scholarly journals Time variability and uncertainty in the fraction of young water in a small headwater catchment

2019 ◽  
Vol 23 (10) ◽  
pp. 4333-4347 ◽  
Author(s):  
Michael Paul Stockinger ◽  
Heye Reemt Bogena ◽  
Andreas Lücke ◽  
Christine Stumpp ◽  
Harry Vereecken
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Time Window ◽  
High Sensitivity ◽  
Nutrient Loss ◽  
Time Variability ◽  
Flow Paths ◽  
Relative Contribution ◽  
Sampling Campaign ◽  
The Mean

Abstract. The time precipitation needs to travel through a catchment to its outlet is an important descriptor of a catchment's susceptibility to pollutant contamination, nutrient loss, and hydrological functioning. The fast component of total water flow can be estimated by the fraction of young water (Fyw), which is the percentage of streamflow younger than 3 months. Fyw is calculated by comparing the amplitudes of sine waves fitted to seasonal precipitation and streamflow tracer signals. This is usually done for the complete tracer time series available, neglecting annual differences in the amplitudes of longer time series. Considering inter-annual amplitude differences, we employed a moving time window of 1 year in weekly time steps over a 4.5-year δ18O tracer time series to calculate 189 Fyw estimates and their uncertainty. They were then tested against the following null hypotheses: (1) at least 90 % of Fyw results do not deviate more than ±0.04 (4 %) from the mean of all Fyw results, indicating long-term invariance. Larger deviations would indicate changes in the relative contribution of different flow paths; (2) for any 4-week window, Fyw does not change more than ±0.04, indicating short-term invariance. Larger deviations would indicate a high sensitivity of Fyw to a 1-week to 4-week shift in the start of a 1-year sampling campaign; (3) the Fyw results of 1-year sampling campaigns started in a given calendar month do not change more than ±0.04, indicating seasonal invariance. In our study, all three null hypotheses were rejected. Thus, the Fyw results were time-variable, showed variability in the chosen sampling time, and had no pronounced seasonality. We furthermore found evidence that the 2015 European heat wave and including two winters into a 1-year sampling campaign increased the uncertainty of Fyw. Based on an increase in Fyw uncertainty when the mean adjusted R2 was below 0.2, we recommend further investigations into the dependence of Fyw and its uncertainty to goodness-of-fit measures. Furthermore, while investigated individual meteorological factors did not sufficiently explain variations of Fyw, the runoff coefficient showed a moderate negative correlation of r=-0.50 with Fyw. The results of this study suggest that care must be taken when comparing Fyw of catchments that were based on different calculation periods and that the influence of extreme events and snow must be considered.

scholarly journals Time-variability of the fraction of young water in a small headwater catchment

2019 ◽  
Author(s):  
Michael P. Stockinger ◽  
Heye R. Bogena ◽  
Andreas Lücke ◽  
Christine Stumpp ◽  
Harry Vereecken
Keyword(s):  
Time Series ◽  
Time Window ◽  
High Sensitivity ◽  
Annual Runoff ◽  
Nutrient Loss ◽  
Time Variability ◽  
Short Term ◽  
Sampling Campaign ◽  
The Mean ◽  
One Year

Abstract. The time precipitation needs to travel through a catchment to its outlet is an important descriptor of a catchment's susceptibility to pollutant contamination, nutrient loss and hydrological functioning. The fast component of total water flow can be estimated by the fraction of young water (Fyw) which is the percentage of streamflow younger than three months. Fyw is calculated by comparing the amplitudes of sine waves fitted to seasonal precipitation and streamflow tracer signals. This is usually done for the complete tracer time series available neglecting annual differences in the amplitudes of longer time series. Considering inter-annual amplitude differences, we here employed a moving time window of one-year length in weekly time steps over a 4.5-years δ18O tracer time series to calculate 189 Fyw results. The results were then tested against the following null hypotheses, defining 2 % difference in Fyw as significant based on results of previous studies: (1) Fyw does not deviate more than ±2% from the mean of all Fyw results indicating long-term invariance. Larger deviations would indicate either flow path changes or a change in the relative contribution of different flow paths; (2) for any four-week window Fyw does not change more than ±2 % indicating short-term invariance. Larger deviations would indicate a high sensitivity of Fyw to a 1–4 weeks shift in the start of a one-year sampling campaign; (3) for a given calendar month Fyw does not change more than ±2 % indicating seasonal invariance of Fyw. In our study, all three null hypotheses were rejected. Thus, the Fyw results were time-variable, showed a high variability in the chosen sampling time and had no pronounced seasonality. Based on high short-term variability of Fyw when the mean adjusted R² was below 0.2 we recommend that a low R2 should be regarded as indicating potentially highly uncertain Fyw results. Furthermore, while investigated individual meteorological factors could not sufficiently explain variations of Fyw, the runoff coefficient showed a moderate negative correlation of r = −0.54 with Fyw. This indicated that when annual runoff exceeded precipitation the catchment received the water deficit from storage which is old water causing a decrease in Fyw. The results of this study suggest that care must be taken when comparing Fyw of catchments that were based on different calculation time periods.

SIMULTANEOUS SPECIFICATION TESTING OF MEAN AND VARIANCE STRUCTURES IN NONLINEAR TIME SERIES REGRESSION

2011 ◽  
Vol 27 (4) ◽  
pp. 792-843 ◽  
Author(s):  
Song Xi Chen ◽  
Jiti Gao
Keyword(s):  
Time Series ◽  
Empirical Likelihood ◽  
Goodness Of Fit ◽  
Test Procedure ◽  
Single Pair ◽  
Test Statistic ◽  
Time Series Regression ◽  
Variance Functions ◽  
Mean And Variance ◽  
The Mean

This paper proposes a nonparametric simultaneous test for parametric specification of the conditional mean and variance functions in a time series regression model. The test is based on an empirical likelihood (EL) statistic that measures the goodness of fit between the parametric estimates and the nonparametric kernel estimates of the mean and variance functions. A unique feature of the test is its ability to distribute natural weights automatically between the mean and the variance components of the goodness-of-fit measure. To reduce the dependence of the test on a single pair of smoothing bandwidths, we construct an adaptive test by maximizing a standardized version of the empirical likelihood test statistic over a set of smoothing bandwidths. The test procedure is based on a bootstrap calibration to the distribution of the empirical likelihood test statistic. We demonstrate that the empirical likelihood test is able to distinguish local alternatives that are different from the null hypothesis at an optimal rate.

scholarly journals Improving the Mean and Uncertainty of Ultraviolet Multi-Filter Rotating Shadowband Radiometer In-Situ Calibration Factors: Utilizing Gaussian Process Regression with a New Method to Estimate Dynamic Input Uncertainty

2018 ◽  
Author(s):  
Maosi Chen ◽  
Zhibin Sun ◽  
John M. Davis ◽  
Yan-An Liu ◽  
Chelsea A. Corr ◽  
...  
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Time Window ◽  
Gaussian Process Regression ◽  
New Method ◽  
Input Uncertainty ◽  
In Situ Calibration ◽  
The Mean ◽  
Mean Function

Abstract. To recover the actual responsivity for Ultraviolet Multi-Filter Rotating Shadowband Radiometer (UV-MFRSR), the complex (e.g. unstable, noisy, and with gaps) time series of its in-situ calibration factors (Vo) need to be smoothed. Many smoothing techniques require accurate input uncertainty of the time series. A new method is proposed to estimate the dynamic input uncertainty by examining overall variation and subgroup means within a moving time window. Using this calculated dynamic input uncertainty within Gaussian Process regression (GP) provides the mean and uncertainty functions of the time series. This proposed GP solution was first applied on a synthetic signal and showed significant smaller RMSEs than a Gaussian Process regression performed with constant values of input uncertainty and the mean function. GP was then applied to three UV-MFRSR Vo time series at three ground sites; The method appropriately accounted for variation in slopes, noises, and gaps at all sites. The validation results demonstrated that the agreement between aerosol optical depths (AODs) calculated using Vo determined by the GP mean function and AERONET AODs were consistently better than those calculated using Vo from standard techniques (e.g. moving average). The improved accuracy of in-situ UVMRP Vo values suggests the GP solution is a robust technique for accurate analysis of complex time series and may be applicable to other fields.

REDUCTION OF NON-SPECIFIC SERUM RESPONSES IN HUMAN PITUITARY GONADOTROPHIN RADIOIMMUNOASSAYS

1979 ◽  
Vol 80 (1) ◽  
pp. 59-68 ◽  
Author(s):  
W. M. HUNTER ◽  
J. G. BENNIE
Keyword(s):  
High Sensitivity ◽  
Specific Response ◽  
Response Curves ◽  
Human Pituitary ◽  
Relative Contribution ◽  
Specific Effects ◽  
The Mean ◽  
Specific Material ◽  
Sufficient Magnitude ◽  
Mean Concentration

Serum and plasma from human and domestic animals contain variable amounts of non-specific material(s) which may be mistaken for hormone in assays for human LH and FSH, based upon antisera of high sensitivity and hormonal monospecificity. The non-specific response curves are generally, but not invariably, less steep than those of the hormone standards and endogenous homologous hormones. The levels of non-specific intrusion can be of sufficient magnitude to obscure specific estimations seriously, particularly at low hormone levels, unless the assays are designed to minimize this effect. The non-specific effects could be minimized (but not abolished) by careful optimization of the assays which involved making the response curve as sensitive as possible and incorporating the serum at a final dilution of 1: 2, since further dilution increased the relative contribution of the non-specific substance(s). The optimized assays require only 48 h of total incubation and show a sevenfold increase in the mean concentration of LH between sera from prepubertal children and adults accompanied by a mean threefold difference in the concentration of FSH.

Features of Thrombi and Diagnostic Accuracy of Impedance Plethysmography in Symptomatic and Asymptomatic Deep Vein Thrombosis

1993 ◽  
Vol 70 (02) ◽  
pp. 266-269 ◽  
Author(s):  
Giancarlo Agnelli ◽  
Benilde Cosmi ◽  
Stefano Radicchia ◽  
Franca Veschi ◽  
Enrico Boschetti ◽  
...  
Keyword(s):  
Deep Vein Thrombosis ◽  
Diagnostic Accuracy ◽  
High Sensitivity ◽  
Impedance Plethysmography ◽  
Surveillance Programme ◽  
Vein Thrombosis ◽  
Asymptomatic Patients ◽  
High Prevalence ◽  
The Mean ◽  
Deep Vein

SummaryImpedance plethysmography (IPG) has high sensitivity and specificity in patients with symptomatic deep vein thrombosis (DVT) while it fails to detect asymptomatic DVT. The aim of this study was to determine whether the features of thrombi such as location, size and occlusiveness could explain the different accuracy of IPG in symptomatic and asymptomatic DVT patients. One-hundred and seventeen consecutive outpatients with a clinical suspicion of DVT and 246 consecutive patients undergoing hip surgery were admitted to the study. In symptomatic patients IPG was performed on the day of referral, followed by venography, while in asymptomatic patients IPG was performed as a surveillance programme, followed by bilateral venography.A venography proved DVT was observed in 37% of the symptomatic patients and 34% of the asymptomatic limbs. A significantly higher proportion of proximal DVTs was found in symptomatic patients than in asymptomatic patients (78% vs 46%; p = 0.001). The mean Marder score, taken as an index of thrombus size, was significantly higher in symptomatic patients than in asymptomatic patients (19.0 vs 9.6; p = 0.0001). A significantly higher proportion of occlusive DVTs was observed in symptomatic than in asymptomatic patients (69% vs 36%; p = 0.001).We conclude that the unsatisfactory diagnostic accuracy of IPG in asymptomatic DVT is due to the high prevalence of distal, small and non occlusive thrombi. Such thrombi are unlikely to cause a critical obstruction of the venous outflow and therefore to produce a positive IPG.

Der Sommer und Herbst 2003 aus phänologischer Sicht | Summer and autumn 2003 from a phenological point of view

2004 ◽  
Vol 155 (5) ◽  
pp. 142-145 ◽  
Author(s):  
Claudio Defila
Keyword(s):  
Time Series ◽  
New Record ◽  
Point Of View ◽  
Late Spring ◽  
Mean Deviation ◽  
Leaf Shedding ◽  
The Mean ◽  
Very High ◽  
Selection Of

The record-breaking heatwave of 2003 also had an impact on the vegetation in Switzerland. To examine its influences seven phenological late spring and summer phases were evaluated together with six phases in the autumn from a selection of stations. 30% of the 122 chosen phenological time series in late spring and summer phases set a new record (earliest arrival). The proportion of very early arrivals is very high and the mean deviation from the norm is between 10 and 20 days. The situation was less extreme in autumn, where 20% of the 103 time series chosen set a new record. The majority of the phenological arrivals were found in the class «normal» but the class«very early» is still well represented. The mean precocity lies between five and twenty days. As far as the leaf shedding of the beech is concerned, there was even a slight delay of around six days. The evaluation serves to show that the heatwave of 2003 strongly influenced the phenological events of summer and spring.

scholarly journals The influence of solar wind on extratropical cyclones – Part 1: Wilcox effect revisited

2009 ◽  
Vol 27 (1) ◽  
pp. 1-30 ◽  
Author(s):  
P. Prikryl ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Time Series ◽  
Solar Wind ◽  
Northern Hemisphere ◽  
High Speed ◽  
Coronal Holes ◽  
Extratropical Cyclones ◽  
Sector Boundary ◽  
Speed Solar Wind ◽  
The Mean ◽  
High Speed Solar Wind

Abstract. A sun-weather correlation, namely the link between solar magnetic sector boundary passage (SBP) by the Earth and upper-level tropospheric vorticity area index (VAI), that was found by Wilcox et al. (1974) and shown to be statistically significant by Hines and Halevy (1977) is revisited. A minimum in the VAI one day after SBP followed by an increase a few days later was observed. Using the ECMWF ERA-40 re-analysis dataset for the original period from 1963 to 1973 and extending it to 2002, we have verified what has become known as the "Wilcox effect" for the Northern as well as the Southern Hemisphere winters. The effect persists through years of high and low volcanic aerosol loading except for the Northern Hemisphere at 500 mb, when the VAI minimum is weak during the low aerosol years after 1973, particularly for sector boundaries associated with south-to-north reversals of the interplanetary magnetic field (IMF) BZ component. The "disappearance" of the Wilcox effect was found previously by Tinsley et al. (1994) who suggested that enhanced stratospheric volcanic aerosols and changes in air-earth current density are necessary conditions for the effect. The present results indicate that the Wilcox effect does not require high aerosol loading to be detected. The results are corroborated by a correlation with coronal holes where the fast solar wind originates. Ground-based measurements of the green coronal emission line (Fe XIV, 530.3 nm) are used in the superposed epoch analysis keyed by the times of sector boundary passage to show a one-to-one correspondence between the mean VAI variations and coronal holes. The VAI is modulated by high-speed solar wind streams with a delay of 1–2 days. The Fourier spectra of VAI time series show peaks at periods similar to those found in the solar corona and solar wind time series. In the modulation of VAI by solar wind the IMF BZ seems to control the phase of the Wilcox effect and the depth of the VAI minimum. The mean VAI response to SBP associated with the north-to-south reversal of BZ is leading by up to 2 days the mean VAI response to SBP associated with the south-to-north reversal of BZ. For the latter, less geoeffective events, the VAI minimum deepens (with the above exception of the Northern Hemisphere low-aerosol 500-mb VAI) and the VAI maximum is delayed. The phase shift between the mean VAI responses obtained for these two subsets of SBP events may explain the reduced amplitude of the overall Wilcox effect. In a companion paper, Prikryl et al. (2009) propose a new mechanism to explain the Wilcox effect, namely that solar-wind-generated auroral atmospheric gravity waves (AGWs) influence the growth of extratropical cyclones. It is also observed that severe extratropical storms, explosive cyclogenesis and significant sea level pressure deepenings of extratropical storms tend to occur within a few days of the arrival of high-speed solar wind. These observations are discussed in the context of the proposed AGW mechanism as well as the previously suggested atmospheric electrical current (AEC) model (Tinsley et al., 1994), which requires the presence of stratospheric aerosols for a significant (Wilcox) effect.

scholarly journals Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores

2019 ◽  
Vol 23 (10) ◽  
pp. 4323-4331 ◽  
Author(s):  
Wouter J. M. Knoben ◽  
Jim E. Freer ◽  
Ross A. Woods
Keyword(s):  
Time Series ◽  
Coefficient Of Variation ◽  
Ad Hoc ◽  
Model Performance ◽  
Technical Note ◽  
Mean Flow ◽  
Model Adequacy ◽  
Robust Model ◽  
The Mean ◽  
Adequacy Assessment

Abstract. A traditional metric used in hydrology to summarize model performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41 indicate that a model improves upon the mean flow benchmark – even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment.

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