Assessing the value of high‐resolution isotope tracer data in the stepwise development of a lumped conceptual rainfall–runoff model

A study was undertaken in a small agricultural catchment in north east Scotland with the objective of assessing the value of high-resolution isotope data for integration within a lumped, conceptual hydrological model to improve calibration and aid evaluation. Daily samples of precipitation and stream flow, collected over a year, were analysed for deuterium using new laser spectroscopy technology. The utility of such high-resolution isotope data was evaluated in relation to the associated uncertainty which was contextualized in relation to uncertainties over hydrometric data and the influence of different sampling resolutions. The simulations were evaluated against model and data errors using auxiliary stream deuterium time series in addition to discharge. The lumped conceptual catchment isotope model (CIM) was developed and adequately reflects flow dynamics and deuterium peaks, but a simple assumption of ‘good mixing’ is not able to fully reproduce the daily stream deuterium dynamic. Using auxiliary data for model evaluation, however, significantly constrained acceptable behavioural parameter sets and therefore reduces the model's degree of freedom. The data indicate that isotopic variability in the stream response is not adequately captured using weekly tracer data. The input resolution of precipitation deuterium concentrations, which were much more variable, proved to be crucial. This approach has provided further assessment of the value of tracers in hydrological modelling, demonstrating their usefulness in terms of model conceptualization, development and calibration, which outweighs the additional uncertainty. Copyright © 2010 John Wiley & Sons, Ltd.

[1]  M. Bonell,et al.  APPLICATION OF UNIT HYDROGRAPH TECHNIQUES TO SOLUTE TRANSPORT IN CATCHMENTS , 1996 .

[2]  J. Kirchner Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology , 2006 .

[3]  Thorsten Wagener Can we model the hydrological impacts of environmental change? , 2007 .

[4]  Markus Weiler,et al.  Conceptualizing lateral preferential flow and flow networks and simulating the effects on gauged and ungauged hillslopes , 2007 .

[5]  L. Wassenaar,et al.  High-precision laser spectroscopy D/H and 18O/16O measurements of microliter natural water samples. , 2008, Analytical chemistry.

[6]  Richard P. Hooper,et al.  A multisignal automatic calibration methodology for hydrochemical models: A case study of the Birkenes Model , 1988 .

[7]  Doerthe Tetzlaff,et al.  Transit time distributions of a conceptual model: their characteristics and sensitivities , 2010 .

[8]  K. Beven On undermining the science? , 2006 .

[9]  D. Chittleborough,et al.  Estimating the contribution of preferential flow to subsurface runoff from a hillslope using deuterium and chloride , 1993 .

[10]  Jeffrey J. McDonnell,et al.  On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration , 2002 .

[11]  Doerthe Tetzlaff,et al.  Regionalization of transit time estimates in montane catchments by integrating landscape controls , 2009 .

[12]  Kevin Bishop,et al.  Simulating interactions between saturated and unsaturated storage in a conceptual runoff model , 2003 .

[13]  Yuqiong Liu,et al.  Reconciling theory with observations: elements of a diagnostic approach to model evaluation , 2008 .

[14]  Mark J. Brewer,et al.  Identifying and assessing uncertainty in hydrological pathways: a novel approach to end member mixing in a Scottish agricultural catchment , 2003 .

[15]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[16]  Keith Beven,et al.  Modelling the chloride signal at Plynlimon, Wales, using a modified dynamic TOPMODEL incorporating conservative chemical mixing (with uncertainty) , 2007 .

[17]  W. Kinzelbach,et al.  Coupling of transport and chemical processes in numerical transport models , 1989 .

[18]  Jim E Freer,et al.  Science versus politics: truth and uncertainty in predictive modelling , 2009 .

[19]  F. Pappenberger,et al.  Ignorance is bliss: Or seven reasons not to use uncertainty analysis , 2006 .

[20]  A. Pietroniro,et al.  A groundwater separation study in boreal wetland terrain: the WATFLOOD hydrological model compared with stable isotope tracers , 2005, Isotopes in environmental and health studies.

[21]  Doerthe Tetzlaff,et al.  Comparing chloride and water isotopes as hydrological tracers in two Scottish catchments , 2010 .

[22]  Keith Beven,et al.  Data‐based modelling of runoff and chemical tracer concentrations in the Haute‐Mentue research catchment (Switzerland) , 2005 .

[23]  P. Maloszewski,et al.  DETERMINING THE TURNOVER TIME OF GROUNDWATER SYSTEMS WITH THE AID OF ENVIRONMENTAL TRACERS 1. Models and Their Applicability , 1982 .

[24]  J. McDonnell,et al.  A review and evaluation of catchment transit time modeling , 2006 .

[25]  Jeffrey J. McDonnell,et al.  Modeling Base Flow Soil Water Residence Times From Deuterium Concentrations , 1991 .

[26]  Doerthe Tetzlaff,et al.  Towards a simple dynamic process conceptualization in rainfall–runoff models using multi-criteria calibration and tracers in temperate, upland catchments , 2009 .

[27]  S. Dunn,et al.  Assessing the value of Cl− and δ18O data in modelling the hydrological behaviour of a small upland catchment in northeast Scotland , 2008 .

[28]  James W. Kirchner,et al.  The fine structure of water‐quality dynamics: the (high‐frequency) wave of the future , 2004 .

[29]  G. Destouni,et al.  Water and solute residence times in a catchment: Stochastic‐mechanistic model interpretation of 18O transport , 1999 .

[30]  A. Pearce,et al.  Storm runoff generation in humid headwater catchments 1 , 1986 .

[31]  A. Langousis,et al.  Marginal methods of intensity‐duration‐frequency estimation in scaling and nonscaling rainfall , 2007 .

[32]  Sarah M. Dunn,et al.  Parameter identification for conceptual modelling using combined behavioural knowledge , 2003 .

[33]  Doerthe Tetzlaff,et al.  Runoff processes, stream water residence times and controlling landscape characteristics in a mesoscale catchment: An initial evaluation , 2006 .

[34]  Doerthe Tetzlaff,et al.  Conceptualization of runoff processes using a geographical information system and tracers in a nested mesoscale catchment , 2007 .

[35]  R. Daren Harmel,et al.  Consideration of measurement uncertainty in the evaluation of goodness-of-fit in hydrologic and water quality modeling , 2007 .

[36]  M. Moss Some basic considerations in the design of hydrologic data networks , 1979 .

[37]  S. Uhlenbrook,et al.  Future trends in transport and fate of diffuse contaminants in catchments, with special emphasis on stable isotope applications , 2006 .

[38]  Henrik Madsen,et al.  Incorporating multiple observations for distributed hydrologic model calibration : An approach using a multi-objective evolutionary algorithm and clustering , 2008 .

[39]  S. Waldron,et al.  Assessing nested hydrological and hydrochemical behaviour of a mesoscale catchment using continuous tracer data , 2007 .

[40]  M. Katsuyama,et al.  Elucidation of the relationship between geographic and time sources of stream water using a tracer approach in a headwater catchment , 2009 .

[41]  S. Uhlenbrook,et al.  Does the incorporation of process conceptualization and tracer data improve the structure and performance of a simple rainfall‐runoff model in a Scottish mesoscale catchment? , 2008 .

[42]  Alan Jenkins,et al.  Isotope hydrology of the Allt a' Mharcaidh catchment, Cairngorms, Scotland : implications for hydrological pathways and residence times , 2000 .

[43]  J. Monteith Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.

[44]  P. Matgen,et al.  Understanding catchment behavior through stepwise model concept improvement , 2008 .

[45]  P. Troch,et al.  A tale of two isotopes: differences in hydrograph separation for a runoff event when using δD versus δ18O , 2009 .

[46]  Jeffrey G. Arnold,et al.  CUMULATIVE UNCERTAINTY IN MEASURED STREAMFLOW AND WATER QUALITY DATA FOR SMALL WATERSHEDS , 2006 .

[47]  Doerthe Tetzlaff,et al.  Conceptualization in catchment modelling: simply learning? , 2008 .

[48]  Doerthe Tetzlaff,et al.  Catchment data for process conceptualization: simply not enough? , 2008 .

[49]  Doerthe Tetzlaff,et al.  Interpretation of homogeneity in δ18O signatures of stream water in a nested sub‐catchment system in north‐east Scotland , 2008 .

[50]  Jim Freer,et al.  Towards a limits of acceptability approach to the calibration of hydrological models : Extending observation error , 2009 .

[51]  Jeffrey J. McDonnell,et al.  Effect of Catchment‐Scale Subsurface Mixing on Stream Isotopic Response , 1991 .

[52]  Jeffrey J. McDonnell,et al.  A new time‐space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale , 2009 .

[53]  Robert E. Criss,et al.  Do Nash values have value? Discussion and alternate proposals , 2008 .

[54]  Hubert H. G. Savenije,et al.  Learning from model improvement: On the contribution of complementary data to process understanding , 2008 .

[55]  Jeffrey J. McDonnell,et al.  How does rainfall become runoff? A combined tracer and runoff transfer function approach , 2003 .

[56]  Jeffrey J. McDonnell,et al.  Integrating tracer experiments with modeling to assess runoff processes and water transit times , 2007 .

[57]  S. Uhlenbrook,et al.  Distributed, high-resolution modelling of 18O signals in a meso-scale catchment , 2007 .

[58]  D. R. Smith,et al.  Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications , 2009, Environ. Model. Softw..

[59]  Richard P. Hooper,et al.  Assessing the Birkenes Model of stream acidification using a multisignal calibration methodology , 1988 .

[60]  Andrea Rinaldo,et al.  Sea level rise, hydrologic runoff, and the flooding of Venice , 2008 .

[61]  Rae Mackay,et al.  Spatial variation in evapotranspiration and the influence of land use on catchment hydrology , 1995 .