Observing Short-Term Geomorphic Change in a Human-Modified River Using Terrestrial Repeat Photographs and Traditional Surveys: Uncompahgre River, Colorado, USA

The Uncompahgre River in Ouray, CO, was modified in 1996 from a braided river system to a meandering river channel. Large boulders of riprap were placed along designed meanders to prevent erosion and enable the development of permanent human structures on the flood plain. Deposition of gravel bars in the modified channel occurs annually during the summer. This gravel is "mined" by the City of Ouray; however, the effects of this excavation and the original modification were never assessed. This study provides an assessment by quantifying cross-sectional area change, cumulative grain-size distributions, shear stresses, slopes, and sinuosities using traditional survey methods. In addition, volume change of a gravel bar inside the modified channel was estimated using extreme oblique photographs (>45 degrees from nadir) that were obtained from nearby cliffs. Close-range photogrammetry was used in the natural channel downstream to evaluate photogrammetric methods using different lenses, image sensors, and camera geometries. Both traditional and photogrammetric methods clearly indicated significant deposition in the modified channel, whereas erosion occurred directly downstream from the modified channel, but did not occur at a reach 1.5 km downstream. In the natural channel, no cross-sectional area change occurred, grains were poorly sorted, and the longitudinal slope was ~four times steeper than the modified channel. Shear stress ratios were used as an erosion threshold, which did not correlate with actual cross-sectional area change, but a decrease in shear stress ratios from May 2011 to September 2011 were associated with erosion. Average RMSE values for DEMs created from extremeoblique photographs of a gravel bar in May 2011 and September 2011 were 0.140 m and 0.324 m, respectively. Using a DEM of difference with a t-statistic filter revealed that 115m3 of gravel was deposited. The Uncompahgre River showed similar geomorphic characteristics to other rivers in southwest Colorado, however, the slope of the natural and modified channels were much steeper than other rivers. Extreme-oblique photography and unconventional sensors both yielded reliable results, showing that these atypical techniques can be used in terrestrial photogrammetric applications such as, post-restoration assessments, as long as proper base-to-height ratios are achieved

Technical note: Ground-based remote sensing of a mountain stream: measuring stage and water width using a simple time-lapse camera.

Remote sensing applied to river monitoring adds complementary information useful for understanding the system behaviour. In this paper, we present a method for visual stage gauging and water surface width measurement using a ground-based time-lapse camera and a fully automatic image analysis algorithm for flow monitoring at a river cross section of a steep, bouldery channel. The remote stage measurement was coupled with a water level logger (pressure transducer) on site and shows that the image-based method gives a reliable estimate of the water height variation and daily flow record when validated against the pressure transducer (R = 0.91). From the remotely sensed pictures, we also extracted the water width and show that it is possible to correlate water surface width and stage. The images also provide valuable ancillary information for interpreting and understanding flow hydraulics and site weather conditions. This image-based gauging method is a reliable, informative and inexpensive alternative or adjunct to conventional stage measurement especially for remote sites

Applications of Time-lapse Imagery for Monitoring and Illustrating Ecological Dynamics in a Water-stressed System

Understanding and perceiving the natural world is a key part of management, policy, conservation, and inevitably for our future. Increased demand on natural resources has heightened the importance of documenting ecosystem changes, and knowledge-sharing to foster awareness. The advancement of digital technologies has improved the efficiency of passive monitoring, connectivity among systems, and expanded the potential for innovative and communicative approaches. From technological progression, time-lapse imagery has emerged a valuable tool to capture and depict natural systems. I sought to enhance our understanding of a water-stressed system by analyzing imagery, in addition to integrating images with data visualization to illustrate the complexity of a river basin in central Nebraska. Image analysis was used to quantify wetland water inundation and vegetation phenology. These measurements from visible changes were combined with less visible data from additional passive monitoring to examine the relationship between vegetation phenology and bat activity, as well as wetland inundation and water quality. Moreover, time-lapse data sequences were constructed by integrating time-lapse imagery with data visualization in an interactive digital framework to examine the applications for communicating social-ecological dynamics. Findings suggest vegetation phenology was differentially associated with seasonal bat activity, possibly related to migratory versus resident life history strategies. In regards to examining wetland hydrology, water inundation was found to be correlated with nitrate, dissolved oxygen, and DEA, and negatively correlated with water temperature, indicating the importance of understanding water levels. AEM-RDA analysis identified several significant temporal patterns occurring with the wetland as well as the river site. Similarities between river and wetland patterns were suggestive of regional conditions driving fluctuations, while discrepancies were indicative of structural, biological, and local differences within individual sites. In examining communicative applications, time-lapse data sequences depicted a range of ecological dynamics while linking visible and invisible occurrences. The framework shows potential to offer a tangible context with explanatory content to aid in understanding environmental changes that are often too subtle to see or beyond the temporal scale of unaided human observation. Overall, cumulative findings suggest time-lapse imagery is of dual utility and has high potential for collecting data and illustrating ecological dynamics. Advisor: Craig R. Alle

Applications of Time-lapse Imagery for Monitoring and Illustrating Ecological Dynamics in a Water-stressed System

Understanding and perceiving the natural world is a key part of management, policy, conservation, and inevitably for our future. Increased demand on natural resources has heightened the importance of documenting ecosystem changes, and knowledge-sharing to foster awareness. The advancement of digital technologies has improved the efficiency of passive monitoring, connectivity among systems, and expanded the potential for innovative and communicative approaches. From technological progression, time-lapse imagery has emerged a valuable tool to capture and depict natural systems. I sought to enhance our understanding of a water-stressed system by analyzing imagery, in addition to integrating images with data visualization to illustrate the complexity of a river basin in central Nebraska. Image analysis was used to quantify wetland water inundation and vegetation phenology. These measurements from visible changes were combined with less visible data from additional passive monitoring to examine the relationship between vegetation phenology and bat activity, as well as wetland inundation and water quality. Moreover, time-lapse data sequences were constructed by integrating time-lapse imagery with data visualization in an interactive digital framework to examine the applications for communicating social-ecological dynamics. Findings suggest vegetation phenology was differentially associated with seasonal bat activity, possibly related to migratory versus resident life history strategies. In regards to examining wetland hydrology, water inundation was found to be correlated with nitrate, dissolved oxygen, and DEA, and negatively correlated with water temperature, indicating the importance of understanding water levels. AEM-RDA analysis identified several significant temporal patterns occurring with the wetland as well as the river site. Similarities between river and wetland patterns were suggestive of regional conditions driving fluctuations, while discrepancies were indicative of structural, biological, and local differences within individual sites. In examining communicative applications, time-lapse data sequences depicted a range of ecological dynamics while linking visible and invisible occurrences. The framework shows potential to offer a tangible context with explanatory content to aid in understanding environmental changes that are often too subtle to see or beyond the temporal scale of unaided human observation. Overall, cumulative findings suggest time-lapse imagery is of dual utility and has high potential for collecting data and illustrating ecological dynamics. Advisor: Craig R. Alle

SURFACE WATER – GROUNDWATER INTERACTIONS IN A PROGLACIAL ALPINE CATCHMENT: Applications of Heat Tracing, Modeling, and Remote Sensing Methods

As climate change occurs, the availability and stability of water resources will be a global concern. The availability of reliable water resources will be of particular concern to regions that currently depend on meltwater from snowpack or glaciers during dry periods. One place whose water stability could be heavily impacted by the loss of meltwater resources is Peru. During the dry, arid months of May through September, the region to the west of the Peruvian Andes relies on stream water resources that originate in proglacial alpine catchments. The Cordillera Blanca, which is a mountain range in the Peruvian Andes, contains the highest density of tropical alpine glaciers worldwide, and the meltwater from these glaciers helps to sustain streamflow during the dry season. Unfortunately, tropical alpine glaciers are rapidly retreating as average annual air temperatures increase. In the Cordillera Blanca, glacial extent has decreased by more than 30% since 1930, and many of the glaciers have already passed a stage known as ‘peak water’, after which they continually contribute less and less water to streamflow. Recent research has indicated that although meltwater is a dominant contributor to streamflow during the dry season, groundwater within alpine aquifer systems may also be an important source of streamflow. Therefore, this research sought to investigate surface water – groundwater interactions in an alpine catchment of the Cordillera Blanca to gain a better understanding of the importance of groundwater in such regions. This research focuses on the Quilcayhuanca Valley, which is a representative proglacial alpine catchment in the Cordillera Blanca, Peru. Glacial meltwater and groundwater contribute to streamflow within this catchment during the dry season. The Quilcayhuanca stream, along with streams that drain from adjacent catchments, flows into the Rio Santa which is a major stream in the region from which people withdraw water for a variety of uses. The high altitude wetlands in the Quilcayhuanca Valley and similar catchments, known as pampas, may represent an important source of groundwater to streamflow. The valley aquifers consist of a mixture of landslide and talus slope deposits from the steep, adjacent bedrock cliffs and glaciofluvial deposits. The valley aquifers are confined from above by glaciolacustrine sediments that were deposited when proglacial lakes were present. In order to better understand the surface water – groundwater interactions in such a setting, we have combined energy balance modeling of stream heat fluxes, thermal infrared remote sensing of stream temperatures, and groundwater flow modeling to a section of the Quilcayhuanca stream that is downstream of direct glacial melt inputs to examine the influence of groundwater. Energy balance modeling of stream temperatures, also known as heat tracing, can be used to estimate groundwater contribution to a stream. This method uses the fluxes of energy into and out of a stream to calculate stream temperature through time and space, and the difference between calculated and observed stream temperatures can be attributed to groundwater inflow. Meteorological and longitudinal stream temperature data were recorded for approximately a week in a portion of the Quilcay stream, and used as input for an energy balance model of the reach. Various model inputs were also varied in order to assess the sensitivity of the model to certain parameters and determine the extent to which uncertainty in certain model parameters affects estimates of groundwater influx. An input that was investigated in depth was the extent to which uncertainty in the daily diurnal streamflow signal affects groundwater inflow estimates, since the streamflow in proglacial streams varies diurnally due to glacial melt. Groundwater influx to the model reach was estimated at 42.1 L s−1 km−1, and the uncertainty in diurnally fluctuating streamflow was determined to affect the estimated relative groundwater contribution to streamflow by approximately ±5%. In order to improve the spatial resolution of the stream temperature data used to inform the energy balance modeling of stream temperatures, we explored the use of ground-based, time-lapse infrared remote sensing to measure stream temperatures along the same study reach in the Quilcayhuanca Valley. During two field seasons, a thermal infrared (TIR) camera was deployed on the steep valley cliffs, recording time-lapse images of stream temperature. Analysis of the infrared images revealed that measured infrared stream temperatures are highly sensitive to infrared temperatures from other objects in the environment that reflect off the stream surface, often leading to large discrepancies between in-situ and remote temperature measurements. We determined that even at nadir views, reflected temperatures can still affect measured TIR stream temperatures, and that previous analytical correction methods performed by the hydrology community have not accurately represented reflected infrared temperatures. While such analytical correction methods could be improved through more accurate measurements of reflected temperatures, an empirical correction approach can also be used to correct stream infrared temperatures. While this data was not ultimately used to refine the stream temperature energy balance model of the Quilcay stream, this investigation has helped improve our understanding of remote sensing of stream temperatures using ground-based, time-lapse thermal infrared imagery. To complement the groundwater influx rates to the Quilcayhuanca stream estimated by stream temperature energy balance modeling, a groundwater flow model of the same pampa aquifer system was developed. Precipitation, stream stage, and groundwater level data that had been collected over various time periods were compiled to parameterize and calibrate the model. Numerous model simulations were explored to determine which model configuration best reproduced the annual hydraulic head patterns in the aquifer and the estimated dry season groundwater flux to the reach of the Quilcay stream. The modeled groundwater flux estimates were then used to estimate the amount of groundwater entering the stream from all pampa regions of the catchment above the gauging station. Results indicate that about 7-53% of Quilcayhuanca streamflow is derived from groundwater depending on the month during the dry season. As the dry season progresses, the relative contribution of groundwater to the stream decreases as the aquifer becomes depleted. Travel time analysis also indicates that the residence time of water in the pampa aquifer system is relatively short, with \u3e80% of water moving through the system in 6 months and the remaining water exiting after around 1-1.5 years. These results suggest that groundwater within these proglacial alpine catchments also contributes to streamflow, and that streamflow is vulnerable glacial loss, especially at the end of the dry season

Observing Short-Term Geomorphic Change in a Human-Modified River Using Terrestrial Repeat Photographs and Traditional Surveys: Uncompahgre River, Colorado, USA

The Uncompahgre River in Ouray, CO, was modified in 1996 from a braided river system to a meandering river channel. Large boulders of riprap were placed along designed meanders to prevent erosion and enable the development of permanent human structures on the flood plain. Deposition of gravel bars in the modified channel occurs annually during the summer. This gravel is "mined" by the City of Ouray; however, the effects of this excavation and the original modification were never assessed. This study provides an assessment by quantifying cross-sectional area change, cumulative grain-size distributions, shear stresses, slopes, and sinuosities using traditional survey methods. In addition, volume change of a gravel bar inside the modified channel was estimated using extreme oblique photographs (>45 degrees from nadir) that were obtained from nearby cliffs. Close-range photogrammetry was used in the natural channel downstream to evaluate photogrammetric methods using different lenses, image sensors, and camera geometries. Both traditional and photogrammetric methods clearly indicated significant deposition in the modified channel, whereas erosion occurred directly downstream from the modified channel, but did not occur at a reach 1.5 km downstream. In the natural channel, no cross-sectional area change occurred, grains were poorly sorted, and the longitudinal slope was ~four times steeper than the modified channel. Shear stress ratios were used as an erosion threshold, which did not correlate with actual cross-sectional area change, but a decrease in shear stress ratios from May 2011 to September 2011 were associated with erosion. Average RMSE values for DEMs created from extremeoblique photographs of a gravel bar in May 2011 and September 2011 were 0.140 m and 0.324 m, respectively. Using a DEM of difference with a t-statistic filter revealed that 115m3 of gravel was deposited. The Uncompahgre River showed similar geomorphic characteristics to other rivers in southwest Colorado, however, the slope of the natural and modified channels were much steeper than other rivers. Extreme-oblique photography and unconventional sensors both yielded reliable results, showing that these atypical techniques can be used in terrestrial photogrammetric applications such as, post-restoration assessments, as long as proper base-to-height ratios are achieved

On the use of smartphones as novel photogrammetric water gauging instruments: Developing tools for crowdsourcing water levels

The term global climate change is omnipresent since the beginning of the last decade. Changes in the global climate are associated with an increase in heavy rainfalls that can cause nearly unpredictable flash floods. Consequently, spatio-temporally high-resolution monitoring of rivers becomes increasingly important. Water gauging stations continuously and precisely measure water levels. However, they are rather expensive in purchase and maintenance and are preferably installed at water bodies relevant for water management. Small-scale catchments remain often ungauged. In order to increase the data density of hydrometric monitoring networks and thus to improve the prediction quality of flood events, new, flexible and cost-effective water level measurement technologies are required. They should be oriented towards the accuracy requirements of conventional measurement systems and facilitate the observation of water levels at virtually any time, even at the smallest rivers. A possible solution is the development of a photogrammetric smartphone application (app) for crowdsourcing water levels, which merely requires voluntary users to take pictures of a river section to determine the water level. Today’s smartphones integrate high-resolution cameras, a variety of sensors, powerful processors, and mass storage. However, they are designed for the mass market and use low-cost hardware that cannot comply with the quality of geodetic measurement technology. In order to investigate the potential for mobile measurement applications, research was conducted on the smartphone as a photogrammetric measurement instrument as part of the doctoral project. The studies deal with the geometric stability of smartphone cameras regarding device-internal temperature changes and with the accuracy potential of rotation parameters measured with smartphone sensors. The results show a high, temperature-related variability of the interior orientation parameters, which is why the calibration of the camera should be carried out during the immediate measurement. The results of the sensor investigations show considerable inaccuracies when measuring rotation parameters, especially the compass angle (errors up to 90° were observed). The same applies to position parameters measured by global navigation satellite system (GNSS) receivers built into smartphones. According to the literature, positional accuracies of about 5 m are possible in best conditions. Otherwise, errors of several 10 m are to be expected. As a result, direct georeferencing of image measurements using current smartphone technology should be discouraged. In consideration of the results, the water gauging app Open Water Levels (OWL) was developed, whose methodological development and implementation constituted the core of the thesis project. OWL enables the flexible measurement of water levels via crowdsourcing without requiring additional equipment or being limited to specific river sections. Data acquisition and processing take place directly in the field, so that the water level information is immediately available. In practice, the user captures a short time-lapse sequence of a river bank with OWL, which is used to calculate a spatio-temporal texture that enables the detection of the water line. In order to translate the image measurement into 3D object space, a synthetic, photo-realistic image of the situation is created from existing 3D data of the river section to be investigated. Necessary approximations of the image orientation parameters are measured by smartphone sensors and GNSS. The assignment of camera image and synthetic image allows for the determination of the interior and exterior orientation parameters by means of space resection and finally the transfer of the image-measured 2D water line into the 3D object space to derive the prevalent water level in the reference system of the 3D data. In comparison with conventionally measured water levels, OWL reveals an accuracy potential of 2 cm on average, provided that synthetic image and camera image exhibit consistent image contents and that the water line can be reliably detected. In the present dissertation, related geometric and radiometric problems are comprehensively discussed. Furthermore, possible solutions, based on advancing developments in smartphone technology and image processing as well as the increasing availability of 3D reference data, are presented in the synthesis of the work. The app Open Water Levels, which is currently available as a beta version and has been tested on selected devices, provides a basis, which, with continuous further development, aims to achieve a final release for crowdsourcing water levels towards the establishment of new and the expansion of existing monitoring networks.Der Begriff des globalen Klimawandels ist seit Beginn des letzten Jahrzehnts allgegenwärtig. Die Veränderung des Weltklimas ist mit einer Zunahme von Starkregenereignissen verbunden, die nahezu unvorhersehbare Sturzfluten verursachen können. Folglich gewinnt die raumzeitlich hochaufgelöste Überwachung von Fließgewässern zunehmend an Bedeutung. Pegelmessstationen erfassen kontinuierlich und präzise Wasserstände, sind jedoch in Anschaffung und Wartung sehr teuer und werden vorzugsweise an wasserwirtschaftlich-relevanten Gewässern installiert. Kleinere Gewässer bleiben häufig unbeobachtet. Um die Datendichte hydrometrischer Messnetze zu erhöhen und somit die Vorhersagequalität von Hochwasserereignissen zu verbessern, sind neue, kostengünstige und flexibel einsetzbare Wasserstandsmesstechnologien erforderlich. Diese sollten sich an den Genauigkeitsanforderungen konventioneller Messsysteme orientieren und die Beobachtung von Wasserständen zu praktisch jedem Zeitpunkt, selbst an den kleinsten Flüssen, ermöglichen. Ein Lösungsvorschlag ist die Entwicklung einer photogrammetrischen Smartphone-Anwendung (App) zum Crowdsourcing von Wasserständen mit welcher freiwillige Nutzer lediglich Bilder eines Flussabschnitts aufnehmen müssen, um daraus den Wasserstand zu bestimmen. Heutige Smartphones integrieren hochauflösende Kameras, eine Vielzahl von Sensoren, leistungsfähige Prozessoren und Massenspeicher. Sie sind jedoch für den Massenmarkt konzipiert und verwenden kostengünstige Hardware, die nicht der Qualität geodätischer Messtechnik entsprechen kann. Um das Einsatzpotential in mobilen Messanwendungen zu eruieren, sind Untersuchungen zum Smartphone als photogrammetrisches Messinstrument im Rahmen des Promotionsprojekts durchgeführt worden. Die Studien befassen sich mit der geometrischen Stabilität von Smartphone-Kameras bezüglich geräteinterner Temperaturänderungen und mit dem Genauigkeitspotential von mit Smartphone-Sensoren gemessenen Rotationsparametern. Die Ergebnisse zeigen eine starke, temperaturbedingte Variabilität der inneren Orientierungsparameter, weshalb die Kalibrierung der Kamera zum unmittelbaren Messzeitpunkt erfolgen sollte. Die Ergebnisse der Sensoruntersuchungen zeigen große Ungenauigkeiten bei der Messung der Rotationsparameter, insbesondere des Kompasswinkels (Fehler von bis zu 90° festgestellt). Selbiges gilt auch für Positionsparameter, gemessen durch in Smartphones eingebaute Empfänger für Signale globaler Navigationssatellitensysteme (GNSS). Wie aus der Literatur zu entnehmen ist, lassen sich unter besten Bedingungen Lagegenauigkeiten von etwa 5 m erreichen. Abseits davon sind Fehler von mehreren 10 m zu erwarten. Infolgedessen ist von einer direkten Georeferenzierung von Bildmessungen mittels aktueller Smartphone-Technologie abzusehen. Unter Berücksichtigung der gewonnenen Erkenntnisse wurde die Pegel-App Open Water Levels (OWL) entwickelt, deren methodische Entwicklung und Implementierung den Kern der Arbeit bildete. OWL ermöglicht die flexible Messung von Wasserständen via Crowdsourcing, ohne dabei zusätzliche Ausrüstung zu verlangen oder auf spezifische Flussabschnitte beschränkt zu sein. Datenaufnahme und Verarbeitung erfolgen direkt im Feld, so dass die Pegelinformationen sofort verfügbar sind. Praktisch nimmt der Anwender mit OWL eine kurze Zeitraffersequenz eines Flussufers auf, die zur Berechnung einer Raum-Zeit-Textur dient und die Erkennung der Wasserlinie ermöglicht. Zur Übersetzung der Bildmessung in den 3D-Objektraum wird aus vorhandenen 3D-Daten des zu untersuchenden Flussabschnittes ein synthetisches, photorealistisches Abbild der Aufnahmesituation erstellt. Erforderliche Näherungen der Bildorientierungsparameter werden von Smartphone-Sensoren und GNSS gemessen. Die Zuordnung von Kamerabild und synthetischem Bild erlaubt die Bestimmung der inneren und äußeren Orientierungsparameter mittels räumlichen Rückwärtsschnitt. Nach Rekonstruktion der Aufnahmesituation lässt sich die im Bild gemessene 2D-Wasserlinie in den 3D-Objektraum projizieren und der vorherrschende Wasserstand im Referenzsystem der 3D-Daten ableiten. Im Soll-Ist-Vergleich mit konventionell gemessenen Pegeldaten zeigt OWL ein erreichbares Genauigkeitspotential von durchschnittlich 2 cm, insofern synthetisches und reales Kamerabild einen möglichst konsistenten Bildinhalt aufweisen und die Wasserlinie zuverlässig detektiert werden kann. In der vorliegenden Dissertation werden damit verbundene geometrische und radiometrische Probleme ausführlich diskutiert sowie Lösungsansätze, auf der Basis fortschreitender Entwicklungen von Smartphone-Technologie und Bildverarbeitung sowie der zunehmenden Verfügbarkeit von 3D-Referenzdaten, in der Synthese der Arbeit vorgestellt. Mit der gegenwärtig als Betaversion vorliegenden und auf ausgewählten Geräten getesteten App Open Water Levels wurde eine Basis geschaffen, die mit kontinuierlicher Weiterentwicklung eine finale Freigabe für das Crowdsourcing von Wasserständen und damit den Aufbau neuer und die Erweiterung bestehender Monitoring-Netzwerke anstrebt