Potential of time‐lapse photography of snow for hydrological purposes at the small catchment scale

Time‐lapse photography provides an attractive source of information about snow cover characteristics, especially at the small catchment scale. The objective of this study was to design and test a monitoring system, which allows multi‐resolution observations of snow cover characteristics. The main aim was to simultaneously investigate the spatio‐temporal patterns of snow cover, snow depth and snowfall interception in the area very close to the camera, and the spatio‐temporal patterns of snow cover in the far range. The multi‐resolution design was tested at three sites in the eastern part of the Austrian Alps (Hochschwab‐Rax region). Digital photographs were taken at hourly time steps between 6:00 and 18:00 in the period November, 2004 to December, 2006. The results showed that the time‐lapse photography allows effective mapping of the snow depths at high temporal resolution in the region close to the digital camera at many snow stake locations. It is possible to process a large number of photos by using an automatic procedure for accurate snow depth readings. The digital photographs can also be used to infer the settling characteristics of the snow pack and snow interception during the day. Although it is not possible to directly estimate the snow interception mass, the photos may indeed give very useful information on the snow processes on and beneath the forest canopy. The main advantage of using time‐lapse photography in the far range of the digital camera is to observe the spatio‐temporal patterns of snow cover over different landscape configurations. The results illustrate that digital photographs can be very useful for parameterising processes such as sloughing on steep slopes, snow deposition in gullies and snow erosion on mountain ridges in a distributed snow model. Copyright © 2011 John Wiley & Sons, Ltd.     

Snow accumulation distribution inferred from time‐lapse photography and simple modelling

The spatial and temporal distribution of snow accumulation is complex and significantly influences the hydrological characteristics of mountain catchments. Many snow redistribution processes, such as avalanching, slushflow or wind drift, are controlled by topography, but their modelling remains challenging. In situ measurements of snow accumulation are laborious and generally have a coarse spatial or temporal resolution. In this respect, time‐lapse photography shows itself as a powerful tool for collecting information at relatively low cost and without the need for direct field access. In this paper, the snow accumulation distribution of an Alpine catchment is inferred by adjusting a simple snow accumulation model combined with a temperature index melt model to match the modelled melt‐out pattern evolution to the pattern monitored during an ablation season through terrestrial oblique photography. The comparison of the resulting end‐of‐winter snow water equivalent distribution with direct measurements shows that the achieved accuracy is comparable with that obtained with an inverse distance interpolation of the point measurements. On average over the ablation season, the observed melt‐out pattern can be reproduced correctly in 93% of the area visible from the fixed camera. The relations between inferred snow accumulation distribution and topographic variables indicate large scatter. However, a significant correlation with local slope is found and terrain curvature is detected as a factor limiting the maximal snow accumulation. Copyright © 2010 John Wiley & Sons, Ltd.     

Snow process monitoring in montane forests with time‐lapse photography

A camera network with hourly resolution was used to monitor the complex snow processes in montane forest environments. We developed a semi‐automatic procedure to interpret snow depths from the digital images, which exhibited high consistency with manual measurements and station‐based recordings. To extract snow interception dynamics, six binary classification methods were compared. The MaxEntropy classifier demonstrated better performance than the other methods under conditions of varying illumination and was therefore selected as the method used for quantifying snow in tree canopies. Snow accumulation and ablation on the ground, as well as snow loading and unloading in the forest canopies, were investigated using snow parameters derived from the time‐lapse photography monitoring. The influences of meteorologic conditions, forest cover, and elevation on the snow processes were also considered. Time‐lapse photography proved to be an effective and low‐cost approach for collecting useful information on snow processes and facilitating the set‐up of hydrological models.     

Potential of time‐lapse photography for identifying saturation area dynamics on agricultural hillslopes

Mapping saturation areas during rainfall events is important for understanding the dynamics of overland flow. In this study, we evaluate the potential of high temporal resolution time‐lapse photography for mapping the dynamics of saturation areas (i.e., areas where water is visually ponding on the surface) on the hillslope scale during natural rainfall. We take 1 image per minute over a 100 × 15 m² depression area on an agricultural field in the Hydrological Open Air Laboratory, Austria. The images are georectified and classified by an automated procedure, using grey intensity as a threshold to identify saturation area. The optimum threshold T is obtained by comparing saturation areas from the automated analysis with the manual analysis of 149 images. T is found to be highly correlated with an image brightness characteristic defined as the greyscale image histogram mode M (Pearson correlation r = 0.91). We estimate T as T = M + C where C is a calibration parameter assumed to be constant during each event. The automated procedure estimates the total saturation area close to the manual analysis with mean normalized root mean square error of 9% and 21% if C is calibrated for each event and taken constant for all events, respectively. The spatial patterns of saturation are estimated with a geometric mean accuracy index of 94% as compared to the manual analysis of the same photos. The patterns are tested against field observations for one date as a preliminary demonstration, which yields a root mean square error of the shortest distance between the measured boundary points and the automatically classified boundary as 23 cm. The usefulness of the patterns is illustrated by exploring run‐off generation processes of an example event. Overall, the proposed classification method based on grey intensity is found to process images with highly varying brightnesses well. It is more efficient than the manual tracing for a large number of images, which allows the exploration of surface flow processes at high temporal resolution.     

Estimating fluvial wood discharge using time‐lapse photography with varying sampling intervals

Monitoring large wood (LW: width > 10 cm, length > 1 m) in transport within rivers is a necessary next step in the development and refinement of wood budgets and is essential to a better understanding of basin‐wide controls and patterns of LW flux and loads. Monitoring LW transport with coarse interval (≥ 1 min) time‐lapse photography enables the deployment of monitoring cameras at large spatial and long temporal scales. Although less precise than continuous sampling with video, it allows investigators to answer broad questions about basin connectivity, compare drainages and years,and identify transport relationships and thresholds. This paper describes methods to: (i) construct fluvial wood flux curves; (ii) analyze the effects of sample interval lengths on transport estimates; and (iii) estimate total wood loads within a specified time period using coarse‐interval time‐lapse photography. Applying these methods to the Slave River, a large‐volume (10³ m³ s^‐1), low‐gradient (10^{? 2} m km^{? 1}) river in the subarctic (60^° N), yielded the following results. A threshold relationship for wood mobility was located around 4500 m³ s^‐1. More wood is transported on the rising limb of the hydrograph because wood flux declines rapidly on the falling limb. Five‐ and ten‐minute sampling intervals provided unbiased equal variance estimates of 1 min sampling, whereas 15 min intervals were biased towards underestimation by 5–6%, possibly due to periodicity in wood flux. Total LW loads estimated from the 1 min dataset and adjusted for a 15% misdetection rate from 13 July to 13 August are: 1600 ± 200 # pieces, 600 ± 200 m³ and of the order of 1.3 × 10⁵ kg carbon. The total wood load for the entire summer season is probably at least double this estimate because only the second half of the summer was monitored and a large early summer peak freshet was missed. Copyright © 2014 John Wiley & Sons, Ltd.     

Statistical probability distribution of snow depth at the model sub‐grid cell spatial scale

Comprehensive snow depth data, collected using georadar and hand probing, were used for statistical analyses of snow depths inside 1 km grid cells. The sub‐grid cell spatial scale was 100 m. Statistical distribution functions were found to have varying parameters, and an attempt was made to connect these statistical parameters to different terrain variables. The results showed that the two parameters mean and standard deviation of snow depth were significantly related to the sub‐grid terrain characteristics. Linear regression models could explain up to 50% of the variation for both of the snowcover parameters mentioned. Copyright © 2004 John Wiley & Sons, Ltd.     

Influence of subsurface injection on time‐lapse seismic: laboratory studies at seismic and ultrasonic frequencies

Seismic monitoring of reservoir and overburden performance during subsurface CO₂ storage plays a key role in ensuring efficiency and safety. Proper interpretation of monitoring data requires knowledge about the rock physical phenomena occurring in the subsurface formations. This work focuses on rock stiffness and elastic velocity changes of a shale overburden formation caused by both reservoir inflation induced stress changes and leakage of CO₂ into the overburden. In laboratory experiments, Pierre shale I core plugs were loaded along the stress path representative for the in situ stress changes experienced by caprock during reservoir inflation. Tests were carried out in a triaxial compaction cell combining three measurement techniques and permitting for determination of (i) ultrasonic velocities, (ii) quasistatic rock deformations, and (iii) dynamic elastic stiffness at seismic frequencies within a single test, which allowed to quantify effects of seismic dispersion. In addition, fluid substitution effects connected with possible CO₂ leakage into the caprock formation were modelled by the modified anisotropic Gassmann model. Results of this work indicate that (i) stress sensitivity of Pierre shale I is frequency dependent; (ii) reservoir inflation leads to the increase of the overburden Young's modulus and Poisson's ratio; (iii) in situ stress changes mostly affect the P‐wave velocities; (iv) small leakage of the CO₂ into the overburden may lead to the velocity changes, which are comparable with one associated with geomechanical influence; (v) non‐elastic effects increase stress sensitivity of an acoustic waves; (iv) and both geomechanical and fluid substitution effects would create significant time shifts, which should be detectable by time‐lapse seismic.     

Use of terrestrial photogrammetry based on structure‐from‐motion for mass balance estimation of a small glacier in the Italian alps

Different high‐resolution techniques can be employed to obtain information about the three‐dimensional (3D) surface of glaciers. This is typically carried out using efficient, but also expensive and logistically demanding, light detection and ranging (LiDAR) technologies, such as airborne scanners and terrestrial laser scanners. Recent technological improvements in the field of image analysis and computer vision have prompted the development of a low‐cost photogrammetric approach, which is referred to as ‘structure‐from‐motion’ (SfM). Combined with dense image‐matching algorithms, this method has become competitive for the production of high‐quality 3D models. However, several issues typical of this approach should be considered for application in glacial environments. In particular, the surface morphology, the different substrata, the occurrence of sharp contrast from solar shadows and the variable distance from the camera positions can negatively affect the image texture, and reduce the possibility of obtaining a reliable point cloud from the images. The objective of this study is to test the structure‐from‐motion multi view stereo (SfM‐MVS) approach in a small debris‐covered glacier located in the eastern Italian Alps, using a consumer‐grade reflex camera and the computer vision‐based software PhotoScan. The quality of the 3D models produced by the SfM‐MVS process was assessed via the comparison with digital terrain models obtained from terrestrial laser scanning (TLS) surveys that were performed at the same epochs. The effect of different terrain gradients and different substrata (debris, snow and firn) was also evaluated in terms of the accuracy of the reconstruction by SfM‐MVS versus TLS. Our results show that the quality of this new photogrammetric approach is similar to the quality of TLS and that point cloud densities are comparable or even higher compared with TLS. However, special care should be taken while planning the SfM survey geometry, to optimize the 3D model quality and spatial coverage. Copyright © 2015 John Wiley & Sons, Ltd.     

Bank erosion in agricultural drainage networks: new challenges from structure‐from‐motion photogrammetry for post‐event analysis

Drainage channels are an integral part of agricultural landscapes, and their impact on catchment hydrology is strongly recognized. In cultivated and urbanized floodplains, channels have always played a key role in flood protection, land reclamation, and irrigation. Bank erosion is a critical issue in channels. Neglecting this process, especially during flood events, can result in underestimation of the risk in flood‐prone areas. The main aim of this work is to consider a low‐cost methodology for the analysis of bank erosion in agricultural drainage networks, and in particular for the estimation of the volumes of eroded and deposited material. A case study located in the Veneto floodplain was selected. The research is based on high‐resolution topographic data obtained by an emerging low‐cost photogrammetric method (structure‐from‐motion or SfM), and results are compared to terrestrial laser scanning (TLS) data. For the SfM analysis, extensive photosets were obtained using two standalone reflex digital cameras and an iPhone5® built‐in camera. Three digital elevation models (DEMs) were extracted at the resolution of 0.1 m using SfM and were compared with the ones derived by TLS. Using the different DEMs, the eroded areas were then identified using a feature extraction technique based on the topographic parameter Roughness Index (RI). DEMs derived from SfM were effective for both detecting erosion areas and estimating quantitatively the deposition and erosion volumes. Our results underlined how smartphones with high‐resolution built‐in cameras can be competitive instruments for obtaining suitable data for topography analysis and Earth surface monitoring. This methodology could be potentially very useful for farmers and/or technicians for post‐event field surveys to support flood risk management. Copyright © 2015 John Wiley & Sons, Ltd.     

On the role of spatial resolution on snow estimates using a process‐based snow model across a range of climatology and elevation

Hydrological processes in mountainous settings depend on snow distribution, whose prediction accuracy is a function of model spatial scale. Although model accuracy is expected to improve with finer spatial resolution, an increase in resolution comes with modelling costs related to increased computational time and greater input data and parameter information. This computational and data collection expense is still a limiting factor for many large watersheds. Thus, this work's main objective is to question which physical processes lead to loss in model accuracy with regard to input spatial resolution under different climatic conditions and elevation ranges. To address this objective, a spatially distributed snow model, iSnobal, was run with inputs distributed at 50‐m—our benchmark for comparison—and 100‐m resolutions and with aggregated (averaged from the fine to the large resolution) inputs from the 50‐m model to 100‐, 250‐, 500‐, and 750‐m resolution for wet, average, and dry years over the Upper Boise River Basin (6,963 km²), which spans four elevation bands: rain dominated, rain–snow transition, and snow dominated below treeline and above treeline. Residuals, defined as differences between values quantified with high resolution (>50 m) models minus the benchmark model (50 m), of simulated snow‐covered area (SCA) and snow water equivalent (SWE) were generally slight in the aggregated scenarios. This was due to transferring the effects of topography on meteorological variables from the 50‐m model to the coarser scales through aggregation. Residuals in SCA and SWE in the distributed 100‐m simulation were greater than those of the aggregated 750 m. Topographic features such as slope and aspect were simplified, and their gradient was reduced due to coarsening the topography from the 50‐ to 100‐m resolution. Therefore, solar radiation was overestimated, and snow drifting was modified and caused substantial SCA and SWE underestimation in the distributed 100‐m model relative to the 50‐m model. Large residuals were observed in the wet year and at the highest elevation band when and where snow mass was large. These results support that model accuracy is substantially reduced with model scales coarser than 50 m.     

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

We test the acquisition of high‐resolution topographic and terrain data using hand‐held smartphone technology, where the acquired images can be processed using technology freely available to the research community. This is achieved by evaluating the quality of digital terrain models (DTM) of a river bank and an Alpine alluvial fan generated with a fully automated, free‐to‐use, structure‐from‐motion package and a smartphone integrated camera (5 megapixels) with terrestrial laser scanning (TLS) data used to provide a benchmark. To evaluate this approach a 16.2‐megapixel digital camera and an established, commercial, close‐range and semi‐automated software are also employed, and the product of the four combinations of the two types of cameras and software are compared. Results for the river bank survey demonstrate that centimetre‐precision DTMs can be achieved at close range (10 m or less), using a smartphone camera and a fully automated package. Results improve to sub‐centimetre precision with either higher‐resolution images or by applying specific post‐processing techniques to the smartphone DTMs. Application to an entire Alpine alluvial fan system shows the degradation of precision scales linearly with image scale, but that (i) the expected level of precision remains and (ii) difficulties in separating vegetation and sediment cover within the results are similar to those typically found when using other photo‐based techniques and laser scanning systems. Copyright © 2014 John Wiley & Sons, Ltd.     

Monitoring CO2 saturation using time‐lapse amplitude versus offset analysis of 3D seismic data from the Ketzin CO2 storage pilot site,Germany

The injection of CO₂ at the Ketzin pilot site commenced in June 2008 and was terminated in August 2013 after 67 kT had been injected into a saline formation at a depth of 630–650 m. As part of the site monitoring program, four 3D surface seismic surveys have been acquired to date, one baseline and three repeats, of which two were conducted during the injection period, and one during the post‐injection phase. The surveys have provided the most comprehensive images of the spreading CO₂ plume within the reservoir layer. Both petrophysical experiments on core samples from the Ketzin reservoir and spectral decomposition of the 3D time‐lapse seismic data show that the reservoir pore pressure change due to CO₂ injection has a rather minor impact on the seismic amplitudes. Therefore, the observed amplitude anomaly is interpreted to be mainly due to CO₂ saturation. In this study, amplitude versus offset analysis has been applied to investigate the amplitude versus offset response from the top of the sandstone reservoir during the injection and post‐injection phases, and utilize it to obtain a more quantitative assessment of the CO₂ gaseous saturation changes. Based on the amplitude versus offset modelling, a prominent decrease in the intercept values imaged at the top of the reservoir around the injection well is indeed associated solely with the CO₂ saturation increase. Any change in the gradient values, which would, in case it was positive, be the only signature induced by the reservoir pressure variations, has not been observed. The amplitude versus offset intercept change is, therefore, entirely ascribed to CO₂ saturation and used for its quantitative assessment. The estimated CO₂ saturation values around the injection area in the range of 40%–60% are similar to those obtained earlier from pulsed neutron‐gamma logging. The highest values of 80% are found in the second seismic repeat in close vicinity to the injection and observation wells.     

Visco‐acoustic prestack reverse‐time migration based on the time‐space domain adaptive high‐order finite‐difference method

It is important to include the viscous effect in seismic numerical modelling and seismic migration due to the ubiquitous viscosity in an actual subsurface medium. Prestack reverse‐time migration (RTM) is currently one of the most accurate methods for seismic imaging. One of the key steps of RTM is wavefield forward and backward extrapolation and how to solve the wave equation fast and accurately is the essence of this process. In this paper, we apply the time‐space domain dispersion‐relation‐based finite‐difference (FD) method for visco‐acoustic wave numerical modelling. Dispersion analysis and numerical modelling results demonstrate that the time‐space domain FD method has great accuracy and can effectively suppress numerical dispersion. Also, we use the time‐space domain FD method to solve the visco‐acoustic wave equation in wavefield extrapolation of RTM and apply the source‐normalized cross‐correlation imaging condition in migration. Improved imaging has been obtained in both synthetic and real data tests. The migration result of the visco‐acoustic wave RTM is clearer and more accurate than that of acoustic wave RTM. In addition, in the process of wavefield forward and backward extrapolation, we adopt adaptive variable‐length spatial operators to compute spatial derivatives to significantly decrease computing costs without reducing the accuracy of the numerical solution.     

A new approach of dynamic monitoring of 5‐day snow cover extent and snow depth based on MODIS and AMSR‐E data from Northern Xinjiang region

Taking the Northern Xinjiang region as an example, we develop a snow depth model by using the Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E) horizontal and vertical polarization brightness temperature difference data of 18 and 36 GHz bands and in situ snow depth measurements from 20 climatic stations during the snow seasons November–March) of 2002–2005. This article proposes a method to produce new 5‐day snow cover and snow depth images, using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products and AMSR‐E snow water equivalent and daily brightness temperature products. The results indicate that (1) the brightness temperature difference (Tb_18h–Tb_36h) provides the most accurate and precise prediction of snow depth; (2) the snow, land and overall classification accuracies of the new images are separately 89.2%, 77.7% and 87.2% and are much better than those of AMSR‐E or MODIS products (in all weather conditions) alone; (3) the snow classification accuracy increases as snow depth increases; and (4) snow accuracies for different land cover types vary as 88%, 92.3%, 79.7% and 80.1% for cropland, grassland, shrub, and urban and built‐up, respectively. We conclude that the new 5‐day snow cover–snow depth images can provide both accurate cloud‐free snow cover extent and the snow depth dynamics, which would lay a scientific basis for water management and prevention of snow‐related disasters in this dry and cold pastoral area. After validations of the algorithms over other regions with different snow and climate conditions, this method would also be used for monitoring snow cover and snow depth elsewhere in the world. Copyright © 2011 John Wiley & Sons, Ltd.     

Climate–surface–pore‐water interactions on a salt crusted playa: implications for crust pattern and surface roughness development measured using terrestrial laser scanning

Sodium accumulating playas (also termed sodic or natric playas) are typically covered by polygonal crusts with different pattern characteristics, but little is known about the short‐term (hours) dynamics of these patterns or how pore water may respond to or drive changing salt crust patterning and surface roughness. It is important to understand these interactions because playa‐crust surface pore‐water and roughness both influence wind erosion and dust emission through controlling erodibility and erosivity. Here we present the first high resolution (10^?3 m; hours) co‐located measurements of changing moisture and salt crust topography using terrestrial laser scanning (TLS) and infra‐red imagery for Sua Pan, Botswana. Maximum nocturnal moisture pattern change was found on the crests of ridged surfaces during periods of low temperature and high relative humidity. These peaks experienced non‐elastic expansion overnight, of up to 30 mm and up to an average of 1.5 mm/night during the 39 day measurement period. Continuous crusts however showed little nocturnal change in moisture or elevation. The dynamic nature of salt crusts and the complex feedback patterns identified emphasize how processes both above and below the surface may govern the response of playa surfaces to microclimate diurnal cycles. © 2015 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.