Disaggregation of precipitation records
| dc.contributor.author | Cadavid, Luis Guillermo, author | |
| dc.contributor.author | Salas, Jose D., advisor | |
| dc.contributor.author | Boes, Duane C., committee member | |
| dc.contributor.author | Yevjevich, Vujica M., 1913-, committee member | |
| dc.contributor.author | Fontane, Darrell G., committee member | |
| dc.date.accessioned | 2018-11-08T22:36:20Z | |
| dc.date.available | 2018-11-08T22:36:20Z | |
| dc.date.issued | 1991 | |
| dc.description.abstract | This investigation is related to temporal disaggregation of precipitation records. The objective is to formulate algorithms to disaggregate precipitation defined at a given time scale into precipitation of smaller time scales, assuming that a certain mechanism or stochastic process originates the precipitation process. The disaggregation algorithm should preserve the additivity property and the sample statistical properties at several aggregation levels. Disaggregation algorithms were developed for two models which belong to the class of continuous time point processes: Poisson White Noise (PWN) and Neyman-Scott White Noise (NSWN). Precipitation arrivals are controlled by a counting process and storm activity is represented by instantaneous amounts of precipitation (White Noise terms). Algorithms were tested using simulated samples and data collected at four precipitation stations in Colorado. The PWN model is the easiest and formulation of the disaggregation model was successful. The algorithm is based on the distribution of the number of arrivals (N) conditional on the total precipitation in the time interval (Y) , the distribution of the White Noise terms conditional on N and Y, and the distribution of the arrival times conditional on N. Its application to disaggregate precipitation is limited due to its lacl; of serial correlation. However, PWN disaggregation model performs well on PWN simulated samples. The NSWN is more complex. Required distributions are the same as for the PWN model. Formulation of a disaggregation algorithm was based on theoretical and empirical results. A procedure for model parameters estimation based on weighted least squares was implemented. This procedure reduces the number of estimation failures as compared to method of moments. NSWN disaggregation model performed well on simulated and recorded samples given that parameters used are similar to those controlling the process at the disaggregation scale. The main shortcoming is the incompatibility of parameter estimates at different aggregation levels. This renders the disaggregation model of limited application. Examination of variation of parameter estimates with the aggregation scale suggests the existence of a region where estimated values appear to be compatible. Finally, it is shown that the use of information at a nearby precipitation station with similar precipitation regime may improve parameter values to use in disaggregation. | |
| dc.format.medium | doctoral dissertations | |
| dc.identifier.uri | https://hdl.handle.net/10217/192791 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation | Catalog record number (MMS ID): 991024218169703361 | |
| dc.relation | GB651.C6 no.106 | |
| dc.relation.ispartof | 1980-1999 | |
| dc.relation.ispartof | Water resources paper, no. 106 | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | Precipitation (Meteorology) -- Mathematical models | |
| dc.subject | Poisson processes | |
| dc.title | Disaggregation of precipitation records | |
| dc.type | Text | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Civil Engineering | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) |
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