The water balance equation is one of the most fundamental concepts in hydrology. How much precipitation a river basin receives, and where that water goes, defines what flora, fauna, and industry the basin can support. Models for solving this equation originally relied only on precipitation, air temperature, and day length, but have adapted as new data becomes available. Recent advances in technology, especially remote sensing and web services, make it cheaper and easier than ever to obtain hydrological data, including many variables that were previously impossible to measure. This thesis will examine the water balance of the San Marcos River Basin and demonstrate how remote sensing and web services can improve our understanding of the basin's hydrology. It was found that 72% of precipitation in the San Marcos Basin is lost to evapotranspiration. This percentage varies from year to year as a function of precipitation, but the annual volume of evapotranspiration stays almost constant. It was only during the second consecutive year of drought that there was an appreciable change in evapotranspiration. This suggests that annual evapotranspiration can be thought of as a property inherent to a watershed's hydrology, and so long as there is enough stored water in the soil, that demand will be met. The water left over after ET takes its share can either flow out of the basin through a river channel or stay within the basin as storage. After examining methods for partitioning the available water between outflow and storage, it was found that lumped water balance models cannot be used in the San Marcos River Basin because of its complex interactions with the Edwards Aquifer. In order to better model soil moisture dynamics and groundwater infiltration, a distributed model will have to be developed that accounts for flow in and out of the aquifer. / text
Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-05-5528 |
Date | 25 June 2012 |
Creators | Siegel, Daniel Bandes, 1984- |
Source Sets | University of Texas |
Language | English |
Detected Language | English |
Type | thesis |
Format | application/pdf |
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