities greater than 1.7 1/min (0.42 US gal/min) and 0.37 m/s (1.2 ft s), respectively. For systems with design head greater than 2 meters (6.6 ft), the 6 mm (1/4 in) diameter hose is recommended with design flows and velocities greater than 0.5 1/min (0.15 US gal/min) and 0.29 m/s (1.0 ft s) respectively.

3 Mishra, D.; Das, B. S.; Sinha, T.; Hoque, J. M.; Reynolds, C.; Islam, M. R.; Hossain, M.; Sar, P.; Menon, M. 2021. Living with arsenic in the environment: an examination of current awareness of farmers in the Bengal Basin using hybrid feature selection and machine learning. Environment International, 153:106529. (Online first) [doi: https://doi.org/10.1016/j.envint.2021.106529]

Drinking water ; Arsenic ; Contamination ; Awareness ; Farmers ; Farming systems ; Communities ; Socioeconomic environment ; Water supply ; Irrigation ; Public health ; Policies ; Machine learning ; Models / Bangladesh / India / Bengal Basin / West Bengal

(Location: IWMI HQ Call no: e-copy only Record No: H050292)

https://www.sciencedirect.com/science/article/pii/S0160412021001549/pdfft?md5=3520f677cef94fd26d81d0009caa2d29&pid=1-s2.0-S0160412021001549-main.pdf
https://vlibrary.iwmi.org/pdf/H050292.pdf

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High levels of arsenic in drinking water and food materials continue to pose a global health challenge. Over 127 million people alone in Bangladesh (BD) and West Bengal (WB) state of India are exposed to elevated levels of arsenic in drinking water. Despite decades of research and outreach, arsenic awareness in communities continue to be low. Specifically, very few studies reported arsenic awareness among low-income farming communities. A comprehensive approach to assess arsenic awareness is a key step in identifying research and development priorities so that appropriate stakeholder engagement may be designed to tackle arsenic menace. In this study, we developed a comprehensive arsenic awareness index (CAAI) and identified key awareness drivers (KADs) of arsenic to help evaluate farmers’ preferences in dealing with arsenic in the environment. The CAAI and KADs were developed using a questionnaire survey in conjunction with ten machine learning (ML) models coupled with a hybrid feature selection approach. Two questionnaire surveys comprising of 73 questions covering health, water and community, and food were conducted in arsenic-affected areas of WB and BD. Comparison of CAAIs showed that the BD farmers were generally more arsenic-aware (CAAI = 7.7) than WB farmers (CAAI = 6.8). Interestingly, the reverse was true for the awareness linked to arsenic in the food chain. Application of hybrid feature selection identified 15 KADs, which included factors related to stakeholder interventions and cropping practices instead of commonly perceived factors such as age, gender and income. Among ML algorithms, classification and regression trees and single C5.0 tree could estimate CAAIs with an average accuracy of 84%. Both communities agreed on policy changes on water testing and clean water supply. The CAAI and KADs combination revealed a contrasting arsenic awareness between the two farming communities, albeit their cultural similarities. Specifically, our study shows the need for increasing awareness of risks through the food chain in BD, whereas awareness campaigns should be strengthened to raise overall awareness in WB possibly through media channels as deemed effective in BD.