Picturing and modeling catchments by representative hillslopes

Abstract. This study explores the suitability of a single hillslope as a parsimonious representation of a catchment in a physically based model. We test this hypothesis by picturing two distinctly different catchments in perceptual models and translating these pictures into parametric setups of 2-D physically based hillslope models. The model parametrizations are based on a comprehensive field data set, expert knowledge and process-based reasoning. Evaluation against streamflow data highlights that both models predicted the annual pattern of streamflow generation as well as the hydrographs acceptably. However, a look beyond performance measures revealed deficiencies in streamflow simulations during the summer season and during individual rainfall–runoff events as well as a mismatch between observed and simulated soil water dynamics. Some of these shortcomings can be related to our perception of the systems and to the chosen hydrological model, while others point to limitations of the representative hillslope concept itself. Nevertheless, our results confirm that representative hillslope models are a suitable tool to assess the importance of different data sources as well as to challenge our perception of the dominant hydrological processes we want to represent therein. Consequently, these models are a promising step forward in the search for the optimal representation of catchments in physically based models.

[2]  M. Sivapalan,et al.  Towards a new generation of hydrological process models for the mesoscale : an introduction , 2007 .

[3]  A. Bronstert,et al.  Automated catena‐based discretization of landscapes for the derivation of hydrological modelling units , 2008, Int. J. Geogr. Inf. Sci..

[4]  Reinder A. Feddes,et al.  Simulation of field water uptake by plants using a soil water dependent root extraction function , 1976 .

[5]  Peter A. Troch,et al.  Hillslope hydrology under glass: confronting fundamental questions of soil-water-biota co-evolution at Biosphere 2 , 2009 .

[6]  J. Ihringer,et al.  Modeling water flow and mass transport in a loess catchment , 2001 .

[7]  K. Eckhardt,et al.  Plant parameter values for models in temperate climates , 2003 .

[8]  Patrick Matgen,et al.  Conceptual modelling of individual HRU’s as a trade-off between bottom-up and top-down modelling, a case study. , 2006 .

[9]  Tom Rientjes,et al.  Flux parameterization in the representative elementary watershed approach: Application to a natural basin , 2005 .

[10]  Pieter Hazenberg Testing the hybrid-3D Hillslope Hydrological Model in a Real-World Controlled Environment , 2015 .

[11]  Erwin Zehe,et al.  A quality assessment of Spatial TDR soil moisture measurements in homogenous and heterogeneous media with laboratory experiments , 2010 .

[12]  Rein Ahas,et al.  Variations of the climatological growing season (1951–2000) in Germany compared with other countries , 2003 .

[13]  R. Freeze,et al.  Blueprint for a physically-based, digitally-simulated hydrologic response model , 1969 .

[14]  Hervé Andrieu,et al.  Modeling the influence of an artificial macropore in sandy columns on flow and solute transfer , 2009 .

[15]  Hubert H. G. Savenije,et al.  Opinion paper: How to make our models more physically-based , 2016 .

[16]  Erwin Zehe,et al.  Uncertainty of simulated catchment runoff response in the presence of threshold processes: Role of initial soil moisture and precipitation , 2005 .

[17]  M. Sivapalan,et al.  On the relative roles of hillslope processes, channel routing, and network geomorphology in the hydrologic response of natural catchments , 1995 .

[18]  Kevin W. Manning,et al.  The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements , 2011 .

[19]  C. Simmons,et al.  HydroGeoSphere: A Fully Integrated, Physically Based Hydrological Model , 2012 .

[20]  Axel Bronstert,et al.  Modelling of runoff generation and soil moisture dynamics for hillslopes and micro-catchments , 1997 .

[21]  Damiano Pasetto,et al.  Multiresponse modeling of variably saturated flow and isotope tracer transport for a hillslope experiment at the Landscape Evolution Observatory , 2016 .

[22]  A. Peters,et al.  Author ' s personal copy Simplified evaporation method for determining soil hydraulic properties , 2008 .

[23]  M. Celia,et al.  A General Mass-Conservative Numerical Solution for the Unsaturated Flow Equation , 1990 .

[24]  Erwin Zehe,et al.  Predictions of rainfall-runoff response and soil moisture dynamics in a microscale catchment using the CREW model , 2006 .

[25]  Hubert H. G. Savenije,et al.  The effect of spatial throughfall patterns on soil moisture patterns at the hillslope scale , 2012 .

[26]  K. Loague,et al.  Physics‐based hydrologic response simulation: platinum bridge, 1958 Edsel, or useful tool , 2004 .

[27]  Peter Lehmann,et al.  Hydrology and Earth System Sciences Rainfall Threshold for Hillslope Outflow: an Emergent Property of Flow Pathway Connectivity , 2022 .

[28]  Keith Beven Streamflow generation processes. , 2006 .

[29]  Axel Kleidon,et al.  A thermodynamic formulation of root water uptake , 2015 .

[30]  M. Adams,et al.  An improved heat pulse method to measure low and reverse rates of sap flow in woody plants. , 2001, Tree physiology.

[31]  E. C. Childs Dynamics of fluids in Porous Media , 1973 .

[32]  S. Bergström,et al.  DEVELOPMENT OF A CONCEPTUAL DETERMINISTIC RAINFALL-RUNOFF MODEL , 1973 .

[33]  James C. I. Dooge,et al.  Looking for hydrologic laws , 1986 .

[34]  Dmitri Kavetski,et al.  Towards more systematic perceptual model development: a case study using 3 Luxembourgish catchments , 2015 .

[35]  Lucien Hoffmann,et al.  Recent Trends in Rainfall-Runoff Characteristics in the Alzette River Basin, Luxembourg , 2000 .

[36]  Erwin Zehe,et al.  Predicting subsurface stormflow response of a forested hillslope - the role of connected flow paths , 2014 .

[37]  Erwin Zehe,et al.  In situ investigation of rapid subsurface flow: Temporal dynamics and catchment-scale implication , 2016 .

[38]  Jeffrey J. McDonnell,et al.  Hydrological connectivity inferred from diatom transport through the riparian-stream system , 2015 .

[39]  M. Kirkby Tests of the random network model, and its application to basin hydrology , 1976 .

[40]  Lucien Hoffmann,et al.  The Influence of Sediment Sources and Hydrologic Events on the Nutrient and Metal Content of Fine-Grained Sediments (Attert River Basin, Luxembourg) , 2012, Water, Air, & Soil Pollution.

[41]  R. D. Black,et al.  Partial Area Contributions to Storm Runoff in a Small New England Watershed , 1970 .

[42]  Ming Ye,et al.  Towards a comprehensive assessment of model structural adequacy , 2012 .

[43]  Peter J. Shouse,et al.  Lateral Water Diffusion in an Artificial Macroporous System: Modeling and Experimental Evidence , 2003 .

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

[45]  Erwin Zehe,et al.  Process identification through rejection of model structures in a mid‐mountainous rural catchment: observations of rainfall–runoff response, geophysical conditions and model inter‐comparison , 2009 .

[46]  Delphis F. Levia,et al.  Forest hydrology and biogeochemistry : synthesis of past research and future directions , 2011 .

[47]  Erwin Zehe,et al.  A thermodynamic approach to link self-organization, preferential flow and rainfall-runoff behaviour , 2013 .

[48]  Julian Klaus,et al.  Modelling rapid flow response of a tile‐drained field site using a 2D physically based model: assessment of ‘equifinal’ model setups , 2010 .

[49]  C. Paniconi,et al.  Surface‐subsurface flow modeling with path‐based runoff routing, boundary condition‐based coupling, and assimilation of multisource observation data , 2010 .

[50]  Thomas A. McMahon,et al.  Physically based hydrologic modeling: 2. Is the concept realistic? , 1992 .

[51]  R. Uijlenhoet,et al.  Similarity analysis of subsurface flow response of hillslopes with complex geometry , 2004 .

[52]  David R. Montgomery,et al.  Physics‐based continuous simulation of long‐term near‐surface hydrologic response for the Coos Bay experimental catchment , 2007 .

[53]  J. Nieber,et al.  Soil pipe contribution to steady subsurface stormflow , 1991 .

[54]  Keith Beven,et al.  Macropores and water flow in soils revisited , 2013 .

[55]  Keith Loague,et al.  Physics‐based hydrologic‐response simulation: Seeing through the fog of equifinality , 2006 .

[56]  Keith Beven,et al.  Changing ideas in hydrology — The case of physically-based models , 1989 .

[57]  Erwin Zehe,et al.  In situ investigation of rapid subsurface flow: Identification of relevant spatial structures beyond heterogeneity , 2016 .

[58]  Erwin Zehe,et al.  Plot and field scale soil moisture dynamics and subsurface wetness control on runoff generation in a headwater in the Ore Mountains , 2009 .

[59]  Hubert H. G. Savenije,et al.  Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the Representative Elementary Watershed (REW) approach , 2005 .

[60]  Joshua M. Bishop,et al.  Measurement and simulation of subsurface tracer migration to tile drains in low permeability, macroporous soil , 2015 .

[61]  Jeffrey J. McDonnell,et al.  Threshold relations in subsurface stormflow: 2. The fill and spill hypothesis , 2006 .

[62]  P. Jarvis The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[63]  Lucien Hoffmann,et al.  Use of regionalized stormflow coefficients with a view to hydroclimatological hazard mapping , 2002 .

[64]  K. Beven Searching for the Holy Grail of Scientific Hydrology: Qt= H(S?R?)A as closure , 2006 .

[65]  V. Klemeš,et al.  Operational Testing of Hydrological Simulation Models , 2022 .

[66]  J. Refsgaard,et al.  Large scale modelling of groundwater contamination from nitrate leaching , 1999 .

[67]  A. Jakeman,et al.  How much complexity is warranted in a rainfall‐runoff model? , 1993 .

[68]  John L. Nieber,et al.  How do disconnected macropores in sloping soils facilitate preferential flow? , 2010 .

[69]  Till Francke,et al.  Modelling sediment export, retention and reservoir sedimentation in drylands with the WASA-SED model , 2010 .

[70]  Erwin Zehe,et al.  Dynamical process upscaling for deriving catchment scale state variables and constitutive relations for meso-scale process models , 2006 .

[71]  Horst H. Gerke,et al.  Combining dual-continuum approach with diffusion wave model to include a preferential flow component in hillslope scale modeling of shallow subsurface runoff , 2012 .

[72]  Hoshin Vijai Gupta,et al.  Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling , 2009 .

[73]  Erwin Zehe,et al.  HESS Opinions: From response units to functional units: a thermodynamic reinterpretation of the HRU concept to link spatial organization and functioning of intermediate scale catchments , 2014 .

[74]  Dmitri Kavetski,et al.  Catchment properties, function, and conceptual model representation: is there a correspondence? , 2014 .

[75]  Markus Weiler,et al.  Tree-, stand- and site-specific controls on landscape-scale patterns of transpiration , 2017 .

[76]  Hoshin Vijai Gupta,et al.  Do Nash values have value? , 2007 .

[77]  Keith Beven,et al.  Searching for the Holy Grail of scientific hydrology: Q t =( S, R, Δt ) A as closure , 2006 .

[78]  D. Schäfer,et al.  The Weiherbach data set: An experimental data set for pesticide model testing on the field scale , 2000 .

[79]  Olaf A. Cirpka,et al.  Simulating the transition of a semi-arid rainfed catchment towards irrigation agriculture , 2011 .

[80]  Hubert H. G. Savenije,et al.  Model complexity control for hydrologic prediction , 2008 .

[81]  Benjamin B. Mirus,et al.  Physics‐based hydrologic‐response simulation: foundation for hydroecology and hydrogeomorphology , 2006 .

[82]  Jeffrey J. McDonnell,et al.  Connectivity at the hillslope scale: identifying interactions between storm size, bedrock permeability, slope angle and soil depth. , 2009 .

[83]  Erwin Zehe,et al.  Disentangling timing and amplitude errors in streamflow simulations , 2016 .

[84]  Erwin Zehe,et al.  A novel explicit approach to model bromide and pesticide transport in connected soil structures , 2011 .

[85]  Balaji Rajagopalan,et al.  Are we unnecessarily constraining the agility of complex process‐based models? , 2015 .

[86]  C. Paniconi,et al.  Hillslope‐storage Boussinesq model for subsurface flow and variable source areas along complex hillslopes: 1. Formulation and characteristic response , 2003 .