Abstract
Abstract. We describe a parameter estimation framework for the Unified Land Model (ULM) that utilizes multiple independent data sets over the continental United States. These include a satellite-based evapotranspiration (ET) product based on MODerate resolution Imaging Spectroradiometer (MODIS) and Geostationary Operational Environmental Satellites (GOES) imagery, an atmospheric-water balance based ET estimate that utilizes North American Regional Reanalysis (NARR) atmospheric fields, terrestrial water storage content (TWSC) data from the Gravity Recovery and Climate Experiment (GRACE), and streamflow (Q) primarily from the United States Geological Survey (USGS) stream gauges. The study domain includes 10 large-scale (≥105 km2) river basins and 250 smaller-scale (<104 km2) tributary basins. ULM, which is essentially a merger of the Noah Land Surface Model and Sacramento Soil Moisture Accounting Model, is the basis for these experiments. Calibrations were made using each of the data sets individually, in addition to combinations of multiple criteria, with multi-criteria skill scores computed for all cases. At large scales, calibration to Q resulted in the best overall performance, whereas certain combinations of ET and TWSC calibrations lead to large errors in other criteria. At small scales, about one-third of the basins had their highest Q performance from multi-criteria calibrations (to Q and ET) suggesting that traditional calibration to Q may benefit by supplementing observed Q with remote sensing estimates of ET. Model streamflow errors using optimized parameters were mostly due to over (under) estimation of low (high) flows. Overall, uncertainties in remote-sensing data proved to be a limiting factor in the utility of multi-criteria parameter estimation.
Highlights
The evolution of land surface models (LSMs) towards increasingly complex representations of hydrologic and biophysical processes requires special attention to the fidelity of the models in partitioning water and energy budget components
For the major basins (Sect. 2.1,) we evaluated the utility of incorporating ET and terrestrial water storage content (TWSC) as described in Sects. 2.2.1– 2.2.3
We considered a single realization of model outputs and observations rather than a range of values that reflect respective uncertainties
Summary
The evolution of land surface models (LSMs) towards increasingly complex representations of hydrologic and biophysical processes requires special attention to the fidelity of the models in partitioning water and energy budget components. Among the variables other than streamflow that have been used for LSM evaluation are evapotranspiration (Nandagiri, 2007), surface heat fluxes (Gupta et al, 1999; McCabe et al, 2005), hydrochemical and isotope tracers (Son and Sivapalan, 2007; Lischeid, 2008; Birkel et al, 2010), land surface temperature (Crow et al, 2003; McCabe et al, 2005), remotely sensed soil moisture (Brocca et al, 2010; Milzow et al, 2011), snow water equivalent (MacLean et al, 2010), terrestrial water storage (Werth and Guntner, 2010; Milzow et al, 2010), and water table level (Khu et al, 2008). Some satellite-based observations have periods of record exceeding a decade for single sensors, and multiple decades for some multi-sensor merged records
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