scholarly journals StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction

2016 ◽  
Vol 9 (12) ◽  
pp. 4491-4519 ◽  
Author(s):  
Aurélien Gallice ◽  
Mathias Bavay ◽  
Tristan Brauchli ◽  
Francesco Comola ◽  
Michael Lehning ◽  
...  
Keyword(s):  
Source Code ◽  
Stream Temperature ◽  
Object Oriented Programming ◽  
Temperature Prediction ◽  
Uncertainty Estimates ◽  
Physically Based ◽  
Snow Model ◽  
Alpine Catchments ◽  
Alpine Rivers

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash–Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

scholarly journals StreamFlow 1.0: An extension to the spatially distributed snow model Alpine3D for hydrological modeling and deterministic stream temperature prediction

2016 ◽  
Author(s):  
Aurélien Gallice ◽  
Mathias Bavay ◽  
Tristan Brauchli ◽  
Francesco Comola ◽  
Michael Lehning ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Source Code ◽  
Stream Temperature ◽  
Object Oriented Programming ◽  
Temperature Prediction ◽  
Uncertainty Estimates ◽  
Physically Based ◽  
Snow Model ◽  
Alpine Catchments

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as a one of the promising approaches to reduce our uncertainty on future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically-based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface runoff, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash–Sutcliffe efficiency (NSE) of 0.82, and hourly mean temperature with a NSE of 0.78.

scholarly journals Snow model comparison to simulate snow depth evolution and sublimation at point scale in the semi-arid Andes of Chile

2021 ◽  
Author(s):  
Annelies Voordendag ◽  
Marion Réveillet ◽  
Shelley MacDonell ◽  
Stef Lhermitte
Keyword(s):  
Model Calibration ◽  
Model Comparison ◽  
Meteorological Forcing ◽  
Local Point ◽  
Physically Based ◽  
Order Of Magnitude ◽  
Snow Model ◽  
Snow Physics ◽  
Semi Arid

Abstract. Physically-based snow models provide valuable information on snow cover evolution and are therefore key to provide water availability projections. Yet, uncertainties related to snow modelling remain large as a result of differences in the representation of snow physics and meteorological forcing. While many studies focus on evaluating these uncertainties, issues still arise, especially in environments where sublimation is the main ablation process. This study evaluates a case study in the semi-arid Andes of Chile and aims to compare two snow models with different complexities, SNOWPACK and SnowModel, at a local point, over one snow season. Their sensitivity relative i) to physical calibration for albedo and fresh snow density and ii) to forcing perturbation is evaluated based on ensemble approaches. Results indicate larger uncertainty depending on the model calibration than between the two models (even though the significant differences in their physical complexity). We also confirm the importance of albedo parameterization, even though ablation is driven by sublimation. SnowModel is particularly sensitive to this choice as it strongly affects both the sublimation and the melt rates. However, the day of snow-free snow surface is not sensitive to the parameterization as it only varies every eight days. The albedo parameterization of SNOWPACK has stronger consequences on melt at the end of the season leading to a date difference of the end of the season of 41 days. However, despite these differences, the sublimation ratio ranges are in agreement for the two models: 42.7–63.5 % for SnowModel and 51.3 and 64.6 % for SNOWPACK, and are related to the albedo calibration choice for the two models. Finally, the sensitivity of both models to the forcing data was in the same order of magnitude and highly influenced by the precipitation uncertainties.

scholarly journals Snow model comparison to simulate snow depth evolution and sublimation at point scale in the semi-arid Andes of Chile

2021 ◽  
Vol 15 (9) ◽  
pp. 4241-4259
Author(s):  
Annelies Voordendag ◽  
Marion Réveillet ◽  
Shelley MacDonell ◽  
Stef Lhermitte
Keyword(s):  
Model Comparison ◽  
Roughness Length ◽  
Meteorological Forcing ◽  
Local Point ◽  
Physically Based ◽  
Order Of Magnitude ◽  
Snow Model ◽  
Snow Physics ◽  
Semi Arid

Abstract. Physically based snow models provide valuable information on snow cover evolution and are therefore key to provide water availability projections. Yet, uncertainties related to snow modelling remain large as a result of differences in the representation of snow physics and meteorological forcing. While many studies focus on evaluating these uncertainties, no snow model comparison has been done in environments where sublimation is the main ablation process. This study evaluates a case study in the semi-arid Andes of Chile and aims to compare two snow models with different complexities, SNOWPACK and SnowModel, at a local point over one snow season and to evaluate their sensitivity relative to parameterisation and forcing. For that purpose, the two models are forced with (i) the most ideal set of input parameters, (ii) an ensemble of different physical parameterisations, and (iii) an ensemble of biased forcing. Results indicate large uncertainties depending on forcing, the snow roughness length z0, albedo parameterisation, and fresh snow density parameterisation. The uncertainty caused by the forcing is directly related to the bias chosen. Even though the models show significant differences in their physical complexity, the snow model choice is of least importance, as the sensitivity of both models to the forcing data was on the same order of magnitude and highly influenced by the precipitation uncertainties. The sublimation ratio ranges are in agreement for the two models: 36.4 % to 80.7 % for SnowModel and 36.3 % to 86.0 % for SNOWPACK, and are related to the albedo parameterisation and snow roughness length choice for the two models.

Deployment of Mobile Learning Course Materials to Android Powered Mobile Devices

2012 ◽  
Vol 10 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Lee Chao
Keyword(s):  
Mobile Devices ◽  
Teaching And Learning ◽  
Science Curriculum ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Traditional Course ◽  
Course Materials ◽  
Course Material ◽  
Android Market

The objective of this article is to facilitate mobile teaching and learning by providing an alternative course material deployment method. This article suggests a course material deployment platform for small universities or individual instructors. Different from traditional course material deployment methods, the method discussed deploys course materials by using services provided by Android Market. After comparing the traditional course material deployment and the alternative deployment, the author presents strategies to take advantage of Android Market in delivering course materials to mobile devices. Through a case study, this article illustrates the application of these strategies in deploying a class menu for an object-oriented programming course in the computer science curriculum.

scholarly journals Evaluating performances of simplified physically based models for landslide susceptibility

2015 ◽  
Vol 12 (12) ◽  
pp. 13217-13256 ◽  
Author(s):  
G. Formetta ◽  
G. Capparelli ◽  
P. Versace
Keyword(s):  
Landslide Susceptibility ◽  
Goodness Of Fit ◽  
Shallow Landslides ◽  
Model Parameters ◽  
Test Case ◽  
Susceptibility Analysis ◽  
Physically Based ◽  
Private And Public ◽  
Physically Based Models

Abstract. Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with model M3 is the best modeling solution for our test case.

scholarly journals Information processing for Similar Source code using LSH Algorithm

2021 ◽  
Vol 23 (07) ◽  
pp. 23-34
Author(s):  
Mrs. Vani Dave ◽  
◽  
Mr Sanjeev Kumar shukla ◽  
Keyword(s):  
Information Processing ◽  
Execution Time ◽  
Source Code ◽  
Locality Sensitive Hashing ◽  
Source File ◽  
C Language ◽  
Fast Search

In this study, we propose a method to quickly search for similar source files for a given source file as a method to examine the origin of reused code. By outputting not only the same contents but also similar contents, it corresponds to the source file that has been changed during reuse. In addition, locality-sensitive hashing is used to search from a large number of source files, enabling fast search. By this method, it is possible to know the origin of the reused code. A case study was conducted on a library that is being reused written in C language. Some of the changes were unique to the project, and some were no longer consistent with the source files. As a result, it was possible to detect the source files that were reused from among the 200 projects with 92% accuracy. In addition, when we measured the execution time of the search using 4 files, the search was completed within 1 second for each file.

scholarly journals How long can we build it? Ensuring usability of a scientific code base

2021 ◽  
Vol 16 (1) ◽  
pp. 11
Author(s):  
Klaus Rechert ◽  
Jurek Oberhauser ◽  
Rafael Gieschke
Keyword(s):  
Data Management ◽  
Source Code ◽  
Research Data ◽  
Scientific Contribution ◽  
Scientific Publications ◽  
Research Data Management ◽  
Code Base

Software and in particular source code became an important component of scientific publications and henceforth is now subject of research data management.  Maintaining source code such that it remains a usable and a valuable scientific contribution is and remains a huge task. Not all code contributions can be actively maintained forever. Eventually, there will be a significant backlog of legacy source-code. In this article we analyse the requirements for applying the concept of long-term reusability to source code. We use simple case study to identify gaps and provide a technical infrastructure based on emulator to support automated builds of historic software in form of source code.  

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