scholarly journals A Cumulative Rainfall Function for Subhourly Design Storm in Mediterranean Urban Areas

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Marco Carbone ◽  
Michele Turco ◽  
Giuseppe Brunetti ◽  
Patrizia Piro
Keyword(s):  
Urban Areas ◽  
Goodness Of Fit ◽  
Nonlinear Least Squares ◽  
Least Square ◽  
Rainfall Time Series ◽  
Storm Events ◽  
Design Storm ◽  
Double Exponential ◽  
Two Parameters ◽  
Precipitation Records

Design storms are very useful in many hydrological and hydraulic practices and are obtained from statistical analysis of precipitation records. However considering design storms, which are often quite unlike the natural rainstorms, may result in designing oversized or undersized drainage facilities. For these reasons, in this study, a two-parameter double exponential function is proposed to parameterize historical storm events. The proposed function has been assessed against the storms selected from 5-year rainfall time series with a 1-minute resolution, measured by three meteorological stations located in Calabria, Italy. In particular, a nonlinear least square optimization has been used to identify parameters. In previous studies, several evaluation methods to measure the goodness of fit have been used with excellent performances. One parameter is related to the centroid of the rain distribution; the second one is related to high values of the standard deviation of the kurtosis for the selected events. Finally, considering the similarity between the proposed function and the Gumbel function, the two parameters have been computed with the method of moments; in this case, the correlation values were lower than those computed with nonlinear least squares optimization but sufficiently accurate for designing purposes.

scholarly journals A stochastic design rainfall generator based on copulas and mass curves

2010 ◽  
Vol 14 (12) ◽  
pp. 2429-2442 ◽  
Author(s):  
S. Vandenberghe ◽  
N. E. C. Verhoest ◽  
E. Buyse ◽  
B. De Baets
Keyword(s):  
Return Period ◽  
Goodness Of Fit ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Point Scale ◽  
Design Studies ◽  
Design Storm ◽  
Practical Usefulness ◽  
Storm Duration ◽  
Scale Design

Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate point-scale design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of a set of statistically identical design storm and rainfall-runoff modelling.

scholarly journals A Comparison between Conceptual and Physically Based Models in Predicting the Hydrological Behavior of Green Roofs

Proceedings ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 8
Author(s):  
Mirka Mobilia ◽  
Antonia Longobardi
Keyword(s):  
Urban Areas ◽  
Goodness Of Fit ◽  
Green Roof ◽  
Green Roofs ◽  
Storm Events ◽  
Climate Conditions ◽  
Hourly Data ◽  
Test Beds ◽  
Fit Indexes ◽  
Flooding Risk

The evolving climate conditions contribute to increase flooding risk in urban areas. Green roofs are effective tools for controlling and managing stormwater runoff. With the aim to prevent these damaging events, an accurate modelling of the response of green roofs to storm events becomes essential. The goal of this research is to compare the accuracy of two hydrological models in predicting the behavior of two green roof test beds in terms of runoff production. The test beds are located in the campus of University of Salerno, in a typical Mediterranean climate and they differ in the composition of the drainage layer. The selected models are the Storm Water management model (SWMM) model and the Nash model. They have been calibrated against hourly data of 25 rainfall-runoff events observed at the experimental site and compared using a number of goodness of fit indexes. The Nash cascade model aims to be a very simple but effective approach. No substantial differences were observed in the behavior of the two green roof plots, though they differ in their design characteristics. Finally, the existence of a relationship between the errors and the rainfall characteristics has been found.

scholarly journals A stochastic design rainfall generator based on copulas and mass curves

2010 ◽  
Vol 7 (3) ◽  
pp. 3613-3648 ◽  
Author(s):  
S. Vandenberghe ◽  
N. E. C. Verhoest ◽  
E. Buyse ◽  
B. De Baets
Keyword(s):  
Time Series ◽  
Return Period ◽  
Goodness Of Fit ◽  
Rainfall Time Series ◽  
Return Periods ◽  
Rainfall Runoff ◽  
Design Studies ◽  
Design Storm ◽  
Practical Usefulness ◽  
Storm Duration

Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of design storm ensembles and rainfall-runoff modelling.

Reliability Analysis and Goodness-of-Fit Test of Pen Cylinder

2012 ◽  
Vol 522 ◽  
pp. 578-581
Author(s):  
Dan Jiang ◽  
Cong Ling Wang ◽  
Ping Yang
Keyword(s):  
Fatigue Life ◽  
Weibull Distribution ◽  
Goodness Of Fit ◽  
Failure Modes ◽  
Least Square Method ◽  
Least Square ◽  
Life Distribution ◽  
Goodness Of Fit Test ◽  
Durability Test ◽  
Two Parameters

According to the durability test results of pen cylinders, including failure modes and fatigue life data, life distribution of pen cylinder is studied. The parameters of Weibull distribution of pen cylinder are estimated by least square method. Using Weibull distribution test, the goodness-of-fit test of the pen cylinder life distribution is carried out. Results of goodness-of-fit test show fatigue life distribution of pen cylinder complies with Weibull distribution with two parameters.

Prediction of Haemoglobin Level by Some Probability Distribution

2020 ◽  
Vol 9 (1) ◽  
pp. 84-88
Author(s):  
Govinda Prasad Dhungana ◽  
Laxmi Prasad Sapkota
Keyword(s):  
Probability Distribution ◽  
Normal Distribution ◽  
Goodness Of Fit ◽  
Continuous Variable ◽  
Hemoglobin Level ◽  
Chi Square ◽  
Chi Square Test ◽  
Log Normal ◽  
Two Parameters ◽  
Best Fit

 Hemoglobin level is a continuous variable. So, it follows some theoretical probability distribution Normal, Log-normal, Gamma and Weibull distribution having two parameters. There is low variation in observed and expected frequency of Normal distribution in bar diagram. Similarly, calculated value of chi-square test (goodness of fit) is observed which is lower in Normal distribution. Furthermore, plot of PDFof Normal distribution covers larger area of histogram than all of other distribution. Hence Normal distribution is the best fit to predict the hemoglobin level in future.

ANALISIS ADVERSITY QUOTIENT DAN KOMUNIKASI INTERPERSONAL DENGAN KOMITMEN ORGANISASI SEBAGAI INTERVENING TERHADAP PRODUKTIVITAS KARYAWAN

2020 ◽  
Vol 7 (2) ◽  
pp. 125-139
Author(s):  
Abd. Rasyid Syamsuri ◽  
Abd. Halim ◽  
Dilla Darvita
Keyword(s):  
Goodness Of Fit ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square ◽  
Inner Model

Tujuan penelitian ini untuk menganalisis pengaruh adversity quotient dan komunikasi interpersonal dengan komitmen organisasi sebagai Intervening terhadap produktvitas karyawan. Penelitian ini kami lakukan di PT. Gloria Jaya Sejahtera Medan-Indonesia dengan pengumpulan data melalui pendekatan survei yang menyebar kuesioner kepada 40 karyawan. Teknik pengumpulan data dilakukan dengan wawancara, kuesioner dan observasi. Alat analisis yang digunakan pada penelitian ini menggunakan software Statistical Product and Service Solutions (SPSS) dan Stuctural Equation Model (SEM) dengan SmartPLS (Partial Least Square). Pengujian dengan model struktural (inner model) dapat diperoleh bahwa nilai R square untuk variabel komitmen organisasi (Z) dan produktivitas karyawan (Y) dapat dijelaskan oleh variabel adverstiy quotient (X1), dan komunikasi interpersonal (X2), sebesar 75,3%, dan 83,3 % sedangkan sisanya dijelaskan oleh varibel lain. Untuk uji kesesuain model (uji goodness of fit) dapat diketahui bahwa nilai Q2 = 0,958 > 0 yang berarti model penelitian adversity quotient (X1), komunikasi interpersonal (X2), komitmen organisasi (Z), dan produktivitas karyawan (Y) di PT. Gloria Jaya Sejahtera Medan memiliki kesesuaian. Hasil penelitian dengan uji-t dapat diketahui bahwa adversity quotient berpengaruh positif dan tidak signifikan terhadap komitmen organisasi dengan nilai t satistik sebesar 1,069 lebih kecil dari t-tabel 1,96, komunikasi interpersonal berpengaruh positif dan signifikan terhadap komitmen organisasi dengan nilai t satistik sebesar 4,259 lebih besar dari t-tabel 1,96, adversity quotient berpengaruh negatif dan signifikan terhadap produktvitas karyawan dengan nilai t satistik sebesar 2,632 lebih besar dari t-tabel 1,96, komunikasi interpersonal berpengaruh positif dan signifikan terhadap produktvitas kerja karyawan dengan nilai t satistik sebesar 2,900 lebih besar dari t-tabel 1,96, komitmen organisasi berpengaruh positif dan signifikan terhadap produktvitas karyawan dengan nilai t satistik sebesar 4,399 lebih besar dari t-tabel 1,96.

scholarly journals Extended Local Analysis of Inexact Gauss-Newton-like Method for Least Square Problems using Restricted Convergence Domains

2016 ◽  
Vol 54 (1) ◽  
pp. 17-33
Author(s):  
Ioannis K. Argyros ◽  
Santhosh George
Keyword(s):  
Convergence Analysis ◽  
Computational Cost ◽  
Nonlinear Least Squares ◽  
Least Square ◽  
Error Tolerance ◽  
Local Analysis ◽  
Large Radius ◽  
Special Cases ◽  
Local Convergence Analysis ◽  
Least Square Problems

Abstract We present a local convergence analysis of inexact Gauss-Newton-like method (IGNLM) for solving nonlinear least-squares problems in a Euclidean space setting. The convergence analysis is based on our new idea of restricted convergence domains. Using this idea, we obtain a more precise information on the location of the iterates than in earlier studies leading to smaller majorizing functions. This way, our approach has the following advantages and under the same computational cost as in earlier studies: A large radius of convergence and more precise estimates on the distances involved to obtain a desired error tolerance. That is, we have a larger choice of initial points and fewer iterations are also needed to achieve the error tolerance. Special cases and numerical examples are also presented to show these advantages.

scholarly journals Trend Dynamics of GRACE Terrestrial Water Storage in the Nile River Basin

2019 ◽  
Author(s):  
Emad Hasan ◽  
Aondover Tarhule
Keyword(s):  
Soil Moisture ◽  
Population Density ◽  
River Basin ◽  
Goodness Of Fit ◽  
Water Storage ◽  
Least Square ◽  
Nile River ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Nile River Basin

GRACE-derived Terrestrial Water Storage Anomalies (TWSA) continue to be used in an expanding array of studies to analyze numerous processes and phenomena related to terrestrial water storage dynamics, including groundwater depletions, lake storage variations, snow, and glacial mass changes, as well as floods, droughts, among others. So far, however, few studies have investigated how the factors that affect total water storage (e.g., precipitation, runoff, soil moisture, evapotranspiration) interact and combine over space and time to produce the mass variations that GRACE detects. This paper is an attempt to fill that gap and stimulate needed research in this area. Using the Nile River Basin as case study, it explicitly analyzes nine hydroclimatic and anthropogenic processes, as well as their relationship to TWS in different climatic zones in the Nile River Basin. The analytic method employed the trends in both the dependent and independent variables applying two geographically multiple regression (GMR) approaches: (i) an unweighted or ordinary least square regression (OLS) model in which the contributions of all variables to TWS variability are deemed equal at all locations; and (ii) a geographically weighted regression (GWR) which assigns a weight to each variable at different locations based on the occurrence of trend clusters, determined by Moran’s cluster index. In both cases, model efficacy was investigated using standard goodness of fit diagnostics. The OLS showed that trends in five variables (i.e., precipitation, runoff, surface water soil moisture, and population density) significantly (p<0.0001) explain the trends in TWSA for the basin at large. However, the models R2 value is only 0.14. In contrast, the GWR produced R2 values ranging between 0.40 and 0.89, with an average of 0.86 and normally distributed standard residuals. The models retained in the GWR differ by climatic zone. The results showed that all nine variables contribute significantly to the trend in TWS in the Tropical region; population density is an important contributor to TWSA variability in all zones; ET and Population density are the only significant variables in the semiarid zone. This type of information is critical for developing robust statistical models for reconstructing time series of proxy GRACE anomalies that predate the launch of the GRACE mission and for gap-filling between GRACE and GRACE-FO.

scholarly journals Evidence That Supertriangles Exist in Nature from the Vertical Projections of Koelreuteria paniculata Fruit

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 23
Author(s):  
Yuping Li ◽  
Brady K. Quinn ◽  
Johan Gielis ◽  
Yirong Li ◽  
Peijian Shi
Keyword(s):  
Root Mean Square ◽  
Goodness Of Fit ◽  
Mean Square ◽  
Sea Stars ◽  
Different Types ◽  
Koelreuteria Paniculata ◽  
Two Parameters ◽  
Mean Square Errors

Many natural radial symmetrical shapes (e.g., sea stars) follow the Gielis equation (GE) or its twin equation (TGE). A supertriangle (three triangles arranged around a central polygon) represents such a shape, but no study has tested whether natural shapes can be represented as/are supertriangles or whether the GE or TGE can describe their shape. We collected 100 pieces of Koelreuteria paniculata fruit, which have a supertriangular shape, extracted the boundary coordinates for their vertical projections, and then fitted them with the GE and TGE. The adjusted root mean square errors (RMSEadj) of the two equations were always less than 0.08, and >70% were less than 0.05. For 57/100 fruit projections, the GE had a lower RMSEadj than the TGE, although overall differences in the goodness of fit were non-significant. However, the TGE produces more symmetrical shapes than the GE as the two parameters controlling the extent of symmetry in it are approximately equal. This work demonstrates that natural supertriangles exist, validates the use of the GE and TGE to model their shapes, and suggests that different complex radially symmetrical shapes can be generated by the same equation, implying that different types of biological symmetry may result from the same biophysical mechanisms.

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