Calibration of a distributed land surface model for a semi-arid basin using remotely sensed data.

Persistent Link:
http://hdl.handle.net/10150/191322
Title:
Calibration of a distributed land surface model for a semi-arid basin using remotely sensed data.
Author:
Yatheendradas, Soni.
Issue Date:
2003
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:
A meso-scale medium-resolution land surface model using the NCEP's NOAH code has been setup over the San Pedro basin in Arizona. The model is driven using the 50-year hydrologically balanced land surface data set developed at the University of Washington (UW), precipitation data from the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) system, and solar radiation influx from the University of Maryland's SRB (Surface Radiation Budget). The remotely sensed forcings are introduced in stages to explore the sensitivity on the simulation results to the remote sensing information. The model was calibrated, using the available remote sensing forcings, to ground observations of the turbulent heat fluxes and ground temperatures using multi-criteria calibration techniques. The simulation results for the distributed model using the default (uncalibrated) and the calibrated parameters are intercompared against each other and against the UW outputs. Results show the PERSIANN data substitution to be a major improving factor in the results in capturing the surface runoffs and the soil moisture diurnal variations because of its fmer sub-hourly temporal resolution as against the UW precipitation forcing which is basically at a daily temporal resolution. Separately, the default seasonal vegetation variation in the NOAH, i.e., constant greenness leaf area index (LAI) and variable greenness fraction (GF) was changed to the opposite case of constant GF and varying LAI using LAI data from the MODIS sensor. Visual inspection of the simulation results show the incompatibility between the NOAH and the MODIS LAI as per the MODIS LAI substitution method used in this study.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Ground -- Surface.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Gupta, Hoshin

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleCalibration of a distributed land surface model for a semi-arid basin using remotely sensed data.en_US
dc.creatorYatheendradas, Soni.en_US
dc.contributor.authorYatheendradas, Soni.en_US
dc.date.issued2003en_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.abstractA meso-scale medium-resolution land surface model using the NCEP's NOAH code has been setup over the San Pedro basin in Arizona. The model is driven using the 50-year hydrologically balanced land surface data set developed at the University of Washington (UW), precipitation data from the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) system, and solar radiation influx from the University of Maryland's SRB (Surface Radiation Budget). The remotely sensed forcings are introduced in stages to explore the sensitivity on the simulation results to the remote sensing information. The model was calibrated, using the available remote sensing forcings, to ground observations of the turbulent heat fluxes and ground temperatures using multi-criteria calibration techniques. The simulation results for the distributed model using the default (uncalibrated) and the calibrated parameters are intercompared against each other and against the UW outputs. Results show the PERSIANN data substitution to be a major improving factor in the results in capturing the surface runoffs and the soil moisture diurnal variations because of its fmer sub-hourly temporal resolution as against the UW precipitation forcing which is basically at a daily temporal resolution. Separately, the default seasonal vegetation variation in the NOAH, i.e., constant greenness leaf area index (LAI) and variable greenness fraction (GF) was changed to the opposite case of constant GF and varying LAI using LAI data from the MODIS sensor. Visual inspection of the simulation results show the incompatibility between the NOAH and the MODIS LAI as per the MODIS LAI substitution method used in this study.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshGround -- Surface.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairGupta, Hoshinen_US
dc.contributor.committeememberSorooshian, Sorooshen_US
dc.identifier.oclc217318433en_US
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