Authors: Francisco Ochoa*, University of Texas - Austin, Kelley A. Crews, University of Texas - Austin
Topics: Water Resources and Hydrology, Environmental Science, Remote Sensing
Keywords: Evapotranspiration, Hydrology, Savanna Ecosystems, Vegetation Indices, Hydrological Modeling, Net Radiation
Session Type: Paper
Start / End Time: 2:00 PM / 3:40 PM
Room: Cabinet Room, Omni, West
Presentation File: No File Uploaded
Savanna ecosystems cover roughly about 20 % of the earth’s land surface. To better understand these systems in terms of both energy and hydrology, an initial assessment of both net radiation and hydrological budgets must be made. Previous efforts made to model evapotranspiration (ET) have used the crop coefficient (Kc) approach through remote sensing that utilizes thermal and spectral bands of satellite multi-spectral imagery to improve estimates of hydrological budgets. This previous work has been conducted in riparian ecosystems and agricultural areas using spectral indices such as the Enhanced Vegetation Index (EVI) and Normalized Differential Vegetation Index, in the United States (US), yet savanna ecosystems remain understudied within the US and throughout the world. Freeman Ranch, a savanna ecosystem in Central Texas, operated three flux towers that recorded energy fluxes at half-hour intervals from 2004 - 2011. Data from one tower were combined with daily MODIS-derived EVI to create an exponential equation that yields Kc. The equation was validated with the second nearby tower. Validation was done by comparing Kc estimates derived from satellite imagery to Kc derived from the flux tower. Kc from the flux tower were calculated by dividing actual ET by the reference ET, a boundary condition of potential ET that is based on Penman-Montieth FAO-56 equation. Precipitation observations and better measurements of net radiation can lead to a better understanding of biomass production within savanna ecosystems. Improved measurements of hydrological budgets in savanna ecosystems can lead to better water planning and land management decisions.