Towards seamless large‐domain parameter estimation for hydrologic models

Abstract

Estimating spatially distributed parameters remains one of the biggest challenges for large‐domain hydrologic modeling. Many large‐domain modeling efforts rely on spatially inconsistent parameter fields, e.g., patchwork patterns resulting from individual basin calibrations, parameter fields generated through default transfer functions that relate geophysical attributes to model parameters, or spatially constant, default parameter values. This paper provides an initial assessment of a multiscale parameter regionalization (MPR) method over large geographical domains to derive seamless parameters in a spatially consistent manner. MPR applies transfer functions at the native scale of the geophysical data, and then scales these model parameters to the desired model resolution. We developed a stand‐alone framework called MPR‐flex for multimodel use and applied MPR‐flex to the variable infiltration capacity model to produce hydrologic simulations over the contiguous United States (CONUS). We first independently calibrate 531 basins across CONUS to obtain a performance benchmark for each basin. To derive the CONUS parameter fields, we perform a joint MPR calibration using all but the poorest behaved basins to obtain a single set of transfer function parameters that are applied to the entire CONUS. Results show that CONUS‐wide calibration has similar performance compared to previous simulations using a patchwork quilt of partially calibrated parameter sets, but without the spatial discontinuities in parameters that characterize some previous CONUS‐domain model simulations. Several avenues to improve CONUS‐wide calibration remain, including selection of calibration basins, objective function formulation, as well as MPR‐flex improvements including transfer function formulations and scaling operator optimization.

Toward seamless hydrologic predictions across spatial scales

“…As noted by Samaniego et al (2010b), this type of regionalization is inadequate because of the nonlinearity of soil and geological formations. The spatial patterns of model parameters that would be obtained by ad hoc extrapolations based on calibrated parameters from small basins or grid cells would most likely lead to unrealistic parameter fields with spatial discontinuities circumscribing river basins, as shown in recent studies by Wood and Mizukami (2014) and Mizukami et al (2017) for the VIC model parameters.…”

“…More recently, a model-agnostic implementation of MPR has been proposed by Mizukami et al (2017) and tested in the VIC model in over 500+ basins in the CONUS. The study of Mizukami et al (2017), in contrast to the present study, does not include flux-matching tests nor the evaluation of model skill across different spatial scales.…”

“…The above-mentioned challenges that we face in estimating key physical parameters in LSMs/HMs have been intensively discussed in many studies Bierkens et al, 2014;Bierkens, 2015;Clark et al, 2016Clark et al, , 2017Mizukami et al, 2017;Peters-Lidard et al, 2017). To further visualize the problems and to understand the deficiencies of current parameterization techniques, we selected a representative sample of LSMs/HMs used for research and/or operational purposes, namely CABLE, CLM, JULES, LISFLOOD, Noah-MP, mHM, PCR-GLOBWB, WaterGAP2 (30 arcmin), Wa-terGAP3 (5 arcmin), CHTESSEL, and HBV.…”

“…1. The Pan-EU domain was selected for depiction, but we note that the problem is general and persistent across other domains (Mizukami et al, 2017). For cases in which a HM does not use this parameter, the "available water capacity" (WaterGAP) or the "field capacity" (HBV) were selected as a surrogate due to their similarity with porosity.…”

Scaling, similarity, and the fourth paradigm for hydrology

“…This data assimilation approach is general and can be used -for example within the SUMMA modeling framework -to test hypotheses related to the appropriate model complexity on a given scale. A model-agnostic MPR system called MPR-flex has been recently applied to the VIC model to estimate seamless parameter and flux fields over the contiguous USA (Mizukami et al, 2017). This symbiosis of model parameterization (MPR-Flex) and simulation frameworks (e.g., SUMMA, mHM, etc.)…”