UK Environmental Change Network (ECN) soil solution chemistry data: 1992-2015

Rennie, S.; Adamson, J.; Anderson, Robert F.; Andrews, C.; Bater, J.; Bayfield, N.; Beaton, K.; Beaumont, D. A.; Benham, Sue; Bowmaker, V.; Britt, C.; Brooker, Rob W.; Brooks, David R.; Brunt, J.; Common, G.; Cooper, Ruth; Corbett, S.; Critchley, N.; Dennis, Peter; Dick, Jan; Dodd, B.; Dodd, N.; Donovan, N.; Easter, J.; Flexen, M.; Gardiner, A.; Hamilton, D. C.; Hargreaves, P.; Hatton‐Ellis, M.; Howe, M.; Kahl, Jeffrey S.; Lane, M.; Langan, Simon; Lloyd, D.; McCarney, B.; McElarney, Y.; McKenna, C.; McMillan, S.; Milne, F.; Milne, Lorus J.; Morecroft, Michael D.; Murphy, Margaret B.; Nelson, A.; Nicholson, H.; Pallett, D.; Parry, D.; Pearce, Imojen; Pozsgai, G.; Rose, Rob; Schäfer, Stefanie; Scott, T.; Sherrin, L.; Shortall, C. R.; Smith, P.; Smith, R. I.; Tait, Ruth; Taylor, C.; Taylor, M.; Thurlow, Martha L.; Turner, A.; Tyson, K. C.; Watson, Helen; Whittaker, M.; Wood, C.D.

doi:10.5285/b330d395-68f2-47f1-8d59-3291dc02923b

Cited by 2 publications

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“…Groundwater from deeper zones is typically more enriched in base cations than shallow water (Anderson et al, 1997); in contrast, organic materials rich in carbon-, nitrogen-, and iron-containing solutes are often more abundant in the shallow soils (Lidman et al, 2017;Tittel et al, 2022;. Although no detailed and consistent information on the sources of solutes is available from the four study catchments, collated soil and groundwater chemistry at Plynlimon (Neal et al, 2004;Shand et al, 2005;Stewart et al, 2022) and soil water data at the ECN sites (Rennie et al, 2017a) supports these vertical sources. We therefore group solutes such as DOC, nitrate, iron, and aluminium as more from shallow subsurface, and cations from groundwater.…”

Section: High Variability In Mobilization Behaviour With Wetness For ...mentioning

confidence: 94%

Hydrologic connectivity and source heterogeneity control concentration–discharge relationships

Knapp

Musolff

2022

Hydrological Processes

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Changes in streamwater chemistry have frequently been used to understand the storage and release of water and solutes at the catchment scale. Streamwater chemistry typically varies in space and time, depending on sources, mobilization mechanisms, and pathways of water and solutes. However, less is known about the role of lateral hydrologic connectivity and how it may influence streamwater chemistry and solute export patterns under different wetness conditions. This study analyses longterm low-frequency data from four UK catchments using antecedent catchment wetness as proxy for lateral hydrologic connectivity. We demonstrate that solute mobilization mechanisms can vary depending on catchment wetness, as different catchment areas become hydrologically connected to or disconnected from streams.We show that flow and streamwater chemistry are mostly decoupled under dry conditions, leading to stronger impacts of the heterogeneity in solute sources on mobilization patterns during dry conditions compared to wet conditions. Our results demonstrate that the lateral and vertical distributions of solutes need to be integrated and considered together with the temporally variable hydrologic connectivity of these lateral areas to the stream when assessing streamwater chemistry. This combined analysis thus enables inferences regarding the lateral distribution of solutes throughout the catchment; it also indicates that a better understanding of the relationship between lateral hydrologic connectivity and the lateral and vertical distributions of solute concentrations can help to identify particularly vulnerable points in the catchment and their potential polluting effects on streams.

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Section: High Variability In Mobilization Behaviour With Wetness For ...mentioning

confidence: 94%

Hydrologic connectivity and source heterogeneity control concentration–discharge relationships

Knapp

Musolff

2022

Hydrological Processes

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The UK Environmental Change Network datasets – integrated and co-located data for long-term environmental research (1993–2015)

Rennie

Andrews

Atkinson

et al. 2020

Earth Syst. Sci. Data

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Abstract. Long-term datasets of integrated environmental variables, co-located together, are relatively rare. The UK Environmental Change Network (ECN) was launched in 1992 and provides the UK with its only long-term integrated environmental monitoring and research network for the assessment of the causes and consequences of environmental change. Measurements, covering a wide range of physical, chemical, and biological “driver” and “response” variables are made in close proximity at ECN terrestrial sites using protocols incorporating standard quality control procedures. This paper describes the datasets (there are 19 published ECN datasets) for these co-located measurements, containing over 20 years of data (1993–2015). The data and supporting documentation are freely available from the NERC Environmental Information Data Centre under the terms of the Open Government Licence using the following DOIs. Meteorology Meteorology: https://doi.org/10.5285/fc9bcd1c-e3fc-4c5a-b569-2fe62d40f2f5 (Rennie et al., 2017a) Biogeochemistry Atmospheric nitrogen chemistry: https://doi.org/10.5285/baf51776-c2d0-4e57-9cd3-30cd6336d9cf (Rennie et al., 2017b) Precipitation chemistry: https://doi.org/10.5285/18b7c387-037d-4949-98bc-e8db5ef4264c (Rennie et al., 2017c) Soil solution chemistry: https://doi.org/10.5285/b330d395-68f2-47f1-8d59-3291dc02923b (Rennie et al., 2017d) Stream water chemistry: https://doi.org/10.5285/fd7ca5ef-460a-463c-ad2b-5ad48bb4e22e (Rennie et al., 2017e) Stream water discharge: https://doi.org/10.5285/8b58c86b-0c2a-4d48-b25a-7a0141859004 (Rennie et al., 2017f) Invertebrates Moths: https://doi.org/10.5285/a2a49f47-49b3-46da-a434-bb22e524c5d2 (Rennie et al., 2017g) Butterflies: https://doi.org/10.5285/5aeda581-b4f2-4e51-b1a6-890b6b3403a3 (Rennie et al., 2017h) Carabid beetle: https://doi.org/10.5285/8385f864-dd41-410f-b248-028f923cb281 (Rennie et al., 2017i) Spittle bugs: https://doi.org/10.5285/aff433be-0869-4393-b765-9e6faad2a12b (Rennie et al., 2018) Vegetation Baseline: https://doi.org/10.5285/a7b49ac1-24f5-406e-ac8f-3d05fb583e3b (Rennie et al., 2016a) Coarse grain: https://doi.org/10.5285/d349babc-329a-4d6e-9eca-92e630e1be3f (Rennie et al., 2016b) Woodland: https://doi.org/10.5285/94aef007-634e-42db-bc52-9aae86adbd33 (Rennie et al., 2017j) Fine grain: https://doi.org/10.5285/b98efec8-6de0-4e0c-85dc-fe4cdf01f086 (Rennie et al., 2017k) Vertebrates Frogs: https://doi.org/10.5285/4d8c7dd9-8248-46ca-b988-c1fc38e51581 (Rennie et al., 2017l) Birds (Breeding bird survey): https://doi.org/10.5285/5886c3ba-1fa5-49c0-8da8-40e69a10d2b5 (Rennie et al., 2017m) Birds (Common bird census): https://doi.org/10.5285/8582a02c-b28c-45d2-afa1-c1e85fba023d (Rennie et al., 2017n) Bats: https://doi.org/10.5285/2588ee91-6cbd-4888-86fc-81858d1bf085 (Rennie et al., 2017o) Rabbits and deer: https://doi.org/10.5285/0be0aed3-f205-4f1f-a65d-84f8cfd8d50f (Rennie et al., 2017p)

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UK Environmental Change Network (ECN) soil solution chemistry data: 1992-2015

Cited by 2 publications

References 0 publications

Hydrologic connectivity and source heterogeneity control concentration–discharge relationships

Hydrologic connectivity and source heterogeneity control concentration–discharge relationships

The UK Environmental Change Network datasets – integrated and co-located data for long-term environmental research (1993–2015)

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