Space-based observations, emerged in the hydrology field in the last two decades, play a fundamental role in providing alternative information of hydrologic variables besides gauge measurements, especially in data scarce regions. Among all satellite products, products derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Satellite are popular due to the satellite's rapid re-visit time and adequate spatial resolutions. However, cloud obscuration limits the usage of products derived from MODIS because clouds block satellites from capturing the ground state of the earth surface. This dissertation aims to (1) recover two cloud-free MODIS datasets of snow and flood using a 3-D interpolation technique, namely, Variational Interpolation (VI) and (2) demonstrate their usefulness for hydrologic applications.

In the first part of this dissertation, the computational stability of the existing VI method is improved, then, we apply the algorithm to produce a cloud-free snow dataset for CONUS from 2000 to 2017. Moreover, by taking into consideration specific assumptions about the water body characteristic, we implement VI algorithm to remove clouds from MODIS flood maps. Promising results from a validation period over the Mississippi River are presented. We also couple the elevation information to derive the cloud-free MODIS water depth maps from the MODIS water extent maps. Water level maps are important for hydrological studies and can also act as references when the future Surface Water and Ocean Topography (SWOT) direct observations of water elevation are available in 2021.

In the second part of this dissertation, we use the resulting cloud-free MODIS flood and water depth maps to improve a hydrological model by reducing model errors via calibration and data assimilation. The calibrated output inundation maps accurately reflect flood events for the Upper Mississippi River Basin in 2013 and 2014. Also, the downstream discharge via the data assimilation scheme can correctly predict flood events during the same validation period. The results indicate that the framework can be further used to monitor and forecast floods.

As we stand on the cusp of another Supreme Court opinion concerning the use of racial considerations in education from Fisher v. University of Texas, the Court’s final verdict may potentially be another set back for affirmative action policies in education. However, the historical trajectory of the Court’s approach to racial issues in and beyond education suggests a more critical assessment of legal moments such as Fisher is needed. That is, Fisher must be placed within a historical racial narrative carefully orchestrated by the Court. The Court’s racial narrative adjudicates social cleavages on race in areas such as voting rights, employment law, criminal justice, and education. A comprehensive engagement of the Court’s discursive trajectory on race is necessary in order to accurately understand the significance of Fisher in the aftermath of Brown v. Board of Education. Without an engagement of the Court’s previous moments, our understanding of Fisher’s significance becomes limited and trapped within the mainstream colorblind racial narrative that all but dismisses the salience of racial subordination in society. This study will show that by engaging the Court’s long and unfortunate history adjudicating racial issues, white privilege and whiteness has been protected and perpetuated by the Court’s powerful authority. Furthermore, regardless of Fisher’s outcome, an engagement of how the Court has defined, protected, and perpetuated whiteness will fundamentally understand Fisher not only as a defeat or victory for racial considerations in education, but as an instantiation of the continuing problem of race in society. As a result, the persistence of racial subordination in the ‘colorblind’ era is anything but coincidental.

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