<p> Despite a rising interest in intermittent river systems, landscape influences on long-term wetting and drying patterns of streamflow are not well understood. There has been a significant increase in the presence of intermittent rivers worldwide due to climate change and subsequent increases in groundwater abstraction, and these effects are intensified in already arid regions such as the American Southwest. Consequently, the spatial extent of wet and dry reaches of Arizona&rsquo;s Agua Fria River, Cienega Creek, and San Pedro River has been documented by citizen scientists for several years. Citizen science involves the use of trained members of the public for data collection, and the analysis of datasets produced from citizen science projects have become a huge asset to the scientific community. Here, we synthesize the most current data (1999&ndash;2016) to determine what stream and valley characteristics act as drivers for patterns of surface water flow. Geologic, geomorphic, and land cover characteristics of these rivers were analyzed via aerial imagery and Digital Elevation Models within ArcGIS 10.3 in conjunction with the Soil and Water Assessment Tool model. Principal Component Analysis was used in order to assess trends across sites. A set of landscape intermittency metrics was produced and then further analyzed using Multiple Linear Regression. We found that land cover had a significant (p-value &lt; 0.01) positive correlation with reach average (i.e., the proportion of channel wet). Physical watershed and channel characteristics each had a negative correlation with both intermittency metrics (i.e., wet/dry status and reach average). However, their results were not significant to the 0.05 level. This study begins to shed light on the drivers of landscape intermittency patterns of desert streams and demonstrates the utility of citizen science in regard to the study of intermittent river systems.</p><p>

<p> In recent decades, there has been an increased awareness of the concentration of the poor in rural and underdeveloped areas and increased attention to scaled economic and multi-dimensional assessments as tools for targeting rural poverty. While this has led to new forms of development intervention in previously neglected regions across the Global South, in Morocco this system of poverty reduction continues to exclude key sites and stakeholders. This thesis asks how local state offices and non-state actors participate in or disrupt the structural systems of development in Morocco and what potential these local communities have for contributing to standardized knowledge production of poverty and development. I use participatory mapping workshops, interviews, and &ldquo;studying up&rdquo; strategies to answer questions of access &ndash; physical and social &ndash; to development planning and interventions. My findings indicate that the Moroccan rural development complex is structurally exclusionary to remote rural communities. The state and its partners have portrayed rural spaces as quickly rising out of poverty thanks to their decentralized and participatory development schemes, yet incongruently, local recipients in the least accessible areas live in spaces devoid of interventions. With all development practices inherently tied to state standards, any oversight or exclusion by state targeting is magnified by the same oversight of its development partners. The scale of targeting and evaluation in international metrics has contributed to this neglect, and the unfortunate result has been a feedback loop of inaccessibility for remote rural pockets of the country. I explain why one spatial indicator, village accessibility to social services, is an appropriate addition to poverty assessments and development targeting, drawing from my conversations with villagers in rural Tinghir Province and the results of my geospatial analysis.</p><p>

<p> Light Detection and Ranging (LiDAR) technology combined with high-resolution differential Global Positioning Systems (dGPS) provide the ability to measure coastal elevation with high precision. This study investigates the use of LiDAR data and GIS to conduct time-series analyses of coastal sediment volume shifts during the 2006-2007 El Ni&ntilde;o winter, Summer of 2007 and following 2007-2008 La Ni&ntilde;a winter in the Oceanside Littoral Cell (OLC). The OLC, located in Southern California, spans from Dana Point to La Jolla and includes over 84 km of coastline. The ability to quantify sediment volume changes contributes to the scientific understanding of the role El Ni&ntilde;o storms play in the OLC sand budget. This study provides a method to analyze LiDAR data to evaluate coastal geomorphologic changes over time. Additionally, identifying specific areas of coastal beach erosion associated with historical El Ni&ntilde;o events can aid beach managers, planners, and scientists in protecting the valuable coastline. LiDAR datasets were prepared and formatted which included ground classifying millions of elevation points. Formatted datasets were inputted into an Empirical Bayesian Kriging (EBK) model, creating high-resolution, 1-meter grid cell, Digital Elevation Models (DEMs). The EBK model also incorporated uncertainty into the workflow by producing prediction error surfaces. LiDAR-derived DEMs were used to calculate sediment volume changes through a technique called DEM differencing. Results were visualized through a series of maps and tables. Overall results show that there was a higher rate of beach sediment erosion during the 2006-2007 El Ni&ntilde;o winter than the 2007-2008 La Ni&ntilde;a winter. Sediment accretion was evident during the intermediary Summer of 2007. Future applications of this study include incorporating bathymetric datasets to understand near-shore sediment transport, evaluating sediment contribution through cliff erosion, and conducting decadal scale studies to evaluate long-term trends with sea level rise scenarios. </p>

The Qadimah Fault has been mapped as a normal fault running through the middle of a planned $$$50 billion city. For this reason, there is an urgent need to evaluate the seismic hazard that the fault poses to the new development. Although several geophysical studies have supported the existence of a fault, the driving mechanism remains unclear. While a fault controlled by gravity gliding of the overburden on a mobile salt layer is unlikely to be of concern to the city, one caused by the continued extension of a normal rotational fault due to Red Sea rifting could result in a major earthquake. A number of geomorphology and geodetic techniques were used to better understand the fault. An analysis of topographic data revealed a sharp discontinuity in slope aspect and hanging wall tilting which strongly supports the existence of a normal fault. A GPS survey of an emergent reef platform which revealed a tilted coral surface also indicates that deformation has occurred in the region. An interferometric synthetic aperture radar investigation has also been performed to establish whether active deformation is occurring on the fault. Ground movements that could be consistent with inter-seismic strain accumulation have been observed, although the analysis is restricted by the limited data available. However, a simple fault model suggests that the deformation is unlikely due to continued crustal stretching. This, in addition to the lack of footwall uplift in the topography data, suggests that the fault is more likely controlled by a shallow salt layer. However, more work will need to be done in the future to confirm these findings.

Accurate and replicable measurements of changes to land cover from drought conditions are essential for monitoring ecosystem disturbances. Techniques designed to measure land cover changes have been developed using data from remote sensing but with variable success. In my three study areas of southeastern parts of the American State of Texas, the change vector analysis (CVA) technique was tested on remote sensing data captured by the Landsat TM sensor taken in the years 2009, 2010, and 2011. This study monitors land use/land cover (LULC) changes due to the extreme Texas drought of 2011; the worst single year drought ever recorded in the state. The Landsat data are converted to vegetation indices; the normalized difference vegetation index (NDVI), bare soil index (BI), normalized difference moisture index (NDMI), as well as Tasseled Cap Transformations (TCT) brightness, greenness and wetness. CVA was used to determine the intensity of change (magnitude) and the type of changes that occurred (direction) between the multi-temporal data. This represents a new and improved method for calculating the direction component. Additionally, the relationship between NDVI and NDMI and between TCT variables and their application in CVA are further explored. The results show that land cover changes occurred due to an increase in precipitation in 2010 as well as considerable decrease of precipitation in 2011 resulting in the devastating drought. Validation procedures show that the CVA method was effective in capturing both magnitude of change and type of change that occurred. The remote sensing approach to monitoring drought-induced land cover changes is systematic, replicable and globally available at any time. Such a reliable methodology is essential for measuring ecosystem threats and human population vulnerability. / A Dissertation submitted to the Department of Geography in partial fulfillment of the Doctor of Philosophy. / Spring Semester 2017. / March 31, 2017. / Change vector analysis, Drought, Landsat, Remote sensing / Includes bibliographical references. / Victor Mesev, Professor Directing Dissertation; Xiuwen Liu, University Representative; Stephanie Pau, Committee Member; Xiaojun Yang, Committee Member.

The simulation of overland flow accumulation is critical for drainage network extraction, soil moisture monitoring, and hydrological modeling, etc. A variety of flow accumulation algorithms have been developed, but the complex and variable terrain has undermined their predictive accuracy. In my dissertation, a new flow accumulation algorithm (SAPC) is proposed that applies different flow distribution schemes to divergent and convergent flow scenarios with respect to slope, aspect, and plan curvature. Flow accumulation for the divergent scenario is slope-driven in the sense that flow distributed to the downslope neighboring cells is proportional to the slope values, and the weight of slope varies with plan curvature, making the SAPC algorithm adaptable to the variation of terrain surface. For the convergent scenario, flow accumulation is determined by aspect and all the water in the center cell is distributed in the same direction in two dimensions. Comparisons between the SAPC algorithm and the other algorithms show that flow accumulations estimated by the SAPC algorithm are closer to the true values for artificial surfaces, and the generated flow pathways are more balanced and smoother without serious artifacts for natural terrain surfaces. The SAPC algorithm is further integrated into the WetSpa Extension model to simulate hydrological responses at the outlet of the Bull Creek watershed for the 100-year tropical storm Hermine occurring in September 2010. The WetSpa Extension model provides both the semi-distributed and the fully-distributed modeling options. The fully-distributed WetSpa Extension model predicts a higher amount of surface runoff and thus the peak flow approaches more to the observed value than that predicted by the semi-distributed model. Flow accumulation is an important spatial parameter involved in hydrological modeling, and specifically it affects flow routing. Incorporating the SAPC algorithm into the WetSpa Extension model helps to obtain a hydrograph that aligns closer to the observed high flow region and more importantly, the model is able to provide the correct time to peak, otherwise there is half an hour of delay in the time to peak when SAPC algorithm is not used. Statistics demonstrate that the SAPC algorithm enables the WetSpa Extension model to be less biased, more confident and efficient. The significance of this dissertation lies in its provision of the possible ways to enhance the adaptability of flow accumulation algorithm to the varying terrain surfaces, and to improve hydrological modeling results through the more accurate and reliable flow accumulation predictions. This interdisciplinary study, which involves terrain analysis, hydrological modeling, and geographic information science (GIS), stresses the importance of location in describing physical features and processes that is usually the focus of geographical investigation. / A Dissertation submitted to the Department of Geography in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2019. / March 29, 2019. / Distributed hydrological modeling, Flow accumulation algorithm, Geographic information science, Python, WetSpa Extension model / Includes bibliographical references. / Victor Mesev, Professor Directing Dissertation; Christopher J. Coutts, University Representative; Xiaojun Yang, Committee Member; Tingting Zhao, Committee Member.

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