Comparison of rainfall sampling schemes using a calibrated Stochastic Rainfall Generator

Persistent Link:
http://hdl.handle.net/10150/191331
Title:
Comparison of rainfall sampling schemes using a calibrated Stochastic Rainfall Generator
Author:
Welles, Edwin.
Issue Date:
1994
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Accurate rainfall measurements are critical to river flow predictions. Areal and gauge rainfall measurements create different descriptions of the same storms. The purpose of this study is to characterize those differences. A stochastic rainfall generator was calibrated using an automatic search algorithm. Statistics describing several rainfall characteristics of interest were used in the error function. The calibrated model was then used to generate storms which were exhaustively sampled, sparsely sampled and sampled areally with 4X4 km grids. The sparsely sampled rainfall was also kriged to 4X4 km blocks. The differences between the four schemes were characterized by comparing statistics computed from each of the sampling methods. The possibility of predicting areal statistics from gauge statistics was explored. It was found that areally measured storms appeared to move more slowly, appeared larger, appeared less intense and have shallower intensity gradients.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Rain and rainfall -- Measurement.; Precipitation (Meteorology) -- Measurement.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Hydrology; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Sorooshian, Soroosh

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleComparison of rainfall sampling schemes using a calibrated Stochastic Rainfall Generatoren_US
dc.creatorWelles, Edwin.en_US
dc.contributor.authorWelles, Edwin.en_US
dc.date.issued1994en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractAccurate rainfall measurements are critical to river flow predictions. Areal and gauge rainfall measurements create different descriptions of the same storms. The purpose of this study is to characterize those differences. A stochastic rainfall generator was calibrated using an automatic search algorithm. Statistics describing several rainfall characteristics of interest were used in the error function. The calibrated model was then used to generate storms which were exhaustively sampled, sparsely sampled and sampled areally with 4X4 km grids. The sparsely sampled rainfall was also kriged to 4X4 km blocks. The differences between the four schemes were characterized by comparing statistics computed from each of the sampling methods. The possibility of predicting areal statistics from gauge statistics was explored. It was found that areally measured storms appeared to move more slowly, appeared larger, appeared less intense and have shallower intensity gradients.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshRain and rainfall -- Measurement.en_US
dc.subject.lcshPrecipitation (Meteorology) -- Measurement.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairSorooshian, Sorooshen_US
dc.contributor.committeememberMichaud, Jeneen_US
dc.contributor.committeememberGoodrich, Daviden_US
dc.contributor.committeememberShuttleworth, Jimen_US
dc.identifier.oclc222034764en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.