FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

Dynamic modeling, simulation and control design of a parafoil-payload system for ship launched aerial delivery system (SLADS)

The objective of this research was to develop a high-fidelity dynamic model of a parafoilpayload system with respect to its application for the Ship Launched Aerial Delivery System (SLADS). SLADS is a concept in which cargo can be transfered from ship to shore using a parafoil-payload system. It is accomplished in two phases: An initial towing phase when the glider follows the towing vessel in a passive lift mode and an autonomous gliding phase when the system is guided to the desired point. While many previous researchers have analyzed the parafoil-payload system when it is released from another airborne vehicle, limited work has been done in the area of towing up the system from ground or sea. One of the main contributions of this research was the development of a nonlinear dynamic model of a towed parafoil-payload system. After performing an extensive literature review of the existing methods of modeling a parafoil-payload system, a five degree-of-freedom model was developed. The inertial and geometric properties of the system were investigated to predict accurate results in the simulation environment. Since extensive research has been done in determining the aerodynamic characteristics of a paraglider, an existing aerodynamic model was chosen to incorporate the effects of air flow around the flexible paraglider wing. During the towing phase, it is essential that the parafoil-payload system follow the line of the towing vessel path to prevent an unstable flight condition called ‘lockout’. A detailed study of the causes of lockout, its mathematical representation and the flight conditions and the parameters related to lockout, constitute another contribution of this work. A linearized model of the parafoil-payload system was developed and used to analyze the stability of the system about equilibrium conditions. The relationship between the control surface inputs and the stability was investigated. In addition to stability of flight, one more important objective of SLADS is to tow up the parafoil-payload system as fast as possible. The tension in the tow cable is directly proportional to the rate of ascent of the parafoil-payload system. Lockout instability is more favorable when tow tensions are large. Thus there is a tradeoff between susceptibility to lockout and rapid deployment. Control strategies were also developed for optimal tow up and to maintain stability in the event of disturbances.

Composing in words and images : a proposal for a tandem approach to written and visual composition pedagogy

This project proposes a module for teaching visual composition within the context of a written composition course. Drawing from process writing theory, critical pedagogy, and photo-elicitation, “Composing In Words And Images” gives composition teachers a module and direct instruction for the incorporation of critical visual composition studies in their writing classes.

Lava discharge rate estimates from thermal infrared satellite data at Pacaya Volcano, Guatemala

Time-averaged discharge rates (TADR) were calculated for five lava flows at Pacaya Volcano (Guatemala), using an adapted version of a previously developed satellite-based model. Imagery acquired during periods of effusive activity between the years 2000 and 2010 were obtained from two sensors of differing temporal and spatial resolutions; the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellites (GOES) Imager. A total of 2873 MODIS and 2642 GOES images were searched manually for volcanic “hot spots”. It was found that MODIS imagery, with superior spatial resolution, produced better results than GOES imagery, so only MODIS data were used for quantitative analyses. Spectral radiances were transformed into TADR via two methods; first, by best-fitting some of the parameters (i.e. density, vesicularity, crystal content, temperature change) of the TADR estimation model to match flow volumes previously estimated from ground surveys and aerial photographs, and second by measuring those parameters from lava samples to make independent estimates. A relatively stable relationship was defined using the second method, which suggests the possibility of estimating lava discharge rates in near-real-time during future volcanic crises at Pacaya.

Ultraviolet digital imaging of volcanic plumes : implementation and application to magmatic processes at basaltic volcanoes

Magmatic volatiles play a crucial role in volcanism, from magma production at depth to generation of seismic phenomena to control of eruption style. Accordingly, many models of volcano dynamics rely heavily on behavior of such volatiles. Yet measurements of emission rates of volcanic gases have historically been limited, which has restricted model verification to processes on the order of days or longer. UV cameras are a recent advancement in the field of remote sensing of volcanic SO2 emissions. They offer enhanced temporal and spatial resolution over previous measurement techniques, but need development before they can be widely adopted and achieve the promise of integration with other geophysical datasets. Large datasets require a means by which to quickly and efficiently use imagery to calculate emission rates. We present a suite of programs designed to semi-automatically determine emission rates of SO2 from series of UV images. Extraction of high temporal resolution SO2 emission rates via this software facilitates comparison of gas data to geophysical data for the purposes of evaluating models of volcanic activity and has already proven useful at several volcanoes. Integrated UV camera and seismic measurements recorded in January 2009 at Fuego volcano, Guatemala, provide new insight into the system’s shallow conduit processes. High temporal resolution SO2 data reveal patterns of SO2 emission rate relative to explosions and seismic tremor that indicate tremor and degassing share a common source process. Progressive decreases in emission rate appear to represent inhibition of gas loss from magma as a result of rheological stiffening in the upper conduit. Measurements of emission rate from two closely-spaced vents, made possible by the high spatial resolution of the camera, help constrain this model. UV camera measurements at Kilauea volcano, Hawaii, in May of 2010 captured two occurrences of lava filling and draining within the summit vent. Accompanying high lava stands were diminished SO2 emission rates, decreased seismic and infrasonic tremor, minor deflation, and slowed lava lake surface velocity. Incorporation of UV camera data into the multi-parameter dataset gives credence to the likelihood of shallow gas accumulation as the cause of such events.

Erupted magma volume estimates at Santiaguito and Pacaya Volcanoes, Guatemala using digital elevation models

High resolution digital elevation models (DEMs) of Santiaguito and Pacaya volcanoes, Guatemala, were used to estimate volume changes and eruption rates between 1954 and 2001. The DEMs were generated from contour maps and aerial photography, which were analyzed in ArcGIS 9.0®. Because both volcanoes were growing substantially over the five decade period, they provide a good data set for exploring effective methodology for estimating volume changes. The analysis shows that the Santiaguito dome complex grew by 0.78 ± 0.07 km3 (0.52 ± 0.05 m3 s-1) over the 1954-2001 period with nearly all the growth occurring on the El Brujo (1958-75) and Caliente domes (1971-2001). Adding information from field data prior to 1954, the total volume extruded from Santiaguito since 1922 is estimated at 1.48 ± 0.19 km3. Santiaguito’s growth rate is lower than most other volcanic domes, but it has been sustained over a much longer period and has undergone a change toward more exogenous and progressively slower extrusion with time. At Santiaguito some of the material being added at the dome is subsequently transported downstream by block and ash flows, mudflows and floods, creating channel shifting and areas of aggradation and erosion. At Pacaya volcano a total volume of 0.21 ± 0.05 km3 was erupted between 1961 and 2001 for an average extrusion rate of 0.17 ± 0.04 m3 s-1. Both the Santiaguito and Pacaya eruption rate estimates reported here are minima, because they do not include estimates of materials which are transported downslope after eruption and data on ashfall which may result in significant volumes of material spread over broad areas. Regular analysis of high resolution DEMs using the methods outlined here, would help quantify the effects of fluvial changes to downstream populated areas, as well as assist in tracking hazards related to dome collapse and eruption.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.