Applying a time-lapse camera network to observe snow processes in mountainous catchments

Abstract. A network of 45 spatially distributed time-lapse cameras was used to carry out a continuous observation of snow processes and snow cover properties throughout three mid-latitude medium elevation mountain catchments in hourly intervals. A simple technical modification was conducted to enable the deployment of the standard digital cameras in any location. Image analysis software was applied to extract information about snow depth, surface albedo, and canopy interception from the digital images. Furthermore, the distributed design of the camera network made it possible to identify the elevation of the snow rain interface for any precipitation event for the interpretation of winter flooding events resulting from snow melt. Study results prove that the application of digital time-lapse photography is an appropriate technique to observe the spatial distribution and temporal evolution of seasonal snow covers in a mountainous environment.

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From observation to the quantification of snow processes with a time-lapse camera network

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1415-2013 ◽

2013 ◽

Vol 17 (4) ◽

pp. 1415-1429 ◽

Cited By ~ 57

Author(s):

J. Garvelmann ◽

S. Pohl ◽

M. Weiler

Keyword(s):

Time Lapse ◽

Precipitation Event ◽

Digital Cameras ◽

Camera Network ◽

Canopy Interception ◽

Study Results ◽

Spatially Distributed ◽

Winter Flooding ◽

Flooding Events ◽

Time Lapse Photography

Abstract. A network of 45 spatially distributed time-lapse cameras was used to carry out a continuous observation of snow processes and snow cover properties throughout three mid-latitude medium elevation mountain catchments in hourly intervals during the winter seasons of 2010/2011 and 2011/2012. A simple technical modification was conducted to enable the deployment of the standard digital cameras in any location. Image analysis software was applied to extract information about snow depth, surface albedo and canopy interception from the digital images. Furthermore, the distributed design of the camera network made it possible to identify the elevation of the snow rain interface for any precipitation event which is very helpful for the interpretation of winter flooding events resulting from snow melt. Exemplary data for all these analyses is presented to show the potential fields of application of this innovative approach. Study results prove that the application of digital time-lapse photography is an appropriate technique to observe the spatial distribution and temporal evolution of seasonal snow covers in a mountainous environment.

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Performance and sensitivity of a spatially distributed hydrological conceptual flood model with snow components.

10.5194/egusphere-egu21-15300 ◽

2021 ◽

Author(s):

François Colleoni ◽

Catherine Fouchier ◽

Pierre-André Garambois ◽

Pierre Javelle ◽

Maxime Jay-Allemand ◽

...

Keyword(s):

Significant Proportion ◽

Slow Flow ◽

Modeling Tools ◽

Snow Modeling ◽

Distributed Modelling ◽

Distributed Framework ◽

Mountainous Catchments ◽

Spatially Distributed ◽

Flow Components ◽

Spatially Varying

In France, flash floods are responsible for a significant proportion&#160;of damages caused by natural hazards, either human or material. Hence,&#160;advanced modeling tools are needed to perform effective predictions. However for mountainous catchments snow modeling components may be required to correctly simulate&#160;river discharge.This contribution investigates the implementation and constrain of snow components in the spatially distributed SMASH* platform (Jay-Allemand et al. 2020). The goal is to upgrade model structure and spatially distributed calibration strategies for snow-influenced catchments, as well as to investigate parametric sensitivity and equifinality issues.&#160;First, the implementation of snow modules of varying complexity is addressed based on Cemaneige (Valery et al. 2010) in the spatially distributed framework. Next, tests are performed on a sample of 55 catchments in the French North Alps. Numerical experiments and global sensitivity analysis enable to determine pertinent combinations of flow components (including a slow flow one) and calibration parameters. Spatially uniform or distributed calibrations using a variational method (Jay-Allemand 2020) are performed and compared on the dataset, for different model structures and constrains. These tests show critical improvements in outlet discharge modeling by adding slow flow and snow modules, especially considering spatially varying parameters. Current and future works focus on testing and improving the constrains of snow modules and calibration strategy, as well as potential validation and multiobjective calibration with snow signatures gained from in situ or satellite data.&#160;*SMASH: Spatially-distributed Modelling and ASsimilation for Hydrology, platform developped by INRAE-Hydris corp. for operational applications in the french flood forecast system VigicruesFlash

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Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives

Hydrology and Earth System Sciences ◽

10.5194/hess-23-1409-2019 ◽

2019 ◽

Vol 23 (3) ◽

pp. 1409-1429 ◽

Cited By ~ 15

Author(s):

Sjoukje Philip ◽

Sarah Sparrow ◽

Sarah F. Kew ◽

Karin van der Wiel ◽

Niko Wanders ◽

...

Keyword(s):

Climate Change ◽

Climate Models ◽

Climate Model ◽

Positive Influence ◽

Anthropogenic Climate Change ◽

Precipitation Event ◽

Climate Change Signal ◽

Hydrological Models ◽

Additional Measure ◽

Flooding Events

Abstract. In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents, for the first time, an attribution of this precipitation-induced flooding to anthropogenic climate change from a combined meteorological and hydrological perspective. Experiments were conducted with three observational datasets and two climate models to estimate changes in the extreme 10-day precipitation event frequency over the Brahmaputra basin up to the present and, additionally, an outlook to 2 ∘C warming since pre-industrial times. The precipitation fields were then used as meteorological input for four different hydrological models to estimate the corresponding changes in river discharge, allowing for comparison between approaches and for the robustness of the attribution results to be assessed. In all three observational precipitation datasets the climate change trends for extreme precipitation similar to that observed in August 2017 are not significant, however in two out of three series, the sign of this insignificant trend is positive. One climate model ensemble shows a significant positive influence of anthropogenic climate change, whereas the other large ensemble model simulates a cancellation between the increase due to greenhouse gases (GHGs) and a decrease due to sulfate aerosols. Considering discharge rather than precipitation, the hydrological models show that attribution of the change in discharge towards higher values is somewhat less uncertain than in precipitation, but the 95 % confidence intervals still encompass no change in risk. Extending the analysis to the future, all models project an increase in probability of extreme events at 2 ∘C global heating since pre-industrial times, becoming more than 1.7 times more likely for high 10-day precipitation and being more likely by a factor of about 1.5 for discharge. Our best estimate on the trend in flooding events similar to the Brahmaputra event of August 2017 is derived by synthesizing the observational and model results: we find the change in risk to be greater than 1 and of a similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach. This study shows that, for precipitation-induced flooding events, investigating changes in precipitation is useful, either as an alternative when hydrological models are not available or as an additional measure to confirm qualitative conclusions. Besides this, it highlights the importance of using multiple models in attribution studies, particularly where the climate change signal is not strong relative to natural variability or is confounded by other factors such as aerosols.

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Spatially distributed runoff at the grounding line of a large Greenlandic tidewater glacier inferred from plume modelling

Journal of Glaciology ◽

10.1017/jog.2016.139 ◽

2017 ◽

Vol 63 (238) ◽

pp. 309-323 ◽

Cited By ~ 23

Author(s):

DONALD SLATER ◽

PETER NIENOW ◽

ANDREW SOLE ◽

TOM COWTON ◽

RUTH MOTTRAM ◽

...

Keyword(s):

General Circulation ◽

Circulation Model ◽

Time Lapse ◽

Atmospheric Temperature ◽

Recent Change ◽

Grounding Line ◽

Tidewater Glacier ◽

Spatially Distributed ◽

Basal Sliding ◽

Catchment Runoff

ABSTRACTUnderstanding the drivers of recent change at Greenlandic tidewater glaciers is of great importance if we are to predict how these glaciers will respond to climatic warming. A poorly constrained component of tidewater glacier processes is the near-terminus subglacial hydrology. Here we present a novel method for constraining near-terminus subglacial hydrology with application to marine-terminating Kangiata Nunata Sermia in South-west Greenland. By simulating proglacial plume dynamics using buoyant plume theory and a general circulation model, we assess the critical subglacial discharge, if delivered through a single compact channel, required to generate a plume that reaches the fjord surface. We then compare catchment runoff to a time series of plume visibility acquired from a time-lapse camera. We identify extended periods throughout the 2009 melt season where catchment runoff significantly exceeds the discharge required for a plume to reach the fjord surface, yet we observe no plume. We attribute these observations to spatial spreading of runoff across the grounding line. Persistent distributed drainage near the terminus would lead to more spatially homogeneous submarine melting and may promote more rapid basal sliding during warmer summers, potentially providing a mechanism independent of ocean forcing for increases in atmospheric temperature to drive tidewater glacier acceleration.

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A Distributed Snow-Evolution Modeling System (SnowModel)

Journal of Hydrometeorology ◽

10.1175/jhm548.1 ◽

2006 ◽

Vol 7 (6) ◽

pp. 1259-1276 ◽

Cited By ~ 287

Author(s):

Glen E. Liston ◽

Kelly Elder

Keyword(s):

Forest Canopy ◽

Snow Water Equivalent ◽

Vegetation Type ◽

Atmospheric Model ◽

Snow Accumulation ◽

Blowing Snow ◽

Canopy Interception ◽

Meteorological Forcing ◽

Spatially Distributed ◽

Evolution Modeling

Abstract SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. Since each of these submodels was originally developed and tested for nonforested conditions, details describing modifications made to the submodels for forested areas are provided. SnowModel was created to run on grid increments of 1 to 200 m and temporal increments of 10 min to 1 day. It can also be applied using much larger grid increments, if the inherent loss in high-resolution (subgrid) information is acceptable. Simulated processes include snow accumulation; blowing-snow redistribution and sublimation; forest canopy interception, unloading, and sublimation; snow-density evolution; and snowpack melt. Conceptually, SnowModel includes the first-order physics required to simulate snow evolution within each of the global snow classes (i.e., ice, tundra, taiga, alpine/mountain, prairie, maritime, and ephemeral). The required model inputs are 1) temporally varying fields of precipitation, wind speed and direction, air temperature, and relative humidity obtained from meteorological stations and/or an atmospheric model located within or near the simulation domain; and 2) spatially distributed fields of topography and vegetation type. SnowModel’s ability to simulate seasonal snow evolution was compared against observations in both forested and nonforested landscapes. The model closely reproduced observed snow-water-equivalent distribution, time evolution, and interannual variability patterns.

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Use of Time-lapse Video to Demonstrate Plant Growth Regulator (PGR) Responses

HortScience ◽

10.21273/hortsci.39.4.875a ◽

2004 ◽

Vol 39 (4) ◽

pp. 875A-875

Author(s):

Derek D. Woolard* ◽

Judy Fugiel ◽

F. Paul Silverman ◽

Peter D. Petracek

Keyword(s):

Treatment Effects ◽

Digital Camera ◽

Time Lapse ◽

Strong Impact ◽

Digital Cameras ◽

Camera Placement ◽

Use Of Time ◽

Notebook Computers ◽

Visual Record ◽

Time Lapse Video

Tables, graphs, and photographs can effectively convey detailed results of a PGR experiment. However, we have observed that demonstrating PGR treatment effects by time-lapse video creates a strong impact on both scientists and non-technical audiences. Time-lapse video also provides a method for obtaining a continuous visual record that can be used to establish the precise chronology of a slow process. Recent advances in notebook computers, inexpensive digital cameras (e.g. 3Com HomeConnect™), and time-lapse software (e.g. Picture WorkLive™) allow scientists and teachers to inexpensively prepare time-lapse videos. Important considerations for the production of quality time-lapse videos include: 1. treatment effects should be substantial, consistent, and visible, 2. digital camera images should be clear, 3. lighting should be constant and provide adequate brightness and proper color, 4. camera movement such as those due to vibrations should be minimal, 5. camera placement should simplify composition. Time-lapse videos of PGR treatment effects will be shown, and methods of production will be discussed.

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Basis-constrained Bayesian Markov-chain Monte Carlo difference inversion for geoelectrical monitoring of hydrogeologic processes

Geophysics ◽

10.1190/geo2018-0643.1 ◽

2019 ◽

Vol 84 (4) ◽

pp. A37-A42 ◽

Cited By ~ 3

Author(s):

Erasmus Kofi Oware ◽

James Irving ◽

Thomas Hermans

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Computational Cost ◽

Model Space ◽

Time Lapse ◽

Tracer Experiment ◽

Hydrologic Process ◽

Spatially Distributed ◽

Geophysical Imaging

Bayesian Markov-chain Monte Carlo (McMC) techniques are increasingly being used in geophysical estimation of hydrogeologic processes due to their ability to produce multiple estimates that enable comprehensive assessment of uncertainty. Standard McMC sampling methods can, however, become computationally intractable for spatially distributed, high-dimensional problems. We have developed a novel basis-constrained Bayesian McMC difference inversion framework for time-lapse geophysical imaging. The strategy parameterizes the Bayesian inversion model space in terms of sparse, hydrologic-process-tuned bases, leading to dimensionality reduction while accounting for the physics of the target hydrologic process. We evaluate the algorithm on cross-borehole electrical resistivity tomography (ERT) field data acquired during a heat-tracer experiment. We validate the ERT-estimated temperatures with direct temperature measurements at two locations on the ERT plane. We also perform the inversions using the conventional smoothness-constrained inversion (SCI). Our approach estimates the heat plumes without excessive smoothing in contrast with the SCI thermograms. We capture most of the validation temperatures within the 90% confidence interval of the mean. Accounting for the physics of the target process allows the detection of small temperature changes that are undetectable by the SCI. Performing the inversion in the reduced-dimensional model space results in significant gains in computational cost.

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Linking frequency of rainstorms, runoff generation and sediment transport across hyperarid talus-pediment slopes

10.5194/egusphere-egu2020-701 ◽

2020 ◽

Author(s):

Yuval Shmilovitz ◽

Efrat Morin ◽

Yair Rinat ◽

Itai Haviv ◽

Genadi Carmi ◽

...

Keyword(s):

Sediment Transport ◽

Time Lapse ◽

Small Scale ◽

Distributed Hydrological Model ◽

Runoff Generation ◽

Low Velocity ◽

Slope Length ◽

Radar Rainfall ◽

X Band ◽

Study Results

Talus-pediment slopes are a common morphologic feature in arid areas and constitute a prominent runoff and sediment source at the watershed and channel scales. The evolution of talus-pediment sequences (talus flatirons) was often linked to climatic cycles, although the physical processes that may account for such a link remained obscure. Our approach is to integrate field measurements, high-resolution radar rainfall data and numerical modeling to link the frequency of storms and the resulted hillslope runoff and sediment transport. We present a quantitative hydrometeorological analysis of rainstorms and their geomorphic impact, potentially involved in the evolution of arid talus-pediment slopes in the Negev desert (Israel). Artificial rainstorms were designed based on intensity-duration-frequency curves and simulated in the field using a rainfall simulator. Then, the obtained experimental results were up-scaled to the entire slope length using a fully distributed hydrological model. In addition, natural storms and their hydro-geomorphic impacts were monitored using X-band radar and time-lapse cameras.These integrated analyses constrain the rainfall threshold for local runoff generation at rain intensity of 14-22 mm h-1 for a duration of 5 min for the study area conditions. We characterized small-scale runoff-generating convective rain cells using an X-band radar and found that small convective cells (~30 km2), having extremely high internal spatial gradients in rainfall intensity and low velocity (<10 m s-1), have the potential to generate local hillslope runoff. The frequency of local runoff-producing rainstorms is ~1-3 per year, but most of these storms activate only small parts of the hillslope. Modeling results indicate that a full extent hillslope runoff occurs under much rarer rainstorms of at least 100-years return interval (1% or less). During such rainstorms, the shear stress produced by the runoff flow (sheetwash) is capable of transporting surface clasts at a distance of ~80 m downslope. However, transport of coarse clasts in the upper parts of the slopes is most probably gravitationally controlled. The erosion efficiency of discrete rare events (1% or less) on the lower part of the slopes highlights their potential to trigger incision and lead to cliff dissection. This study results support the hypothesis that a climatic shift in terms of the properties and frequency of extreme rainstorms, rather than the common views of it as changing precipitation means, can play an important role in shaping and in transforming landscapes in such arid setting.

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Informational and Symbolic Content of over-the-Counter Drug Advertising on Television

Journal of Drug Education ◽

10.2190/4x1b-6h51-m4jx-r7w8 ◽

1997 ◽

Vol 27 (2) ◽

pp. 173-197 ◽

Cited By ~ 16

Author(s):

James C. Tsao

Keyword(s):

Drug Effects ◽

Time Lapse ◽

Drug Usage ◽

Consumer Awareness ◽

Over The Counter ◽

Drug Advertising ◽

Advertising Strategy ◽

Study Results ◽

Promotional Efforts ◽

Symbolic Content

The informational and symbolic content of 150 over-the-counter drug commercials on television are empirically analyzed in this study. Results on the informational content suggest that over-the-counter drug ads tend to focus on the concern of what the drug will do for the consumer, rather than on the reasons why the drug should be ingested. Accordingly, advertising strategy is centered on consumer awareness of the product as the primary goal. Educational commitment, however, did not seem to be blended into the promotional efforts for over-the-counter drugs. Findings on the symbolic content of over-the-counter drug ads reveal that drug images have been distorted. Performance of most drugs has been portrayed to be simple resolutions to relieve the symptom. Moreover, a casual attitude toward drug usage is encouraged in the commercials, while time lapse of drug effects is overlooked.

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Infrared and Chlorophyll Fluorescence Imaging Methods for Stress Evaluation

HortScience ◽

10.21273/hortsci.47.6.697 ◽

2012 ◽

Vol 47 (6) ◽

pp. 697-698 ◽

Cited By ~ 10

Author(s):

D. Michael Glenn

Keyword(s):

Chlorophyll Fluorescence ◽

Fluorescence Imaging ◽

Time Lapse ◽

Plant Performance ◽

Chlorophyll Fluorescence Imaging ◽

Sensor Technology ◽

Digital Cameras ◽

Imaging Methods ◽

Research Grade ◽

The Cost

Infrared and chlorophyll fluorescence imaging methods are useful techniques to evaluate environmental effects on plant performance. With the advent of digital imaging and advances in sensor technology, infrared (IR) thermography has become more accurate and less expensive. Modern IR cameras can resolve 0.5 °C temperature differences and research-grade instruments can resolve 0.05 °C. This precision has allowed the physical processes of freezing and transpiration to be more accurately studied and modeled. Chlorophyll fluorescence imaging, although still an expensive technology, has also become sufficiently rugged to be useful in the field. The measurement of quantum efficiency, Fv/Fm, provides clear data on the effect of various environmental and biotic effects on the performance of photosynthesis in plants through the effect on photosystem II. Modern digital cameras with low signal-to-noise ratios can also image chlorophyll fluorescence using time lapse exposure. Peltier-cooled charge coupled device (CCD) cameras can measure the autoluminescence in stressed plants that is generated by reactive oxygen species. Advances in technology have reduced the cost and precision of imaging equipment to a point that they are more applicable tools to plant scientists.

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