scholarly journals Information Analysis of Catchment Hydrologic Patterns across Temporal Scales

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Baoxiang Pan ◽  
Zhentao Cong
Keyword(s):  
Epistemic Uncertainty ◽  
Temporal Scale ◽  
Information Analysis ◽  
Energy Correlation ◽  
Temporal Scales ◽  
Correlation Pattern ◽  
Event Scale ◽  
Information Contents ◽  
Input Variables ◽  
Annual Water

Catchment hydrologic cycle takes on different patterns across temporal scales. The interim between event-scale hydrologic process and mean annual water-energy correlation pattern requires further examination to justify self-consistent understanding. In this paper, the temporal scale transition revealed by observation and simulation was evaluated in an information theoretical framework namedAleatory Epistemic Uncertainty Estimation. The Aleatory Uncertainty refers to posterior uncertainty of runoff given the input variables’ observations. The Epistemic Uncertainty refers to the posterior uncertainty increase due to the imperfect observationdecodingin models. Daily hydrometeorological observations in 24 catchments were aggregated from 10 days to 1 year before implementing the information analysis. Estimations of information contents and flows of hydrologic terms across temporal scales were related with the catchments’ seasonality type. It also showed that information distilled by the monthly and annual water balance models applied here did not correspond to that provided by observations around temporal scale from two months to half a year. This calls for a better understanding of seasonal hydrologic mechanism.

scholarly journals Adaptive Multiscale Symbolic-Dynamics Entropy for Condition Monitoring of Rotating Machinery

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1138
Author(s):  
Chunhong Dou ◽  
Jinshan Lin
Keyword(s):  
Symbolic Dynamics ◽  
Spatial Scales ◽  
Approximate Entropy ◽  
Rotating Machinery ◽  
Temporal Scale ◽  
Permutation Entropy ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Vibration Data ◽  
Temporal Statistics

Vibration data from rotating machinery working in different conditions display different properties in spatial and temporal scales. As a result, insights into spatial- and temporal-scale structures of vibration data of rotating machinery are fundamental for describing running conditions of rotating machinery. However, common temporal statistics and typical nonlinear measures have difficulties in describing spatial and temporal scales of data. Recently, statistical linguistic analysis (SLA) has been pioneered in analyzing complex vibration data from rotating machinery. Nonetheless, SLA can examine data in spatial scales but not in temporal scales. To improve SLA, this paper develops symbolic-dynamics entropy for quantifying word-frequency series obtained by SLA. By introducing multiscale analysis to SLA, this paper proposes adaptive multiscale symbolic-dynamics entropy (AMSDE). By AMSDE, spatial and temporal properties of data can be characterized by a set of symbolic-dynamics entropy, each of which corresponds to a specific temporal scale. Afterward, AMSDE is employed to deal with vibration data from defective gears and rolling bearings. Moreover, the performance of AMSDE is benchmarked against five common temporal statistics (mean, standard deviation, root mean square, skewness and kurtosis) and three typical nonlinear measures (approximate entropy, sample entropy and permutation entropy). The results suggest that AMSDE performs better than these benchmark methods in characterizing running conditions of rotating machinery.

Multifractal Properties of Meteorological Drought at Different Time Scales in a Tropical Location

2020 ◽  
pp. 2150007
Author(s):  
Samuel Toluwalope Ogunjo
Keyword(s):  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Temporal Scale ◽  
Fluctuation Analysis ◽  
Monthly Precipitation ◽  
Scaling Exponent ◽  
Economic Activities ◽  
Temporal Scales ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Range Correlations

Tropical countries, like Nigeria, depend on rainfall for agriculture, power generation, transportation and other economic activities. Drought will hinder the performance of these activities, hence, it poses a significant threat to the economy. Understanding fluctuations and structures in droughts will help in forecasting, planning and mitigating its impact on livelihoods. In this study, the multifractal properties of drought at four temporal scales were investigated over different locations across Nigeria. Drought was computed using the standardized precipitation index from monthly precipitation data from 1980 to 2010. Using multifractal detrended fluctuation analysis, meteorological drought was found to have multifractal properties at 1-, 6-, 12- and 24-month temporal scale. The generalized Hurst exponent of drought at different time-scale showed dependence on scaling exponent. Long-range correlations were found to be main source of multifractality at all temporal scales. The multifractal strength increases with increasing temporal scale except for a few locations. The range of spectrum width were found to be 0.306–0.464 and 0.596–0.993 at 1- and 24-month temporal scale, respectively. No significant trend was found in the degree of multifractality across different climatic zones of Nigeria.

scholarly journals Multiple Temporal Scales Assessment in the Hydrological Response of Small Mediterranean Catchments

2019 ◽  
Author(s):  
Josep Fortesa ◽  
Julian García-Comendador ◽  
Aleix Calsamiglia ◽  
Miquel Tomàs-Burguera ◽  
Jérôme Latron ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Biotic Factors ◽  
Hydrological Response ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Temporal Scales ◽  
Event Scale ◽  
Hydrological Variability ◽  
Abiotic And Biotic Factors ◽  
Annual Scale

Mediterranean catchments are characterized by significant spatial and temporal hydrological variability caused by the interaction of natural as well human-induced abiotic and biotic factors. This study investigates the (non-)linearity rainfall-runoff relationship at multiple temporal scales in representative small Mediterranean catchments (i.e., < 10 km2) to achieve a better understanding of the hydrological response. Rainfall-runoff relationship was evaluated in 44 catchments at annual and event –203 events in 12 of these 44 catchments– scales. A linear rainfall-runoff relation was observed at annual scale with higher scatter in pervious than impervious catchments. Larger scattering was observed at event scale, although pervious lithology and agricultural land use promoted significant rainfall-runoff linear relations in winter and spring. These relationships were particularly analysed during five hydrological years in Es Fangar catchment (3.35 km2; Mallorca, Spain) as a temporal downscaling to assess intra-annual variability in which antecedent wetness conditions played a significant role in runoff generation.

scholarly journals Hillslope characteristics as controls of subsurface flow variability

2012 ◽  
Vol 9 (6) ◽  
pp. 6889-6934 ◽  
Author(s):  
S. Bachmair ◽  
M. Weiler
Keyword(s):  
Soil Properties ◽  
Shallow Water ◽  
Water Table ◽  
Explanatory Power ◽  
Measurement Techniques ◽  
Subsurface Flow ◽  
Shallow Water Table ◽  
Temporal Scales ◽  
Event Scale ◽  
Flow Variability

Abstract. Hillslope hydrological dynamics, particularly subsurface flow (SSF), are highly variable and complex. A profound understanding of factors controlling this variability is needed. Therefore we investigated the relationship between variability of shallow water table dynamics and various hillslope characteristics. We ask whether measurable hillslope properties explain patterns of subsurface flow variability. To approach this question shallow water table dynamics of three adjacent large-scale hillslopes were monitored with high spatial and temporal resolution over 18 months. The hillslopes are similar in terms of topography and parent material, but different in vegetation cover (grassland, coniferous forest, and mixed forest). We expect vegetation to be an important driver of water table dynamics at our study site, especially given the minor differences in topography. Various hillslope properties were determined in the field and via GIS analysis: common topography descriptors, well depth, soil properties via slug tests, and several vegetation parameters. Response variables characterizing the water table response per well were calculated for different temporal scales (entire time series, seasonal scale, event scale). Partial correlation analysis and a Random Forest machine learning approach were carried out to assess the explainability of SSF variability by measurable hillslope characteristics. We found a complex interplay of predictors, yet soil properties and topography showed the highest single explanatory power. Surprisingly, vegetation characteristics played a minor role. Solely throughfall and canopy cover exerted a slightly stronger control, especially in summer. Most importantly, the examined hillslope characteristics explained only a small proportion of the observed SSF variability. Consequently there must be additional important drivers not represented by current measurement techniques of the hillslope configuration (e.g. bedrock properties, preferential pathways). We also found interesting differences in explainability of SSF variability among temporal scales and between both forested hillslopes and the grassland hillslope.

Dealing With Knowledge Uncertainties in Pipeline Reliability Based Design and Assessment

2008 ◽  
Author(s):  
Maher Nessim ◽  
Joe Zhou ◽  
Mark Fuglem
Keyword(s):  
Epistemic Uncertainty ◽  
Probability Distributions ◽  
Limit State ◽  
Reliability Estimate ◽  
Formal Approach ◽  
Minimum Requirement ◽  
Reliability Based Design ◽  
Other Information ◽  
Input Variables ◽  
Knowledge Uncertainty

Knowledge uncertainties result from limitations of the data and other information required to define parameters that are used in estimating reliability with respect to a given failure threat. The parameters affected typically represent distribution parameters of input random variables used in the calculation; for example, the mean corrosion growth rate for a given pipeline segment. Knowledge uncertainties are distinct from randomness, which is typically manifested in variations in the basic input parameters affecting a given limit state; for example, variations in the excavator force applied to the pipeline in different impact events. Randomness is reflected in the probability distributions used to model the input variables affected and is automatically built into the reliability estimate. However, the reliability estimate is conditional on the values used for parameters affected by knowledge uncertainty. Since these parameters can take a range of values with different probabilities, knowledge uncertainty is best represented as a distribution or confidence interval on the calculated failure probability. Two approaches are proposed to deal with knowledge uncertainties in Reliability Based Design and Assessment (RBDA) applications in which design and operational choices are accepted if they meet a specified reliability target. The first is a formal approach in which reliability targets must be met with a specified level of confidence (e.g. meet the reliability targets with 90% confidence). The second approach is an informal one in which a single conservative value is used for each parameter affected by knowledge uncertainties. Although this approach relies on the judgment of the user, it has the advantage of being simple. In the context of standardizing RBDA, it is recommended that epistemic uncertainty be identified as an important issue that must be considered in demonstrating compliance. It is also recommended that both formal and informal approaches be permitted as viable means of accounting for epistemic uncertainty. The informal approach should be included as a minimum requirement, whereas the formal approach should be presented as an option. This recommended strategy addresses epistemic uncertainty without creating a significant obstacle to the application of RBDA.

scholarly journals Simulating Destructive and Constructive Morphodynamic Processes in Steep Beaches

2021 ◽  
Vol 9 (1) ◽  
pp. 86
Author(s):  
Katerina Kombiadou ◽  
Susana Costas ◽  
Dano Roelvink
Keyword(s):  
Beach Profile ◽  
Short Term ◽  
Temporal Scales ◽  
Event Scale ◽  
Significant Recovery ◽  
Beach Morphodynamics ◽  
Wave Forcing ◽  
Runup Height ◽  
Calibration Parameters

Short-term beach morphodynamics are typically modelled solely through storm-induced erosion, disregarding post-storm recovery. Yet, the full cycle of beach profile response is critical to simulating and understanding morphodynamics over longer temporal scales. The XBeach model is calibrated using topographic profiles from a reflective beach (Faro Beach, in S. Portugal) during and after the incidence of a fierce storm (Emma) that impacted the area in early 2018. Recovery in all three profiles showed rapid steepening of the beachface and significant recovery of eroded volumes (68–92%) within 45 days after the storm, while berm heights reached 4.5–5 m. Two calibration parameters were used (facua and bermslope), considering two sets of values, one for erosive (Hm0 ≥ 3 m) and one for accretive (Hm0 < 3 m) conditions. A correction of the runup height underestimation by the model in surfbeat mode was necessary to reproduce the measured berm elevation and morphology during recovery. Simulated profiles effectively capture storm erosion, but also berm growth and gradual recovery of the profiles, showing good skill in all three profiles and recovery phases. These experiments will be the basis to formulate event-scale simulations using schematized wave forcing that will allow to calibrate the model for longer-term changes.

scholarly journals Die Zeit in zweidimensionaler Betrachtung

2016 ◽  
Vol 64 (6) ◽  
Author(s):  
Anton Friedrich Koch
Keyword(s):  
Second Order ◽  
Temporal Scale ◽  
Two Dimensional ◽  
Temporal Scales ◽  
One Dimensional ◽  
First Order ◽  
The Past ◽  
The Future

AbstractB-time, i. e. the temporal scale of the B-series of events, is one and the same for all times, while A-times (the temporal scales of A-series) are as many as there are moments of time. This means that A-theorists will have to consider one-dimensional time two-dimensionally: as changing within itself at every moment. The two-dimensional view is here put to service for a meta-compatibilist theory of freedom, a theory, that is, which reconciles freedom, determinism and their first order incompatibility at the second order. Kant’s position is interpreted as meta-compatibilist as well, but as having the drawback of separating time and freedom. In order to appreciate the connection of time and freedom, one has to acknowledge that in free acts the future is determined further according to plan, while at the same time the past is (with nomological necessity) co-determined further in countless unclear and inscrutable ways. A free act thus consumes its own range of freedom by positing retroactively the sufficient causal antecedents for its taking place: It was free before it occurred and is part of nature after.

scholarly journals Validation study of TMPA 3B42V6 in a typical alpine and gorge region: Jinsha River basin, China

2013 ◽  
Vol 13 (12) ◽  
pp. 3479-3492 ◽  
Author(s):  
Y. C. Yang ◽  
G. W. Cheng ◽  
J. H. Fan ◽  
W. P. Li ◽  
J. Sun ◽  
...  
Keyword(s):  
River Basin ◽  
Validation Study ◽  
Probability Of Detection ◽  
Temporal Scale ◽  
Rain Event ◽  
Temporal Scales ◽  
Jinsha River ◽  
Daily Scale ◽  
The Mean

Abstract. Because of density and distribution flaws inherent with in situ rainfall measurements, satellite-based rainfall products, especially the Tropical Rainfall Measuring Mission (TRMM), were expected to offer an alternative or complement for modeling of hydrological processes and water balance analysis. This study aims at evaluating the validity of a standard product, the TRMM Multi-satellite Precipitation Analysis (TMPA) 3B42V6, by comparing it with in situ ground gauge datasets on a typical alpine and gorge region in China, the Jinsha River basin. The validation study involved the performance of the 3B42V6 product on 3 h, daily and monthly temporal scales. Statistical analysis methods were used for rainfall and rain event estimation. The results affirmed that the 3B42V6 product demonstrated increasing accuracy when the temporal scales were increased from 3 h to daily to monthly. The mean correlation coefficient of rainfall time series between the 3B42V6 product and the gauge over the Jinsha River basin reached 0.34 on the 3 h scale, 0.59 on the daily scale, and 0.90 on the monthly scale. The mean probability of detection (POD) of the 3B42V6 product reached 0.34 on the 3 h scale and 0.63 on the daily scale. The 3B42V6 product of 80.4% of stations obtained an acceptable bias (± 25%) over the investigation area. A threshold of nearly 5.0 mm d−1 in daily rainfall intensity split the 3B42V6 product into overestimates (< 5.0 mm d−1) and underestimates (> 5.0 mm d−1). The terrain elements of altitude, longitude, and latitude were the major influencing factors for 3B42V6 performance. In brief, the 3B42V6 dataset has great potential for research on hydrologic processes, especially daily or large temporal scale. As for fine temporal scale applications, such as flood predictions based on a 3 h scale dataset, it is necessary to conduct adjustments or to combine the 3B42V6 product with gauges to be more accurate regarding the issues in the study area or in analogous regions with complicated terrains.

scholarly journals Hillslope characteristics as controls of subsurface flow variability

2012 ◽  
Vol 16 (10) ◽  
pp. 3699-3715 ◽  
Author(s):  
S. Bachmair ◽  
M. Weiler
Keyword(s):  
Soil Properties ◽  
Shallow Water ◽  
Water Table ◽  
Explanatory Power ◽  
Measurement Techniques ◽  
Subsurface Flow ◽  
Shallow Water Table ◽  
Temporal Scales ◽  
Event Scale ◽  
Flow Variability

Abstract. Hillslope hydrological dynamics, particularly subsurface flow (SSF), are highly variable and complex. A profound understanding of factors controlling this variability is needed. Therefore we investigated the relationship between variability of shallow water table dynamics and various hillslope characteristics. We ask whether measurable hillslope properties explain patterns of subsurface flow variability. To approach this question, shallow water table dynamics of three adjacent large-scale hillslopes were monitored with high spatial and temporal resolution over 18 months. The hillslopes are similar in terms of topography and parent material, but different in vegetation cover (grassland, coniferous forest, and mixed forest). We expect vegetation to be an important driver of water table dynamics at our study site, especially given the minor differences in topography. Various hillslope properties were determined in the field and via GIS analysis: common topography descriptors, well depth, soil properties via slug tests, and several vegetation parameters. Response variables characterizing the water table response per well were calculated for different temporal scales (entire time series, seasonal scale, event scale). Partial correlation analysis and a Random Forest machine learning approach were carried out to assess the explainability of SSF variability by measurable hillslope characteristics. We found a complex interplay of predictors, yet soil properties and topography showed the highest single explanatory power. Surprisingly, vegetation characteristics played a minor role. Solely throughfall and canopy cover exerted a slightly stronger control, especially in summer. Most importantly, the examined hillslope characteristics explained only a small proportion of the observed SSF variability. Consequently there must be additional important drivers not represented by current measurement techniques of the hillslope configuration (e.g. bedrock properties, preferential pathways). We also found interesting differences in explainability of SSF variability among temporal scales and between both forested hillslopes and the grassland hillslope.

scholarly journals Prediction of Municipal Solid Waste Generation for Developing Countries in Temporal Scale: A Fuzzy Inference System Approach

2017 ◽  
Vol 19 (3) ◽  
pp. 511-520 ◽  
Keyword(s):  
Municipal Solid Waste ◽  
Solid Waste ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Temporal Scale ◽  
Age Group ◽  
Consumer Expenditure ◽  
Waste Generation ◽  
Inference System ◽  
Input Variables

Fuzzy Inference System (FIS) based prediction models for the Municipal Solid Waste (MSW) generation has been developed in the present work to study the influences of total population, percapita annual income, literacy rate, age group and monthly consumer expenditure on temporal variability of MSW generation for Kolhapur city, India. Ten models were developed considering two input variables at a time to study the effect of the socioeconomic and demographic parameters on MSW generation. Finally, all five input variables were considered in a single model to predict MSW generation in a temporal scale. Result shows that, the model with input variables consumer expenditure and age group was best fitted with highest coefficient of determination (0.985) value and lowest standard error of the estimate (1.562) value for the modelling period. For the design period, models related to consumer expenditure show higher waste generation. Models related to population and age show prediction similar to ‘Kolhapur Municipal Corporations’ prediction. However model with input literacy and income shows very low waste generation prediction. The proposed modelling technique is very useful in MSW generation prediction for a temporal scale in uncertain and random environment globally.

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