Aufgrund seiner nahezu kontinuierlichen eruptiven Aktivität zählt der Merapi zu den gefährlichsten Vulkanen der Welt. Der Merapi befindet sich im Zentralteil der dicht bevölkerten Insel Java (Indonesien). Selbst kleinere Ausbrüche des Merapi stellen deswegen eine große Gefahr für die ansässige Bevölkerung in der Umgebung des Vulkans dar. Die am Merapi beobachtete enge Korrelation zwischen seismischer und vulkanischer Aktivität erlaubt es, mit Hilfe der Überwachung der seismischen Aktivität Veränderungen des Aktivitätszustandes des Merapi zu erkennen. Ein System zur automatischen Detektion und Klassifizierung seismischer Ereignisse liefert einen wichtigen Beitrag für die schnelle Analyse der seismischen Aktivität. Im Falle eines bevorstehenden Ausbruchszyklus bedeutet dies ein wichtiges Hilfsmittel für die vor Ort ansässigen Wissenschaftler.<br /> In der vorliegenden Arbeit wird ein Mustererkennungsverfahren verwendet, um die Detektion und Klassifizierung seismischer Signale vulkanischen Urprunges aus den kontinuierlich aufgezeichneten Daten in Echtzeit zu bewerkstelligen. Der hier verwendete A nsatz der hidden Markov Modelle (HMM) wird motiviert durch die große Ähnlichkeit von seismischen Signalen vulkanischen Ursprunges und Sprachaufzeichnungen und den großen Erfolg, den HMM-basierte Erkennungssysteme in der automatischen Spracherkennung erlangt haben. <br /> Für eine erfolgreiche Implementierung eines Mustererkennungssytems ist es notwendig, eine geeignete Parametrisierung der Rohdaten vorzunehmen. Basierend auf den Erfahrungswerten seismologischer Observatorien wird ein Vorgehen zur Parametrisierung des seismischen Wellenfeldes auf Grundlage von robusten Analyseverfahren vorgeschlagen. Die Wellenfeldparameter werden pro Zeitschritt in einen reell-wertigen Mustervektor zusammengefasst. Die aus diesen Mustervektoren gebildete Zeitreihe ist dann Gegenstand des HMM-basierten Erkennungssystems. Um diskrete hidden Markov Modelle (DHMM) verwenden zu können, werden die Mustervektoren durch eine lineare Transformation und nachgeschaltete Vektor Quantisierung in eine diskrete Symbolsequenz überführt. Als Klassifikator kommt eine Maximum-Likelihood Testfunktion zwischen dieser Sequenz und den, in einem überwachten Lernverfahren trainierten, DHMMs zum Einsatz.<br /> Die am Merapi kontinuierlich aufgezeichneten seismischen Daten im Zeitraum vom 01.07. und 05.07.1998 sind besonders für einen Test dieses Klassifikationssystems geeignet. In dieser Zeit zeigte der Merapi einen rapiden Anstieg der Seismizität kurz bevor dem Auftreten zweier Eruptionen am 10.07. und 19.07.1998. Drei der bekannten, vom Vulkanologischen Dienst in Indonesien beschriebenen, seimischen Signalklassen konnten in diesem Zeitraum beobachtet werden. Es handelt sich hierbei um flache vulkanisch-tektonische Beben (VTB, h < 2.5 km), um sogenannte MP-Ereignisse, die in direktem Zusammenhang mit dem Wachstum des aktiven Lavadoms gebracht werden, und um seismische Ereignisse, die durch Gesteinslawinen erzeugt werden (lokaler Name: Guguran).<br /> Die spezielle Geometrie des digitalen seismischen Netzwerkes am Merapi besteht aus einer Kombination von drei Mini-Arrays an den Flanken des Merapi. Für die Parametrisierung des Wellenfeldes werden deswegen seismische Array-Verfahren eingesetzt. Die individuellen Wellenfeld Parameter wurden hinsichtlich ihrer Relevanz für den Klassifikationsprozess detailliert analysiert. Für jede der drei Signalklassen wurde ein Satz von DHMMs trainiert. Zusätzlich wurden als Ausschlussklassen noch zwei Gruppen von Noise-Modellen unterschieden.<br /> Insgesamt konnte mit diesem Ansatz eine Erkennungsrate von 67 % erreicht werden. Im Mittel erzeugte das automatische Klassifizierungssystem 41 Fehlalarme pro Tag und Klasse. Die Güte der Klassifikationsergebnisse zeigt starke Variationen zwischen den individuellen Signalklassen. Flache vulkanisch-tektonische Beben (VTB) zeigen sehr ausgeprägte Wellenfeldeigenschaften und, zumindest im untersuchten Zeitraum, sehr stabile Zeitmuster der individuellen Wellenfeldparameter. Das DHMM-basierte Klassifizierungssystem erlaubte für diesen Ereignistyp nahezu 89% richtige Entscheidungen und erzeugte im Mittel 2 Fehlalarme pro Tag.<br /> Ereignisse der Klassen MP und Guguran sind mit dem automatischen System schwieriger zu erkennen. 64% aller MP-Ereignisse und 74% aller Guguran-Ereignisse wurden korrekt erkannt. Im Mittel kam es bei MP-Ereignissen zu 87 Fehlalarmen und bei Guguran Ereignissen zu 33 Fehlalarmen pro Tag. Eine Vielzahl der Fehlalarme und nicht detektierten Ereignisse entstehen jedoch durch eine Verwechslung dieser beiden Signalklassen im automatischen Erkennnungsprozess. Dieses Ergebnis konnte aufgrund der ähnlichen Wellenfeldeigenschaften beider Signalklassen erklärt werden, deren Ursache vermutlich in den bekannt starken Einflüssen des Mediums entlang des Wellenausbreitungsweges in vulkanischen Gebieten liegen. <br /> Insgesamt ist die Erkennungsleistung des entwickelten automatischen Klassifizierungssystems als sehr vielversprechend einzustufen. Im Gegensatz zu Standardverfahren, bei denen in der Seismologie üblicherweise nur der Startzeitpunkt eines seismischen Ereignisses detektiert wird, werden in dem untersuchten Verfahren seismische Ereignisse in ihrer Gesamtheit erfasst und zudem im selben Schritt bereits klassifiziert. / Merapi volcano is one of the most active and dangerous volcanoes of the earth. Located in central part of Java island (Indonesia), even a moderate eruption of Merapi poses a high risk to the highly populated area. Due to the close relationship between the volcanic unrest and the occurrence of seismic events at Mt. Merapi, the monitoring of Merapi's seismicity plays an important role for recognizing major changes in the volcanic activity. An automatic seismic event detection and classification system, which is capable to characterize the actual seismic activity in near real-time, is an important tool which allows the scientists in charge to take immediate decisions during a volcanic crisis. <br /> In order to accomplish the task of detecting and classifying volcano-seismic signals automatically in the continuous data streams, a pattern recognition approach has been used. It is based on the method of hidden Markov models (HMM), a technique, which has proven to provide high recognition rates at high confidence levels in classification tasks of similar complexity (e.g. speech recognition). Any pattern recognition system relies on the appropriate representation of the input data in order to allow a reasonable class-decision by means of a mathematical test function. Based on the experiences from seismological observatory practice, a parametrization scheme of the seismic waveform data is derived using robust seismological analysis techniques. The wavefield parameters are summarized into a real-valued feature vector per time step. The time series of this feature vector build the basis for the HMM-based classification system. In order to make use of discrete hidden Markov (DHMM) techniques, the feature vectors are further processed by applying a de-correlating and prewhitening transformation and additional vector quantization. The seismic wavefield is finally represented as a discrete symbol sequence with a finite alphabet. This sequence is subject to a maximum likelihood test against the discrete hidden Markov models, learned from a representative set of training sequences for each seismic event type of interest.<br /> A time period from July, 1st to July, 5th, 1998 of rapidly increasing seismic activity prior to the eruptive cycle between July, 10th and July, 19th, 1998 at Merapi volcano is selected for evaluating the performance of this classification approach. Three distinct types of seismic events according to the established classification scheme of the Volcanological Survey of Indonesia (VSI) have been observed during this time period. Shallow volcano-tectonic events VTB (h < 2.5 km), very shallow dome-growth related seismic events MP (h < 1 km) and seismic signals connected to rockfall activity originating from the active lava dome, termed Guguran.<br /> The special configuration of the digital seismic station network at Merapi volcano, a combination of small-aperture array deployments surrounding Merapi's summit region, allows the use of array methods to parametrize the continuously recorded seismic wavefield. The individual signal parameters are analyzed to determine their relevance for the discrimination of seismic event classes. For each of the three observed event types a set of DHMMs has been trained using a selected set of seismic events with varying signal to noise ratios and signal durations. Additionally, two sets of discrete hidden Markov models have been derived for the seismic noise, incorporating the fact, that the wavefield properties of the ambient vibrations differ considerably during working hours and night time. <br /> A total recognition accuracy of 67% is obtained. The mean false alarm (FA) rate can be given by 41 FA/class/day. However, variations in the recognition capabilities for the individual seismic event classes are significant. Shallow volcano-tectonic signals (VTB) show very distinct wavefield properties and (at least in the selected time period) a stable time pattern of wavefield attributes. The DHMM-based classification performs therefore best for VTB-type events, with almost 89% recognition accuracy and 2 FA/day. <br /> Seismic signals of the MP- and Guguran-classes are more difficult to detect and classify. Around 64% of MP-events and 74% of Guguran signals are recognized correctly. The average false alarm rate for MP-events is 87 FA/day, whereas for Guguran signals 33 FA/day are obtained. However, the majority of missed events and false alarms for both MP and Guguran events are due to confusion errors between these two event classes in the recognition process. <br /> The confusion of MP and Guguran events is interpreted as being a consequence of the selected parametrization approach for the continuous seismic data streams. The observed patterns of the analyzed wavefield attributes for MP and Guguran events show a significant amount of similarity, thus providing not sufficient discriminative information for the numerical classification. The similarity of wavefield parameters obtained for seismic events of MP and Guguran type reflect the commonly observed dominance of path effects on the seismic wave propagation in volcanic environments.<br /> The recognition rates obtained for the five-day period of increasing seismicity show, that the presented DHMM-based automatic classification system is a promising approach for the difficult task of classifying volcano-seismic signals. Compared to standard signal detection algorithms, the most significant advantage of the discussed technique is, that the entire seismogram is detected and classified in a single step.

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeterscale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a datascarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Knowledge of the provenance of crustal volatiles and the processes by which they are released is extremely important for the dynamics of magmatic systems. Presented here are the results of multiple investigations, which aim to understand magmatic volatile contamination from contrasting but complementary perspectives. The main methodologies used include He and C isotope values and CO2/3He ratios of volcanic gases and fluids; simulation of magma-carbonate interaction using high-pressure high-temperature experimental petrology; X-ray microtomography of vesiculated xenoliths and computer modeling. Findings show that the contribution from upper crustal volatiles can be substantial, and is dependant on the upper crustal lithology on which a volcano lies, as well as the composition of the magma supplied. Carbonate dissolution in particular is strongly controlled by the viscosity of the host magma. The details of the breakdown of vesiculated xenoliths is complex but has wide reaching implications, ranging from the dissemination of crustally derived materials through a magma body to highlighting that crustal volatiles are largely unaccounted for in both individual volcano and global volatile budgets. In synthesizing the conclusions from each of the individual perspectives presented, I propose the contribution of volatiles from crustal sources to play a significant role in many geological systems. This volatile component should be taken into consideration in future research efforts.

Volcanic ash, pumice and Moringa oleifera (M. oleifera) were investigated as indigenous materials for removal of natural organic matter (NOM) at Kampala and Masaka water treatment plants in Uganda. Coagulation and filtration experiments were done using raw water at Kampala (Ggaba) and Masaka (Boma) National Water &amp; Sewerage Corporation water treatment plants. Assessment of the two plants was done and they were found to be faced with differing challenges given the nature of their raw water sources. Therefore, the study was conducted to seek appropriate treatment processes that suite the conditions at the respective plant and avoid or minimize formation of unwanted chlorination by-products. The results from the study indicated that there were both operational and design handicaps at the Ggaba treatment plant with a need to modify the filtration and clarification units. At Masaka, pre-chlorination led to increases in total trihalomethanes as high as 4000%. The characterization studies indicated the major fraction of NOM to be hydrophilic and there was no variation in the character of NOM along the unit treatment processes investigated. On the other hand experiments conducted at both the pilot and laboratory scale gave promising results. Simple horizontal flow roughing filter at Masaka gave rise to dissolved organic carbon (DOC) and ferrous iron removals of 27% and 89% respectively. With a combined use of pumice and hydrogen peroxide in the filter, DOC removals of up to 68% were achieved. The results from jar test experiments also indicated that use of alum with M. oleifera coagulant extracted with sodium chloride solution as coagulant aid is promising as a first stage in the treatment train for waters with a humic materials and high content of iron, typical of swamp water sources. Therefore the findings show that it is possible to avoid the formation of unwanted by-products by application of roughing filtration with hydrogen peroxide in place of the pre-chlorination process. Assessment of the characteristics of the volcanic ash showed that it meets the requirements for a filtration material; and results obtained from the pilot study showed that it was a suitable alternative material for use in a dual media filtration system. There was an increase in the filter run length of about two and half fold in the dual media filtration column compared to the mono medium column. / Vulkanaska, pimpsten och Moringa oleifera (M. oleifera) undersöktes som inhemska material for borttagande av naturligt organiskt material (NOM) i Kampala och Masaka reningsverk i Uganda. Koagulation och filtreringsexperiment gjordes med hjalp av råvatten i Kampala (Ggaba) och Masaka (Boma)reningsverk, som ingår i Nationella Vatten- och avloppsreningsverk, ett företag i Uganda. En bedömning av de två anläggningarna gjordes och det visade sig stå inför olika utmaningar på grund av de olika råvattnens karaktär. Den här studien genomfördes för att söka lämpliga processer för behandling av anpassade till förhållandena vid respektive anläggning samt för att undvika eller minimera uppkomsten av olika klorerade biprodukter. Resultatet från studien visade att det fanns problem både när det gäller design och arbetsrutiner på reningsverket Ggaba med ett behov att ändra filtrerings- och klarningsenheternaI Masaka ökade förkloreringsprocessen den totala mängden trihalometaner med 4000 %. Karakteriseringen av naturligt organiskt material (NOM) visade på en stor andel hydrofilt material och att ingen förändring av det organiska materialets karaktär skedde längs den undersökta processenheten. Å andra sidan visade både laboratorieförsök och experiment i pilotanläggningen att lovande resultat. Ett enkelt horisontellt flöde genom ett grovt filter i pilotanläggningen i Masaka resulterade i 89% mindre järn och 27% mindre NOM. Med en kombination av pimpsten och väteperoxid i filtret var avlägsnandet av löst organiskt material(DOC) från vattnet 68%. Resultaten från batchexperiment (jar test) i laboratoriet visade också lovande resultat för aluminium tillsammans med en koagulant extraherad med natriumklorid från Moringa oleifera (MOC-SC), som ett första steg för vatten från sumpmark med höga halter av järn och organiskt material. Således visar resultaten att det går att undvika bildandet av höga halter av trihalometan (THM) genom genom tillämpning av grovfitrering med väteperoxid i stället för förkloreringsprocessen. Utvärderingen av vulkanaskans egenskaper visade att vulkanaskan uppfyller kraven på ett filtermaterial och resultaten från pilotanläggningen visade att det är ett lämpligt material i ett filtreringssystem med två media. Den utnyttjade delen av filtret var 2,5 gånger längre i körningen med dubbla medier jämfört med ett medium. / <p>QC 20120910</p> / MAKERERE – Sida/SAREC RESEARCH COLLABORATION

Certain alteration minerals are used to identify the hydrothermally altered rocks. Potassic, phyllic (sericitic), propylitic, argillic and silicification are main alteration types observed in volcanic rocks. The role of remote sensing in alteration mapping is the differentiation of the minerals that are unique for In this study, Landsat TM 5 images are used. General alteration trend in the area is mapped by conventional methods of color composite, band rationing, principal component analysis and multi-linear regression analysis. Detailed mineral mapping carried on by using the United States Geological Survey (USGS) spectral library data. Spectral reflectances of selected minerals are analyzed according to the TM band intervals and appropriate band ratios are selected. TM bands 1,2,3,4,5 and 7 are used. Outputs of mineral maps are investigated for zonal distribution. Mineral maps that are obtained by the mineral separation method reveal that the youngest volcanic complex Hasandag is poorly altered. Instead, Ke&ccedil / iboyduran, Melendiz and Tepek&ouml / y volcanic complexes are found to be highly altered with the pattern of clay dominant in the center and increasing oxidation towards flanks. Also the alteration along the previously mapped buried faults is a proof that the method can provide information about the alteration source.

The purpose of this study is to understand the geological, petrographical, mineralogical and geochemical characteristics of analcime-bearing tuffs in the Biga Peninsula and to determine formation process of these tuffs. The study area lies between Ayvacik and K&uuml / &ccedil / &uuml / kkuyu. The rock units are pre-Eocene basement rocks, Miocene Behram Volcanics (Arikli Tuff, andesite, andesitic agglomerate), Pliocene volcanics, Miocene lacustrine sediments (K&uuml / &ccedil / &uuml / kkuyu Formation) and Quaternary alluvium. Analcimes which are found in Arikli Tuff are the main objective of this study. Detailed petrographical, mineralogical and geochemical studies were caried out on the Arikli Tuff samples by using petrographical microscope, X-ray diffractometry, scanning electron microscopy, diffrential thermal analyses inductively coupled plasma &amp / #8211 / mass spectrometry and optical emission spectrometry. Fine-grained and coarse-grained analcime crystals in Arikli Tuff were determined by their colorless, isotropic, trapezohedral and low relief. In addition to petrographic study, SEM and XRD methods also confirmed the presence of analcime. Two modes of occurrences were determined by the petrographical and mineralogical studies / coarse-grained euhedral or anhedral crystals in cavities and pumice fragments and single crystals or clusters of fine-grained analcimes embedded in the matrix. It was stated that there are two types of formation of analcime / alteration of volcanic glass and precipitation from alkaline solution based on petrographical and SEM studies. Geochemical methods, moreover, support the formation types.

Deep non-volcanic tremor is a newly discovered seismic phenomenon with low amplitude, long duration, and no clear P- and S-waves as compared with regular earthquake. Tremor has been observed at many major plate-boundary faults, providing new information about fault slip behaviors below the seismogenic zone. While tremor mostly occurs spontaneously (ambient tremor) or during episodic slow- slip events (SSEs), sometimes tremor can also be triggered during teleseismic waves of distance earthquakes, which is known as "triggered tremor". The primary focus of my Ph.D. work is to understand the physical mechanisms and necessary conditions of triggered tremor by systematic investigations in different tectonic regions. These include Taiwan, California, southwest Japan, Alaska and the Aleutian Arc, Cascadia, and New Zealand. In the first chapter of my dissertation, I conduct a systematic survey of triggered tremor beneath the Central Range (CR) in Taiwan for 45 teleseismic earthquakes from 1998 to 2009 with Mw ≥ 7.5. Triggered tremors are visually identified as bursts of high-frequency (2-8 Hz), non-impulsive, and long-duration seismic energy that are coherent among many seismic stations and modulated by the teleseismic surface waves. A total of 9 teleseismic earthquakes has triggered clear tremor in Taiwan. The peak ground velocity (PGV) of teleseismic surface waves is the most important factor in determining tremor triggering potential, with an apparent threshold of ~0.1 cm/s, or 7-8 kPa. However, such threshold is partially controlled by the background noise level, preventing triggered tremor with weaker amplitude from being observed. In addition, I find a positive correlation between the PGV and the triggered tremor amplitude, which is consistent with the prediction of the 'clock-advance' model. This suggests that triggered tremor can be considered as a sped-up occurrence of ambient tremor under fast loading from the passing surface waves. Finally, the incident angles of surface waves also play an important rule in controlling the tremor triggering potential. The next chapter focuses on a systematic comparison of triggered tremor around the Calaveras Fault (CF) in northern California (NC), the Parkfield-Cholame section of the San Andreas Fault (SAF) in central California (CC), and the San Jacinto Fault (SJF) in southern California (SC). Out of 42 large (Mw ≥7.5) earthquakes between 2001 and 2010, only the 2002 Mw 7.9 Denali fault earthquake triggered clear tremor in NC and SC. In comparison, abundant triggered and ambient tremor has been observed in CC. Further analysis reveal that the lack of triggered tremor observations in SC and NC is not simply a consequence of their different background noise levels as compared to CC, but rather reflects different background tremor rates in these regions. In the final chapter, I systematically search for triggered tremor following the 2011 Mw9.0 Tohoku-Oki earthquake in the regions where ambient or triggered tremor has been found before. The main purpose is to check whether triggered tremor is observed in regions when certain conditions (e.g., surface wave amplitudes) are met. Triggered tremor is observed in southwest Japan, Taiwan, the Aleutian Arc, south-central Alaska, northern Vancouver Island, the Parkfield-Cholame section of the SAF in CC and the SJF in SC, and the North Island of New Zealand. Such a widespread triggering of tremor is not too surprising because of the large amplitude surface waves (minimum peak value of ~0.1 cm/s) and the associated dynamic stresses (at least ~7-8 kPa), which is one of the most important factors in controlling the triggering threshold. The triggered tremor in different region is located close to or nearby the ambient tremor active area. In addition, the amplitudes of triggered tremor have positive correlations with the amplitudes of teleseismic surface waves among many regions. Moreover, both Love and Rayleigh waves participate in triggering tremor in different regions, and their triggering potential is somewhat controlled by the incident angles. In summary, systematically surveys of triggered tremor in different tectonic regions reveal that triggered tremor shares similar physical mechanism (shear failure on the fault interface) as ambient tremor but with different loading conditions. The amplitude of the teleseismic surface wave is one of the most important factors in controlling the tremor triggering threshold. In addition, the frequency contents and incident angles of the triggering waves, and local fault geometry and ambient conditions also play certain roles in determining the triggering potential. On the other hand, the background noise level and seismic network coverage and station quality also could affect the apparent triggering threshold. Because triggered tremor occurs almost instantaneously during the teleseismic surface waves, and the tremor amplitude is somewhat controlled by the amplitude of the triggering waves, the occurrence time and the size of the triggered tremor could be somewhat predictable, so long as we know the amplitude and period of surface waves and associated time-varying dynamic stresses. Hence, further analysis of triggered tremor may provide important new clues on the nucleation and predictability of seismic events.

Models of tephra fallout are used to assess volcanic hazards in advance of eruptions and in near-real-time. Current models often approximate the wind field using simplistic assumptions of the atmosphere that cannot account for typical variations in wind velocity that occur in time and three-dimensional space. Here, a widely used mesoscale atmospheric model is used to improve forecasts of the location of the major axis of dispersion for erupting plumes. The Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) specializes in atmospheric prediction for regions on the order of ten to hundreds of kilometers on a side. MM5 generates realistic wind fields based on the laws of conservation of mass, energy, and momentum, along with land surface data and atmospheric forecasts and observations.

The thinning trend of a low-aspect ratio ignimbrite (LARI) in a direction of increasing topographic relief at the Pululagua Volcanic Complex, Ecuador, is established by correlating continuous ground penetrating radar (GPR) profiles and radar reflector behavior with stratigraphic measurements and unit behavior. Minimum density-current and vertical (cross-sectional) velocity analyses of the LARIs parent pyroclastic density-current are performed by analyzing the exchange of kinetic energy for potential energy in an upslope direction. Continuous GPR profiles were acquired in a direction of increasing topographic relief with the intent of identifying the LARI within the GPR record and examining the relationships between the LARI and the underlying paleo-topographical surface. Stratigraphic measurements recorded throughout the field area demonstrate that the LARI thins 7.5 m in an upslope direction (over 480 m distance and 95 m elevation). Stratigraphic measurements enable correlations with GPR profiles, resulting in LARI identification. By utilizing GPR derived paleo-topographical surface elevations, minimum flow velocities of the LARI-producing parent pyroclastic density-current at the base of upslope flow are shown to be at least 25 m/s. Vertical velocity analyses based on the identification of internal GPR reflectors, interpreted as flow streamlines, yield pyroclastic surge-like cross-sectional velocity profiles of the LARIs parent density-current. Maximum density-current velocities at the base of upslope flow reach 24 m/s and diminish toward the base of the current.

Masaya volcano, Nicaragua, has been the site of tremendous Plinian basaltic eruptions. Two eruptions ~6,500 and 2,250 BP formed the 6 kilometer (km) x 11 km, northwest trending Masaya caldera. The present day active Santiago Crater within the caldera is the site of persistent volcano degassing and occasional phreatic explosions. While the mechanism responsible for these phreatic explosions is unclear, one possible explanation is the interaction of groundwater with the shallow magma chamber beneath Masaya. This interaction with meteoric water is supported by the substantial steam discharge from the vent, which is significantly larger than other similar volcanoes in the world. To better understand these interactions, the distribution of groundwater was characterized for the volcano based on interpretation of 29 Transient Electromagnetic (TEM) soundings. The TEM data were modeled using two independent methods to estimate resistivity as a function of depth. Results from modeling the TEM data indicate an overlying highly resistive layer throughout the caldera that is underlain by one or more conductive layers. The implied water table of the caldera is expressed as a subdued replica of the topography in the higher vent regions in the central and southern portions of the caldera and decreases to a level that coincides with the elevation Lake Masaya in the lower sections of the caldera. The water table elevation in the caldera also shows a marked difference from the regional groundwater flow system as there is a large gradient in head values suggesting a sharp change in transmissivity along the caldera boundaries, which indicate the caldera is hydraulically isolated from the surrounding region. In order to better understand the hydrologic processes at Masaya caldera, a 3-D finite difference groundwater model was created using the 29 estimated water levels and two groundwater flux measurements to simulate the hydrologic system The model calibration revealed that a deep, highly permeable layer must feed the active vent in order for the steam emissions to be maintained at their current levels. This information about the caldera provides a baseline for forecasting the response of this isolated groundwater system to future changes in magmatic activity.