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Journal ArticleDOI

A Tracer-Based Method for Classifying Groundwater Dependence in Boreal Headwater Streams

01 Oct 2019-Journal of Hydrology (Elsevier)-Vol. 577, pp 123762

AbstractEcosystem protection requires a better definition of groundwater (GW) dependence and tools to measure this dependence. In this study, a classification method for the GW dependence of headwater streams was devised based on the fact that GW affects discharge, thermal regime, and water quality. The method was tested in three boreal headwater streams discharging from two esker aquifers. Spatial and temporal variability of GW dependence were studied in the stream continuum at several locations, by combining continuous measurements of temperature, electrical conductivity, and discharge with discrete sampling of environmental tracers (e.g., stable water isotopes, silica, chloride). The stream tracer index method developed was used to classify stream sections into GW-dominated, GW-surface water (SW) transition, and SW-dominated zones. We found that, spatially, GW dependence along the stream varied widely, with calculated stream tracer index values ranging from 33 to 94%. The GW-dominated areas extended at least 745, 1 682, and 4 202 m downstream from the main GW discharge points in the three streams studied. A stream located in a pristine peatland-dominated catchment was more prone to rapid change from GW- to SW-dominated than two streams located in catchments dominated by peatland forestry. These results suggest that to evaluate the GW dependence of streams, it may be sufficient to sample stream sections only once, during summer low-flow conditions. The proposed method can serve as a water management tool, especially for streams of exceptional ecological importance or in places where anthropogenic activities are expected to change local hydrology and ecology.

Topics: STREAMS (53%), Groundwater (50%)

Summary (4 min read)

1 Introduction

  • The authors combined continuous measurements of discharge, temperature (T), and electrical conductivity (EC) with use of stable water isotopes and other environmental tracers to study the GW-SW transition zones in three boreal streams known to have high proportions of GW from esker aquifers.
  • The authors expected to find a transition zone within which a spring-originated stream turns into a SW-dominated system.
  • By definition, SW is the water in surface storage units (e.g., lakes, streams, rivers, wetlands) and GW is the water underground.
  • This work addresses the following research questions: i).

2 Materials and methods 2.1 Study sites

  • The three streams selected for the study are located in Rokua and Viinivaara esker aquifer areas and are 60 km from each other.
  • The study sites belong to a mid-boreal coniferous forest belt.
  • In the Rokua esker area, the authors selected two streams, Siirasoja and Lohioja, where surrounding peatlands are intensively drained for forestry.
  • The average channel widths and average maximum depths along the streams studied are presented in the Supporting Information Table S1 .

2.1.1 Siirasoja and Lohioja streams in Rokua esker aquifer

  • The aquifer itself is unconfined, but the heavily drained peatlands in the surroundings partly confine the GW [Rossi et al., 2012] .
  • The catchments are located next to each other and the land use consists mainly of peatland forestry and some agricultural land (Table 1 ).
  • Some of the ditches in Siirasoja catchment have no flow and some fully penetrate the peat layer and reach the mineral soil beneath, causing increased GW discharge to the stream.
  • GW discharge has been found to be either diffuse seepage or point type, and is induced by high pressure underneath the peat layer (Rossi et al. 2012) .

2.1.2 Mesioja stream in Viinivaara esker aquifer

  • The authors study stream, Mesioja, discharges from a spring located at the break of slope where the sandy aquifer meets the peat formation and flows partly underground between measurement locations M2 and M3 (Table 1 ).
  • The lower catchment area is mostly pristine peatland with bog-type vegetation.
  • The GW dependence of the peatland area varies widely; spatial isotope studies by Isokangas et al. (2017) showed that the stable isotopic composition of the peatland pore water is not uniform near Mesioja stream, with δ 18 O values ranging between approximately -8‰ and -13‰ at 10 cm depth during the period 4-11 August 2014.

2.2 Field measurements

  • Stable isotopic composition of water samples was analyzed using cavity ring-down spectroscopy with a Picarro L2120-i analyzer and the isotope ratios were expressed in δ notation relative to Vienna Standard Mean Ocean Water , with precision for δ 18 O and δ 2 H values of ±0.1‰ and ±1.0‰, respectively.
  • Nutrients, alkalinity, and geochemical parameters were analyzed using Finnish national standards in an accredited (SFS-EN ISO/IEC 17025:2005) laboratory at the Finnish Environment Institute (SYKE) [National Board of Waters, 1981] .

2.2.1 Local groundwater and surface water quality

  • The measurement locations are presented in the map in Supporting Information Fig. S1 .
  • The nearest SW sampling locations of SYKE are situated 27 km (Nuorittajoki suu station) and 9 km (Nuorittajoki Töntönkoski station) from Mesioja catchment.
  • Most of the parameters were analyzed using samples from Töntönkoski station and, although the measurements were performed before their stream sampling campaign, the data were assumed to be representative for the study period because there had not been any major changes in land use in the area.
  • The SW sampling location of Nuorittajoki suu station is located rather far from their study stream but, as the land use is relatively similar to that in Mesioja catchment (Supporting Information Fig. S1 ), the data were assumed to be representative for the study area.
  • In Rokua, the measurements by SYKE were also used as a reference for SW.

2.3 Data analysis

  • To reduce the dimensionality of the dataset while retaining as much of its variation as possible, the authors performed principal component analysis (PCA) for the stream data (chemical and physical water quality parameters and discharge).
  • It is preferred over the princomp function because of its better numerical accuracy [Anderson, 2013] .
  • The authors also scaled and centered the data using the prcomp function.
  • The authors performed the analysis for two datasets; the average values of all measurements for each site and the average values for the low-flow situation (July measurements).
  • As each stream had almost the same number of sampling locations, they had similar weighting in the analysis and PCA was deemed suitable for use, although the autocorrelation between samples was borne in mind when analyzing the results.

2.3.1 The stream tracer index method

  • 𝑛 where x variable is the classification value based on the chosen water quality variable.
  • The classification values are determined by evaluating whether the tracer in question indicates a clear GW signal (x=1), a mixture of GW and SW (transition zone, x=0.5), or a clear surface water signal (x=0).
  • After the appropriate values are chosen, the stream tracer index values can be calculated using equations ( 1) and ( 2).

3.1 Stream discharge and its origin

  • Based on the stable water isotope dataset, the water origin in all three streams was mainly GW (Fig. 6 and Supporting Information Fig. S2 ).
  • In Siirasoja and Lohioja streams at Rokua, the isotopic composition remained relatively stable except during the rain events in November 2014 (Fig. 3 ), when the isotopically more enriched SW increased the delta values of the streams.
  • In Mesioja, the water isotope responses were more complex than in Lohioja and Siirasoja.
  • At upstream locations, the isotopic composition resembled GW, but further downstream the delta values increased, indicating larger contributions from enriched surface runoff and soil water.
  • At the furthest downstream locations, the delta values were again more negative, indicating GW discharge into the stream also at downstream locations (Fig. S2 ).

3.2 Spatial and temporal variations in stream water temperature

  • During summer, water temperature generally increased from headwater to downstream in all streams (June-September, mean air T at Pudasjärvi airport 14.0 ºC and at Vaala-Pelso station 13.3 °C).
  • The streams generally had different diurnal variations (Fig. 4 ).
  • The coefficient of variation for temperature was smallest for headwater locations in both warm (June-September) and cold (April, May, October, November) seasons.
  • This shows that GW sustains stable thermal regimes in both warm and cold seasons.
  • In Lohioja and Siirasoja streams, water temperatures at different measurement points were more similar than in Mesioja.

3.3 Spatial and temporal variations in stream chemical properties

  • In Lohioja, Clconcentrations indicated that the first measurement location (L1) had a clear GW signal and the other locations were in the GW-SW transition zone.
  • In Siirasoja, the first three locations had Clconcentrations near to the GW reference value, the next two belonged to the GW-SW transition zone, and the last measurement location had a clear SW signal.
  • In the Rokua area the reference values showed a clear distinction from each other.
  • For all measurements, 75% of the variation in the data was explained by the first two principal components (PCs), while for low-flow measurements these two PCs explained 79% of the variation.
  • Thus, generally low PC1 loadings indicated high GW influence.

3.4 Groundwater and surface water dominance of streams

  • The authors results show that boreal headwater streams can be highly GW-dependent.
  • Changes in GW discharge would particularly affect the position and length of the GW-SW transition zone in the stream continuum and could thus alter stream ecosystems.
  • As GW supports stream flow, especially at upstream measurement locations, their study streams would most probably dry out without GW input at least occasionally.
  • Earlier snowmelt due to climate change may also lower GW levels in the region during summer months, exacerbating the impacts of drought [Okkonen et al., 2010; Okkonen and Kløve, 2011] .

4.2 Thermal properties change radically in the stream continuum

  • The authors results showed that GW plays a major role in the thermal sensitivity of the streams studied, such that GW-dependent areas were less sensitive to changes in air temperature, although still responded to it.
  • The water temperature at these locations still showed diurnal variations and during exceptionally warm days the water temperature increased.
  • Fortunately, these events were relatively short (some days) and the highest temperatures were only short-term mid-day events (e.g., on 1 July 2013, T in Siirasoja stream, location S3, increased to 10 °C for 45 minutes).
  • Jyväsjärvi et al. (2015) showed that even a 1 °C increase in mean water temperature of springs can affect the species present in water and alter bryophyte and macroinvertebrate communities in streams discharging from springs.
  • In addition, salmonid fish in particular have been found to be extremely sensitive to the current warming trend and thermal refuges are becoming even more important for preserving their populations [Isaak et al., 2015] .

4.3 The applicability of local groundwater and surface water reference values

  • Moreover, GW quality reflects the local geology.
  • The piezometers were sampled quarterly during 2010-2012.
  • This suggests that SiO 2 and Clare more reliable tracers in this area.
  • In addition, temporal variations in GW and SW quality were detected in both the Rokua and Viinivaara areas.
  • The average coefficient of variation for the GW reference variables used (excluding PO 4 3--P) was 7.5% and that for the SW reference variables was 17.4%.

4.4 Surface water input causes changes in water quality in the stream continuum

  • A disadvantage is that expert knowledge is needed to choose appropriate tracers for a selected area and the classification values for those tracers.
  • The method resembles other management tools, such as 42 analytic hierarchy process [Subramanian and Ramanathan, 2012] , so in that regard it should be rather easy to adopt in decision making.
  • Furthermore, the stream tracer index method could be especially helpful in the intense monitoring programs required in areas of exceptional ecological importance [Bertrand et al., 2014] .
  • The method could also be applied in places where anthropogenic actions are expected to change the local hydrology and affect stream ecosystems.
  • In addition, available historical data could be applied in some cases if there have not been any major changes in the catchment area.

5 Conclusions

  • It is important to classify boreal headwater streams, owing to their ability to act as refuges, supporting stable conditions vital for specific aquatic biota in a changing climate.
  • The results of this study suggest that it might be sufficient to sample stream sections only once, during summer low-flow conditions, when evaluating the groundwater dependence of streams.
  • The stream tracer index method could serve as a useful management tool, especially at sites of exceptional ecological importance or at sites where anthropogenic measures are expected to change the local hydrology.

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Accepted Manuscript
Research papers
A Tracer-Based Method for Classifying Groundwater Dependence in Boreal
Headwater Streams
Elina Isokangas, Anna-Kaisa Ronkanen, Pekka M. Rossi, Hannu Marttila,
Bjørn Kløve
PII: S0022-1694(19)30474-3
DOI: https://doi.org/10.1016/j.jhydrol.2019.05.029
Reference: HYDROL 23762
To appear in:
Journal of Hydrology
Received Date: 30 November 2018
Revised Date: 7 May 2019
Accepted Date: 8 May 2019
Please cite this article as: Isokangas, E., Ronkanen, A-K., Rossi, P.M., Marttila, H., Kløve, B., A Tracer-Based
Method for Classifying Groundwater Dependence in Boreal Headwater Streams, Journal of Hydrology (2019), doi:
https://doi.org/10.1016/j.jhydrol.2019.05.029
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers
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1 Manuscript Title:
2 A Tracer-Based Method for Classifying Groundwater Dependence in Boreal Headwater Streams
3
4 Corresponding author:
5 Elina Isokangas
6 Water Resources and Environmental Engineering Research Unit
7 Faculty of Technology, University of Oulu
8 P.O. Box 4300, FI-90014, Finland
9 email: elina.isokangas@gmail.com
10
11 Co-authors:
12 Anna-Kaisa Ronkanen* (anna-kaisa.ronkanen@oulu.fi)
13 Pekka M. Rossi* (pekka.rossi@oulu.fi)
14 Hannu Marttila* (hannu.marttila@oulu.fi)
15 Bjørn Kløve* (bjorn.klove@oulu.fi)
16 *Water Resources and Environmental Engineering Research Unit
17 Faculty of Technology, University of Oulu
18 P.O. Box 4300, FI-90014, Finland
19

2
20 Abstract
21 Ecosystem protection requires a better definition of groundwater (GW) dependence and tools to
22 measure this dependence. In this study, a classification method for the GW dependence of
23 headwater streams was devised based on the fact that GW affects discharge, thermal regime, and
24 water quality. The method was tested in three boreal headwater streams discharging from two
25 esker aquifers. Spatial and temporal variability of GW dependence were studied in the stream
26 continuum at several locations, by combining continuous measurements of temperature, electrical
27 conductivity, and discharge with discrete sampling of environmental tracers (e.g., stable water
28 isotopes, silica, chloride). The stream tracer index method developed was used to classify stream
29 sections into GW-dominated, GW-surface water (SW) transition, and SW-dominated zones. We
30 found that, spatially, GW dependence along the stream varied widely, with calculated stream
31 tracer index values ranging from 33 to 94 %. The GW-dominated areas extended at least 745,
32 1682, and 4202 m downstream from the main GW discharge points in the three streams studied. A
33 stream located in a pristine peatland-dominated catchment was more prone to rapid change from
34 GW- to SW-dominated than two streams located in catchments dominated by peatland forestry.
35 These results suggest that to evaluate the GW dependence of streams, it may be sufficient to
36 sample stream sections only once, during summer low-flow conditions. The proposed method can
37 serve as a water management tool, especially for streams of exceptional ecological importance or
38 in places where anthropogenic activities are expected to change local hydrology and ecology.
39
40 Keywords: stable water isotopes, environmental tracers, groundwater-dependent ecosystems,
41 headwater streams
42

43 1 Introduction
44 Headwater streams have a large effect on downstream hydrological and geochemical processes
45 and ecological functions [Freeman et al., 2007; Finn et al., 2011]. Groundwater (GW) is generally
46 a major contributing factor to maintaining the baseflow of headwater streams [Sophocleous, 2002;
47 Winter, 2007] and has specific geochemical, physical, and biological characteristics that differ
48 from surface water (SW) [Bertrand et al., 2012]. Therefore, any changes in GW discharge to
49 headwater streams can have a major impact on stream water quality and volume, with the most
50 pronounced effects occurring in areas that are highly influenced by GW. In order to reduce the
51 impacts on groundwater-dependent ecosystems (GDEs), tools are needed for their classification,
52 management, and protection [EC, 2006; Richardson et al., 2011; Rohde et al., 2017]. However,
53 GDE classification of headwater streams is not straightforward because standard procedures are
54 lacking and the GW-SW transition zones and ecotones can vary temporally and seasonally.
55 Dynamic environmental factors govern the healthy functioning of freshwater ecosystems and
56 are categorized as: flow patterns, sediment and organic matter inputs, temperature and light
57 penetration, chemical and nutrient conditions, and plant and animal assemblages [Younger, 2006].
58 In GW-dependent stream ecosystems, many organisms rely on conditions sustained by GW. These
59 conditions are i) discharge volume, ii) stable thermal regime, and iii) water quality [Bertrand et al.,
60 2012]. During sensitive summer and winter low-flow periods in particular, GW input to headwater
61 streams provides important refuges maintaining stable discharge [Younger, 2006] and thermal
62 conditions in these streams [Dugdale et al., 2013; Snyder et al., 2015]. As GW-dominated streams
63 provide more stable conditions for stream ecosystems than SW-dominated streams [Webb et al.,
64 2008], these ecosystems will become even more important in supporting thermal refuges in a
65 changing climate. However, GW-dominated headwater streams can be sensitive to local
66 anthropogenic actions such as agriculture, drainage for forestry, and GW abstraction [Ramchunder
67 et al., 2012; Rossi et al., 2012, 2014; Saarinen et al., 2013; Eskelinen et al., 2016], which can
68 lower GW levels, alter GW discharge patterns to headwater streams, and change water quality and
69 the ecology of streams [Poff and Zimmerman, 2010]. This emphasizes the need to classify these
70 ecosystems, in order to better protect and manage them and the connected GW systems.
71

4
72 Use of environmental tracers, such as stable water isotopes and water chemistry, is an efficient
73 and flexible method to study dynamic and spatially varying GW-SW interactions in water courses
74 and streams [Leibundgut et al., 2009; Bertrand et al., 2014]. However, past tracer approaches have
75 often focused on only one location in a stream [Kendall and Coplen, 2001; Litt et al., 2015;
76 Soulsby et al., 2015; Niinikoski et al., 2016] or on intensive sampling for a rather short period
77 [Klaus and McDonnell, 2013]. Thus, these studies cannot give a full spatial and temporal picture
78 of GW dependence in the stream continuum. Recent studies highlight the importance of spatially
79 dense sampling to determine stream water chemistry [Zimmer et al., 2013] and stable water
80 isotopes [Singh et al., 2016]. The specific geochemistry of different landscape units in the
81 catchment can alter the chemical composition of stream water [Blumstock et al., 2015]. A study by
82 Zimmer et al. [2013] suggests that GW contributions from distinct soil types control the spatial
83 similarities found in stream water chemistry in varying flow conditions. The catchment structures
84 (i.e. catchment “forms”, the hydrogeological setup of the catchment) also cause small-scale
85 differences in baseflow stable water isotopes [Singh et al., 2016]. In general, variations in stream
86 water quality can result from changes in mixing proportions of GW and SW, and spatial or
87 temporal changes in water quality, which can complicate interpretation of tracer data [Kirchner,
88 2016a, 2016b].
89 Recent tracer modelling approaches have focused particularly on studying the water age
90 distributions in catchments [e.g., Birkel and Soulsby, 2015; Soulsby et al., 2015; Huijgevoort et al.,
91 2016; Ala-aho et al., 2017]. These modeling efforts are increasingly being supported by
92 continuous measurement of isotope data [Tweed et al., 2016], which has improved estimates of
93 young water fractions [Stockinger et al., 2016] and thus also estimates of GW fractions in streams.
94 However, at this point high-resolution data cannot be obtained cost-effectively from several
95 locations along the stream, which would be necessary for assessing spatial variations in GW
96 dependence. Although low-resolution isotope data have uncertainties when estimating water

Citations
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Journal ArticleDOI
Abstract: Funding Information: We would like to acknowledge financial support from the UK Natural Environment Research Council (project NE/P010334/1) via a CASE industrial studentship with Chivas Brothers. David Drummond, Katya Dimitrova-Petrova and Eva Loerke are thanked for assistance with fieldwork, while we acknowledge Dr Aaron Neill for his advice on young water fraction analyses. Trevor Buckley and staff at the Glenlivet Distillery are thanked for on-site assistance and supply of data and abstraction records. We thank Audrey Innes, Dr Bernhard Scheliga, and Dr Ilse Kamerling for their support with the laboratory isotope analysis. Publisher Copyright: © 2020 The Authors. Hydrological Processes published by John Wiley & Sons Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

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  • ...…abstraction legislation under climate change projections, there is a need to understand (a) the relative role of different water sources (Isokangas et al., 2019), both in terms of water quantity and quality (specifically, temperature) (b) the resilience of these sources under different…...

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Abstract: The characteristics of groundwater systems and groundwater contamination in Finland, Norway and Iceland are presented, as they relate to outbreaks of disease. Disparities among the Nordic countries in the approach to providing safe drinking water from groundwater are discussed, and recommendations are given for the future. Groundwater recharge is typically high in autumn or winter months or after snowmelt in the coldest regions. Most inland aquifers are unconfined and therefore vulnerable to pollution, but they are often without much anthropogenic influence and the water quality is good. In coastal zones, previously emplaced marine sediments may confine and protect aquifers to some extent. However, the water quality in these aquifers is highly variable, as the coastal regions are also most influenced by agriculture, sea-water intrusion and urban settlements resulting in challenging conditions for water abstraction and supply. Groundwater is typically extracted from Quaternary deposits for small and medium municipalities, from bedrock for single households, and from surface water for the largest cities, except for Iceland, which relies almost entirely on groundwater for public supply. Managed aquifer recharge, with or without prior water treatment, is widely used in Finland to extend present groundwater resources. Especially at small utilities, groundwater is often supplied without treatment. Despite generally good water quality, microbial contamination has occurred, principally by norovirus and Campylobacter, with larger outbreaks resulting from sewage contamination, cross-connections into drinking water supplies, heavy rainfall events, and ingress of polluted surface water to groundwater.

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Abstract: Water flows in peatland margins is an under-researched topic. This study examines recharge from a peatland to an esker aquifer in an aapa mire complex of northern Finland. Our objective was to study how the aapa mire margin is hydrogeologically connected to the riverside aquifer and spatial and temporal variations in the recharge of peatland water to groundwater (GW). Following geophysical studies and monitoring of the saturated zone, a GWmodel (MODFLOW) was used in combination with stable isotopes to quantify GW flow volumes and directions. Peatland water recharge to the sandy aquifer indicated a strong connection at the peatland–aquifer boundary. Recharge volumes from peatland to esker were high and rather constant (873 m d ) and dominated esker recharge at the study site. The peat water recharging the esker boundary was rich in dissolved organic carbon (DOC). Stable isotope studies on water (δO, δH, and d-excess) from GW wells verified the recharge of DOC-rich water from peatlands to mineral soil esker. Biogeochemical analysis revealed changes from DOC to dissolved inorganic carbon in the flow pathway from peatland margin to the river Kitinen. This study highlights the importance of careful investigation of aapa mire margin areas and their potential role in regional GW recharge patterns.

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Journal ArticleDOI
Abstract: Reconstruction of continental palaeoclimate and palaeohydrology is currently hampered by limited information about isotopic patterns in the modern hydrologic cycle. To remedy this situation and to provide baseline data for other isotope hydrology studies, more than 4800, depth- and width-integrated, stream samples from 391 selected sites within the USGS National Stream Quality Accounting Network (NASQAN) and Hydrologic Benchmark Network (HBN) were analysed for δ18O and δ2H (http://water.usgs.gov/pubs/ofr/ofr00-160/pdf/ofr00-160.pdf). Each site was sampled bimonthly or quarterly for 2·5 to 3 years between 1984 and 1987. The ability of this dataset to serve as a proxy for the isotopic composition of modern precipitation in the USA is supported by the excellent agreement between the river dataset and the isotopic compositions of adjacent precipitation monitoring sites, the strong spatial coherence of the distributions of δ18O and δ2H, the good correlations of the isotopic compositions with climatic parameters, and the good agreement between the ‘national’ meteoric water line (MWL) generated from unweighted analyses of samples from the 48 contiguous states of δ2H=8·11δ18O+8·99 (r2=0·98) and the unweighted global MWL of sites from the Global Network for Isotopes in Precipitation (GNIP) of the International Atomic Energy Agency and the World Meteorological Organization (WMO) of δ2H=8·17δ18O+10·35. The national MWL is composed of water samples that arise in diverse local conditions where the local meteoric water lines (LMWLs) usually have much lower slopes. Adjacent sites often have similar LMWLs, allowing the datasets to be combined into regional MWLs. The slopes of regional MWLs probably reflect the humidity of the local air mass, which imparts a distinctive evaporative isotopic signature to rainfall and hence to stream samples. Deuterium excess values range from 6 to 15‰ in the eastern half of the USA, along the northwest coast and on the Colorado Plateau. In the rest of the USA, these values range from −2 to 6‰, with strong spatial correlations with regional aridity. The river samples have successfully integrated the spatial variability in the meteorological cycle and provide the best available dataset on the spatial distributions of δ18O and δ2H values of meteoric waters in the USA. Published in 2001 by John Wiley & Sons, Ltd.

699 citations


Journal ArticleDOI
Abstract: Research on stream and river temperatures is reviewed with particular attention being given to advances in understanding gained since 1990 and on investigations of fundamental controls on thermal behaviour, thermal heterogeneity at different spatial scales, the influence of human impacts and the nature of past and future trends. Copyright  2008 John Wiley & Sons, Ltd.

666 citations