Development and application of improved long-term datasets of surface hydrology for Texas

Lee, K., Gao, H., Huang, M., Sheffield, J. and Shi, X. (2017) Development and application of improved long-term datasets of surface hydrology for Texas. Advances in Meteorology, 2017, 8485130. (doi: 10.1155/2017/8485130)

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Abstract

Freshwater availability and agricultural production are key factors for sustaining the fast growing population and economy in the state of Texas, which is the third largest state in terms of agricultural production in the United States. This paper describes a long-term (1918–2011) grid-based (1/8°) surface hydrological dataset for Texas at a daily time step based on simulations from the Variable Infiltration Capacity (VIC) hydrological model. The model was calibrated and validated against observed streamflow over 10 Texas river basins. The simulated soil moisture was also evaluated using in situ observations. Results suggest that there is a decreasing trend in precipitation and an increasing trend in temperature in most of the basins. Droughts and floods were reconstructed and analyzed. In particular, the spatially distributed severity and duration of major Texas droughts were compared to identify new characteristics. The modeled flood recurrence interval and the return period were also compared with observations. Results suggest the performance of extreme flood simulations needs further improvement. This dataset is expected to serve as a benchmark which may contribute to water resources management and to mitigating agricultural drought, especially in the context of understanding the effects of climate change on crop yield in Texas.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Shi, Dr John Xiaogang
Authors: Lee, K., Gao, H., Huang, M., Sheffield, J., and Shi, X.
College/School:College of Social Sciences > School of Social & Environmental Sustainability
Journal Name:Advances in Meteorology
Publisher:Hindawi
ISSN:1687-9309
ISSN (Online):1687-9317
Copyright Holders:Copyright © 2017 Kyungtae Lee et al.
First Published:First published in Advances in Meteorology 2017:Advances in Meteorology
Publisher Policy:Reproduced under a Creative Commons License
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