Technical note: An improved discharge sensitivity metric for young water fractions

Abstract. Recent virtual and experimental investigations have shown that the young water fraction Fyw (i.e. the proportion of catchment outflow younger than circa 2–3 months) increases with discharge in most catchments. The discharge sensitivity of Fyw has been defined as the rate of increase in Fyw with increasing discharge (Q) and has been estimated by the linear regression slope between Fyw and Q, hereafter called DS(Q). The combined use of both metrics, Fyw and DS(Q), provides a promising method for catchment inter-comparison studies that seek to understand streamflow generation processes. Here we explore the discharge sensitivity of Fyw in the intensively sampled small Mediterranean research catchment Can Vila. Intensive sampling of high flows at Can Vila allows young water fractions to be estimated for the far upper tail of the flow frequency distribution. These young water fractions converge toward 1 at the highest flows, illustrating a conceptual limitation in the linear regression method for estimating DS(Q) as a metric of discharge sensitivity: Fyw cannot grow with discharge indefinitely, since the fraction of young water in discharge can never be larger than 1. Here we propose to quantify discharge sensitivity by the parameter of an exponential-type equation that expresses how Fyw varies with discharge. The exponential parameter (Sd) approximates DS(Q) at moderate discharges where Fyw is well below 1; however, the exponential equation and its discharge sensitivity metric better capture the non-linear relationship between Fyw and Q and are robust with respect to changes in the range of sampled discharges, allowing comparisons between catchments with strongly contrasting flow regimes.

Download Full-text

Technical note: An improved discharge sensitivity metric for young water fractions

10.5194/hess-2019-447 ◽

2019 ◽

Author(s):

Francesc Gallart ◽

Jana von Freyberg ◽

María Valiente ◽

James Kirchner ◽

Pilar Llorens ◽

...

Keyword(s):

Linear Regression ◽

Type Equation ◽

Technical Note ◽

Experimental Investigations ◽

Linear Regression Method ◽

Exponential Parameter ◽

Water Fraction ◽

Combined Use ◽

Rate Of Increase ◽

Water Fractions

Abstract. Recent virtual and experimental investigations have shown that the young water fraction Fyw (i.e. the proportion of catchment outflow younger than circa 2–3 months) increases with discharge in most catchments. The discharge sensitivity of Fyw has been defined as the rate of increase in Fyw with increasing discharge (Q), and has been estimated by the linear regression slope between Fyw and Q, hereafter called DS(Q). The combined use of both metrics, Fyw and DS(Q), provides a promising method for catchment inter-comparison studies that seek to understand streamflow generation processes. Here we explore the discharge sensitivity of Fyw in the intensively sampled small Mediterranean research catchment Can Vila. Intensive sampling of high flows at Can Vila allows young water fractions to be estimated for the far upper tail of the flow frequency distribution. These young water fractions converge toward 1 at the highest flows, illustrating a conceptual limitation in the linear regression method for estimating DS(Q) as a metric of discharge sensitivity: Fyw cannot grow with discharge indefinitely, since the fraction of young water in discharge can never be larger than 1. Here we propose to quantify discharge sensitivity by the parameter of an exponential-type equation expressing how Fyw varies with discharge. The exponential parameter (Sd) approximates DS(Q) at moderate discharges where Fyw is well below 1; however, the exponential equation and its discharge sensitivity metric better capture the non-linear relationship between Fyw and Q and are robust with respect to changes in the range of sampled discharges, allowing comparisons between catchments with strongly contrasting flow regimes.

Download Full-text

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i6.255 ◽

2018 ◽

Vol 6 (6) ◽

pp. 119

Author(s):

Mohammad Shohidul Islam ◽

Sultana Easmin Siddika ◽

S M Injamamul Haque Masum

Keyword(s):

Linear Regression ◽

Correlation Coefficients ◽

Rain Gauge ◽

Regression Method ◽

Linear Regression Method ◽

Climate Data ◽

Rainfall Forecasting ◽

Statistical Parameters ◽

Time Duration ◽

Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

Download Full-text

An alternative model of the vibronic coupling in octahedral complexes

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19881134 ◽

1988 ◽

Vol 53 (6) ◽

pp. 1134-1140

Author(s):

Martin Breza ◽

Peter Pelikán

Keyword(s):

Linear Regression ◽

Alternative Model ◽

Potential Surface ◽

Analytical Formula ◽

Coupling Model ◽

Regression Method ◽

Vibronic Coupling ◽

Linear Regression Method ◽

Active Systems ◽

Jahn Teller

It is suggested that for some transition metal hexahalo complexes, the Eg-(a1g + eg) vibronic coupling model is better suited than the classical T2g-(a1g + eg) model. For the former, alternative model, the potential constants in the analytical formula are evaluated from the numerical map of the adiabatic potential surface by using the linear regression method. The numerical values for 29 hexahalo complexes of the 1st row transition metals are obtained by the CNDO/2 method. Some interesting trends of parameters of such Jahn-Teller-active systems are disclosed.

Download Full-text

Research on the viscosity of stabilized emulsions in different pipe diameters using pressure drop and phase inversion

Experimental and Computational Multiphase Flow ◽

10.1007/s42757-020-0102-2 ◽

2021 ◽

Author(s):

Jose Plasencia ◽

Nathanael Inkson ◽

Ole Jørgen Nydal

Keyword(s):

Pressure Drop ◽

Salt Water ◽

Flow Behavior ◽

Turbulent Viscosity ◽

Relative Viscosity ◽

Cfd Modeling ◽

Water Fraction ◽

Water Fractions ◽

Oil Emulsions ◽

Mixture Velocity

AbstractThis paper reports experimental research on the flow behavior of oil-water surfactant stabilized emulsions in different pipe diameters along with theoretical and computational fluid dynamics (CFD) modeling of the relative viscosity and inversion properties. The pipe flow of emulsions was studied in turbulent and laminar conditions in four pipe diameters (16, 32, 60, and 90 mm) at different mixture velocities and increasing water fractions. Salt water (3.5% NaCl w/v, pH = 7.3) and a mineral oil premixed with a lipophilic surfactant (Exxsol D80 + 0.25% v/v of Span 80) were used as the test fluids. The formation of water-in-oil emulsions was observed from low water fractions up to the inversion point. After inversion, unstable water-in-oil in water multiple emulsions were observed under different flow regimes. These regimes depend on the mixture velocity and the local water fraction of the water-in-oil emulsion. The eddy turbulent viscosity calculated using an elliptic-blending k-ε model and the relative viscosity in combination act to explain the enhanced pressure drop observed in the experiments. The inversion process occurred at a constant water fraction (90%) and was triggered by an increase of mixture velocity. No drag reduction effect was detected for the water-in-oil emulsions obtained before inversion.

Download Full-text

The Accuracy Assessment of Weapon System Using Grey Linear Regression Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.268-270.1809 ◽

2012 ◽

Vol 268-270 ◽

pp. 1809-1813

Author(s):

Dai Yu Zhang ◽

Bao Wei Song ◽

Zhou Quan Zhu

Keyword(s):

Linear Regression ◽

Fuzzy Theory ◽

Accuracy Assessment ◽

Regression Method ◽

Small Sample ◽

Easy Access ◽

Linear Regression Method ◽

Grey Theory ◽

Weapon System ◽

Complex Engineering

The accuracy assessment of weapon system is always a complex engineering. How to make the most of the information given in only a few tests and obtain reasonable estimate is always a problem. Based on the fuzzy theory and grey theory, a grey linear regression method is presented. From the numerical example, we can see that this method provides an easy access to deal with data in small sample case and may have potential use in the analysis of weapon performance.

Download Full-text

Demineralization Depth Using QLF and a Novel Image Processing Software

International Journal of Dentistry ◽

10.1155/2010/958264 ◽

2010 ◽

Vol 2010 ◽

pp. 1-7 ◽

Cited By ~ 8

Author(s):

Jun Wu ◽

Zachary R. Donly ◽

Kevin J. Donly ◽

Steven Hackmyer

Keyword(s):

Image Processing ◽

Linear Regression ◽

Polarized Light ◽

Region Of Interest ◽

Linear Regression Method ◽

Percent Loss ◽

Significant Linear Correlation ◽

Processing Software ◽

Image Processing Software ◽

Imagej Software

Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model wasY=0.32X+0.17, whereXwas the percent loss of fluorescence andYwas the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating theP-value=.0014. TheFtest for the entire model was 62.86, which shows theP-value=.0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization.

Download Full-text

Perancangan Aplikasi Prediksi Jumlah Pendaftar Siswa Baru Dengan Metode Regresi Linier (Studi Kasus: SMA RK Deli Murni Bandar Baru)

Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) ◽

10.32672/jnkti.v3i3.2520 ◽

2020 ◽

Vol 3 (3) ◽

pp. 330-334

Author(s):

Novita Ria Lase ◽

Fristi Riandari

Keyword(s):

Linear Regression ◽

Regression Method ◽

Point Of View ◽

Computational Techniques ◽

Linear Regression Method ◽

Simple Linear Regression ◽

Tuition Fees ◽

Use Of Data ◽

New Students ◽

New Student

The problem of the SMA RK Deli Murni Bandar Baru school is to predict how many facilities that need to be provided for new students such as chairs, tables and others. This study discusses the prediction of the number of new student registrants at SMA RK Deli Murni Bandar Baru based on the amount of tuition fees using a simple linear regression method. From a commercial point of view, the use of data mining can be used to handle the explosion of data volumes, using computational techniques can be used to produce information needed which is an asset that can increase the competitiveness of an institution. Prediction is almost the same as classification and estimation, except that in the prediction the value of the results will be in the future. This system can be used to predict the number of applicants in the following year to help the school. The advantage is that this simple linear regression method is very simple so that it is easy to calculate and use. Saves the time needed to solve problems, especially those that are very complex.

Download Full-text