Geostatistical Tools Can Improve Hydrologic Characterization to Support National-Domain Simulation of 
Complete Water Budgets

ABSTRACT:
Characterization of hydrologic records at continental domains, including vast swaths of unmonitored 
locations, is one of the quintessential challenges of hydrology.  Both statistical and mechanistic 
hydrologic models have been developed to address this challenge.  Geostatistical tools have become 
popular for reproducing historical daily hydrographs in a spatially-continuous manner at continental 
scales.  These tools, in turn, can be used to improve the calibration, development and application of 
mechanistic models of the full water budget at similar scales.  Through a consideration of 
geostatistical hydrograph simulation, we show statistical tools can used to correct systemic bias in 
hydrologic models, develop at-site information and uncertainty for mechanistic calibration, and drive 
calibration towards improved objectives.  Considerations of global uncertainty and bias-correction can 
alter how we begin to re-imagine our use of hydrologic simulation.  Much in the spirit of stochastic 
streamflow models, statistical and mechanistic models can be brought together to develop the next 
generation of stochastic models of complete hydrologic cycles.  As we attempt to characterize 
national-domain hydrologic cycles in a manner to support robust decision making, incorporating 
statistical tools into mechanistic modeling will improve the use of models, the characterization of 
uncertainty and the development of improved models.