Groundwater is increasingly being over-drafted in the southeastern U.S., despite abundant rainfall and the apparent availability of surface water. Using the state of Louisiana as an example, the current study quantifies the stresses on water resources and investigates the potential for opportunities to use surface water in lieu of groundwater pumping. The assessment is based on two approaches: first, the National Hydrography Dataset (NHDPlus), which provides estimates of mean monthly and annual streamflow information (averaged over 1970-2000), is used to assess water stresses under climatologically average conditions of water availability. In the second approach, the hourly streamflow estimates from the second phase of North American Land Data Assimilation System (NLDAS-2) dataset (available for 1979-present) are used to incorporate intra-annual and inter-annual variability in surface water availability and the impact on water stress calculations at different temporal scales (seasonal and annual). The analysis is performed on a watershed scale representing Hydrological Unit Code boundaries (HUC12). The analysis on HUC12 scale depicts the spatial variations in the stresses and signalizes some areas with very high stresses that can be masked when estimated at larger scale, e.g. parish scale or HUC8 watershed scale. The WaSSI results indicate that the overall stresses in Louisiana are below one; however, some watersheds show stresses greater than one, which are largely attributable to water consumption for thermoelectric facilities or irrigation. The sensitivity of WaSSI to surface water supply showed that water stressed areas have a higher probability (greater than 90%) of becoming stressed under climate variability. Moreover, estimating the stresses on surface water and groundwater sources separately reveals the abundant availability of surface water with a significant over-drafting of groundwater wells that suggest new opportunities for reallocation of surface water use to reduce groundwater over pumping. Furthermore, the current study evaluates the quality of multi-sensor radar-based QPE estimates as one of the hydrologic forcing datasets in producing NLDAS-2 streamflow estimates. Using radar-based QPE products in frequency analysis reveals a systematic underestimation bias observed between radar- and gauge-bases frequency estimates. This underestimation bias was mostly attributable to the conditional bias inherent in the radar product. Addressing such key outstanding problems would provide more robust estimates of radar-rainfall products necessary for different hydrologic applications.
|Commitee:||Borrok, David, Habib, Emad, Hernandez, Rafael, Khattak, Mohammad, Sun, Xiaoduan|
|School:||University of Louisiana at Lafayette|
|School Location:||United States -- Louisiana|
|Source:||DAI-B 78/12(E), Dissertation Abstracts International|
|Subjects:||Hydrologic sciences, Civil engineering, Water Resource Management|
|Keywords:||Climate variability, Multi-sensor precipitation estimates, Precipitation frequency analysis, Water stresses, Water system sustainability|
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