DEVELOPMENT OF A UNIFIED LAND MODEL WITH MULTI-CRITERIA OBSERVATIONAL DATA FOR THE SIMULATION OF REGIONAL HYDROLOGY AND LAND-ATMOSPHERE INTERACTION

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DEVELOPMENT OF A UNIFIED LAND MODEL WITH MULTI-CRITERIA OBSERVATIONAL DATA FOR THE SIMULATION OF REGIONAL HYDROLOGY AND LAND-ATMOSPHERE INTERACTION

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Title: DEVELOPMENT OF A UNIFIED LAND MODEL WITH MULTI-CRITERIA OBSERVATIONAL DATA FOR THE SIMULATION OF REGIONAL HYDROLOGY AND LAND-ATMOSPHERE INTERACTION
Author: Livneh, Ben
Abstract: A unified land model (ULM) is described that combines the surface flux parameterizations in the Noah land surface model (used in most of NOAA's coupled weather and climate models) with the Sacramento soil moisture accounting model (Sac; used for hydrologic prediction within the National Weather Service). The major motivation was to develop a model that has a history of strong hydrologic performance, while having the ability to be used as the land surface parameterization in coupled land-atmosphere models. Initial comparisons were made with observed surface fluxes and soil moisture wherein ULM performed well compared with its parent models (Noah, Sac) with a notably improved representation of the soil drying cycle. Parameter tuning was ultimately needed to capture streamflow dynamics, leading to a parameter estimation framework that utilized multiple independent data sets over the continental United States. These included a satellite-based evapotranspiration (ET) product based on MODerate resolution Imaging Spectroradiometer (MODIS) and Geostationary Operation Environmental Satellites (GOES) imagery, an atmospheric-water balance based ET estimate that uses 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 United States Geological Survey (USGS) stream gauges. At large scales (≥ 105 km2) calibrations using Q as an objective function resulted in the best overall multi-criteria performance. At small scales (< 104 km2), about one-third of the basins had their highest Q performance from multi-criteria calibrations (to Q and ET) suggesting that traditional calibration may benefit by supplementing remote sensing data. Finally, a scheme to transfer calibrated parameters was employed using Principal Components Analysis (PCA) to derive predictive relationships between model parameters and commonly used catchment attributes (meteorological, geomorphic, land-cover characteristics), several satellite remote sensing products, as well as the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) database. Regional model performance was most improved when locally optimized parameters were first resampled based on their performance at neighboring basins, termed zonalization. For a large number of basins, the regionalized model performed comparably to the calibrated version, affirming this PCA methodology as a viable means for transferring geospatial parameter information.
Description: Thesis (Ph.D.)--University of Washington, 2012
URI: http://hdl.handle.net/1773/20731
Author requested restriction: No embargo

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