Hillslope dynamics modeled with increasing complexity

Summary Few studies have investigated how much model complexity is needed to simulate both the hillslope outflow and the internal hillslope dynamics. We studied the influence of model complexity on simulations for the Panola Mountain trenched hillslope. We analyzed the influences of the inclusion of bedrock permeability, variable soil depth and preferential flow on modeled hillslope responses. We found that without the inclusion of bedrock leakage the long-term subsurface flow response measured at the trenchface and the threshold relation between total precipitation and total subsurface flow could not be simulated adequately. Individual events could still be represented acceptably, showing the importance of long time series for model calibration and validation. The use of spatially constant bedrock conductivity allowed us to simulate spatially variable bedrock leakage rates because of the spatially variable depths of saturation. Without variable soil depth the spatial variability of subsurface flow along the trenchface and its temporal dynamics during events could not be represented. In addition the spatial patterns of saturation at the soil-bedrock interface did not agree with the observed patterns and responses to smaller events were underestimated. Inclusion of preferential flow mainly influenced the distribution of the maximum saturation depths at the soil-bedrock interface and increased peak flows and recessions. Soil moisture measurements were less useful for model validation for the Panola hillslope than measurements of the spatial patterns of saturation and subsurface flow. We plea for a new blue print for the set-up of hillslope experiments such that their data is useful for studies on hillslope model complexity and for model validation and rejection.

[1]  George H. Hargreaves,et al.  Moisture availability and crop production. , 1975 .

[2]  D. Weyman,et al.  THROUGHFLOW ON HILLSLOPES AND ITS RELATION TO THE STREAM HYDROGRAPH , 1970 .

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

[4]  Mark S. Wigmosta,et al.  A comparison of simplified methods for routing topographically driven subsurface flow , 1999 .

[5]  Paul D. Bates,et al.  The effect of model configuration on modelled hillslope -riparian interactions , 2003 .

[6]  S. P. Anderson,et al.  Near-surface hydrologic response for a steep, unchanneled catchment near Coos Bay, Oregon: 2. Physics-based simulations , 2007, American Journal of Science.

[7]  Richard P. Hooper,et al.  Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology , 2007 .

[8]  Jeffrey J. McDonnell,et al.  On the interrelations between topography, soil depth, soil moisture, transpiration rates and species distribution at the hillslope scale , 2006 .

[9]  Kevin Bishop,et al.  A TEST OF TOPMODEL'S ABILITY TO PREDICT SPATIALLY DISTRIBUTED GROUNDWATER LEVELS , 1997 .

[10]  Tomomi Terajima,et al.  Experimental studies on the effects of pipeflow on throughflow partitioning , 1995 .

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

[12]  D. Stonestrom,et al.  Determining rates of chemical weathering in soils : solute transport versus profile evolution , 1998 .

[13]  Jeffrey J. McDonnell,et al.  Virtual experiments: a new approach for improving process conceptualization in hillslope hydrology , 2004 .

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

[15]  F. Naef,et al.  A combined field and numerical approach to investigate flow processes in natural macroporous soils under extreme precipitation , 1997 .

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

[17]  Keith Beven,et al.  Hydrological processes—Letters. Topographic controls on subsurface storm flow at the hillslope scale for two hydrologically distinct small catchmetns , 1997 .

[18]  S. P. Anderson,et al.  Concentration‐discharge relationships in runoff from a steep, unchanneled catchment , 1997 .

[19]  T. Mizuyama,et al.  Effects of pipe flow and bedrock groundwater on runoff generation in a steep headwater catchment in Ashiu, central Japan , 2002 .

[20]  J. Hewlett,et al.  Moisture and energy conditions within a sloping soil mass during drainage , 1963 .

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

[22]  R. Z. Whipkey SUBSURFACE STORMFLOW FROM FORESTED SLOPES , 1965 .

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

[24]  Keith Beven,et al.  The role of bedrock topography on subsurface storm flow , 2002 .

[25]  Keith Beven,et al.  NEW METHOD DEVELOPED FOR STUDYING FLOW ON HILLSLOPES , 1996 .

[26]  J. McDonnell,et al.  Effect of bedrock permeability on subsurface stormflow and the water balance of a trenched hillslope at the Panola Mountain Research Watershed, Georgia, USA , 2007 .

[27]  Ross Woods,et al.  The changing spatial variability of subsurface flow across a hillside , 1996 .

[28]  Jeffrey J. McDonnell,et al.  Testing nutrient flushing hypotheses at the hillslope scale: A virtual experiment approach , 2006 .

[29]  Jeffrey J. McDonnell,et al.  Threshold relations in subsurface stormflow: 1. A 147‐storm analysis of the Panola hillslope , 2006 .

[30]  Jeffrey J. McDonnell,et al.  The role of lateral pipe flow in hillslope runoff response: an intercomparison of non-linear hillslope response , 2005 .

[31]  J. McDonnell,et al.  Base cation concentrations in subsurface flow from a forested hillslope: The role of flushing frequency , 1998 .

[32]  Keith Beven,et al.  Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology , 2001 .

[33]  I. Cordery,et al.  Formation of runoff at the hillslope scale during intense precipitation , 2006 .

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

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

[36]  Keith Beven,et al.  On explanatory depth and predictive power , 2001 .

[37]  R. Hunt,et al.  Are Models Too Simple? Arguments for Increased Parameterization , 2007, Ground water.

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

[39]  Axel Bronstert,et al.  Capabilities and limitations of detailed hillslope hydrological modelling , 1999 .

[40]  R. Fannin,et al.  Hydrologic response of soils to precipitation at Carnation Creek, British Columbia, Canada , 2000 .

[41]  Günter Blöschl,et al.  Spatial Patterns of Catchment Hydrology: Observations and Modelling , 2000 .

[42]  P. F. Hudak,et al.  Alternatives for Ground Water Cleanup , 1995 .

[43]  Jeffrey J. McDonnell,et al.  Tracer and hydrometric study of preferential flow in large undisturbed soil cores from the Georgia Piedmont, USA , 1999 .

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

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

[46]  A reference data set of hillslope rainfall‐runoff response, Panola Mountain Research Watershed, United States , 2008 .