Mechanistic insights from emergent landslides in physical experiments

Landslides pose a major natural hazard, and heterogeneous conditions and limited data availability in the field make it difficult to connect mapped landslide inventories to the underlying mass-failure mechanics. To test and build predictive links between landslide observations and mechanics, we monitored 67.89 h of physical experiments in which an incising and laterally migrating river generated landslides by undercutting banks of moist sand. Using overhead photos (every 20 s) and 1-mm-resolution laser topographic scans (every 15–30 min), we quantified the area, width, length, depth, volume, and time of every visible landslide, as well as the scarp angles for those within 3 min prior to a topographic scan. Both the landslide area–frequency distribution and area–volume relationship are consistent with those from field data. Cohesive strength controlled the peak in landslide area–frequency distribution. These results provide experimental support for inverting landslide inventories to recover the mechanical properties of hillslopes, which can then be used to improve hazard predictions.

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The Determinants of Access to Sanitation: The Role of Human Rights and the Challenges of Measurement

Water ◽

10.3390/w13121676 ◽

2021 ◽

Vol 13 (12) ◽

pp. 1676

Author(s):

Rebecca Schiel ◽

Bruce M. Wilson ◽

Malcolm Langford

Keyword(s):

Sustainable Development ◽

Human Rights ◽

Field Data ◽

Data Availability ◽

Regression Analyses ◽

Human Right ◽

Sustainable Development Goal ◽

Development Goal ◽

The Sustainable Development

Ten years after the United Nation’s recognition of the human right to water and sanitation (HRtWS), little is understood about how these right impacts access to sanitation. There is limited identification of the mechanisms responsible for improvements in sanitation, including the international and constitutional recognition of rights to sanitation and water. We examine a core reason for the lack of progress in this field: data quality. Examining data availability and quality on measures of access to sanitation, we arrive at three findings: (1) where data are widely available, measures are not in line with the Sustainable Development Goal (SDG) targets, revealing little about changes in sanitation access; (2) data concerning safe sanitation are missing in more country-year observations than not; and (3) data are missing in the largest proportions from the poorest states and those most in need of progress on sanitation. Nonetheless, we present two regression analyses to determine what effect rights recognition has on improvements in sanitation access. First, the available data are too limited to analyze progress toward meeting SDGs related to sanitation globally, and especially in regions most urgently needing improvements. Second, utilizing more widely available data, we find that rights seem to have little impact on access.

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

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211028870 ◽

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.

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Evaluating the role of deterioration models for condition assessment of sewers

Journal of Hydroinformatics ◽

10.2166/hydro.2015.122 ◽

2015 ◽

Vol 17 (5) ◽

pp. 789-804 ◽

Cited By ~ 18

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.

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Rainfall-runoff modelling of a rocky catchment with limited data availability: Defining prediction limits

Journal of Hydrology ◽

10.1016/j.jhydrol.2010.04.004 ◽

2010 ◽

Vol 387 (1-2) ◽

pp. 128-140 ◽

Cited By ~ 8

Author(s):

R.F. Vázquez ◽

J. Feyen

Keyword(s):

Data Availability ◽

Rainfall Runoff ◽

Limited Data ◽

Prediction Limits

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

Hydrological Sciences Journal ◽

10.1623/hysj.53.3.588 ◽

2008 ◽

Vol 53 (3) ◽

pp. 588-601 ◽

Cited By ~ 89

Author(s):

ALEJANDRA STEHR ◽

PATRICK DEBELS ◽

FRANCISCO ROMERO ◽

HERNAN ALCAYAGA

Keyword(s):

Hydrological Modelling ◽

Data Availability ◽

Limited Data

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Assessment of nitrogen and phosphorus flows in agricultural and urban systems in a small island under limited data availability

The Science of The Total Environment ◽

10.1016/j.scitotenv.2016.08.159 ◽

2017 ◽

Vol 574 ◽

pp. 1521-1532 ◽

Cited By ~ 20

Author(s):

I. Firmansyah ◽

M. Spiller ◽

F.J. de Ruijter ◽

G.J. Carsjens ◽

G. Zeeman

Keyword(s):

Data Availability ◽

Urban Systems ◽

Small Island ◽

Limited Data ◽

Nitrogen And Phosphorus

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Income Risk of German Farms and its Drivers

German Journal of Agricultural Economics ◽

10.30430/69.2020.2.85-107 ◽

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.

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

Review of Network Economics ◽

10.2202/1446-9022.1209 ◽

2010 ◽

Vol 9 (2) ◽

Cited By ~ 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.

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