Improving computational efficiency in global river models by implementing the local inertial flow equation and a vector‐based river network map

Global river models are an essential tool for both earth system studies and water resources assessments. As advanced physical processes have been implemented in global river models, increasing computational cost has become problematic for executing ensemble or long-term simulations. To improve computational efficiency, we here propose the use of a local inertial flow equation combined with a vector-based river network map. A local inertial equation, a simplified formulation of the shallow water equations, was introduced to replace a diffusion wave equation. A vector-based river network map which flexibly discretizes river segments was adopted in order to replace the traditional grid-based map which is based on a Cartesian grid coordinate system. The computational efficiency of the proposed flow routing and river network map was tested by executing hydrodynamic simulations with the CaMa-Flood global river model. The simulation results suggest that the computational efficiency can be improved by more than 300% by applying the local inertial equation. It can be improved by a further 60% by implementing the vector-based river network map instead of a grid-based map. It is found that the vector-based map with evenly distributed flow distances between calculation units allows longer time steps compared to the grid-based map because the latter has very short flow distances between calculation units at high latitudes which critically limit time step length. Considering the improvement in simulation speed, the local inertial equation and a vector-based river network map are preferable in global hydrodynamic simulations with high computational demands such as ensemble or long-term experiments.

[1]  S. Calmant,et al.  Large‐scale hydrologic and hydrodynamic modeling of the Amazon River basin , 2013 .

[2]  P. Bates,et al.  Applicability of the local inertial approximation of the shallow water equations to flood modeling , 2013 .

[3]  Yuzuru Matsuoka,et al.  Development of highly accurate global polygonal drainage basin data , 2009 .

[4]  Paul D. Bates,et al.  Adjustment of a spaceborne DEM for use in floodplain hydrodynamic modeling , 2012 .

[5]  Paul D. Bates,et al.  Improving the stability of a simple formulation of the shallow water equations for 2‐D flood modeling , 2012 .

[6]  S. Kanae,et al.  An integrated model for the assessment of global water resources – Part 2: Applications and assessments , 2008 .

[7]  P. Bates,et al.  Optimal Cross-Sectional Spacing in Preissmann Scheme 1D Hydrodynamic Models , 2009 .

[8]  J. Arnold,et al.  SWAT2000: current capabilities and research opportunities in applied watershed modelling , 2005 .

[9]  Naota Hanasaki,et al.  GSWP-2 Multimodel Analysis and Implications for Our Perception of the Land Surface , 2006 .

[10]  H. Douville,et al.  A new river flooding scheme for global climate applications: Off‐line evaluation over South America , 2008 .

[11]  Aaron Boone,et al.  The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin , 2012 .

[12]  David A. Seal,et al.  The Shuttle Radar Topography Mission , 2007 .

[13]  Paul D. Bates,et al.  An adaptive time step solution for raster-based storage cell modelling of floodplain inundation , 2005 .

[14]  Augusto Getirana,et al.  Integrating spatial altimetry data into the automatic calibration of hydrological models , 2010 .

[15]  S. Kanae,et al.  Global flood risk under climate change , 2013 .

[16]  K. Verdin,et al.  New Global Hydrography Derived From Spaceborne Elevation Data , 2008 .

[17]  Taikan Oki,et al.  Changes in Flood Risk under Global Warming Estimated Using MIROC5 and the Discharge Probability Index , 2012 .

[18]  Tessa Eikelboom,et al.  A physically based model of global freshwater surface temperature , 2012 .

[19]  P. Bates,et al.  A simple raster-based model for flood inundation simulation , 2000 .

[20]  G. Miguez-Macho,et al.  The role of groundwater in the Amazon water cycle: 1. Influence on seasonal streamflow, flooding and wetlands , 2012 .

[21]  Petra Döll,et al.  Validation of a new global 30-min drainage direction map , 2002 .

[22]  F. Pappenberger,et al.  Deriving global flood hazard maps of fluvial floods through a physical model cascade , 2012 .

[23]  T. Oki,et al.  Multimodel Estimate of the Global Terrestrial Water Balance: Setup and First Results , 2011 .

[24]  Matthew D. Wilson,et al.  Simple spatially-distributed models for predicting flood inundation: A review , 2007 .

[25]  H. Hasumi,et al.  Improved Climate Simulation by MIROC5: Mean States, Variability, and Climate Sensitivity , 2010, Journal of Climate.

[26]  P. Bates,et al.  A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. , 2010 .

[27]  Shinjiro Kanae,et al.  First estimate of the future global population at risk of flooding , 2009 .

[28]  Dennis P. Lettenmaier,et al.  Coupled daily streamflow and water temperature modelling in large river basins , 2012 .

[29]  M. Coe,et al.  Simulating the surface waters of the Amazon River basin: impacts of new river geomorphic and flow parameterizations , 2008 .

[30]  C. Rennó,et al.  Height Above the Nearest Drainage – a hydrologically relevant new terrain model , 2011 .

[31]  Bernhard Lehner,et al.  Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems , 2013 .

[32]  Taikan Oki,et al.  Role of rivers in the seasonal variations of terrestrial water storage over global basins , 2009 .

[33]  S. Kanae,et al.  A physically based description of floodplain inundation dynamics in a global river routing model , 2011 .

[34]  R. Paiva,et al.  Large scale hydrologic and hydrodynamic modeling using limited data and a GIS based approach , 2011 .

[35]  L. Alfieri,et al.  GloFAS – global ensemble streamflow forecasting and flood early warning , 2012 .

[36]  P. Döll,et al.  High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management , 2011 .

[37]  Victor Eijkhout,et al.  River Network Routing on the NHDPlus Dataset , 2011 .

[38]  P. Bates,et al.  A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas , 2012 .

[39]  G. Russell,et al.  Continental-Scale River Flow in Climate Models , 1994 .

[40]  Taikan Oki,et al.  Deriving a global river network map and its sub-grid topographic characteristics from a fine-resolution flow direction map , 2009 .

[41]  Charles J Vörösmarty,et al.  Scaling gridded river networks for macroscale hydrology: Development, analysis, and control of error , 2001 .

[42]  Albert J. Kettner,et al.  WBMsed, a distributed global-scale riverine sediment flux model: Model description and validation , 2013, Comput. Geosci..

[43]  Y. He,et al.  Simulating hydrologic and hydraulic processes throughout the Amazon River Basin , 2009 .

[44]  J. Crétaux,et al.  Hydrology and Earth System Sciences Evaluation of the Isba-trip Continental Hydrologic System over the Niger Basin Using in Situ and Satellite Derived Datasets v. Pedinotti Et Al.: Isba-trip Continental Hydrologic System over the Niger Basin , 2022 .

[45]  T. Oki,et al.  Impact of Climate Change on River Discharge Projected by Multimodel Ensemble , 2006 .

[46]  A. Becker,et al.  Disaggregation, aggregation and spatial scaling in hydrological modelling , 1999 .

[47]  Taikan Oki,et al.  Global projections of changing risks of floods and droughts in a changing climate , 2008 .

[48]  T. Oki,et al.  Design of Total Runoff Integrating Pathways (TRIP)—A Global River Channel Network , 1998 .

[49]  S. Kanae,et al.  Analysis of the water level dynamics simulated by a global river model: A case study in the Amazon River , 2012 .

[50]  Aaron Boone,et al.  Automatic parameterization of a flow routing scheme driven by radar altimetry data: Evaluation in the Amazon basin , 2013 .

[51]  Taikan Oki,et al.  Assessment of Annual Runoff from Land Surface Models Using Total Runoff Integrating Pathways (TRIP) , 1999 .