2019
DOI: 10.1029/2019gl083937
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Small Ponds in Headwater Catchments Are a Dominant Influence on Regional Nutrient and Sediment Budgets

Abstract: Small ponds—farm ponds, detention ponds, or impoundments below 0.01 km2—serve important human needs throughout most large river basins. Yet the role of small ponds in regional nutrient and sediment budgets is essentially unknown, currently making it impossible to evaluate their management potential to achieve water quality objectives. Here we used new hydrography data sets and found that small ponds, depending on their spatial position within both their local catchments and the larger river network, can domina… Show more

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Cited by 58 publications
(42 citation statements)
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References 40 publications
(54 reference statements)
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“…Holgerson and Raymond (2016) found extremely small ponds (<0.001 km 2 ) are responsible for 15% of CO 2 emissions, while Cheng and Basu (2017) found half of total nitrogen removal from lentic waterbodies occurred in wetlands < 0.001 km 2 . Finally, small connected ponds (<0.01 km 2 ) are responsible for 34%, 69%, and 12% of nitrogen, phosphorous, and sediment retention in the northeastern US, respectively, and this is most pronounced in the headwaters (Schmadel et al., 2019). Here, however, we show that at mean annual flow lake influence for potential evasion of terrestrial CO 2 in the Connecticut River system is most pronounced downstream of the headwaters.…”
Section: Resultsmentioning
confidence: 99%
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“…Holgerson and Raymond (2016) found extremely small ponds (<0.001 km 2 ) are responsible for 15% of CO 2 emissions, while Cheng and Basu (2017) found half of total nitrogen removal from lentic waterbodies occurred in wetlands < 0.001 km 2 . Finally, small connected ponds (<0.01 km 2 ) are responsible for 34%, 69%, and 12% of nitrogen, phosphorous, and sediment retention in the northeastern US, respectively, and this is most pronounced in the headwaters (Schmadel et al., 2019). Here, however, we show that at mean annual flow lake influence for potential evasion of terrestrial CO 2 in the Connecticut River system is most pronounced downstream of the headwaters.…”
Section: Resultsmentioning
confidence: 99%
“…However, most work on gas evasion at network scales neglects to acknowledge the two systems' intrinsic connectivity via transport mechanics and network topology (Crawford et al, 2014;Fergus et al, 2017;Gardner et al, 2019;Wetzel, 2001). This disconnect is beginning to be addressed in related subfields like sediment transport (Czuba & Foufoula-Georgiou, 2015;Czuba et al, 2017) and nutrient transport (Bertuzzo et al, 2017;Schmadel et al, 2018Schmadel et al, , 2019Wollheim et al, 2008). A preliminary treatment of nitrous oxide emissions from rivers versus reservoirs has also been performed (Maavara et al, 2019).…”
mentioning
confidence: 99%
“…Hereafter, our use of 'regional' refers to these basins. Input data for our model are based on extensive measurements of nitrogen sources and riverine loads in the Northeastern United States described previously by Schmadel et al (2019) and detailed in the supplementary material.…”
Section: Methodsmentioning
confidence: 99%
“…given that the simple scaling model presented omits key factors that influence river network biogeochemistry, including biogeochemical activity in the water column of larger rivers 34,38 ; hydrologic dynamics in the streambed 39 ; ponded waters (including reservoirs and floodplains) 40,41 ; saturating reaction kinetics 3 ; stoichiometry 42 ; climate regime 43 ; and spatially heterogeneous material loading 44 .…”
Section: Merging Observations With Scaling Theorymentioning
confidence: 99%
“…zero-order process rates) but potentially allowed to vary with stream size (Equation 2). The second approach applied first-order reaction kinetics as is commonly assumed in network models of nutrient or carbon flux 41,47 . In this approach, a reaction rate as uptake velocity (L T -1 ) is applied, where the local areal process rate by the stream bottom is then determined by concentration of reactant in the water column.…”
Section: Conceptual Overviewmentioning
confidence: 99%