Your search found 15 records
(Location: IWMI HQ Call no: IWMI 621.3678 G000 MEL Record No: H040633)
The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land- cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhausted application of the remote sensing technique rather summary of some important applications in environmental studies and modeling.
2 Melesse, A. M.. (Ed.) 2011. Nile river basin: hydrology, climate and water use. Dordrecht, Netherlands: Springer. 419p.
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044019)
3 Melesse, A. M.; Abtew, W.; Setegn, S. G.; Dessalegne, T. 2011. Hydrological variability and climate of the Upper Blue Nile River Basin. In Melesse, A. M. (Ed.). Nile River Basin: hydrology, climate and water use. Dordrecht, Netherlands: Springer. pp.3-37.
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044021)
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044022)
5 Mekonnen, M.; Melesse, A. M.. 2011. Soil erosion mapping and hotspot area identification using GIS and remote sensing in Northwest Ethiopian highlands, near Lake Tana. In Melesse, A. M. (Ed.). Nile River Basin: hydrology, climate and water use. Dordrecht, Netherlands: Springer. pp.207-224.
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044030)
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044032)
7 Hoffman, C.; Melesse, A. M.; McClain, M. E. 2011. Geospatial mapping and analysis of water availability, demand and use within the Mara River Basin. In Melesse, A. M. (Ed.). Nile River Basin: hydrology, climate and water use. Dordrecht, Netherlands: Springer. pp.359-382.
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044038)
8 Yitayew, M.; Melesse, A. M.. 2011. Critical water resources issues in the Nile River Basin. In Melesse, A. M. (Ed.). Nile River Basin: hydrology, climate and water use. Dordrecht, Netherlands: Springer. pp.401-416.
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044040)
9 Abtew, W.; Melesse, A. M.. (Eds.) 2008. Proceedings of the workshop on Hydrology and Ecology of the Nile River Basin under Extreme Conditions, Addis Ababa, Ethiopia, 16-19 June 2008. Sandy, UT, USA: Aardvark Global Publishing. 368p. + 1CD.
(Location: IWMI HQ Call no: 551.48 G136 ABT Record No: H044302)
(0.46 MB)
10 Chebud, Y. A.; Melesse, A. M.. 2008. Ground water flow simulation of the Lake Tana Basin, Ethiopia. In Abtew, W.; Melesse, A. M. (Eds.). Proceedings of the Workshop on Hydrology and Ecology of the Nile River Basin under Extreme Conditions, Addis Ababa, Ethiopia, 16-19 June 2008. Sandy, UT, USA: Aardvark Global Publishing. pp.146-159.
(Location: IWMI HQ Call no: 551.48 G136 ABT Record No: H044320)
(0.91 MB)
11 Chebud, Y. A.; Melesse, A. M.. 2008. Hydrological water balance of Lake Tana, Ethiopia. In Abtew, W.; Melesse, A. M. (Eds.). Proceedings of the Workshop on Hydrology and Ecology of the Nile River Basin under Extreme Conditions, Addis Ababa, Ethiopia, 16-19 June 2008. Sandy, UT, USA: Aardvark Global Publishing. pp.182-199.
(Location: IWMI HQ Call no: 551.48 G136 ABT Record No: H044322)
(1.07 MB)
12 Abtew, W.; Melesse, A. M.; Dessalegne, T. 2008. Characteristics of monthly and annual rainfall of the Upper Blue Nile Basin. In Abtew, W.; Melesse, A. M. (Eds.). Proceedings of the Workshop on Hydrology and Ecology of the Nile River Basin under Extreme Conditions, Addis Ababa, Ethiopia, 16-19 June 2008. Sandy, UT, USA: Aardvark Global Publishing. pp.250-262.
(Location: IWMI HQ Call no: 551.48 G136 ABT Record No: H044326)
(0.78 MB)
13 Melesse, A. M.; Abtew, W.; Dessalegne, T. 2008. Simple model and remote sensing methods of evaporation estimation for Rift Valley Lakes in Ethiopia. In Abtew, W.; Melesse, A. M. (Eds.). Proceedings of the Workshop on Hydrology and Ecology of the Nile River Basin under Extreme Conditions, Addis Ababa, Ethiopia, 16-19 June 2008. Sandy, UT, USA: Aardvark Global Publishing. pp.263-276.
(Location: IWMI HQ Call no: 551.48 G136 ABT Record No: H044327)
(0.86 MB)
14 Abtew, W.; Melesse, A. M.. (Eds.) 2008. Proceedings of the workshop on Hydrology and Ecology of the Nile River Basin under Extreme Conditions, Addis Ababa, Ethiopia, 16-19 June 2008. Sandy, UT, USA: Aardvark Global Publishing. 368p. + 1CD.
(Location: IWMI HQ Call no: 551.48 G136 ABT c2 Record No: H044337)
(Location: IWMI HQ Call no: e-copy only Record No: H051572)
(4.66 MB)
Citizen Science can fulfill the quest for high-quality and sufficient environmental data, such as rainfall. However, the factors affecting the quality of rainfall data collected by the citizen scientists are not well understood. In this study, we examined the effect of citizen scientists’ attributes on the quality of rainfall data. For this purpose, Principal Component Analysis (PCA), stepwise regression and Multiple Linear Regressions (MLR) were used. A quality control procedure was developed and applied for daily observed rainfall data collected in the summer rainy season of 2020. Attributes of the citizen scientists’ were gathered for those who collected rainfall data in the urban and peri-urban Akaki catchment which is located in the Upper Awash sub-basin, Ethiopia. We found that easy-to-detect errors, which were identified during the initial stage of quality control, formed most of the errors in the rainfall data. The PCA and the stepwise regression results revealed that four dominant attributes (education level, gauge relative location, use of smartphone app, and supervisor’s travel distance) highly affected the rainfall data quality. The MLR model using these four prominent dominant variables performed very well with R2 value of 0.98. The k-fold cross validation result showed that the developed model can be used to predict the relationships between data quality and attributes of citizen scientists with high accuracy. Hence, the PCA technique, stepwise regression and MLR model can provide useful information regarding the influence of citizen scientists’ attributes on rainfall data quality. Therefore, future studies should carefully consider citizen scientists’ attributes when engaging and supervising citizen scientists, with a comprehensive data quality control while monitoring rainfall.
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