Sensitivity of runoff to small scale spatial variability of observed rainfall in a distributed model
| dc.contributor.author | Faurés, Jean-Marc,1961- | |
| dc.creator | Faurés, Jean-Marc,1961- | en_US |
| dc.date.accessioned | 2011-11-28T14:15:20Z | |
| dc.date.available | 2011-11-28T14:15:20Z | |
| dc.date.issued | 1990 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/192050 | |
| dc.description.abstract | The spatial variability of rainfall is known to play an important role in the process of surface runoff generation. Yet, the typical assumption of uniform rainfall is still applied in modeling the hydrological behavior of small watersheds. To investigate the validity of this assumption, an experiment was conducted in a small catchment (4.4 ha) in a semi-arid environment. The distributed model KINEROS was used to assess the sensitivity of predicted runoff to rainfall variability. Uncertainties in estimating rainfall input were shown to have three major components: measurement errors, spatial variability of the rainfall field, and wind. Their relative importance is a function of the catchment scale, topography and physical properties of the storms. Computation of runoff based on the data from a unique raingage entails a high degree of uncertainty. Even at small scales, the number and location of raingages directly control the accuracy of runoff simulation. | |
| dc.language.iso | en | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.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. | en_US |
| dc.subject | Hydrology. | |
| dc.subject | Runoff -- Mathematical models. | |
| dc.subject | Rain and rainfall -- Mathematical models. | |
| dc.title | Sensitivity of runoff to small scale spatial variability of observed rainfall in a distributed model | en_US |
| dc.type | Thesis-Reproduction (electronic) | en_US |
| dc.type | text | en_US |
| dc.contributor.chair | Sorooshian, Soroosh | en_US |
| dc.contributor.chair | Woolhiser, David A. | en_US |
| dc.identifier.oclc | 213468311 | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | masters | en_US |
| thesis.degree.discipline | Hydrology and Water Resources | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.name | M.S. | en_US |
| dc.description.note | hydrology collection | en_US |
| refterms.dateFOA | 2018-06-12T07:08:19Z | |
| html.description.abstract | The spatial variability of rainfall is known to play an important role in the process of surface runoff generation. Yet, the typical assumption of uniform rainfall is still applied in modeling the hydrological behavior of small watersheds. To investigate the validity of this assumption, an experiment was conducted in a small catchment (4.4 ha) in a semi-arid environment. The distributed model KINEROS was used to assess the sensitivity of predicted runoff to rainfall variability. Uncertainties in estimating rainfall input were shown to have three major components: measurement errors, spatial variability of the rainfall field, and wind. Their relative importance is a function of the catchment scale, topography and physical properties of the storms. Computation of runoff based on the data from a unique raingage entails a high degree of uncertainty. Even at small scales, the number and location of raingages directly control the accuracy of runoff simulation. |
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