Hyperresolution hydrologic modeling in a regional watershed and its interpretation using empirical orthogonal functions

Hyperresolution (<1 km) hydrologic modeling of regional watersheds is expected to support a broad range of terrestrial water cycle studies, but its feasibility is still challenging due to process, data and computational constraints, as well as difficulties in interpreting the high-dimensional dataset of spatiotemporal model forcings and outputs. We address some of these modeling challenges by extending the application of a physically-based, distributed hydrologic model to the Rio San Miguel watershed (3796 km2) in Mexico based on prior efforts that demonstrated the process fidelity at smaller spatiotemporal scales. Long-term (7 year) simulations are conducted at a hyperresolution (∼78 m) over the large domain using parallel simulation capabilities. To address data sparseness, we develop strategies to integrate ground, remotely-sensed and reanalysis data for setting up, forcing and parameterizing the model. Complementary tests with observations at individual stations and remotely-sensed spatial patterns reveal a robust model performance. After building confidence in the model, we interpret the spatiotemporal model forcings and outputs using empirical orthogonal functions (EOFs) analyses. For all model outputs, a large portion (58–80%) of the spatiotemporal variability can be explained by two dominant EOFs, which are related to model forcings and basin properties. Terrain controls on soil water accumulation have a marked impact on the spatial distribution of most hydrologic variables during the wet season. In addition, soil properties affect soil moisture patterns, while vegetation and elevation distributions influence evapotranspiration and runoff fields. Given the large outputs from long-term hyperresolution simulations, EOF analyses provide a promising avenue for extracting meaningful hydrologic information within complex, regional watersheds.

[1]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[2]  M. Ek,et al.  Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water , 2011 .

[3]  A-Xing Zhu,et al.  Estimation of theoretical maximum speedup ratio for parallel computing of grid-based distributed hydrological models , 2013, Comput. Geosci..

[4]  Fabio Castelli,et al.  Vegetation Dynamics within the North American Monsoon Region , 2011 .

[5]  E. Vivoni,et al.  Quantification of hydrologic impacts of climate change in a Mediterranean basin in Sardinia, Italy, through high-resolution simulations , 2014 .

[6]  D. Lettenmaier,et al.  Production of Temporally Consistent Gridded Precipitation and Temperature Fields for the Continental United States , 2005 .

[7]  Tiantian Xiang,et al.  Seasonal evolution of ecohydrological controls on land surface temperature over complex terrain , 2014 .

[8]  R. Maxwell,et al.  A comparison of two physics-based numerical models for simulating surface water–groundwater interactions , 2010 .

[9]  Marco Piras,et al.  Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrome , 2013 .

[10]  M. Flörke,et al.  Future long-term changes in global water resources driven by socio-economic and climatic changes , 2007 .

[11]  Claudia Notarnicola,et al.  Topographical and ecohydrological controls on land surface temperature in an alpine catchment , 2010 .

[12]  Dara Entekhabi,et al.  Generation of triangulated irregular networks based on hydrological similarity , 2004 .

[13]  D. Gochis,et al.  The diurnal cycle of clouds and precipitation along the Sierra Madre Occidental observed during NAME-2004: Implications for warm season precipitation estimation in complex terrain , 2008 .

[14]  Mauro Sulis,et al.  Assessment of climate change impacts at the catchment scale with a detailed hydrological model of surface‐subsurface interactions and comparison with a land surface model , 2011 .

[15]  Ian T. Jolliffe,et al.  Empirical orthogonal functions and related techniques in atmospheric science: A review , 2007 .

[16]  Olaf Kolditz,et al.  Surface‐subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks , 2014 .

[17]  Richard K. Taft,et al.  Multiscale Variability of the Flow during the North American Monsoon Experiment , 2007 .

[18]  K. Beven,et al.  A physically based, variable contributing area model of basin hydrology , 1979 .

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

[20]  R. Koster,et al.  Land Surface Controls on Hydroclimatic Means and Variability , 2012 .

[21]  F. Pappenberger,et al.  The impact of weather forecast improvements on large scale hydrology: analysing a decade of forecasts of the European Flood Alert System , 2010 .

[22]  Felipe J. Colón-González,et al.  Multimodel assessment of water scarcity under climate change , 2013, Proceedings of the National Academy of Sciences.

[23]  Jan Vanderborght,et al.  Proof of concept of regional scale hydrologic simulations at hydrologic resolution utilizing massively parallel computer resources , 2010 .

[24]  S. Schubert,et al.  Numerical simulation of the large‐scale North American monsoon water sources , 2003 .

[25]  Enrique R. Vivoni,et al.  Spatial patterns, processes and predictions in ecohydrology: integrating technologies to meet the challenge , 2012 .

[26]  R. Fensholt,et al.  Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements , 2004 .

[27]  Benjamin B. Mirus,et al.  First‐order exchange coefficient coupling for simulating surface water–groundwater interactions: parameter sensitivity and consistency with a physics‐based approach , 2009 .

[28]  Kurt H. Riitters,et al.  Topographic controls on the regional‐scale biodiversity of the south‐western USA , 2004 .

[29]  K. Abbaspour,et al.  Modeling blue and green water availability in Africa , 2008 .

[30]  Chaopeng Shen,et al.  Evaluating controls on coupled hydrologic and vegetation dynamics in a humid continental climate watershed using a subsurface‐land surface processes model , 2013 .

[31]  E. Vivoni,et al.  Ecohydrology of water‐limited environments: A scientific vision , 2006 .

[32]  Yongqiang Liu.  Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region , 2003 .

[33]  C. Vörösmarty,et al.  Global water resources: vulnerability from climate change and population growth. , 2000, Science.

[34]  Gwangseob Kim,et al.  Space-time characterization of soil moisture from passive microwave remotely sensed imagery and ancillary data , 2002 .

[35]  S. Sorooshian,et al.  Effective and efficient global optimization for conceptual rainfall‐runoff models , 1992 .

[36]  F. Dominguez,et al.  Precipitation recycling variability and ecoclimatological stability - A study using NARR data. Pa , 2008 .

[37]  Dara Entekhabi,et al.  Controls on runoff generation and scale-dependence in a distributed hydrologic model , 2007 .

[38]  Paolo Salandin,et al.  Coupled and uncoupled hydrogeophysical inversions using ensemble Kalman filter assimilation of ERT‐monitored tracer test data , 2015 .

[39]  Enrique R. Vivoni,et al.  Utility of coarse and downscaled soil moisture products at L-band for hydrologic modeling at the , 2012 .

[40]  E. Vivoni,et al.  On the spatiotemporal variability of soil moisture and evapotranspiration in a mountainous basin within the North American monsoon region , 2010 .

[41]  Franz Barthelmes,et al.  Determination of dominant periodic components of water storage changes from GRACE and global hydrology models , 2007 .

[42]  R. Bras,et al.  A kinematic model of infiltration and runoff generation in layered and sloped soils , 1992 .

[43]  Clemens Simmer,et al.  The Influence of Hydrologic Modeling on the Predicted Local Weather: Two-Way Coupling of a Mesoscale Weather Prediction Model and a Land Surface Hydrologic Model , 2002 .

[44]  Baoguo Li,et al.  Assessing grain crop water productivity of China using a hydro-model-coupled-statistics approach Part I: Method development and validation , 2010 .

[45]  Enrique R. Vivoni,et al.  Limits to Flood Forecasting in the Colorado Front Range for Two Summer Convection Periods Using R , 2013 .

[46]  J. Ronchail,et al.  Spatio‐temporal rainfall variability in the Amazon basin countries (Brazil, Peru, Bolivia, Colombia, and Ecuador) , 2009 .

[47]  Valeri Yuryevich Ivanov,et al.  A continuous real-time interactive basin simulator (RIBS) , 2002 .

[48]  M. Latif,et al.  A Cautionary Note on the Interpretation of EOFs , 2002 .

[49]  Enrique R. Vivoni,et al.  Vegetation‐hydrology dynamics in complex terrain of semiarid areas: 1. A mechanistic approach to modeling dynamic feedbacks , 2008 .

[50]  R. Rigon,et al.  GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets , 2006 .

[51]  A. Hamlet,et al.  Spatial‐temporal variations of evapotranspiration and runoff/precipitation ratios responding to the changing climate in the Pacific Northwest during 1921‐2006 , 2013 .

[52]  Enrique R. Vivoni,et al.  A modeling approach reveals differences in evapotranspiration and its partitioning in two semiarid ecosystems in Northwest Mexico , 2014 .

[53]  Thomas J. Jackson,et al.  Vegetation water content during SMEX04 from ground data and Landsat 5 Thematic Mapper imagery , 2008 .

[54]  E. Vivoni,et al.  Catchment hydrologic response with a fully distributed triangulated irregular network model , 2004 .

[55]  Keith Beven,et al.  Including spatially variable effective soil depths in TOPMODEL , 1997 .

[56]  W. Rawls,et al.  Estimating generalized soil-water characteristics from texture , 1986 .

[57]  Enrique R. Vivoni,et al.  Diagnosing Seasonal Vegetation Impacts on Evapotranspiration and Its Partitioning at the Catchmen , 2012 .

[58]  Venkat Lakshmi,et al.  Analysis of process controls in land surface hydrological cycle over the continental United States , 2004 .

[59]  Petra Döll,et al.  Estimating the Impact of Global Change on Flood and Drought Risks in Europe: A Continental, Integrated Analysis , 2006 .

[60]  E. Vivoni,et al.  On the effects of triangulated terrain resolution on distributed hydrologic model response , 2005 .

[61]  Hideki Kobayashi,et al.  Continuous observation of tree leaf area index at ecosystem scale using upward-pointing digital cameras , 2012 .

[62]  Cédric H. David,et al.  Hydrological evaluation of the Noah‐MP land surface model for the Mississippi River Basin , 2014 .

[63]  Enrique R. Vivoni,et al.  Temporal Downscaling and Statistical Analysis of Rainfall across a Topographic Transect in Northwest Mexico , 2014 .

[64]  Günter Blöschl,et al.  Advances in the use of observed spatial patterns of catchment hydrological response , 2002 .

[65]  Antonio Trabucco,et al.  Climate change mitigation through afforestation/reforestation: A global analysis of hydrologic impacts with four case studies , 2008 .

[66]  Marco P. Maneta,et al.  A Spatially Distributed Model to Simulate Water, Energy, and Vegetation Dynamics Using Information from Regional Climate Models , 2013 .

[67]  Jeffrey D. Niemann,et al.  Spatial patterns from EOF analysis of soil moisture at a large scale and their dependence on soil, land-use, and topographic properties , 2007 .

[68]  E. Vivoni,et al.  Variation of hydrometeorological conditions along a topographic transect in northwestern Mexico d , 2007 .

[69]  W. J. Shuttleworth,et al.  Hydroclimatology of the North American Monsoon region in northwest Mexico , 2006 .

[70]  P. Döll,et al.  A global hydrological model for deriving water availability indicators: model tuning and validation , 2003 .

[71]  E. Vivoni,et al.  Ecosystem biophysical memory in the southwestern North America climate system , 2013 .

[72]  E. Vivoni,et al.  Vegetation controls on soil moisture distribution in the Valles Caldera, New Mexico, during the North American monsoon , 2008 .

[73]  Vipin Kumar,et al.  A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs , 1998, SIAM J. Sci. Comput..

[74]  Stephen M. Saleeby,et al.  Elevation-Dependent Trends in Precipitation Observed during NAME , 2008 .

[75]  R. Maxwell,et al.  Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model , 2008 .

[76]  F. Dominguez,et al.  Precipitation recycling variability and ecoclimatological stability - A study using NARR data. Pa , 2008 .

[77]  Enrique R. Vivoni,et al.  Distributed Hydrologic Modeling in Northwest Mexico Reveals the Links between Runoff Mechanisms a , 2012 .

[78]  Arun Kumar,et al.  Long‐range experimental hydrologic forecasting for the eastern United States , 2002 .

[79]  L. Feyen,et al.  Ensemble projections of future streamflow droughts in Europe , 2013 .

[80]  Enrique R. Vivoni,et al.  Improved land-atmosphere relations through distributed footprint sampling in a subtropical scrubland during the North American monsoon , 2010 .

[81]  Dara Entekhabi,et al.  Preserving high-resolution surface and rainfall data in operational-scale basin hydrology: a fully-distributed physically-based approach , 2004 .

[82]  Thomas J. Jackson,et al.  Soil Moisture Retrieval Using a Two-Dimensional L-Band Synthetic Aperture Radiometer in a Semiarid Environment , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[83]  E. Vivoni,et al.  Observed shifts in land surface conditions during the North American Monsoon: Implications for a vegetation–rainfall feedback mechanism , 2010 .

[84]  M. Camporese,et al.  Simplified modeling of catchment-scale evapotranspiration via boundary condition switching , 2014 .

[85]  E. Vivoni,et al.  Submesoscale spatiotemporal variability of North American monsoon rainfall over complex terrain , 2007 .

[86]  Enrique R. Vivoni,et al.  Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment , 2011 .

[87]  D. Goodrich,et al.  Linearity of basin response as a function of scale in a semiarid watershed , 1997 .

[88]  Michael T. Coe,et al.  Investigation of Hydrological Variability in West Africa Using Land Surface Models , 2005 .