Advertisement

On Complementing the Tracer Toolbox for Quantifying Hydrological Connectivity: Insights Gained from Terrestrial Diatom Tracer Experiments

  • L. PfisterEmail author
  • S. T. Allen
  • C. E. Wetzel
  • N. Martínez-Carreras
Chapter
  • 130 Downloads
Part of the Ecological Studies book series (ECOLSTUD, volume 240)

Abstract

Prior to the widespread use of tracers, early forest hydrology studies relied mostly on hydrometric measurements (soil moisture content, groundwater levels, discharge, precipitation inputs). A dominant pre-tracer paradigm was that high precipitation intensities resulted in rapid runoff responses, when infiltration rates were exceeded by precipitation rates, as deduced from hydrometric data. Early hydrologic tracer applications included performing hydrograph separations to understand the fractions of event and pre-event water in streams. Using additional tracers, the end-member mixing analysis model was introduced for quantifying contributions of multiple geographic stormflow sources. With longer series of tracer measurements, more sophisticated inferences became possible, such as transit time distributions and young water fractions. A limitation to the common toolbox of hydrological tracers is that stable isotopes and geochemical tracers do not specifically show surface connectivity, allowing for ambiguity in our understanding of how ‘event water’ actually reaches streams. Furthermore, there are challenges in aggregating these tracer measurements across diverse landscapes to understand larger scale connectivity patterns. Here, we provide a primer on tracer applications in studying the hydrological connections in watersheds and forests. After providing an overview of general basics in tracer applications, we focus on a new type of tracer—terrestrial diatoms—and give some insights into their use for tracing the onset/cessation of surface hydrological connectivity. Given that this is a newly developing tracer method, we demonstrate the process of exploring and testing tracer applications. Furthermore, we discuss the differences among and complementarity between diatoms and more traditional tracers (e.g. solutes).

Notes

Acknowledgements

Research on the potential for terrestrial diatoms to serve as hydrological tracers has been funded through the National Research Fund of Luxembourg (Grants C09/SR/14—BIGSTREAM & C12/SR/4018854—ECSTREAM). The authors would like to acknowledge Jeffrey J. McDonnell for providing comments on an earlier version of this chapter.

References

  1. Ambroise B (2004) Variable ‘active’ versus ‘contributing’ areas or periods: a necessary distinction. Hydrol Process 18:1149–1155.  https://doi.org/10.1002/hyp.5536 CrossRefGoogle Scholar
  2. Barron JA, Baldauf JG (1995) Cenozoic marine diatom biostratigraphy and applications to paleoclimatology and paleoceanograhy. In: Blome CD et al (eds) (Convenors) Siliceous microfossils, paleontological society short courses in paleontology, vol 8, pp 107–118Google Scholar
  3. Barthold FK, Tyralla C, Schneider K, Vaché KB, Frede HG, Breuer L (2011) How many tracers do we need for end member mixing analysis (EMMA)? A sensitivity analysis. Water Resour Res 47:W08519.  https://doi.org/10.1029/2011WR010604 CrossRefGoogle Scholar
  4. Benettin P, Velde Y, van der Zee S, Rinaldo A, Botter G (2013) Chloride circulation in a lowland catchment and the formulation of transport by travel time distributions. Water Resour Res 49:4619–4632.  https://doi.org/10.1002/wrcr.20309 CrossRefGoogle Scholar
  5. Bonell M, Barnes CJ, Grant CR, Howard A, Burns J (1999) High rainfall, response-dominated catchments: a comparative study of experiments in tropical northeast Queensland with temperate New Zealand. In: Kendall C, JJ MD (eds) Isotope tracers in catchment hydrology. Elsevier, Amsterdam, pp 347–390.  https://doi.org/10.1016/B978-0-444-81546-0.50018-5 CrossRefGoogle Scholar
  6. Boulêtreau S, Garabétian F, Sauvage S, Sánchez-Pérez JM (2006) Assessing the importance of a self-generated detachment process in river biofilm models. Freshw Biol 51:901–912.  https://doi.org/10.1111/j.1365-2427.2006.01541.x CrossRefGoogle Scholar
  7. Bracken L, Croke J (2007) The concept of hydrological connectivity and its contribution to understanding runoff-dominated geomorphic systems. Hydrol Process 21:1749–1763.  https://doi.org/10.1002/hyp.6313 CrossRefGoogle Scholar
  8. Burns DA, McDonnell JJ, Hooper RP, Peters NE, Freer JE, Kendall C et al (2001) Quantifying contributions to storm runoff through end-member mixing analyses and hydrologic measurements at the Panola Mountain Research Watershed (Georgia, USA). Hydrol Process 15: 1903–1924.  https://doi.org/10.1002/hyp.246 CrossRefGoogle Scholar
  9. Burns DA (2002) Stormflow hydrograph separation based on isotopes: the thrill is gone – what’s next? Hydrol Process 16:1515–1517.  https://doi.org/10.1002/hyp.5008 CrossRefGoogle Scholar
  10. Buttle JM, Peters DL (1997) Inferring hydrological processes in a temperate basin using isotopic a geochemical hydrograph separation: a re-evaluation. Hydrol Process 11:557–573.  https://doi.org/10.1002/(SICI)1099-1085(199705)11:6<557::AID-HYP477>3.0.CO;2-Y CrossRefGoogle Scholar
  11. Coles AE, Wetzel CE, Martínez-Carreras N, Ector L, McDonnell JJ, Frentress J et al (2016) Diatom as a tracer of hydrological connectivity: are they supply limited? Ecohydrology 9:631–645.  https://doi.org/10.1002/eco.1662 CrossRefGoogle Scholar
  12. Coplen TB, Neiman PJ, White AB, Ralph FM (2015) Categorisation of northern California rainfall for periods with and without a radar brightband using stable isotopes and a novel automated precipitation collector. Tellus Ser B Chem Phys Meteorol 67:28574.  https://doi.org/10.3402/tellusb.v67.28574 CrossRefGoogle Scholar
  13. De Graaf L, Cammeraat E, Pfister L, Wetzel C, Klaus J, Hissler C (2015) Do diatoms percolate through soil and can they be used for tracing the origin of runoff? EGU General Assembly Conference Abstracts 2015 17:EGU2015-8961Google Scholar
  14. Desilets SLE, Ferré TPA, Ekwurzel B (2008) Flash flood dynamics and composition in a semiarid mountain watershed. Water Resour Res 44:W12436.  https://doi.org/10.1029/2007WR006159 CrossRefGoogle Scholar
  15. Dunne T, Black RD (1970) Partial area contributions to storm runoff in a small New England watershed. Water Resour Res 6:1296–1311.  https://doi.org/10.1029/WR006i005p01296 CrossRefGoogle Scholar
  16. Dunne T, Moore TR, Taylor CH (1975) Recognition and prediction of runoff-producing areas in humid regions. Hydrol Sci Bull 20:305–327Google Scholar
  17. Ector L, Rimet F (2005) Using bioindicators to assess rivers in Europe: an overview. In: Lek S, Scardi M, PFM V, Descy JP, Park YS (eds) Modelling community structure in freshwater ecosystems. Springer, Berlin/Heidelberg, pp 7–19.  https://doi.org/10.1007/3-540-26894-4_2 CrossRefGoogle Scholar
  18. Fischer BM, van Meerveld HI, Seibert J (2017) Spatial variability in the isotopic composition of rainfall in a small headwater catchment and its effect on hydrograph separation. J Hydrol 547:755–769.  https://doi.org/10.1016/j.jhydrol.2017.01.045 CrossRefGoogle Scholar
  19. Foussereau X, Graham WD, Akpoji GA, Destouni G, Rao PSC (2001) Solute transport through a heterogeneous coupled vadose-saturated zone system with temporally random rainfall. Water Resour Res 37:1577–1588.  https://doi.org/10.1029/2000WR900389 CrossRefGoogle Scholar
  20. Freeman MC, Pringle CM, Jackson CR (2007) Hydrologic connectivity and the contribution of stream headwaters to ecological integrity at regional scales. J Am Water Resour Assoc 43:5–14CrossRefGoogle Scholar
  21. Fritz SC, Juggins S, Battarbee RW, Engstrom DR (1991) Reconstruction of past changes in salinity and climate using a diatom-based transfer function. Nature 352:706–708CrossRefGoogle Scholar
  22. Harman CJ (2015) Time-variable transit time distributions and transport: theory and application to storage-dependent transport of chloride in a watershed. Water Resour Res 51:1–30.  https://doi.org/10.1002/2014WR015707 CrossRefGoogle Scholar
  23. Hewlett JD, Hibbert AR (1967) Factors affecting the response of small watersheds to precipitation in humid areas. In: Sopper WE, Lull HW (eds) International symposium on forest hydrology. Pergamon, Oxford, pp 275–290Google Scholar
  24. Hooper RP, Christophersen N, Peters NE (1990) Modelling streamwater chemistry as a mixture of soil water end-members – an application to the Panola Mountain catchment, Georgia, USA. J Hydrol 116:321–343.  https://doi.org/10.1016/0022-1694(90)90131-G CrossRefGoogle Scholar
  25. Horton RE (1933) The role of infiltration in the hydrologic cycle. Trans Am Geophys Union 14:446–460.  https://doi.org/10.1029/TR014i001p00446 CrossRefGoogle Scholar
  26. Ingraham NL, Caldwell EA, Verhagen BT (1999) Arid catchments. In: Kendall C, JJ MD (eds) Isotope tracers in catchment hydrology. Elsevier, Amsterdam, pp 435–465.  https://doi.org/10.1016/B978-0-444-81546-0.50020-3 CrossRefGoogle Scholar
  27. Kendall C, McDonnell JJ (1998) Isotope tracers in catchment hydrology. Elsevier Science Publishers BV, AmsterdamGoogle Scholar
  28. Kirchner JW, Tetzlaff D, Soulsby C (2010) Comparing chloride and water isotopes as hydrological tracers in two Scottish catchments. Hydrol Process 24:1631–1645.  https://doi.org/10.1002/hyp.7676 CrossRefGoogle Scholar
  29. Kirchner JW (2016) Aggregation in environmental systems – part 1: seasonal tracer cycles quantify young water fractions, but not mean transit times, in spatially heterogeneous catchments. Hydrol Earth Syst Sci 20:279–297.  https://doi.org/10.5194/hess-20-279-2016 CrossRefGoogle Scholar
  30. Klaus J, McDonnell JJ (2013) Hydrograph separation using stable isotopes: review and evaluation. J Hydrol 505:47–64.  https://doi.org/10.1016/j.jhydrol.2013.09.006 CrossRefGoogle Scholar
  31. Klaus J, Chun KP, McGuire KJ, McDonnell JJ (2015a) Temporal dynamics of catchment transit times from stable isotope data. Water Resour Res 51:4208–4223.  https://doi.org/10.1002/2014WR016247 CrossRefGoogle Scholar
  32. Klaus J, Wetzel CE, Martínez-Carreras N, Ector L, Pfister L (2015b) A tracer to bridge the scales: on the value of diatoms for tracing fast flow path connectivity from headwaters to meso-scale catchments. Hydrol Process 29:5275–5289.  https://doi.org/10.1002/hyp.10628 CrossRefGoogle Scholar
  33. Leibundgut C, Malozewski P, Külls C (2009) Tracers in hydrology. Wiley, ChichesterCrossRefGoogle Scholar
  34. Lobo EA, Heinrich CG, Schuch M, Wetzel CE, Ector L (2016) Diatoms as bioindicators in rivers. In: Neccho O (ed) River algae. Springer, Heidelberg, pp 245–271.  https://doi.org/10.1007/978-3-319-31984-1_11 CrossRefGoogle Scholar
  35. Maloszewski P, Rauert W, Stichler W, Herrmann A (1983) Application of flow models in an alpine catchment area using tritium and deuterium data. J Hydrol 66:319–330.  https://doi.org/10.1016/0022-1694(83)90193-2 CrossRefGoogle Scholar
  36. Maloszewski P, Zuber A (1993) Principles and practice of calibration and validation of mathematical models for the interpretation of environmental tracer data in aquifers. Adv Water Resour 16:173–190.  https://doi.org/10.1016/0309-1708(93)90036-F CrossRefGoogle Scholar
  37. Martínez-Carreras N, Wetzel CE, Frentress J, Ector L, McDonnell JJ, Hoffmann L et al (2015) Hydrological connectivity inferred from diatom transport through the riparian-stream system. Hydrol Earth Syst Sci 19: 3133–3151.  https://doi.org/10.5194/hess-19-3133-2015 CrossRefGoogle Scholar
  38. Martínez-Carreras N, Hissler C, Gourdol L, Klaus J, Juilleret J, Iffly JF et al (2016) Storage controls on the generation of double peak hydrographs in a forested headwater catchment. J Hydrol 543:255–269.  https://doi.org/10.1016/j.jhydrol.2016.10.004 CrossRefGoogle Scholar
  39. McDonnell JJ (1990) A rationale for old water discharge through macropores in a steep, humid catchment. Water Resour Res 26:2821–2832.  https://doi.org/10.1029/WR026i011p02821 CrossRefGoogle Scholar
  40. McDonnell JJ, Sivapalan M, Vaché K, Dunn S, Grant G, Haggerty R et al (2007) Moving beyond heterogeneity and process complexity: a new vision for watershed hydrology. Water Resour Res 43:W07301.  https://doi.org/10.1029/2006WR005467 CrossRefGoogle Scholar
  41. McDonnell JJ, McGuire K, Aggarwal P, Beven KJ, Biondi D, Destouni G et al (2010) How old is streamwater? Open questions in catchment transit time conceptualization, modelling and analysis. Hydrol Process 24:1745–1754.  https://doi.org/10.1002/hyp.7796 CrossRefGoogle Scholar
  42. McGlynn BL, McDonnell JJ (2003) Quantifying the relative contributions of riparian and hillslope zones to catchment runoff. Water Resour Res 39:1310.  https://doi.org/10.1029/2003WR002091 CrossRefGoogle Scholar
  43. McGuire KJ, McDonnell JJ, Weiler M, Kendall C, McGlynn BL, Welker JM et al (2005) The role of topography on catchment-scale water residence time. Water Resour Res 41:W05002.  https://doi.org/10.1029/2004WR003657 CrossRefGoogle Scholar
  44. McGuire KJ, McDonnell JJ (2006) A review and evaluation of catchment transit time modeling. J Hydrol 330: 543–563.  https://doi.org/10.1016/j.jhydrol.2006.04.020 CrossRefGoogle Scholar
  45. Morgenstern U, Stewart MK, Stenger R (2010) Dating of streamwater using tritium in a post nuclear bomb pulse world: continuous variation of mean transit time with streamflow. Hydrol Earth Syst Sci 14:2289–2301.  https://doi.org/10.5194/hess-14-2289-2010 CrossRefGoogle Scholar
  46. Pfister L, McDonnell JJ, Wrede S, Hlúbiková D, Matgen P, Fenicia F et al (2009) The rivers are alive: on the potential for diatoms as a tracer of water source and hydrological connectivity. Hydrol Process 23:2841–2845.  https://doi.org/10.1002/hyp.7426 CrossRefGoogle Scholar
  47. Pfister L, Wetzel CE, Klaus J, Martínez-Carreras N, Antonelli M, Teuling A et al (2017) Terrestrial diatoms as tracers in catchment hydrology: a review. WIREs Water 4:e1241.  https://doi.org/10.1002/wat2.1241 CrossRefGoogle Scholar
  48. Pringle C (2003) The need for a more predictive understanding of hydrologic connectivity. Aquat Conserv 13:467–471.  https://doi.org/10.1002/aqc.603 CrossRefGoogle Scholar
  49. Richey DG, McDonnell JJ, Erbe MW, Hurd TM (1998) Hydrograph separations based on chemical and isotopic concentrations: a critical appraisal of published studies from New Zealand, North America and Europe. J Hydrol (NZ) 37:95–111Google Scholar
  50. Rodriguez NB, McGuire KJ, Klaus J (2018) Time-varying storage–water age relationships in a catchment with a Mediterranean climate. Water Resour Res 54:3988–4008.  https://doi.org/10.1029/2017WR021964 CrossRefGoogle Scholar
  51. Shukla SK, Mohan R (2012) The contribution of diatoms to worldwide crude oil deposits. In: Gordon R, Seckbach J (eds) The science of algal fuels. Springer, Dordrecht, pp 355–382.  https://doi.org/10.1007/978-94-007-5110-1_20 CrossRefGoogle Scholar
  52. Sklash MG, Farvolden RN (1979) The role of groundwater in storm runoff. J Hydrol 43:45–65.  https://doi.org/10.1016/0022-1694(79)90164-1 CrossRefGoogle Scholar
  53. Smucker NJ, Detenbeck NE, Morrison AC (2013) Diatom responses to watershed development and potential moderating effects of near-stream forest and wetland cover. Freshwater Sci 32:230–249.  https://doi.org/10.1899/11-171.1 CrossRefGoogle Scholar
  54. Soulsby C, Tetzlaff D, Hrachowitz M (2009) Tracers and transit times: windows for viewing catchment scale storage? Hydrol Process 23:3503–3507.  https://doi.org/10.1002/hyp.7501 CrossRefGoogle Scholar
  55. Stewart MK, Mehlhorn J, Elliott S (2007) Hydrometric and natural tracer (oxygen-18, silica, tritium and sulphur hexafluoride) evidence for a dominant groundwater contribution to Pukemanga Stream, New Zealand. Hydrol Process 21:3340–3356.  https://doi.org/10.1002/hyp.6557 CrossRefGoogle Scholar
  56. Stewart MK, Thomas JT (2008) A conceptual model of flow to the Waikoropupu Springs, NW Nelson, New Zealand, based on hydrometric and tracer (18O, Cl, 3H and CFC) evidence. Hydrol Earth Syst Sci 12:1–19.  https://doi.org/10.5194/hess-12-1-2008 CrossRefGoogle Scholar
  57. Stewart MK, Morgenstern U, McDonnell JJ (2010) Truncation of stream residence time: how the use of stable isotopes has skewed our concept of streamwater age and origin. Hydrol Process 24:1646–1659.  https://doi.org/10.1002/hyp.7576 CrossRefGoogle Scholar
  58. Stewart MK, Fahey BD (2010) Runoff generating processes in adjacent tussock grassland and pine plantation catchments as indicated by mean transit time estimation using tritium. Hydrol Earth Syst Sci 14:1021–1032.  https://doi.org/10.5194/hess-14-1021-2010 CrossRefGoogle Scholar
  59. Stoermer EF, Smol JP (2010) The diatoms: applications for the environmental and earth sciences. Cambridge University Press, CambridgeGoogle Scholar
  60. Tauro F, Martínez-Carreras N, Barnich F, Juilleret J, Wetzel CE, Ector L et al (2016) Diatom percolation through soils: a proof of concept laboratory experiment. Ecohydrology 9: 753–764.  https://doi.org/10.1002/eco.1671 CrossRefGoogle Scholar
  61. Tetzlaff D, Soulsby C, Bacon PJ, Youngson AF, Gibbins C, Malcolm IA (2007) Connectivity between landscapes and riverscapes – a unifying theme in integrating hydrology and ecology in catchment science. Hydrol Process 21:1385–1389.  https://doi.org/10.1002/hyp.6701 CrossRefGoogle Scholar
  62. Uhlenbrook S, Frey M, Leibundgut C, Maloszewski P (2002) Hydrograph separations in a mesoscale mountainous basin at event and seasonal timescales. Water Resour Res 38.  https://doi.org/10.1029/2001WR000938 CrossRefGoogle Scholar
  63. Uhlenbrook S, Hoeg S (2003) Quantifying uncertainties in tracer-based hydrograph separations: a case study for two-, three- and five-component hydrograph separations in a mountainous catchment. Hydrol Process 17:431–453.  https://doi.org/10.1002/hyp.1134 CrossRefGoogle Scholar
  64. Van Dam H, Mertens A, Sinkeldam J (1994) A coded checklist and ecological indicator values of freshwater diatoms from The Netherlands. Neth J Aquat Ecol 28:117–133.  https://doi.org/10.1007/BF02334251 CrossRefGoogle Scholar
  65. Wrede S, Fenicia F, Martínez-Carreras N, Juilleret J, Hissler C, Krein A et al (2015) Towards more systematic perceptual model development: a case study using 3 Luxembourgish catchments. Hydrol Process 29:2731–2750.  https://doi.org/10.1002/hyp.10393 CrossRefGoogle Scholar
  66. Wu N, Faber C, Sun X, Qu Y, Wang C, Ivetic S et al (2016) Importance of sampling frequency when collecting diatoms. Sci Rep 6:36950.  https://doi.org/10.1038/srep36950 CrossRefGoogle Scholar
  67. Wu N, Faber C, Ulrich U, Fohrer N (2018) Diatoms as an indicator for tile drainage flow in a German lowland catchment. Environ Sci Eur 30.  https://doi.org/10.1186/s12302-018-0133-5

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • L. Pfister
    • 1
    • 2
    Email author
  • S. T. Allen
    • 3
  • C. E. Wetzel
    • 4
  • N. Martínez-Carreras
    • 1
  1. 1.Environmental Research and Innovation Department, Catchment and Eco-hydrology Research GroupLuxembourg Institute of Science and TechnologyBelvauxLuxembourg
  2. 2.Faculty of Science, Technology and CommunicationUniversity of LuxembourgEsch-sur-AlzetteLuxembourg
  3. 3.ETHZ, Institute of Terrestrial EcosystemsZürichSwitzerland
  4. 4.Environmental Research and Innovation Department, Environmental Microbiology and BiotechnologyLuxembourg Institute of Science and TechnologyBelvauxLuxembourg

Personalised recommendations