Process-based modeling of soil moisture, soil temperature, and surface energy fluxes in the U.S. southern plains
Abstract
This study seeks to evaluate the capability and transferability of a physically-based hydrologic model to simulate temporal dynamics (1-hour resolution) to understand the trade-offs between precipitation, soil moisture and surface energy fluxes at foot-print measurement sites. One of the benefits of training a process-based model is the capacity to use it as a complement in standard weather stations to predict energy fluxes, and soil temperature estimations.
Modeling of the terrestrial surface's soil moisture and temperature, and boundary layer energy fluxes is key for understanding the spatio-temporal variability of hydrometeorological conditions that drive mean and extreme (i.e. floods and droughts) events. The surface energy balance (SEB) and soil temperature profile (STP) play an important role in the ground and near surface hydro-energetic dynamics, especially in water exchange processes such as the evapotranspiration (ET). ET is determinant on agriculture and different sectors. This study, uses the Triangulated Irregular Network TIN-based Real Time Integrated Basin Simulator (tRIBS), which is a continuous physically-based distributed hydrological model, tested over different locations in Oklahoma to evaluate the utility of the model as a tool to provide estimations of the SEB components in typical environments of the U.S. southern plains. The calibration, and validation of the model were performed using available Eddy Covariance Tower (ECT) observations distributed across Oklahoma. The model calibration was based on a hybrid strategy with a manual procedure followed by an automatized procedure that uses the Shuffled Complex Evolution (SCE) algorithm. All data used to parametrize the model was open source (i.e. MODIS products MOD13Q1, MCD15A3H, MCD43A) to represent dynamic vegetation conditions in albedo, leaf area index and vegetation fraction. Comparing more than 10200 hours of simulations the correlation coefficients (CC) between simulated and observed values are high providing confidence on the model performance. The validation strategy over the ECT was focused on the energy fluxes simulations during a different period. Transferability of this dynamic-vegetation parameterization will be accomplished through uncalibrated simulations in a similar ECT within Oklahoma.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H11H1568C
- Keywords:
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- 0496 Water quality;
- BIOGEOSCIENCESDE: 1805 Computational hydrology;
- HYDROLOGYDE: 1895 Instruments and techniques: monitoring;
- HYDROLOGYDE: 1916 Data and information discovery;
- INFORMATICS