Development of spatial interpolation techniques for estimation of rainfall
| dc.contributor.author | Shater, Omima Abass Osman | |
| dc.date.accessioned | 2019-08-29T10:19:41Z | |
| dc.date.accessioned | 2020-01-07T14:41:04Z | |
| dc.date.available | 2019-08-29T10:19:41Z | |
| dc.date.available | 2020-01-07T14:41:04Z | |
| dc.date.issued | 1999 | |
| dc.description | Available in print form | en_US |
| dc.description.abstract | The ultimate goal of this study is to model the spatial variation of the rainfall and to estimate the rainfall surface for Rufiji and Pangani basins by using geo-statistical techniques of characterising the spatial continuity. The research was carried out in two steps. The first step is the application of experimental measures of spatial variability and variogram models. Whilst the second step is the application of interpolation techniques (kriging). In the first step, the variogram model was used to model the spatial fluctuation of the quantity under study (in this case rainfall), software called VARIOWIN (Panntier, 1996) is used for this purpose. The kriging technique was used to weight irregular space point data to estimate rainfall of regularly spaced prediction grid with certain resolution. In this analysis various geostatistical techniques are implemented, simple kriging (SK), ordinary kriging (OK), non-stationary kriging, kriging with an external drift (KT), and co-kriging (COK). Generally, OK type produced reasonably good estimation results with R2 value 58.8 and 60.4% for Pangani and Rufiji Basins respectively. An attempt was made to improve the rainfall estimation. By incorporating related secondary variable in this case mean annual CCD. The results show little or no improvement at all for kriging with an external drift (KT). An encouraging improvement is observed in including the secondary variable (CCD) as a ratio to the primary variable (rainfall). The results of R2 are improved from 58.8 to 69.9% for Pangani and from 60.4 to 71.5% for Rufiji basin. Further improvement was obtained for both basins by using the estimated rainfall surface from ratio as the secondary variable. The results of R2 are improved from 69.9 to 73.7% for Pangani and from 71.5 to 77.2% for Rufiji basin. After exhaustive modelling analysis, parameter sensitivity analysis, and examination of the residual error was carried out for any indication of systematic relationship. The parameter values, as they are in acceptable ranges, have been found more resistance (less sensitive in the sense of the efficiency criteria R2 for any different combination. Thus, rather than investigating The parameter values for further improvement on the estimated values, it is advisable to investigate the spatial behaviour of the rainfall as well as its related secondary variable. The recommendations for solving this type of problem have been given on the last chapter. | en_US |
| dc.identifier.citation | Shater, O. A. O. (1999) Development of spatial interpolation techniques for estimation of rainfall, Masters’ dissertation, University of Dar es Salaam. Available at (http://41.86.178.3/internetserver3.1.2/detail.aspx) | en_US |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/278 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of Dar es Salaam | en_US |
| dc.subject | Rain and rainfall | en_US |
| dc.subject | Rainfall | en_US |
| dc.subject | reliability | en_US |
| dc.subject | Interpolation techniques | en_US |
| dc.subject | Tanzania | en_US |
| dc.title | Development of spatial interpolation techniques for estimation of rainfall | en_US |
| dc.type | Thesis | en_US |