Browsing by Author "Moreno-Madriñán, Max Jacobo"
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Item How satellites can help control the spread of diseases such as Zika(The Conversation US, Inc., 2016-02-15) Moreno-Madriñán, Max Jacobo; Epidemiology, Richard M. Fairbanks School of Public HealthItem Improving Remote Sensing Algorithms Towards Inland Water Cyanobacterial Assessment From Space(2021-09) Ogashawara, Igor; Li, Lin; Moreno-Madriñán, Max Jacobo; Druschel, Gregory K.; Hwang, Taehee; Wang, LixinWater is an essential resource for life on Earth, and monitoring its quality is an important task for mankind. However, the amount of water quality data collected by the traditional method is insufficient for the conservation and sustainable management of this important resource. This challenge will be exacerbated by increasing harmful algal blooms at the global scale. To fill this gap, Earth Observations (EO) have been proposed to help stakeholders make their decisions, but the use of EO for monitoring inland water quality is still in development. In this context, the main objective of this study was to improve the estimation of cyanobacteria via remote sensing data. To achieve this goal, the water type classification was first used to identify the dominant optically active constituents within aquatic environments. This information is crucial for understanding the optical properties of inland waters and selecting the best remote sensing algorithm for specific optical water types. The next research question was to develop a universal structure for retrieval of the inherent optical properties of several important aquatic systems around the world, which can be used as a corner stone for developing a globally applicable remote sensing algorithm. The third research topic of this dissertation is about removing the interference of chlorophyll-a with the absorption strength at 620 nm where phycocyanin exhibits its diagnostic absorption so that the estimation of phycocyanin concentration can be improved. Despite the novelty of the proposed remote sensing algorithms which are able to accommodate distinct water optical properties, there are abundant opportunities for improving the parameterization of the proposed models to retrieve inland water quality and optical properties when a global database of optical and water quality measurements is available. Considering the current advancement in spaceborne technology and the existence of a coordinate effort for global calibration and validation of remote sensing algorithms for monitoring inland waters, there is a high potential for operational assessment of harmful cyanobacterial blooms using the remote sensing algorithms proposed in this dissertation.Item Origin and Fate of Odorous Metabolites, 2-Methylisoborneol and Geosmin, in a Eutrophic Reservoir(2019-06) Clercin, Nicolas André; Druschel, Gregory K.; Jacinthe, Pierre-André; Filippelli, Gabriel; Moreno-Madriñán, Max Jacobo; Janga, Sarath ChandraTaste-and-Odor (T&O) occurrences are a worldwide problem and can locally have extensive socio-economic impacts in contaminated waterbodies. Tracing odorous compounds in surface waters or controlling the growth of producing organisms is particularly challenging. These approaches require the understanding of complex interactions between broad climate heterogeneity, large-scale physical processes such basin hydrology, lake/reservoir circulation, responses of aquatic ecosystems and communities. Eagle Creek Reservoir (ECR), a eutrophic water body, located in central Indiana experiences annual odorous outbreaks of variable durations and intensities that can impair its water quality. Two major compounds, 2-methylisoborneol and geosmin, have been identified as the main culprits occurring seasonally when the reservoir receives high discharges and nutrient loads from its main tributaries. Under these conditions, the growth of T&O-producing bacteria tends to take over other phytoplanktic organisms. Discrete samples collected within the water column during severe outbreaks in 2013 revealed that some bacterioplankton members belonging to Actinobacteria (Streptomyces) and Cyanobacteria (Planktothrix) were involved in the generation of T&O compounds. Most of this production occurred in the upper layers of the water column where higher abundances of key enzymes from MIB and geosmin metabolic pathways were detected. Application of a copper-based algaecide to curb the biosynthesis of bacterial metabolites led to geosmin production (linked to Cyanobacteria) being quickly terminated, whereas MIB levels (linked to Actinobacteria) lingered for several weeks after the algaecide treatment. Significant chemical differences in the association of these metabolites were measured in ECR. Geosmin was dominantly found cell-bound and settling after cellular death increases susceptibility to biodegradation in bottom sediments. MIB was mostly found dissolved making it less susceptible to biodegradation in bottom sediments. Genetic data identified Novosphingobium hassiacum and Sphingomonas oligophenolica (α- Proteobacteria) as potential degraders of geosmin and, four Flavobacterium species (Bacteroidetes) as potential MIB degraders. The role of Eagle Creek natural sediments in the removal of bacterial metabolites via chemical adsorption was also tested but was not proven efficient. Bacterial breakdown activity was demonstrated to be the major loss mechanism of MIB and geosmin.Item Slope algorithm to map algal blooms in inland waters for Landsat 8/ Operational Land Imager images(SPIE, 2016-12) Ogashawara, Igor; Li, Lin; Moreno-Madriñán, Max Jacobo; Department of Environmental Health Science, School of Public HealthMonitoring algal blooms using traditional methods is expensive and labor intensive. The use of satellite technology can attenuate such limitations. A common problem associated with the application of such technology is the need to eliminate the effects of atmosphere, which can be, at least, a time-consuming task. Thus, a remote sensed algal bloom monitoring system needs a simple algorithm which is nonsensitive to atmospheric correction and that could be applied to small aquatic systems. A slope algorithm (SAred−NIR) was developed to detect and map the extension of algal blooms using the Landsat 8/Operational Land Imager. SAred−NIR was shown to have advantages over other commonly used indices to monitor algal blooms, such as normalized difference vegetation index (NDVI), normalized difference water index, and floating algae index. SAred−NIR was shown to be less sensitive to different atmospheric corrections, less sensitive to thin clouds, and less susceptible to confusion when classifying water and moderate bloom conditions. Based on ground truth data from Eagle Creek Reservoir, Indiana, SAred−NIR showed an accuracy of 88.46% while NDVI only showed a 46.15% accuracy. Finally, based on qualitative and quantitative results, SAred−NIR can be used as a tool to improve the governance of small size water resources.Item Water clarity response to climate warming and wetting of the Inner Mongolia-Xinjiang Plateau: A remote sensing approach(Elsevier, 2021-11) Zhang, Yibo; Shi, Kun; Zhang, Yunlin; Moreno-Madriñán, Max Jacobo; Xu, Xuan; Zhou, Yongqiang; Qin, Boqiang; Zhu, Guangwei; Jeppesen, Erik; Environmental Health Science, School of Public HealthWater clarity (generally quantified as the Secchi disk depth: SDD) is a key variable for assessing environmental changes in lakes. Using remote sensing we calculated and elucidated the SDD dynamics in lakes in the Inner Mongolia-Xinjiang Lake Zone (IMXL) from 1986 to 2018 in response to variations in temperature, rainfall, lake area, normalized difference vegetation index (NDVI) and Palmer's drought severity index (PDSI). The results showed that the lakes with high SDD values are primarily located in the Xinjiang region at longitudes of 75°–93° E. In contrast, the lakes in Inner Mongolia at longitudes of 93°–118° E generally have low SDD values. In total, 205 lakes show significant increasing SDD trends (P < 0.05), with a mean rate of 0.15 m per decade. In contrast, 75 lakes, most of which are located in Inner Mongolia, exhibited significant decreasing trends with a mean rate of 0.08 m per decade (P < 0.05). Pooled together, an overall increase is found with a mean rate of 0.14 m per decade. Multiple linear regression reveals that among the five variables selected to explain the variations in SDD, lake area accounts for the highest proportion of variance (25%), while temperature and rainfall account for 12% and 10%, respectively. In addition, rainfall accounts for 52% of the variation in humidity, 8% of the variation in lake area and 7% of the variation in NDVI. Temperature accounts for 27% of the variation in NDVI, 39% of the variation in lake area and 22% of the variation in PDSI. Warming and wetting conditions in IMXL thus promote the growth of vegetation and cause melting of glaciers and expansion of lake area, which eventually leads to improved water quality in the lakes in terms of higher SDD. In contrast, lakes facing more severe drought conditions, became more turbid.