The availability of in situ snow water equivalent (SWE), snowmelt and run-off measurements is still very limited especially in remote areas as the density of operational stations and field ...observations is often scarce and usually costly, labour-intense and/or risky. With remote sensing products, spatially distributed information on snow is potentially available, but often lacks the required spatial or temporal requirements for hydrological applications. For the assurance of a high spatial and temporal resolution, however, it is often necessary to combine several methods like Earth Observation (EO), modelling and in situ approaches. Such a combination was targeted within the business applications demonstration project SnowSense (2015–2018), co-funded by the European Space Agency (ESA), where we designed, developed and demonstrated an operational snow hydrological service. During the run-time of the project, the entire service was demonstrated for the island of Newfoundland, Canada. The SnowSense service, developed during the demonstration project, is based on three pillars, including (i) newly developed in situ snow monitoring stations based on signals of the Global Navigation Satellite System (GNSS); (ii) EO snow cover products on the snow cover extent and on information whether the snow is dry or wet; and (iii) an integrated physically based hydrological model. The key element of the service is the novel GNSS based in situ sensor, using two static low-cost antennas with one being mounted on the ground and the other one above the snow cover. This sensor setup enables retrieving the snow parameters SWE and liquid water content (LWC) in the snowpack in parallel, using GNSS carrier phase measurements and signal strength information. With the combined approach of the SnowSense service, it is possible to provide spatially distributed SWE to assess run-off and to provide relevant information for hydropower plant management in a high spatial and temporal resolution. This is particularly needed for so far non, or only sparsely equipped catchments in remote areas. We present the results and validation of (i) the GNSS in situ sensor setup for SWE and LWC measurements at the well-equipped study site Forêt Montmorency near Quebec, Canada and (ii) the entire combined in situ, EO and modelling SnowSense service resulting in assimilated SWE maps and run-off information for two different large catchments in Newfoundland, Canada.
For numerous hydrological applications, information on snow water equivalent (SWE) and snow liquid water content (LWC) are fundamental. In situ data are much needed for the validation of model and ...remote sensing products; however, they are often scarce, invasive, expensive, or labor‐intense. We developed a novel nondestructive approach based on Global Positioning System (GPS) signals to derive SWE, snow height (HS), and LWC simultaneously using one sensor setup only. We installed two low‐cost GPS sensors at the high‐alpine site Weissfluhjoch (Switzerland) and processed data for three entire winter seasons between October 2015 and July 2018. One antenna was mounted on a pole, being permanently snow‐free; the other one was placed on the ground and hence seasonally covered by snow. While SWE can be derived by exploiting GPS carrier phases for dry‐snow conditions, the GPS signals are increasingly delayed and attenuated under wet snow. Therefore, we combined carrier phase and signal strength information, dielectric models, and simple snow densification approaches to jointly derive SWE, HS, and LWC. The agreement with the validation measurements was very good, even for large values of SWE (>1,000 mm) and HS (> 3 m). Regarding SWE, the agreement (root‐mean‐square error (RMSE); coefficient of determination (R2)) for dry snow (41 mm; 0.99) was very high and slightly better than for wet snow (73 mm; 0.93). Regarding HS, the agreement was even better and almost equally good for dry (0.13 m; 0.98) and wet snow (0.14 m; 0.95). The approach presented is suited to establish sensor networks that may improve the spatial and temporal resolution of snow data in remote areas.
Key Points
Snow water equivalent, liquid water content, and snow height were simultaneously derived with one sensor setup only
This continuous and nondestructive approach for bulk snow cover properties determination is based on GPS signals travelling through snowpack
The correlation with validation data for three entire winter seasons encompassing dry‐snow accumulation and wet‐snow melting periods is high
Snow water equivalent (SWE) can be measured using low-cost Global
Navigation Satellite System (GNSS) sensors with one antenna placed below the
snowpack and another one serving as a reference above ...the snow. The
underlying GNSS signal-based algorithm for SWE determination for dry- and
wet-snow conditions processes the carrier phases and signal strengths and
additionally derives liquid water content (LWC) and snow depth (HS). So far,
the algorithm was tested intensively for high-alpine conditions with
distinct seasonal accumulation and ablation phases. In general, snow
occurrence, snow amount, snow density and LWC can vary considerably with
climatic conditions and elevation. Regarding alpine regions, lower
elevations mean generally earlier and faster melting, more rain-on-snow
events, and shallower snowpack. Therefore, we assessed the applicability of
the GNSS-based SWE measurement at four stations along a steep elevation
gradient (820, 1185, 1510 and 2540 m a.s.l.) in the eastern Swiss Alps
during two winter seasons (2018–2020). Reference data of SWE, LWC and HS
were collected manually and with additional automated sensors at all
locations. The GNSS-derived SWE estimates agreed very well with manual
reference measurements along the elevation gradient, and the accuracy
(RMSE = 34 mm, RMSRE = 11 %) was similar under wet- and dry-snow
conditions, although significant differences in snow density and
meteorological conditions existed between the locations. The GNSS-derived
SWE was more accurate than measured with other automated SWE sensors.
However, with the current version of the GNSS algorithm, the determination
of daily changes of SWE was found to be less suitable compared to manual
measurements or pluviometer recordings and needs further refinement. The
values of the GNSS-derived LWC were robust and within the precision of the
manual and radar measurements. The additionally derived HS correlated well
with the validation data. We conclude that SWE can reliably be determined
using low-cost GNSS sensors under a broad range of climatic conditions, and
LWC and HS are valuable add-ons.
Near-field antenna measurements can be efficiently performed with Unmanned Aerial Vehicles (UAVs). An accurate knowledge of the position of the UAV is needed for determination of the 3D antenna ...pattern. In this paper, we perform a Real-Time Kinematic (RTK) positioning of UAVs with Global Navigation Satellite System (GNSS) signals and assess the accuracy with a laser tracker that provides ranging measurements with a precision of up to 16μm. The measurement results show that the positioning solutions of the GNSS RTK system and of the Laser tracker agree within a few centimeters. This accuracy is also correctly indicated by the self-assessment of the RTK system.
Results of an international campaign to photometrically monitor the unique pre–main‐sequence eclipsing object KH 15D are reported. An updated ephemeris for the eclipse is derived that incorporates a ...slightly revised period of 48.36 days. There is some evidence that the orbital period is actually twice that value, with two eclipses occurring per cycle. The extraordinary depth (∼3.5 mag) and duration (∼18 days) of the eclipse indicate that it is caused by circumstellar matter, presumably the inner portion of a disk. The eclipse has continued to lengthen with time, and the central brightness reversals are not as extreme as they once were.V−RandV−Icolors indicate that the system is slightly bluer near minimum light. Ingress and egress are remarkably well modeled by the passage of a knife edge across a limb‐darkened star. Possible models for the system are briefly discussed.
Model-Based System Architecture Tim Weilkiens, Jesko G. Lamm, Stephan Roth, Markus Walker
2015, 2015-11-02T00:00:00, 2015-10-12, 2015-10-26
eBook
Presents modeling approaches that can be performed in SysML and other modeling languages This book combines the emerging discipline of systems architecting with model- based approaches using SysML. ...The early chapters of the book provide the fundamentals of systems architecting; discussing what systems architecting entails and how it benefits systems engineering. Model-based systems engineering is then defined, and its capabilities to develop complex systems on time and in a feasible quality are discussed. The remainder of the book covers important topics such as: architecture descriptions; architecture patterns; perspectives, viewpoints, views and their relation to system architecture; the roles of a system architect, their team, and stakeholders; systems architecting processes; agile approaches to systems architecting; variant modeling techniques; architecture frameworks; and architecture assessment. The book's organization allows experts to read the chapters out of sequence. Novices can read the chapters sequentially to gain a systematic introduction to system architecting. Model-Based System Architecture: * Provides comprehensive coverage of the Functional Architecture for Systems (FAS) method created by the authors and based on common MBSE practices * Covers architecture frameworks, including the System of Systems, Zachman Frameworks, TOGAF®, and more * Includes a consistent example system, the "Virtual Museum Tour" system, that allows the authors to demonstrate the systems architecting concepts covered in the book Model-Based System Architecture is a comprehensive reference for system architects and systems engineers in technology companies. This book will also serve as a reference to students and researchers interested in functional architectures. Tim Weilkiens is the CEO at the German consultancy oose Innovative Informatik and co-author of the SysML specification. He has introduced model-based systems engineering to a variety of industry sectors. He is author of several books about modeling and the MBSE methodology SYSMOD. Jesko G. Lamm is a Senior Systems Engineer at Bernafon, a Swiss manufacturer for hearing instruments. With Tim Weilkiens, Jesko G. Lamm founded the Functional Architectures working group of the German chapter of INCOSE. Stephan Roth is a coach, consultant, and trainer for systems and software engineering at the German consultancy oose Innovative Informatik. He is a state-certified technical assistant for computer science from Physikalisch- Technische Lehranstalt (PTL) Wedel and a certified systems engineer (GfSE)®- Level C. Markus Walker works at Schindler Elevator in the research and development division as elevator system architect. He is an INCOSE Certified Systems Engineering Professional (CSEP) and is engaged in the committee of the Swiss chapter of INCOSE.
The Snow Water Equivalent (SWE) is a key parameter for hydrological applications. In this paper, we describe a novel snow monitoring station that determines SWE solely from differential carrier phase ...measurements of both GPS and Galileo satellites. The SWE estimates are compared with several traditional sensors to demonstrate the achievable performance. The measurement results also show that just 4 Galileo satellites reduce the combined fixing time of RTK positioning by up to 3 minutes.
Results of an international campaign to photometrically monitor the unique
pre-main sequence eclipsing object KH 15D are reported. An updated ephemeris
for the eclipse is derived that incorporates a ...slightly revised period of 48.36
d. There is some evidence that the orbital period is actually twice that value,
with two eclipses occurring per cycle. The extraordinary depth (~3.5 mag) and
duration (~18 days) of the eclipse indicate that it is caused by circumstellar
matter, presumably the inner portion of a disk. The eclipse has continued to
lengthen with time and the central brightness reversals are not as extreme as
they once were. V-R and V-I colors indicate that the system is slightly bluer
near minimum light. Ingress and egress are remarkably well modeled by the
passage of a knife-edge across a limb-darkened star. Possible models for the
system are briefly discussed.
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