scholarly journals Mapping surface rock exposures to enhance geohazard susceptibility assessment: a random forest approach

2020 ◽  
Author(s):  
Chris Williams ◽  
Andrew Finlayson ◽  
Romesh Palamakumbura ◽  
Tim Kearsey ◽  
Severine Cornillon ◽  
...  
Keyword(s):  
Random Forest ◽  
Water Reservoir ◽  
Data Availability ◽  
Limited Data ◽  
Sediment Thickness ◽  
Surface Rock ◽  
Natural Rock ◽  
Primary Water ◽  
Rock Exposure ◽  
Sediment Cover

<p>We present the approach taken to map surface rock exposures in upland areas of Scotland. This has been carried out as a means of enhancing the mapping of superficial sediment thickness which has important applications including the assessment of potential geohazard susceptibility. The presented study includes selected test cases that have been constructed prior to scaling up the approach to upland areas across Great Britain (GB).</p><p>The presence of rock at surface acts as a marker of locations with minimal superficial sediment cover (essentially a zero depth). The thickness of superficial sediments across GB are currently estimated based on borehole records which range in both quality and coverage, with limited data particularly for upland regions. Superficial sediment thickness is an integral factor for assessing geohazard processes including landslides. Therefore, by improving datasets detailing rock at surface, we can enhance superficial sediment thickness estimates and enhance the variable inputs to the models used to assess geohazard susceptibility.</p><p>The GB landscape has been subject to a range of different environmental processes through time with its current topography being the subject of glacial erosion through to marine incursions. However, these patterns are not uniform and this results in a range of landscapes. The resulting domains are an important consideration when attempting to model the relationship between the presence and absence of natural rock exposures.  With a wealth of information available across GB including high resolution topography, the resulting (often scale-dependent) geomorphometric derivatives, geological datasets as well as satellite imagery, we are able to consider a range of possible relationships that might exist. We combine these datasets coupled with field validation of rock absence/presence to train a random forest classifier for specific domains with the aim being to identify a way of modelling rock exposure in areas of limited data availability as is the case for many upland areas.</p><p>The methodology and results of the approach for specific process domains will be presented with a specific focus on the Glen Gyle catchment, at the head of Loch Katrine (the primary water reservoir for the city of Glasgow) in the Trossachs National Park, Scotland. This is an area that has been subject to recent landslides which have affected local properties and infrastructure.</p>

Regional Bicycle Network Evaluation and Strategic Planning: A Quantitative Methodological Approach Despite Limited Data Sources for Cycling

2021 ◽  
pp. 036119812110288
Author(s):  
Alex van Dulmen ◽  
Martin Fellendorf
Keyword(s):  
Travel Demand ◽  
Choice Model ◽  
Methodological Approach ◽  
Data Availability ◽  
Data Sources ◽  
Test Case ◽  
Demand Model ◽  
Limited Data ◽  
Demand Models ◽  
Bicycle Infrastructure

In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.

scholarly journals Evaluating the role of deterioration models for condition assessment of sewers

2015 ◽  
Vol 17 (5) ◽  
pp. 789-804 ◽  
Author(s):  
Marius Møller Rokstad ◽  
Rita Maria Ugarelli
Keyword(s):  
Failure Modes ◽  
Structural Condition ◽  
Data Availability ◽  
Limited Data ◽  
Sewer Pipes ◽  
Explanatory Variables ◽  
Deterioration Model ◽  
Sewer Rehabilitation ◽  
Inspection Data

Ensuring reliable structural condition of sewers is an important criterion for sewer rehabilitation decisions. Deterioration models applied to sewer pipes support the rehabilitation planning by means of prioritising pipes according to their current and predicted structural status. There is a benefit in applying such models if sufficient inspection data for calibration, an appropriate deterioration model, and adequate covariates to explain the variability in the conditions are available. In this paper it is discussed up to what level the application of sewer deterioration models can be beneficial under limited data availability. The findings show that the indirect nature of the explanatory covariates which are commonly used in sewer deterioration models makes it difficult to harness any benefit from modelling sewer conditions at a network level, but that the deterioration model application still may be beneficial for prioritising inspection candidates. The prediction power of the current sewer deterioration models is limited by the adequacy of the explanatory variables available, and by the fact that different failure modes are mixed in the aggregated condition class, and not modelled explicitly.

Hydrological modelling with SWAT under conditions of limited data availability: evaluation of results from a Chilean case study

2008 ◽  
Vol 53 (3) ◽  
pp. 588-601 ◽  
Author(s):  
ALEJANDRA STEHR ◽  
PATRICK DEBELS ◽  
FRANCISCO ROMERO ◽  
HERNAN ALCAYAGA
Keyword(s):  
Hydrological Modelling ◽  
Data Availability ◽  
Limited Data

Income Risk of German Farms and its Drivers

2020 ◽  
Vol 69 (2) ◽  
pp. 85-107
Author(s):  
Christoph Duden
Keyword(s):  
Data Availability ◽  
Risk Exposure ◽  
Individual Risk ◽  
Farm Income ◽  
Future Research ◽  
Limited Data ◽  
Income Risk ◽  
Absolute Level ◽  
Farm Accountancy Data Network ◽  
Farm Types

The analysis of income risk is the basis for successful whole farm risk management. The measurement of risks helps to objectively assess the farms’ individual risk exposure. However, due to limited data availability, comprehensive overall risk analyses are often scarce, e.g. for Germany. The present study analyses risk exposure for more than 3,000 farms in Germany in the period 1996/97-2015/16 on the basis of the national Farm Accountancy Data Network (FADN). Our results show that (i) risk exposure is heterogeneous and that fluctuations and particularly large decreases in farm income are rarely attributable to individual risk components (e. g. prices or yields), (ii) farm income risk has been higher in the period after 2007 for many farms, especially arable and dairy farms, (iii) while the income risk in dairy farming increased, it is still lower than that of most other farm types in the period 2006/07-2015/16, (iv) the for-mation of expected values has a significant influence on the absolute level of the measured risk and should be given more attention in future research.

scholarly journals Overcoming Data Limitations in Nonparametric Benchmarking: Applying PCA-DEA to Natural Gas Transmission

2010 ◽  
Vol 9 (2) ◽  
Author(s):  
Maria Nieswand ◽  
Astrid Cullmann ◽  
Anne Neumann
Keyword(s):  
Natural Gas ◽  
Optimization Problem ◽  
Original Data ◽  
Data Availability ◽  
Efficiency Evaluation ◽  
Limited Data ◽  
Data Limitations ◽  
Specific Performance ◽  
Natural Gas Transmission ◽  
Regulated Industries

We empirically demonstrate a practical approach of efficiency evaluation with limited data availability in some regulated industries. We apply PCA-DEA for radial efficiency measurement to U.S. natural gas transmission companies in 2007. PCA-DEA reduces dimensions of the optimization problem while maintaining most of the variation in the original data. Our results suggest that the methodology reduces the probability of over-estimation of individual firm-specific performance.

scholarly journals Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5488
Author(s):  
Daniel Vassallo ◽  
Raghavendra Krishnamurthy ◽  
Thomas Sherman ◽  
Harindra J. S. Fernando
Keyword(s):  
Wind Speed ◽  
Random Forest ◽  
Great Plains ◽  
Wind Farms ◽  
Data Availability ◽  
Training Data ◽  
Forecasting Accuracy ◽  
Wind Speed Forecasting ◽  
Atmospheric Radiation Measurement ◽  
Model Versus

Although the random forest (RF) model is a powerful machine learning tool that has been utilized in many wind speed/power forecasting studies, there has been no consensus on optimal RF modeling strategies. This study investigates three basic questions which aim to assist in the discernment and quantification of the effects of individual model properties, namely: (1) using a standalone RF model versus using RF as a correction mechanism for the persistence approach, (2) utilizing a recursive versus direct multi-step forecasting strategy, and (3) training data availability on model forecasting accuracy from one to six hours ahead. These questions are investigated utilizing data from the FINO1 offshore platform and Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) C1 site, and testing results are compared to the persistence method. At FINO1, due to the presence of multiple wind farms and high inter-annual variability, RF is more effective as an error-correction mechanism for the persistence approach. The direct forecasting strategy is seen to slightly outperform the recursive strategy, specifically for forecasts three or more steps ahead. Finally, increased data availability (up to ∼8 equivalent years of hourly training data) appears to continually improve forecasting accuracy, although changing environmental flow patterns have the potential to negate such improvement. We hope that the findings of this study will assist future researchers and industry professionals to construct accurate, reliable RF models for wind speed forecasting.

scholarly journals Evaluating Groundwater Management Sustainability under Limited Data Availability in Semiarid Zones

Water ◽  
2015 ◽  
Vol 7 (12) ◽  
pp. 4305-4322 ◽  
Author(s):  
Javier Senent-Aparicio ◽  
Julio Pérez-Sánchez ◽  
José García-Aróstegui ◽  
Alicia Bielsa-Artero ◽  
Juan Domingo-Pinillos
Keyword(s):  
Groundwater Management ◽  
Data Availability ◽  
Limited Data

Seismic Response of Dam-Sediment-Water on Fluid-Solid Coupling

2013 ◽  
Vol 353-356 ◽  
pp. 2645-2651
Author(s):  
Yi Zhi Yan ◽  
Chang Xin Xiong ◽  
Zhi Min Su
Keyword(s):  
Porous Medium ◽  
Seismic Response ◽  
Compressible Fluid ◽  
Water Reservoir ◽  
Elastic Solid ◽  
Hydrodynamic Pressure ◽  
Calculation Model ◽  
Sediment Thickness ◽  
Two Phase ◽  
Model Based

Studying the important effects of sediments on the seismic response of dams ,This paper established the calculation model based on regarding the water reservoir as compressible fluid ,the dam and the foundation as an elastic solid, the sediment as Liquid-Solid two-phase porous medium. The results showed that the sediment thickness and properties have important effects on the dam seismic. Increasing the thickness of sediment ,the seismic response of acceleration significantly decreased, the hydrodynamic pressure significantly reduced , which is benefited to the safety of the dam.

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