Influence of snow on the hydrology and hydrochemistry of the Allt a' Mharcaidh, Cairngorm mountains, Scotland

Helliwell, Rachel; Soulsby, Chris; Ferrier, Robert C.; Jenkins, Alan; Harriman, R.

doi:10.1016/s0048-9697(98)00165-x

Cited by 37 publications

(26 citation statements)

References 18 publications

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“…The Allt a'Mharcaidh (MHAR) is located in the Cairngorm Mountains at elevations between 330 and 1020 m. The sub-arctic climate results in relatively low precipitation of about 1100 mm yr −1 and mean annual temperatures of 5.3 • C. In this study it is the only catchment that receives significant amounts of precipitation as snow (∼ 30 %;Helliwell et al, 1998). It is underlain by fractured granite of lower Old Red Sandstone age, covered by thick deposits of locallyderived drift of up to 10 m in depth .…”

Section: Study Areamentioning

confidence: 93%

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

Hrachowitz

Savenije

Bogaard

et al. 2013

Hydrol. Earth Syst. Sci.

272

443

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Abstract. The complex interactions of runoff generation processes underlying the hydrological response of streams remain not entirely understood at the catchment scale. Extensive research has demonstrated the utility of tracers for both inferring flow path distributions and constraining model parameterizations. While useful, the common use of linearity assumptions, i.e. time invariance and complete mixing, in these studies provides only partial understanding of actual process dynamics. Here we use long-term (< 20 yr) precipitation, flow and tracer (chloride) data of three contrasting upland catchments in the Scottish Highlands to inform integrated conceptual models investigating different mixing assumptions. Using the models as diagnostic tools in a functional comparison, water and tracer fluxes were then tracked with the objective of exploring the differences between different water age distributions, such as flux and resident water age distributions, and characterizing the contrasting water age pattern of the dominant hydrological processes in the three study catchments to establish an improved understanding of the wetness-dependent temporal dynamics of these distributions.The results highlight the potential importance of partial mixing processes which can be dependent on the hydrological functioning of a catchment. Further, tracking tracer fluxes showed that the various components of a model can be characterized by fundamentally different water age distributions which may be highly sensitive to catchment wetness history, available storage, mixing mechanisms, flow path connectivity and the relative importance of the different hydrological processes involved. Flux tracking also revealed that, although negligible for simulating the runoff response, the omission of processes such as interception evaporation can result in considerably biased water age distributions. Finally, the modeling indicated that water age distributions in the three study catchments do have long, power-law tails, which are generated by the interplay of flow path connectivity, the relative importance of different flow paths as well as by the mixing mechanisms involved. In general this study highlights the potential of customized integrated conceptual models, based on multiple mixing assumptions, to infer system internal transport dynamics and their sensitivity to catchment wetness states.

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Section: Study Areamentioning

confidence: 93%

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

Hrachowitz

Savenije

Bogaard

et al. 2013

Hydrol. Earth Syst. Sci.

272

443

View full text Add to dashboard Cite

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“…Rapid changes in water temperature or water chemistry can potentially be detrimental to in-stream ecology (Wilby et al 2015, Helliwell et al 1998). …”

Section: The Historical Picturementioning

confidence: 99%

“…the amount of snow and the timing of any temperature rise and rainfall occurrence) and on the catchment (e.g. via differences in timing of runoff from different altitudes) (Wilby et al 2015), water quality and hydro-ecology (Helliwell et al 1998), and hydro-electric power generation (Harrison et al 2001). …”

Section: Introductionmentioning

confidence: 99%

“…Chemical factors affected were concentrations of nitrate, sodium and calcium ions and silica, along with alkalinity and pH, but concurrent seasonality of water quantity makes interpretation of the results complex. Further analyses for a sub-arctic catchment in Scotland (Soulsby et al 1997;Helliwell et al 1998) also showed a significant influence of snowmelt on water chemistry, with peaks in concentration of certain ions (particularly chlorine ions) and peaks in acidity (troughs in pH) coinciding with snowmelt events. The chemistry of the snowpack itself was shown to vary with altitude and with the amount 11 of snowfall in the winter, and some of the variations are linked to the presence of anthropogenic pollution in the atmosphere (Helliwell et al 1998).…”

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confidence: 95%

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A review of snow in Britain

Kay

2016

Progress in Physical Geography: Earth and Environment

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Climate change is likely to have a significant effect on snow globally, with most effect where current winter temperatures are close to 0°C, including parts of upland Britain. There is evidence of decreasing trends in observations of snowfall and lying snow in Britain, and climate projections suggest a continuation of this trend. Although river flows in Britain are generally dominated by rainfall rather than snowmelt, some upland catchments have a significant snowmelt contribution. There is evidence of changes in observed and projected river flows in some catchments in Britain, linked to changes in snow, but it can be difficult to distinguish the effects of snow changes from those of other concurrent changes (climatic and non-climatic). Flow regime changes in catchments with widespread and prolonged winter snow cover usually involve increases in winter flow and decreases in spring flow, but the effect on catchments with more transient snow cover is less clear, as is the effect on high flows and water quality. Snow can also affect a number of other factors of socioeconomic or environmental importance (e.g. transport and farming). There is some evidence that disruption due to snow may be less frequent in future, but disruption from other types of weather event may increase. The impacts of snow tend to be worse in areas where events occur less frequently, due to unpreparedness, so there is a need to guard against complacency when it comes to future snow events in Britain, which can still be expected despite a likely reduction in frequency. Further modelling of the potential impacts of climate change, including modelling the influence of snow changes as well as other climatic and non-climatic changes, would aid adaptation and encourage mitigation. KeywordsSnowfall, snowmelt, trends, river flows, transport disruption, climate change I IntroductionThe sensitivity of snow and ice to temperature change means that they may provide one of the most obvious signals for climate change (Vaughan et al. 2013). Global warming is already influencing snow and ice processes, with reductions in annual average snow cover extent and earlier snowmelt observed in regions across the northern hemisphere (Stewart 2009, Derksen andBrown 2012). However, the effect of changes in temperature on snowfall and snowmelt (and subsequently on river flows) may be complicated by coincident changes in precipitation, to the extent that impacts may be masked until thresholds are crossed (Stewart 2009). The effects are thus likely to vary by location, for example depending on altitude (Skaugen et al. 2012, Trivedi et al. 2007, Harrison et al. 2001) and atmospheric circulation patterns (Irannezhad et al. 2016, Stewart 2009. Studies suggest that the areas most affected have been those where current winter temperatures are close to 0°C, with less impact in colder or warmer regions (Stewart 2009, Hamlet andLettenmaier 2007). In 2 parts of Britain, particularly Scotland, the climate is in this transitional zone where only a small temperature increase c...

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“…The Cairngorm Mountains are renowned as the snowiest part of the UK (Helliwell et al, 1998). Therefore, the influence of snow packs on acidic episodes must also be considered.…”

Section: Sea-salt Conductivity (µS CMmentioning

confidence: 99%

Acid episodes in the Allt a'Mharcaidh, Scotland: an investigation based on sub-hourly monitoring data and climatic patterns

Bonjean¹,

Hutchins²,

Neal³

2007

Hydrol. Earth Syst. Sci.

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Stream waters in the Allt aMharcaidh catchment (Cairngorms, Scotland) have been monitored for flow, conductivity and pH at sub-hourly resolution; and for a range of chemical, biological and physical parameters, less intensively, since the mid-1980s. The Allt aMharcaidh stream is subject to acidic events (pH<5.5) triggered by both hydrology and sea-salt inputs from the atmosphere. This paper investigates the drivers of these acidic events using variables derived from sub-hourly monitored data. It also examines the influence of the North Atlantic Oscillation (NAO) on episode severity. Sub-hourly datasets are used to derive multiple regression models expressing stream H + concentration as a function of the sea-salt conductivity and the peak instantaneous flow rate amongst other explanatory variables. The relationship between sea-salt conductivity and the NAO is significant but hidden due to issues such as time lags and the influence of atmospheric patterns other than the NAO.

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Influence of snow on the hydrology and hydrochemistry of the Allt a' Mharcaidh, Cairngorm mountains, Scotland

Cited by 37 publications

References 18 publications

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

What can flux tracking teach us about water age distribution patterns and their temporal dynamics?

A review of snow in Britain

Acid episodes in the Allt a'Mharcaidh, Scotland: an investigation based on sub-hourly monitoring data and climatic patterns

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