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Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas

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Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas. / Lee, Kyungtae; Gao, Huilin; Huang, Maoyi et al.
In: Advances in Meteorology, Vol. 2017, 8485130, 06.03.2017.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Lee, K, Gao, H, Huang, M, Sheffield, J & Shi, X 2017, 'Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas', Advances in Meteorology, vol. 2017, 8485130. https://doi.org/10.1155/2017/8485130

APA

Lee, K., Gao, H., Huang, M., Sheffield, J., & Shi, X. (2017). Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas. Advances in Meteorology, 2017, Article 8485130. https://doi.org/10.1155/2017/8485130

Vancouver

Lee K, Gao H, Huang M, Sheffield J, Shi X. Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas. Advances in Meteorology. 2017 Mar 6;2017:8485130. doi: 10.1155/2017/8485130

Author

Lee, Kyungtae ; Gao, Huilin ; Huang, Maoyi et al. / Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas. In: Advances in Meteorology. 2017 ; Vol. 2017.

Bibtex

@article{a79dda60c50f4906b009e04adc4545cc,
title = "Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas",
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.",
author = "Kyungtae Lee and Huilin Gao and Maoyi Huang and Justin Sheffield and Xiaogang Shi",
year = "2017",
month = mar,
day = "6",
doi = "10.1155/2017/8485130",
language = "English",
volume = "2017",
journal = "Advances in Meteorology",
issn = "1687-9309",
publisher = "Hindawi Limited",

}

RIS

TY - JOUR

T1 - Development and Application of Improved Long-Term Datasets of Surface Hydrology for Texas

AU - Lee, Kyungtae

AU - Gao, Huilin

AU - Huang, Maoyi

AU - Sheffield, Justin

AU - Shi, Xiaogang

PY - 2017/3/6

Y1 - 2017/3/6

N2 - 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.

AB - 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.

U2 - 10.1155/2017/8485130

DO - 10.1155/2017/8485130

M3 - Journal article

AN - SCOPUS:85016067332

VL - 2017

JO - Advances in Meteorology

JF - Advances in Meteorology

SN - 1687-9309

M1 - 8485130

ER -