Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 2/1/2012
Publication Date: 2/19/2012
Citation: Yu, X., Duffy, C., Crow, W.T., Milak, S., Bhatt, G., Shi, Y. 2012. Using NLDAS-2 for initializing integrated watershed models: Model spin-up for the AirMOSS Campaign. Meeting Abstract. 2012 CDROM. Interpretive Summary:
Technical Abstract: Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) investigation has been developed for high-resolution in time and space root-zone soil moisture and carbon estimation. AirMOSS will build an ultra-high frequency (UHF) synthetic aperture radar (SAR) that has the capability to penetrate through substantial vegetation canopies and subsurface and retrieve information to the depths as deep as 1.2m depending on the soil moisture content. To meet the high temporal and spatial resolution of AirMOSS data Penn State Integrated Hydrologic Model (PIHM) – a fully-coupled physics-based hydrologic model is used. PIHM has ability to simulate terrestrial hydrological process at watershed and river basin scales. The finite volume based discretization and SUNDIALS based numerical solution strategy of PIHM enables to capture the high frequency shallow groundwater, soil moisture and stream-reach interactions in the context of tightly-coupled integrated modeling framework. NLDAS-2 land-surface forcing dataset was used as climate input to the hydrologic model. In this application, vertical soil moisture redistribution and land-surface energy modules are developed for assimilation of AirMOSS soil moisture observation data and providing further information for simulation of carbon dynamics. The first applications were the Tonzi Site (38°25'54'N 120°57'58'W), in the Upper Cosumnes River Watershed, and the Harvard Forest (42°31'48'N 72°11'24'W), including the East Branch Fever Brook, Headwaters East Branch Swift River and Mill Brook Millers River. A 42-km^2 catchment around Tonzi site and a 168-km^2 catchment around Harvard Forest were selected for soil moisture and energy transport simulation. Various processes representation specific to alpine region has been improved in PIHM to better simulate the data collected through AirMOSS. Dynamic snow accumulation and melt are also implemented for cold season processes. The state-of-the–art remote sensing technology is meant to support calibration and validation of hydrologic modeling and future improvements in the carbon dynamics coupled with the terrestrial water cycle.