First step: Construction of Extreme Rainfall timeseries

Similar documents
Intensity-Duration-Frequency (IDF) Curves Example

Using the Budget Features in Quicken 2008

Orange Visualization Tool (OVT) Manual

Location Latitude Longitude Durham, NH

How to Create Stream Networks using DEM and TauDEM

Probability Methods in Civil Engineering Prof. Dr. Rajib Maity Department of Civil Engineering Indian Institute of Technology, Kharagpur

SOLVING PROBLEMS BASED ON WINQSB FORECASTING TECHNIQUES

Hotelling s One- Sample T2

An area chart emphasizes the trend of each value over time. An area chart also shows the relationship of parts to a whole.

What is DMAP (Drought Monitoring And Prediction) software?

NEW HOLLAND IH AUSTRALIA. Machinery Market Information and Forecasting Portal *** Dealer User Guide Released August 2013 ***

1 Introduction to Minitab

Demand Forecasting. for. Microsoft Dynamics 365 for Operations. User Guide. Release 7.1. April 2018

Probability Methods in Civil Engineering Prof. Dr. Rajib Maity Department of Civil Engineering Indian Institute of Technology Kharagpur

HEC-HMS Lab 4 Using Frequency Storms in HEC-HMS

Worksheet: The Climate in Numbers and Graphs

Copy the rules into MathLook for a better view. Close MathLook after observing the equations.

SWIM and Horizon 2020 Support Mechanism

System Identification of RTD Dynamics (Tom Co, 11/26/2006; 11/25/2007, 11/15/2009)

Water Information Portal User Guide. Updated July 2014

Studying Topography, Orographic Rainfall, and Ecosystems (STORE)

Building Inflation Tables and CER Libraries

Bloomsburg University Weather Viewer Quick Start Guide. Software Version 1.2 Date 4/7/2014

LAB 3 INSTRUCTIONS SIMPLE LINEAR REGRESSION

Satellite-Based Precipitation Data Delivery System for Thailand. Infrastructure Development Institute-Japan

Tests for Two Coefficient Alphas

New Intensity-Frequency- Duration (IFD) Design Rainfalls Estimates

1D-HAM. Coupled Heat, Air and Moisture Transport in Multi-layered Wall Structures. Manual with brief theory and an example. Version 2.

Investigating Factors that Influence Climate

Gridded Ambient Air Pollutant Concentrations for Southern California, User Notes authored by Beau MacDonald, 11/28/2017

2.4. Model Outputs Result Chart Growth Weather Water Yield trend Results Single year Results Individual run Across-run summary

Studying Topography, Orographic Rainfall, and Ecosystems (STORE)

McIDAS-V Tutorial Displaying Point Observations from ADDE Datasets updated July 2016 (software version 1.6)

Review of existing statistical methods for flood frequency estimation in Greece

Ratio of Polynomials Fit One Variable

Jasco V-670 absorption spectrometer

Gridding of precipitation and air temperature observations in Belgium. Michel Journée Royal Meteorological Institute of Belgium (RMI)

WMS 10.1 Tutorial GSSHA Applications Precipitation Methods in GSSHA Learn how to use different precipitation sources in GSSHA models

AAG TPoint Mapper (Version 1.40)

Harvard Life Science Outreach December 7, 2017 Measuring ecosystem carbon fluxes using eddy covariance data ACTIVITIES I. NAME THAT ECOSYSTEM!

Quality Measures (QM) Report. Self Guided Tutorial

Probability Methods in Civil Engineering Prof. Rajib Maity Department of Civil Engineering Indian Institute of Technology, Kharagpur

Practical Session Instructions. Terrestrial Water Storage. Drought Monitoring

FireFamilyPlus Version 5.0

Assignment 2: Conformation Searching (50 points)

Remember that C is a constant and ë and n are variables. This equation now fits the template of a straight line:

Distribution Fitting (Censored Data)

Newton's 2 nd Law. . Your end results should only be interms of m

D.T.M: TRANSFER TEXTBOOKS FROM ONE SCHOOL TO ANOTHER

EARTHQUAKE ANALYSIS with SAP2000

Jackson County 2013 Weather Data

Quick Start Guide New Mountain Visit our Website to Register Your Copy (weatherview32.com)

Passing-Bablok Regression for Method Comparison

Ligand Scout Tutorials

FleXScan User Guide. for version 3.1. Kunihiko Takahashi Tetsuji Yokoyama Toshiro Tango. National Institute of Public Health

UNST 232 Mentor Section Assignment 5 Historical Climate Data

Senior astrophysics Lab 2: Evolution of a 1 M star

Watershed Modeling Orange County Hydrology Using GIS Data

George Mason University Department of Civil, Environmental and Infrastructure Engineering

IT S TIME FOR AN UPDATE EXTREME WAVES AND DIRECTIONAL DISTRIBUTIONS ALONG THE NEW SOUTH WALES COASTLINE

WMS 9.0 Tutorial GSSHA Modeling Basics Infiltration Learn how to add infiltration to your GSSHA model

VELA. Getting started with the VELA Versatile Laboratory Aid. Paul Vernon

Confidence Intervals for One-Way Repeated Measures Contrasts

Cerno Application Note Extending the Limits of Mass Spectrometry

LABORATORY NUMBER 9 STATISTICAL ANALYSIS OF DATA

TORO SENTINEL APPLICATION NOTE AN01: ET-BASED PROGRAMMING

Weather Data Weather Forecasts Weather Risk Consultancy Weather Risk Management Software SWS Weather Data Format

Electric Fields and Equipotentials

Exponential, Gamma and Normal Distribuions

How to Perform a Site Based Plant Search

NINE CHOICE SERIAL REACTION TIME TASK

Hydrologic Modeling System HEC-HMS

REPLACE DAMAGED OR MISSING TEXTBOOK BARCODE LABEL

(THIS IS AN OPTIONAL BUT WORTHWHILE EXERCISE)

Decision 411: Class 3

George Mason University Department of Civil, Environmental and Infrastructure Engineering. Dr. Celso Ferreira Prepared by Lora Baumgartner

Using the Morinus Astrology Program

Exercise 6: Using Burn Severity Data to Model Erosion Risk

20. Security Classif.(of this page) Unclassified

Physics Lab #5: Starry Night Observations of the Sun and Moon

Tutorial. Getting started. Sample to Insight. March 31, 2016

Estimating Design Rainfalls Using Dynamical Downscaling Data

Uncertainty in IDF Curves

THE LATE BLIGHT MODELING SOFTWARE «Pameseb Late Blight»

Preparations and Starting the program

GLD Skill Booster #4:

Decision 411: Class 3

Using Tables and Graphing Calculators in Math 11

Athena Visual Software, Inc. 1

LITERATURE REVIEW. History. In 1888, the U.S. Signal Service installed the first automatic rain gage used to

THE CRYSTAL BALL FORECAST CHART

Expected Values, Exponential and Gamma Distributions

Global Atmospheric Circulation Patterns Analyzing TRMM data Background Objectives: Overview of Tasks must read Turn in Step 1.

Creating PET Adjustment Coefficients

Using the EartH2Observe data portal to analyse drought indicators. Lesson 4: Using Python Notebook to access and process data

Spread footing settlement and rotation analysis

Using SkyTools to log Texas 45 list objects

PLANNED UPGRADE OF NIWA S HIGH INTENSITY RAINFALL DESIGN SYSTEM (HIRDS)

OECD QSAR Toolbox v.3.3. Step-by-step example of how to build a userdefined

Transcription:

First step: Construction of Extreme Rainfall timeseries You may compile timeseries of extreme rainfalls from accumulated intervals within the environment of Hydrognomon or import your existing data e.g. from Excel. Case 1: Compile your own timeseries You need a rainfall timeseries of 10-minutes or hourly or daily time step. Then you will compile extreme rainfall timeseries (annual) with intervals as integer multiples of the time step. (e.g. a 10 minutes rainfall timeseries may produce extreme rainfall timeseries of 10 minutes, 20, 30, 40 minutes, intervals of accumulation; an hourly rainfall timeseries may produce extreme rainfall timeseries of 1, 2, 3, hours intervals of accumulation. Define a new timeseries: Choose Series -> New menu A new window appears:

Set desired time step, title, variable (cumulative). Check Time step is strict only if your data have constant time step. If not leave it unchecked. Copy your data from Excel, or your favorite spreadsheet software: Date format should be: yyyy/mm/dd hh:mm for hourly /ten minute data yyyy/mm/dd for daily data yyyy/mm or yyyy/mm/01 for monthly data Select two or three adjacent columns (the third one contains flags). Paste your data to Hydrognomon:

Under Tools -> Regularize step, run this feature in order to make time step strict if it is not: Now use Tools -> Extremes evaluation menu item to show the window bellow: Set the desired time step for IDF analysis (should be Yearly), IDF variable (use either height or intensity). Do not use Hydrological year, this feature is implemented for the Greek weather (rainfalls start from October). Select the desired multiplier, e.g. a multiplier of 24 will evaluate a extreme rainfall timeseries for duration of 24 hours, if the rainfall timeseries is of hourly time step. Repeat the process by using several multipliers, e.g. a set of (1, 3, 6, 60, 144) applied on ten-minute timeseries will produce extreme timeseries of (10min, ½ hour, 1 hour, 24 hours) duration. See time series properties for each new (extreme rainfall) timeseries. Set the comments and title to contain information about the accumulation interval. Finally save the timeseries as files.

Case 2: Import your existing extreme rainfall timeseries You may add new time series with annual (yearly) time step. Copy your data e.g. from Excel to Hydrognomon and save them to file. Second step: IDF evaluation Load (or compile) desired Timeseries First, load the timeseries of extreme rainfalls into Time series data window (I send you these files). Each column is a timeseries containing the annual values of maximum accumulated rainfall (maximum accumulated 5 min, 10 min, 24 h). The selection of the actual number of timeseries /intervals is upon your experience. A sequence that we are using is that of the following example (5 min, 10 min, ½ hour, 1 hour, 2 hours, 6 hours, 12, 24 hours and sometimes 48 hours). Load the timeseries order by accumulation interval (e.g. from 5 min to 24 hours). See timeseries properties: Check that the time step is Annual, and specify accumulation interval in timeseries title and in comments. The use of hydrological year is suggested if the rainfall in your

Country has periodicity from 1 st of October to 30 September of the next year. In other case you may use the ordinary year (1 st of January to 31 December). Choose timeseries for IDF curves evaluation Use the menu under: Tools -> IDF curves Then a new window appears as follows:

Choose each of the timeseries from the left list (Available timeseries), specify the (source) timeseries variable (Height / Intensity), duration (accumulation interval) in either minutes or hours. Set Time resolution if this information is available (e.g. the base absolute minimum time step from which timeseries of greater interval are accumulated, in other cases choose Time resolution unknown ). Leave the Desired amount to 1/3. Finally press the IDF Analysis button, then, the following window appears:

This is the first screen, showing several (multiple) IDF curves at once. By pressing some of the check buttons on the right panel, you may choose which of the IDF curves to display.

Press the Single cuve tab in order to get extensive analysis for a single curve with a specified return period: Set the desired return period in years (T), e.g. 200. Press the Calculate button to get the alpha (a) parameter of the IDF curve. The above function: i(mm/h) := 77.22 / (d + 0.186)^0.792 it is the IDF curve for a return period of 200 years, using the GEV-Max distribution (you may alter the statistical distribution type, see bellow). Press the Calculate button in the Confidence interval for a panel in order to get confidence interval for a by a statistical simulation process (Monte Carlo). Sample limits and confidence interval are displayed respectively showing the probable variation of the main IDF curve with a confidence level of 90, 95 or 99%.

Press the Data tab to get the sample parameters, also the distribution function parameters and the curvature of the IDF curves: Mean value / standard deviation / skewness are the sample characteristics calculated with moment method. LMoment 1-3 are the sample characteristics calculated with the L- Moments method.

Press the Distribution plot tab to show the fit of sample data to the statistical distribution function: You may choose the desired durations to show from the right list (5 min 24 hours).

Statistical Distributions Use the menu Options -> Distribution to set a Statistical Distribution Type. Default is GEV-Max, statistical parameters calculated with L-Moments method and with kappa parameter constant to a specified value (default is 0.15). Choose a distribution from: Exponential distribution Gamma / LogPearson III Gumbel (Max) EV2-Max (Extreme Values 2) GEV-Max (General Extreme Values distribution, k may or not be specified). Pareto Some of the distributions parameters may be calculated with L-Moments method or else with the ordinary moment method. Use the Specify GEV kappa in order to alter the default 0.15 value. The selection of the GEV-Max distribution for the description of extreme rainfall intensities, is based on works of Koutsogiannis, you may contact him for more information. Choose another Paper (distribution/plot) in order to linearize better the sample values on the Distribution plot. Choose Consider time resolution effect in order to multiply rainfall intensity values with a factor of discretization.