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Anbumozhi, Venkatachalam; Matsumoto, Kunihiko; Yamaji, Eiji

doi:10.1023/a:1014420822465

Cited by 41 publications

(12 citation statements)

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“…Surface area was determined using Google Earth satellite imagery. Reservoir volume was calculated using the formula for a prismoid by assuming that all sites maintained their original shape, including slopes of 1.5 : 1 ratio (Andresen et al, 2015). From these measurements, an Index of Basin Permanence (IBP) was calculated (Kerekes, 1977).…”

Section: Abiotic and Biotic Variablesmentioning

confidence: 99%

“…The global abundance of these systems remains uncertain (Verpoorter et al, 2014), but statistical extrapolation suggest there may be around 16 million artificial reservoirs worldwide (Lehner et al, 2011). Regional-scale inventories indicate that collectively upwards of 8 million farm reservoirs exist in the USA (Brunson, 1999;Smith et al, 2002), China (Chen et al, 2019), India (Anbumozhi et al, 2001), South Africa (Mantel et al, 2017), and Australia alone (Lowe et al, 2005;MDBA, 2008;Grinham et al, 2018a). The density of farm reservoirs can exceed 30 % of agricultural area in some regions such as China where food demand is high (Chen et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Regulation of carbon dioxide and methane in small agricultural reservoirs: optimizing potential for greenhouse gas uptake

et al. 2019

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Abstract. Small farm reservoirs are abundant in many agricultural regions across the globe and have the potential to be large contributing sources of carbon dioxide (CO2) and methane (CH4) to agricultural landscapes. Compared to natural ponds, these artificial waterbodies remain overlooked in both agricultural greenhouse gas (GHG) inventories and inland water global carbon (C) budgets. Improved understanding of the environmental controls of C emissions from farm reservoirs is required to address and manage their potential importance in agricultural GHG budgets. Here, we conducted a regional-scale survey (∼ 235 000 km2) to measure CO2 and CH4 surface concentrations and diffusive fluxes across 101 small farm reservoirs in Canada's largest agricultural area. A combination of abiotic, biotic, hydromorphologic, and landscape variables were modelled using generalized additive models (GAMs) to identify regulatory mechanisms. We found that CO2 concentration was estimated by a combination of internal metabolism and groundwater-derived alkalinity (66.5 % deviance explained), while multiple lines of evidence support a positive association between eutrophication and CH4 production (74.1 % deviance explained). Fluxes ranged from −21 to 466 and 0.14 to 92 mmol m−2 d−1 for CO2 and CH4, respectively, with CH4 contributing an average of 74 % of CO2-equivalent (CO2-e) emissions based on a 100-year radiative forcing. Approximately 8 % of farm reservoirs were found to be net CO2-e sinks. From our models, we show that the GHG impact of farm reservoirs can be greatly minimized with overall improvements in water quality and consideration to position and hydrology within the landscape.

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Section: Abiotic and Biotic Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Regulation of carbon dioxide and methane in small agricultural reservoirs: optimizing potential for greenhouse gas uptake

et al. 2019

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“…There are about 127,000 tanks in the southern region consisting of Andhra Pradesh, Tamil Nadu and Karnataka state. Tamil Nadu is a water-scarce state with annual per capita water availability of about 900 cm 3 as against India's average of 2,200 cm 3 (Anbumozhi et al 2001). Most of the rivers in Tamil Nadu flow only during the monsoon season and it is not possible to construct more large-scale reservoirs due to the flat landscape (Arumugam et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Real-time monitoring of water level and storage dynamics of irrigation tank using IoT

et al. 2020

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The internet of things (IoT), an emerging technological marvel, consists of a group of physical objects such as vehicles, machines and sensors to monitor and transfer data over the internet with much less human to machine interaction. It relies on a host of technologies like application programming interfaces (API), which in turn, help the devices to get connected with the internet. Efficient irrigation tank management requires a strong database on continuous water level dynamics for irrigation decision-making. Real-time tank water level monitoring is possible through an IoT device by integrating sensors and microcontroller that can send the water level data to the cloud. Google sheet is used to store the water level data that can be viewed using web application as well as mobile application. The contour map of the study tank is used to develop the stage (water level) vs volume curve. The volume of water present in the tank at any time can be arrived at for any tank water level using the above curve. The developed device can provide real-time continuous water level data with low cost and simple infrastructure, thus aiding tank water management.

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“…The global abundance of these systems remains uncertain (Verpoorter et al, 2014), but statistical extrapolation suggest there may be around 16 million worldwide (Lehner et al, 2011). Regional-scale inventories indicate that upwards of 8 million farm reservoirs exist in the USA (Brunson, 1999;Smith et al, 2002), China (Chen et al, 2019), India (Anbumozhi et al, 2001), South Africa (Mantel et al, 2017), and Australia alone (Lowe et al, 2005;MDBA, 2008;Grinham et al, 2018a). The density of farm reservoirs can exceed 30% of agricultural area in some regions such as China where food demand is high (Chen et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Regulation of carbon dioxide and methane in small agricultural reservoirs: Optimizing potential for greenhouse gas uptake

Webb¹,

Leavitt²,

Simpson³

et al. 2019

Preprint

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Abstract. Small farm reservoirs are abundant in many agricultural regions across the globe and have the potential to be large contributing sources of carbon dioxide (CO2) and methane (CH4) to agricultural landscapes. Compared to natural ponds, these artificial waterbodies remain overlooked in both agricultural greenhouse gas (GHG) inventories and inland water global carbon (C) budgets. Improved understanding of the environmental controls of C emissions from farm reservoirs is required to address and manage their potential importance. Here, we conducted a regional scale survey (~ 235,000 km2) to measure CO2 and CH4 concentrations and diffusive fluxes across 101 small farm reservoirs in Canada's largest agricultural area. A combination of abiotic, biotic, hydromorphologic, and landscape variables were modelled using generalized additive models (GAMs) to identify regulatory mechanisms. We found that CO2 concentration was best estimated by a combination of internal metabolism and groundwater-derived alkalinity (65.7 % deviance explained), while multiple lines of evidence support a positive association between eutrophication and CH4 production (74.1 % deviance explained). Fluxes ranged from −21 to 466 and 0.14 to 92 mmol m−2 d−1 for CO2 and CH4, respectively, with CH4 contributing an average of 74% of CO2-equivalent (CO2-e) emissions. Approximately 19 % farm reservoirs were found to be net CO2-e sinks. From our models, we show that the GHG impact of farm reservoirs can be greatly minimised through overall improvements in water quality and the construction and maintenance of deeper reservoirs.

show abstract

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Cited by 41 publications

References 0 publications

Regulation of carbon dioxide and methane in small agricultural reservoirs: optimizing potential for greenhouse gas uptake

Regulation of carbon dioxide and methane in small agricultural reservoirs: optimizing potential for greenhouse gas uptake

Real-time monitoring of water level and storage dynamics of irrigation tank using IoT

Regulation of carbon dioxide and methane in small agricultural reservoirs: Optimizing potential for greenhouse gas uptake

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